Biotesty pro sledování přítomnosti hormonálně aktivních látek v povrchových a odpadních vodách

Transkript

1 Disertační práce v oboru Ekotoxikologie Barbora Jarošová Biotesty pro sledování přítomnosti hormonálně aktivních látek v povrchových a odpadních vodách Masarykova univerzita, Přírodovědecká fakulta, Centrum pro výzkum toxických látek v prostředí (RECETOX) Brno 2013

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3 Bibliografické informace Autor: Barbora Jarošová Název disertační práce: Title of dissertation: Biotesty pro sledování přítomnosti hormonálně aktivních látek v povrchových a odpadních vodách Bioassays for assessment of presence of endocrine active compounds in surface and waste waters Studijní program: Specializace: Biologie Ekotoxikologie Supervizor: Mgr. Klára Hilscherová, Ph.D. Rok obhajoby: 2013 Klíčová slova: Keywords: čistírna odpadních vod, in vitro, estrogenita, androgenita, toxicita dioxinového typu, pasivní vzorkování, endokrinní disrupce waste water treatment plant, in vitro, estrogenicity, androgenicity, dioxin-like toxicity, cytotoxicity, passive sampling, endocrine disruptor

4 Barbora Jarošová, Masarykova univerzita, 2013

5 Poděkování Ráda bych podělovala zejména: své vedoucí během celého magisterského i doktorského studia - Mgr. Kláře Hilscherové, Ph.D. za její rady, obětavou práci a zajištění podmínek pro moji práci Prof. Luďku Bláhovi Ph.D. za pomoc, zajištění podmínek při mojí práci a za vynikající vedení ekotoxikologické sekce výzkumného centra svým kolegům a přátelům z centra RECETOX za jejich pomoc a za sdílení myšlenek týkajících se nejen výzkumu speciální dík bych chtěla vyjádřit také Ing. Branislavu Vranovi, který byl vždy ochotný pomáhat mi se studiemi zaměřenými na pasivní vzorkování můj velký dík také patří pracovníkům čistíren odpadních vod, kteří mi ve svém volném čase obětavě pomáhali s výzkumem a spolupracujícím kolegům z dalších institucí největší dík pak patří mému manželovi a rodině za podporu a lásku, kterou mi vytvořili podmínky pro kreativní práci

6 Abstrakt In vitro biotesty umožňují relativně rychle a levně sledovat látky s určitým specifickým mechanismem působení přítomné ve vodách. Jejich pomocí byly charakterizovány skupiny látek schopných aktivovat/inhibovat estrogenní, androgenní a arylhydrokarbonový receptor a tím přispívat k možné endokrinní disrupci u vodních organismů. Sedm horních toků řek, které byly minimálně zatížené antropogenním znečištěním, obsahovalo nízký estrogenní a dioxinový potenciál. Stejné toky po průtoku prvními většími obcemi, z nichž každá měla čistírnu odpadních vod (ČOV), vykazovaly až 14krát vyšší estrogenní aktivitu a většinou také mírně zvýšenou dioxinovou aktivitu. To, že obce s ČOV mohou být zdrojem estrogenních, dioxinových i androgenních látek, bylo potvrzeno také v celoroční studii odpadních vod na ČOV v Brně Modřicích a to i přes vysokou účinnost odstranění estrogenních a androgenních látek. Jako nejrizikovější pro vodní organismy byly identifikovány letní měsíce. Estrogenní a dioxinová aktivita byly dále potvrzeny v některých vzorcích odpadních vod z odtoků různých evropských ČOV a to v koncentracích podobných dříve zjištěným hladinám na ČOV v Brně i hladinám uváděným v jiných evropských zahraničních studiích. Koncentrace analyticky stanovených polárních organických látek většinou spíše nekorelovaly s výsledky in vitro testů, což ukazuje na to, že jiné než stanovované látky byly zodpovědné za detekované potenciály, nebo že stanovované látky působily v nižších koncentracích, než byl limit detekce analytických metod. Na základě literární rešerše byla podrobně diskutována míra možných rizik spojených s naměřenými potenciály. In vitro testy byly dále použity v mezilaboratorní studii hodnotící různé typy biologických potencí vod odebraných v různě upravených odpadních i povrchových vodách včetně pitné vody. Ze 103 různých biotestů provedených 20ti laboratořemi asi polovina zachytila odpověď u alespoň jednoho typu vzorku a odpovědi biotestů podaly konzistentní obraz o určitém typu toxicity různých vzorků. Výsledky námi používaných testů ukázaly snižování toxicity v průběhu jednotlivých čistících kroků. In vitro testy se ukázaly jako citlivý nástroj pro sledování specifických aktivit v povrchových a odpadních vodách.

7 Abstract Compounds with specific modes of action like activation/inhibition of estrogenic, androgenic or arylhydrocarbon receptors have been monitored in complex environmental mixtures (surface and waste waters) by different in vitro assays. Some estrogenic as well as dioxin-like potentials have been detected in extracts of headwaters with minimal anthropogenic pollution. Estrogenicity of the headwaters increased by factor at locations downstream of the first town adjacent to the rivers. The towns treated their waste waters in conventional waste water treatment plant (WWTP). Dioxin-like activity was increased in most places downstream of the towns too. Treated waste water has been also identified as a source of estrogenic, androgenic and dioxin-like compounds in a study of WWTP in city of Brno, Czech Republic, nevertheless the efficiency to remove estrogenicity and androgenicity was greater than 98 % in most months during year. Summer season was identified as the most critical period because of lower dilution by river water. Estrogenicity and dioxin-like activity were also monitored in samples from 75 and 25 different European treated waste waters, respectively. The concentrations of detected activities were comparable to those detected previously at WWTP in Czech Republic or previously published in other European studies. The results of instrumental analyses generally did not correlate with potentials detected by in vitro assays showing that other than target compounds were responsible for the in vitro responses or that the compounds were effective in concentrations lower than limits of detection of instrumental analyses. The possible environmental impacts of detected activities were discussed. Twenty international laboratories collaborated and applied 103 unique in vitro bioassays to a common set of 10 water samples, including WWTP effluents, the effluents from different treatment steps in treatment plant recycling water, storm water, surface water and drinking water. Sixty-two of 103 bioassays showed positive results in at least one sample, typically in wastewater treatment plant effluent. Each type of water had a characteristic bioanalytical profile with particular groups of toxicity pathways either consistently responsive or not responsive across test systems. All 5 tests employed by our laboratory were responsive.

8 Seznam článků, z nichž vychází disertační práce Článek I Jarosova B, Blaha L, Vrana B, Randak T, Grabic R, Giesy JP, Hilscherova K. Changes in concentrations of hydrophilic organic contaminants and of endocrine-disrupting potential downstream of small communities located adjacent to headwaters. Environment International 45: 22-31; Článek II Jalova V, Jarosova B, Blaha L, Giesy JP, Ocelka T, Grabic R, Jurcikova J, Vrana B, Hilscherova K. Estrogen-, androgen- and aryl hydrocarbon receptor mediated activities in passive and composite samples from municipal waste and surface waters. Environment International 59: ; Článek III Loos R, Carvalho R, António DC, Comero S, Locoro G, Tavazzi S, Paracchini B, Ghiani M, Lettieri T, Blaha L, Jarosova B, Voorspoels S, Servaes K, Haglund P, Fick J, Lindberg R, Schwesig D, Gawlik BM. EU-wide monitoring survey on emerging polar organic contaminants in wastewater treatment plant effluents. Water Research; 2013 in press. Nabídnuté články Článek IV Jarosova B, Ersekova A, Hilscherova K, Loos R, Gawlik B, Giesy JP, Blaha L. Europe-wide monitoring of estrogenicity in waste water treatment plant effluents; Článek V Jarosova B, Blaha L, Giesy JP, Hilscherova K. What level of estrogenic activity determined by in vitro assays in municipal waste waters can be considered as safe? Environment International; 2013.

9 Článek VI Escher BI, Allinson M, Altenburger R, Bain P, Balaguer P, Busch W, Crago J, Humpage A, Denslow ND, Dopp E, Hilscherova K, Kumar A, Grimaldi M, Jayasinghe BS, Jarosova B, Jia A, Makarov S, Maruya KA, Medvedev A, Mehinto AC, Mendez JE, Poulsen A, Prochazka E, Richard J, Schifferli A, Daniel Schlenk D, Stefan Scholz S, Fujio Shiraishi F, Shane Snyder S, Guanyong Su G, Tang JYM, van der Burg B, van der Linden S, Werner I, Westerheide SD, Wong CKC, YANG M, Yeung BHY, Xiaowei Zhang X, Leusch FDL. Benchmarking organic micropollutants in wastewater, recycled water and drinking water with in vitro bioassays. Environmental Science & Technology; 2013.

10 Autorčin podíl na článcích Článek I Článek II Článek III Článek IV Článek V Článek VI Barbora Jarošová provedla a vyhodnotila in vitro biotesty, interpretovala jejich výsledky i vztah k jiným provedeným analýzám, napsala manuskript a s pomocí své vedoucí udělala konečné úpravy článku. Barbora Jarošová extrahovala vzorky odpadních vod, otestovala tyto extrakty pomocí in vitro biotestů, interpretovala a diskutovala jejich výsledky a napsala úvodní část, výsledky a diskusi týkající se vzorků odpadní vody v článku pojednávajícím dále i o povrchových vodách v brněnské aglomeraci, který kompletovala kolegyně Veronika Jálová. Barbora Jarošová se podílela jak vlastní prací tak koordinací na odběrech vzorků z České republiky, extrakci vzorků z EU a měření jejich estrogenního potenciálu a toxicity dioxinového typu. Do článku pak napsala a diskutovala kapitoly, které se těchto účinků týkají a podílela se také na finálních revizích článku. Barbora Jarošová napsala článek, ve kterém detailně diskutovala výsledky měření estrogenního potenciálu odpadních vod z celé EU. Na jejich měření se podílela jak vlastní prací, tak koordinací měření svých kolegů. Barbora Jarošová s pomocí své vedoucí napsala článek, ve kterém rozebrala možnosti interpretace estrogenních in vitro testů v komunálních odpadních vodách a odvodila limity pro jednotlivé testy. Barbora Jarošová koordinovala testování vzorků pomocí 5-ti různých biotestů, vzorky ředila a připravovala pro testování a naměřené výsledky vyhodnocovala a reportovala hlavním autorům článku. Dále se spolu se svou vedoucí podílela na konečných revizích článku.

11 Seznam použitých zkratek AEQ androgenní ekvivalent (z anglického Androgenic Equivalent) AhR arylhydrokarbonový receptor AR androgenní receptor ceeq z anglického calculated Estrogenic Equivalent ČOV čistírna/y odpadních vod E1 estron E2 17β-estradiol E3 estriol EE2 17α-ethinylestradiol EC50 koncentrace způsobující 50 % odpověď v testu (z anglického Effective Concentration) ED endokrinní disrupce/endokrinně disrupční EDCs látky narušující hormonální systém organismů (z anglického Endocrine Disruptive Compounds) EEQ estrogenní ekvivalent (z anglického Estrogenic Equivalent) EL estrogenní limit (max. bezpečné EEQ naměřené určitým biotestem) ER estrogenní receptor GR glukokortikoidní receptor Kov rozdělovací koeficient oktanol/voda MeOH methanol NEK norma/y environmentální kvality PNEC bezpečná hladina pro organismy (z anglického Predicted-No- Effect Concentration) POCIS pasivní vzorkovač polárních látek (z anglického Polar Organic Chemical Integrative Sampler) POCIS Pest POCIS uzpůsobený pro vzorkování širokého spektra relativně polárních pesticidů POCIS Pharm POCIS uzpůsobený pro vzorkování širokého spektra relativně polárních farmaceutických látek POP perzistentní organické polutanty

12 SPE TCDD TEQbio ŽP extrakce na tuhé fázi (z anglického Solid Phase Excraction) 2,3,7,8 tetrachlorodibenzo-p-dioxin ekvivalent TCDD naměřený biotestem životní prostředí

13 Obsah 1. Hlavní cíle disertační práce Úvod Co je endokrinní disrupce a proč ji zkoumat? Látky narušujícími hormonální systém organismů a další skupiny látek s nimi související Zaměření na odpadní a povrchové vody Biotesty jako nástroje pro sledování přítomnosti hormonálně aktivních látek v environmentálních vzorcích Použité materiály a metody Vzorkované lokality Odběr vzorků Aktivní vzorkování Pasivní vzorkování Zpracování vzorků Vzorky vody Vzorky z pasivních vzorkovačů Použité biotesty Výsledky Anti/estrogenita, anti/androgenita a toxicita dioxinového typu u vzorků říční vody minimálně zatížené antropogenními vlivy a u vzorků odebraných z týchž řek pod prvními obcemi (článek I) Anti/estrogenita, anti/androgenita Toxicita dioxinového typu Variabilita anti/estrostrogenního, anti/androgenního a dioxinového potenciálu směsí látek přítomných v přítoku a v odtoku z modelové ČOV v průběhu roku a účinnost odstranění těchto látek (článek II) Anti/estrogenita Anti/androgenita Toxicita dioxinového typu Hodnocení estrogenního a dioxinového potenciálu látek přítomných ve vzorcích odtoků z evropských ČOV (článek III, IV) Estrogenita Toxicita dioxinového typu Výsledky mezinárodní interlaboratorní studie hodnotící různé biotesty z hlediska zjišťování zbytkového znečištění odpadních vod na ČOV, které recyklují odpadní vody na vody pitné (článek VI) Diskuse

14 5.1. Hladiny estrogenního ekvivalentu naměřené v povrchových vodách (článek I) Hladiny TCDD ekvivalentu naměřené v povrchových vodách (článek I) Srovnání hladin ED potenciálů naměřených v povrchových vodách s analytickými výsledky (článek I) Hladiny estrogenního ekvivalentu naměřené v odpadních vodách (článek II, III, IV) Hladiny androgenního ekvivalentu naměřené v odpadních vodách (článek II) Hladiny TCDD ekvivalentu naměřené v odpadních vodách (článek II, III) Srovnání hladin ED potenciálů naměřených v odpadních vodách s analytickými výsledky (článek II, III, IV) Environmentální význam detekovaných hladin ED potenciálů (článek I, II, III, IV, V) Estrogenita (článek V) Androgenita Antiandrogenita Toxicita dioxinového typu Shrnutí a závěr Reference Přílohy

15 1. Hlavní cíle disertační práce 1) Pomocí in vitro biotestů charakterizovat anti/estrogenní, anti/androgenní a dioxinový potenciál směsí látek přítomných v řekách, které jsou jen minimálně zatíženy antropogenními vlivy (článek I). 2) Pomocí in vitro biotestů sledovat změny anti/estrogenního, anti/androgenního a dioxinového potenciálu směsí látek přítomných v řekách minimálně zatížených antropogenním znečištěním po průtoku obcemi s čistírnami odpadních vod (ČOV) (článek I). 3) V návaznosti na diplomovou práci pomocí in vitro biotestů dokončit charakterizaci variability anti/estrogenního, anti/androgenního a dioxinového potenciálu směsí látek přítomných v přítoku a v odtoku z modelové čistírny odpadních vod v průběhu roku (článek II). 4) V návaznosti na diplomovou práci pomocí in vitro biotestů dokončit charakterizaci efektivity odstranění látek s anti/estrogenním, anti/androgenním a dioxinovým potenciálem na modelové ČOV(článek II). 5) Pomocí in vitro biotestů charakterizovat estrogenní a dioxinový potenciál směsí látek přítomných ve vzorcích odtoků z evropských ČOV, které byly zároveň analyzovány pro přítomnost více než 150 polárních organických látek (článek III, IV). 6) Porovnat výsledky in vitro biotestů s výsledky analytických metod (článek I, II, III, IV). 7) Diskutovat význam zjištěných hladin endokrinně-disrupčních potenciálů z hlediska možných dopadů na vodní organismy (článek I, II, III, IV a především článek V). 8) Koordinací a vyhodnocením různých biotestů se podílet na mezinárodní interlaboratorní studii, jejímž cílem bylo navrhnout vhodnou baterii biotestů pro hodnocení míry účinnosti jednotlivých stupňů čištění v pokročilých ČOV recyklujících povrchové a odpadní vody až na vodu splňující parametry pro vodu pitnou (článek VI). 15

16 2. Úvod 2.1. Co je endokrinní disrupce a proč ji zkoumat? Vývoj a reprodukce většiny živočichů včetně člověka závisí mimo jiné na funkčnosti endokrinního systému. Narušení této funkčnosti s negativním dopadem na zdraví je možné označit jako endokrinní disrupci (ED). Aktuální souhrn vědeckých poznatků o ED u člověka i u divoce žijících zvířat vypracovaný pod záštitou Světové zdravotnické organizace a Programu OSN pro životní prostředí (WHO and UNEP 2013) např. uvádí: V posledních desetiletích je zaznamenáván nárůst onemocnění souvisejících s narušením fungování hormonálního systému. Příkladem může být nízká kvalita spermatu mladých mužů, která snižuje jejich schopnost reprodukce. V některých zemích Evropy vzrostla až na 40 % populace. Dále se např. celosvětově objevuje nárůst vrozených genitálních malformací mužů nebo počty endokrinně ovlivněných rakovin. Některé země mají vysoké procento neuro-behaviorálních poruch způsobené narušením thyroidních drah. Jiným příkladem je stále stoupající procento obézních lidí nebo lidí s cukrovkou typu II. Počty výskytu endokrinně ovlivněných nemocí stoupají příliš rychle na to, aby byly způsobeny genetickými faktory. Jako možné příčiny vzniku se jeví vliv výživy, věk prvního mateřství, virová onemocnění nebo expozice látkám, které narušují hormonální rovnováhu organismů (WHO and UNEP 2013). Ve své doktorské práci se budu zabývat právě látkami narušujícími hormonální systém organismů a jejich environmentálními směsmi. Chtěla bych zdůraznit, že látky, na které se zaměřuji, jsou jen jedním ze jmenovaných faktorů, které mohou mít vliv na zmiňované účinky. Zatímco důkazy o negativním působení látek na endokrinní systém lidí jsou velmi omezené (WHO and UNEP 2013), jsou známé a dobře zdokumentované mnohé příklady u divoce žijících zvířat (např. Sumpter and Johnson 2008). 16

17 2.2. Látky narušujícími hormonální systém organismů a další skupiny látek s nimi související Látky narušující hormonální systém organismů (EDCs, z anglického Endocrine Dirsrupting Compound*) jsou definovány např. jako exogenní látky nebo směsi látek, které mění jednu nebo více funkcí endokrinního systému a následně mohou vést ke škodlivým účinkům na celý organismus nebo na jeho potomstvo nebo na (sub)populace (IPCS/OECD 1998). Takovéto vlastnosti může mít řada látek, se kterými se člověk a další živočichové dostávají běžně do styku. Naprostá většina z nich nebyla na tyto účinky testována (WHO and UNEP 2013). Nejedná se přitom zdaleka jen o tradiční polutanty jako pesticidy nebo perzistentní organické látky. Tyto vlastnosti byly identifikovány u řady farmak (např. 17α-ethinylestradiol (EE2) používaný v hormonální antikoncepci), tzv. zboží denní potřeby (např. kosmetické přípravky nebo krémy s UV filtrem), surfaktantů, různých aditiv průmyslových materiálů, zpomalovačů hoření, těžkých kovů, nebo přirozených hormonů (příloha VII). Jsou to látky s často velmi odlišnými fyzikálně-chemickými vlastnostmi, což je logické při uvážení složitosti endokrinního systému a množství různých drah, proteinů a receptorů, jejichž ovlivněním může docházet k endokrinní disrupci. Popis endokrinního systému a známých mechanismů rekcí EDCs je dostupný např. v publikaci WHO and UNEP (2013, p. 1-10). Tradičně zkoumanými EDCs jsou některé látky ze skupiny perzistentních organických polutantů (POP), neboť vlivem jejich dlouhého poločasu života a typické vlastnosti - hydrofobicity dochází k jejich zakoncentrování v tukových tkáních živočichů a tím ke zvýšení expozice a často také k tzv. bioobohacování. K bioobohacování dochází, pokud se v tělech organismů na vyšších trofických úrovních potravních řetězců vyskytují vysoké koncentrace organických polutantů právě vlivem předešlého koncentrování těchto látek v tělech organismů na nižších trofických úrovních. Vlivem rozsáhlého výzkumu a následných legislativních opatření např. Stockholmská úmluva o POP, kterou podepsalo 178 států, dochází v posledních desetiletích k obnově některých ohrožených populací zvířat. Příkladem takových obnovených populací jsou lachtani v Baltickém moři, nebo mořští mlži v přístavech, kde se dříve používal *Poznámka autorky: anglické zkratky jsou ponechány u těch výrazů, u kterých zatím nebyl ustálen český ekvivalent 17

18 tributylcín (WHO and UNEP 2013). Většina látek, které nahradily POP, však nebyla zatím na EDCs vlastnosti dostatečně testována a v některých zemích dokonce stále stoupají i hladiny známých POP v tkáních živočichů (WHO and UNEP 2013). Během posledních dvou desetiletí bylo prokázáno, že i další méně hydrofóbní a méně perzistentní látky mohou způsobit endokrinní disrupci organismů s možným dopadem na celé populace. Jde především o působení tzv. pseudoperzistentních látek, což jsou polutanty, které sice mohou mít v životním prostředí (ŽP) kratší poločas života (typicky několik hodin až dnů), ale jejich konstantní přísun způsobuje, že jsou v ŽP neustále přítomné v relativně stabilních koncentracích. Příkladem může být přirozený hormon 17βestradiol (E2), jehož poločas života v říční vodě se pohybuje okolo několika málo dnů, avšak jeho kontinuální přísun z čištěných nebo případně i nečištěných splaškových odpadních vod způsobuje relativně stálou přítomnost jeho reziduí ve vodách pod výpustmi těchto vod (Sumpter and Johnson 2008). Řada pseudoperzistentních látek patří do skupiny označované také jako polární organické polutanty. Jde však o látky polární pouze ve srovnání např. s POP, jejichž koeficient oktanol/voda (Kov), podle něhož se hydrofobicita/hydrofilita látek stanovuje, se běžně pohybuje okolo Polární organické polutanty většinou mívají Kov do , což ale znamená, že i tyto látky mají mnohem větší tendenci přecházet do lipofilních tkání než do vody (např. Alvarez et al. 2007). Dalším pojmem, který se často vyskytuje v souvislosti s polárními organickými látkami je emerging pollutants (nové typy pilutantů). Jsou to látky, které se vyskytují v ŽP v nízkých, avšak nelze vyloučit, že biologicky aktivních koncentracích, a to téměř po celém světě. Vzhledem k zmíněným nízkým koncentracím byla jejich existence objevena poměrně nedávno, až po zdokonalení analytických metod. Jedná se např. o některá farmaka, látky obsažené v tzv. zboží denní spotřeby (Personal Care Products) nebo v čisticích prostředcích. Řada emerging pollutans jsou právě EDCs a/nebo polární organické polutanty anebo mají být na ED vlastnosti teprve testovány. EDCs jsou dále rozdělovány na tzv. prokázané EDCs - způsobující některým organismům ED v environmentálních koncentracích (může jít i o spolupůsobení ve směsích), a potenciální EDCs - byly u nich identifikovány vlastnosti, které 18

19 naznačují, že by mohly způsobit ED (např. vazba na některý z receptorů endokrinního systému), ale zatím nebylo potvrzeno, že by ji způsobovaly in vivo. Důvodem, proč většina látek nebyla na tento typ toxicity in vivo testovaná, je mimo jiné to, že negativní účinky ED se mohou projevit až v další generaci jedinců nebo jen při působení v určité kritické periodě životního cyklu a je proto nutné provádět chronické a multigenerační studie (WHO and UNEP 2013). To dělá testování extrémně nákladným a zdlouhavým a existuje proto snaha využívat rychlé screeningové metody, které by poukázaly na ty látky, které jsou potenciálními EDCs a mají být proto v in vivo testech prozkoumány přednostně. Baterii screeningových testů již např. využívá "United States Environmental Protection Aagency" (americká obdoba Ministerstva ŽP). Jednotlivé látky na trhu tedy jsou anebo mají být dle legislativ příslušných zemí postupně testovány. Přehled známých potenciálních EDCs je uveden v příloze VII Zaměření na odpadní a povrchové vody Vzhledem k tomu, že vodní prostředí je většinou konečným rezervoárem chemických látek (Obrázek 1), jsou vodní organismy (např. ryby či vodní bezobratlí) a živočichové, jejichž citlivá stádia se vyvíjejí ve vodě (např. obojživelníci), jedněmi z nejvíce ohrožených druhů živočichů ve smyslu ED (Vethaak et al. 2007). Feminizace samců ryb v řekách pod výpustmi z ČOV byla pozorována v mnoha zemích světa (Sumpter and Johnson 2008, Vethaak et al. 2007) včetně ČR (Zlabek et al. 2004, Penaz et al. 2005, Randak et al. 2009). Endokrinní disrupce byla pozorovaná také u bezobratlých. Nejznámější je vymírání populací předožábrých plžů vlivem malformací pohlavní soustavy způsobených organocíny, které se používaly k nátěrům lodí (Vos et al. 2000). V ČR byla ED pozorována např. u populace raka bahenního (Pontastacus leptodactylus) ve vodách v blízkosti uhelných dolů na Karvinsku (Mazurova et al. 2008). Další příklady endokrinní disrupce volně žijících zvířat jako je ztenčování skořápek vajec rybožravých ptáků, pokles reprodukční schopnosti tuleňů v baltickém moři či feminizace samců aligátorů z jezera znečištěného pesticidy shrnuje např. literární rešerše Vos et al. (2000). Všechny dosud známé 19

20 příklady se přitom váží na vodní prostředí. S ohledem na nutnost charakterizovat především působení dosud málo prozkoumaných skupin EDCs, jakými jsou polární organické polutanty, jsem se během doktorského studia zaměřila na hlavní známé zdroje těchto látek - odpadní vody a jejich nejčastější recipienty - řeky. Obrázek 1: Zjednodušené schéma zdrojů znečištění vod a pohybu polutantů 2.4. Biotesty jako nástroje pro sledování přítomnosti hormonálně aktivních látek v environmentálních vzorcích Organismy v reálném prostředí ale nejsou vystaveny jednotlivým chemickým látkám, nýbrž jejich směsím. Hodnocení potenciálu vzorků vody narušovat endokrinní systém na základě znalostí jednotlivých v nich obsažených EDCs, nemusí být přesné. Díky neznalosti všech přítomných EDCs a případně jejich 20

21 interakcí může docházet k významnému zkreslení ED potenciálu (Leusch et al. 2005). Další limitací je často finanční náročnost instrumentálních analytických metod, neboť některé významné EDCs působí hormonální narušení již v řádech jednotek ng/l a jejich analytické stanovení v komplexních matricích, jako je odpadní voda, je proto problematické (např. Caldwell et al. 2012). Tradiční chemické analýzy proto bývají doplňovány nebo nahrazovány biologickými metodami - stejnými nebo velmi podobnými, jako jsou ty, používané k určení jednotlivých potenciálních EDCs. Tyto testy s tkáňovými kulturami (in vitro) umožňují kvantitativní hodnocení ED potenciálu environmentálních směsí bez nutné znalosti chemického složení směsí a mechanismu interakcí jednotlivých látek (Jedlickova 2008). Během doktorského studia jsem pomocí in vitro biotestů zkoumala především anti/estrogenní a anti/androgenní působení látek příromných v odpadních a povrchových vodách. Jedná se o jedny z nejvíce sledovaných mechanismů narušení hormonálního systému organismů především proto, že minimálně u obratlovců se estrogeny a androgeny významně podílejí na vývoji pohlavních buněk i pohlavních orgánů, na rozvoji sexuálního chování, na vývoji oplodněných vajíček, na růstu embrya a řadě dalších dějů (Jedlickova 2008). Dále byla u vzorků odpadních a povrchových vod hodnocena toxicita dioxinového typu. Dioxinově aktivní látky mohou způsobovat neurotoxicitu, karcinogenezi, imunotoxicitu nebo teratogenitu (Hilscherova et al. 2000). Dosud byla tomuto typu toxicity věnována pozornost především u nepolárních organických látek. V našem výzkumu jsme sledovali toxicitu dioxinového typu ve vodní fázi odpadních anebo povrchových vod. 21

22 3. Použité materiály a metody Tato kapitola obsahuje základní informace o použitých materiálech a metodách. Podrobný popis materiálů a metod, jako např. objemy odebraných vzorků, značky použitých pomůcek, přesné postupy extrakcí, měření odpovědí buněk a podobně, jsou uvedeny v jednotlivých článcích (přílohy I - VI) Vzorkované lokality Pro zjištění ED potenciálu (anti/estrogenita, anti/androgenita a toxicita dioxinového typu) u řek minimálně zatížených antropogenními zdroji znečištění a pro pozorování vlivu obcí s ČOV na ED potenciál těchto toků byly vybrány lokality na horních tocích řek/potoků nad a pod obcemi: Králíky, Jilemnice, Cvikov, Tachov, Volary, Vimperk a Prachatice (Obrázek 2, Článek I). Velikost obcí se lišila od 1900 obyvatel do obyvatel. Všechny ČOV měly primární (mechanický) a sekundární (biologický) stupeň čištění, konkrétněji šlo o nádrže s aktivovaným kalem. Obec Cvikov navíc používala ČOV s dodatečným dočišťovacím jezírkem. Lokality byly vybrány kolegy z Jihočeské univerzity v Českých Budějovicích, Výzkumného ústavu rybářského a hydrobiologického ve Vodňanech, kteří na těchto místech hodnotili biomarkery ED a stresu u ryb. Hlavním kritériem proto bylo, kromě nízké zátěže antropogenními zdroji, výskyt jezů, který umožňoval oddělit ryby exponované látkami z ČOV a ryby, které s těmito látkami nepřišly do styku. Závěry našeho výzkumu byly dále srovnány s výsledky chemických analýz vzorků, které byly analyzovány týmem pracovníků Zdravotního ústavu se sídlem v Ostravě, Národní referenční laboratoře pro POP v Ostravě. 22

23 Obrázek 2: Mapa České republiky s vyznačením vzorkovaných lokalit sloužících pro zjištění ED potenciálu u toků minimálně zatížených antropogenními zdroji a pro pozorování vlivu obcí s ČOV na ED potenciál těchto toků. Efektivita odstranění a variabilita ED potenciálu (anti/estrogenita, anti/androgenita a toxicita dioxinového typu) v průběhu roku, byly hodnoceny na nově rekonstruované (termín dokončení modernizace r. 2004) ČOV v Brně Modřicích (článek II). Jedná se opět o ČOV s primárním (mechanickým) a sekundárním (biologickým) stupňem čištění, ale jde o ČOV sloužící v současné době více než ekvivalentních obyvatel a z toho důvodu pro ni platí také přísnější parametry pro odstraňování zejména dusíku a fosforu. Aktivační nádrže jsou proto rozděleny do zón podle množství prokysličení, které slouží především k podpoře de/nitrifikačních bakterií. Odstranění fosforu bylo sice navrženo biologickou cestou, ale v době vzorkování probíhalo přidáváním srážedla. Důvodem byla obtížnost zajištění anaerobních podmínek (není přítomen ani kyslík, ani oxidované dusíkaté sloučeniny), které jsou pro 23

24 biologické odbourávání fosforu nezbytné. ČOV v Brně Modřicích byla zvolena kvůli blízkosti místa provádění analýz a kvůli dobré reprezentativnosti moderních evropských ČOV (podobná technologie jako většina městských ČOV v EU). Studie byla navíc využita pro doplnění výzkumu prováděného řadou dalších institucí (viz článek II). Výběr lokalit pro hodnocení estrogenního a dioxinového potenciálu čištěných odpadních vod z ČOV v rámci EU byl proveden (na základě dobrovolnosti) různými institucemi spolupracujícími s výzkumnými laboratořemi Evropské komise v Ispře, Itálie (článek III, IV). Nebyla požadována žádná kritéria výběru, ale dodavatelé vzorků byli informování, že jedním z cílů studie bylo charakterizovat koncentrace a účinky nových typů polutantů v ČOV přijímajících; a) výhradně splaškové vody nebo b) vody industriální a splaškové nebo c) vody industriální, splaškové i dešťové. Většina vod proto pocházela z obecních ČOV o různých velikostech. Několik vzorků také pocházelo z čistě průmyslových ČOV, ale tyto byly vybrány pouze jednou spolupracující institucí v Belgii. Odpadní vody byly zaslány z 16ti zemí EU. U těch ČOV, jejichž původ mohl být zveřejněn, je lokalita a popis základních technických parametrů zobrazen v článku VI (Table SI 1). Pro účely srovnávací studie různých biotestů byly odebrány vzorky odpadních vod ze dvou různých australských ČOV recyklujících odpadní vody až na vody, které dosahují parametrů pro pitnou vodu a jsou využívány jako voda užitková (článek VI). Vzorky byly u obou ČOV odebrány v různých stupních čištění počínajících dokončeným sekundárním stupněm (biologické čištění - podobné jako u popisované ČOV v Brně Modřicích) a dále na první ČOV šlo o vzorky odpadní vody zpracované pomocí membránové mikrofiltrace, reverzní osmózy a oxidace pomocí peroxidu vodíku a UV záření. Kromě vzorku ze sekundárního čištění byly na druhé ČOV hodnoceny odpadní vody dále čištěné oxidačními procesy pomocí ozónu spojené s odstraněním zbytkových škodlivin pomocí sorpce na aktivní uhlí. Dalšími vzorky byla říční voda sloužící jako zdroj pitné vody a dále tato voda upravená na vodu pitnou. Kromě toho byla testována srážková voda a kontrolní vzorek procedurální blank (destilovaná voda). Výběr i zpracování vzorků bylo provedeno koordinujícím týmem 24

25 mezilaboratorní studie (článek VI). Vzorky byly jednotlivými laboratořemi hodnoceny bez znalosti původu extraktů (jako slepé vzorky ) Odběr vzorků Aktivní vzorkování Odebrat reprezentativní vzorek je základem pro správnou interpretaci výsledků měření a u vzorků vody z ŽP je to poměrně nesnadný úkol. Koncentrace látek ve vodách se mohou měnit např. v závislosti na vypouštění odpadních vod z průmyslových podniků nebo z domácností. Běžně se za reprezentativní vzorek považuje 24hodinový směsný vzorek, odebíraný minimálně každé 2 hodiny. Objemy jednotlivých odběrů mohou být stejné (v české terminologii tzv. vzorek typu B) nebo se mohou lišit úměrně k velikosti průtoku (tzv. vzorek typu C). Vzorek typu C je např. českou legislativou vyžadován pro standardní testování kvality odpadních vod na velkých ČOV. Nicméně přítok na velké (více než ekvivalentních obyvatel) ČOV je na rozdíl od malých ČOV většinou poměrně stálý a tak mezi vzorky typu B a C na těchto ČOV nebývá velký rozdíl. Naopak u menších obcí se přítok odpadních vod do čistírny často radikálně mění během dne, ale odběr vzorků úměrný k průtoku není legislativou požadován a proto jsou pro vzorkování na těchto ČOV většinou k dispozici jen vzorky typu B. Jednorázově odebrané vzorky reprezentují pouze okamžitou situaci a proto nejsou příliš často používány pro charakterizaci ED potenciálu. Směsné vzorky typu B byly použity ve studii zaměřené na sledování účinnosti ČOV v Brně Modřicích odstraňovat látky s ED potenciálem a ke sledování variability této účinnosti a velikosti ED potenciálu během roku (článek II). Dále byly spolu s jednorázovými vzorky použity při hodnocení estrogenního a dioxinového potenciálu různých čištěných odpadních vod z EU (článek III, IV - vzorky byly poskytnuty koordinující laboratoří Evropské komise (Ispra, Itálie), autorka práce se spolupodílela pouze na odběrech 7 vzorků z ČR). Detailní údaje o způsobu vzorkování na jednotlivých evropských ČOV bohužel nejsou k dispozici. 25

26 Vzorky byly při aktivním vzorkování odebírány do skleněných lahví pomocí automatických vzorkovačů dlouhodobě používaných na jednotlivých ČOV. Dlouhodobost používání těchto zařízení může hrát významnou roli vzhledem k faktu, že mnohá aditiva plastů (plasty bývají součástí vzorkovačů), mohou být EDCs (Kinnberg 2003), a proto je důležité používat raději vzorkovače, které jsou při rutinních odběrech na ČOV téměř denně vymývány vzorky, než vzorkovače nové. Ve studii evropských odpadních vod bohužel nejsou dostupné podrobnosti o vzorkování, nicméně vzorky byly přepravovány ve speciálních HDPE plastových lahvích testovaných laboratořemi Evropské komise (článek III, IV) Pasivní vzorkování V reálných podmínkách může docházet k jednorázovému uvolnění polutantů, jako je např. náhlé vypuštění odpadních vod nebo přepad odlehčovacích komor v kanalizační síti vlivem nadměrného hydrologického zatížení této sítě. Není-li monitoring kontinuální, což z finančního hlediska většinou není možné, ani pomocí 24hodinového směsného vzorku se tak nemusí podařit podobné znečištění zachytit. To je jedním z hlavních důvodů pro použití tzv. pasivního vzorkování, které umožňuje stanovit průměrné koncentrace ED potenciálů či jednotlivých polutantů za určitý čas (obvykle v řádu týdnů). Pasivní vzorkovací metody jsou založeny na samovolném průniku rozpuštěných látek z vodního prostředí do vzorkovacího zařízení - pasivního vzorkovače, ve kterém jsou tyto látky následně zachyceny a zkoncentrovány (Kohoutek et al. 2007). To navíc umožňuje lepší stanovení koncentrací jinak obtížně detekovatelných látek. Během doktorského studia jsem hodnotila vzorky ze dvou typů pasivních vzorkovačů. Šlo o tzv. Polar Organic Chemical Integrative Sampler (POCIS) z nichž jeden byl uzpůsoben pro vzorkování širokého spektra relativně polárních farmaceutických látek (POCIS Pharm) a druhý pesticidů (POCIS Pest). Obě spektra vzorkovaných látek se přitom do velké míry překrývala (Alvarez et al. 2007, Arditsoglou and Voutsa 2008). POCIS Pest a POCIS Pharm byly využity ve studii hodnotící ED potenciál antropogenně málo zatížených toků a vliv obcí s ČOV na ně (článek I). Pasivní vzorkovače byly umístěny přibližně 0,5 m pod hladinu a byly exponovány po dobu dní, 26

27 což je doba kratší, než za jakou dosahují polární organické látky nasycení v sorbentech vzorkovačů POCIS (Söderström et al. 2009, Alvarez et al. 2008). Proto jsme předpokládali, že polární organické polutanty, jejichž účinky jsme pomocí POCIS zkoumali, by se měly nacházet v tzv. lineární fázi vzorkování (článek I). Pasivní vzorkovače POCIS i tzv. Semipermeable Membrane Devices (SPMD) sloužící pro vzorkování nepolárních organických látek byly dále použity v článku II, kde byl mimo vody z ČOV hodnocen dále ED potenciál říční vody ovlivněný městkou aglomerací. Tato část práce byla ale převážnou většinou zpracována kolegyní Veronikou Jálovou a proto se jí ve své dizertační práci budu věnovat jen okrajově Zpracování vzorků Vzorky vody Vzorky vody byly vždy zpracovány do 24 hodin od odběru/obdržení vzorku. Do té doby byly uchovávány v chladu (4 C), aby se pokud možno co nejvíce předešlo degradacím látek ve vzorcích. Vzorky jsou obvykle extrahovány pomocí tzv. extrakce na tuhé fázi (Solid Phase Excraction, SPE), které předchází filtrace (filtry nebo vata se skleněnými vlákny) nebo centrifugace pevných složek vzorků tak, aby nedošlo k ucpání pevné fáze při extrakci. Extrakční metody, přesněji řečeno sorbenty a eluční činidla, podobně jako možná acidifikace vzorků před zpracováním se vyvíjejí a velmi různí. V počátcích mého doktorského studia neexistovala jednotná standardizovaná metoda pro přípravu vzorků na testování jejich různého ED potenciálu. Nejvíce studií se zaměřovalo na estrogenní, případně androgenní působení látek ve vzorcích, které byly většinou nalezeny v polární - metanolové (MeOH) frakci extraktů (např. Kinnberg 2003, Fernandez et al. 2007). Methanol je navíc vhodným rozpouštědlem pro provádění většiny in vitro testů. Při použití více elučních rozpouštědel je nutné rozpouštědla dále odpařit a po té látky rekonstituovat v MeOH. Při tomto kroku přitom hrozí ztráta ED aktivity, a 27

28 proto jsme se rozhodli pro hodnocení ED potenciálu v MeOH extraktech odpadních vod (článek II, III, IV). Vysoká účinnost (> 95 %) extrakce standardního estrogenu E2 při eluci kolon C18 nebo HLB Waters Oasis methanolem byla navíc již dříve ověřena jak námi, tak ve studii Leusch et al. (2006). C18 nebo HLB Waters Oasis jsou k popisovanému účelu nejčastěji používanými kolonami nebo disky s tuhým sorbentem. Z důvodů menší pracnosti většina autorů pozdějších studií používala HLB Waters Oasis (např. Miege et al. 2009, Macova et al. 2011). Tyto sorbenty byly použity i v našich studiích (článek II, III, IV, VI). Po eluci sorbentu byly extrakty dále zakoncentrovány pomocí slabého proudu dusíku. V současné době, kdy in vitro testy pro hodnocení různých ED potenciálů (nejen estrogenní a androgenní aktivity) procházejí v mezinárodním měřítku hodnocením jejich využitelnosti v legislativě a nezbytnou standardizací, začínají být konečně blíže diskutovány také nejvhodnější metody extrakce vodných vzorků. Pokud je autorce známo, v současné době je odborné veřejnosti dostupný pouze dokument australské vlády Chapman et al. (2011). Za účelem zjištění extrakční metody, která by zachytila nejen látky s ED potenciálem, ale i látky s jinými negativní účinky na buňky jako je např. nespecifická toxicita, genotoxicita, vliv na metabolismus, peroxidace lipidů a podobně, byla zkoumána výtěžnost extrakce látek s různými fyzikálněchemickými vlastnostmi a s různými účinky na buňky. Nejlepší výtěžnosti exktrakce různých látek bylo dosaženo při použití SPE kolon HLB Waters Oasis doplněnými o další kolonu Supelclean coconut charcoal cartridge (článek VI). Jako eluční činidlo byl použit MeOH, ale sorbenty byly dále eluovány pomocí směsi hexan:aceton v poměru l:1 objemových %. Dle této metody byly zpracovány vzorky čištěné odpadní vody v mezinárodní studii hodnotící vhodnost různých in vitro metod pro charakterizaci znečištění recyklované odpadní vody (článek VI) Vzorky z pasivních vzorkovačů Pasivní vzorkovače POCIS byly zpracovány dle metod dříve standardizovaných Alvarez et al. (2007). Vzhledem k tomu, že pasivní vzorkovače POCIS obsahují tuhé sorbenty, mohou být po vyjmutí z vody zamrazeny a eluovány později. 28

29 Doba zamražení (-18 C) byla kratší než 2 měsíce. Sorbenty ze vzorkovačů byly převedeny do prázdných skleněných SPE kolon odkud byly podobně jako při SPE metodě eluovány. V případě POCIS Pharm byl dle postupu použit MeOH, v případě POCIS-Pest směs dichlormethanu, MeOH a toluenu v objemových poměrech 8:1:1 (Alvarez et al. 2007). V případě POCIS Pest byl objem extraktu pomocí slabého proudu dusíku snížen na minimum a místo původní směsi rozpouštědel byl přidán MeOH Použité biotesty Ve své doktorské práci jsem ED potenciál vzorků z ŽP charakterizovala pomocí tzv. testů odpovědi reporterového genu. Hodnotila jsem potenciál reálných směsí látek v odpadních nebo říčních vodách stimulovat/inhibovat transkripční aktivitu vázanou na aktivaci estrogenního (ER), androgenního (AR) nebo arylhydrokarbonového (AhR) receptoru. Princip těchto různých in vitro testů vysvětlím pomocí příkladu aktivace estrogenního receptoru, protože ostatní použité testy fungují na obdobných principech s drobnými rozdíly popsanými dříve v diplomové práci (Jedlickova 2008). Pro hodnocení estrogenity jsem používala geneticky modifikované buňky upravené transfekcí (umělým přenosem) DNA, která obsahuje sekvenci reporterového genu (Sanderson et al. 1996). Dojde-li k aktivaci receptoru vazbou estrogenu nebo xenobiotika, pak je kromě genů řízených estrogeny stimulována teké exprese reporterového genu, čímž je zahájena syntéza enzymu luciferázy, jehož množství je stanovováno luminiscenční metodou. Intenzita luminiscence je přímo úměrná koncentraci takových látek ve vzorku, které aktivují estrogenní receptor. Princip testu je schematicky znázorněn na Obrázku 3. Stanovení míry estrogenního působení vzorků je prováděno srovnáním s estrogenním působením standardního estrogenu E2. Výsledek měření je vyjádřen jako tzv. estrogenní ekvivalent (z anglického Estrogenic Equivalent, EEQ), který odpovídá koncentraci E2, která vyvolala v testu stejnou odpověď jako vzorek. 29

30 Podobně byl androgenní potenciál vzorků vyjádřen jako androgenní ekvivalent (AEQ) vztažený na standardní androgen testosteron případně dihydrotestosteron a dioxinový potenciál jako tzv. TEQbio, jehož standardem byl 2,3,7,8 tetrachlorodibenzo-p-dioxin (TCDD). Přehled použitých testů a standardních látek je uveden v Tabulce 1. Obrázek 3: Schéma molekulárního mechanismus estrogenního děje (převzato z Hilscherová et al. (2000)). Xenoestrogen - xenobiotikum s estrogenním účinkem, ER - estrogenní receptor, HSP - pomocné proteiny (Heat Schock Proteins), ERE úseky DNA, na které se váže aktivovaný ER (Estrogen Responsive Elements) 30

31 Tabulka 1: Přehled použitých in vitro testů a standardních látek sledovaný biotest parametr aktivace/ inhibice MVLN ER Saccharomyces aktivace/ inhibice cerevisiae* AR pozitivní kontrola 17β-estradiol testosteron způsob prezentace výsledků estrogenní ekvivalent vztažený k 17β-estradiolu (EEQ) androgenní ekvivalent vztažený k testosteronu (TEQ) ekvivalent TCDD (TEQbio) nebo REF 10 (Relative Enrichment Factor) = zakoncentrování vody, které způsobilo 10 % aktivaci číslo článku, ve kterém byl test použit I, II, III, IV H4IIEluc aktivace AhR TCDD I, II, III, IV, VI REF 10 (Relative Enrichment aktivace/ inhibice Factor) = zakoncentrování vody, herα-hela ER 17β-estradiol které způsobilo 10 % aktivaci VI aktivace AR a glukokortikoidního dihydrotestosteron androgenní ekvivalent vztažený MDA-kb2 receptoru (GR) k dihydrotestosteronu (AEQ) II, VI REF 20 (Relative Enrichment Factor) = zakoncentrování vody, které způsobilo 20 % inhibici MDA-kb2 Inhibice AR a GR flutamid nebo ekvivalent flutamidu II, VI REF 10 (Relative Enrichment Factor) = zakoncentrování vody, AhR- CAFLUX aktivace AhR TCDD které způsobilo 10 % aktivaci VI *modifikované k expresi humánního AR a luciferázového reporterového genu I, II 31

32 4. Výsledky Tato kapitola shrnuje především informace o výsledcích in vitro testů, které v rámci doktorského studia měřila autorka práce. Další výsledky, jako např. hladiny analyticky stanovených látek nebo uvážení rizik naměřených potenciálů pro vodní biotu, jsou stručně shrnuty v diskusi a podrobnější výsledky lze najít v jednotlivých článcích Anti/estrogenita, anti/androgenita a toxicita dioxinového typu u vzorků říční vody minimálně zatížené antropogenními vlivy a u vzorků odebraných z týchž řek pod prvními obcemi (článek I) Anti/estrogenita, anti/androgenita Estrogenita byla detekována na téměř všech zkoumaných lokalitách a to jak ve vzorcích nad obcemi tak pod nimi. Ve všech vzorcích odebraných pod obcemi však byla koncentrace estrogenního potenciálu zvýšená oproti situaci nad obcemi a to 1,3krát 14krát (Obrázek 4). U pozaďových lokalit (nad obcemi) se detekovaný EEQ lišil od nedetekovatelných množství (<0,2 ng/pocis) po 0.5 ng/pocis, což po přepočtu na koncentraci ve vodě (článek I, Eq. 1) činilo <0,1 0,3 ng/l. Koncentrace EEQ pod obcemi se lišily od nedetekovatelných množství (0,3 ng/pocis) až po 4,8 ng/pocis, což po přepočtu odpovídalo <0,2-2,3 ng/l. Estrogenní potenciál v extraktech z POCIS Pest a Pharm se přitom významně nelišil (článek I, capture 3.2.). Antiestrogenní a anti/androgenní potenciál nebyl detekován v žádném ze vzorků. 32

33 Obrázek 4: Estrogenní aktivita extraktů z POCIS Pest a POCIS Pharm stanovená s využitím MVLN buněčné linie. Prázdná místa značí estrogenitu pod limitem detekce, chybové úsečky směrodatnou odchylku ze dvou nezávislých měření Toxicita dioxinového typu Toxicita dioxinového typu byla detekována v extraktech pocházejících z lokalit nad i pod obcemi. Vyšší potenciál byl sice častěji detekován ve vzorcích pod obcemi, ale vliv obcí jakožto zdroje těchto látek byl oproti estrogennímu potenciálu výrazně nižší. Většina dioxinové aktivity byla detekována v extraktech z POCIS Pharm (MeOH extrakt, HLB waters sorbent), zatímco většina extraktů z POCIS Pest nevykazovala tuto aktivitu nad detekčním limitem - 0,09 ng/pocis TEQbio (Obrázek 5). Jedná se o první studii, kde byla toxicita dioxinového typu hodnocena a zjištěna v extraktech vzorkovačů POCIS. 33

34 Obrázek 5: Toxicita dioxinového typu detekovaná v extraktech z POCIS Pest a POCIS Pharm s využitím H4IIELuc buněčné linie. Prázdná místa značí toxicitu dioxinového typu pod limitem detekce, chybové úsečky směrodatnou odchylku ze dvou nezávislých měření Variabilita anti/estrogenního, anti/androgenního a dioxinového potenciálu směsí látek přítomných v přítoku a v odtoku z modelové ČOV v průběhu roku a účinnost odstranění těchto látek (článek II) Výsledky měření anti/estrogenního a anti/androgenního potenciálu vzorků odpadní vody a účinnost jejich odstranění na ČOV již byly zahrnuty v autorčině diplomové práci (Jedlickova 2008). Kvůli zachování celistvosti výsledků výzkumu a navazující diskuse jsou stručně zopakovány i v této části dizertační práce Anti/estrogenita Estrogenní potenciál odpadní vody se pohyboval of 5 do 125 ng/l EEQ na přítoku do ČOV a od 0,1 do 5,1 ng/l EEQ po vyčištění (Tabulka 2). Účinnost odstranění estrogenních látek na ČOV v průběhu roku dosahovala 80 až >99 %, s mediánem 99% (Tabulka 2). U žádného z extraktů vzorků odpadní vody nebyl naměřen antiestrogenní potenciál. 34

35 Tabulka 2: Estrogenní potenciál vzorků odpadní vody a účinnost jeho odstranění na ČOV v Brně Modřicích. Koncentrace jsou vyjádřeny jako ng ekvivalentu 17β-estradiolu (EEQ) na litr vody. Estrogenita [ng/l EEQ] Odběr Přítok Odtok % odstranění EEQ květen 07 33,6 0,1 99,8 červen ,5 3,6 95,6 červenec 07 44,4 2,3 94,9 srpen 07 43,9 0,2 99,5 září 07 67,6 0,9 98,6 říjen 07 25,2 5,1 79,9 listopad 07 17,9 0,1 99,7 prosinec 07 16,9 1,0 94,1 leden 08 13,5 0,2 98,8 únor 08 5,4 0,1 98,3 březen 08 33,9 0,8 97,5 duben 08 13,7 0,1 99,6 Naměřené EEQ u přítoku do ČOV se v průběhu roku lišily až 23krát a v případě odtoku až 83krát. Nejvyšších hodnot bylo u obou typů vzorků dosaženo v letním období, což toho roku odpovídalo nižším stavům dešťové vody v kanalizační síti a tím i vyššímu podílu splašků v odpadní vodě. Údaje o roční variabilitě ED potenciálů jsou nezbytné mimo jiné proto, že většina odběrů odpadních vod bývá prováděna mimo zimní období a díky nižším teplotám by se mohla zpomalit bakteriální degradace a tím i efektivita odstranění sledovaných látek (Caliman and Gavrilescu 2009). Tato hypotéza však potvrzena nebyla. V zimním období byly hladiny ED potenciálů buď nižší, jako v případě EEQ, nebo nebyla sezonalita patrná vůbec, jako v případě androgenního nebo dioxinového potenciálu (viz níže). Mnohem nižší variabilitu vykazovala vysoká účinnost odstranění estrogenních látek. Z výsledků vyplývá, že nejvyšší rizika přísunu estrogenních látek pro vodní organismy je možné očekávat v průběhu nízkých stavů vod, v tomto případě v létě. Podobné závěry publikovali nedávno Anderson et al. (2012), avšak tento předpoklad nemusí platit pro všechna místa. Některé ČOV mohou odstranit větší podíl 35

36 estrogenních látek v suchých obdobích, protože doba zdržení vody na ČOV může být, díky jejím nízkým objemům, mnohonásobně delší (Etienne Vermeirssen, Swiss Fed Inst Aquat Sci & Technol, EAWAG, ústní sdělení). Na základě našich výsledků a výsledků evropských zahraničních studií, jsme pro hodnocení estrogenního potenciálu jako kritická určili zejména tato 2 různá období: 1) Suchá období, kdy koncentrace EDC mohou být zvýšené díky nízkému ředění dešťovou nebo říční vodou 2) Období přívalových dešťů, kdy doba zdržení odpadních vod v ČOV klesá na minimum a v řadě případů jsou splaškové vody ředěné dešťovou vodou přímo uvolňovány do recipientů ať už odlehčovacími komorami na ČOV nebo na kanalizační síti Anti/androgenita Androgenita byla detekována pouze u některých extraktů odpadní vody na přítoku a to v rozmezí 23 až 193 ng/l AEQ. U žádného extraktu vzorku vody z odtoku nebyla při hodnocení androgenního potenciálu naměřena významná indukce luminiscence. Díky vysoké citlivosti buněk k toxicitě vzorků (viz níže), bylo nejnižší stanovitelné množství androgenních látek poměrně vysoké (1,3 až 3,7 ng/l AEQ pro odtok a 23 až 70 ng/l AEQ pro přítok) a proto jsme se rozhodli údaje o těchto detekčních limitech zahrnout do výsledkové tabulky (Tabulka 3). V případě přítomnosti androgenních látek na úrovni této meze stanovitelnosti by byla minimální účinnost jejich odstranění vždy vyšší než 94 % (Tabulka 3). 36

37 Tabulka 3: Androgenní potenciál vzorků odpadní vody a účinnost jeho odstranění na ČOV v Brně Modřicích. Koncentrace jsou vyjádřeny jako ng ekvivalentu testosteronu (AEQ) na litr vody. Androgenita [ng/l AEQ] Odběr Přítok Odtok % odstranění AEQ květen <3,7 >98 červen <2,2 >98 červenec 07 < 70 <2,2 >97 srpen 07 <70 <2,6 >96 září 07 <23 <1,3 >94 říjen <1,3 >98 listopad <1,3 >99 prosinec <1,3 >99 leden <1,3 >99 únor <1,3 >99 březen <1,3 >97 duben <1,3 >96 Ačkoliv antiandrogennita nebyla u vzorků odpadních vod detekována, použitá buněčná linie byla velmi citlivá k cytotoxicitě a antiandrogenní účinky proto mohly být touto toxicitou překryty. Svědčí o tom také výsledky kolegyně Jálové (článek II), která pomocí jiné, na cytotoxicitu méně citlivé, buněčné linie (MDA-kb2) antiandrogenní vlastnosti říční i povrchové vody vzorkované pomocí POCIS i SPMD semikvantitativně detekovala (článek II). Navíc, ve studii čištěných odpadních vod ze 2 ČOV, které upravovaly odpadní vodu až na vodu s parametry pitné vody (článek VI), byla u některých vzorků pomocí této linie (MDA-kb2) naměřena antiandrogenní aktivita odpovídající jednotkám µg/l flutamidového ekvivalentu Toxicita dioxinového typu Toxicita dioxinového typu se pro látky v extraktech odpadní vody na přítoku pohybovala od 0,1 do 3,4 ng/l TEQbio a od 0,1 do 0,7 ng/l TEQbio pro extrakty vody na odtoku (Tabulka 4). Účinnost odstranění těchto látek se v průběhu roku 37

38 pohybovala od 13 do 90 %, ve dvou případech byla pozorovaná hladina vyšší na výstupu než na vstupu (Tabulka 4). Tabulka 4: Toxicita dioxinového typu naměřená v extraktech vzorků odpadní vody a účinnost jejího odstranění na ČOV v Brně Modřicích. Koncentrace jsou vyjádřeny jako ng ekvivalentu 2,3,7,8-tetrachlorodibenzo-p-dioxinu (TEQbio) na litr vody. Toxicita dioxinového typu [ng/l TEQbio] Odběr Přítok Odtok % odstranění TEQ květen 07 0,6 0,3 41 červen 07 1,8 0,4 79 červenec 07 1,3 0,2 83 srpen 07 3,4 0,3 90 září 07 1,0 0,4 60 říjen 07 1,2 0,6 53 listopad 07 0,6 0,5 13 prosinec 07 1,8 0,2 88 leden 08 1,0 0,6 35 únor 08 0,7 0,7-8 březen 08 0,8 0,2 76 duben 08 0,1 0, Hodnocení estrogenního a dioxinového potenciálu látek přítomných ve vzorcích odtoků z evropských ČOV (článek III, IV) Estrogenita U 27 ze 75ti testovaných extraktů odtoků z evropských ČOV byl naměřen estrogenní potenciál vyšší než 0,5 ng/l EEQ, což byl v této studii limit detekce. Estrogenita u pozitivních vzorků se lišila od 0,53 to 17,9 ng/l EEQ s mediánem 1,2 a průměrem 2,7 ng/l EEQ. Medián a aritmetický průměr všech 75ti testovaných vzorků byl < 0,5 ng/l EEQ a 0,9 ng/l EEQ. Dalších 9 vzorků 38

39 bylo cytotoxických/antiestrogenních (tyto 2 různé účinky se v biotestu projevují podobně a pro jejich odlišení by bylo třeba extrakty dále testovat jinými testy, které nebyly prováděny). Mezi testovanými ČOV bylo také 6 českých městských ČOV, jejichž EEQ se lišil od <0,5 ng/l po 2,1 ng/l. Ačkoliv se může zdát, že voda na výtocích z ČOV v České republice má ve srovnání s celoevropským standardem průměrné až mírně vyšší hodnoty estrogenního potenciálu, takovýto závěr by byl zavádějící a to nejen vzhledem k malému počtu vzorků, který nemůže být zcela reprezentativní pro celou republiku, ale také díky možné variabilitě v průběhu roku. Výsledky představují zatím největší existující soubor hodnot o estrogenním potenciálu v odtocích z ČOV v EU, ale zobrazují pouze okamžitou situaci, která se, jak jsme již dříve ukázali, může v průběhu delšího časového období mnohonásobně lišit. Proto není smysluplné na jejím základě např. porovnávat jednotlivé státy. Mezi EEQ naměřeným u jednotlivých skupin ČOV (městské ČOV lišící se velikostí, průmyslové ČOV a ČOV, ke kterým provozovatelé neposkytli žádné bližší informace) nebyl statisticky významný rozdíl (článek VI, capture Estrogenicity of different categories of WWTPs ). Největší ČOV přitom zpravidla čistily jak vody splaškové, tak průmyslové a dešťové, zatímco nejmenší čistírny upravovaly zejména vody splaškové Toxicita dioxinového typu Toxicita dioxinového typu byla potvrzena i u 21 z 25ti testovaných vzorků odtoků z ČOV v EU. Testované vzorky byly vybrány náhodně a byla u nich zjištěna poměrně konstantní hladina toxicity dioxinového typu. Hladiny TEQbio se lišily od <0,1 ng/l do 0,44 ng/l. Medián všech testovaných vzorků byl 0,15 ng/l TEQbio. 39

40 4.4. Výsledky mezinárodní interlaboratorní studie hodnotící různé biotesty z hlediska zjišťování zbytkového znečištění odpadních vod na ČOV, které recyklují odpadní vody na vody pitné (článek VI) Na výsledcích studie se podílelo 20 různých laboratoří (článek VI). Šedesát dva ze 103 biotestů, použitých pro hodnocení odstranění znečištění z různých vzorků čištěných nebo povrchových vod (viz kapitola 3.1. Vzorkované lokality ), zachytilo odpověď u alespoň jednoho z testovaných vzorků. Odpověď v kontrolním vzorku byla zachycena 4 biotesty, ale signál odpovědi kontrolního vzorku byl ve 3 případech v porovnání se signály ostatních vzorků velmi slabý a v jednom testu byla deklarována pravděpodobná chyba měření. U vzorků vod upravených odlišnými technologiemi čištění bylo možné sledovat různé bioanalytické profily. To znamená, že téměř všechny laboratoře konzistentně zaznamenaly pozitivní odpovědi určitých testů u určitých vzorků. Na příklad testy specifických typů toxicit byly velmi velmi často pozitivní u vzorků konvenčně čistěných odpadních vod (mechanický stupeň čištění + aktivovaný kal), zatímco pozitivní odpovědi testů oxidačního stresu se obvykle vyskytovaly u vod po úpravě na vodu pitnou (článek VI, Figure S10-S13). Celkově bylo nejvíce pozitivních odpovědí zachyceno u typu toxicity, která souvisí s metabolismem xenobiotik (pregnane X receptor a AhR), u testů vazby na hormonální receptory (zejména ER, antiandrogenní aktivita a GR), u testů genotoxicity a testů oxidativního stresu. Výsledky této interlaboratorní studie potvrdily vysokou validitu námi používaných in vitro testů, protože většina našich výsledků byla velmi dobře porovnatelná s výsledky podobných testů jiných laboratoří (článek VI, Table S5, Figure S5-S7). Pouze linie MDA-kb2 se zdá citlivější pro detekci androgenních látek než jiné metody, což je v souladu s našimi předchozími výsledky, kdy pomocí geneticky modifikovaných Sacharomyces cerevisiae nebylo možné tuto aktivitu detekovat, zatímco pomocí linie MDA-kb2 detekována byla (viz kapitola 5.5. Hladiny androgenního ekvivalentu naměřené v odpadních vodách ). Z hlediska další charakterizace ED potenciálu odpadních vod pomocí bioanalytických metod je třeba se blíže zaměřit také na 40

41 GR mechanismus působení, kterému se momentálně v centru RECETOX věnuje kolegyně Petra Macínová (Macikova et al. 2013). 41

42 5. Diskuse 5.1. Hladiny estrogenního ekvivalentu naměřené v povrchových vodách (článek I) Studie toků minimálně zatížených antropogenními vlivy je jednou z mála, kde byl hodnocen ED potenciál pozaďových lokalit. Dostatečně citlivý biotest tedy dokáže zachytit estrogenní potenciál i na místech minimálně ovlivněných člověkem. To potvrdili např. Matthiessen and Johnson (2007), kteří mimo jiné hodnotili estrogenní potenciál 6ti horních toků britských řek, kde jedinými známými zdroji antropogenního znečištění (pokud nebereme v úvahu látky obsažené ve srážkách) bylo několik osamocených domů s jímkami a septiky. I tito autoři používali POCIS a pomocí testu s reportérovým genem a genem pro estrogenní receptor vložených do kvasinkových buněk (Yeast Estrogen Screen) detekovali koncentrace po přepočtu na koncentrace ve vodě (s výjimkou jedné lokality s extrémně vysokou koncentrací) od méně než limit detekce (0.08 ng/l) po 1.4 ng/l s mediánem 0.3 ng/l. To jsou mírně vyšší, ale srovnatelné hodnoty, než jaké byly naměřeny v naší studii. Jinou studii s obdobnými výsledky provedli Nadzialek et al. (2010), kteří detekovali estrogenní potenciál 0,01 a 0,03 ng/l EEQ na 2 referenčních lokalitách v Belgii. Tento estrogenní potenciál je taktéž srovnatelný s hladinami detekovanými v naší studii, zvláště když uvážíme, že přepočet koncentrace v POCIS na koncentraci ve vodě je konzervativní a reprezentuje tak nejhorší možný scénář (článek I). Zvýšený estrogenní potenciál na všech 7 lokalitách pod obcemi oproti vzorkům odebraným nad obcemi ukazuje, že obce jsou zdrojem estrogenních látek. K podobným výsledkům dospěli např. Vermeirssen et al. (2005), kteří hodnotili švýcarské toky a na lokalitách označených za nejméně zatížené naměřili srovnatelné EEQ, jaké jsou publikovány v naší studii. Sellin et al. (2009) také naměřili zvýšené koncentrace estrogenních látek na lokalitách pod obcemi ve státě Nebraska, USA. Tito autoři stanovovali známé estrogenní látky analyticky a jejich estrogenní potenciál odvodili pomocí známých potencí v in vitro 42

43 testech. Takto odvozené EEQ označované obvykle jako ceeq ( Calculated EEQ ), činilo až 22,7 ng/pocis, což je podstatně více, než bylo naměřeno v naší studii. Nicméně takto vysoké ceeq bylo naměřeno/spočítáno pod lokalitou s ČOV, která měla technologii aktivovaného kalu vázaného na pevný materiál, který je známý nízkou účinností v odstranění estrogenů oproti technologii nádrží s aktivovaným kalem, jaká byla používána na všech lokalitách v naší studii (Svenson et al. 2003). Významu detekovaných koncentrací ED potenciálů z hlediska environmentálních rizik je věnována samostatná kapitola (5.8.) 5.2. Hladiny TCDD ekvivalentu naměřené v povrchových vodách (článek I) Negativní účinky zprostředkované AhR jako jsou neurotoxicita, karcinogeneze, imunotoxicita nebo reprodukční toxicita (Hilscherova et al. 2000) bývají připisovány hlavně účinkům nepolárních perzistentních agonistů AhR, jako jsou polychlorované dibenzo-p-dioxiny a furany a některé polychlorované bifenyly. Nicméně AhR může být aktivován i řadou méně perzistentních látek včetně některých polykondenzovaných aromatických uhlovodíků (Denison et al. 2004). Všechny zmíněné látky jsou hydrofobní povahy a toxicita dioxinového typu bývá proto sledována především v nepolárních matricích, jako jsou tkáně živočichů nebo pasivní vzorkovače typu SPMD. Nedávné studie však potvrdily určitý podíl toxicity dioxinového typu také ve vodné fázi odpadních vod (viz kapitola 5.6.) a nastolily tak otázku identifikace dalších dioxinově aktivních polutantů s nižší hydrofobicitou. Toxicita dioxinového typu byla v povrchových vodách hodnocena také v České republice v okolí města Brna (článek II). V extraktech z POCIS však tato aktivita byla detekována pouze ve vzorcích odpadní vody nebo v místě vzorkování několik desítek metrů od výpustě z ČOV, přičemž hladina TEQbio v řece pod touto výpustí byla mírně vyšší oproti hladinám naměřeným u málo zatížených toků pod obcemi. 43

44 5.3. Srovnání hladin ED potenciálů naměřených v povrchových vodách s analytickými výsledky (článek I) Pomocí analytických metod naměřené koncentrace pesticidů a farmak (článek I, Table 2, 4, 5) byly ve srovnání s jinými lokalitami velmi nízké obzvlášť ve vzorcích odebraných nad obcemi (např. Arditsoglou and Voutsa 2008, Söderström et al. 2009). Nicméně analýza ukázala zvýšené koncentrace některých farmak ve vzorcích odebraných pod obcemi a to jak v extraktech z POCIS Pharm, tak POCIS pest. Tento trend nebyl patrný u skupiny pesticidů, což odpovídá logické distribuci těchto dvou skupin látek. Zatímco farmaka jsou většinou používána v místech lidských sídel, pesticidy se dostávají do toků plošnými zdroji a obce tudíž nebývají jejich hlavními zdroji. Ze známých látek s ED účinky byly hodnoceny triazinové pesticidy, nicméně jejich koncentrace v řádech ng/l byly mnohonásobně nižší než ty, u kterých jsou známé negativní účinky (mg/l) na vodní organismy (Danzo 1997, Vonier et al. 1996) a jejich ceeq byl zanedbatelný. Za naměřený EEQ tudíž byly zodpovědné jiné než sledované látky Hladiny estrogenního ekvivalentu naměřené v odpadních vodách (článek II, III, IV) Naměřené hladiny EEQ, jak na přítoku a odtoku modelové ČOV, tak na odtocích z ČOV v rámci EU byly velmi dobře porovnatelné s dalšími většími studiemi provedenými v Evropě např. Korner et al. (2001) v Německu, Vethaak et al. (2005) v Holandsku, Aerni et al. (2004) ve Švýcarsku nebo Cargouet et al. (2004) ve Francii i v jiných vyspělých zemích na světě (Nakada et al. 2004, Leusch et al. 2005, Tan et al. 2007, článek II, Table 3). Po vynechání jedné odlehlé hodnoty (53 ng/l EEQ, kterou detekovali Aerni et al. (2004)), autoři všech jmenovaných evropských studií uvedli hladiny EEQ v odtocích z ČOV v rozsahu menší než limit detekce až 24 ng/l, což jsou hladiny velmi podobné těm detekovaným námi. 44

45 5.5. Hladiny androgenního ekvivalentu naměřené v odpadních vodách (článek II) Androgenní aktivita byla hodnocena pouze u 24 vzorků přítoku a odtoku z jedné ČOV v průběhu roku a byla detekována v rozmezí 23 až 193 ng/l AEQ u vzorků přítoků. U vzorků z odtoků detekována nebyla a detekční limity se lišily (v závislosti na cytotoxicitě konkrétních vzorků) od 1,3 až 3,7 ng/l AEQ. K podobným výsledkům (pod limitem detekce) dospěla i studie, ve které byly hodnoceny vzorky ze dvou ČOV upravující vodu až na vodu pitnou (článek VI). Ze sedmi různých použitých biotestů v článku VI, byl AEQ nad limitem detekce naměřen pouze pomocí testu s buněčnou linií MDA-kb2, která kromě agonistů AR detekuje také agonisty GR. Po potlačení agonistů AR pomocí flutamidu, však byla GR aktivita nízká, z čehož lze usoudit na větší podíl AR než GR aktivity. Maximální AEQ koncentrace byla detekovaná (pomocí MDAkb2) u vzorků konvečně čištěné odpodní vody a pohybovala se okolo 4 ng/l. Námi naměřené hodnoty AEQ pro extrakty odpadní vody na přítoku a hodnoty pod limitem detekce anebo v řádu jednotek ng/l pro extrakty odpadní vody na odtoku jsou také dobře porovnatelné s údaji ze zahraničních ČOV (Svenson and Allard 2004) Hladiny TCDD ekvivalentu naměřené v odpadních vodách (článek II, III) Jak již bylo řečeno, detekce toxicity dioxinového typu ve vzorcích vody byla provedena jen v několika pilotních studiích a hladiny TEQbio uváděné v zahraniční literatuře se poměrně liší. To je pravděpodobně dáno rozdílnou dobou expozice buněk v jednotlivých testech. Dagnino et al. (2010) pozorovali pokles dioxinové aktivity s prodloužením doby expozice a tito autoři také testovali vzorky v nejkratší době expozice 7 hodin. Doba expozice v našich testech byla, stejně jako u Reungoat et al. (2010) 24 hodin a naše výsledky jsou s výsledky této studie velmi podobné (Tabulka 5). 45

46 Tabulka 5: Toxicita dioxinového typu v odpadních vodách na odtoku z čistíren odpadních vod vyjádřená v ng/l TEQbio. Vzorek Citace Medián Min. Max. N t (h) ČR článek II 0,36 0,14 0,74 12* 24 (roční odběry) EU článek III 0,15 <0,1 0, Austrálie Reungoat et al. (2010) 0,31 0,26 0, Francie Dagnino et al. (2010) 17,1 2,1 43,7 3 8 Čína Ma et al. (2005) <0,01 <0,01 <0, N - počet lokalit, ze kterých byly vzorky odebrány t - doba expozice (h - hodiny) * jedná se o 12 vzorků odebraných v různých měsících v průběhu 1 roku na jediné ČOV 5.7. Srovnání hladin ED potenciálů naměřených v odpadních vodách s analytickými výsledky (článek II, III, IV) Naše studie nebyly primárně zaměřené na chemickou analýzu EDCs, které jsou obvykle považovány za zodpovědné za převážnou část naměřeného ED potenciálu nebo negativní účinky na vodní organismy (příloha VII), ale na kombinaci in vitro biotestů s analýzou méně prozkoumaných skupin látek jako jsou farmaka, látky denní spotřeby, nové polárnější pesticidy a podobně. Kombinace těchto metod jednoznačně poukázala na odpadní vody z ČOV jakožto zdroj farmak a látek denní spotřeby pro povrchové vody (článek I, II, III, IV), což je v souladu se závěry jiných zahraničních studií (např. Miege et al. 2009). Naopak koncentrace polycyklických aromatických uhlovodíků nebo organických halogenovaných látek, což jsou látky v odpadních vodách legislativně regulované, se vlivem ČOV (ani vlivem splachů z města Brna) nezvýšily (článek II). Ačkoliv ČOV v Brně Modřicích velmi efektivně odstraňovala estrogenní/androgenní potenciál i celkovou cytotoxicitu pro buňky, rezidua antibiotik, desinfekčních prostředků (triklosan) nebo dalších látek ze skupiny nových typů polutantů nebyly na českých a ani zahraničních ČOV odstraněny s tak vysokou účinností. Vzhledem k tomu, že stávající ČOV byly navrženy tak, aby odstraňovaly zejména patogeny a živiny, k odstranění 46

47 těchto nových skupin látek je třeba upravit současné technologie nebo přidat technologie nové (článek II). Tématu účinnosti odstraňování EDCs a jiných nových typů polutantů se věnuje autorčina rigorózní práce (Jedlickova 2010). Náklady na takovéto řešení jsou ale velmi vysoké a je proto třeba zvážit rizika spojená s výskytem těchto látek a dále možnosti omezení jiných zdrojů, ať už primárních (např. u spotřebitele) nebo sekundárních (např. zamezení úniku nečištěných odpadních vod). Výsledky analýz koncentrací 156 polárních organických látek v 90ti odtocích z evropských ČOV, včetně šesti českých ČOV, shrnuje článek III. Ačkoliv naměřené koncentrace některých skupin látek u těchto vzorků významně korelovaly mezi sebou (nejlépe humánní farmaka s umělými sladidly, článek IV, SI Table 3), žádná ze skupin zkoumaných látek (farmaka, látky denní spotřeby, veterinární antibiotika, perfluorované látky, organofosfátové zpomalovače hoření, polární pesticidy a některé jejich metabolity, protikorozivní látky (benzotriazoly), mošusové látky, siloxany, rentgenové kontrastní látky a Gadolinium) nekorelovala s naměřeným estrogenním potenciálem. Steroidní hormony, které jsou obvykle za naměřené EEQ z velké části zodpovědné (např. Sumpter and Johnson 2008), nebyly naměřeny nad limitem detekce, který byl 10 ng/l. To ukazuje na dobrou použitelnost in vitro testu, neboť díky němu byly detekovány hladiny EEQ, které mohou mít negativní vliv na vodní organismy Environmentální význam detekovaných hladin ED potenciálů (článek I, II, III, IV, V) In vitro biotesty měří určitou specifickou vlastnost látek přítomných ve směsích, jako je v našem případě aktivace/blokace příslušného receptoru a nepodávají informace o přímém vlivu na organismy, které tyto látky mohou navíc např. aktivně přijímat, specificky metabolizovat nebo vyloučit. Je proto obtížné stanovit míru rizika pro organismy jen na základě výsledků těchto testů. Látky, které budou přijímány nebo metabolizovány organismem odlišně než standardní látka, budou mít odlišný potenciál způsobovat odpověď v in vitro 47

48 testech a v živých organismech (in vivo). Čím podrobnější informace o látkách, které způsobují daný negativní účinek u živočichů, máme, tím přesněji můžeme odhadovat rizika s nimi spojená na základě výsledků in vitro testů. Pokud není známo, které látky se na negativních účincích podílejí, je možné pouze srovnat naměřený ED potenciál s nejnižšími účinnými koncentracemi známých EDCs, pokud jsou tyto informace pro danou matrici k dispozici Estrogenita (článek V) V současné době není v Evropě ani jinde ve světě stanovena žádná závazná norma limitující výši povolené estrogenní aktivity ve vodě. Evropská komise však nově zařadila steroidní estrogeny E2 a EE2 do seznamu látek, jejichž výskyt a účinky mají být sledovány. Tyto látky mohou být později zařazeny do seznamu prioritních látek, jejichž výskyt má být v rámci hodnocení chemického stavu vod při implementaci Rámcové směrnice o vodách monitorován a neměl by překračovat normy environmentální kvality (NEK). Navržené NEK byly odvozeny na základě výsledků multigeneračních studií hodnotící vliv E2 a EE2 na rozmnožování ryb, jakožto nejcitlivějšího ukazatele u nejcitlivějších organismů (Young 2004) a použitím standardních faktorů nejistoty. NEK pro E2 v povrchové vodě je pouhých 0,41 ng/l a pro EE2 dokonce 0,035 ng/l. Tato hodnota je v současné době v environmentálních matricích analyticky velmi obtížně stanovitelná. Z literární rešerše uvedené v článku V vyplývá, že steroidní estrogeny estron (E1), E2, estriol (E3), a EE2 jsou převážně zodpovědné za estrogenní aktivitu naměřenou pomocí in vitro testů ve vzorcích komunálních odpadních vod. Kromě toho jsou (E1), E2, a EE2 pravděpodobně zodpovědné za feminizaci samců ryb pod výpustmi z těchto ČOV, která byla pozorována po celém světě (článek V). Tyto 4 látky se v odtocích z komunálních ČOV používajících nádrže s aktivovaným kalem (nejběžnější typ ČOV v EU) vyskytují v určitých přibližně podobných poměrech. To je dáno jejich podobnými poměry na vstupech do ČOV (Anderson et al. 2012) a jejich osudem v ČOV. Caldwell et al. (2012) na základě údajů z dostupných testů na živých organismech stanovil koncentrace těchto steroidních estrogenů, které by neměly mít negativní vliv na 48

49 vodní organismy a stanovil tak tzv. PNEC (z anglického Predicted-No-Effect Concentration, článek IV, Table SI 2). Pomocí srovnání koncentrací způsobujících 50 % odpověď (EC50) jednotlivých steroidů vůči EC50 standardu E2 (článek IV), jsme odvodili pro námi používaný test potence jednotlivých steroidů způsobovat odpověď in vitro (dále jen in vitro potence s indexem příslušné látky). Z literatury jsme shromáždili údaje o komunálních odpadních vodách (odtoky z ČOV), ve kterých byly dříve pomocí analytických metod naměřené koncentrace E1, E2, E3 a EE2 a spočítali jsme procenta koncentrace těchto jednotlivých steroidů. Jako 100 % byl brán součet jejich koncentrací (článek V). Dále jsme vynásobili tato koncentrační procenta in vitro potencemi příslušných estrogenů a získali tak procenta celkového ceeq, kterými by se na něm E1, E2, E3 nebo EE2 podílely. V 51 různých odtocích z ČOV by se E1, E2, E3 a EE2 typicky (mediány) podílely na 21, 41, 4 a 17 % celkového ceeq (článek V, Table 2). Pokud by tedy např. E1 byl zodpovědný za 21 % celkového detekovaného EEQ, jaký by byl maximální EEQ, při kterém by nedošlo k překročení bezpečné koncentrace E1 ve vodě (PNEC E1 = 6 ng/l)? Odpověď jsme vypočítali podle vzorce 1: EEQ E1 = PNEC E1 x in vitro potence E1 / podíl E1 na ceeq (vzorec 1) EEQ E1 = 6 x 0,13 / 0,21 EEQ E1 =3,7 ng/l EEQ E1 - maximální bezpečný EEQ komunálních odpadních vod vzhledem k E1. Při vyšším EEQ než je EEQ E1 hrozí překročení bezpečné koncentrace E1 stanovené na základě výsledků testů s živými organismy. PNEC E1 - Bezpečná koncentrace E1 pro vodní organismy převzatá z Caldwell et al. (2012), stanoveno na základě testů s živými organismy. in vitro potence E1 - schopnost E1 indukovat odpověď v daném in vitro testu v porovnání se standardem E2 podíl E1 na ceeq - typický podíl E1 (medián ze všech hodnot) na celkovém ceeq odvozeném na základě výsledků analytických metod 49

50 Stejnou otázku jsme si položili pro E2, E3 a EE2 a výsledkem při použití obdoby vzorce 1 bylo: EEQ E2 =4,9 ng/l ; EEQ E3 =165 ng/l a EEQ EE2 =0,64 ng/l. Při nejnižším vypočítaném limitním EEQ (0,64 ng/l) naměřeným naším biotestem by tedy neměla být v typickém odtoku z ČOV překročena žádná z bezpečných hladin PNEC pro E1, E2, E3 ani EE2. Použité bezpečné hladiny PNEC byly odvozeny z dlouhodobých studií (delší než 60 dní). Při vzorkování, které má za cíl odhalit možná rizika, jsou však vzorky vody často odebírány v období nízkých stavů vod, který se zpravidla dříve než do 60ti dní zvýší a tím dojde i k naředění sledovaných látek. Pro tyto případy je proto možné ve výpočtech využít PNEC odvozené z krátkodobých studií (Anderson et al. 2012). Při jejich použití by PNEC žádného ze 4 estrogenů nebyl v typickém odtoku z komunální ČOV překročen do EEQ 3,2 ng/l. Při měření naším biotestem EEQ 0,64 ng/l tedy ukazuje obvyklou, z hlediska steroidních estrogenů, bezpečnou hladinu pro vodní organismy a to po celou dobu jejich životního cyklu. EEQ 3,2 ng/l pak ukazuje stejnou bezpečnou hladinu ale jen pro krátkodobou expozici. Kromě reálného odhadu je ale třeba vždy určit také relevantní nejhorší možný scénář. Ten je v našem případě tvořen stejným výpočtem jako vzorec 1, ale namísto obvyklých procent příspěvku jednotlivých steroidů k celkovému ceeq (mediány) je vzat jejich maximální příspěvek (článek V). Ten byl vypočítán jako 91, 93, 40 a 40 % pro E1, E2, E3 a EE2 (článek V, Table 2). Bezpečná hladina pro dlouhodobou expozici vodních organismů pak byla pro námi používný in vitro test 0,3 ng/l EEQ a bezpečná hladina pro krátkodobou (do 60 dní) expozici 1,3 ng/l EEQ. Tyto hladiny byly označené jako estrogenní limit (EL). Ve studii sedmi toků, které nebyly zatíženy téměř žádnými známými zdroji antropogenního znečištění, zjištěné hladiny EEQ nepřekročily estrogenní limit, avšak EEQ některých vzorků se blížilo jeho hranici pro dlouhodobou expozici. To je typická ukázka obtížné aplikovatelnosti EL pro toky, kde steroidní estrogeny pravděpodobně (vzhledem k minimálním zdrojům antropogenního znečištění) nebyly zodpovědné za detekované EEQ. Naopak velmi dobře 50

51 porovnatelné s EL mohou být výpusti z městských ČOV nebo zvýšení EEQ v řekách vlivem odpadních vod z obcí, které udává Tabulka 6. Na lokalitě s maximálním naměřeným EEQ v řece pod obcí (2,3 ng/l EEQ), který překročil nejen krátkodobý i dlouhodobý EL, ale také dlouhodobý limitní EEQ pro typický odtok z ČOV, byly potvrzeny zvýšené hladiny žloutkového proteinu vitellogeninu u samců pstruha obecného (Salmo trutta fario L.) oproti hladinám v rybách nad obcí a to více než krát (článek II). Hladiny EEQ naměřené v odpadní vodě v Brně Modřicích sice také většinou překračovaly dlouhodobý EL a v některých měsících i EL pro krátkodobou expozici, ale je třeba si uvědomit, že ryby nejsou exponovány odtokem z ČOV, ale říční vodu, tedy odtokem zředěným touto vodou. Ředící faktory se v Brně Modřicíh pohybují přibližně od 0,1 po 0,3 (maximálně 30 % říční vody je tvořeno odpadní vodou). Vezmeme-li v úvahu ředící faktor 0,3, pak by v řece pod ČOV byl dlouhodobý EL překročen ve 4 vzorcích z 12ti testovaných, ale jen ve 2 měsících po sobě a to v měsíci červnu a červenci (doba expozice může být delší než 60 dní). Tomu odpovídá i sledování sezonality, která ukázala letní období jako nejvíce rizikové. Krátkodobý EL by byl překročen pouze u jednoho vzorku (z měsíce října) a to pouze za předpokladu maximálního ředění odpadní vody vodou říční. Lze tedy usoudit, že existuje riziko, že v letních měsících za nízkých průtoků říční vody a vysokého podílu odpadní vody v řece, mohou být překročeny bezpečné hladiny steroidních estrogenů. Ve studii odpadních vod z EU bohužel nebyly dostupné ředící poměry a tak lze pouze porovnat naměřené EEQ odpadní vody a EL (Tabulka 6). Tabulka 6: Estrogenita v řekách pod obcemi nebo v odpadní vodě na odtoku z čistíren, vyjádřená jako estrogenní ekvivalent EEQ (ng/l) a estrogenní limit EL (ng/l EEQ). Vzorek Citace Medián Min. Max. N EL>60dní EL<60dní ČR řeky pod obcemi Článek I 0,5 <0,2 2,3 7 0,3 1,3 ČR odpadní voda Článek II 0,5 0,1 5,1 12* 0,3 1,3 (roční odběry) EU odpadní voda Článek III, IV <0,5 <0,5 17,9 59 0,3 1,3 * jedná se o 12 vzorků z jedné ČOV; N - počet vzorkovaných lokalit 51

52 Androgenita Ačkoliv případů negativních účinků androgenů v povrchových vodách je ve srovnání s účinky estrogenními méně, jsou známé případy maskulinizace ryb žijících ve vodách v blízkosti papírenských továren nebo chovů prasat, kde byly používány růstové hormony, zejména trenbolone acetát (Wilson 2003, Blankvoort et al. 2005). Zodpovědnými androgeny v blízkosti papíren se zdají být fytosteroly, přesněji jejich degradační produkty uvolněné během zpracování dřeva (Jenkins et al. 2001). Dosud nebyly pro androgenní aktivitu stanoveny žádné bezpečné hladiny těchto látek ani normy environmentální kvality. Hodnoty nejnižší naměřené efektivní koncentrace standardních androgenů (nejčastěji testosteronu nebo dihydrotestosteronu) pro ryby, jakožto předpokládané nejcitlivější vodní organismy, je udáván v řádech µg/l (Runnalls et al. 2010), což je mnohonásobně více, než bylo detekováno v našich studiích. Riziko negativních účinků vlivem androgenních látek v testovaných vodách by proto mělo být velmi nízké, což ale nemusí platit pro jiné typy lokalit v České republice, jako jsou např. místa pod papírnami Antiandrogenita Negativní působení antiandrogenních látek na živočichy z vodního prostředí bylo pozorováno např. v 80 letech minulého století na Floridě. Vlivem směsi mnoha průmyslových a zemědělských kontaminantů, z nichž jako nejvýznamnější příčina byl určen degradační produkt pesticidu DDT - antiandrogen p,p'-dde, došlo u aligátorů v jezeře Apopka k vývojovým poruchám pohlavních orgánů a následnému vymírání celé populace (Guillette et al. 1996). V nedávné době se britští výzkumníci zamysleli nad rozporem, proč zatímco u samců hlodavců a u člověka bývají poruchy reprodukce nejčastěji spojovány se směsí estrogenů a antiandrogenů, v případě feminizace samců ryb pod výpustmi z ČOV je hlavní příčina těchto účinků připisována pouze estrogenům (Jobling et al. 2009). Zmínění autoři vytvořili model různého působení látek odhadnutých nebo naměřených v 30 britských řekách a statisticky potvrdili, že pozorovaná feminizace ryb nejlépe odpovídala modelu působení směsi antiandrogenních a estrogenních látek (Jobling et al. 2009). K tomuto přístupu lze dodat i další argument, totiž, že u některých estrogenů jako 52

53 např. DDT nebo bisfenol A, byly prokázány zároveň antiandrogenní účinky (Sohoni and Sumpter 1998). Normy environmentální kvality ani bezpečné hladiny pro antiandrogenní aktivitu nebyly zatím stanoveny. Co se týká účinných hladin jednotlivých antiandrogenů, jejich minimální účinné koncentrace na ryby (nejcitlivější organismy (Runnalls et al. 2010)) se velmi liší i mezi antagonisty androgenního receptoru. Syntetický androgen flutamid, který se užívaná zejména při léčbě rakoviny prostaty, účinkuje na ryby až v koncentracích vyšších než desítky µg/l. Naproti tomu cyprosteron acetát, steroidní syntetická látka používaná také při léčbě rakoviny prostaty či jako hormonální léčba např. při nadměrném ochlupení žen, nutnosti snížení libida, nebo u některých transsexuálů, účinkuje na ryby již v koncentracích desítek ng/l. Momentálně v literatuře nejsou pro vodní živočichy dostupné žádné minimální účinné hladiny inhibitorů enzymů zodpovědných za genezi testosteronu nebo dihydrotestosteronu. Ačkoliv negativní účinky na vodní organismy vlivem čistě antiandrogenních látek běžně přítomných v odpadních nebo povrchových vodách se nezdají být pravděpodobné, nelze zatím vyloučit rizika spolupůsobení těchto látek např. s estrogeny Toxicita dioxinového typu Jak již bylo řečeno, údaje o dioxinové toxicitě vodných vzorků jsou pilotními údaji o tomto typu toxicity ve vodní fázi vzorků a pro zhodnocení environmentálních rizik je třeba dalšího výzkumu. 53

54 6. Shrnutí a závěr Ve studii toků málo zatížených antropogenními vlivy v České republice byla ve většině extraktů z pasivních vzorkovačů vzorkujících polární látky naměřena nízká hladina estrogenního potenciálu a toxicity dioxinového typu. Na stejných tocích pod prvními obcemi (obce byly vybaveny konvenčními ČOV), byla na všech 7 zkoumaných lokalitách naměřená 1 až 14krát vyšší estrogenita oproti vzorkům odebraných nad obcemi. Hladina toxicity dioxinového typu byla u vzorků odebraných pod obcemi vyšší jen na některých lokalitách. V extraktech nad i pod obcemi byly naměřené nízké hladiny polárních pesticidů a farmak ve srovnání s jinými studiemi a lokalitami, avšak koncentrace některých farmak pod obcemi byly zvýšené oproti hladinám nad obcemi. Z pohledu negativních účinků na vodní organismy se jako nejvíce rizikový jevil estrogenní potenciál. Účinnost městské ČOV odstraňovat anti/estrogenní, anti/androgenní a dioxinový potenciál byla hodnocena v extraktech ze vzorků odpadních vod odebraných na přítoku a na odtoku z ČOV v Brně Modřicích a to ve 12ti vzorcích z různých měsíců v roce. Zjištěná účinnost odstraňovat estrogenní a androgenní látky byla velmi vysoká (často nad 98 %), i přesto však mohly zbytkové hladiny estrogenních látek v letních měsících pro vodní organismy představovat reálné riziko. Antiestrogenní ani antiandrogenní potenciál vzorků detekován nebyl, avšak antiandrogenita mohla být překryta obecnou cytotoxicitou extraktů. Toxicita dioxinového typu byla potvrzena v obou typech vzorků a účinnost v odstranění těchto látek v průběhu roku značně kolísala. Instrumentální analýza více než 150 polárních organických látek v odtocích z evropských ČOV, kterou prováděly různé laboratořč pod záštitou Evropské komise, byla doplněna o detekci estrogenního potenciálu těchto odtoků a u vybraných odtoků také o stanovení toxicity dioxinového typu. Naměřený estrogenní potenciál se dobře shodoval s dosavadními výsledky jiných větších evropských studií. Ve 21 z 25ti testovaných extraktů vody na odtocích z evropských ČOV byla navíc potvrzena toxicita dioxinovéto typu. Studie představuje nejkomplexnější soubor dat o polárních organických polutantech a 54

55 estrogenní aktivitě v evropských ČOV a demonstruje vhodnost kombinace analytických a biologických metod. Díky rozsáhlé literární rešerši o známých estrogenních látkách působících in vitro a in vivo, osudu těchto látek v ČOV a dále citlivosti vodních organismů vůči nim, byl vytvořen odhad hladin maximálního EEQ specifického pro daný biotest, při kterém by neměla být překročena bezpečná koncentrace steroidních estrogenů ve vodě. V případě, že můžeme považovat tyto látky za zodpovědné za negativní účinky na organismy, je možné toto EEQ použít pro odhad environmentálních rizik na základě výsledků in vitro testů. Použitelnost 103 různých biotestů pro hodnocení kvality recyklované vody (odpadní a povrchové vody jsou recyklovány na vodu pitnou) byla hodnocena ve studii koordinované zahraničními institucemi. Asi polovina biotestů zachytila odpověď u alespoň jednoho typu vzorku. Pozitivní odpovědi biotestů přitom dávaly konzistentní obraz o určitém typu toxicity (např. některé vzorky vykazovaly odpovědi v různých biotestech vypovídajících o oxidativním stresu, jiné v biotestech specifických účinků). Všechny námi používané testy byly dostatečně citlivé, aby zachytily odpověď alespoň u některých typů testovaných vzorků a podaly konzistentní a s výsledky ostatních testů dobře porovnatelné odpovědi. Námi použité bitesty hodnotící specifické účinky jsou citlivými, rychlými a relativně levnými nástroji k hodnocení ED potenciálů v environmentálních vodách. Lze díky nim především sledovat zdroje těchto látek a monitorvat jejich hladiny. Na druhou stranu extrakční metody, přesné postupy měření a vyhodnocení zatím nebyly u naprosté většiny testů standardizovány a vyžadují v tomto směru mezinárodní spolupráci. 55

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61 Wilson EM. Biological function and mode of action of the androgen receptor. Pure and Applied Chemistry 75: ; Young WF, Whitehouse, P., Johnson, I. and Sorokin, N. Proposed Predicted- No-Effect-Concentrations (PNECs) for Natural and Synthetic Steroid Oestrogens in Surface Waters. Environment Agency; Zlabek V, Randak T, Kolarova J, Svobodova Z, Hajslova J, Suchan P. Monitoring of endocrine disruption in chub (Leuciscus cephalus L.) population from the Vltava river. Toxicology and Applied Pharmacology 197: 256;

62 Přílohy I. Článek I II. Článek II III. Článek III IV. Článek IV V. Článek V VI. Článek VI VII. Tabulka VII VIII. Curriculum Vitae 62

63 Článek I Příloha I

64 Environment International 45 (2012) Contents lists available at SciVerse ScienceDirect Environment International journal homepage: Changes in concentrations of hydrophilic organic contaminants and of endocrine-disrupting potential downstream of small communities located adjacent to headwaters B. Jarosova a, L. Blaha a, B. Vrana a, T. Randak b, R. Grabic b, J.P. Giesy c,d,e,f,g, K. Hilscherova a, a Research Centre for Toxic Compounds in the Environment (RECETOX), Faculty of Science, Masaryk University, Kamenice 126/3, 62500, Brno, Czech Republic b University of South Bohemia in Ceske Budejovice, Faculty of Fisheries and Protection of Waters, South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses, Zatisi 728/II, Vodnany, Czech Republic c Department of Biomedical Veterinary Sciences and Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada d Zoology Dept. and Center for Integrative Toxicology, Michigan State University, East Lansing, MI 48824, USA e Department of Biology and Chemistry, City University of Hong Kong, Hong Kong SAR, PR China f Zoology Department, College of Science, King Saud University, P. O. Box 2455, Riyadh 11451, Saudi Arabia g Environmental Science Program, Nanjing University, Nanjing, PR China article info abstract Article history: Received 7 January 2012 Accepted 4 April 2012 Available online xxxx Keywords: Androgen Dioxin-like activity Estrogen In vitro assay POCIS Waste Water Treatment Plant Endocrine-disruptive potential and concentrations of polar organic contaminants were measured in seven headwaters flowing through relatively unpolluted areas of the Czech Republic. Towns with Wastewater Treatment Plant (WWTP) discharges were the first known sources of anthropogenic pollution in the areas. River water was sampled several kilometers upstream (US) and several tens of meters downstream (DS) of the WWTP discharges, by use of Pesticide and Pharmaceutical Polar Organic Integrative Samplers (POCIS- Pest, POCIS-Pharm). Extracts of passive samplers were tested by use of a battery of in vitro bioassays to determine overall non-specific cytotoxicity, endocrine-disruptive (ED) potential and dioxin-like toxicity. The extracts were also used for quantification of polar organics. There was little toxicity to cells caused by most extracts of POCIS. Estrogenicity was detected in all types of samples even though US locations are considered to be background. At US locations, concentrations of estrogen equivalents (EEq) ranged from less than the detection limits (LOD) to 0.5 ng EEq/POCIS. Downstream concentrations of EEqs ranged from less than LOD to 4.8 ng EEq/POCIS. Concentrations of EEq in POCIS extracts from all DS locations were 1 to 14 times greater than those at US locations. Concentrations of EEq measured in extracts of POCIS-Pest and POCIS-Pharm were in a good agreement. Neither antiestrogenic nor anti/androgenic activities were detected. Concentrations of 2,3,7,8-TCDD equivalents (TEqbio) were detected in both types of POCIS at concentrations ranging from less than the LOD to 0.39 ng TEqbio/POCIS. Nearly all extracts of POCIS-Pharm contained greater concentrations of TEqbio activity than extracts of POCIS-Pest. Concentrations of pesticides and pharmaceuticals in extracts of POCIS were generally small at all sampling sites, but levels of some pharmaceuticals were significantly greater in both types of POCIS from DS locations. Chemical analyses along with the results of bioassays documented impacts of small towns with WWTPs on headwaters Elsevier Ltd. All rights reserved. Abbreviations: AEq, androgenic equivalent; AhR, Aryl hydrocarbon receptor; DS, downstream;e1, estrone; E2, 17β-estradiol;E3,Estriol;EC, effective concentration;ed, endocrine disruption; EDCs, endocrine disruptive compounds; EE2, 17α-ethynylestradiol; EEq, estrogenic equivalent; HpOCs, hydrophilic organic compounds; K ow, octanol water partition coefficient; LOD, limit of detection; LOQ, limit of quantification; NR, Neutral Red; PCBs, polychlorinated biphenyls; PCDDs, polychlorinated dibenzodioxins; PCDFs, polychlorinated dibenzofurans; PNEC, Predicted No Effects Concentration; POCIS, Polar Organic Chemical Integrative Sampler; POCIS-Pest, Polar Organic Chemical Integrative Sampler optimized for polar Pesticides; POCIS-Pharm, Polar Organic Chemical Integrative Sampler optimized for most Pharmaceuticals; Rs, sampling rate (L/day); TEqbio, dioxin-like equivalent obtained in bioassay; TCDD, 2,3,7,8-tetrachlorodibenzo-p-dioxin; US, upstream; WWTP, Waste Water Treatment Plant. Corresponding author. address: hilscherova@recetox.muni.cz (K. Hilscherova). 1. Introduction Municipal and industrial waste waters can be sources of compounds that are able to cause acute toxicity as well as sublethal chronic abnormalities including disruption of hormonal balance in aquatic organisms (endocrine disruption, ED). Persistent and bioaccumulative organic chemicals have been conventionally monitored, but less persistent and less hydrophobic organic compounds are currently used as pesticides, prescription and non-prescription drugs and personal care products. Despite their lesser bioconcentration potential, relatively large fluxes of some of these compounds into aquatic systems might be acutely toxic and/or induce sublethal chronic abnormalities (Alvarez /$ see front matter 2012 Elsevier Ltd. All rights reserved. doi: /j.envint

65 B. Jarosova et al. / Environment International 45 (2012) et al., 2007). Furthermore, some of these chemicals (particularly pharmaceuticals) can be highly potent, such that even concentrations at or near analytical detection limits may have biological activity. Concentrations and/or ecotoxicological effects of hydrophilic organic compounds (HpOCs, contain one or more polar functional groups or a significant molecular dipole moment) have been reported in discharges of Waste Water Treatment Plants (WWTP) and/or downstream receiving waters (Aguayo et al., 2004; Bolong et al., 2009; Caliman and Gavrilescu, 2009). Downstream reaches of rivers have been shown to be polluted by compounds of both industrial and communal origin (Bolonget al., 2009), and therefore it is difficult to evaluate contributions and effects of pollutants released by individual towns. There are fewer sources of HpOC pollution in the headwaters and their potential impacts are not easy to assess, since there is limited information on concentrations of pollutants in the background areas. Although different groups of HpOCs can contribute to adverse effects, xenoestrogens and xenoandrogens have emerged as environmental issues due to their ability to mimic or otherwise adversely affect functions of natural reproductive hormones, which could result in impaired reproduction of aquatic organisms (Matthiessen and Johnson, 2007). Even though the efficiencies of conventional WWTPs with activated sludge systems to remove estrogenic and androgenic compounds seem to be relatively high (88 >99% for estrogens and 96 >99% for androgens (Korner et al., 2000; Leusch et al., 2010; Murk et al., 2002; Svenson and Allard, 2004), concentrations of these endocrine disruptive compounds (EDCs) in some effluents are sufficient to cause ED (Kirk et al., 2002). Since some EDCs can cause adverse effects at small concentrations (ng/l), it is difficult and expensive to detect them by instrumental analyses (Korner et al., 2000). Moreover, because they occur in mixtures, even if they can be quantified, it is difficult to predict the potential effects of these compounds (Leusch et al., 2005). Therefore, in vitro bioassays can serve as cheaper and more environmentally relevant alternative to screen for the combined effects of mixtures on specific biological endpoints (Kinnberg, 2003). The most frequently reported effect connected with EDs in surface waters is feminization of male fish downstream of WWTPs (Jobling and Tyler, 2003). Among estrogenic EDCs, the steroidal estrogens estrone (E1), estradiol (E2), and synthetic estrogen analogue, ethinyl estradiol (EE2), are some of the most potent endocrine disruptors in sewage effluents, all having more than thousand times greater potency to cause ED, at least in fish, than most other xenobiotics (Young et al., 2004). Under environmental conditions, steroidal hormones have been identified to be primarily responsible for observed adverse estrogenic effects on fish downstream of WWTPs although other weakly estrogenic compounds, such as alkylphenols and bisphenol A, can contribute to the effects (Desbrow et al., 1998; Gross-Sorokin et al., 2006). Important is also the fact that effluents from WWTPs can contain antiandrogenic chemicals as well. Their presence has been suggested by previous studies as a potential complication in establishing the chemical causation of fish sexual disruption (Tyler and Jobling, 2008). Efforts to identify the contributing antiandrogens are now underway, using a targeted fractionation process combined with screening by recombinant yeast assay and high-quality analytical chemistry. It should also be mentioned that certain compounds may act as both estrogens and antiandrogens (e.g. Suzuki et al., 2005). There are two different approaches of sampling water, either active or passive. We chose to use passive integrative sampling, rather than traditional grab or composite sampling, for two reasons: i) passive sampling permits determination of time-weighted average concentrations of HpOCs in water, which is especially important when concentrations of HpOCs fluctuate over time because of changes in weather or variable diurnal patterns of consumption of products which are primary sources of HpOCs and, ii) the most potent EDCs usually occur at small concentrations (ng/l) and passive integrative samplers serve as an effective alternative to collecting and handling large volumes of water (Alvarez et al., 2007). One useful passive sampler for HpOCs is the Polar Organic Chemical Integrative Sampler (POCIS). Relatively good correlations have been observed between concentrations of estrogenic equivalent (EEq) determined in bioassays for POCIS and grab water samples (Arditsoglou and Voutsa, 2008; Vermeirssen et al., 2005). POCIS has been shown to sample a wide variety of polar as well as moderate hydrophobic organic compounds with log K ow of less than 4. Two types of adsorbents are considered standard for deployment of POCIS in the field. One of the two standard configurations, POCIS-Pest, preferentially concentrates waterborne HpOCs such as polar pesticides, natural and synthetic hormones, and other wastewater-related contaminants. The other, POCIS-Pharm, incorporates a sorbent optimal for sequestering polar pharmaceuticals (Alvarez et al., 2007). Both types of POCIS exhibited linear uptake of phenolic and steroid compounds during 28-day tests conducted in laboratory during which concentrations of analytes in water were held constant. The correlation coefficients of the linear regression with respect to timescale were greater than for POCIS-Pest and for POCIS- Pharm, which suggests that uptake was time-integrative and the rate of uptake was not time-dependent during the exposure period. Moreover, rates of sampling (R s ) were not affected by changes in concentrations of tested compounds (Arditsoglou and Voutsa, 2008; Matthiessen and Johnson, 2007). In the present study, water quality in terms of HpOCs and EDCs was studied in several headwaters in the Czech Republic. A combination of instrumental analyses of individual chemicals and in vitro assays with extracts from POCIS-Pest and POCIS-Pharm was conducted to: i) determine background levels of anti/estrogenic, anti/androgenic and dioxinlike activities in headwater streams upstream of known sources of anthropogenic pollution, and ii) evaluate the impacts of small towns and their WWTP discharges on concentrations of mixtures of EDCs in rivers. 2. Methods 2.1. Collection of samples One POCIS-Pest and one POCIS-Pharm (Exposmeter AB, Sweden) sampler were deployed at each location. Study locations were upstream and downstream of seven municipal WWTPs, which were situated on small rivers and streams in relatively unpolluted areas of the Czech Republic (Fig. 1). Upstream (US) POCIS were placed from 2 to 5 km upstream of WWTPs in highland forest areas with minimal anthropogenic impact, while downstream (DS) sites were within 150 to 250 m of WWTP effluents. The towns studied, Králíky, Jilemnice, Cvikov, Tachov, Volary, Vimperk and Prachatice, are the upstream- N W E S Fig. 1. Locationofthesamplingsiteson smallriversintheczechrepublic: 1 RiverTichá Orlice near town Králíky; 2 Stream Roudnický potok (upstream) and Jizerka river (downstream) near town Jilemnice; 3 Stream Boberský potok near town Cvikov; 4 RiverMže neartown Tachov; 5 River Volyňkaneartown Vimperk; 6 StreamVolarský potok near town Volary; 7 Stream Živný potok near town Prachatice. 1

66 24 B. Jarosova et al. / Environment International 45 (2012) most sources of anthropogenic pollution on the assessed rivers/ streams. These rivers/streams have natural or seminatural habitats flowing mostly through woodlands but there are agricultural fields or pastures in close proximity (0.2 3 km) to most of the towns. All WWTPs applied mechanical biological treatment with activated sludge and Cvikov WWTP had an additional stabilizing pond (1.4 ha). All locations were sampled in June 2008, except for Prachatice, which was sampled in January Duration of deployment of samplers was 2 to 3 weeks. Duration of deployment should be within the linear uptake period for most HpOCs. Characteristics of WWTPs and river/stream conditions are summarized (Table 1) Extraction of POCIS After collection of POCIS, all samples (entire POCIS) were stored at 18 C until analysis. The exposed POCIS was disassembled; the sorbent was transferred to the glass gravity flow chromatographic column with glass wool plug and analytes were eluted by the appropriate solvent mixture. Methanol was used as the eluent for POCIS- Pharm and a mixture of dichlormethane: methanol: toluene (8:1:1) was used for POCIS-Pest. The eluate was then evaporated to a small volume, the solvent was changed to methanol and the sample volume was adjusted to 2 ml for chemical analyses. Hexane, dichloromethane, acetone, toluene (all in Suprasolv purity), water and methanol (Hypergrade for LC/MS) were purchased from Merck (Darmstadt, Germany). The aliquots of extracts were further concentrated four-fold under a gentle stream of nitrogen to decrease the LOD for in vitro assays. The process blank samples were prepared following sample preparation procedure of both POCIS types and they were analyzed together with the other samples Bioassays Four individual bioassays were used to determine overall cytotoxicity, anti/estrogenicity, anti/androgenicity and dioxin-like potencies of extracts of POCIS-Pest and POCIS-Pharm samplers. The reporter gene assays employed mammalian cell lines MVLN and H4IIE-luc and two types of recombinant Saccharomyces cerevisiae. MVLN are human breast carcinoma cells stably transfected with luciferase gene under the control of estrogen receptor, which were used for the assessment of cytotoxicity and anti/estrogenicity. Cytotoxicity of the samples was also investigated by recombinant strain of S. cerevisiae which expresses genes for enzyme luciferase under standard conditions (Leskinen et al., 2005). The potency of POCIS extracts to modulate androgen receptor-mediated responses was examined by use of recombinant S. cerevisiae that were modified to express human androgen receptor along with firefly luciferase under transcriptional control of androgen-responsive element (Michelini et al., 2005). H4IIE-luc are rat hepato-carcinoma cells stably transfected with the luciferase gene under control of Aryl hydrocarbon receptor (AhR) and they were used for the assessment of dioxin-like activity (Sanderson et al., 1996). At least two independent experiments were conducted in each bioassay for each exposure variant. All dilutions of POCIS extracts or controls were tested at least in triplicate. Cytotoxicity of the samples can bias the results of the bioassays, therefore viability of cells was assessed several ways: Viability of MVLN cells was determined by use of the Neutral Red (NR) test where the NR dye is incorporated in the lysosomes of living cells and the uptake of NR is proportional to the number of viable cells. For cytotoxicity testing by NR-test, MVLN cells were seeded at a density of cells/well in 96-well microplate ViewPlates (Packard, Meriden, CT, USA) and incubated for 24 h at 37 C under atmosphere enriched with 5% CO 2. During this period cells were grown in DMEM- F12 without phenol red (Sigma Aldrich, USA) containing 10% foetal calf serum previously treated with dextran-coated charcoal to reduce concentrations of natural steroids in the serum. After 24 h, cells were exposed to dilutions of extracts from POCIS and solvent control (methanol, 0.5% v/v). Cytotoxicity was determined after 24 h of exposure, when NR (Sigma-Aldrich, Czech Republic) was added to the exposure medium in microplates to make a final concentration of 0.5 mg/ml. Cells were then incubated for 1 h at 37 C. Afterwards, the cells were washed twice with phosphate buffered saline and lysed in the presence of acetic acid ethanol solution (25:25:0.5; ethanol:water:acetic acid) for 15 min on a shaker. Finally, NR uptake was determined spectrophotometrically (Power Wave, BioTek, USA) at 570 nm. Absorbance was related to the response of the solvent control and the percentage of cytotoxicity of each sample dilution (viability of the cells exposed to the sample dilution relative to viability of cells exposed to solvent control (considered as 100%)) was determined. For the other way of assessing the viability, the recombinant strain of S. cerevisiae which expresses genes for enzyme luciferase under standard conditions (Leskinen et al., 2005) was used. In the presence of cytotoxic substances in the medium, luminescent light, produced normally by interaction between luciferase and added substrate luciferin, is less. When reaching a linear phase of growth, yeast were seeded into 96-well culture ViewPlates (Packard, Meriden, CT, USA) and exposed to vehicle, dilutions of POCIS extracts or to medium alone. Yeast cells were incubated for 2.5 h at 30 C and then the signal was detected after addition of D-luciferin substrate. Detected luminescence was used to express the percentage of cytotoxicity caused by each sample dilution, as determined by the viability of the cells exposed to sample dilution relative to viability of cells exposed to solvent control, which was assigned a value of 100%. Exposure for the determination of the anti/estrogenic potency of extracts in MVLN cells was conducted the same way as for the NR cytotoxicity evaluation described above with the following difference: cells were exposed to dilutions of POCIS extracts, calibration of the reference estrogen E2 (dilution series M E2, Sigma- Aldrich, Czech Republic) and solvent control (methanol, 0.5% v/v). After 24 h of exposure, the intensity of luminescence was measured Table 1 Description of sampling sites, river parameters and sampling dates and duration. Site no. Name of town Inhabitants no. Name of recipient river(stream) Effluent % a River Q355 [m 3 /s] River flow velocity [m/s] Sampling duration [day] Date of sampling b 1 Králíky 4800 Tichá Orlice 20% May 11 June 2 Jilemnice 6000 Roudnický potok 5% (US) May 11 June (US)/Jizerka (DS) c 0.02 (DS) 3 Cvikov 1900 Boberský potok 10% May 11 June 4 Tachov Mže 15% May 12 June 5 Vimperk 7650 Volyňka 4% May 12 June 6 Volary 4000 Volarský potok 5% May 12 June 7 Prachatice Živný potok 30% /16 d 7/14 d 30 January a Average contribution of WWTP effluent to the recipient. b All samples were taken in c US = upstream site, DS = downstream site. d US POCIS-Pest and both DS POCISes have been exposed for 23 days while US POCIS-Pharm for 16 days.

67 B. Jarosova et al. / Environment International 45 (2012) using Promega Steady Glo Kit (Promega, Mannheim, Germany). After subtraction of the response of the solvent control, luminescence in the estrogenicity assay was related to the maximal response of standard ligand (E2max for estrogenicity) and converted to percentages of E2max. Maximal induction as well as the shape of the curve differed among samples, thus equal efficacy or parallelism of the dose response curves could not be assumed (Villeneuve et al., 2000). To avoid any predictions beyond the measured responses with all samples and to estimate the estrogenic equivalents (EEq) in the samples (expressed in ng E2/ POCIS) the EEq 20 estimate based on the 20% E2max response was reported, since most of the active samples did not reach the 50% E2max. EEq 20 values were based on relating the amount of E2 causing 20% of the E2max response (EC 20 ) to the amount of sample causing the same response determined from regression analysis (equivalent of amount of E2 per amount of sample). The EC values were calculated by nonlinear logarithmic regression of dose response curve of calibration standard and samples in Graph Pad Prism (GraphPad Software, San Diego, USA). The anti/estrogenicity was assessed by simultaneous exposure of the sample extract and 17β-estradiol (33 pm E2). Duration of sampling varied from 16 to 23 days at different locations. Based on the evidence from previous research that uptake of phenolic as well as steroidal estrogens is linear in terms of time and concentration up to at least 28 days (Alvarez et al., 2007; Arditsoglou and Voutsa, 2008), we present our results normalized to 20 days of deployment along with the primary data in Table 3. The normalization was performed to simplify the comparability of our results among different locations and also with other studies in discussion. The data are presented both these ways to demonstrate the possible influence of the somewhat different deployment periods of the samplers on the results and their interpretation. Concentrations of EEq in water were estimated by use of the sampling rate of E2 (0.09 L/day) previously determined by Matthiessen and Johnson (2007). It is important to stress, that these recalculated values represent approximate estimates of EEq concentrations in water and the values should not be considered as definite concentrations. This estimation will be further discussed in detail. Concentrations of EEq in water were calculated (Eq. (1)). C w ¼ C POCIS =R s t where: C w is the estimated concentration of EEq in water (ng/l), C POCIS are concentrations of EEq in extracts from POCIS (ng/pocis; primary not normalized values), R s is sampling rate (L/day) of E2 previously determined by Matthiessen and Johnson (2007) and t is the sampling period (days). As it was mentioned, anti/androgenity of POCIS extracts was determined by use of recombinant strain of S. cerevisiae. Plating and dosing were the same as for determination cytotoxicity of sample extracts in another strain of S. cerevisiae described above, but in this case, yeast cells were exposed not only to POCIS extracts and controls of pure medium and vehicle but also to dilutions of standard (testosterone in a range from to 10 6 M, Sigma-Aldrich, Czech Republic). The H4IIE-luc model was used for analysis of dioxin-like activity of the samples (Sanderson et al., 1996). Cells were seeded at a density of per well in 96-well microplate ViewPlates (Packard, Meriden, CT, USA) and incubated for 24 h under 5% CO 2 at 37 C, in DMEM-F12 medium with phenol red (Sigma Aldrich, USA) containing 10% foetal calf serum. After 24 h, cells were exposed to the reference compound 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD, with a dilution series of M, Ultra Scientific, USA), or dilutions of POCIS extracts and solvent control (methanol, 0.5% v/v). After 24 h of exposure, the intensity of luminescence was measured using Promega Steady Glo Kit (Promega, Mannheim, Germany). Results from the H4IIE-luc in vitro assay were analyzed by the same approach as described for the determination of the EEq above. Presented TEq bio are expressed in ng of TCDD per POCIS. TEq bio values were based on EC 20 values because most samples did not reach greater EC responses. For each bioassay the limit of detection was determined as the lowest observable effect concentration of standard chemical divided by the greatest non-cytotoxic extract concentration expressed as POCIS equivalent. ð1þ Table 2 List of pesticides and pharmaceuticals analyzed in extracts from both POCIS-Pest and POCIS-Pharm and list of perfluorinated organic compounds analyzed in extracts from POCIS- Pest. Pharmaceuticals Pesticides Perfluorinated organics Carbamazepine 2,4,5-T MCPA Perfluoro-1-hexanesulfonate Cephalexin 2,4-D MCPP_MECOPROP 2H-perfluoro-2-octenoic acid Ciprofloxacin Acetochlor Metalaxyl Perfluoro-1-octanesulfonamide Diaveridine Alachlor Metamitron N-methylperfluoro-1-octanesulfonamide Diclofenac Atrazine Methabenzthiazuron Perfluorooctanoic acid Enrofloxacin Atrazine desethyl Methamidophos Perfluorooctane sulfonic acid Erythromycin Azoxystrobin Methidathion Perfluorononanoic acid Metronidazole Bentazone Metobromuron Norfloxacin Bromacil Metolachlor Ofloxacin Carbofuran Metoxuron Sulfachloropyridazine Cyanazine Metribuzin Sulfamethazine Desmetryn Monolinuron Sulfamethoxazole Diazinon Nicosulfuron Sulfamethoxypyridazine Dichlobenil Phorate Sulfapyridine Dichlorprop Phosalone Trimethoprim Dimethoate Phosphamidon Diuron Prometryn Fenarimol Propiconazole Fenhexamid Propyzamide Fipronil Pyridate Fluazifop-p-butyl Rimsulfuron Hexazinone Simazine Chlorbromuron Tebuconazole Chlorotoluron Terbuthylazine Imazethapyr Terbutryn Isoproturon Thifensulfuron-methyl Kresoxim-methyl Thiophanate-methyl Linuron Tri-allate

68 26 B. Jarosova et al. / Environment International 45 (2012) LC/MS/MS analyses Chemicals such as natrium sulfate, silicagel, methanol etc. were purchased from Merck (Darmstadt, Germany). 13 C labeled and native perfluorinated compounds were purchased from Wellington Laboratories. 13 C labeled Simazine, Sulfamethoxazol, 2.4D and Ciprofloxacin were purchased from Cambridge Isotope Laboratories. Native compounds were purchased from Dr. Ehrenstorfer, AccuStandards and Absolute Standards. All of the standards were purchased from Labicom ltd. (Olomouc, Czech Republic). A list of analyzed compounds is given in Table 2. A cocktail of internal standards was spiked into each POCIS extract (100 μl of the standard mixture in water was added to 100 μl of POCIS extract). Chemicals were identified and quantified by use of LC/MS/MS. Analyses were performed using three different LC/MS/ MS methods. Chemicals in POCIS extracts were quantified by use of internal standards. A subsample (20 μl for pesticide and 10 μl for pharmaceuticals) was injected onto an analytical column (Phenomenex C18 Aqua, 2 mm 50 mm, 5 μm particles). The HTS PAL (CTC) autosampler, Rheos2000 (Flux) quaternary pump and TSQ Quantum AccessTM (ThermoScientific, USA) triple quadrupole tandem mass spectrometer were used for analyses of polar pesticides, pharmaceuticals and perfluorinated compounds. Two MS/MS transitions were monitored (where possible) for native analytes to confirm identity. An agreement of results obtained from both transitions better than 30% was accepted as a confirmed result. Isotope dilution and internal standard methods were used for the quantification of target compounds. Quantification limits (LOQs) of analytes were calculated the same way as concentration but peak area corresponding to instrument LOQ was used instead of peak area found in sample. Thus, LOQs are adjusted to internal standards. Most detected compounds have been shown to be in the linear uptake phase for at least 23 days (the maximal deployment period in our study) (Alvarez et al., 2007). Thus, we present concentrations of those compounds normalized to 20 days of deployment to enable more precise interpretation of our results across different locations and also better comparability with other studies in discussion Statistical analysis Due to violations of the assumptions of parametric statistical testing, differences between results of the two applied cytotoxicity detection systems as well as between potencies of POCIS-Pest and POCIS- Pharm extracts to induce nonspecific cytotoxicity and act through specific modes of action were evaluated by nonparametric Wilcoxon Matched Pairs test. The same test was applied to assess differences between concentrations of pollutants detected in POCIS-Pest and Pharm extracts. The nonparametric Spearman rank correlation was used to assess the similarity of the potential of POCIS-Pest and Pharm extracts to act through specific modes of action. All statistical analyses were performed with Statistica for Windows 9.0 (StatSoft, Tulsa, OK, USA), the tests were considered significant at pb Results There was no response above detection limits observed for blanks in any of the bioassays. The limits of detection in blanks were 0.06 ng EEq/POCIS for estrogenity, 1.29 ng AEq/POCIS for androgenity and 0.03 ng TEqbio/POCIS for dioxin-like activity Cytotoxicity Most tested concentrations of POCIS extract equivalents ( % 0.25% POCIS/mL) were not cytotoxic to yeast or to MVLN cells. At the greatest tested POCIS extract equivalent concentration 0.5% POCIS extract/ml samples from some locations caused cytotoxicity of as much as 50% (Fig. 2). For both types of POCIS the cytotoxic effects were comparable or greater at DS locations than at US locations with a single exception where the POCIS- Pharm extract at location 5 exhibited greater cytotoxicity at the US location (Fig. 2B). However, the greater cytotoxicity observed DS of WWTPs compared to US was statistically significant only for extracts of POCIS-Pest measured by yeast test. In all other cases, including all extracts of POCIS-Pharm in both bioassays and POCIS-Pest in MVLN cells, the magnitude of differences in cytotoxicity was not statistically significant between US and DS. Although the yeast test was significantly more sensitive to cytotoxicity of POCIS- Pharm extracts (p=0.009) than the MVLN test, the results of the two tests were comparable among POCIS extracts, with no significant difference between the results of the two tests with extracts of POCIS-Pest (p=0.79). The yeast test was also significantly more sensitive to POCIS-Pharm extracts than POCIS-Pest extracts (p=0.01), whereas there was no statistically significant difference between cytotoxicity of extracts of the two types of samplers in the MVLN test Anti/estrogenicity Estrogenicity was detected in extracts of both types of POCIS and differences were observed between US and DS locations. No extract showed significant antiestrogenic activity (data not shown). Although samples from DS locations were more estrogenic than those from US locations at all sites, some EEq was detected also in most US samples (Table 3). Because uptake of the more potent and also some less potent estrogens has previously been demonstrated to be time integrative for more than 25 days (e.g. Arditsoglou and Voutsa, 2008), here estrogenic potentials detected in extracts of POCIS are reported also as normalized to 20 days of POCIS deployment. However, differences between data obtained before and after the normalization to 20 days of POCIS deployment were negligible (Table 3). Concentrations of EEq greater than the LOD (0.1 to 0.6 ng/pocis) were observed in four out of seven US locations in both types of POCIS. The variation among LOD is caused by slightly different cytotoxicity of extracts. Detected concentrations of EEq in US samples ranged from 0.3 to 0.5 ng/pocis20 days in POCIS-Pest as well as in POCIS- Pharm extracts. Since there were no known anthropogenic impacts near US sites, the detected EEq concentrations can be considered as background. Estrogenic equivalents in extracts from DS samples were greater than the LOD at all sites with the single exception of the POCIS-Pest extract at site 2. Concentrations ranged from 0.7 to 4.0 ng/pocis 20 days for POCIS-Pest and from 0.5 to 4.2 ng/pocis 20 days for POCIS-Pharm extracts. The greatest concentrations of EEq were observed at DS locations at sites 3 and 7 (Table 3). At site 3 DS samples contained more than 10-fold greater concentration of EEq than the US sample in the case of POCIS-Pest and more than 14-fold greater concentration of EEq than the US POCIS-Pharm. At site 7 DS samples contained more than 7-fold greater concentrations of EEQ than the US sample from POCIS-Pest and more than 5-fold greater concentration than the US sample from POCIS-Pharm, respectively. Estrogenic potential of water was estimated (Eq. (1)). For US localities sampled by both types of POCIS the calculated water EEq concentrations detected above LOD varied from 0.1 to 0.3 ng/l. Estimated estrogenic potential in water in DS locations sampled by POCIS-Pest ranged from less than 0.4 to 2.2 ng EEq/L and for those sampled by POCIS- Pharm from 0.3 to 2.3 ng EEq/L (Table 3). There were statistically significant correlations between estrogenic potentials of the pesticide and pharmaceutical POCIS extracts (Spearman rank 0.79, N=7, LOD values were replaced by value of 1/2 LOD), despite the discrepancy at the DS location at site 6. At DS location at site 6, repeated evaluation of estrogenic potential confirmed the difference of estrogenicity in extract of POCIS-Pharm compared to POCIS-Pest. The likeness of estrogenicity in extracts of POCIS-Pest and Pharm was also confirmed by nonparametric Wilcoxon Matched Pairs test, which indicated no significant difference between POCIS-Pest and Pharm (p=0.81) Anti/androgenicity There was no significant androgenic activity in any extract in the test with recombinant yeast assay (data not shown). Detection limit was 1.29 ng AEq/POCIS. None of the extracts has shown antiandrogenic activity (data not shown) Dioxin-like activity Dioxin-like activity was detected in most extracts. At US locations sampled by POCIS-Pest, concentrations exceeded the detection limit of 0.03 ng TEqbio/POCIS in only two cases whereas extracts from the POCIS-Pharm sampler deployed at the same locations had detectable concentrations at six out of seven sites (Fig. 3). Concentrations of TEq bio at US locations ranged from less than the LOD to 0.08 and to 0.22 ng TEq bio/pocis for extracts of POCIS-Pest and POCIS-Pharm, respectively. DS sites mostly showed greater concentrations of TEqbio in extracts from POCIS-Pharm than from POCIS-Pest. Extracts from DS POCIS-Pest contained concentrations of TEqbio that ranged from less than LOD of 0.08 to 0.26 ng TEq bio/pocis and from 0.08 to 0.39 ng TEq bio/pocis in extracts of POCIS-Pharm. When considering all samples together, significantly greater concentrations of TEq bio were observed in extracts of POCIS-Pharm than extracts of POCIS-Pest (WilcoxonMatchedPairstest; P=0.0029). Nevertheless, similarpatternsof greaterconcentrations of TEq bio at DS locations with similar orders of magnitudes were observed in extracts of both types of POCIS. At most sites, concentrations of TEqbio were greater DS of WWTPs (Fig. 3). Concentrations TEqbio in extracts of DS POCIS-Pest at sites 4 and 7 were greater than those inextracts of POCIS-Pest from US, by 1.4- and 4.9-fold, respectively. Concentrations of TEq bio in extracts of POCIS-Pharm at sites 1, 2 and 5 were approximately equivalent

69 B. Jarosova et al. / Environment International 45 (2012) Fig. 2. Cytotoxicity of extracts (concentration of 0.5% POCIS/mL) from upstream (US) and downstream (DS) measured by the yeast screen (A) and by Neutral Red test with MVLN cells (B). Error bars show standard deviations. For samples without any cytotoxic effect, no values are presented. for US and DS locations, whereas they were about 3-fold greater at the DS location of sites 3 and 4 and at least about 5-fold greater at the DS location at sites 6 and Chemical analyses Although most of the selected chemicals that were monitored were not detected in extracts at concentrations greater than the LOQ (0.1 to 14 ng/pocis), concentrations of several pharmaceuticals were greater at DS relative to US locations (Table 4). The greatest concentrations of pharmaceuticals were observed at the DS location of site 7. Pharmaceuticals found most frequently and also at the greatest concentrations were carbamazepine and diclofenac. Concentrations of carbamazepine ranged from less than the detection limit (2 8 ng/pocis) to 9 ng/pocis20 days in extracts from US locations and from 13 to 339 ng/pocis20 days in extracts from DS locations. The concentrations of diclofenac ranged from less than the LOQ (2 8 ng/pocis) to 31 ng/pocis 20 days in extracts from US locations and from 18 to 409 ng/pocis 20 days in extracts from DS locations. Concentrations in extracts of POCIS-Pest and POCIS-Pharm were comparable with a few exceptions, such as sulfapyridine at sites 3 and 4. Except pharmaceuticals presented in Table 4, a few other compounds ofloxacin, norfloxacin, ciprofloxacin and erythromycin were detected above the detection limits (LOQ ng/pocis), all detected concentrations were lower than 100 ng/pocis 20 days. Concentrations of most pesticides that were monitored were less than the LOQ ( ng/pocis). Most pesticides, which were quantifiable, were triazines, and their concentrations were generally small (b100 ng/pocis20 days). Concentrations of all detected triazines, including atrazine, atrazine desethyl, hexazinone, simazine and terbuthylazine are summarized in Table 5. Besides triazines, acetochlor at a concentration of 1375 ng/pocis 20 days was detected in one isolated POCIS-Pest sample from US location of site 2. Beside the pharmaceuticals and pesticides, perfluorinated organic compounds (listed in Table 2) were also monitored in extracts of POCIS-Pest. However, concentrations greater than the LOQ of ng/pocis were observed only in a few cases Table 3 Estrogenic activities in POCIS-Pest and POCIS-Pharm extracts measured by MVLN in vitro assay expressed as ng EEq/POCIS, normalized to sampling period of 20 days and recalculated (according to Eq. (1)) to approximate EEq water concentrations. Site no. US/DS a POCIS depl. b (day) EEq in POCIS extracts (ng/pocis) EEq in POCIS extracts normalized to 20 days of POCIS deployment (ng/pocis20 days) Estimated EEq in water derived from E2 R s c and EEq of POCIS extract (ng/l) POCIS Pest POCIS Pharm POCIS Pest POCIS Pharm POCIS Pest POCIS Pharm 1 US ±0.01 b b b0.1 DS 1.0± ± US 16 b0.3 b0.3 b0.4 b0.4 b0.2 b0.2 DS b ±0.6 b b US ± ± DS 4.2± ± US ± ± DS 0.9± ± US ± ± DS 0.9± ± US 21 b0.3 b0.3 b0.3 b0.3 b0.2 b0.2 DS 0.7± ± US 23/16 d b0.6 b0.6 b0.5 b0.8 b0.3 b0.4 DS 4.5± ± a US = upstream site, DS = downstream site. b Duration of POCIS deployment. c R s = sampling rate. d US POCIS-Pest and both DS POCISes have been exposed for 23 days while US POCIS-Pharm for 16 days.

70 28 B. Jarosova et al. / Environment International 45 (2012) Fig. 3. Dioxin-like activity of upstream (US) and downstream (DS) POCIS-Pest and POCIS-Pharm extracts determined by H4IIE-luc in vitro assay. White columns indicate TEq bio concentrations less than our detection limit (0.03 ng/pocis); error bars show standard deviations. and were less than 5 ng/pocis with single exception of perfluorooctane sulfonic acid, which was detected at DS location 2 at concentration 36 ng/pocis. 4. Discussion Most previous studies assessing ED contamination of rivers focused on the influence of urbanized areas and larger WWTPs (Kinnberg, 2003), but there is less information on the impact of smaller sources on headwaters where better quality of water would be expected. Our study brings important information on the background levels of ED and HpOCs compounds and the influence of smaller towns without major industrial activities on headwaters pollution. Seven small rivers or streams were sampled by use of POCIS-Pest and POCIS-Pharm passive samplers US and DS of the most upstream sources of anthropogenic pollution, which were small towns with WWTP discharges. Sampling rates for most compounds, which were investigated by use of POCIS in turbulent conditions, have been reported to range from 0.12 to 0.26 L/day (95%centile of published R s ; Alvarez et al., 2007; Arditsoglou and Voutsa, 2008; Harman et al., 2008; Macleod et al., 2007; Mazzella et al., 2007). This means that in 16 days, which is the minimal time of deployment of POCIS in the study, the results of which are reported here, the amount of the chemicals present in POCIS would be equivalent to L of river water ( L/ day 16 days). Thus, the least concentration causing cytotoxic effect 0.5% POCIS/mL, would represent 9.6- to 20.8-fold concentrated river water. Therefore our results suggest little overall cytotoxicity of river water and weak impact of WWTPs onto this unspecific toxicity. The results of the two systems used to detect cytotoxicity, yeast and mammalian cells, were similar with the exception of greater cytotoxicity of extracts of POCIS-Pharm in the yeast cells. This observation indicates greater sensitivity of the yeast model toward some chemicals that are more concentrated by POCIS-Pharm. Chemical analyses of POCIS-Pest and Pharm extracts did not reveal any significant differences in concentrations of monitored pollutants. However, it has been suggested that some pharmaceuticals have multiple functional groups, which have a tendency to strongly bind to the carbonaceous component of the triphasic adsorbent mixture contained in POCIS- Pest, which results in poor solvent extraction recoveries of some members of this class of compounds during sample processing (Alvarez et al., 2007). Our results demonstrating weak cytotoxicity correspond to another study of Alvarez et al. (2008), who used Microtox assay to evaluate toxicity of POCIS from surface waters burdened by extensive agriculture. In that study, no extract from passive samplers (POCIS, SPMD) exposed for 29 to 65 days displayed acute toxicity. Although the study, the results of which are reported here, was conducted in relatively unpolluted areas, some estrogenic activity was detected even at US locations (Table 3). Authors of some other studies had referred to detect concentrations of EEq in reference rivers. Nadzialek et al. (2010), who used active sampling and MCF-7 assay, found EEq concentrations at both tested reference sites in Belgium to be 0.01 and 0.03 ng/l. These concentrations are comparable with those estimated in our study (b ng EEq/L) especially if we consider our recalculated results as the worst case scenario. In contrast, Sellin et al. (2009), who used POCIS-Pharm and chemical analyses of their Table 4 Results of the LC/MS/MS analyses pharmaceuticals with greatest detected concentrations in extracts from POCIS-Pest and POCIS-Pharm (ng/pocis 20 days). Results are normalized to sampling period of 20 days. Site no. US/ DS a Sulfapyridine Sulfamethoxazole Trimethoprim Carbamazepine Diclofenac POCIS Pest POCIS Pharm POCIS Pest POCIS Pharm POCIS Pest POCIS Pharm POCIS Pest POCIS Pharm POCIS Pest POCIS Pharm 1 US DS US DS US DS US DS US DS US DS US DS less than LOQ ( ng/pocis). a US = upstream site, DS = downstream site.

71 B. Jarosova et al. / Environment International 45 (2012) Table 5 Results of the LC/MS/MS analyses - concentrations of triazines (ng/pocis 20 days), which were the most frequently detected pesticides at tested sites. Results are normalized to sampling period of 20 days. Site no. US/ DS a Atrazine Atrazine desethyl Hexazinone Simazine Terbuthylazine POCIS Pest POCIS Pharm POCIS Pest POCIS Pharm POCIS Pest POCIS Pharm POCIS Pest POCIS Pharm POCIS Pest POCIS Pharm 1 US DS US DS US DS US DS US DS US DS US DS less than LOQ ( ng/pocis). a US = upstream site, DS = downstream site. extracts to monitor estrogens in rivers of Nebraska, reported calculated EEq concentrations above detection limit (1 ng/pocis 7 days )in2outof 3 reference sites and the concentrations (1.9 and 1.5 ng/pocis 7 days ) were at least one order of magnitude greater than those found in our study. MatthiessenandJohnson (2007)evaluated, among others, estrogenic potential of 6 British headwaters with only few sources of estrogenic contamination (isolated houses with septic tanks). They used POCIS, which was previously calibrated in a laboratory study and yeast estrogen screen assay to evaluate estrogenic potential of the POCIS extracts. Their EEq concentrations ranged from less than the LOD (0.08 ng/l) to 1.4 ng/l with a median of 0.3 ng/l (except of 1 site with extremely great EEq value), which are slightly greater but comparable results to ours. Greater estrogenic potential DS of WWTPs compared to US was detected at all sampled sites (Table 3). Comparable results were obtained by Vermeirssen et al. (2005), who monitored estrogens in POCIS Pest and Pharm extracts deployed US and DS of 5 municipal WWTPs in Switzerland. Four out of the five rivers were, according to earlier DS samples analyses, chosen as moderate to greatly estrogenic whereas one river as less estrogenic. The concentrations of EEq at the least burdened site were very similar to those obtained in our study (0.4 ng EEq/POCIS 22 days in extracts of both types of POCIS placed US and ng EEq/POCIS 22 days in extract of POCIS-Pest and ng EEq/POCIS 22 days of POCIS-Pharm situated DS of the WWTP). In contrast, the river with the greatest estrogenic pollution contained more than 20 ng EEq/POCIS 22 days in both POCIS extracts of US samples and comparable EEq concentrations in DS ones. Similar to our results most DS samples displayed increase of estrogenic activity compared to US ones. Greater concentrations of estrogens in all POCIS samplers deployed DS of municipal WWTPs of smaller towns compared to US sites were also found in Nebraska (Sellin et al., 2009). Those authors determined estrogenic equivalents analytically (based on known potential of steroidal estrogens to cause the effect) and the recalculated EEq concentrations were greater (up to 22.7 ng/pocis 7 days ) than those detected by bioassays in our study. However, the greatest EEq concentrations were detected DS of WWTP with trickling filters technology which had been previously proved to be less effective in estrogens removal than activated sludge systems (Svenson et al., 2003) such as those inall WWTPs in our study. Concentrations of EEq in POCIS extracts were converted to approximate concentrations of EEq in water by use of sampling rate of E2 because: i) in numerous studies steroidal estrogens have been identified to be responsible for most (often more than 90%) of estrogenic activity detected by in vitro assays in municipal waste waters effluents (e.g. Korner et al., 2001; Routledge et al., 1998) ii) compared to E1, Estriol (E3) and EE2, E2 has the least R s (Arditsoglou and Voutsa, 2008), which enabled to estimate the worst case scenario (the greatest concentration) and iii) E2 is the standard reference compound used for EEq calculations. For estimating concentrations of EEq in water, R s for E2 previously established for the same standardized POCIS configuration as used in our study was applied in calculation (0.09 L/day; Matthiessen and Johnson, 2007). From the rates of sampling for E2 given in the literature (Arditsoglou and Voutsa, 2008; Matthiessen and Johnson, 2007), the R s calibrated at 10 C was used because the temperature was similar to the conditions in the studied streams and rivers and the application of the lowest R s value resulted in the worst case scenario estimate. Furthermore, application of the E2 sampling rate calibrated at 23.5±0.5 C by Arditsoglou and Voutsa (2008) would result in a range b0.1 to 1.8 ng/l EEq, which is similar to the currently presented results (Table 3). Rate of sampling can vary under different environmental conditions (e.g. diverse water flow rates, ph or temperature) but all the stations (with exception of location 7) were sampled at the same time eliminating thus at least partially variability. Moreover, the flow rates were always greater than 0.02 m/s and it has been demonstrated that under turbulent conditions sampling rates do not dramatically change as a function of flow velocity (Li et al., 2010). Another line of evidence, which supports the approach of EEq calculation applied in the study, is direct comparison of POCIS with grab samples as reported by Vermeirssen et al. (2005). Those authors measured estrogenic activity in both extracts of POCIS and grab samples and concentrations of EEq in extracts of POCIS were approximately 3-fold greater than the average concentrations of EEq in grab samples. These findings indicated the rate of sampling for estrogenic compounds is approximately 0.14 L/day. This experimentally established R s is consistent with the results observed in this study where it was assumed that use of R s for E2 could serve as an approximation to estimate concentrations of EEq in water and that these recalculated results represent a realistic estimate of the worst case scenario. Even though the most estrogenic extracts came from POCIS exposed DS of Prachatice town (site 7), which has the most inhabitants and the largest proportion of WWTP effluent in relation to the recipient river (Table 1), these two parameters did not correlate with the estrogenic potentials in POCIS extracts from other sites. Other forces, for example different primary sources of estrogens or different WWTP capacity or technology, probably influenced the EEq concentrations in DS samples. Estrogenic activity detected in extracts of POCIS-Pest or POCIS-Pharm was similar, this observation is consistent with previous field as well as calibration studies (Arditsoglou and Voutsa, 2008; Vermeirssen et al., 2005).

72 30 B. Jarosova et al. / Environment International 45 (2012) Although dioxin-like compounds are usually investigated in less polar matrices such as SPMD or sediments, some recent studies (Dagnino et al., 2010; Reungoat et al., 2010) affirmed this activity also in water phase. In this study, dioxin-like activity was detected in both types of POCIS ( ng TEq bio /POCIS), even at several US locations. Sampling rates for known AhR active compounds and kinetic of their sampling has not been reported for POCIS yet. Therefore our results cannot be recalculated to water concentrations nor to unified number of days of their deployment. Dioxin-like activity has been traditionally connected with hydrophobic compounds such as polychlorinated dibenzodioxins (PCDDs), polychlorinated dibenzofurans (PCDFs) or polychlorinated biphenyls (PCBs). Since experimentallydetermined values for log K ow range from 6.1 to 8.2 for PCDD and PCDF congeners (Chrostowski and Foster, 1996) and from 4.66 up to 7.44 for PCB congeners, respectively (Zhou et al., 2005), these compounds are not expected to be sampled by POCIS. Our results suggest that less hydrophobic compounds like PAHs, which are also known to bind to AhR, or some unknown compounds might represent non-negligible part of dioxin-like activities in aquatic environment and this issue desires further research. In this study concentrations of TEq bio in extracts of POCIS-Pharm were approximately 2-fold greater than those in extracts of POCIS- Pest. Up to authors' knowledge, no other comparisons of concentrations of TEq bio in extracts of POCIS-Pest and POCIS-Pharm have been published. However, since the same sorbent mass and membrane were used for both types of POCIS, it seems that different affinity of dioxin-like compounds to the POCIS-Pest vs. POCIS-Pharm sorbent might be responsible for the observed difference. Another reason could be the efficiency of extraction methods. However, the most potent and traditionally studied dioxin-like pollutants are hydrophobic substances and POCIS-Pest was extracted by less polar solvent than POCIS-Pharm. Even though in vitro assays revealed some specific potencies of mixtures that might cause effects to the aquatic biota, chemical analyses of a wide range of compounds (Table 2) did not show significant contamination. The greatest effects were observed in estrogenic activity screening assay. However, steroidal estrogens, which have been shown to be responsible for most of the estrogen equivalents in waste waters (Desbrow et al., 1998), were not monitored in this study. Among detected chemicals, some triazines are known to be able to disturb endocrine system of organisms (Danzo, 1997; Vonier et al., 1996). In this study, triazines were detected at concentrations from less than 0.1 to 1875 ng/pocis 20 days (Table 5) and their previously published sampling rates varied from 0.12 to 0.26 L/day (Alvarez et al., 2007; Mazzella et al., 2007). Estimated concentrations of triazines in water ranged from less than 0.02 ng/l to 781 ng/l, but these compounds are known to be effective at concentrations greater than mg/l (Danzo, 1997; Vonier et al., 1996) and thus their contribution to the responses detected by the in vitro systems can be considered negligible. Concentrations of all monitored chemicals were small compared to the results of other studies (Arditsoglou and Voutsa, 2008; Soderstrom et al., 2009), which was in good agreement with our intention to sample relatively unpolluted areas. Despite the small concentrations of studied contaminants there were obviously increased concentrations of pharmaceuticals in DS samples. This was not so remarkable in case of pesticides. The reason of greater differences of pharmaceuticals concentrations in US and DS extract than pesticides might be the fact that pharmaceuticals are used only in human quarters or farms whereas pesticides are used also in areas distant from towns. When considering the environmental significance of our results, some of the detected estrogenic equivalents concentrations had been reported to cause adverse effects. Authors of most studies, who observed estrogenic adverse effects on aquatic biota, reported EEq concentrations or corresponding concentrations of estrogens higher than those detected in our study (e.g. Sellin et al., 2009; Vermeirssen et al., 2005; Young et al., 2004). However, for example, Vethaak et al. (2005) found elevated levels of yolk protein vitellogenin in male bream (Abramis brama) in river with EEq levels determined by in vitro ER- CALUX assay as low as 0.17 ng/l. In that study, steroidal hormones were identified as the main contributors to the EEq (Vethaak et al., 2005). To authors' knowledge, the only estrogen, for which LOEC concentrations lower than 0.5 ng/l in vivo has been reported, was EE2 (Young et al., 2004). For example, Zha et al. (2008) demonstrated that the reproduction of the F-1 minnows was completely inhibited at EE2 concentration as low as 0.2 ng/l in a multigeneration study with Chinese rare minnows (Gobiocypris rarus). In our study, the upstream locations (with estimated EEqs b ng/l) were chosen as background sites without any grasslands or human settlements near the catchments and therefore we do not expect steroidal estrogens, particularly the synthetic EE2, to be responsible for the detected EEq. Contrariwise, at downstream locations with estimated EEq b ng/l, where municipal waste water effluents were considered as the main sources of estrogens, the presence of highly potent steroidal estrogens would be expected. The relative potency of any estrogens to E2 can differ for in vitro and in vivo studies (e.g. Johnson and Sumpter, 2001). The greatest difference has been reported for EE2. In the in vitro assay that we used (MVLN) the estrogenic potency of EE2 relative to E2 is 1.25 whereas in in vivo studies concerning production of yolk protein vitellogenin or alteration of ovarian somatic index in fish it has been reported to be approximately (Gutendorf and Westendorf, 2001; Young et al., 2004). This indicates that the overall estrogenic equivalents for in vivo situation might be even greater that those derived from in vitro tests. As far as the authors know, there are no studies available on potential in vivo adverse effects in similar locations as examined in our study. Therefore it is not possible to reliably estimate the environmental significance of detected EEq yet. The levels of vitellogenin in brown trout (Salmo trutta fario L.) from US and DS Prachatice (corresponding to our location 7) were investigated in September 2007 by researchers from Faculty of Fisheries and Protection of Waters, University of South Bohemia. There were significantly increased levels of vitellogenin in male brown trout captured downstream compared to the upstream site. The number of examined fish males was 6 at each US and DS location. The median plasma concentration were bellow detection limit of 10 ng/ml in male fish from upstream site and 3035 μg/ml in those from downstream site (Zlabek, personal communication). This corresponds with the results of our study, where the estrogenic activity was bellow detection limit in POCIS exposed upstream of Prachatice, while there were the greatest EEq among all sites in our study detected in POCIS from the Prachatice downstream site (2.3 ng/l). Thus, the increased EEq values from in vitro studies might indicate potential in vivo effects. Generally, the relevance of in vitro determined estrogenic equivalents for in vivo situation is a very important issue, which requires further research and which is also in focus of our further studies. 5. Conclusion The study brought new information about concentrations of polar organic contaminants and endocrine-disruptive potential in relatively unpolluted rivers and about the influence of smaller towns on this type of contamination in affected headwaters. There was an obvious impact on all sites despite the fact that the towns are equipped with municipal WWTPs with advanced activated sludge systems of treatment. Increased exposure potential of estrogenic and dioxin-like compounds (determined by in vitro assays) downstream of the towns were demonstrated. Some of the detected estrogenic equivalents concentrations had been reported to cause adverse effects. The study also demonstrated the suitability of passive sampling combined with chemical analyses and in vitro bioassays to reveal these impacts.

73 B. Jarosova et al. / Environment International 45 (2012) Acknowledgments This study has been supported by the projectsof Ministry of Education C.R. (ENVISCREEN no. 2B08036 and INCHEMBIOL MSM ), by the project CETOCOEN (CZ.1.05/2.1.00/ ) from the European Regional Development Fund, CENAKVA (CZ.1.05/2.1.00/ ) and the project SP/2e7/229/07 (Ministry of Environment C.R.). The research was also supported by a Discovery Grant from the Natural Science and Engineering Research Council of Canada (project # ) and a grant from the Western Economic Diversification Canada (project # 6578 and 6807). The authors wish to acknowledge the support of an instrumentation grant from the Canada Foundation for Infrastructure. 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75 Článek II Příloha II

76 Environment International 59 (2013) Contents lists available at SciVerse ScienceDirect Environment International journal homepage: Estrogen-, androgen- and aryl hydrocarbon receptor mediated activities in passive and composite samples from municipal waste and surface waters V. Jálová a, B. Jarošová a, L. Bláha a, J.P. Giesy b,c,d,e,f, T. Ocelka g, R. Grabic h, J. Jurčíková g, B. Vrana a, K. Hilscherová a, a Research Centre for Toxic Compounds in the Environment (RECETOX), Masaryk University, Kamenice 753/5, , Brno, Czech Republic b Dept. of Biomedical Veterinary Sciences and Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada c State Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing, , PR China d Department of Zoology, Center for Integrative Toxicology, Michigan State University, East Lansing, MI, USA e School of Biological Sciences, University of Hong Kong, Hong Kong, China f Department of Biology and Chemistry, State Key Laboratory for Marine Pollution, City University of Hong Kong, Hong Kong, China g Institute of Public Health Ostrava, National Reference Laboratory for POPs, Ostrava, Czech Republic h University of South Bohemia in Ceske Budejovice, Faculty of Fisheries and Protection of Waters, South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses, Zatisi 728/II, Vodnany, Czech Republic article info abstract Article history: Received 1 January 2013 Accepted 30 June 2013 Available online xxxx Keywords: Estrogenic Androgenic Cytotoxicity Bioassay in vitro Passive sampling Dioxin-like Passive and composite sampling in combination with in vitro bioassays and identification and quantification of individual chemicals were applied to characterize pollution by compounds with several specific modes of action in urban area in the basin of two rivers, with 400,000 inhabitants and a variety of industrial activities. Two types of passive samplers, semipermeable membrane devices (SPMD) for hydrophobic contaminants and polar organic chemical integrative samplers (POCIS) for polar compounds such as pesticides and pharmaceuticals, were used to sample wastewater treatment plant (WWTP) influent and effluent as well as rivers upstream and downstream of the urban complex and the WWTP. Compounds with endocrine disruptive potency were detected in river water and WWTP influent and effluent. Year-round, monthly assessment of waste waters by bioassays documented estrogenic, androgenic and dioxin-like potency as well as cytotoxicity in influent waters ofthe WWTPand allowed characterization ofseasonalvariability of these biologicalpotentials in waste waters. The WWTP effectively removed cytotoxic compounds, xenoestrogens and xenoandrogens. There was significant variability in treatment efficiency of dioxin-like potency. The study indicates that the WWTP, despite its up-to-date technology, can contribute endocrine disrupting compounds to the river. Riverine samples exhibited dioxin-like, antiestrogenic and antiandrogenic potencies. The study design enabled characterization of effects of the urban complex and the WWTP on the river. Concentrations of PAHs and contaminants and specific biological potencies sampled by POCIS decreased as a function of distance from the city Elsevier Ltd. All rights reserved. 1. Introduction There is increasing evidence that environmental contaminants have the potential to disrupt endocrine processes. This might result in adverse effects on reproduction, cause certain cancers, and other toxicities related to (sexual) differentiation, growth, and development (Giesy et al., 2000; Miles-Richardson et al., 1999; Sanderson and van den Berg, 2003; Snyder et al., 2000). A variety of pollutants that are found in surface and waste waters, such as organochlorine pesticides (OCPs), polychlorinated biphenyls (PCBs), polychlorinated dioxins and furans (PCDD/Fs), polycyclic aromatic hydrocarbons (PAHs), alkylphenols, synthetic steroids, pesticides, pharmaceuticals and personal care products (PPCPs), but also natural products such Corresponding author. Tel.: ; fax: address: hilscherova@recetox.muni.cz (K. Hilscherová). as phytoestrogens, have been shown to elicit endocrine disruptive effects. Sources of endocrine disrupting compounds (EDCs) are associated with larger urbanized and industrial areas. However, influences of smaller local sources can also be significant, especially where dilution is minimal (Jarosova et al., 2012). EDCs are also released to aquatic environments from both municipal and various industrial waste waters (Garcia-Reyero et al., 2004). Relative contributions of EDCs to surface waters depend on efficacies of sewage treatment systems, which is dependent on both capacity and technology of the wastewater treatment plant (WWTP). Potential risks of adverse effects of effluents from WWTPs to aquatic environments are influenced by volume of effluent, discharge of the receiving river, weather conditions and probably other factors that affect dissipation through dilution and/or degradation (Sumpter, 1995). Wastewater treatment plants receive mixtures of molecules from domestic, agricultural, and/or industrial wastes and /$ see front matter 2013 Elsevier Ltd. All rights reserved.

77 V. Jálová et al. / Environment International 59 (2013) thus waste waters can contain mixtures of many of the above listed pollutants and their degradation products (Alvarez et al., 2005). Despite intensive removal of xenobiotics by municipal WWTPs, which can range from 88 to N99% and 96 to N99% for xenoestrogens and xenoandrogens, respectively (Korner et al., 2000; Leusch et al., 2010; Murk et al., 2002; Svenson and Allard, 2004), they often do not remove all chemicals from the effluent. Moreover, during treatment some contaminants can be deconjugated to their more biologically active forms (Desbrow et al., 1998). Thus, most effluents still contain complex mixtures of molecules, including transformation products formed during treatment. Adverse effects on endocrine function and/or reproductive health associated with exposure to effluents from WWTPs, which can persist several kilometers from the point of effluent entry (Harries et al., 1996), have been demonstrated in wild fish populations (Jobling et al., 1998) or fishes caged downstream from WWTPs (Snyder et al., 2004). Several studies combining the use of chemical analyses and in vitro assays have revealed steroid estrogens as the most potent endocrine disruptors in WWTP effluents with thresholds for adverse effects of a few ng/l (Korner et al., 2000; Matsui et al., 2000; Nakada et al., 2004; Routledge et al., 1998; Snyder et al., 2000). However, other EDCs can be effective in various landuse conditions (Sole et al., 2000) and special consideration should be paid to mixtures of pollutants. Also, more information is needed to assess the potential contribution from other sources than just the WWTPs. Selection of an appropriate sampling approach is crucial to determining the presence of contaminants and assessment of their potential for effects on aquatic environment. Traditional grab samples represent the immediate situation, thus only those contaminants present at the time of sampling are characterized. Episodic events such as spills or stormwater runoff can be missed since contaminants can dissipate prior to the next sampling (Alvarez et al., 2005; Huckins et al., 1990, 1993). A more representative way to sample, that represents an integrated estimate of the time-averaged exposure is composite samples collected over time. But, even this type of extensive sampling represents isolated conditions over relatively short durations. This sort of intensive sampling program is resource-intensive, requiring sampling staff and/or special equipment, which cannot be easily employed at many sites, especially at locations where equipment might be at risk to vandalism. An alternative protocol is passive sampling, which enables estimation of time-weighted concentrations of contaminants and sequesters residues from episodic events commonly not detected by use of intermitent grab sampling. Passive sampling requires minimal resources of both personnel and equipment. Passive samplers have no moving parts to fail and require no electricity to function. They can be placed out of sight to avoid vandalism. Passive sampling can be used in situations of variable water conditions and because they concentrate residues from water they can enable detection of ultra-trace, yet toxicologically relevant concentrations of contaminant mixtures over extended durations (Alvarez et al., 2004). Other advantages include relatively simple, single deployment as compared to collecting and processing multiple water samples, greater mass of chemical residues sequestered, and the ability to detect chemicals which dissipate quickly (Alvarez et al., 2005; Huckins et al., 1990). Passive sampling also eliminates the need for some tedious and time-consuming cleanup steps associated with other types of sample collection. Semipermeable membrane devices (SPMDs) have been developed as in situ, integrating passive samplers for monitoring of trace-level, waterborne hydrophobic contaminants (Huckins et al., 1993) and have been used for effective sampling of multiple classes of chemicals, including PAHs, PCBs, OCPs, PCDD/Fs, alkylated phenols, moderately polar organophosphate insecticides, pyrethroid insecticides, neutral organometallic compounds, and certain heterocyclic aromatic compounds (Petty et al., 2000a). Since SPMDs can mimic accumulation by aquatic organisms that can bioconcentrate trace amounts of organic contaminants, SPMDs measure not only the presence, but also the bioavailability and bioconcentration potential of organic contaminants (Huckins et al., 1990; Petty et al., 2000b). Polar Organic Chemical Integrative Samplers (POCIS) sequester waterborne hydrophilic contaminants, such as polar pesticides, pharmaceuticals, ingredients from personal care and consumer products, natural and synthetic hormones (Alvarez et al., 2004, 2005; Petty et al., 2004). Depending on the sorbent used, POCIS can be modified for sampling of general hydrophilic contaminants or pharmaceuticals (Alvarez et al., 2005). The aim of this study was characterization of the influence of the industrialized urban region of Brno, Czech Republic and its associated municipal WWTP on contamination of the Svratka and Svitava rivers by compounds with endocrine disruptive potency by joint use of bioassays, two types of passive samplers and identification and quantification of selected organic chemicals. One goal was to assess the year-round variability in endocrine disruptive potency of WWTP influent and effluent water and thus treatment efficiency for EDCs by collecting composite samples monthly. The second major goal was to determine the relative magnitude of contributions of the urban area and the WWTP on contamination of these two urban rivers by endocrine disruptive compounds that can modulate the arylhydrocarbon (AhR), estrogen (ER) and androgen (AR) receptors. A battery of in vitro bioassays was used to assess potencies of agonists of these three receptors. Two types of passive samplers, POCIS and SPMD, were used to collect integrated samples of hydrophobic and hydrophilic compounds and assess their potencies to interfere with the three receptors signalling. 2. Materials and methods 2.1. Sampling design Samples were collected from the region around Brno, the second largest metropolitan district of the Czech Republic in Central Europe. The metropolitan region of Brno with more than 400,000 inhabitants is spread through the basin formed by the Svratka and Svitava Rivers. The city has a central wastewater treatment plant and a variety of industrial activities. The municipal WWTP treats wastewater conveyed by a system of sanitary sewers from the city of Brno and increasingly also by a system of pumping stations from its surroundings. The WWTP was recently reconstructed and enhanced to a capacity of 513,000 population equivalent with permissible volume of discharged wastewater of 4222 L/s. Waste water is subjected to primary (mechanical) treatment followed by biological stage of activation with pre-denitrification and anaerobic phosphorus removal (system of circulatory activation with change of anaerobic, anoxic and aerated zones). Excess activated sludge is then anaerobically stabilized (Brněnské vodárny a kanalizace, 2010; Ministry of the Environment, 2010). The influent and effluent of the WWTP were sampled monthly from May 2007 until April In addition, SPMD and POCIS passive samplers were placed in the influent (site 5) and effluent (site 6) of the WWTP and at seven sites in the Svratka, Svitava and Bobrava Rivers at locations upstream and downstream of Brno and downstream of the WWTP effluent (Fig. 1). Passive samplers were deployed for 23 days and collected during October Sampling locations in the Svratka River were: Kninicky (site 1) upstream of the city of Brno (downstream of the dam of Brno reservoir) and a site downstream of Brno upstream of the confluence with the Svitava River (Svratka before confluence, site 2). Locations monitored in the Svitava River included Bilovice and Svitavou (site 3), a small town upstream of Brno, and another site downstream of Brno upstream of the confluence with the Svratka River (Svitava before confluence, site 4). Another sampling site was selected in the Bobrava River (site 9), which is a tributary affected mostly by agriculture that flows into the Svratka River downstream of the WWTP. Downstream of the WWTP and the confluence of the Bobrava and Svratka rivers samples were collected near a small town Rajhradice (site 7) and at Zidlochovice (site 8, approximately 20 km downstream from Brno).

78 374 V. Jálová et al. / Environment International 59 (2013) Fig. 1. Map of the Czech Republic showing locations of sampling sites in the vicinity of Brno. Sampling sites: 1 Svratka River, Kninicky, 2 Svratka River before confluence, 3 Svitava River, Bilovice nad Svitavou, 4 Svitava River before confluence, 5 WWTP Modrice, influent, 6 WWTP Modrice, effluent, 7 Svratka River, Rajhradice, 8 Svratka River, Zidlochovice, 9 Bobrava River Passsive water sampling and preparation of extracts SPMD and POCIS disks were obtained from Exposmeter AB, Tavelsjo, Sweden. Prior to passive sampling, the sampling protocol was prepared with QA/QC. One POCIS was used for both chemical analysis and bioassay testing. Two SPMDs were used in duplicates for chemical analysis, one SPMD was used for toxicity assessment. SPMDs for chemical analysis contained performance reference compounds (PRC) used as onsite SPMDs calibration. Four deuterated PAHs ([ 2 H 10 ]acenaphthene, [ 2 H 10 ]fluorene, [ 2 H 10 ]phenanthrene, and [ 2 H 12 ]chrysene) and four 13 C 12 -labeled PCBs (PCB 3, 8, 37, and 54) were used as PRCs. Transport, field and laboratory blanks were used. A standard sampling arrangement was used as described in Grabic et al. (2010). It consists of a combination of POCIS and SPMDs mounted on commercially available stainless steel holders in protective deployment canisters made of perforated stainless steel plates. These samplers were suspended at m depth of the water column in cryptic locations to minimize vandalism. After exposure for 23 days, samplers were recovered, cleaned and sealed in airtight, metal cans and placed on ice in a cooler for transport to the laboratory. Membranes were stored in sealed cans in a freezer at 18 C until analysis. Before analysis SPMDs were cleaned and dialyzed with hexane in accordance with previously published methods (Ellis et al., 1995). Combined dialysates were adjusted to a volume of 10 ml. Chemical residues sampled by POCIS were recovered from the sorbent by organic solvent elution with a combination of methanol:toluene:dichloromethane (1:1:8, v/v/v). Volumes of all extracts were reduced by rotary evaporation and under a gentle stream of nitrogen, then solvent was exchanged to methanol (Alvarez et al., 2005). The final equivalent concentrations were 1 sampler/ml. A portion of each extract was transferred into DMSO for testing in bioassays Processing of waste water Samples of influent and effluent were collected from the municipal WWTP on the Svratka River, downstream of Brno, once a month for 12 months. Water was collected every 2 h and composited over a 24-h period. Samples of influent were prefiltered through glass wool and 47 mm diameter glass fiber filter with 2.7 μm pores (Filap, Czech Republic) and both influent and effluent samples were filtered through glass fiber filters (1 μm pores, Whatman, Sigma-Aldrich, Czech Republic) to prevent solid phase extraction (SPE) cartridges from clogging during later extraction. Filters were extracted and tested separately to ensure that no compounds with significant potency in any of the assays were removed by filtration. Organic compounds in filtrates were extracted within 24 h by SPE by use of Oasis HLB cartridges (Waters, Czech Republic). Cartridges were activated by methanol and equilibrated by water according to producer instructions. After samples had passed through cartridges, they were dried by air for min and eluted by use of 15 ml methanol. Extracts were rotary evaporated to reduce the volume to approximately 2 ml and then evaporated in a gentle stream of nitrogen to final volumes of 1 ml Instrumental analyses Organic extracts of SPMD and POCIS samplers were analyzed for wide range of organic compounds. Samples were analyzed in accordance with standard EN ISO/IEC Detailed analytical procedures were described in Grabic et al. (2010). A set of internal standards was used in the analyses. These included carbon 13 C 12 -labeled PCBs (3, 15, 31, 52, 118, 153, 180, 194, 206, 209), TCS, PFOC (perfluorooctanesulfonic acid [PFOS], perfluoro-nonanoic acid [PFNA], perfluoro-octanoid acid [PFOA]), and native standards purchased from Wellington Laboratories (Canada). 13 C-labeled OCPs (γ-hch and DDE), PAH ( 13 C 2 6 -labeled PAHs U.S. Environmental Protection Agency [U.S. EPA] 16 PAH cocktail), and polar compounds (simazine, 2,4-D, sulfamethoxazol, ciprofloxacin) were purchased from Cambridge Isotope Laboratories (USA). The native ones were purchased from Dr. Ehrenstorfer, AccuStandards, and Absolute Standards via Labicom (Czech Republic). All solvents, including hexane, dichloromethane, acetone, toluene (SupraSolv purity), water, and methanol (hypergrade for LC/MS) were of the highest quality from Merck (Germany). Organic extracts of SPMDs were characterized by quantifying 16 US EPA polycyclic aromatic hydrocarbons (PAH): acenaphthene, acenaphthylene, anthracene, benzo[a]anthracene, benzo[a]pyrene, benzo[b] fluoranthene, benzo[ghi]perylene, benzo[k]fluoranthene, chrysene, dibenzo[a,h]anthracene, fluoranthene, fluorene, indeno(1,2,3-cd)pyrene, naphthalene, phenanthrene, and pyrene), polychlorinated biphenyls (PCBs): tri-, tetra-, penta-, hexa-, hepta-, octa-, nona-, and decacongeners, organochlorine pesticides (OCPs): hexachlorbenzene, α-, β-, γ-, δ-stereoisomers of hexachlorohexane (HCH), two congeners of dichlorodiphenyltrichloroethane (DDT) and its degradation products,

79 V. Jálová et al. / Environment International 59 (2013) dichlorodiphenyldichloroethylene (DDE) and dichlorodiphenyldichloroethane (DDD), triclosan (TCS) and its environmental transformation product methyl triclosan (MeTCS) and polybrominated diphenyl ethers (PBDEs), expressed as the sum of congeners. POCIS extracts were analyzed for polar pesticides, pharmaceuticals and perfluorinated compounds (PFCs), expressed as the sum of perfluoroorganic compounds (PFHxS, FHUEA, FOSA, N-MeFOSA, PFOA, PFOS, PFNA). A complete list of individual pesticides and pharmaceuticals analyzed in POCIS is attached in footnotes to Table 1. Gas chromatography/mass spectrometry (GC/MS) was used for identification and quantification of PAHs. PAHs with more rings that could not be analyzed by use of GC/MS were analyzed by use of high performance liquid chromatography with fluorescence detector (HPLC/FLD). Quantification of PCBs, OCPs, PBDEs, triclosan and its metabolite were performed by GC/MS-MS. Polar pesticides, pharmaceuticals and PFCs were identified and quantified by use of HPLC/MS-MS. Limits of detection for identified groups of chemicals were as follows: PAHs 3 ng/spmd, MeTCS/TCS 3 ng/spmd, OCPs 0.2 ng/spmd, PCBs 0.1 ng/spmd, polar pesticides: ng/pocis, antibiotics: 1 2 ng/pocis, other pharmaceuticals 5 ng/pocis. Analytical procedure involved evaluation of recoveries of internal standards. Recoveries were within following ranges: PAHs: %, MeTCS/TCS: %, OCPs, PCBs: %, polar pesticides, pharmaceuticals: %. Both trip and analytical blanks were analyzed. Laboratory blanks were subtracted. Trip blanks contributed 0 5 % of the total exposure, therefore no subtraction was performed In vitro bioassays Four transactivation reporter gene bioassays were used to assess receptor-mediated potencies of organic extracts of waters from the WWTP and passive samplers. All assays were conducted in 96 well microplates and included several dilutions of extracts in triplicate to provide a dose-response curve for each sample. All media and chemicals were purchased from Sigma-Aldrich (Czech Republic) unless otherwise specified AhR-mediated potency AhR-mediated (dioxin-like) potency was determined by use of the H4IIE-luc bioassay, which is rat hepatoma cell line containing a luciferase reporter gene under control of dioxin-responsive enhancers (DRE) (Hilscherova et al., 2001; Sanderson et al., 1996; Villeneuve et al., 2002). H4IIE-luc cells were cultured in Dulbecco's modified Eagle's medium (DMEM) (BioTech, Czech Republic) supplemented with 10% fetal calf serum Mycoplex (PAA, Austria). The H4IIE-luc cells were seeded in the culture medium at density of 15,000 cells/well and after 24 h exposed to samples, calibration reference or solvent control. Standard calibration was performed with 2,3,7,8-tetrachlorodibenzop-dioxin (TCDD; Ultra Scientific, USA; dilution series pm). After 24 h of exposure, intensity of luciferase luminescence corresponding to the receptor activation was measured by use of Promega Steady Glo Kit (Promega, USA) ER-mediated potency Estrogen receptor mediated potency was evaluated by use of the MVLN bioassay, a human breast carcinoma cell line transfected with the luciferase gene under control of estrogen receptor activation (Demirpence et al., 1993; Freyberger and Schmuck, 2005; Hilscherova et al., 2002). MVLN cells were cultured in medium DMEM/F12 supplemented with 10% fetal calf serum Mycoplex (PAA, Austria). MVLN cells were seeded at density of 20,000 cells/well in DMEM/ F12 supplemented with 10% dialyzed fetal calf serum (PAA, Austria), which was additionally dextran/charcoal treated to further decrease background concentrations of hormones. Approximately 24 h after plating, cells were exposed to samples, calibration reference or solvent control in DMEM/F12. Standard calibration was performed with 17β-estradiol (E 2 ; dilution series pm). Effects of extracts on MVLN were assessed either singly or in combination with competing Table 1 The results of chemical analysis of passive samplers extracts. Ranges: the sum of detected compounds the sum of detected compounds plus limit of detection for the nondetected compounds. POCIS Sampling site Pesticides a Sulfonamides b Other antibiotics c Other pharmaceuticals d PFCs ng/pocis ,087 10, ,550 18, SPMD Sampling site PAHs PCBs OCPs Triclosan MeTriclosan PBDEs ng/l pg/l pg/l pg/l pg/l pg/l , , a Pesticides: clopyralid, bentazone, bromoxynil, 2,4-D, MCPA, dichlorprop, mecoprop (MCPP), 2,4,5-T, imazethapyr, thifensulfuron-methyl, methamidophos, nicosulfuron, rimsulfuron, metamitron, dimethoat, atrazin_desethyl, metoxuron, phosphamidon, cyanazin, metribuzin, simazin, bromacil, carbofuran, hexazinon, thiophanate-methyl, monolinuron, chlorotoluron, isoproturon, metobromuron, atrazin, desmetryn, dichlobenil, methabenzthiazuron, diuron, methidathion, ethofumesat, azoxystrobin, linuron, terbuthylazine, chlorbromuron, propyzamide, prometryn, metolachlor,fenhexamid, fenarimol, acetochlor,terbutryn, fipronil, kresoxim-methyl, tebuconazole, diazinon, propiconazole, phorate, phosalone, fluazifop-p-butyl, tri-allate, pyridate, alachlor, metalaxyl. b Sulfonamides: sulfapyridin, sulfamethazin, sulfamethoxypyridazin, sulfachloropyridazin, sulfamethoxazol. c Other antibiotics: metronidazol, cefalexin, ofloxacin, norfloxacin, ciprofloxacin, enrofloxacin, erythromycin, trimetoprim. d Other pharmaceuticals: diaveridin, carbamazepin, diclofenac.

80 376 V. Jálová et al. / Environment International 59 (2013) endogenous ligand (33 pm 17β-estradiol) given concentration is near its EC 50 value. Exposure duration and final measurement was the same as in the case of H4IIE-luc bioassay described above AR-mediated potency (Anti)androgenicity of passive samplers extracts was assessed in a bioassay with MDA-kb2 cells, a human breast carcinoma cell line stably transfected with luciferase reporter gene under control of functional endogenous androgen receptor (AR) and glucocorticoid receptor (GR) (Wilson et al., 2002). MDA-kb2 cells were cultured in L-15 Leibovitz medium supplemented with 10% fetal calf serum Mycoplex (PAA, Austria). MDA-kb2 were seeded at density of 50,000 cells/well and exposed after 24 h to samples, calibration reference or solvent control in L-15 Leibovitz medium supplemented with 10% dextran/ charcoal treated dialyzed fetal calf serum. Standard calibration was performed with dihydrotestosterone (DHT; dilution series 1 pm 10 μm). In addition to androgenic effects, antiandrogenicity was assessed in combination with competing endogenous ligand (1 nm dihydrotestosterone). After 24 h of exposure, intensity of luciferase luminescence was measured with prepared luciferase reagent (Wilson et al., 2002). Organic extracts of influent and effluent waters were assessed in a bioluminescent yeast assay based on recombinant Saccharomyces cerevisiae cells modified to express human androgen receptor along with firefly luciferase under transcriptional control of androgenresponsive element to detect compounds affecting AR-mediated hormonal signalling. The assay with the androgen-responsive yeast model was performed according to Leskinen et al. (2005). Yeast cells were seeded in 96-well microplates and exposed to reference testosterone (T; dilution series 1 pm 10 μm), the sample alone or in combination with testosterone (10 nm) to determine antiandrogenic effect. Yeast cells were incubated for 2.5 h and then the signal was detected after addition of D-luciferin substrate Cytotoxicity Non-cytotoxic sample concentrations to be used in each bioassay with mammalian cell lines were determined by use of the neutral red uptake assay (Freyberger and Schmuck, 2005). Particular bioassays with individual cell lines were processed as previously described. At the end of the exposure period, neutral red solution (0.5 mg/ml of media) was added and cells were incubated for 1 h at 37 C. Medium was removed and cells washed with PBS and lysed with 1% acetic acid in 50% ethanol. Absorbance was measured in a microplate spectrophotometer at 570 nm. Yeast strain of recombinant S. cerevisiae constitutively expressing luciferase, which has shown greater sensitivity compared to the mammalian cells, was used for detailed cytotoxicity assessment (Leskinen et al., 2005; Michelini et al., 2005). Complete dose responses relationships of cytotoxic effects for all samples were determined after 2.5 h exposure. The intensity of luciferase luminescence after addition of D-luciferin corresponded to the number of surviving cells (Leskinen et al., 2005) Data analysis Sample responses expressed as relative luminescence units were converted to percentage of maximum response of the standard curves (% TCDDmax/E 2 max/dhtmax/tmax). The response of the solvent control was substracted from both standard and sample responses prior to the conversion. EC values were calculated by nonlinear logarithmic regression of dose response curves of calibration standards and samples (Graph Pad Prism, GraphPad Software, San Diego, California, USA). Relative potencies expressed as TCDD equivalents (BIOTEQ)/E 2 equivalents (EEQ)/androgen equivalents (AEQ) were calculated by relating the EC 50 value of standard calibration with the concentration of the tested sample inducing the same response (Villeneuve et al., 2000). Due to cytotoxicity, it was not possible to obtain complete dose response curves in testing of waste water samples in the yeast assay. Thus, their AEQ values were calculated as point estimates because maximum detected luminescence induction at noncytotoxic concentrations did not exceed 15%. Cytotoxicity, antiestrogenicity and antiandrogenicity corresponded to the decrease in detected luminescence/absorbance signal given by solvent control in case of cytotoxicity and specified amount of competing standard ligand for the other effects. IC 50 values for antiestrogenicity and antiandrogenicity or IC 20 values in cases that the effects did not cause 50% response, were calculated from dose response curves expressed in percentage of signal of competitive concentration of added natural ligand (33 pm E 2, 1 nm DHT, 10 nm testosterone). For better clarity of the trends in graphs the values are expressed as an index of antiestrogenicity (AE) or antiandrogenicity (AA), which corresponds to reciprocal value of IC 20 or IC 50. Similarly, the index of cytotoxicity was derived as the reciprocal value of IC 20 or IC 50 for the cytotoxic response Calculation of dissolved water concentrations from passive sampler data Concentrations of target analytes in water were calculated from the mass absorbed by the SPMD, the in situ sampling rate of the compounds and their sampler water partition coefficients using the kinetic uptake model by Huckins et al. (2006). Sampling rates of target compounds were estimated from dissipation of performance reference compounds (PRCs) from SPMDs during exposure using nonlinear least squares method by Booij and Smedes (2010), considering the fraction of individual PRCs that remain in the SPMD after the exposure as a continuous function of their partition coefficients, with sampling rate as an adjustable parameter. The necessary sampler water partition coefficients values were estimated from the respective octanol/water partition coefficients according to Huckins et al. (2006). For the purpose of comparison of toxic potencies of extracts from SPMDs from different sampling sites the measured toxic equivalent concentrations (TEQ) in extracts [ng/spmd] were translated to water concentrations C W-TEQ [ng/l or pg/l] at the individual sites. Since physicochemical properties of the compounds that exhibit bioassay response in the extracts are not known, linear uptake was assumed (Eq. (1)). C w TEQ ¼ TEQ R s t Where: R S is the sampling rate and t is the exposure time. The necessary R S values were obtained using the PRC model described above. Since R S is only a weak function of hydrophobicity, values of R S with a medium molecular mass (MW = 300) were applied in all calculations. For POCIS data, no correction for the potential effect of environmental variables was performed and results were simply compared on the basis of toxic equivalent concentrations (TEQ) in sampler extracts [ng/pocis]. It has been demostrated that water flow rate has a relatively minor influence on the accumulation of a number of pollutants including EDCs into POCIS (Li et al., 2010). Thus, it appears not necessary to adjust sampling rates for POCIS when they are deployed in areas where the water flows vary only slightly. 3. Results 3.1. Concentrations of individual residues Greatest concentrations of polar pesticides, pharmaceuticals and perfluoroorganic compounds in POCIS were detected at site 6 (WWTP effluent) (Table 1). Concentrations of contaminants found in ð1þ

81 V. Jálová et al. / Environment International 59 (2013) POCIS from WWTP influent (site 5) were less than in POCIS at WWTP effluent and comparable or greater than in those from the other sites. The explanations of greater detected levels of some contaminants and biological potencies in passive samplers from WWTP effluent are elaborated in detail in the Discussion section. Concentrations of some pharmaceuticals in POCIS from the sites upstream of Brno were slightly greater than downstream, but concentrations in the Svratka River were generally approximately 4-fold less than in the Svitava River. Similarly, concentrations of PFCs were approximately 6-fold greater in Svitava than in Svratka, while concentrations of pesticides were comparable in both rivers. Greater concentrations of pesticides were found at site 9 on the tributary of the Svratka River. Concentrations of pharmaceuticals were greater bellow the WWTP effluent. There was a slight decrease of concentrations of contaminants in POCIS as a function of distance from the city and WWTP. The greatest concentrations of most pollutants sampled by SPMD were observed in samples from the WWTP, with concentrations of PAHs and triclosan greatest in the influent (site 5), while concentrations of methyl triclosan were greatest in the effluent (site 6) (Table 1). Greater concentrations of PCBs and methyl triclosan were detected already upstream of Brno in the Svitava River (sites 3, 4). Concentrations of most pollutants did not increase much directly downstream of Brno on both rivers (sites 2, 4), except for PCBs in the Svratka River. Concentrations of PAHs were slightly lesser downstream of the WWTP (site 7) and further decreased at the longer distance from the city (site 8), while no such trend was observed for concentrations of PCBs and OCPs. Concentrations of PBDEs, triclosan and methyl triclosan were significantly greater downstream of the WWTP Cytotoxicity Some samples of WWTP influent water caused 20% cytotoxicity even at 25-fold dilution, but effluent water samples caused cytotoxicity only at 100% water equivalents or were not cytotoxic (Fig. 2A). Removal efficiency for cytotoxicity in waste water was 83 to 98% throughout the year, except of one time point when toxicity of the influent was small and thus efficiency of removal was lower (46%). All POCIS extracts elicited cytotoxic effects, with the greatest cytotoxicity observed for samples from the WWTP effluent (site 6, Fig. 2B), which was about 50% greater than the effect of the WWTP influent sample (site 5). Cytotoxicity of POCIS exposed to river water was 4 to 10-fold lower, with greater toxicity in water from the Svitava River. It slightly increased downstream of the WWTP (site 7). A greater than 93% decrease in cytotoxicity after treatment of wastewater was observed in SPMD samples (Fig. 2C), where the WWTP influent sample (site 5) exhibited the greatest cytotoxicity. Cytotoxicity of compounds sampled by SPMD from upstream of Brno was greater in Svratka river, and it increased in river Svitava after flowing through the city and also downstream of WWTP (Fig. 2C) AhR-mediated potency Significant AhR-mediated (dioxin-like) potency expressed as bioassay-derived 2,3,7,8-TCDD equivalents (BIOTEQ) was detected in most samples. Samples of influent water from the WWTP generally elicited greater dioxin-like potency than did effluent water (Fig. 3A). Concentrations of BIOTEQ were between 0.1 and 3.4 ng TCDD/L for influent and 0.1 to 0.7 ng TCDD/L for effluent. Efficiency of treatment of the WWTP for compounds with dioxin-like potency varied during the year from 13 to 90%, except for two cases when the removal efficiency was even negative. In February and April effluent samples contained 8 and 27% greater levels of BIOTEQ than corresponding influent samples, respectively. Significant dioxin-like potency in POCIS samples was detected only for samples from the WWTP (sites 5, 6) and site 7 (sampling site directly downstream of the WWTP) (Fig. 3B, A Waste water dilution causing 20% cytotoxicity B Index of cytotoxicity (1/IC50) C Index of cytotoxicity (1/IC20) insert). Concentrations of BIOTEQs were between 0.3 and 2 ng TCDD/ POCIS. Potency detected in the WWTP effluent (site 6) was 5-fold greater than that in the influent (site 5). All extracts of SPMD contained detectable AhR-mediated potency with the greatest response in the WWTP influent sample (site 5) and also in the Bobrava River which was affected by agriculture (site 9, Fig. 3B). Concentrations of BIOTEQ determined from SPMD ranged from 8.2 to 14.6 pg TCDD/L ER-mediated potency Influent Effluent Sampling site Sampling site Fig. 2. Cytotoxicity of samples extracts detected in the bioluminescent yeast assay: (A) influent and effluent water samples from the WWTP; (B) POCIS (Index of cytotoxicity expressed as reciprocal value of IC 50, [sampler/ml] 1 ); (C) SPMD (Index of cytotoxicity expressed as reciprocal value of IC 20, [L/mL] 1 ); no column = no significant activity. Potency of ER agonists was detected in water from the WWTP during all samplings throughout the year (Fig. 4). Values of 17β-estradiol (E 2 ) equivalents (EEQ) varied from 5.4 to 124 ng E 2 /L in influent and from 0.1 to 5.1 ng E 2 /L in effluent. Efficiency of treatment to remove EEQ ranged from 80 to greater than 99 %. POCIS sample from the WWTP influent (site 5) had a concentration of EEQ of 7.3 ng E 2 /

82 378 V. Jálová et al. / Environment International 59 (2013) A BIOTEQ (ng TCDD/L) B BIOTEQ (pg TCDD/L) ng TCDD/POCIS Influent Effluent Sampling site EEQ (ng E2/L) May 07 June 07 Influent Effluent July 07 August 07 September 07 October 07 November 07 December 07 January 08 February 08 March 08 April 08 Fig. 4. Estrogenic potency, expressed as estradiol equivalents (EEQ) of extracts of WWTP influent and effluent water, detected in MVLN assay; no column = no significant activity. greatest antiandrogenic potency in extracts of POCIS was observed at site 4 in the Svitava River, directly downstream of Brno (Fig. 6A). The antiandrogenic potency of the extract of the POCIS exposed to WWTP influent (site 5) was comparable with the potency observed in samples from most sites on the rivers. There was no antiandrogenic potency observed in POCIS exposed to WWTP effluent (site 6). There was generally no antiandrogenic potency in extracts of SPMD exposed upstream of the WWTP, while there was antiandrogenic potency in samples from the WWTP (sites 5, 6) and from sites downstream of the WWTP. The antiandrogenic potency of compounds sampled by SPMD was approximately 60% greater in WWTP influent than that in effluent (Fig. 6B). Fig. 3. AhR-Mediated (Dioxin-like) potency of samples extracts detected in H4IIE-luc assay expressed as BIOTEQ equivalents: (A) influent and effluent water from the WWTP; (B) SPMD and POCIS. A 2400 sampler. The concentration of EEQ in the extract of POCIS exposed to effluent (site 6) was less than 0.6 ng E 2 /sampler, which was the limit of detection. There were no EEQ detectable in POCIS from the rivers or in any SPMD samples. Influent and effluent water samples from the WWTP showed no significant antiestrogenic potency when tested in the presence of E 2. Alternatively, antiestrogenic potency was detected in extracts of SPMD and POCIS from all sites. Data from SPMDs indicate greater antiestrogenicity in sites from river Svratka compared to Svitava already upstream of Brno. Greatest antiestrogenicity was observed in POCIS exposed to WWTP effluent while all samples from rivers and WWTP influent showed comparable potency (Fig. 5). Index of antiestrogenicity B (1/IC50) Sampling site 3.5. AR-mediated potency Significant androgenic potencies were found mostly at the greatest non-cytotoxic concentrations of influent water samples and concentrations of androgen equivalents (AEQ) ranged from b23 to 193 ng testosterone/l (Table 2). Concentrations of AEQ determined for non-cytotoxic concentrations of effluent extracts were less than the limit of detection, which was 1 4 ng testosterone/l. Efficiency of treatment to remove androgenic compounds was greater than 96 99%. POCIS from WWTP influent and effluent were the only other samples to exhibit detectable AEQ with concentrations of 32.6 and 6.9 ng DHT/sampler, respectively. No antiandrogenic potency was observed in non-cytotoxic concentrations of samples from influent or effluent water from the WWTP. Antiandrogenic potency in competition with the added endogenous ligand DHT was detected in most extracts of SPMD and POCIS. The Index of antiestrogenicity (1/IC20) Sampling site Fig. 5. Antiestrogenicpotencies ofsamples extracts determinedby use ofthemvln assay in the presence of 33 pm estradiol expressed as index of antiestrogenicity: (A) POCIS reciprocal value of IC 50 [sampler/ml] 1 ), (B) SPMD reciprocal value of IC 20 [L/mL] 1 ).

83 V. Jálová et al. / Environment International 59 (2013) Table 2 Androgenic activity of influent and effluent water extracts from the WWTP detected in the yeast assay. (LOD ranged from 1.3 to 70 ng testosterone/l because of variable cytotoxicity of samples). Sampling date 4. Discussion AEQ (ng testosterone/l) Influent Effluent May b3.7 June b2.2 July 07 b70 b2.2 August 07 b70 b2.6 September 07 b23 b1.3 October b1.3 November b1.3 December b1.3 January b1.3 February b1.3 March b1.3 April b1.3 Rivers can be contaminated by many chemicals, some of which have the potential to affect normal reproduction, development and behavior of wildlife species and potentially also human health. Some of these compounds can be released to rivers from large city agglomerations via WWTP and other point-discharge or diffuse sources (Cargouet et al., 2004; Jobling et al., 1998; Sabaliunas et al., 2000; Snyder et al., 2000). In recent years, WWTP have been studied as potential sources of endocrine disruptive compounds to the aquatic environment (Harries et al., 1996; Murk et al., 2002; Tan et al., A Index of antiandrogenicity B Index of antiandrogenicity (1/IC50) (1/IC50) Sampling site Sampling site Fig. 6. Antiandrogenic potency of samples extracts determined by use of the MDA-kb2 assay in the presence of 1 nm dihydrotestosteron (DHT), expressed as an index of antiandrogenicity (reciprocal value of IC 50): (A) POCIS [sampler/ml] 1, (B) SPMD [L/mL] 1 ; no column = no significant activity. 2007). There are several studies that have investigated WWTPs by use of various approaches including passive sampling combined with instrumental analysis and/or bioassays (Tan et al., 2007; Vermeirssen et al., 2005). However, there has been less information on other possible sources. Moreover, the studies using bioassays were focused mainly on estrogenic potency and there is limited data on other specific biological potencies in mixtures extracted from surface or waste waters. In addition, mostly known endocrine disruptive compounds, such as estrogens, androgens, phthalates or alkylphenols are analyzed, but more data is needed for other pollutants, such as widely used compounds from the group of pharmaceuticals and personal care products. In this study potencies for ligands in mixtures to interact with specific receptors as well as concentrations of several classes of pollutants were measured in waste waters and surface waters of two rivers in an urban metropolitan area in Central Europe with a variety of industries and modern recently renovated WWTP with advanced treatment capacity and efficiency. The sampling design and a complex approach using passive sampling along with chemical analysis and bioassays enabled to characterize the distribution and sources of pollutants in the model part of river basin. Based on measured residues, water of the Svitava River upstream of Brno seems to be more polluted than the Svratka River. Specifically, concentrations of pharmaceuticals, PFCs, PCBs and methyl triclosan were lower in the Svratka River. Furthermore, greater potencies for cytotoxicity of the hydrophilic fraction were observed in the Svitava River upstream of Brno. These data point to some pollution sources on river Svitava upstream of Brno agglomeration. There was no obvious influence of the city itself or WWTP on the concentrations of PAHs and organohalogenated compounds except of somewhat increased PCBs in Svratka downstream of Brno. Thus, neither runoff from the metropolitan region of Brno nor the effluent of the WWTP contributed significantly to the pollution with these compounds. Alternatively, concentrations of pharmaceuticals, antibiotics, triclosan and PBDEs were not affected by the city, but increased downstream of the WWTP, despite its up-to-date treatment technology. The data from passive samples document highly efficient removal of hydrophilic antiandrogenic and about 60% removal of hydrophobic antiandrogenic pollutants during WW treatment. Despite this removal, the concentrations of hydrophobic antiandrogenic pollutants in the river increased downstream of the WWTP similarly to the cytotoxic potency. Concentrations of triclosan and methyl triclosan were increased by the WWTP. For polar pesticides there was no influence of the city itself or WWTP. Concentrations of most of the polar compounds sampled by POCIS and associated biological potencies went down at the last study site about 20 km downstream of the city. There was no such decrease in levels of hydrophobic pollutants sampled by SPMD and their biological potencies, except of PAHs. The decrease of PAHs concentrations downstream of WWTP was not due to particle adsorption and sedimentation after flow out from WWTPs, since there was no increase of PAHs levels in river sediments (data not shown). For all pollutants sampled by POCIS as well as some pollutants sampled by SPMD, the greatest concentrations were detected in WWTP effluent. Similarly, in the POCIS exposed to effluent there was also the greatest cytotoxicity, dioxin-like and antiestrogenic potency. All these concentrations and potencies were greater than for the WWTP influent. There are at least two explanations of the observed elevated concentrations and toxic potencies of compounds accumulated in passive samplers in the WWTP effluent in comparison to influent. Passive sampling methods measure the concentration of freely dissolved contaminants, which is directly related to the contaminants' chemical activity (Mayer et al., 2003). This also indicates the bioavailability or pressure (fugacity) of contaminants on organisms and consequently represents the exposure level for organisms. In the WWTP influent hydrophobic compounds are largely sorbed to the suspended particulate material so that their freely dissolved concentration is small (Lohmann et al., 2012). In the wastewater

84 380 V. Jálová et al. / Environment International 59 (2013) treatment process the content of suspended material is efficiently reduced, which in turn results in a strong decrease of sorption capacity for hydrophobic compounds in WWTP effluent. However, some persistent compounds are not eliminated by the treatment process. As a result of the reduced uptake capacity of the particulate matter, free dissolved concentrations (chemical activity) in the effluent are higher than in the influent, which is in turn reflected in their levels found in passive samplers, especially in SPMDs. Differences in uptake might be affected by different passive sampler exposure conditions in WWTP influent and effluent, respectively. Among potential factors that affect uptake kinetics into passive samplers, hydrodynamics and fouling are the most important ones. The visual observation of channels in WWTP influent and effluent indicates a similar turbulent water flow character in both cases. Thus, influent/effluent differences in hydrodynamics can hardly explain the observed up to ten-fold increase in accumulated amounts of some compounds in passive samplers (e.g. compounds in POCIS; Table 1). We hypothesize that fouling of samplers is the more important factor that affects the uptake of both hydrophobic as well as hydrophilic compounds into passive samplers. The raw waste water is a very complex mixture which contains debris, mud, various particles and even dispersed emulsions of liquids that are non-miscible with water (such as fats). Fouling and layers of dirt can reduce uptake of compounds into passive samplers (Stuer-Lauridsen, 2005) and lead to lower sampling rates by a) physical blockage of active surface of samplers by debris; b) thickening the diffusion barriers; c) reduction of the driving force for sampler uptake by shifting the partitioning equilibria between sampler and the surrounding environment. Our study indicates that passive sampling (especially for POCIS samples) may not be a reliable method in raw sewage water and could lead to significant underestimation of actual concentrations of dissolved pollutants. This problem is really specific to the raw sewage water and does not concern passive samples from any other site. Most studies using in vitro assays include cytotoxicity tests, which determine the greatest possible sample concentration that is not cytotoxic for the cells to be used as the maximal tested concentration for the specific effects. In this study, dose response curves and IC 50 of extracts on yeast cells were determined. The efficient decrease of cytotoxicity in SPMD and waste water after waste water treatment might be due to activated sludge processes as well as flocculation, which have been shown to have the greatest efficiency of removal of cytotoxic compounds (Ma et al., 2005). Cytotoxicity of waste waters did not correlate with estrogenic or androgenic potencies of these waste waters. This observation is consistent with the results reported by Vega-Lopez et al. (2007), who found no correlation between estrogenic disruption and toxicity determined in MCF-7 cells for samples of water from two Mexican lakes, which receive domestic and industrial wastewaters after secondary treatment. These results support the theory that estrogenic potency in waste waters is caused primarily by steroidal estrogens, which are potent at ng/l concentrations and therefore does not correlate with the overall cytotoxicity. Cytotoxicity of extracts of all POCIS in the yeast assay can be related to sesquestered pollutants, especially antibiotics and other pharmaceuticals determined by chemical analysis. There are few studies that have focused on effects of urban pollution on the overall toxicity of waters in municipal rivers. Toxicity determined by the Microtox assay was directly proportional to urban land cover in streams around six metropolitan areas in the USA (Bryant and Goodbred, 2009). Toxicity of river water sampled by SPMD in Microtox and Daphnia pulex test has been observed in the Neris River after flowing through the capital city of Lithuanina (Sabaliunas et al., 2000). This finding is consistent with the observation of greater toxicity of compounds sampled by SPMD from the Svitava River downstream of the metropolitan area compared to upstream of Brno observed in this study. Detected AhR-mediated potency in both SPMD and POCIS indicated contribution of both hydrophobic and polar compounds to the overall dioxin-like potential of samples. Similarly in river sediments, mass-balance calculations based on fractionation with subsequent quantification have suggested that PAHs can account for a considerable portion of the dioxin-like potency together with unidentified more polar AhR-active compounds (Hilscherova et al., 2001). Dioxin-like potency found in all extracts of SPMDs was probably linked with the presence of known hydrophobic AhR ligands, such as PAHs or PCBs. Although dioxin-like compounds are usually investigated in less polar matrices such as SPMD or sediments, some recent studies (Dagnino et al., 2010; Reungoat et al., 2010) confirmed AhR potency in water phase. Results of another study (Jarosova et al., 2012) reported dioxin-like potency of 0.05 to 0.39 ng BIOTEQ/POCIS in headwaters with small local sources of pollution. In the current study, POCIS samples exhibited dioxin-like potency only at three sites, inside and downstream of the WWTP, which suggests that waste waters contain some hydrophilic dioxin-like compounds that are not completely removed during treatment. This result is in agreement with the dioxin-like potencies detected WWTPs influent and effluent waters. The data for waste water samples show dioxinlike potency specifically for the polar methanolic extracts and thus might not include influence of some hydrophobic pollutants. Efficiency of treatment by the WWTP determined from BIOTEQs of the waste water samples was not as great for chemicals with dioxin-like potency as in the case of elimination of cytotoxicity or hormone-like potencies. Efficiencies of treatment varied substantially throughout the year. Release of some particle-bound compounds during treatment and lesser efficiency of treatment related to greater persistence of some AhR-active compounds might have contributed to this difference. However, the absolute concentrations of BIOTEQ were less than those observed in other studies eventhough only a limited number of papers report dioxin-like potency in the dissolved phase. For example, Dagnino et al. (2010) detected AhR potency (by the same method as we used) in influent and effluent of French municipal WWTPs with an activated sludge system supplemented with biofilter to be as great as 37 to 112 ng TCDD/L, and 2.8 to 11.6 ng TCDD/L, respectively. Efficiency of removal was approximately 90% and the authors concluded that removal of AhR potency in this type of WWTPs depends primarily on removal of suspended solids with which they are associated. Alternatively, Ma et al. (2005) did not find concentrations of BIOTEQ that were greater than 14 pg TCDD/L in either influents or effluents from a pilot plant in a Beijing WWTP, China. The observation that xenoestrogens and xenoandrogens were detected in waste water and POCIS samples from the WWTP, but not in SPMDs, implies that polar compounds accounted for the estrogenic and androgenic potencies. Since feminization of fish downstream from WWTPs has been observed in rivers worldwide, estrogenic potential of different types of waters has been evaluated in multiple studies. Examples of estrogenic potencies detected by various in vitro assays documenting the comparability of our findings to the situation in other parts of the world are compiled in Table 3. Relatively great efficiency of removal of estrogenic potency in various WWTPs has been documented both by composite water sampling as well as POCIS sampling. The majority of municipal or domestic WWTPs have implemented at least physical and biological treatment techniques. Activated sludge processes, similar to those of WWTP investigated in this study, are the most widely used types of biological treatment processes worldwide. Most studies that have focused on WWTP of similar types to that studied here found the treatment efficiencies for estrogens ranging from N88 to N99% (Leusch et al., 2005; Murk et al., 2002), 90 95% (Korner et al., 2000; Murk et al., 2002) or greater than 95% (Tan et al., 2007), but other studies have reported lesser efficiencies (Cargouet et al., 2004). Efficiency of removal of estrogenic potency, as determined by the MVLN assay, in four mechanical biological municipal or domestic WWTPs in Paris

85 V. Jálová et al. / Environment International 59 (2013) Table 3 Examples of estrogenic activities in waste waters and surface waters as detected by various in vitro assays. Matrix EEQ ng/l Country In vitro assay a Reference Wastewater influent Germany E-Screen Korner et al. (2000) Queensland, Australia E-Screen Leusch et al. (2005) The Netherlands ER-CALUX, YES Murk et al. (2002) Japan YES Onda et al. (2002) 1 30 Sweden YES Svenson et al. (2003) Queensland, Australia E-Screen Tan et al. (2007) Czech Republic MVLN This study Wastewater effluent 6 Germany E-Screen Korner et al. (2000) b0.75 Queensland, Australia E-Screen Leusch et al. (2005) The Netherlands ER-CALUX, YES Murk et al. (2002) 4 25 Japan YES Onda et al. (2002) b Sweden YES Svenson et al. (2003) Japan YES Nakada et al. (2004) USA MVLN Snyder et al. (2001) b Queensland, Australia E-Screen Tan et al. (2007) Czech Republic MVLN This study Surface water The Netherlands ER-CALUX Murk et al. (2002) Belgium E-Screen Nadzialek et al. (2010) b0.18 Portugal YES Sousa et al. (2010) USA MVLN Snyder et al. (2001) b Sweden YES Svenson et al. (2003) Korea E-Screen Oh et al. (2009) a E-Screen cell proliferation assay, ER-CALUX estrogen receptor chemical activated luciferase gene expression assay, YES yeast estrogen screen, MVLN luciferase reporter gene-based assay using the MVLN cell line. ranged from 62 to 97% (Cargouet et al., 2004), which was similar to those reported for five WWTPs in the United Kingdom, which had reported efficiencies of 70 to 100% (Kirk et al., 2002). Efficiency of removal observed in this study was 80 to N99%, but in most tested samples it was greater than 96%. In previous studies, concentrations of estrogen equivalents (EEQ) of river water upstream and downstream of several WWTPs, quantified by use of the yeast estrogen screen (YES), was significantly correlated with EEQ based on chemical analysis of steroidal estrogens for grab samples and POCIS (Vermeirssen et al., 2005). Also chemical and biological (E-Screen assay) analyses used to determine the concentrations of 15 endocrine disrupting compounds and estrogenicity in grab and passive samples from five municipal WWTPs showed good agreement (Tan et al., 2007). Alternatively, assessment of contamination of headwater streams from livestock farms documented that measured waterborne steroids accounted for some of the detected estrogenicity, but a considerable portion of estrogenicity could not be attributed to concentrations of identified estrogens (Matthiessen et al., 2006). Androgenic potency of waste water in bioassays was shown to decrease during progression through the WWTP (Michelini et al., 2005). Concentrations of AEQ and efficiencies of removal observed in our study are similar to those reported for three Swedish municipal WWTPs that used activated sludge systems, and had androgenic potencies in yeast androgen screen (YAS) in influents ranging from 30 to 75 AEQ ng/l (and AEQ ng/l in effluents) with efficiencies of removal of 96 98% (Svenson and Allard, 2004). However, some studies detected androgenic potencies in waste water influents that were greater than those observed in our study (Kirk et al., 2002; Leusch et al., 2006). Androgenic potencies in effluents of some WWTPs were as great as hundreds of ng AEQ/L, but in other WWTPs effluents they were less than the limits of quantification (Blankvoort et al., 2005; Kirk et al., 2002; Leusch et al., 2006; Sousa et al., 2010). Efficiencies of removal of androgens ranged from 82 to more than 99% when activated sludge was included in treatment processes, but significantly less when only primary treatment or for example biological trickling filters were employed (Kirk et al., 2002; Leusch et al., 2006). This observation is consistent with efficiencies of removal determined in this study which were greater than 96% in all cases. Also results obtained with POCIS samples confirmed significant removal of compounds with estrogenic and androgenic potency. Our results document that the efficiency of removal of both estrogenic and androgenic potency of the Brno WWTP can be ranked among the most efficient clarification WWTPs that do not implement advanced treatment. However, the results reported here also show that the efficiency of treatment can vary especially for dioxin-like and cytotoxic compounds, and thus one timepoint sampling might not be sufficient for its determination. Results of this study provide unique information on the variability of cytotoxicity and specific potencies in waste waters during the whole year. Estrogenic potency seemed to be greater in the dryer summer season when there is less dilution than during winter when more precipitation results in greater runoff, but also greater dilution (Fig. 4). However, there was no clear trend for androgenic potencies. Lower temperatures in winter did not negatively influence removal of estrogenic potency by the WWTP, but it might have affected the breakdown of more persistent compounds causing the dioxinlike potency. The greatest cytotoxicity was observed during summer, which might be correlated with lesser dilution (Fig. 2), but with another peak in winter, when probably some other types of pollutants associated with more typical winter sources (such as combustion) might play more significant role. However, the dioxin-like potency did not vary as much as estrogenicity throughout the year, except for August when it was approximately 3-fold greater than during the rest of the year. This observation is probably due to less dilution in summer and possibly also some immediate pollution situation that can affect the samples collected during a single day. There is limited information on seasonal variability of specific potencies of contaminants in waste waters. A study conducted in the UK (Kirk et al., 2002) found that estrogenic and also androgenic potencies in influents and effluents were less in samples collected in months of rainy weather. The recombinant yeast assay was used to assess variability of estrogenic potencies in influent and effluent of Canadian municipal WWTP implementing an additional cleaning step of UV disinfection (Fernandez et al., 2008). Estrogenic potencies of composite samples of influent taken every week from September to December were not dependent on sampling season, while EEQ levels in final effluents were very high, exceeding 100 ng EEQ/L in September and ranging from about 50 to 80 ng EEQ/L from the end of October till the end of the campaign. Lower EEQ concentrations in effluent in autumn and winter compared to summer were seen also in our study, but the ranges of EEQ values were much lower than those reported by Fernandez et al. (2008).

86 382 V. Jálová et al. / Environment International 59 (2013) Similar to the results of this study, small estrogenic potencies and/or concentrations of industrial estrogen mimics and natural estrogens were frequently detected in WWTP discharges, due to their incomplete removal by WWTPs (Table 3). However, even these concentrations have been shown to be effective in causing some biological effects. It has been demonstrated in a 7-year whole-lake experiment that long term exposure to estrogens (5-6 ng/l ethinyl estradiol) can affect sustainability of wild fish populations (Kidd et al., 2007). Moreover, a multigeneration study of Chinese rare minnows (Gobiocypris rarus) demonstrated that reproduction of the F 1 minnows was completely inhibited at the ethinyl estradiol concentration as low as 0.2 ng/l (Zha et al., 2008). These results suggest that even when efficiencies of removal of estrogen are as great as those observed in this study, risks to aquatic organisms can still occur due to the concentrations of estrogens that are constantly released from waste water effluents. The risk seems to be greatest in cases when the volume of effluent waters represents a greater proportion in relation to the receiving waters. Next to the estrogenic and androgenic potencies detected in POCIS and water from WWTP, there were also some antiestrogenic and antiandrogenic pollutants in passive samples from WWTP, which however were not detected in the influent and effluent water samples. This difference indicates that antiestrogenic and antiandrogenic potency is related probably to less polar compounds, which were not in sufficient concentrations included in the methanolic extract of waste water. Moreover, the antiestrogenic/antiandrogenic potencies in waste waters could be masked by relatively great cytotoxicity of the methanolic extracts. Furthermore, passive samples enable higher preconcentration of the compounds compared to the composite water samples and thus the antiestrogenic/antiandrogenic activity detected in passive samples might have been bellow the limit of detection for the water samples. The passive samples from rivers exhibited neither estrogenic nor androgenic potency, but rather antiestrogenic and antiandrogenic potential. The antiestrogenic potency was detected in extracts from passive samplers exposed upstream of the city. In the study by Garcia-Reyero et al. (2001) (anti)estrogenicity was detected by recombinant yeast assay in waste waters and all samples of river water. The lack of estrogenic potency in POCIS and SPMD from river water in the study reported here could be caused by the presence of sufficient concentrations of chemicals that have been shown to have antiestrogenic potency, including pesticides, such as linuron or atrazine (Orton et al., 2009). Antiandrogenic potency was detected at most sampling sites. Hydrophilic antiandrogenic compounds were found in POCIS at sampling sites upstream of the city, whereas antiandrogenic potency in SPMD associated with the more hydrophobic pollutants was detected namely in the WWTP and downstream of the WWTP. Multiple contaminants are known to be associated with antiandrogenic potency (Orton et al., 2009; Sohoni and Sumpter, 1998), including some pesticides, which were detected by chemical analysis (e.g. p,p -DDE, diuron). 5. Conclusion This study revealed the presence of compounds with endocrine disruptive potency in both river water and WWTP influent and effluent. The results of year-round waste water assessment confirmed high treatment efficiency of the WWTP for cytotoxic compounds, xenoestrogens and xenoandrogens. There was significant seasonal variability of efficiency of treatment, especially of dioxin-like potencies. Despite its high efficiency WWTP had impact on the pollution with endocrine disruptive compounds. The approach employed enabled determination of contributions of the metropolitan urban area and the WWTP to contamination of the rivers. Concentrations of PAHs and most pollutants sampled by POCIS decreased as a function of distance downstream of the city. Passive sampling, along with in vitro bioassays and chemical analysis allowed determination of a broad spectrum of contaminants and specific biological potencies and revealed the pollution situation in this model region. More research should be performed in the future to better characterize passive sampler performance under complex exposure conditions in raw wastewaters. Acknowledgments This research was supported by CETOCOEN (CZ.1.05/2.1.00/ ) project granted by the European Union and administered by the Ministry of Education, Youth and Sports of the Czech Republic, and by the projects of the MSMT 2B06093 and ENVISCREEN 2B Prof. Giesy was supported by the program of 2012 High Level Foreign Experts (#GDW ) funded by the State Administration of Foreign Experts Affairs, the P.R. China to Nanjing University and the Einstein Professor Program of the Chinese Academy of Sciences. He was also supported by the Canada Research Chair program, and an at large Chair Professorship at the Department of Biology and Chemistry and State Key Laboratory in Marine Pollution, City University of Hong Kong. References Alvarez DA, Petty JD, Huckins JN, Jones-Lepp TL, Getting DT, Goddard JP, et al. Development of a passive, in situ, integrative sampler for hydrophilic organic contaminants in aquatic environments. 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90 Accepted Manuscript EU-wide monitoring survey on emerging polar organic contaminants in wastewater treatment plant effluents Robert Loos, Raquel Carvalho, Diana C. António, Sara Comero, Giovanni Locoro, Simona Tavazzi, Bruno Paracchini, Michela Ghiani, Teresa Lettieri, Ludek Blaha, Barbora Jarosova, Stefan Voorspoels, Kelly Servaes, Peter Haglund, Jerker Fick, Richard H. Lindberg, David Schwesig, Bernd M. Gawlik PII: S (13) DOI: /j.watres Reference: WR To appear in: Water Research Received Date: 22 March 2013 Revised Date: 3 July 2013 Accepted Date: 17 August 2013 Please cite this article as: Loos, R., Carvalho, R., António, D.C., Comero, S., Locoro, G., Tavazzi, S., Paracchini, B., Ghiani, M., Lettieri, T., Blaha, L., Jarosova, B., Voorspoels, S., Servaes, K., Haglund, P., Fick, J., Lindberg, R.H., Schwesig, D., Gawlik, B.M., EU-wide monitoring survey on emerging polar organic contaminants in wastewater treatment plant effluents, Water Research (2013), doi: / j.watres This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

91 ACCEPTED MANUSCRIPT 1 2 EU-wide monitoring survey on emerging polar organic contaminants in wastewater treatment plant effluents Robert Loos a *, Raquel Carvalho a, Diana C. António a, Sara Comero a, Giovanni Locoro a, Simona Tavazzi a, Bruno Paracchini a, Michela Ghiani a, Teresa Lettieri a, Ludek Blaha b, Barbora Jarosova b, Stefan Voorspoels c, Kelly Servaes c, Peter Haglund d, Jerker Fick d, Richard H. Lindberg d, David Schwesig e, Bernd M. Gawlik a a European Commission, Joint Research Centre, Institute for Environment and Sustainability, Via Enrico Fermi, Ispra, Italy b Masaryk University, Faculty of Science, RECETOX, Kamenice 5, CZ Brno, Czech Republic c VITO, Flemish Institute for Technological Research, Boeretang 200, 2400 Mol, Belgium d Umeå University, Umeå, Sweden e IWW Water Centre, Moritzstr. 26, Muelheim an der Ruhr, Germany ACCEPTED MANUSCRIPT *Corresponding author phone ; fax: ; Robert.Loos@jrc.ec.europa.eu

92 ACCEPTED MANUSCRIPT 2 24 Keywords 25 Wastewater treatment plants (WWTPs); effluent water; European wide monitoring; polar organic contaminants; pharmaceuticals and personal care products (PPCPs) Abstract In the year 2010, effluents from 90 European wastewater treatment plants (WWTPs) were analyzed for 156 polar organic chemical contaminants. The analyses were complemented by effect-based monitoring approaches aiming at estrogenicity and dioxinlike toxicity analyzed by in vitro reporter gene bioassays, and yeast and diatom culture acute toxicity optical bioassays. Analyses of organic substances were performed by solidphase extraction (SPE) or liquid-liquid extraction (LLE) followed by liquid chromatography tandem mass spectrometry (LC-MS-MS) or gas chromatography highresolution mass spectrometry (GC-HRMS). Target microcontaminants were pharmaceuticals and personal care products (PPCPs), veterinary (antibiotic) drugs, perfluoroalkyl substances (PFASs), organophosphate ester flame retardants, pesticides (and some metabolites), industrial chemicals such as benzotriazoles (corrosion inhibitors), iodinated x-ray contrast agents, and gadolinium magnetic resonance imaging agents; in addition biological endpoints were measured. The obtained results show the presence of 125 substances (80 % of the target compounds) in European wastewater effluents, in concentrations ranging from low nanograms to milligrams per liter. These results allow for an estimation to be made of a European median level for the chemicals ACCEPTED MANUSCRIPT investigated in WWTP effluents. The most relevant compounds in the effluent water with the highest median concentration levels were the artificial sweeteners acesulfame and

93 ACCEPTED MANUSCRIPT sucralose, benzotriazoles (corrosion inhibitors), several organophosphate ester flame retardants and plasticizers (e.g. tris(2-chloroisopropyl)phosphate; TCPP), pharmaceutical compounds such as carbamazepine, tramadol, telmisartan, venlafaxine, irbesartan, fluconazole, oxazepam, fexofenadine, diclofenac, citalopram, codeine, bisoprolol, eprosartan, the antibiotics trimethoprim, ciprofloxacine, sulfamethoxazole, and clindamycine, the insect repellent N,N -diethyltoluamide (DEET), the pesticides MCPA and mecoprop, perfluoroalkyl substances (such as PFOS and PFOA), caffeine, and gadolinium. 1. Introduction European Commission Directive 91/271/EEC (EC, 1991) concerns the collection, treatment and discharge of urban wastewater and the treatment and discharge of wastewater from certain industrial sectors. Its aim is to protect the environment from any adverse effects caused by the discharge of such waters. The increasing extent and level of municipal wastewater treatment in Europe in the past decades has significantly improved the quality of surface waters, even though obligations set for the European Union are not equally fulfilled by all its members (EC, 2004; Reemtsma et al., 2006). However, priority substances or other organic compounds are not regulated in wastewater treatment plant (WWTP) effluents (EC, 1991), but in surface waters under the Water Framework Directive (EC, 2000). Whilst household and industrial wastewater treatment has been implemented ACCEPTED MANUSCRIPT progressively across Europe, and existing treatment technologies produce water that meets current legislation on water-quality standards, it has been demonstrated that the

94 ACCEPTED MANUSCRIPT removal of many emerging (i.e. not yet regulated) contaminants, including pharmaceuticals and personal care products (PPCPs), hormones, and other industrial chemicals is incomplete. Various studies over recent years have shown that treated municipal wastewater contributes significantly to water pollution from micropollutants (e.g.: Ashton et al., 2004; Castiglioni et al., 2006; Clara et al., 2005; De la Cruz et al., 2012; Gabet-Giraud et al., 2010; Gracia-Lor et al., 2010, 2012; Gros et al., 2010; Hollender et al., 2009; Jelic et al., 2012; Joss et al., 2005, 2006; Kasprzyk-Hordern, et al., 2009; Köck-Schulmeyer et al., 2011; Lindqvist et al., 2005; Martínez Bueno et al., 2012; Micropoll, 2011; 2012; Miège et al., 2009; Nakada et al., 2006; Paxéus, 2004; Radjenović et al., 2007a,b; Reemtsma et al., 2006; Ternes, 1998; Vieno et al., 2007; Verlicchi et al., 2012; Zhang et al., 2008a). Conventional WWTPs are designed to remove pathogens and coliforms and to reduce loads of carbon, nitrogen, and phosphorus. In addition, many non-polar chemical compounds are well removed by sorption to sludge. Other important removal pathways of organic compounds during wastewater treatment are biotransformation / biodegradation, and stripping by aeration (volatilization) (Radjenović et al., 2007a). Several polar compounds, especially those which are poorly degradable, may however be discharged with WWTP effluents into receiving waters and then occur in surface waters (Reemtsma et al., 2006). Some polar chemical compounds such as nonylphenol (Yu et al., 2009; Zhang et al., 2008b) or perfluoroalkyl substances (PFASs) such as perfluorooctansulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) (Becker et al., ACCEPTED MANUSCRIPT ) are even formed in WWTPs from precursor compounds.

95 ACCEPTED MANUSCRIPT In 2006, Reemtsma and co-workers published the first EU-wide study on the occurrence of polar organic pollutants in WWTP effluents and the receiving surface waters. In their study, the effluents of eight municipal WWTPs in Western Europe were analyzed by liquid chromatography - mass spectrometry (LC-MS) for the occurrence of 36 polar pollutants, comprising PPCPs and other household and industrial chemicals. Half of the determined compounds were not significantly removed in tertiary wastewater treatment with enhanced nutrient removal (Reemtsma et al., 2006). In the last years, several fate studies on the occurrence and behavior of PPCPs, endocrine disruptors, illicit drugs, and other industrial chemicals have been performed. The efficiency of the removal of PPCPs (and other compounds) was found to be strongly dependent on the technology implemented in the WWTP (Hollender et al., 2009; Kasprzyk-Hordern, et al., 2009; Vieno et al., 2007). The main objective of this study was to assess the occurrence of as many as possible polar organic chemical contaminants in WWTP effluents as well as relevant biological endpoints such as estrogenicity, on a European scale (Gawlik et al., 2012). In this study 90 WWTPs across Europe were sampled, 156 chemicals were measured and four different toxicity assays were conducted on selected samples. 2. Materials and Methods ACCEPTED MANUSCRIPT 2.1. EU-wide sampling campaign, sample transport and storage The identity of the individual 90 WWTPs investigated in this study cannot be disclosed in this publication. The samples came from Austria (number of samples: 6), Belgium (18), Czech Republic (7), Cyprus (2), Finland (6), France (5), Germany (2), Greece (2),

96 ACCEPTED MANUSCRIPT Hungary (2), Ireland (2), Italy (2), Lithuania (3), Netherlands (11), Portugal (2), Slovenia (1), Spain (3), Sweden (11), and Switzerland (5). The selection of the WWTPs was done autonomously by the participating EU Member States; no selection criteria were given by the JRC (Joint Research Centre). On the other hand, the participants were aware of the aims of the study and therefore most of them provided samples of wastewaters treated by WWTPs of different / variable capacities and wastewater sources (domestic, industrial, rain). Around half of the plants provided us with information on the plant capacity (m 3 /d) and the population equivalents, which was in the range of <1000 up to over 1 million (for at least 3 plants); i.e. WWTPs of all sizes were investigated in this study. Thus, the selection of the plants was quite representative of the EU. Mainly municipal WWTPs were investigated, but some plants were dominated by industrial wastewaters. Sampling was performed by grab sampling or in many cases also with automated systems, which resulted in 24h composite water samples. One liter water samples, stored in HDPE plastic bottles, were shipped to the JRC Ispra (Italy) by fast courier in thermostatic boxes with cooling elements; the samples were stored in a refrigerator at ~4 C, and further distributed as fast as possible to the other expert laboratories. The storage time for the samples (in the refrigerator) was in most cases between one and two months, which is the maximum accepted time to ensure stability of the samples (Gawlik et al., 2012; Vanderford et al., 2012) Selection of the target compounds ACCEPTED MANUSCRIPT The target compounds and toxicological endpoints analyzed in the different laboratories are given in the supporting information (SI). They were selected on the basis of previous experience (Loos et al., 2007; 2009a; 2010). An important compound selection criteria

97 ACCEPTED MANUSCRIPT was their known fate and behavior in the environment (e.g. water solubility or persistency), i.e. their environmental and toxic relevance (such as their endocrine disrupting potential). Another criteria was the availability of analytical procedures. The compounds analyzed by the JRC (Italy) (in 90 samples) comprise a group of 54 polar organic chemicals belonging to different categories: PPCPs, pesticides (and metabolites), benzotriazoles, perfluoroalkyl substances (PFAS), and artificial sweeteners (sucralose and acesulfame). The Umeå University (Sweden) analyzed 66 pharmaceutical compounds and 10 organophosphate ester flame retardants and plasticizers (in 89 samples). VITO (Belgium) analyzed 20 antibiotic compounds in 30 selected samples. IWW Water Centre (Germany) analyzed 6 x-ray contrast agents and gadolinium magnetic resonance imaging contrast media (73 samples). RECETOX (Czech Republic) assessed estrogenicity equivalents (EEQ) (75 samples) and dioxin-like toxicity (25 samples). Finally, the JRC (Italy) analyzed the acute toxicity to yeast and diatom cultures of the effluents by optical bioassays (13 samples) Analytical methods The analytical methods for the different compound classes are summarized below. More details can be found in the supporting information (SI) Multi-compound SPE-LC-MS-MS method (JRC-IES) The effluent water samples were extracted by solid-phase extraction (SPE) with 200 mg ACCEPTED MANUSCRIPT Oasis HLB cartridges (Waters) using an automated AutoTrace SPE workstation (Thermo Scientific). Before extraction, the samples (500 ml) were spiked with the internal standard, which contained the mass-labeled substances 13 C 3 -atrazine, carbamazepine-d10,

98 ACCEPTED MANUSCRIPT ,4-D-d3, estrone-d2, 13 C 3 -ibuprofen, MCPA-d3, 13 C 4 -PFOA, 13 C 5 -PFNA, 13 C 4 -PFOS, 13 C 3 -simazine, sucralose-d6, and triclosan-d10. The spiking level in the water samples was 10 ng/l for 13 C 4 -PFOA, 100 ng/l for the other labeled compounds. 13 C 5 -PFNA, and 13 C 4 -PFOS, 1 µg/l for sucralose-d6, and The cartridges were activated and conditioned with 5 ml methanol and 5 ml water (Milli-Q) at a flow-rate of 5 ml/min. The water samples (400 ml) were passed through the wet cartridges at a flow-rate of 5 ml/min, the columns rinsed with 2 ml water (3 ml/min), and the cartridges dried for 30 min using nitrogen at 0.6 bars. Elution was performed with 6 ml methanol (3 ml/min). Evaporation of the extracts with nitrogen gas to 500 µl was performed at a temperature of 35 C in a water bath using a TurboVap II Concentration Workstation (Caliper Life Sciences). Analyses were performed by reversed-phase liquid chromatography (RP-LC) followed by electrospray ionization (ESI) mass spectrometry (MS) detection with a triple-quadrupole MS-MS system (Agilent 1100 Series LC system coupled to a Quattro Micro MS from Waters). Quantitative LC-MS-MS analysis was performed in two separate runs in the multiple reaction monitoring (MRM) mode in negative and positive ionization. A Hypersil Gold column was used for the separations (Thermo Electron Corp., mm, 3µm). The eluents used were water (0.1% acetic acid) and acetonitrile. The flow-rate was 0.25 ml/min. The gradient started with 90% water and ACCEPTED MANUSCRIPT proceeded to 90% acetonitrile over 25 min, conditions hold for 5 min, returned back to the starting conditions over 5 min, and followed by 5 min equilibration. The injection volume was 5 µl.

99 ACCEPTED MANUSCRIPT Pharmaceuticals by SPE-LC-MS-MS (UMEA) A large number of pharmaceutical compounds were analyzed according the analytical method presented in Grabic et al. (2012) (see Tables SI1 and SI2). The water samples were extracted by SPE with Oasis HLB (200 mg) cartridges (Waters). Before extraction, the samples (100 ml) were filtered through a 0.45 µm membrane filter (MF, Millipore) and acidified to ph3 using sulphuric acid. Five nanograms of each internal surrogate standard were added to each sample. The glass bottles were closed, and then the samples were mixed by shaking. The internal standards used were: amitriptyline-d6, fluoxetine-d5 and 13 C-tramadol-d3 (Cambridge Isotope Laboratories), oxazepam-d5, promethazine-d7, risperidone-d4, and 13 C 15 2 N-tamoxifen (Sigma-Aldrich) (see SI). The cartridges were activated and conditioned with 5 ml methanol and 5 ml water at a flow-rate of 5 ml/min. The water samples were passed through the wet cartridges at a flow-rate of 5 ml/min, the columns rinsed with 2 ml water (flow 3 ml/min), and the cartridges dried for 10 min using air. Elution was performed with 5 ml methanol followed by 3 ml ethylacetate. The eluents were evaporated to 20 µl under a gentle air stream, and dissolved in 5% acetonitrile in water, with 0.1% formic acid, to a final volume of 1 ml. Analyses were performed by RP-LC followed by heated electrospray ionization (ESI), in positive and negative mode, mass spectrometry (MS) detection with a triplequadrupole MS-MS system. LC was performed with an Accela LC pump (Thermo Fisher ACCEPTED MANUSCRIPT Scientific) and a PAL HTC autosampler (CTC Analytics). Tandem mass spectrometry was performed on a bench-top triple-quadrupole TSQ Quantum Ultra EMR (Thermo Fisher Scientific).

100 ACCEPTED MANUSCRIPT The eluents used for the separations of the target analytes were water, methanol and acetonitrile. The water phase used was acidified with 0.1% formic acid. The elution conditions were programmed as follows: 200 µl/min of 100% water for 1 min followed by a gradient change to 20/20/60 water/acn/methanol at a flow of 250 µl/min in 8 min, and final gradient change to ACN/methanol 40/60 at a flow of 300 µl/min in 11 min. These parameters were held for 1 min and then changed to starting conditions and retained 4 min to equilibrate the column for the next run. The injection volume was 20 l (by autosampler) Organophosphate esters (OPEs) by LLE-GC-HRMS (UMEA) The organophosphate ester flame retardants analyzed were: tri-iso-butylphosphate (TIBP), tributylphosphate (TBP), tris(2-chloroethyl)phosphate (TCEP), tris(2-chloroisopropyl)phosphate (TCPP), tris(1,3-dichloro-2-propyl)phosphate (TDCP), tris(2- butoxyethyl)phosphate (TBEP), triphenylphosphate (TPP), 2-ethylhexyldiphenylphosphate (EHDPP), tris(2-ethylhexyl)phosphate (TEHP), and tricresylphosphate (TCP). The effluent samples (100 ml) were extracted according to Bester (2005) using liquidliquid extraction (LLE) with toluene after adding an aliquot of internal standard solution of 27 deuterated tri-n-butylphosphate (TBP-d27). The organic phase containing the organophosphate esters (OPEs) was separated from the aqueous one after freezing the samples overnight at minus 20 C. The extracts were then concentrated to approximately 1 ml by rotary evaporation, quantitatively transferred to conical GC vials, and further ACCEPTED MANUSCRIPT 222 reduced to 100 l under a gentle stream of nitrogen.

101 ACCEPTED MANUSCRIPT The samples were analyzed using a GC-HRMS high-resolution system consisting of an Agilent Technologies 6890 GC equipped with a CTC Analytics autosampler and coupled to a Micromass AutoSpec-Ultima MS tuned to a resolution of One l of each sample was injected into the GC, which was operated in splitless mode (2 min splitless time). The injector temperature was set to 250 C and gas chromatographic separation was carried out using a DB-5 fused silica capillary column (30 m 0.25 mm 0.25 m) from J&W Scientific (Folsom, CA). The GC oven was initially held at 80 C for 4 min, increased to 190 C at a rate of 15 C/min, and then at 10 C/min to the final temperature of 310 C, which was maintained for 4 min. Helium was used as a carrier gas at a flow rate of 1.3 ml/min. The MS was operated in selected ion monitoring (SIM) mode with electron ionization at 37 ev. The OPEs were identified by comparing mass fragment ratios and retention times of sample components and reference standards, and quantified using the internal standard technique, which automatically corrects the data for losses during sample work-up and analysis Antibiotics by SPE-UHPLC-MS-MS (VITO) The analytical method was optimized in order to cope with the diverse physico-chemical properties of the analytes of interest (Table SI4). Therefore, extractions of sample aliquot were performed at either ph3 or ph6. Tetracyclines and sulfonamides tend to form stable complexes with divalent metallic ions like calcium and magnesium. To prevent this ACCEPTED MANUSCRIPT complexation, the chelating agent Na 2 EDTA 2H 2 O (250 mg) was added (Díaz-Cruz and Barceló, 2006; Gros et al., 2006). For a limited set of analytes that were determined at ph6 the chelating agent was not used.

102 ACCEPTED MANUSCRIPT Each ph-adjusted extraction was performed on 250 ml of sample using Oasis HLB SPE cartridges (Waters). Sample pretreatment was performed as follows. For each effluent sample, 1 aliquot was acidified to ph3 and 2 aliquots to ph6 using 6 N HCl. After addition of 250 mg of Na 2 EDTA 2H 2 O the solution was shaken and stored for 2h. For extractions at ph3, the Oasis HLB SPE cartridges were conditioned with consecutively 20 ml of methanol, 6 ml of Milli-Q water and 6 ml of acidified water (ph2). For the extraction of the effluent samples at ph6 with and without addition of Na 2 EDTA 2H 2 O, the cartridges were conditioned with 20 ml of methanol and 12 ml of Milli-Q water. The samples were loaded on the SPE cartridges; then they were washed with 10 ml of Milli-Q water to remove residual EDTA and were consecutively dried under reduced atmospheric pressure. The compounds of interest were eluted with 20 ml of methanol. The extract was evaporated close to dryness and brought to a final volume of 0.5 ml using methanol. Recoveries above 80% were obtained for the majority of the compounds. The instrumental analysis was performed using a Waters Acquity UPLC system. The compounds of interest were separated on an Acquity BEH C 18 column (2.1 mm 150 mm, 1.7 µm). The column temperature was kept at 40 C. A gradient elution programme with water (0.1% formic acid) (solvent A) and acetonitrile (0.1% formic acid) (solvent B) was used. The flow rate of the mobile phase was 0.4 ml/min. An aliquot of ACCEPTED MANUSCRIPT 10 µl of the final extract was injected into the LC system. The UPLC system was coupled to a triple quadrupole MS detector (Micromass Quattro Premier XE, Waters), that was 266 operated in positive electrospray ionisation mode (ESI+).

103 ACCEPTED MANUSCRIPT X-ray contrast agents by LC-MS-MS (IWW Water Centre) Non filtered samples (1 liter) were acidified to ph3 using HCl (12.5%). Prior to extraction, samples were spiked with labeled internal standard substances (100 µl) to a spiking level of 5 ng/l (amidotrizoic acid-d6) and 20 ng/l (iopromide-d3) respectively. Sample processing was done by a manually operated SPE vacuum device BAKER SPE- 10 (Mallinckrodt Baker) using 3-ml SPE-cartridges filled with 200 mg embedded reversed phase Isolute ENV+ adsorbent (Biotage). The cartridges were activated and conditioned with 2 3 ml methanol/acetonitrile (50/50) and 2 3 ml blank water (ph3) ensuring that the adsorbent did not run dry. Water samples were passed through the wet cartridges at a flow-rate of 5 ml/min, thereafter the columns were rinsed with 2 3 ml water (ph7), and the cartridges dried for 60 min under reduced pressure using an air stream. Elution was performed with 5 2 ml methanol/acetonitrile (50/50). Concentration of extract was performed with a TurboVap LV Evaporation System from Caliper Life Sciences using a gentle stream of nitrogen. The temperature of the eluent during concentration was kept at 40 C by using a water bath. The final solvent volume was adjusted to 1 ml methanol/water (5/95). An aliquot was used for the LC-MS determination. HPLC analyses were performed by using a RP-LC column of the type Gemini C18 (150 mm 2 mm, 3 µm) from Phenomenex followed by positive electrospray ionization ACCEPTED MANUSCRIPT (ESI) mass spectrometry (MS) detection using atmospheric-pressure ionization (API) with a triple-quadrupole tandem mass spectrometric system (Waters TQD-MS-MS) Quantitative LC-MS-MS analysis was performed in the multiple reaction monitoring (MRM) mode (Table SI15).

104 ACCEPTED MANUSCRIPT Biological methods / in-vitro bioassays (RECETOX) Similarly to the chemical methods the water samples were extracted by SPE with Oasis HLB cartridges with only a few differences. A half liter of each water sample with suspended particle material was manually shaken to simulate turbulent conditions of wastewater effluent and filtered through glass fiber filter (2 µm, Fisher Scientific). Consequently, the samples were applied to the Oasis HLB SPE columns (500 mg, 6 ml). The columns were activated by 6 ml methanol and equilibrated by 8 ml distilled water without applying vacuum. Maximal pressure used for draining the samples was 0.3 bars and average flow rate approximately 5 ml/min. When the samples passed through the solid phase, the columns were left to dry for about 10 min, and consequently were gravimetrically eluted by 6 ml of methanol without use of any pressure. Finally, the eluents were concentrated under a gentle nitrogen stream at laboratory temperature to final volumes which corresponded to 1200-times concentrated original effluents. This aliquot was chosen as maximum concentration which was mostly not cytotoxic to the cells in our previous studies. Sample extracts were stored at -18 C until analyses. The results were expressed as estrogenic (EEQ) or dioxin-like equivalents (TEQbio) with respect to standard estrogen (17β-estradiol; E2), or dioxin (2,3,7,8-tetrachlorodibenzo-pdioxin; TCDD). Limits of detection for estrogenic and dioxin-like activity were 0.5 ng/l EEQ (estrogen equivalents) and 0.1 ng/l TEQ bio (dioxin toxic equivalents determined with the biotest), respectively. For the bioassay on estrogenic activity, the negative controls were cells in medium and cells in medium + solvent, the positive controls was ACCEPTED MANUSCRIPT β-estradiol (dilution series pm). Samples were always tested in triplicates.

105 ACCEPTED MANUSCRIPT Yeast and diatom culture bioassays (JRC-IES) The yeast Saccharomyces cerevisiae strain W303.1a was used for the cytotoxicity tests based on its sensitivity to oxidative stress. Cultures were grown on YNB medium supplemented with uracyl, tryptophan, leucine, histidine and adenine. The initial cell density was 10 7 cell/ml as estimated by optical density at 600 nm on a Tecan Infinite Pro spectrophotometer. Three technical and biological replicates were performed per condition. The diatom Thalassiosira pseudonana (strain CCMP 1335) was cultured at a density of 10 6 cells/ml in artificial seawater (ASW-f/2) with 32 g/l salinity. In addition, cultures were progressively adapted to lower salinities (24, 16 and 8 g/l), and maintained for at least one month prior to the tests. Cell densities were determined by optical density at 450 nm as previously described (Bopp and Lettieri, 2007). The wastewater samples were concentrated on a Vacufuge vacuum concentrator (Eppendorf AG, Hamburg, Germany) to half the volume and then filtered through a 0.22 µm filter membrane. The samples were added to the culture media and tested at 1:1 or 1:2 of the initial effluent concentration for both yeast and diatom bioassays. For those effluents eliciting cytoxicity, additional dilutions were tested for diatom to determine the lowest concentration causing an effect. Both yeast and diatom bioassay were optimized and adapted to a 96-well microtiter plate for fast-screening of multiple samples. Measured cell densities were corrected by removing the optical density contribution of ACCEPTED MANUSCRIPT each blank (effluent added to the culture media). The acute toxicity was determined at different time points covering the exponential growth phase in both organisms.

106 ACCEPTED MANUSCRIPT Results and Discussion 3.1. Chemical compounds identified Table 1 summarizes the analytical results for the polar organic chemical contaminants which were measured in the 90 WWTP effluents across Europe. The compounds are sorted according to their frequency of detection (Freq. in %) and highest medium concentrations; 125 out of the 156 target substances were found at least once (percentage of 80 %). Put here Table Frequency of detection The high overall frequency of detection of the organic micropollutants investigated is shown by the percentile frequency (Freq.) of detection (Table 1). The average frequency of detection for all 156 compounds was 43%. The most frequently detected compounds are reported at the top of the table (13 with a frequency of 100 %, which were detected in all samples). Twenty seven compounds (out of 156) were not detected in any of the samples. In addition, it must be noted that also 17β-estradiol, 17α-ethinylestradiol, and estrone were analyzed within the multi-compound screening method (negative ESI method) in all samples (by JRC), but these estradiol hormones were not detected in any of the samples above the LOQ of ~ 10 ng/l Median concentrations and 90 th percentiles The compounds with the highest median concentration levels measured are depicted in ACCEPTED MANUSCRIPT Figure 1. These chemicals are of high relevance in WWTP effluents. In addition, the 90 th percentile values of the data (Table 1) can give an indication of compounds whose

107 ACCEPTED MANUSCRIPT concentrations greatly exceed typical values (e.g. above 1 µg/l, 200 or 100 ng/l). These values can also be used to identify effluents with higher than usual concentrations of specific micropollutants (as compared to an average WWTP). In addition, box-whisker plots, giving a full graphical statistical evaluation, have been produced for the 30 most relevant compounds (Figure SI2). Put here Figure Maximum concentrations The (single) maximum concentrations found for the contaminants are of relevance, too, because under the Water Framework Directive there are in addition to the annual average environmental quality standards (AA-EQS) also maximum allowable EQS values (MAC- EQS), which are acute toxicity standards that must not be exceeded in any sample (of surface water). The highest concentrations were found for the chemicals acesulfame (2.5 mg/l), 1H-benzotriazole (221 µg/l), iopromide (150 µg/l), TBEP (43 µg/l), methylbenzotriazole (24 µg/l), PFHxA (23.9 µg/l), TCPP (21 µg/l), irbesartan (17.9 µg/l), PFOA (15.9 µg/l), DEET (N,N -diethyltoluamide) (15.8 µg/l), sucralose (12.9 µg/l), iomeprol (12.0 µg/l), amidotrizoic acid (8.4 µg/l), iohexol (7.7 µg/l), eprosartan (6.8 µg/l), iopamidol (6.1 µg/l), EHDPP (5.4 µg/l), carbamazepine (4.6 µg/l), telmisartan (4.3 µg/l), triclosan (4.3 µg/l), gemfibrozil (3.6 µg/l), linuron (3.2 µg/l), caffeine (3.0 µg/l), PFHpA (3.0 µg/l), PFNA (2.7 µg/l), haloperidol (2.7 µg/l), terbutylazine ACCEPTED MANUSCRIPT (2.4 µg/l), loperamide (2.4 µg/l), MCPA (2.4 µg/l), TCEP (2.4 µg/l), mecoprop (2.2 µg/l), ibuprofen (2.1 µg/l), PFOS (2.1 µg/l), oxazepam (1.8 µg/l), TBP (1.7 µg/l), sulfamethoxazole (1.7 µg/l), PFDA (1.7 µg/l), ketoprofen (1.7 µg/l), terbutylazine- desethyl (1.5 µg/l), diuron (1.4 µg/l), memantine (1.3 µg/l), etc.

108 ACCEPTED MANUSCRIPT Comparison with other WWTP studies A comparison with other WWTP studies is important for the interpretation of the results In the EU-wide WWTP study performed by Reemtsma and co-workers (2006) (see introduction), the complexing agent EDTA (ethylenediaminetetraacetic acid), which was not analyzed in our study, was the substance with by far the highest median concentrations (60 µg/l). Moreover, very high concentrations (median: 57 µg/l) were found in this study for sulfophenyl carboxylates, a group of biodegradation intermediates of the anionic surfactants LAS (linear alkylbenzene sulfonates). In our study, the highest median concentration was found for acesulfame (14.3 µg/l), followed by the benzotriazoles (1H-benzotriazoles and 4- and 5-methylbenzotriazole). The median concentration of 1H-benzotriazole (2.7 µg/l) corresponds very well to the study by Reemtsma et al. (2006), who found a median of 2.9 µg/l. Other compounds determined by Reemtsma et al. (2006) at relatively high levels (µg/l range) were benzothiazoles, naphthalenedisulfonates, and nonylphenolethoxy-carboxylates (NPECs), the predominant biodegradation intermediates of NPEO (nonylphenol-ethoxylates) surfactants (not analyzed in our study). In the Swiss Micropoll Strategy project (Micropoll, 2011; 2012), 47 Swiss-specific micropollutants were identified out of 250 candidate substances (using a prioritization procedure), representative for the contamination caused through micropollutants from municipal wastewater. Similar average effluent concentrations were found for many of these substances in our study (see Table SI16). ACCEPTED MANUSCRIPT

109 ACCEPTED MANUSCRIPT Perfluoroalkyl substances (PFASs) The discharge of municipal wastewaters is one of the principal routes of entry of perfluoroalkyl substances such as PFOA and PFOS into the aquatic environment. Often PFAS concentrations increase in WWTPs as a result of biodegradation of precursors during the activated sludge process. PFOA is generally fully discharged into receiving rivers, while about half of PFOS is retained in the sewage sludge (Becker et al., 2008, 2010; Guo et al., 2010; Huset et al., 2008). The most frequent PFAS found in our study was PFOA (detection frequency of 99%), followed by PFHpA (C7; 94%), PFOS (93%), PFNA (C9; 89%), PFDA (C10; 81%), PFHxA (C6; 71%), and PFHxS (C6; 70%). PFOA was also detected at the highest median concentration levels (12.9 ng/l), followed by PFOS (12.2 ng/l), PFHxA (5.7 ng/l), PFHpA (5.1 ng/l), PFHxS (3.4 ng/l), PFDA (2.9 ng/l), and PFNA (2.3 ng/l). The highest (single) maximum concentrations were found for PFHxA (23.9 µg/l), and PFOA (15.9 µg/l), followed by PFHpA (3.0 µg/l), PFNA (2.7 µg/l), PFOS (2.1 µg/l), PFDA (1.7 µg/l), and PFHxS (922 ng/l) in industrial WWTPs. Similar PFAS levels in the ng/l range are reported in the literature from Europe, USA, and Asia (Table SI17). Despite the voluntary phasing out of the production of perfluorooctane sulfonyl-based chemicals in 2002 (by the main producers), and European restrictions on the marketing and use in 2006 (EC, 2006), the detection of PFOS in ACCEPTED MANUSCRIPT WWTPs indicates that products containing PFASs are still releasing these substances into 419 the environment.

110 ACCEPTED MANUSCRIPT Benzotriazoles Benzotriazoles are compounds with high water solubility and a high polarity; they are moderately persistent against biological and photochemical degradation processes in WWTPs and the aquatic environment. The occurrence of benzotriazoles in municipal wastewaters is caused by its application as anticorrosive additives in dishwasher products, but there are also many industrial applications (Janna et al., 2011). Median concentrations found in our EU-wide WWTP study were 2.7 µg/l for 1Hbenzotriazole (BT), and 2.1 µg/l for methylbenzotriazole (mixture of 4- and 5-isomers, also called tolyltriazoles; TT), with maximum values up to 221 µg/l and 24.3 µg/l for BT and TT, respectively. These levels are in relatively good agreement with the literature (mainly from Berlin and Switzerland; Table SI18). The 4- and 5-TT isomers are not separated in routine LC-MS. Therefore, we report the mixture of both isomers. According to literature, the 4-isomer is more stable in the environment (De la Cruz et al., 2012; Reemtsma et al., 2010; Voutsa et al., 2006; Weiss et al., 2006) Pharmaceuticals and personal care products (PPCPs) The removal of PPCPs in WWTPs has been investigated in several comprehensive studies before. State of the art biological treatment schemes for municipal wastewater are very effective for easily biodegradable compounds such as ibuprofen with elimination rates of around 90%. Conventional WWTPs, however, are less efficient in degrading moderately persistent pharmaceutical compounds such as diclofenac, naproxen, ACCEPTED MANUSCRIPT bezafibrate, sulfonamide and macrolide antibiotics, or beta blockers, with eliminations usually between 20 and 80%. Carbamazepine and sulfamethoxazole are almost

111 ACCEPTED MANUSCRIPT completely persistent during activated sludge treatment (Clara et al., 2005; Lindqvist et al., 2005; Hollender et al., 2009; Joss et al, 2006; Michael et al., 2013; Radjenović et al., a). We compared the concentrations of the pharmaceuticals found in the WWTP effluents with several literature studies. This comparison shows that lower median effluent concentrations were found in our large-scale European-wide study (n=90) compared to local studies of single WWTPs (Miége et al., 2009; Table SI19). Also Reemtsma and co-workers (2006) found for many pharmaceuticals (diclofenac, ibuprofen, ketoprofen, naproxen, bezafibrate, carbamazepine, clofibric acid, and sulfmethoxazole) median concentrations in the range of µg/l in WWTP effluents. A reason for the lower median pharmaceutical concentrations in our study might be that also several industrial WWTPs were included in the study. Maximum and average concentrations were, however, in relatively good agreement. Some examples of important studies are given here. For example, the maximum effluent concentrations were for most compounds in quite good agreement with a study in seven WWTPs in the main cities along the Ebro river basin (north-east of Spain) (Gros et al., 2010), except for diclofenac, carbamazepine, and ranitidine (Table SI20). A comparison with the municipal WWTP of the city Lausanne (CH) shows a relatively good agreement for most of the substances (average ACCEPTED MANUSCRIPT concentrations), with the exception of only bezafibrate and diclofenac (De la Cruz et al., 2012) (Table SI21). Rosal et al. (2010) performed a one-year survey of the WWTP of Alcalá de Henares (Madrid, Spain) by studying the occurrence and fate of 84 pollutants (mainly PPCPs). The maximum and average concentrations in this study were similar to

112 ACCEPTED MANUSCRIPT our study for around half of the compounds (Table SI22). A five-month monitoring program was undertaken in South Wales in the UK to determine the fate of 55 PPCPs, endocrine disruptors and illicit drugs in two different WWTPs (Kasprzyk-Hordern et al., 2009). The maximum concentrations of the substances studied were relatively similar to our study for several pharmaceuticals (trimethoprim, ibuprofen, diclofenac, naproxen, carbamazepine, clofibric acid, and bezafibrate); the median concentrations of our study were in most cases much lower (Table SI23). The comparison with a study by Martínez Bueno et al. (2012) who carried out an almost two-year monitoring program in five municipal WWTPs located in the north, centre and south-east of Spain, shows a good agreement with our results for about 50% of the pharmaceuticals (Table SI24). An interesting pharmaceutical is diclofenac, because it has been proposed as a new priority substance under the European Water Framework Directive. A comparison of our effluent concentrations found for diclofenac with literature data showed relatively low levels in our study (maximum: 174 ng/l, median 43 ng/l, average 50 ng/l) (Table SI25). A reason might be problems with different analytical standards, as noticed also during two interlaboratory studies on non-steroidal anti-inflammatory drugs (NSAIDs) (Farré et al., 2008; Heath et al., 2010). Triclosan is an antimicrobial agent used in a multitude of household products; in WWTPs around 90% of the incoming triclosan is removed from the water, by ACCEPTED MANUSCRIPT degradation and adsorption to sludge (Bester, 2003; Heidler and Halden, 2008; Singer et al., 2002), which is a high but not complete removal. Indeed, it has been found in WWTP effluents as well as in surface water and ground water (and sewage sludge) in many countries (Chen et al., 2012b). The concentrations of triclosan found in our EU-wide

113 ACCEPTED MANUSCRIPT study (maximum: 4.3 µg/l; average: 75 ng/l) are in relative good agreement with other local European studies (Table SI26) Pesticides In comparison to PPCPs, less information is available on the occurrence of pesticides in WWTPs (De la Cruz et al., 2012; Hollender et al., 2009; Martínez Bueno et al., 2012; Singer et al., 2010), because diffuse agricultural field run-off might be more relevant for the contamination of surface (and ground) waters with pesticides. The average DEET (insecticide) concentration found in our study (678 ng/l) is comparable with those found in the Swiss Micropoll Project (593 ng/l) (Micropoll, 2011; 2012). Moreover, Table SI27 shows a good agreement of our data with literature for the average effluent concentrations of diuron, desethylatrazine, isoproturon, linuron, simazine, and mecoprop (De la Cruz et al., 2012; Hollender et al., 2009; Martínez Bueno et al., 2012; Singer et al., 2010) Sweeteners acesulfame and sucralose Acesulfame and sucralose were recently identified as ubiquitous and emerging environmental contaminants. These artificial sweeteners are not eliminated in WWTPs and are persistent in surface and coastal waters (Buerge et al., 2009; Loos et al., 2009b; Mead et al., 2009; Oppenheimer et al., 2011; Scheurer et al., 2009). The maximum ACCEPTED MANUSCRIPT (2.5 mg/l for acesulfame and 13 µg/l for sucralose) and medium concentration levels (14.3 µg/l for acesulfame and 1.7 µg/l and sucralose) are in good agreement with literature data (Buerge et al., 2009; Hollender et al., 2009; Scheurer et al., 2009). Acesulfame was the substance with the highest overall concentrations found in our study.

114 ACCEPTED MANUSCRIPT Organophosphate ester flame retardants Organophosphate esters are (emerging) high-production-volume chemicals used as flame retardants and plasticizers to protect or to enhance the properties of plastics, textiles, furniture and many other materials. Chlorinated organophosphate esters flame retardants are hardly removed in WWTPs (Reemtsma, et al., 2008). Table 1 shows that these chemicals were among the most relevant substances investigated in our study. The median concentration levels found (TCPP 620 ng/l, TCEP 71 ng/l, and TBEP 190 ng/l) are in good agreement with the European WWTP survey by Reemtsma and co-workers (2006) (TCPP and TCEP mean concentrations: 0.6 and 0.2 µg/l, respectively), and an Austrian study in 16 WWTPs (median of TCPP, TCEP, and TBEP: 580 ng/l, 74 ng/l, and 130 ng/l, respectively; Martínez-Carballo et al., 2007). Nowadays, TCPP is more prominent in effluents than TCEP, reflecting the phasing out of the latter X-ray contrast agents X-ray contrast agents were only found in some WWTP effluents (detection frequency between %), because they are often related to hospital effluents. However, they are also present in municipal WWTP effluents because they are excreted out of the human body over ~24h after treatment (Pérez et al., 2007). A very high single maximum concentration was found for iopromide with 150 µg/l in one sample. The average concentrations found in our study (iopromide 2.7 µg/l, amidotrizoic acid 619 ng/l, iomeprol 376 ng/l, iohexol 158 ng/l, iopamidol 144 ng/l) are in very good agreement with ACCEPTED MANUSCRIPT 530 the Micropoll Project in Switzerland (Micropoll, 2011; 2012) (Table SI28).

115 ACCEPTED MANUSCRIPT Bioanalytical results (estrogenity and dioxin like activity) From the total number of 75 analyzed WWTP effluents, 27 sample extracts showed estrogenic activity higher than the detection limit > 0.5 ng/l EEQ (estrogen equivalents). Estrogenic activity varied (in positive samples) from 0.53 to 17.9 ng/l EEQ. The median of all tested samples was < 0.5 ng/l EEQ. These levels of detected EEQs are well comparable to the results of previous studies evaluating estrogenic activity of European WWTP effluent samples by different in vitro bioassays (Table SI29). To evaluate approximate levels of dioxin-like activity, 25 WWTP effluent sample extracts were studied. Twenty one out of the 25 tested sample extracts exceeded the detection limit (0.10 ng/l TEQ bio ) but the maximum detected dioxin-like activity was relatively low, reaching only 0.44 ng/l TEQ bio with median around 0.15 ng/l TEQ bio. A comparison with a limited number of previously published studies on dioxin-like activity in dissolved water phase is given in Table SI Acute toxicity to yeast and diatoms Toxicity tests were conducted on a representative subset of thirteen WWTPs (coming from different countries) to analyze the potential hazard to organisms posed by complex mixtures of chemicals, even if they are present at low concentrations when considered independently. Effluents were analyzed for their cytotoxic effect regarding the growth of the yeast Saccharomyces cerevisiae and the marine diatom Thalassiosira pseudonana. The effect elicited by the different effluents was quite comparable between yeast and diatom ACCEPTED MANUSCRIPT cultures. Most of the effluents were not harmful to any of the organisms. Five of the tested effluents even induced an increase in the growth of the cultures, more evidenced in the case of diatom (Figure SI3). The higher growth upon exposure to these effluents may

116 ACCEPTED MANUSCRIPT indicate an abnormal enrichment in nutrients, which is particularly relevant to autotrophic organisms like diatom, and may be an indication of the eutrophication potential of the effluent water. From the 13 effluent waters tested, only three induced cytotoxicity in both organisms. By using different effluent dilutions in both organisms it was possible to rank the effluents according to the dose-dependent toxicity elicited and strikingly both bioassays provided the same ranking results. In addition, the use of a secondary stress condition in diatoms, i.e. decreased salinity, increased the sensitivity of the assay and allowed the detection of a toxic effect at lower WWTP effluent dilutions. One of the three WWTP effluents causing cytotoxicity in both diatom and yeast contained diuron at 1.4 µg/l. This was the highest concentration found in all the WWTP effluents analyzed, and is above the annual average environmental quality standard (AA-EQS) of 0.2 ug/l. In addition, we have data confirming a slight effect of diuron at this concentration, causing growth inhibition in diatom (data not shown). This suggests that this compound is likely one of the major toxicants in the effluent, although it could only explain 10-20% of the observed effect. In contrast, none of the chemicals analyzed in the two other WWTP effluents, could explain the caused cytotoxicity. While it is difficult to link the observed toxicity in some WWTP effluents to the presence of any single chemical (measured in this study or others), the data shows the importance in addressing the whole chemical composition of the water samples in addition to the concentration of single compounds. 4. Conclusions ACCEPTED MANUSCRIPT This European-wide monitoring study on the occurrence of organic micropollutants in WWTP effluents represents the largest EU wide monitoring survey on WWTP effluents

117 ACCEPTED MANUSCRIPT ever performed. It produced a comprehensive data set on many so far only locally investigated emerging compound classes including pharmaceuticals and personal care products (PPCPs), veterinary (antibiotic) drugs, perfluoroalkyl substances (PFASs), organophosphate ester flame retardants, pesticides (and some metabolites), industrial chemicals such as benzotriazoles (corrosion inhibitors), x-ray contrast agents, and gadolinium compounds. European-wide monitoring surveys are important for the prioritization of emerging pollutants under the Water Framework Directive. It is being discussed in Europe to upgrade WWTPs with additional tertiary or complementary treatment steps such as ozonation and/or powdered activated carbon adsorption to remove micropollutants from WWTP effluents to improve water quality. Under the view of escalating population growth, and increased water stress in many regions of the world, reuse of treated water and wastewater recycling are becoming more important options for water supply. The increasing worldwide contamination of freshwater systems with thousands of industrial and natural chemical compounds is one of the key environmental problems facing humanity. Although most of these compounds are present at low concentrations, many of them raise considerable toxicological concerns, particularly when present in complex mixtures (Schwarzenbach et al., 2006). This was confirmed in the present study by specific in vitro biodetection tools as well as by significant toxicity induced by some of the tested WWTP effluents in two aquatic organisms. ACCEPTED MANUSCRIPT

118 ACCEPTED MANUSCRIPT Acknowledgements The activity was supported by numerous persons at various wastewater treatment plants who contributed to the success of this campaign. Thanks to all of them. For the sake of anonymity of the sampling stations, we cannot list them more precisely. The provided single samples are insufficient to make any statement on the efficiency of the water treatment process. Umeå University acknowledges the Swedish Environmental Protection Agency for financial support. Supplementary data A huge amount of supplementary data (supporting information; SI) related to this article can be found online at ACCEPTED MANUSCRIPT

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125 ACCEPTED MANUSCRIPT Radjenović, J., Petrović, M., Barceló, D., 2007a. Advanced mass spectrometric methods applied to the study of fate and removal of pharmaceuticals in wastewater treatment. Trends in Analytical Chemistry 26, Radjenović, J., Petrović, M., Barceló, D., 2007b. Analysis of pharmaceuticals in wastewater and removal using a membrane bioreactor. Analytical and Bioanalytical Chemistry 387, Reemtsma, T., Weiss, S., Mueller, J., Petrović, M., Gonzalez, S., Barceló, D., Ventura, F., Knepper, T., Polar pollutants entry into the water cycle by municipal wastewater: A European perspective. Environmental Science & Technology 40, Reemtsma, T., Benito Quintana, J., Rodil, R., García-López, M., Rodríguez, I., Organophosphorus flame retardants and plasticizers in water and air. I. Occurrence and fate. Trends in Analytical Chemistry 27, Reemtsma, T., Miehe, U., Duennbier, U., Jekel, M., Polar pollutants in municipal wastewater and the water cycle: Occurrence and removal of benzotriazoles. Water Research 44, Scheurer, M., Brauch, H.-J., Lange, F.T., Analysis and occurrence of seven artificial sweeteners in German waste water and surface water and in soil aquifer treatment (SAT), Analytical and Bioanalytical Chemistry 394, Singer, H., Müller, S., Tixier, C., Pillonel, L., Triclosan: Occurrence and fate of a widely used biocide in the aquatic environment: field measurements in wastewater treatment plants, surface waters, and lake sediments. Environmental Science & Technology 36, Singer, H., Jaus, S., Hanke, I., Lück, A., Hollender, J., Alder, A.C., Determination of biocides and pesticides by on-line solid phase extraction coupled with mass spectrometry and their behaviour in wastewater and surface water. Environmental Pollution 158, ACCEPTED MANUSCRIPT

126 ACCEPTED MANUSCRIPT Ternes, T.A., Occurrence of drugs in German sewage treatment plants and rivers. Water Research 32, Vanderford, B.J., Drewes, J.E., Hoppe-Jones, C., Eaton, A., Haghani, A., Guo, Y., Snyder, S.A., Ternes, T., Schluesener, M., Wood, C.J., Evaluation of analytical methods for EDCs and PPCPs via interlaboratory comparison. ISBN ; Water Research Foundation. Verlicchi, P., Al Aukidy, M., Zambello, E., Occurrence of pharmaceutical compounds in urban wastewater: Removal, mass load and environmental risk after a secondary treatment - A review. Science of the Total Environment 429, Vieno, V., Tuhkanen, T., Kronberg, L., Elimination of pharmaceuticals in sewage treatment plants in Finland. Water Research 41, Voutsa, D., Hartmann, P., Schaffner, C., Giger, W., Benzotriazoles, alkylphenols and bisphenol A in municipal wastewaters and in the Glatt River, Switzerland. Environmental Science and Pollution Research 13 (5), Weiss, S., Jakobs, J., Reemtsma, T., Discharge of three benzotriazole corrosion inhibitors with municipal wastewater and improvements by membrane bioreactor treatment and ozonation. Environmental Science & Technology 40, Yu, Y., Zhai, H., Hou, S., Sun, H., Nonylphenol ethoxylates and their metabolites in sewage treatment plants and rivers of Tianjin, China. Chemosphere 77, 1 7. Zhang, Y, Geißen, S.-U., Gal, C., 2008a. Carbamazepine and diclofenac: Removal in wastewater treatment plants and occurrence in water bodies. Chemosphere 73, Zhang, J., Yang, M., Zhang, Y., Chen, M., 2008b. Biotransformation of nonylphenol ethoxylates during sewage treatment under anaerobic and aerobic conditions. Journal of Environmental Science 20 (2), ACCEPTED MANUSCRIPT 834

127 ACCEPTED MANUSCRIPT FIGURE and TABLE Captions Fig. 1: Medium concentrations of the target compounds (90 samples). Excluded is acesulfame (14.3 µg/l). Table 1: Summary of analytical results for chemicals in EU WWTP effluents. The compounds are sorted according to their frequency of detection (Freq. in %) and highest medium concentrations; Max. is the maximum concentration found, Med. the median concentration, and Per90 the 90 th percentile; calculated from all samples (not only the positive); levels below LOQ were set as zero; priority substances of the WFD in blue font; Gadolinium in red (the only inorganic substance). ACCEPTED MANUSCRIPT

128 ACCEPTED MANUSCRIPT Table 1: Summary of analytical results for chemicals in EU WWTP effluents. Chemical LOQ [ng/l] Freq. [%] Max. [ng/l] Average [ng/l] Med. [ng/l] Per90 [ng/l] Methylbenzotriazole µg/l 2.9 µg/l 2.1 µg/l 4.7 µg/l TCPP, Tris(2-chloroisopropyl)-phosphate µg/l Tramadol DEET, N,N -Diethyltoluamide µg/l TBEP, Tris(2-butoxyethyl)phosphate µg/l TBP, Tributylphosphate TIBP, Tri-iso-butylphosphate TDCP, Tris(1,3-dichloro-2-propyl)phosphate Irbesartan µg/l TCEP Tris(2-chloroethyl)phosphate Gadolinium TPP, Triphenylphosphate Risperidone Venlafaxine PFOA, Perfluorooctanoic acid µg/l Fluconazole Codeine Diphenhydramine Repaglinide H-Benzotriazole µg/l 6.3 µg/l 2.7 µg/l 10.9 µg/l Bisoprolol Flecainide EHDPP, 2-Ethylhexyldiphenyl-phosphate PFHpA, Perfluoroheptanoic acid Acesulfame mg/l 76 µg/l 14.3 µg/l 61 µg/l Trimethoprim Caffeine PFOS, Perfluorooctansulfonate Alfuzosin Bupropion Carbamazepine Ciprofloxacine Oxazepam Diclofenac* PFNA, Perfluorononanoic acid Sucralose µg/l 2.6 µg/l 1.7 µg/l 6.1 µg/l Memantine Orphenadrine Sulfamethoxazole (VITO) Citalopram Haloperidol Sulfamethoxazole (JRC) PFDA, Perfluorodecanoic acid Fexofenadine MCPA Diltiazem Diuron ACCEPTED MANUSCRIPT

129 ACCEPTED MANUSCRIPT Terbutaline Clindamycine Mecoprop ,4-D PFHxA µg/l Diazinon PFHxS, Perfluorohexansulfonate Atrazine Terbutylazine Naproxen Telmisartan Bezafibrate Eprosartan Gemfibrozil Zolpidem Ibuprofen Terbutylazine-desethyl Hydroxyzine Isoproturon Ketoprofen Bentazone Amidotrizoic acid µg/l µg/l Trihexyphenidyl Ranitidine Nitrophenol Triclosan* Levamisole Lincomycine Rosuvastatin Iopromide µg/l 2.7 µg/l µg/l Biperiden Penicilline V Clotrimazole Metolachlor Dichlorprop Mianserin Simazine Clofibric Acid Dinitrophenol Atrazine-desethyl Iomeprol µg/l Fluoxetine Clomipramine Iohexol µg/l Iopamidol µg/l Sertraline Tiamuline Clonazepam Chlortoluron Carbaryl Hexazinone ACCEPTED MANUSCRIPT

130 ACCEPTED MANUSCRIPT Loperamide Alprazolam Pizotifen Fenofibrate Nefazodone Linuron Buprenorphin Fentanyl Methabenzthiazuron Cilazapril Maprotiline Sulfadiazine Tilmicosine Flumequine ,4,5-T Cyproheptadine Glibenclamide Amitryptiline Tamoxifen Duloxetine TCP, Tricresylphosphate Atorvastatin Verapamil Miconazole Chlorpromazine Flupetixol Flutamide Substances not identified (detected): Alachlor, Azelastine, Bromocriptin, Chloprothixen, Clemastine, Dicycloverine, 17β-Estradiol, Estrone, 17α-Ethinylestradiol, Etonogestrel, Fluphenazine, Flupentixol, Glimepiride, Iothalamic acid, Meclozine, Metoxuron, Paroxetin, Perphenazine, Promethazin, TEHP, Oxytetracycline, Doxycycline, Penicilline G, Amoxicilline, Ampicilline, Florfenicol, Tylosine, Sulfadoxine, Enrofloxacine, Fenbendazole. In addition, PFBS could not be detected due to a chromatographic interference. * 1 Diclofenac: It might be possible that the levels for Diclofenac are higher than reported here (see section ) * 2 Triclosan levels are probably the double of the reported concentrations because the used HDPE bottles are not recommended for use when sampling for this compound (due to adsorption) (Vanderford et al., 2012, chapter 2, page 19). ACCEPTED MANUSCRIPT

131 ACCEPTED MANUSCRIPT 2500 Median concentrations (ng/l) ACCEPTED MANUSCRIPT

132

133 Článek IV Příloha IV

134 Europe-wide monitoring of estrogenicity in waste water treatment plant effluents Barbora Jarošová 1, A. Erseková 1, K. Hilscherová 1, R. Loos 2, B. Gawlik 2, J. P. Giesy 3, L. Bláha 1* 1 Masaryk University, Faculty of Science, RECETOX, Kamenice 5, CZ Brno, Czech Republic 2 European Commission - DG Joint Research Centre (JRC), Institute for Environment and Sustainability (IES), Ispra, Italy 3 University of Saskatchewan, Department of Veterinary Biomedical Sciences, 44 Campus Drive, Saskatoon, SK, Canada, S7N 5B3 *Corresponding author (blaha@recetox.muni.cz, ) Abstract Although the presence of emerging pollutants including estrogenic compounds in the environment has been extensively studied in the last decades, many questions related to their occurrence and risks have not been fully resolved yet. In 2010, pan-european monitoring campaign of Waste Water Treatment Plant (WWTP) effluents was conducted. Snap-shot samples from 90 European WWTP effluents were collected and analyzed for estrogenicity (using MVLN in vitro reporter gene assay) and for more than 150 polar organic and 20 inorganic compounds to obtain a comprehensive overview on many so far only locally investigated compound classes. Instrumental analyses did not detect any steroidal estrogens in any of these samples above the quantification limit of 10 ng/l. However, the effect-based monitoring approach with the MVLN cell line showed significant estrogenic activity above the limit of detection 0.5 ng 17-beta estradiol equivalents per liter (ng EEQ/L) in 27 out of 75 samples tested. The estrogenicity ranged from 0.53 to 17.9 ng EEQ/L. The greatest activities were detected in WWTPs at some of the major European cities indicating the importance of this contamination source. Beside municipal WWTPs effluents also some industrial treated waste waters showed significant effect such as antiestrogenicity or cytotoxicity. Comparison of the bioassay responses with the results of instrumental chemical analyses did not find any clear relationships with particular chemical classes but the results indicate the need to investigate phytoestrogens in waste waters from plant-processing factories. The present pan- European study demonstrates the potential of the effect-based biomonitoring as an important complementary tool to chemical analyses in the detection of estrogenic contaminants at low levels, which may be of toxicological concern for aquatic biota. 1

135 Keywords Waste water, estrogenicity, estrogen, Europe, in vitro 1. Introduction Estrogenic compounds present in treated waste waters have been shown to cause adverse reproductive effects in aquatic biota. Feminization of male fishes living downstream from waste water treatment plants (WWTPs) has been observed worldwide (Sumpter & Johnson 2008). Steroid estrogens, particularly natural hormones such as estrone (E1) and 17β-estradiol (E2) and synthetic hormone used in many contraceptives 17α-ethynylestradiol (EE2), have been identified as the major causative agens in domestic-origin treated waste waters (Anderson et al. 2012, Jarosova et al submitted article). Feminization of fishes has been also observed at several locations downstream from industrial WWTP discharges near places with textile and tannery industries, where high concentrations of alkylphenols have been detected (Sumpter & Johnson 2008). The most potent estrogenic alkylphenol is 4-tertiary isomer of nonylphenol (NP) and to lesser extend also octylphenol (OP) and these two compounds have been reported to be mainly responsible for the adverse effects downstream of the industrial WWTPs (Sumpter & Johnson 2008, Sole et al. 2000). Compared to steroid estrogens, alkylphenols are at least thousand times less potent estrogens (Young 2004, Leusch et al. 2010) but their concentrations detected near textile industry exceeded concentrations as high as 100 ug/l (e.g. Sole et al. 2000), which is about a hundred thousand times more than the common environmental concentrations of steroid estrogens (Runnalls et al. 2010). Steroid estrogens can cause adverse reproductive effects to the most sensitive organisms (i.e. fish) at low ng/l ranges which stimulated efforts to improve analytical techniques for environmental samples (Sumpter & Johnson 2008). Despite of all efforts, reliable quantification of steroid estrogens in environmental samples such as complex waste waters remains a problem (Caldwell et al. 2012). In addition, even reliable detection of few selected estrogens does not guarantee identification of actual estrogenic potential present in environmental sample. Some unexpected molecules or interactions increasing or inhibiting the overall estrogenic activity have been observed in several studies (e.g. (Cargouet et al. 2004, Pawlowski et al. 2003). Therefore, there is a need to complement the targeted chemical instrumental methods by biological approaches (Leusch et al. 2010). Naturally, in situ and in vivo bioassays would be the most relevant to detect adverse effects but they are expensive and time and animals consuming which limits their application for broader monitoring of water quality. On the other hand, in vitro bioassays can serve as rapid and relatively cheap screening method to estimate total estrogenic activity of all compounds that act through the same mode of action (i.e. binding to estrogenic receptor) present in the mixtures, and they are currently being considered to be used in tiered monitoring of estrogenicity of environmental waters (Leusch et al. 2010). 2

136 In the year 2010, effluents from different European WWTPs were collected and analyzed in order to obtain a comprehensive data set on many so far only locally investigated emerging compound classes including pharmaceuticals and personal care products (PPCPs), veterinary (antibiotic) drugs, perfluoroalkyl substances (PFASs), organophosphate ester flame retardants, pesticides and their metabolites or industrial chemicals such as corrosion inhibitors benzotriazoles, polycyclic musk fragrances, x-ray contrast agents, Gadolinium compounds, and siloxanes (Loos et al. 2013). The instrumental targeted chemical analyses were complemented by applying effect-based monitoring approaches aiming at estrogenicity, dioxin-like activity and yeast and diatom culture acute toxicity (Loos et al. 2013). In the present paper we discuss in detail the results of estrogenicity detected using the reporter gene bioassay in the extracts of 75 WWTPs effluents and compare the bioassay responses with the extensive chemical analyses of emerging pollutants. Environmental risks of detected estrogenicity (expressed as ng/l EEQ) are discussed by comparing the detected concentrations of EEQ with effective in vivo concentrations of major estrogens to aquatic biota such as fish. 2. Methods 2.1. Description of the campaign, waste water treatment plants and sampling The selection of the WWTPs was done by voluntarily participating European Union Member States and no criteria were required by the main coordinator of the project (Loos et al. 2013). The participants were, however, aware of the aims of the study and therefore waste waters from WWTPs of different capacities and diverse waste water sources (domestic with or without rain, with or without industrial) have been collected from most participating countries. Supplementary Table SI 1 gives a list of the 75 WWTPs from 16 different countries investigated in the present study. Table SI 1 contains information on the type of discharges treated in the plant (domestic or industrial), the plant capacity (m 3 /d), the capacity in population equivalents, the type of secondary treatment, and, if applicable, the type of tertiary treatment applied. Unfortunately, not all participants of the campaign (owners of the WWTPs) provided all the information requested. The information was collected for 48 municipal and 12 industrial WWTPs, whereas no available metadata were available for 15 tested WWTPs (information not provided by the owners, neither found on the internet). With the exception of few small WWTPs (Capacity of Equivalent Population, CEP < 10,000) and possibly also some of the WWTPs for which there was no information, all investigated municipal WWTPs included activated sludge processes with nitrification and/or denitrification and chemical precipitation of phosphorus, which represent the most common WWTP technology in the European Union. Only 4 municipal WWTPs reported use of biological phosphorus removal technology and another 4 municipal WWTPs utilised tertiary treatment step (filtration and chlorination or UV light). Some of the small WWTPs (CEP < 10,000) utilized activated 3

137 sludge and chemical precipitation of organics and phosphorus without the de/nitrification (Table SI 1). Sampling was performed by grab sampling or in many cases also with automated systems as 24h composite samples. Eight one liter aliquots of water samples from each WWTP, stored in high-density polyethylene (HDPE) plastic bottles, were shipped to the coordinator (Joint Research Centre - JRC, Ispra, Italy) by fast courier in polystyrene boxes with cooling elements. The samples were stored at ~4 C and further distributed as fast as possible to the other expert laboratories for analyses (Loos et al. 2013) Verification of stability of selected samples during storage and shipping With respect to complexity of the Europe-wide campaign, the time from sampling to extraction differed from few weeks to 2 and occasionally even 3 months. The samples were not sterilized or acidified and possible degradation of the measured compounds and their biological activities might occur. Therefore, samples of seven different WWTP effluents, which were collected by authors of this study in the Czech Republic, were further divided into two aliquots, which were extracted (using the methods described below) within 48 h after the sampling and after the receipt of the same samples back from the coordinator (45 d later), respectively. Differences in the estrogenicity between the samples extracted directly after sampling and with delay have been studied to investigate stability of the samples during storage and shipping Sample preparation by the solid-phase extraction Water samples were extracted by solid-phase extraction with Oasis HLB cartridges (6 ml, 500 mg, Waters Oasis, CZ). Samples were filtered through glass fiber filter (2 µm, Fisher Scientific, CZ) prior extraction. Each column was activated by 6 ml of MeOH and equilibrated by 8 ml of distilled water without vacuum. The water samples (500 ml) were passed through the wet cartridges at a flow-rate of 5 ml min -1, then the columns were left to dry for 10 min, and consequently eluted by 6 ml of MeOH. The eluates were concentrated by nitrogen stream at laboratory temperature to final volumes which corresponded to 1200-times concentrated original effluents. This equivalent was selected as a maximal concentration which was not cytotoxic to the cells in our previous studies, and enabled detecting estrogenic activity with the limits of detection (LOD) for estrogenicity 0.5 ng EEQ/L. Sample extracts were stored at -18 C until analyses In vitro bioassays To determine estrogenicity of the sample extracts as well as specific potencies of individual estrogens (E1, E2, E3 and EE2), human breast carcinoma MVLN cells stably 4

138 transfected with firefly luciferase gene under the control of estrogen receptor were used (Demirpence et al. 1993, Novak et al. 2009). Cells were grown in DMEM-F12 without phenol red (Sigma Aldrich, USA) containing 10% fetal calf serum at 5% CO 2 and 37 C. Once the cells reached about 80% confluence they were trypsinized and seeded into a sterile 96-well plate at density 25,000 cells/well. For experiments, cells were grown in medium containing foetal calf serum treated with dextran-coated charcoal (strongly reduces concentrations of natural steroids in the calf serum). After 24 h, the cells were exposed to the calibration of the reference estrogen - 17β-estradiol (dilution series pm E2), the dilution series of other steroid estrogens (1 10,000 pm for E1 and E3; pm for EE2), to the dilution series of the tested samples (at least 5 different concentrations), and blank and solvent controls (0.5% v/v methanol). Exposures were conducted in three replicates for 24 h at 37 C. After the exposure, intensity of luminescence was measured using Promega Steady Glo Kit (Promega, Mannheim, Germany). Analyses of the estrogenic potency of E1, E3 and EE2 were repeated independently at least three times. Assessment of in vitro activity of the first 25 samples of waste water extracts were performed at least twice. The standard deviations between experiments were in median 18% (maximum 46%) which was in a good agreement with our long term results. Remaining 50 waste water samples were analyzed in a single experiment Quantification of estrogenicity The results of estrogenicity bioassay were expressed as EEQ with respect to standard estrogen E2. After subtraction of the solvent control response, detected induction of luminescence was related to the maximal response of standard ligand (E2max) and converted into percentages of E2max. Since most extracts did not reach 50% of E2max (i.e. EC 50 ), the results were determined as EC 25. The EC 25 values were based on relating the amount of E2 causing 25% of the E2 response (EC 25 ) to the amount of sample causing the same level of response. Values were determined from the nonlinear logarithmic regression of dose-response curve of calibration standard and samples using the Graph Pad Prism Software (GraphPad Software, San Diego, USA). A few effluents showed decrease of the estrogenic response with higher extract concentrations. Estrogenicity of these samples has been described as "below LOD" but they are specifically highlighted since the presence of antiestrogenic or cytotoxic compounds could mask the actual estrogenicity Determination of the MVLN cell line-specific potencies of E1, E3 and EE2 relative to E2 After converting the results into percentages of E2max (as described above), EC 50 of doseresponse curves of E2, E1, E3 and EE2 were determined from the nonlinear logarithmic regression in Graph Pad Prism (GraphPad Software, San Diego, USA). The specific potencies 5

139 were then determined as the ratio of EC 50 of the model compound (E1, E3 or EE2) and EC 50 of the reference E2. The EC 50 of each of the model compound was always divided by EC 50 of E2 which was obtained from measurements of cells exposed on the same microwell plate. The final specific potency relative to E2 was an average from three independent experiments Statistical analyses Differences in estrogenicity among the samples from 6 groups of WWTP effluents (4 categories of municipal WWTP effluents divided according to the plant capacities, Industrial WWTP effluents and "unidentified" WWTP effluents) were tested by nonparametric Kruskal- Wallis test. Spearman Correlation was used to investigate the relationship between the results of chemical and biological analyses. All statistical analyses were performed with Statistica for Windows 10.0 (StatSoft, Tulsa, OK, USA). For the statistical analyses, the concentrations below LOD were replaced by ½ of LOD. 3. Results and discussion 3.1. Verification of stability of selected samples during storage and shipping Estrogenicity of the 7 effluent samples extracted within 48h after sampling was not significantly higher than estrogenicity of the same samples extracted after delivery from the coordinator 45 d later (Table 1). The coefficients of variation between the freshly and later extracted samples were lower or comparable to the standard error of the used bioassay. In two of the samples, higher EEQs was detected in extracts prepared after longer storage (Table 1). These results demonstrate that at least in the case of samples from the Czech Republic, there was no significant change in the estrogenic activity during storage and shipping Levels of detected estrogenic activity From the total number of 75 analyzed WWTP effluents, 27 sample extracts showed estrogenic activity higher than the detection limit (> 0.5 ng/l EEQ). Estrogenic activity in 27 positive samples ranged from 0.53 to 17.9 ng/l EEQ with median 1.2 and arithmetic mean 2.7 ng/l EEQ (Figure 1). Median and arithmetic mean of all 75 tested samples were < 0.5 ng/l and 0.9 ng/l EEQ, respectively. The levels of detected EEQs are well comparable to the results of previous studies evaluating estrogenic activity of European WWTP effluents by different in vitro bioassays. For example, (Svenson et al. 2003) used human estrogen receptor, hosted in a yeast strain, to quantify estrogenicity in samples of effluents from 20 Swedish municipal WWTPs. In the Swedish study, the treatment plants were selected to represent different treatment processes 6

140 regarding chemical precipitation (coagulation and precipitation by Al or Fe to remove phosphorus and coagulate dissolved organic material) and microbial processes. The EEQs detected in Swedish WWTP effluents ranged from less than 0.1 to 15 ng/l. The other larger studies evaluating estrogenicity of European WWTPs effluents were for example those performed by Korner et al. (2001) in Germany, Vethaak et al. (2005) in the Netherlands, Aerni et al. (2004) in Switzerland or Cargouet et al. (2004) in France. After the exclusion of the one outlying value (53 ng/l EEQ) reported by Aerni et al. (2004), the levels of measured EEQ in all these studies varied from less than 0.03 to 24 ng/l, which is also in a good agreement with the results determined in the present study. However, all the other studies reported higher frequency of detection of positive samples in comparison to our study. Several reasons could be considered. First, we have done no further concentrations of the initially negative samples. The detection limit of 0.5 ng EEQ/L in the present study was thus slightly higher in comparison to previous investigations ( ng/l EEQ), which resulted in lower number of positive "estrogenic" samples. Second, higher levels of EEQ in previously published studies were often detected at municipal WWTPs with other treatment technologies then activated sludge with nitrification, which was the most frequent in our study. For example, in the Dutch study by Vethaak et al. (2005) where most treatment plants contained the activated sludge system with nitrification step (similar to the present pan-european campaign) the frequency of positively estrogenic samples with EEQ > 0.5 ng/l would be only 10% (in contrast to reported 95% with much lower LOD of 0.1 ng/l EEQ). Finally, the frequency of positives was also affected by cytotoxicity/antiestrogenicity in 9 samples, which might mask the effects of estrogens present in the complex mixtures (Figure 1) Estrogenicity of different categories of WWTPs Approximately one third of the 48 samples that originated from the municipal WWTPs displayed estrogenicity greater than 0.5 ng/l EEQ (LOD) and 4 samples were cytotoxic/antiestrogenic. The EEQ of positive extracts varied from 0.53 to 12.2 ng/l and the greatest value was detected at WWTP of one of the major cities with one of the highest capacity (Figure 1). However, statistical comparisons in estrogenicity among the groups of municipal WWTPs of different capacities showed no significant differences. Although the quantitative information on proportion of industrial and domestic waste waters was available only for limited number of WWTPs (see supplementary Table SI 1), the larger WWTPs (CEP 100,000 to > 500,000) typically contained not only domestic but also significant (about 11-40%) contribution of industrial waste waters. Low impact of proportion of industrial waste waters in municipal WWTPs on fish feminization has been previously demonstrated by Jobling et al. (2006), who found no correlation between feminization of fish and amounts of industrial waste waters in UK Rivers. Alternatively, Jobling et al. (2006) reported clear link between the proportion of sewage effluent in the river and the degree of endocrine disruption in wild fish. 7

141 On the other hand, the present study found no significant differences between estrogenicities of municipal and "purely" industrial WWTP effluents where 9 out of 12 industrial WWTP effluents were either estrogenic (five extracts with EEQ ranging ng/l) or cytotoxic/antiestrogenic (4 extracts). The most estrogenic sample among the industrial effluents originated from the WWTP of the factory processing potatoes; the second most estrogenic sample was from the company running WWTP for waste waters from tank cleaning and treatment of industrial waters of variable origin. Other estrogenic samples originated from pharmaceutical factory or company producing pesticides whereas the cytotoxic/antiestrogenic extracts were treated waste waters from companies processing plants in order to produce polyphenols, dyeing textiles, cleaning tanks or producing amines. It should be pointed out that majority of the industrial samples originated from a single country - Belgium (Table SI 1), so they cannot represent the Europe-wide situation for the industrial WWTP effluents. It is also interesting to note that 2 out of 3 investigated treated waste waters originating from plant-processing factories were either anti/estrogenic or cytotoxic. So far, only phytoestrogen genistein (abundant in soya, flour and many vegetables) have been identified as the major contributor to detected estrogenicity in environmental waters (Kawanishi et al. 2004). Many other phytoestrogens (e.g. coumestrol, zearalenone, β- sitosterol, enterolactone) have been identified in WWTP effluents or rivers but their concentrations and/or estrogenic potencies were much lower in comparison to genistein or to other anthropogenic estrogens (Pawlowski et al. 2003, Kawanishi et al. 2004, Lagana et al. 2004). Liu et al. (2010), who reviewed estrogenic potency and occurrence of phytoestrogens in the environment, concluded that phytoestrogens should be considered and investigated as possible significant contributors to estrogenicity of environmental waters especially at locations close to the plant-processing manufactures, and this conclusion is also supported by findings of the present study. Regarding the cytotoxicity/antiestrogenicity of extract from textile dyeing industrial waste water, it is interesting to note that Sole et al. (2000), who reported fish feminization downstream of WWTP from textile industry, also detected in vitro cytotoxicity and not estrogenicity of the extracts of corresponding water samples. This demonstrates that cytotoxicity of samples can mask the actual estrogenic activity and therefore the cytotoxicity/antiestrogenicity of the samples should be reported and these samples should be considered as potentially estrogenic. With regard to 15 WWTPs for which no or limited data on collected waters or capacities were available (supplementary Table SI 1), six of the effluents showed estrogenic activity above LOD and one sample was highly cytotoxic/antiestrogenic. One of the extracts reached the greatest value of detected EEQ in the present study, i.e ng/l but the owner of this WWTP provided only the information on plant discharge capacity of 1,000 m 3 /d, which corresponds to some of the smallest municipal WWTPs in the present study. This WWTP is situated near town with about 7,000 citizens (coordinates cannot be disclosed) with light industry, agriculture including soya production and brewery, and hypothetically phytoestrogens could contribute to high estrogenicity detected. The other 5 positive samples reached values from 0.6 to 6.0 ng/l EEQ, the range which was not significantly different from estrogenicities detected in other groups of samples. 8

142 3.4. Comparison of estrogenic activity with chemical analyses Estrone, E2 and EE2, which are known to be the most potent estrogens of waste water effluents (e.g. Gardner et al. 2012, Anderson et al. 2012) have been analysed but not detected in any of the samples above LOQ of 10 ng/l (Loos et al. 2013). Some of the other chemicals detected in the studied samples have previously been reported to be estrogenic or antiestrogenic but their actual concentrations were too low to induce the effects in in vitro assay. For example the effective estrogenic concentrations of triazines, hexazinon and diazinon are known to be greater than mg/l (Danzo 1997, Vonier et al. 1996) but the greatest sum of the detected concentrations of all measured triazines and triazols (atrazine, atrazinedesethyl, simazine, terbutylazine, terbutylazine-desethyl, propazine, hexazinon and diazinon) was 1,8 µg/l in the sample WWTP B12, which was not estrogenic above LOD (Figure 1). Chemical results of each positive sample (estrogenic, antiestrogenic/cytotoxic) were further searched for the presence of elevated (several times higher than median) concentrations of any detected chemical. A few samples contained elevated concentrations of e.g. perfluoroalkyl substances or pharmaceutical fluconazole but similar or even greater concentrations of these pollutants were always present also in samples with negative results in the in vitro assay. The only sample which was positive in the in vitro assay (strongly cytotoxic/antiestrogenic) and contained much greater concentrations of some selected chemicals than other samples was the industrial WWTP effluent coded WWTP E9. The sample contained high concentration of triclosan (more than 4 µg/l) and it was also the only sample where siloxanes were detected. The WWTP is run by company which dyes textile and it is the only WWTP of textile industry investigated in the present study (Table SI 1, WWTP E9). Triclosan is currently used as an antimicrobial agent in various household applications or cosmetics but also in functional clothing such as functional shoes and underwear. The maximum concentration observed was very high compared to other studies reviewed in Dann & Hontela (2011) and the concentrations might have been even greater because HDPE bottles used in the present study are not recommended for sampling of this compound (Loos et al. 2013). Some studies showed antiestrogenic or estrogenic effects of triclosan at concentrations around 20 or 100 μg/l, which are greater than those detected in this study. However, triclosan has been shown to disrupt thyroid hormone homeostasis and possibly the reproductive axis of tadpoles (Rana catesbeiana) in much lower concentrations than detected in this study (e.g μg/l) and the detected concentration might be also toxic too algae (Dann & Hontela 2011, Brausch & Rand 2011). Much less information is available on toxicity of high production volume chemicals siloxanes, polymeric ingredients in the synthesis of silicone products (Warner et al. 2010). The main concerns are the possibility of their accumulation in arctic organisms and their toxicity via inhalation (Warner et al. 2010, Siddiqui et al. 2007) but recent investigations suggested rather minor risk under current emission levels (Redman et al. 2012). 9

143 We have also investigated possible relationships between the results of the in vitro assay (nonparametric Spearman Correlation) and total concentrations of all analyzed contaminants as well as with the levels of various analyzed chemical classes (concentrations of pharmaceuticals, personal care products, veterinary drugs, perfluoroalkyl substances, organophosphate ester flame retardants, pesticides and their metabolites, benzotriazoles, polycyclic musk fragrances, x-ray contrast agents, Gadolinium compounds, and siloxanes). None of the sums of concentrations of pollutants from each of the investigated groups correlated with EEQ. The most significant correlation (R = 0.56) was found between the sums of concentrations of pharmaceuticals and sweeteners (Table SI 3). Weak correlation is in line with the fact that most investigated WWTP effluents were municipal, in which steroid hormones are most likely responsible for the estrogenicity. While chemical analyses were not able to reveal their concentrations below the LOQ 10 ng/l, estrogenicity was detected by in vitro assay demonstrating thus usefulness of complementing the chemical analyses by effect-based monitoring as also concluded e.g by Leusch et al. (2010) Environmental risks and specific sensitivities to E1, E3 and EE2 relative to E2 EEQs detected in this study ( ng/l) are comparable or even greater than the lowest observable effective concentration of the most effective estrogens which can be expected in WWTP effluents. For example, Zha et al. (2008) demonstrated complete inhibition of Chinese rare minnows (Gobiocypris rarus) at EE2 concentration as low as 0.2 ng/l. Therefore, detected EEQ concentrations might be of toxicological concerns even though some dilution of the effluents by recipients is considered. Unfortunately, information on the proportion of sewage effluent in the recipient river was not available for WWTPs in this study thus the only estimation of environmental risks could be done as if biota was exposed to the undiluted effluents. In different studies, estrogen-related adverse effects on aquatic biota were observed at different EEQ values determined by various in vitro assays. For example, Vethaak et al. (2005) found elevated levels of yolk protein vitellogenin in male bream (Abramis brama) in the river with EEQ levels as low as 0.17 ng/l determined by vitro ER-CALUX assay. On the other hand, Huggett et al. (2003) did not find any in vivo response in fish exposed to WWTP effluents with EEQ concentrations around 7 ng/l measured by Yeast Estrogen Screen (YES). However, the same study (Huggett et al. 2003) showed elevated levels of Vtg in male fish exposed to the effluent from different WWTP showing similar YES-derived EEQ concentrations of 7 ng/l EEQ. These inconsistencies can be related either to different sensitivities of different assays towards estrogenic compounds in environmental samples or to different composition of specific mixture and the fact that in vitro and in vivo sensitivities to individual compounds can significantly differ (Jarosova et al submitted article, Young 2004). Other reason can also be interactions among molecules within the mixtures (Leusch et al. 2005). Nevertheless, the usefulness of in vitro assays for evaluating estrogenic activity in 10

144 different types of waters has been evaluated and recognized (Leusch et al. 2010, Murk et al. 2002), and bioassay are now being harmonised and standardized as a tiered monitoring tool. Although the EEQ value of toxicological concern from in vitro assays has not been fully recognized yet (Leusch et al. 2010) some suggestions for waste waters have been developed in our recent study (Jarosova et al submitted article). By combining literature data on the occurrence and bioassay-specific in vitro potencies of the most potent estrogens found in municipal WWTPs (i.e. E1, E2, E3 and EE2) and taking into account PNECs for these compounds derived from fish studies (Caldwell et al. 2012) (Table SI 2), we have derived concentrations of EEQ below which none of the PNECs of any of the major steroids would be exceeded. When estrogenicity of certain sample exceeds suggested EEQ value in a specific in vitro bioassay, potential in vivo risk cannot be excluded. Limit EEQ values were derived for 2 different exposure scenarios (Jarosova et al submitted article); longer-term exposure limits are meant for situations when the detected concentrations of EEQ can be expected to stay constant or to increase in a 60 d period whereas the shorterterm exposure limits should be applied when the detected EEQ concentrations can be expected to decrease in 60 d (usually due to higher river flow caused by rain events (Anderson et al. 2012)). For the MVLN assay used in the present study, the derived estrogenic limits were 0.3 ng/l EEQ for longer-term exposures and 1.4 ng/l for shorter-term exposures (Jarosova et al submitted article). All positively estrogenic samples in this study (N=27) exceeded the longer-term limit and 9 of them exceeded also the shorter-term limit indicating that estrogens determined in several of the investigated WWTP effluents can be of risks for aquatic biota. 4. Conclusions From the total number of 75 analyzed European WWTP effluents, 27 sample extracts showed estrogenic activity higher than the detection limit 0.5 ng/l EEQ and another 9 samples displayed cytotoxic/antiestrogenic responses, which could mask presence of estrogens. Estrogenic activity varied from 0.53 to 17.9 ng/l EEQ with mean value of 0.9 ng/l EEQ. Estrogenicity was not significantly correlated with the results of chemical analyses, which were, however, not able to detect steroid estrogens below relatively high LOQ 10 ng/l. High concentration of triclosan (more than 4000 ng/l) and siloxanes were detected in the sample extract, which was strongly cytotoxic/antiestrogenic. Potent estrogenicity detected in the samples of factories processing plants indicated potential importance of phytoestrogens in these types of waste waters, which require future investigation. Complementation of the pan- European chemical monitoring by the effect-based approach brought an important additional information on levels of estrogenicity, which were shown to exceed suggested limits indicating thus toxicological concern for aquatic biota. 11

145 Acknowledgement Authors highly acknowledge support from numerous persons at various waste water treatment plants who contributed to the success of the study. The research was supported by project CETOCOEN from the European Regional Development Fund. References Aerni, H.R., B. Kobler, B.V. Rutishauser, F.E. Wettstein, R. Fischer, W. Giger, A. Hungerbuhler, M.D. Marazuela, A. Peter, R. Schonenberger, A.C. Vogeli, M.J.F. Suter & R.I.L. Eggen Combined biological and chemical assessment of estrogenic activities in wastewater treatment plant effluents. Analytical and Bioanalytical Chemistry 378: Anderson, P.D., A.C. Johnson, D. Pfeiffer, D.J. Caldwell, R. Hannah, F. Mastrocco, J.P. Sumpter & R.J. Williams Endocrine disruption due to estrogens derived from humans predicted to be low in the majority of U.S. surface waters. Environmental Toxicology and Chemistry 31: Brausch, J.M. & G.M. Rand A review of personal care products in the aquatic environment: Environmental concentrations and toxicity. Chemosphere 82: Caldwell, D.J., F. Mastrocco, P.D. Anderson, R. Lange & J.P. Sumpter Predicted-no-effect concentrations for the steroid estrogens estrone, 17 beta-estradiol, estriol, and 17 alpha-ethinylestradiol. Environmental Toxicology and Chemistry 31: Cargouet, M., D. Perdiz, A. Mouatassim-Souali, S. Tamisier-Karolak & Y. Levi Assessment of river contamination by estrogenic compounds in Paris area (France). Science of the Total Environment 324: Dann, A.B. & A. Hontela Triclosan: environmental exposure, toxicity and mechanisms of action. Journal of Applied Toxicology 31: Danzo, B.J Environmental xenobiotics may disrupt normal endocrine function by interfering with the binding of physiological ligands to steroid receptors and binding proteins. Environmental Health Perspectives 105: Demirpence, E., M.J. Duchesne, E. Badia, D. Gagne & M. Pons Mvln Cells - a Bioluminescent Mcf-7- Derived Cell-Line to Study the Modulation of Estrogenic Activity. Journal of Steroid Biochemistry and Molecular Biology 46: Gardner, M., S. Comber, M.D. Scrimshaw, E. Cartmell, J. Lester & B. Ellor The significance of hazardous chemicals in wastewater treatment works effluents. Science of the Total Environment 437: Huggett, D.B., C.M. Foran, B.W. Brooks, J. Weston, B. Peterson, K.E. Marsh, T.W. La Point & D. Schlenk Comparison of in vitro and in vivo bioassays for estrogenicity in effluent from North American municipal wastewater facilities. Toxicological Sciences 72: Jarosova B., L. Blaha, J.P. Giesy & K. Hilscherova What level of estrogenic activity determined by in vitro assays in municipal waste waters can be considered as safe? Environment International - ( accepted with medium revisions). Jobling, S., R. Williams, A. Johnson, A. Taylor, M. Gross-Sorokin, M. Nolan, C.R. Tyler, R. van Aerle, E. Santos & G. Brighty Predicted exposures to steroid estrogens in UK rivers correlate with widespread sexual disruption in wild fish populations. Environmental Health Perspectives 114: Kawanishi, M., T. Takamura-Enya, R. Ermawati, C. Shimohara, M. Sakamoto, K. Matsukawa, T. Matsuda, T. Murahashi, S. Matsui, K. Wakabayashi, T. Watanabe, Y. Tashiro & T. Yagi Detection of genistein as an estrogenic contaminant of river water in Osaka. Environmental Science & Technology 38: Korner, W., P. Spengler, U. Bolz, W. Schuller, V. Hanf & J.W. Metzger Substances with estrogenic activity in effluents of sewage treatment plants in southwestern Germany. 2. Biological analysis. Environmental Toxicology and Chemistry 20: Lagana, A., A. Bacaloni, I. De Leva, A. Faberi, G. Fago & A. Marino Analytical methodologies for determining the occurrence of endocrine disrupting chemicals in sewage treatment plants and natural waters. Analytica Chimica Acta 501: Leusch, F.D.L., C. De Jager, Y. Levi, R. Lim, L. Puijker, F. Sacher, L.A. Tremblay, V.S. Wilson & H.F. Chapman Comparison of Five in Vitro Bioassays to Measure Estrogenic Activity in Environmental Waters. Environmental Science & Technology 44:

146 Leusch, F.D.L., H.F. Chapman, W. Korner, S.R. Gooneratne & L.A. Tremblay Efficacy of an advanced sewage treatment plant in southeast Queensland, Australia, to remove estrogenic chemicals. Environmental Science & Technology 39: Liu, Z.H., Y. Kanjo & S. Mizutani A review of phytoestrogens: Their occurrence and fate in the environment. Water Research 44: Loos, R., R. Carvalho, D.C. Antonio, S. Comero, G. Locoro, S. Tavazzi, B. Paracchini, M. Ghiani, T. Lettieri, L. Blaha, B. Jarosova, S. Voorspoels, K. Servaes, P. Haglund, J. Fick, R.H. Lindberg, D. Schwesig & B.M. Gawlik EU-wide monitoring survey on emerging polar organic contaminants in wastewater treatment plant effluents. Water Research - in press Murk, A.J., J. Legler, M.M.H. van Lipzig, J.H.N. Meerman, A.C. Belfroid, A. Spenkelink, B. van der Burg, G.B.J. Rijs & D. Vethaak Detection of estrogenic potency in wastewater and surface water with three in vitro bioassays. Environmental Toxicology and Chemistry 21: Novak, J., V. Jalova, J.P. Giesy & K. Hilscherova Pollutants in particulate and gaseous fractions of ambient air interfere with multiple signaling pathways in vitro. Environment International 35: Pawlowski, S., T. Ternes, M. Bonerz, T. Kluczka, B. van der Burg, H. Nau, L. Erdinger & T. Braunbeck Combined in situ and in vitro assessment of the estrogenic activity of sewage and surface water samples. Toxicological Sciences 75: Redman, A.D., E. Mihaich, K. Woodburn, P. Paquin, D. Powell, J.A. McGrath & D.M. Di Toro Tissuebased risk assessment of cyclic volatile methyl siloxanes. Environmental Toxicology and Chemistry 31: Runnalls, T.J., L. Margiotta-Casaluci, S. Kugathas & J.P. Sumpter Pharmaceuticals in the Aquatic Environment: Steroids and Anti-Steroids as High Priorities for Research. Human and Ecological Risk Assessment 16: Siddiqui, W.H., D.G. Stump, V.L. Reynolds, K.P. Plotzke, J.F. Holson & R.G. Meeks A two-generation reproductive toxicity study of decamethylcyclopentasiloxane (D-5) in rats exposed by whole-body vapor inhalation. Reproductive Toxicology 23: Sole, M., M.J.L. de Alda, M. Castillo, C. Porte, K. Ladegaard-Pedersen & D. Barcelo Estrogenicity determination in sewage treatment plants and surface waters from the Catalonian area (NE Spain). Environmental Science & Technology 34: Sumpter, J.P. & A.C. Johnson th Anniversary Perspective: Reflections on endocrine disruption in the aquatic environment: from known knowns to unknown unknowns (and many things in between). Journal of Environmental Monitoring 10: Svenson, A., A.S. Allard & M. Ek Removal of estrogenicity in Swedish municipal sewage treatment plants. Water Research 37: Vethaak, A.D., J. Lahr, S.M. Schrap, A.C. Belfroid, G.B.J. Rijs, A. Gerritsen, J. de Boer, A.S. Bulder, G.C.M. Grinwis, R.V. Kuiper, J. Legler, T.A.J. Murk, W. Peijnenburg, H.J.M. Verhaar & P. de Voogt An integrated assessment of estrogenic contamination and biological effects in the aquatic environment of The Netherlands. Chemosphere 59: Vonier, P.M., D.A. Crain, J.A. McLachlan, L.J. Guillette & S.F. Arnold Interaction of environmental chemicals with the estrogen and progesterone receptors from the oviduct of the American alligator. Environmental Health Perspectives 104: Warner, N.A., A. Evenset, G. Christensen, G.W. Gabrielsen, K. Borga & H. Leknes Volatile Siloxanes in the European Arctic: Assessment of Sources and Spatial Distribution. Environmental Science & Technology 44: Young, W.F., Whitehouse, P., Johnson, I. and Sorokin, N Proposed Predicted-No-Effect-Concentrations (PNECs) for Natural and Synthetic Steroid Oestrogens in Surface Waters, Environment Agency. Zha, J.M., L.W. Sun, Y.Q. Zhou, P.A. Spear, M. Ma & Z.J. Wang Assessment of 17 alphaethinylestradiol effects and underlying mechanisms in a continuous, multigeneration exposure of the Chinese rare minnow (Gobiocypris rarus). Toxicology and Applied Pharmacology 226:

147 FIGURE and TABLE Captions Figure 1: Estrogenic activity expressed as 17β-estradiol equivalent (EEQ) of 75 extracts of European Waste Water Treatment Plant (WWTP) effluents determined by MVLN in vitro assay. No values indicate estrogenicity below LOD (< 0.5 ng/l), open and full triangles show slight and strong cytotoxic/antiestrogenic effects, respectively. Municipal WWTPs (with domestic and some industrial waste waters) are shown in panels A, B and C. Figure D displays smaller WWTPs with most waste waters of domestic origin. Figure E refers to industrial WWTPs and Figure F shows WWTPs for which no detailed information was available. Table 1: Estrogenic activity in extracts of seven Waste Water Treatment Plant (WWTP) effluents prepared directly after sampling (at 48 h) and after longer storage (45 d). Estrogenicity is expressed as 17β-Estradiol Equivalent (EEQ). 14

148 Figure 1 15

149 Table 1: Estrogenic activity in extracts of seven Waste Water Treatment Plant (WWTP) effluents prepared directly after sampling (at 48 h) and after longer storage (45 d). Estrogenicity is expressed as 17β-Estradiol Equivalent (EEQ). Number of WWTP extraction 48 h after sampling (ng/l EEQ) extraction 45 d after sampling (ng/l EEQ) coefficient of variation between samples extracted at 48 h and 45 d(%) WWTP A2 2.0 ± ±0.5 2 WWTP A3 1.0 ± ± WWTP B ± ± WWTP C3 2.0 ± ± WWTP C8 0.8 ±0.2 <0.5 23* WWTP D1 1.0 ± ± WWTP D5 <0.5 <0.5 0 *coefficient of variation was calculated as if the value <0.5 was

150 Supporting Information Paper: Europe-wide monitoring of estrogenicity in waste water treatment plant effluents Authors: Barbora Jarošová 1, A. Erseková 1, K. Hilscherová 1, R. Loos 2, B. Gawlik 2, J. P. Giesy 3, L. Bláha 1* 1 Research Centre for Toxic Compounds in the Environment (RECETOX), Masaryk University, Kamenice 3, CZ Brno, Czech Republic 2 European Commission - DG Joint Research Centre (JRC), Institute for Environment and Sustainability (IES), Ispra, Italy 3 University of Saskatchewan, Department of Veterinary Biomedical Sciences, 44 Campus Drive, Saskatoon, SK, Canada, S7N 5B3 *Corresponding author (blaha@recetox.muni.cz, ) 17

151 Table SI 1: Characterization of sampled waste water treatment plants (WWTPs) Label in this article Country Location Composition of waste water 18 Plant capacity [m 3 /d] Capacity population equivalent Type of secondary treatment WWTP A1 Italy Roma nord ACEA Dom. Ind. Rain biological, not specified WWTP A2 Czech Rep. Not displayed Dom. Ind. Rain > > AS, DN, N, CHP WWTP A3 Czech Rep. Not displayed Dom. Ind. Rain > > AS, DN, N, CHP WWTP A4 Finland Helsinki Dom. Ind. probably a a AS, DN, N, CHP Rain WWTP A5 Germany Bremen Dom. Ind. Rain AS, D/N, CHP WWTP A6 Germany Klärwerk Gut Dom. Ind. Rain AS, DN, N, CHP Marienhof WWTP A7 Ireland Dublin AS (sequencing batch reactor) with DN/N WWTP A8 Netherlands Harnaschpolder Dom. Ind. Rain AS, DN/N, BP WWTP A9 Netherlands Rotterdam Dokhaven Mainly Dom AS, D/N - SHARON and ANAMMOX, CHP WWTP A10 Switzerland Zürich Werdhölzli Dom. Ind. Rain AS, DN, N, BP, CHP WWTP B1 Slovenia Ljubljana Dom. (62%), Ind. (11%), Rain (21%) AS not further specified WWTP B2 Czech Rep. Not displayed Dom. Ind. Rain AS, DN, N, CHP WWTP B3 Lithuania Kaunas AS, DN/N, CHP WWTP B4 Netherlands Venlo b AS, DN/N, BP WWTP B5 Netherlands Almere Dom., Hospital, no Rain not specified WWTP B6 Austria Wiener Neustadt - Sud Dom. (90%), Paper Ind AS, DN/N, P removal not specified, WWTP B7 Austria AWV Hall i. Tirol-Fritzens Dom. Ind. (Rain was not further specified) AS not further specified WWTP B8 Belgium Deurne Waste water from Antwerp a AS not further specified WWTP B9 Finland Espoo Dom. Ind. Rain not specified AS, DN, N, P removal not specified WWTP B10 Netherlands Amstelveen Dom AS not further specified WWTP B11 Netherlands Nieuwgraaf Dom. Ind. (30-40%), Hospital AS not further specified WWTP B12 Netherlands Garmerwold (Noorderzijlvest) Dom AS, DN/N - SHARON, P Type of tertiary treatment Final disinfection step UV Light Treatment removal not specified WWTP B13 Netherlands Zaandam Oost Dom. Urban runoff, Ind. Craft Industry AS, DN/N, P removal not specified WWTP B14 Lithuania Klaipedo vanduo Dom. Ind. (Rain was not further specified) a AS, DN/N, P removal not specified WWTP B15 Lithuania Panevezys regional Dom. Ind. Rain not specified WWTP C1 Cyprus Larnaka Dom AS, no DN, N and P Tert. with sand removal not specified filtration, chlorination WWTP C2 Spain Ulldecona not specified WWTP C3 Czech Rep. Not displayed Dom. Rain AS, N, DN, CHP WWTP C4 Austria Eisenstadt eisbachtal b b AS, DN/N not specified, CHP WWTP C5 Austria Feldkirchen AS, N, DN, BP WWTP C6 Belgium Hasselt Dom AS, (DN/N and P removal not specified) WWTP C7 Cyprus Limassol Dom. Ind AS, N, DN, no BP (CHP not specified) Tert. with sand filtration, chlorination WWTP C8 Czech Rep. Not displayed Dom. Rain AS, N, DN, CHP WWTP C9 Ireland Oberstown cyclic AS, N, DN, CHP WWTP C10 Netherlands Leek (Noorderzijlvest) WWTP C11 Netherlands Simpelveld Dom not specified Dom., Health Care not specified Unit WWTP C12 Netherlands Winterswijk Dom. Ind.(30-40%). Hospital not specified WWTP C13 Spain Tortosa not specified WWTP C14 Switzerland Affoltern a.a. Dom. Ind. Rain AS, DN/N not specified, CHP

152 Label in this article Country Location Composition of waste water Plant capacity [m 3 /d] Capacity population equivalent Type of secondary treatment WWTP D1 Czech Rep. Not displayed Dom. Ind. no Rain AS, N, DN, CHP WWTP D2 Germany AZV Hungerbachtal a AS not further specified WWTP D3 Hungary Alattyán Mainly Dom. 250 not specified WWTP D4 Switzerland Wenslingen Dom. Rain 700 AS (DN/N and P removal not specified) WWTP D5 Czech Rep. Not displayed Dom. Ind. no Rain AS, N, DN, CHP WWTP D6 Finland Nummi-Pusula b a Fe coag., As (no DN/N) WWTP D7 Spain Godall not specified WWTP D8 Switzerland Konolfingen Dom. Ind. Rain AS, CHP (DN/N not specified) WWTP D9 Switzerland Seuzach Dom. Rain AS, CHP (DN/N not specified) WWTP E1 Belgium Agristo Food industry (potato products) WWTP E2 Belgium TWZ Evergem Tank cleaning and various ind. activities WWTP E3 Belgium Bayer Antwerpen Chemical industry (e.g. pesticide production) WWTP E4 Belgium 3M Different industrial branches WWTP E5 Belgium Janssen Pharmaceuticals Pharmaceutical industry WWTP E6 Austria WV Hofsteig Dom(25%). Ind.(75%) (Metal, food, textile) AS not further specified WWTP E7 Belgium Ajjinomoto Omnichem Herbal extracts, polyphenols production WWTP E8 Belgium Ardo Food industry (frozen vegetable) WWTP E9 Belgium Colortex Textile industry (dyeing) WWTP E10 Belgium EOC Oudenaarde Chemical industry (e.g. adhesives, surfactants) WWTP E11 Belgium Tack Oostrozebeke Tank cleaning and various ind. activities WWTP E12 Belgium Taminco Chemical industry (Amine company) WWTP F1 Hungary Martfű Dom. or soya or brewery production? WWTP F2 Portugal Parada AS, DN, N, no BP WWTP F3 Austria AWV Region Feldkirch AS not further specified WWTP F4 Portugal Viana do Castelo a AS not further specified WWTP F5 Greece Thessaloniki (EELTH) Dom. Ind. probably Rain WWTP F6 Italy Depuratore 'Jugendwerk Brebbia' WWTP F7 Belgium Geel trickling filter, AS (INVENT ) WWTP F8 Belgium Ronse WWTP F9 Belgium Waregem Region with textile industry Type of tertiary treatment sand filtration WWTP F10 Finland Lohja WWTP F11 Finland Mäntsälä WWTP F12 Finland Vihti WWTP F13 Greece Thessaloniki (EEL AINEIA) Waste water from Thermaikos city WWTP F14 Belgium Claerebout WWTP F15 Belgium Shanks lokeren Dom. domestic, Ind. industrial, AS - reservoirs with activated sludge, DN denitrification, N nitrification, DN/N - biological treatment of nitrogen (not specified if N, DN or both are used), BP - biological removal of phosphorus, CHP - chemical precipitation of phosphorus a - approximate number b - refers to average daily discharge or to currently connected equivalent citizens not to maximal capacity of WWTP 19

153 Table SI 2: The in vivo derived Predicted-No-Effect-Concentrations (PNECs) of estrone (E1), 17β-estradiol (E2), estriol (E3) and 17α-ethynylestradiol (EE2) (Caldwell et al. 2012) Long-term studies (>60 d) Short-term studies (<60 d) PNEC E1 6 ng/l 20 ng/l PNEC E2 2 ng/l 5 ng/l PNEC E3 60 ng/l 200 ng/l PNEC EE2 0.1 ng/l 0.5 ng/l Table SI 3: Spearman Correlation of sums of concentrations of chemicals detected within different groups of compounds tested in the present study (The group of veterinary antibiotics was not included in the presented correlation table since only about half of samples were analyzed for their presence. There was no significant correlation of these compounds with concentrations of EEQ). Spearman Correl. Pharmace uticals Sweeters Musks OrgPflame ret. PCPs Gd Benzotri azoles X-ray contrast media Pestici des Nitrophe nols PFASs Pharmaceuticals Sweeters 0.52* Musks 0.34* 0.22 OrgP-flame ret. 0.33* * PCPs 0.31* Gd 0.28* 0.24* * 0.06 Benzotriazoles 0.24* X-ray contrast media * 0.13 Pesticides Nitrophenols PFASs * Siloxanes EEQ * Asterisks indicate statistically significant correlations (P<0.05) PFASs - Perfluoroalkyl Substances, OrgP-flame ret. - Organophosphate ester flame retardants, PCPs - Personal Care Products, Gd - gadolinium Siloxa nes References Caldwell, D.J., F. Mastrocco, P.D. Anderson, R. Lange & J.P. Sumpter Predicted-noeffect concentrations for the steroid estrogens estrone, 17 beta-estradiol, estriol, and 17 alpha-ethinylestradiol. Environmental Toxicology and Chemistry 31:

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155 Článek V Příloha V

156 What level of estrogenic activity determined by in vitro assays in municipal waste waters can be considered as safe? Barbora Jarošová a, Luděk Bláha a, John P. Giesy b, Klára Hilscherová a * a Research Centre for Toxic Compounds in the Environment (RECETOX), Masaryk University, Kamenice 3, CZ Brno, Czech Republic b Department of Biomedical Veterinary Sciences and Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada * corresponding author, hilscherova@recetox.muni.cz, tel: Abstract In vitro assays are broadly used tools to evaluate the estrogenic activity in municipal Waste Water Treatment Plant (WWTP) effluents and their receiving rivers. Since potencies of individual estrogens to induce in vitro and in vivo responses can differ it is not possible to directly evaluate risks posed by in vitro measures of estrogenic activity. Estrone (E1), 17βestradiol (E2), 17α-ethynylestradiol (EE2) and to some extent, estriol (E3) have been shown to be responsible for the majority of in vitro estrogenic activity of municipal WWTP effluents. Therefore, in vitro thresholds expressed as 17β-estradiol Equivalents (EEQ) in municipal WWTP effluents were derived based on simplified situation that assumed that the steroid estrogens are responsible for all estrogenicity determined with particular in vitro assays. Bioassay-specific thresholds were derived from bioassay-specific in vitro potencies of steroid estrogens, in vivo potencies of these compounds, and their relative contributions to the over-all estrogenicity detected in municipal WWTP effluents. Thresholds for 15 individual bioassays varied from 0.1 to 0.4 ng EEQ/L for samples collected during periods of high or average river flows and from 0.5 to 2 ng EEQ/L for samples collected during low-flow periods. The thresholds are supposed to be increased by use of dilution factors for specific locations. 1

157 Abbreviations ceeq- calculated E2-Equivalents E1- Estrone E2-17β-estradiol E3- Estriol EE2-17α-ethynylestradiol EEF- Estrogenic Equivalency Factor EEQ- 17β-estradiol equivalent Ei - E1, E2, E3 or EE2 EL- Estrogenic Limit NP- Nonylphenol OP- Octylphenol P- Percentage of total ceeq PNEC- Predicted No Effect Concentration TIE -Toxicity Identification and Evaluation VTG- Vitellogenin WWTP- Waste Water Treatment Plant YES - Yeast Estrogenicity Screening Assay Keywords Estrogen, threshold, in vitro assay, environmental risk assessment, waste water treatment plant 2

158 1. Introduction Municipal waste waters and effluents of municipal Waste Water Treatment Plants (WWTPs) are one of the main sources of estrogenic compounds in aquatic environments (e.g. Bolong et al. 2009). Feminization of fish due to presence of estrogenic compounds has been observed worldwide (Sumpter and Johnson 2008). Some estrogenic chemicals, particularly steroid estrogens, are known to cause disruption of the endocrine system of fishes and abnormalities of the reproductive tract (e.g. Bolong et al. 2009, Petrovic et al. 2004) in ng/l concentrations, which commonly occur in aquatic environment worldwide. Several approaches exist to monitor the presence of estrogenic compounds in surface waters. Traditional assessment of water contamination has been based on identifying and quantifying individual chemicals, but this approach has some limitations. It is expensive because it requires sophisticated equipment and highly trained personnel (Caldwell et al. 2012). Furthermore, the individual constituents of complex mixtures occurring in the environment might not be known or there might not be methods or standards for them or the methods might not be sufficiently sensitive to measure the individual constituents or there might be matrix interferences in quantification (Caldwell et al. 2012, Korner et al. 2000). In addition, chemical analyses of selected micropollutants cannot always identify all of the estrogenic potential present in environmental samples because some unexpected molecules or infra- or supra-additive interactions can occur (Leusch et al. 2005). Therefore, biological monitoring approaches are needed. In situ and in vivo bioassays are the most relevant tools for the detection of adverse effects but they are also expensive and time and animals consuming. In vitro bioassays can serve as a rapid, sensitive and relatively inexpensive integrative screening method to estimate total estrogenic activity of all compounds in the mixtures that act through the same mode of action (Hilscherova et al. 2000). The most frequently used in vitro assays are transactivation assays (Kinnberg 2003) which evaluate the ability of samples/chemicals to stimulate estrogen receptor and upregulate subsequent expression of a reporter gene (hereinafter in vitro estrogenicity assays). Moreover, in vitro estrogenicity assays are currently being considered to be used in tiered monitoring of environmental waters (Leusch et al. 2010). Several studies comparing estrogenic activity detected in environmental samples by different in vitro assays have been conducted showing that the studied assays are useful for environmental monitoring (Murk et al. 2002, Leusch et al. 2010). However, the in vitro potency of individual estrogens can be significantly different from their in vivo potencies and therefore more work is needed to better understand what can be learned from the results of these in vitro assays towards in vivo situation; and to identify trigger levels of estrogenic activity which would allow prioritization of samples for further investigation (Leusch et al. 2010). Concentrations greater than 1 ng EEQ/L from in vitro assays are often considered to be associated with adverse effects on individuals. This is based on the observation that adverse reproductive effects in fish occurred when environmental samples assessed by Yeast Estrogenicity Screening (YES) assay contained more than the 1 ng EEQ/L (e.g. Metcalfe et al. 2001). However, can 1 ng/l EEQ be 3

159 the trigger concentration for any in vitro estrogenicity assay and any surface water sample? Are there more suitable trigger concentrations (Estrogenic Limits; ELs) applicable for waste or surface waters or for specific environmental conditions? In this paper, these questions were addressed specifically for municipal un/treated waste waters and their receiving waters by: i) comparing estrogenic potencies of major known estrogens among different in vitro assays; ii) considering in vivo potencies of major steroid estrogens; iii) taking into account relative contributions of steroid estrogens to over-all in vitro estrogenic activities detected in municipal WWTP effluents, and iv) combination of gathered information into final formula for derivation of bioassay specific EL. 2. Methods 2.1. Compounds responsible for in vitro and in vivo estrogenic activity A variety of diverse chemicals present in the environment have been shown to interfere with regulation of endogenous estrogens. Despite their relatively great concentrations in the environment, their potency is mostly too small to significantly contribute to observed overall estrogenic activity in complex samples (Sumpter and Johnson 2008). There is strong evidence from both in vivo and in vitro studies that both endogenous and synthetic steroid estrogens, including estrone (E1), 17β-estradiol (E2), 17α-ethinyl estradiol (EE2), and for most in vitro assays also estriol (E3) are usually responsible for most of the estrogenic activity in municipal waste waters and their receiving waters (e.g. Aerni, et al. 2004, Jobling et al. 2007, Korner et al. 2001). The first researchers who described these compounds as the causative estrogens were Desborow et al. (1998) in UK WWTP effluents. They used a Toxicity Identification and Evaluation (TIE) approach, which combines fractionation procedures with biological screening to separate the active extract until a sample is clean enough for efficient chemical analyses. Purdom et al. (1994) and Routledge et al. (1998) demonstrated that concentrations of steroid estrogens present in the effluents (the lesser ng/l range) could cause the effects observed in wild fish living downstream of some WWTPs, such as elevated levels of plasma vitellogenin (VTG). Another piece of evidence that human-excreted chemicals are most probably responsible for feminization of fish is that there was no correlation between feminization of fish and amounts of industrial waste waters in UK Rivers. Alternatively, the clearest link to the degree of endocrine disruption in wild fish has been found with the proportion of sewage effluent in the river (Jobling et al. 2006). A similar situation was observed in other countries. For example, Snyder et al. (2001) concluded by the use of a TIE approach that E2 and EE2 were the dominant estrogens (contributed 88-99% to the total EEQ) in water samples from 3 municipal WWTPs in south 4

160 central Michigan; 4 locations on the Trenton Channel of the Detroit River, Michigan; and 5 locations in Lake Mead, Nevada. Steroid estrogens were identified by the same approach to cause most observed estrogenicity in WWTPs effluents and their receiving waters in the vicinity of Paris, France or in WWTP effluent discharged to the Tamagawa River in Tokyo (Cargouet et al. 2004, Nakada et al. 2004). A bioassay-directed fractionation method was also developed and applied on male fish bile, since estrogens are mainly excreted via bile into the intestine in fish (Houtman et al. 2004). The natural hormones E2, E1, and E3 accounted for the majority of estrogenic activity in male bream bile at all 3 tested locations in the Netherlands (Houtman et al. 2004). Other studies which have focused on identifying and quantifying causative estrogens in municipal WWTP effluents used comparison of chemical analyses of known estrogenic compounds with in vitro assessment of estrogenicity. Concentrations of detected compounds were multiplied by their relative potencies compared to E2 (derived using the in vitro assay); and summed using concentration additivity. The calculated E2-equivalents (ceeq) were compared to the overall estrogenic activity determined for the whole sample extract by the in vitro assay (EEQ). Authors of these studies mostly concluded that steroid estrogens contributed more than 90% of the measured estrogenic activity (e.g. Aerni et al. 2004, Rutishauser et al. 2004, Korner et al. 2001). However, at some locations concentrations of ceeq were significantly different from the concentrations of EEQ determined by use of bioassays (e.g. Aerni et al. 2004, Thorpe et al. 2006, Vermeirssen et al. 2005). Authors of these studies often stated that it was not clear whether the difference was caused by the combination of uncertainties in the accuracy of analytical and bio-analytical methods or by unknown estrogenic compounds or their interactions (Aerni et al. 2004, Thorpe et al. 2006, Vermeirssen et al. 2005). To address the methodological uncertainties, Avbersek et al. (2011) developed a protocol for determining steroid estrogens in environmental samples which unified the sample preparation for chemical and biological analyses. The authors obtained strong correlations (r 2 >0.92) between calculated concentrations of ceeq and EEQ measured in vitro for both spiked and environmental waste water samples. However, until now their approach had not been applied to a sufficient number of waste waters to make a general conclusion. Beside steroid estrogens, alkylphenols particularly 4-tertiary isomers of nonylphenol (NP) and to lesser extend also octylphenol (OP) have been reported to be responsible for adverse effects on fish at several hot spots associated with particular industries (Sole et al. 2000, Sumpter and Johnson 2008). In these rivers, concentrations of NP exceeded 100 µg/l whereas their common environmental concentrations occur in the low µg/l units or less (Johnson and Jurgens 2003, Sole et al. 2000). NP and OP are transformation products of two of the most important alkylphenol polyethoxylates which have been economically important as nonionic surfactants for decades and used in a variety of industrial and household applications and therefore are ubiquitous (Johnson et al. 2005). Despite their ubiquity, their contributions to in vitro 5

161 estrogenicity in rivers and municipal WWTPs effluents, contrary to WWTP effluents from textile industries, is usually small and corresponds with their small in vitro potencies in nearly all in vitro assays (Table 1). In the European Union (EU), in contrast to the USA, use of nonylphenol ethoxylates as surfactants has been restricted (Directive 2003/53/EC) and consequently, their concentrations in the environment and relative contributions to estrogenicity have been decreasing in the EU in recent years. Moreover, in the EU, NP and OP are considered to be priority pollutants and their concentrations in surface waters should be reduced to less than the Environmental Quality Standards which are 0.3 µg NP/L and 0.1 µg OP/L as annual averages of all detected concentrations (Directive 2008/105/EC). In a recent British study of more than 160 WWTP effluents, the median concentration of NP was 0.22 µg/l which is less than the median concentration in streams of the USA, which was reported to be as great as 0.8 µg NP/L (Gardner et al. 2012, Kolpin et al. 2002). Although the median concentration of NP reported for the study of streams in the USA was influenced by a greater focus on more polluted locations (Kolpin et al. 2002), these results demonstrate that different legislative regulation can result in different environmental concentrations of estrogens in various countries. In a few studies, natural estrogenic compounds, such as phytoestrogens, have been reported to contribute significant proportions of estrogenicity in municipal WWTP effluents or their receiving waters (Liu et al. 2010). In one river in Japan, genistein was identified as the compound responsible for most of the estrogenic activity (Kawanishi et al. 2004). Genistein is one of the most abundant phytoestrogens present in soya, flour and many vegetables and it was also identified in substantial concentrations (around 10 μg/l) in treated effluents from wood pulp mills (Kiparissis et al. 2001). Some other flavonoids have been identified in WWTP effluents or rivers but their concentrations and/or estrogenic potencies were much less (Kawanishi et al. 2004, Lagana et al. 2004, Pawlowski et al. 2003). Compounds with relatively high estrogenic potency are also mycoestrogens, such as zearalenol, although few studies (Lagana et al. 2004, Pawlowski et al. 2003) document their occurrence. A few other studies have investigated estrogenicity in surface water at localities with minimal sources from human activities and detected some estrogenic activity which might have been caused by phytoestrogens (Jarosova et al. 2012, Nadzialek et al. 2010), these studies were not designed to identify the compounds. Overall, it seems that the wide variety of phytoestrogens present in municipal WWTP effluents and/or in rivers could contribute to measured estrogenic activity, even though the examples of their identification are rare. Phytoestrogens should be considered as possible significant contributors to estrogenicity detected in samples from places in the vicinity of plant-product manufactures or places with greater consumption of soya (Liu et al. 2010). Although there is always the possibility that some unexpected compounds could be responsible for estrogenicity of municipal WWTP effluents at specific places; several lines of evidence, the majority of the information presented in the literature and considerable agreement across the world document that steroid estrogens, particularly E1, E2, EE2 and occasionally also 6

162 E3 (when in vitro assays responsive to E3 are used) are usually responsible for majority (often more than 90%) of estrogenic activity of municipal WWTP effluents entering rivers (Sumpter and Johnson 2008) In vitro potency of model estrogens Estrogenic potencies of various compounds, relative to that of E2 and expressed as Estrogenic Equivalency Factors (EEF) within different in vitro assays have been reviewed and the results are summarized (Table 1). According to the data reviewed, EEF of estrogens can differ by orders of magnitude, not only among different in vitro assays but also among laboratories employing different procedures for the same assay. For example, Gutendorf and Westendorf (2001) used 48h exposure in the MVLN assay and reported EEF of E1 to be 0.01 whereas Van den Belt et al. (2004) used 20h exposure in the same assay and reported the EEF of E1 to be 0.2. The largest differences in EEFs of steroid estrogens among different assays can be seen for E3 (Table 1). In the YES assay, the EEF of E3 was lesser by a factor of compared to other assays. The differences in reviewed estrogenic potencies demonstrate the need to use specific EEFs for particular bioassays with standard operating procedure to derive the in vitro EL. It does not seem suitable to consider one level of EEQ determined by any in vitro assay as generally accepted EL. If such a general level would be stated, it should be derived from the bioassays with the lowest EEFs Predicted-no-effect concentrations (PNECs) of steroidal estrogens Steroid estrogens are known to be the most potent estrogens in in vivo assays, all having potencies more than a thousand-fold in the most sensitive organism (fish) than other xenobiotics (Caldwell et al. 2012, Young et al. 2004). Data from studies of effects on reproduction of fishes were used to develop a species sensitivity distribution and PNECs of 0.1 and 2 ng/l for EE2 and E2, respectively, were derived (Caldwell et al. 2012). These PNECs were derived from longterm studies of reproduction used as the most sensitive endpoint in fishes, which were the most sensitive organisms, and should be sufficient for protection of reproductive health in fish exposed continuously for several life stages or multiple generations. In the environment, such constant, continuous exposures are likely to be rare, since concentrations of estrogens vary considerably, depending on hydrological conditions (Anderson et al. 2012). Therefore, PNECs from shorter-term exposure of less than 60 d, were also derived at 0.5 and 5 ng/l for EE2 and E2, respectively (Caldwell et al. 2012). Insufficient data were available to use the same methods to derive PNECs for E1 and E3, and therefore, these PNEC were based on in vivo VTG induction studies and in vitro estrogenicity study accompanied with application of safety factors and the 7

163 assumption that the relative ability to induce VTG by each of the steroid estrogens corresponds with the relative effects on reproductive endpoints (Caldwell et al. 2012). Resulting PNECs were 6 ng/l for E1 and 60 ng/l for E3 during longer-term exposures, and 20 and 200 ng/l for E1 and E3 in shorter-term exposures, respectively (Caldwell et al. 2012). Since it had been established that E1, E2, E3 and EE2 are usually responsible for more than 90% in vitro estrogenicity of treated municipal waste waters and that in vivo these compounds are extremely potent, especially EE2; in vitro ELs for municipal WWTP effluents based on simplified situation assuming that steroid estrogens are responsible for all estrogenicity determined with the in vitro assay were derived. 3. Results and discussion 3.1. Derivation of Estrogenic Limits for municipal waste waters Since EE2 was determined to be the most potent estrogen in vivo and, contrary to other steroid estrogens, it is much more potent in vivo than in vitro by approximately 20-fold; the worst case scenario in vitro EL could be derived by assuming that EE2 is responsible for the all of the in vitro estrogenicity (Equation 1). EL worst-case = EEF EE2 PNEC EE2 (1) Where: EL worst-case is the over-all in vitro estrogenicity below which no in vivo PNECs of steroidal estrogens is exceeded, EEF EE2 is the estrogenic potency of EE2 relative to 17β-estradiol determined in specific in vitro assay and PNEC EE2 is in vivo derived PNEC for EE2. This EL worst-case, specific for particular bioassays, would represent the worst case scenario, but it would not be realistic because EE2 is usually not the only estrogen responsible for the activity (Sumpter and Johnson 2008). To answer the question what portion of in vitro activity can be accounted for by EE2; literature on the occurrence of EE2 and the other steroid estrogens in municipal WWTP effluents was reviewed Occurrence of steroid estrogens in municipal WWTP effluents Concentrations of four main steroid estrogens, E1, E2, E3 and EE2 in effluents of municipal WWTPs were reviewed. Concentrations of all four major estrogens were available for 51 WWTP effluents (Table 2). In total about 150 papers investigating concentrations of estrogens in WWTP effluents were reviewed but most studies either reported only summarized results or did not investigate the presence of E3 since it has relatively small potencies to cause 8

164 endocrine disruption in organisms compared to E1, E2 and EE2 (Caldwell et al. 2012). However, E3 can occur in significant amounts in WWTP effluents (Table 2) and it is quite potent in some in vitro systems (Table 1) and therefore it might be important for interpretation of the overall results. Forty seven out of the 51 WWTP listed in Table 2 included activated sludge treatment, which is the most common technology in municipal WWTPs. Most WWTPs also employed a nitrification step, which is known to enhance degradation of steroid estrogens (e.g. Khanal et al. 2006). Three WWTPs utilized nitrifying and denitrifying bacteria supported by solid filters and one WWTP was a system of lagoons without any artificial biological or chemical treatment. Authors of most studies reported concentrations of steroid estrogens as means of multiple samples collected at particular WWTP. To obtain representative ratios of individual estrogens in different WWTP effluents, mean concentrations of steroids were calculated and used for studies where primary data from all samples were available. When concentrations of some steroid estrogens were available for several samples originating from the same effluent and only some of the values were reported to be less than the Limit of Detection (LOD), 1/2 of LOD (stated in appropriate study) was taken into account. To insure that the maximal contribution of EE2 as well as contributions of other steroids was not significantly underestimated due to averaging the primary data, primary data were investigated separately and both datasets were compared (Supplementary data, Table SD 1, 2). Estrone was the most frequently detected steroid estrogen with the greatest concentrations in most WWTP effluents (Table 2). There are two main reasons for this. First E1 was the second most abundant steroid estrogen in WWTP influents (e.g. Anderson et al. 2012, Liu et al. 2009) and the most abundant one - E3 is known to be quickly degraded in the treatment processes (Anderson et al. 2012, Jin et al. 2008). Also, besides degradation of E1 during treatment, E1 can also be newly formed as a degradation product of E2 (Johnson and Sumpter 2001). Based on the results of published studies, it can be generally concluded that conventional WWTPs, utilizing activated sludge systems without de/nitrification steps, are efficient at removal of E2 (median removal 85%) and E3 (median 97%), but removal of E1 is lower with median of 67% (Anderson et al. 2012). Some studies found E2 to occur at the greatest concentrations in WWTP effluents (Table 2), which indicates the importance of operational conditions and technology of the specific WWTPs. Comparable or greater concentrations of E2 than E1 are typically detected at municipal WWTPs with solid supported bacteria or at conventional WWTPs with shorter retention time of solids, which does not support development of diverse microbial community, particularly nitrifiers (Svenson et al. 2003, Kirk et al. 2002). Due to its relatively lesser potency, E3 is relatively rarely investigated compared to E1, E2, and EE2. E3 has been reported to be rather rapidly degraded in conventional WWTPs (Anderson et al. 2012). However, in effluents of some municipal WWTPs E3 was detected at concentrations that were greater than E1, E2 or EE2. E3 which has been reported to be the most polar estrogen, might be lost during cleanup of samples by use of silica (Aerni et al. 2004, Fernandez et al. 2007). The least 9

165 concentrations and frequency of detection were reported for synthetic steroid EE2 (Table 2). Since the primary route of entry of EE2 into the aquatic environment is through excretion by women using contraceptives, the initial load of this chemical is less than E1, E2 or E3 (Young et al. 2004). EE2 is the least abundant steroid estrogen in effluents of municipal WWTPs (Table 2, 3), but its potency to cause ED, especially in fish, is high. Moreover, its limits of detection are mostly greater than concentrations considered to be biologically potent (Table 2,Young et al. 2004). To confirm the representativeness of concentrations of steroid estrogens median and maximal concentrations were compared to previously reported comprehensive data sets on occurrence of estrogens in treated waste waters (Gardner et al. 2012, Miege et al. 2009). Miege et al. (2009) compiled data about concentrations of emerging pollutants including E1, E2, E3 and EE2 in WWTP influents and effluents but this compilation was not limited to the studies where all four compounds were determined simultaneously as in our study. Gardner et al. (2012) reported recent results of a British national study of more than 160 different municipal WWTP effluents. The medians of all three investigations are similar (Table 3). The maximal observed concentration of E2 was 96 ng/l in the present study and 30 ng/l in a previous study by Miege et al. (2009). However, this difference was caused by one outlier value detected in the sample from a Canadian lagoon system and the 95 centile concentration of E2 was similar to that reported by others (Table 3). The 95%ile of EE2 reported in the British study by Gardner et al. (2012) was less than those observed in the present study or by Miege et al. (2009). The data in the study by Gardner et al. (2012) were more consistent with predictions by Hannah et al. (2009) who calculated concentrations of EE2 based on estimates of per capita use of EE2, water use of 200 L/capita/day, loss of EE2 via metabolism, and loss via removal in treatment in waste waters treated by secondary removal step in Europe and the USA to range from 0.4 to 1.2 ng/l. However, greater concentrations of EE2 observed in the present study as well as in the database presented by Miege et al. (2009) largely originate from the study of 4 WWTPs around Paris, France, where greater concentrations could be explained by greater consumption of EE2 compared to other cities (Cargouet et al. 2004) Determination of percentage contribution of steroid estrogens to total ceeq Based on known concentrations of E1, E2, E3 and EE2 ([E1], [E2], [E3] and [EE2]) in municipal WWTP effluents and in vitro potencies of individual compounds relative to E2 (EEF); the ceeq for each WWTP effluent and each bioassay were calculated (Equation 2). ceeq = [E1] EEF E1 + [E2] EEF E2 + [E3] EEF E3 + [EE2] EEF EE2 (2) The ceeqs were calculated for each specific set of EEFs determined for individual bioassays (Table 1) for which potentials of all 4 estrogens were reported (Table 2, Table SD 3-9). When 10

166 some estrogen was not detected at concentrations greater than LOD, 1/2 of LOD was taken into account. Consequently, the percentage of total ceeq for each steroid estrogen and each in vitro bioassay was determined (Equation 3). P Ei = ([Ei] EEF Ei / ceeq ) 100% (3) Where: P Ei is percentage of total ceeq for Ei, where Ei is E1, E2, E3 or EE2. When less than two steroids were detected at concentrations greater than the LOD in some WWTP effluents, the percentage of total ceeqs was not determined for any steroid in this effluent, because the values would rather be indicative of the LOD than the actual contribution of ceeq. Percentages of contributions to total ceeq which were derived by use of EEFs specific for the MVLN in vitro assay are presented in Table 2. Percentages of contributions to total ceeq calculated for the other 14 bioassays are presented in Supplementary data (Table SD 3-9). In case of the MVLN in vitro assay the ranges of percentages of total ceeq for E1 and E2 were very wide (from 4 to 93%, Table 2). In contrast, the maximal percentages of total ceeq for E3 and EE2 were 40%. Similar patterns were obtained when other in vitro assays were used. The maximal contribution of E1 to total ceeq was 97% in case of YES assays and also ER-CALUX assays, 95% in case of MELN assays and 91% in case of E-screen assays (Table SD 3-9). Maximal percentage of contribution to ceeq for E2 was more than 90% in any types of assays. E3 was responsible maximally for 4% of the ceeq in the assessment on YES assays but the maximal contribution to total ceeq by E3 was 64% when assessed by other bioassays. EE2 was usually responsible for about 20% of total ceeq (median of percentage of ceeq for most assays), but the maximal value from all of the assays was 68%. In most assays, EE2 was responsible for less than 50% of total ceeq (Table SD 3-9) Safe levels of estrogenic activity (estrogenic limits) in municipal WWTP effluents determined by in vitro assays After determination of maximal percentage of total ceeq contributed by each considered estrogen by use of each bioassay, the concentration of EEQ below which PNECs of the steroids would not be exceeded, were derived (Equation 4). EL Ei = EEF Ei PNEC Ei / (P Ei-max / 100%) (4) Where: Ei is E1, E2, E3 or EE2, EEF Ei is estrogenic potency of model compound (Ei) relative to 17β-estradiol determined in specific in vitro assay, PNEC Ei is in vivo derived PNEC for individual Ei, and P Ei-max is maximal percentage of total ceeq for each Ei determined for specific bioassay. 11

167 The use of P Ei-max was more protective than use of the 95%ile of P Ei not only to be precautionary, but also because there were large differences among P max and P 95%ile for E1 and E1 was often the only steroid present in effluents at concentrations greater than the LOD (Table 2). Here a final safe concentration of total measured EEQ in municipal effluents that is expected to cause no adverse effects, is defined as the estrogenic limit (EL) and represents in vitro EEQ at which none of the PNECs for individual estrogens, E1, E2, E3 or EE2 is exceeded. When EL Ei were calculated for all four of these compounds, the least concentration was reported as the proposed EL. For nine of the 15 bioassays studied (Table 4) the EL EE2 was the least EL Ei despite the fact that EE2 occurred at the lowest concentrations of the investigated compounds (Table SD 10). The reason for this is the greater in vivo estrogenic potency of EE2, as measured by the PNEC, which was less than in case of E1, E2 or E3 by factors ranging from 10 to 600. For six of the 15 bioassays the EL E1 was the least EL Ei. These 6 bioassays had EEF E1 values ranging from 0.01 to 0.03, which is approximately an order of magnitude less than the EEF E1 derived by use of most bioassays (Table 1). In all investigated bioassays EL E2 and especially EL E3 were much greater, by factors 3-15 in the case of EL E2 and in the case of EL E3, than the final ELs, which is indicative of the lower risks posed by E3 and to a lesser extent E2 compared to E1 and EE2. This result is consistent with previous assumptions (Johnson and Sumpter 2001). Since in vivo PNECs for steroids have been determined for longer-term (multi-generation studies, more than 60d) and shorter-term (less than 60d) exposures, ELs were also calculated for both shorter- and longer-term exposure scenarios. Under environmental conditions concentrations of the steroids in rivers receiving WWTP effluents vary depending mainly on high and low water flows (Anderson et al. 2012). During rainless days and/or dryer seasons, river flow is usually lesser and since there is less dilution, concentrations in rivers can be greater. However, such conditions can be of relatively short duration, lasting only several days (Anderson et al. 2012). Therefore, the shorter-term ELs are more appropriate for evaluation of samples taken during these periods. Alternatively, longer-term ELs should be used when assessing potential effects during periods of mean or greater than average flows that might occur during rainy days or wetter seasons, when the estrogenicity can be expected to not decrease much for periods longer than 60d. In vitro ELs for longer-term exposures ranged from 0.1 to 0.4 ng EEQ/L with a median of 0.3 ng EEQ/L, while ELs for shorter-term exposures ranged from 0.5 to 2 ng EEQ/L with a median of 1.3 ng EEQ/L (Table 4). The smaller values for the ELs are near LOD of most bioassays (Leusch et al. 2010). However, WWTP effluents are usually diluted by recipients so ELs should be divided by appropriate dilution factors. For example if the contribution of WWTP effluent to the river flow was 10%, the ELs would vary 1 from 4 ng EEQ/L and 5 to 20 ng/l EEQ for longer-term and shorter-term exposures, respectively. Use of EEFs for individual steroid hormones and knowledge of dilution factors for specific points in space and time allow comparison of LODs of the bioassays with the ELs so that it can be decided whether less 12

168 expensive assays, with greater LODs can be used. When untreated waste waters are considered as a possible source of estrogenic contamination, the percentage of total ceeq for EE2 would be less due to the presence of greater concentrations of natural estrogens (Anderson et al. 2012, Miege et al. 2009, Muller et al. 2008, Liu et al. 2009). Therefore, ELs derived for municipal WWTP effluents are protective enough also for untreated municipal waste waters Estrogenic Limits for rivers receiving municipal WWTP effluents ELs developed to assess municipal WWTP effluents might be directly applicable for only some reaches of rivers that are influenced primarily by WWTP effluents. With increasing distance from discharges, proportions of total ceeq might change due to differential weathering in rivers. For E1 and E2 similar ranges of half-lives at 20 C in river water were reported to be 5 and 3d, respectively, whereas EE2 was more persistent (Jurgens et al. 2002). Photodegradation is the primary mechanism of transformation of EE2 with a half-life in water of approximately 17d (Jurgens et al. 2002, Sumpter et al. 2006). Greater proportions of EE2 to ceeq were observed in river water compared to WWTP discharge (Cargouet et al. 2004). While it would be useful to know the relative percentage contributions of individual estrogens to total ceeq in different distances from WWTP discharges, few data are available on this this phenomenon. This is because steroid estrogens occur in rivers at concentrations that are near to or less than the LODs for instrumental quantification. However, these small contributions can still be biologically relevant. For instance, when the in vivo PNEC for EE2 is compared with reported LODs (Table 2) it can be seen that the PNECs are of the same order of magnitude. Information about compounds responsible for estrogenicity as well as for other specific modes of actions in rivers is limited compared to what is available for WWTP effluents or rivers close to their discharges. Therefore, more research is needed to enable derivation of ELs for parts of rivers which are not in close vicinity of WWTP discharges Applicability of derived Estrogenic Limits and future research The derived in vitro ELs are applicable for municipal WWTP effluents and parts of rivers close to their discharges where E1, E2, E3 and EE2 are expected to be responsible for the majority of the estrogenicity. Most information on the occurrence of steroid estrogens in waste waters presented here originate from European countries, therefore the best applicability of the ELs should be for the situation in Europe. Different patters might occur in other regions of the world which could change the proportion of occurrence of estrogenic compounds in waters. For instance, in Japan, there is little use of the contraceptives and therefore the contribution of EE2 to the estrogenicity would be expected to be less than in EU countries (Sumpter and Johnson 2008). 13

169 Alternatively, greater concentration of EE2, of more than 100 ng/l, were reported in a single sample of effluent from WWTP in Canada (Fernandez et al. 2007). This demonstrates the possibility of different P EE2-max compared to those reported in dataset used in this study. Most WWTP effluents investigated in this study employed primary treatment followed by activated sludge treatment, which represent the most common type of municipal WWTPs. However, different types of treatment could also result in different ratios of steroid estrogens. EL worst-case might be applied in cases when the presented percentages of total ceeq cannot be considered to be representative (Table 4). Once the proposed EL approach is applied, the database used for P Eimax derivation can be enlarged or modified according to relevant available information e.g. from national reports. It is also necessary to point out the limited ability of in vitro estrogenicity assays to detect some compounds with lesser in vitro potencies, which might lead to underestimation of their estrogenic effects in case when the in vivo potencies would be much greater (relative to E2). In vivo PNECs have not been determined for many estrogenic compounds which might occur in some aquatic environments and therefore more research is needed to evaluate the applicability of the in vitro estrogenicity assays to be used in environments where the steroid estrogens cannot be expected as the dominant estrogens. Last but not least, it should be always kept in mind that the mentioned in vitro estrogenicity assays evaluate one specific mechanism of action and that there are usually compounds with different modes of actions in environmental matrices. 4. Conclusions Bioassay specific thresholds for over-all in vitro estrogenicity in municipal WWTP effluents were derived considering bioassay specific in vitro potencies of major steroidal estrogens, in vivo derived PNECs of these compounds, and their relative contributions to the over-all estrogenic activity detected in municipal WWTP effluents. Since the in vivo PNECs for the steroids have been determined for longer-term (more than 60d) and short-term (less than 60d) exposures, also the ELs have been calculated for short-term and longer-term exposure scenarios. The ELs for longerterm exposures should be used for samples when we can expect no decrease of estrogenicity in periods longer than 60d, which usually corresponds with periods of average or high river flow. In low-flow seasons when dilution can be expected in less than 60d the ELs based on short-term in vivo studies should be used. The derived ELs for 15 individual bioassays varied from 0.1 to 0.4 ng/l EEQ for longer-term exposures and from 0.5 to 2 ng/l EEQ for short-term exposures, respectively. The best applicability of the derived ELs is for areas, where steroidal estrogens have been confirmed or suspected as being responsible for fish feminization downstream municipal WWTPs. 14

170 Acknowledgements The work was supported by the Czech Science Foundation grant No. GACR P503/12/0553. Prof. Giesy was supported by the Canada Research Chair program, a Visiting Distinguished Professorship in the Department of Biology and Chemistry and State Key Laboratory in Marine Pollution, City University of Hong Kong, the 2012 "High Level Foreign Experts" (#GDW ) program, funded by the State Administration of Foreign Experts Affairs, the P.R. China to Nanjing University and the Einstein Professor Program of the Chinese Academy of Sciences. References Aerni HR, Kobler B, Rutishauser BV, Wettstein FE, Fischer R, Giger W, Hungerbuhler A, Marazuela MD, Peter A, Schonenberger R and others Combined biological and chemical assessment of estrogenic activities in wastewater treatment plant effluents. Analytical and Bioanalytical Chemistry 378(3): Anderson PD, Johnson AC, Pfeiffer D, Caldwell DJ, Hannah R, Mastrocco F, Sumpter JP, Williams RJ Endocrine disruption due to estrogens derived from humans predicted to be low in the majority of U.S. surface waters. Environmental Toxicology and Chemistry 31(6): Avbersek M, Zegura B, Filipic M, Heath E Integration of GC-MSD and ER-Calux (R) assay into a single protocol for determining steroid estrogens in environmental samples. Science of the Total Environment 409(23): Balaguer P, Fenet H, Georget V, Comunale F, Terouanne B, Gilbin R, Gomez E, Boussioux AM, Sultan C, Pons M and others Reporter cell lines to monitor steroid and antisteroid potential of environmental samples. Ecotoxicology 9(1-2): Baronti C, Curini R, D'Ascenzo G, Di Corcia A, Gentili A, Samperi R Monitoring natural and synthetic estrogens at activated sludge sewage treatment plants and in a receiving river water. Environmental Science & Technology 34(24): Bermudez DS, Gray LE, Wilson VS Modelling defined mixtures of environmental oestrogens found in domestic animal and sewage treatment effluents using an in vitro oestrogen-mediated transcriptional activation assay (T47D-KBluc). International Journal of Andrology 35(3): Bjorkblom C, Salste L, Katsiadaki I, Wiklund T, Kronberg L Detection of estrogenic activity in municipal wastewater effluent using primary cell cultures from three-spined stickleback and chemical analysis. Chemosphere 73(7): Bolong N, Ismail AF, Salim MR, Matsuura T A review of the effects of emerging contaminants in wastewater and options for their removal. Desalination 239(1-3): Breinholt V, Larsen JC Detection of weak estrogenic flavonoids using a recombinant yeast strain and a modified MCF7 cell proliferation assay. Chemical Research in Toxicology 11(6):

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176 Table 1. Estrogenic potencies of model compounds relative to 17 -estradiol (Estrogenic Equivalency Factors - EEFs) determined in different in vitro assays. Chemical YES ER-CALUX MELN T47D-KBluc E-SCREEN MVLN Estrone * Estriol 3.50E E * 2.40E E E α-ethynylestradiol * Nonylphenol 2.19E E E E E E E E E E E E E E E E E E E E E E E E E E E E tert-Octylphenol 4.79E-04 3 Cytotoxic #3 4.79E E E E E E E E E E E E E E E-04 3 Genistein 2.45E E E E E E E E E E E-03 ** E-05 3 YES - yeast estrogenicity screening assay (Routledge and Sumpter 1996), ER-CALUX - Estrogen Receptor mediated Chemical Activated LUciferase gene expression assay (Van der Burg et al. 2010), MELN - MCF-7 cells stably transfected with the estrogen responsive gene EREbetaGlob-Luc-SVNeo (Balaguer et al. 2000), T47D-KBluc - T47D human breast cancer cells stably transfected with a triplet estrogen-responsive elements promoter luciferase reporter gene construct (Wilson et al. 2004), E-SCREEN - the MCF7 cell proliferation assay (Soto et al. 1998), MVLN - MCF-7 cells stably transfected with luciferase gene under the control of estrogen receptor (Demirpence et al. 1993) *Original unpublished data - in vitro potencies determined by the authors of the present study by comparing the EC 50 values from dose-response curves of E 2 and other estrogens # 4-tert-Octylphenol was cytotoxic to the cells at concentrations lower than EC 50 ** value based on EC 10, not EC Svenson et al. (2003), 2. Murk et al. (2002), 3. Leusch et al. (2010), 4. Bermudez et al. (2012), 5. Gutendorf and Westendorf (2001), 6. Van den Belt et al. (2004), 7. Sonneveld et al. (2006), 8. Furuichi et al. (2004), 9. Aerni et al. (2004), 10. Legler et al. (2002), 11. Drewes et al. (2005), 12. Avbersek et al. (2011), 13. Korner et al. (2001), 14. Houtman et al. (2004), 15. Pawlowski et al. (2004), 16. Caldwell at al. (2012), 17. Thorpe et al. (2006), 18. Rutishauser et al. (2004), 19. Snyder et al. (2001), 20. Leusch et al. (2006), 21. Wilson et al. (2004), 22. Breinholt and Larsen (1998), 23. Nishihara et al. (2000) 21

177 Table 2. Concentrations of four main steroidal estrogens (E1, E2, E3 and EE2) and their relative percentage contribution (P) to total calculated estrogenic equivalents (ceeq) in municipal WWTP effluents Country WWTP Name or Code Equiv. Citizens (thousands) N Concentration (ng/l) (Average of N samples) ceeq P-Percentage of total ceeq for MVLN assay # E1 E2 E3 EE2 (ng/l) E1 E2 E3 EE2 Switzerland (Aerni et al. 2004)## France (Aerni et al. 2004) ## Italy, Roma (Baronti et al. 2000), (Johnson et al. 2000) France (Muller et al. 2008) Finland (Bjorkblom et al. 2008) Greece (Pothitou & Voutsa 2008) Norway (Thomas et al. 2007) France (Cargouet et al. 2004) Austria (Clara et al. 2005) France (Labadie & Budzinski 2005a) France (Labadie & Budzinski 2005b) Slovenia (Avbersek et al. 2011) California (Drewes et al. 2005) China, Chongqing (Ye et al. 2012) Glatt <(0.7-1) * Rontal Surental <(1-1.5 ) <(0.7-1) * 15* Fr <(1-1.5 ) <(0.7-1) * 12* Fr <(1-1.5 ) <(0.7-1) * 6* Cobis Fregene Ostia Roma Sud Roma Est Roma Nord WWTP < * 38 Turku 160 n.a <0.6 < * 1*. WWTP 1 n.a. 5 <3 <2 <3 < Oslo TF <3 <3 < > Evry Valenton Colombes TF Aheres WWTP n.a WWTP n.a 8.0 < * WWTP n.a <1 <5 <1 < WWTP 4 6 n.a Eysines < * Elbeuf 110 n.a 1.9 <1.8 <4.8 < > Rouen 450 n.a <2.4 < < >6 - Tancarville n.a. n.a 4.1 <5.3 <3.1 < > WWTP < * WWTP <1.4 < * 20* WWTP < * WWTP 1 > <1 <2 < > WWTP 2 > <1 <1 <1 < WWTP 3 > WWTP 4 > <4.7 < * 5* WWTP 5 > < * WWTP 6 > <0.6 <3.3 < > WWTP 7 > <3.3 < * 9* WWTP A <1.5 <2.5 < > WWTP B <2.5 < * 19* WWTP C <1.5 <2.5 < > WWTP D < < * 22 33* WWTP E < < * 24 40* WWTP F <1.5 <2.5 < > WWTP G <1.5 <2.5 < > WWTP H < < * 27 32* WWTP I n.a <1.5 <2.5 < >

178 Country WWTP Name or Code Equiv. Citizens (thousands) N Concentration (ng/l) (Average of N samples) ceeq P-Percentage of total ceeq for MVLN assay # E1 E2 E3 EE2 (ng/l) E1 E2 E3 EE2 Canada (Fernandez et al. 2007) WWTP J <1.5 <2.5 < > WWTP B TF ** WWTP C <7.1 <1.5 < > WWTP D <7.1 <1.5 < > WWTP E W AVERAGE MEDIAN < min <1 <1 <0.6 <0.2 < max %ile < N - number of samples of which the average concentration is displayed ceeq - calculated Estrogenic Equivalent (eq. 2) # - EEF E1 was 0.13; EEF E2 was 1; EEF E3 was 0.11; and EEF EE2 was 1.09 as determined by the authors of the present study by comparing the EC50 values from dose-response curves of E2 and other estrogens in MVLN assay # # - only minimal and maximal values were reported in this study, therefore the averages were calculated from this values * - ½ of LOD was taken into account ** - one out of 7 values was excluded from displayed data as outlier value n.a. - not available TF - trickling filter technology W - wetland lagoons without any other treatment steps (17d hydraulic retention time) 23

179 Table 3. Comparison of medians and maximal concentrations of steroid estrogens in municipal waste water treatment plant effluents among different data sets E1 (ng/l) E2 (ng/l) E3 (ng/l) EE2 (ng/l) N med max 95%ile N med max 95%ile N med max 95%ile N med max 95%ile This study < Miege et al.(2009) n.a n.a n.a n.a. Gardner et al.(2012) n.a n.a n.a med - median n.a. - not available N - number of investigated WWTP effluents 24

180 Table 4. Proposed estrogenic limits (ELs) for total EEQs determined by use of in vitro bioassays in municipal waste water treatment plant effluents and/or rivers close to their discharges Assay EL - municipal waste waters (ng EEQ/L) longer-term exposures shorter-term exposures longer-term exposures EL worst case (ng EEQ/L) shorter-term exposures YES (Aerni et al. 2004), (Rutishauser et al. 2004) YES (Svenson et al. 2003) YES (Caldwell et al. 2012) YES (Leusch et al. 2010) ER-CALUX (Sonneveld et al. 2006) ER-CALUX (Avbersek et al. 2011) ER-CALUX (Houtman et al. 2004) MELN (Leusch et al. 2010) MELN (Leusch et al. 2010) E-screen (Gutendorf and Westendorf 2001) E-screen (Drewes et al. 2005) E-screen (Leusch et al. 2010) E-screen (Leusch et al. 2010) MVLN* MVLN (Gutendorf and Westendorf 2001) Min Max Median EL - proposed safe levels of in vitro determined estrogenicity YES - yeast estrogenicity screening assay (Routledge and Sumpter 1996) ER-CALUX - Estrogen Receptor mediated Chemical Activated LUciferase gene expression assay (Van der Burg et al. 2010) MELN - MCF-7 cells stably transfected with the estrogen responsive gene ERE-betaGlob-Luc-SVNeo (Balaguer et al. 2000) E-SCREEN - the MCF7 cell proliferation assay (Soto et al. 1998) MVLN - MCF-7 cells stably transfected with luciferase gene under the control of estrogen receptor (Demirpence et al. 1993) *Unpublished data - in vitro potencies were determined by the authors of the present study by comparing the EC50 values from dose-response curves of E2 and other estrogens 25

181 Supplementary data What level of estrogenic activity determined by in vitro assays in municipal waste waters can be considered as safe? Barbora Jarošová a, Luděk Bláha a, John P. Giesy b, Klára Hilscherová a * a Research Centre for Toxic Compounds in the Environment (RECETOX), Masaryk University, Kamenice 3, CZ Brno, Czech Republic b Department of Biomedical Veterinary Sciences and Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada * corresponding author, hilscherova@recetox.muni.cz, tel:

182 Comparison of primary and averaged data of concentrations of steroid estrogens in municipal WWTP effluents Ratios of concentrations of individual steroids were calculated for both datasets (with primary and averaged concentrations of steroid estrogens, Table SD 1, 2) according to eq. SD 1. Ei Percentage of total concentration = 100 % [Ei] / ([E1] + [E2] + [E3] + [EE2]) (eq. SD 1.) Where: Ei is E1, E2, E3 or EE2 The 95 %ile contributions of E1, E2, E3 and EE2 were comparable in both data sets; and the 95 %ile of contribution of EE2 was even greater in averaged dataset indicating no significant underestimation due to averaging of the primary data (Table SD 1, 2). 27

183 Table SD 1. Concentrations of four main steroid estrogens (E1, E2, E3 and EE2) expressed as averages of N samples from one location and the comparison of their relative contribution to total concentration. Country Switzerland (Aerni et al. 2004)# France (Aerni et al. 2004) # Italy, Roma (Baronti et al. 2000), (Johnson et al. 2000) France (Muller et al. 2008) Finland (Bjorkblom et al. 2008) Greece (Pothitou & Voutsa 2008) Norway (Thomas et al. 2007) France (Cargouet et al. 2004) Austria (Clara et al. 2005) France (Labadie & Budzinski 2005a) France (Labadie & Budzinski 2005b) Slovenia (Avbersek et al. 2011) California (Drewes et al. 2005) China, Chongqing (Ye et al. 2012) WWTP Name or Equiv. Citizens N Concentration (ng/l) Percentage of total concentration (%) Code (thousands) E1 E2 E3 EE2 E1 E2 E3 EE2 Glatt <(0.7-1) Rontal Surental <(1-1.5 ) <(0.7-1) Fr <(1-1.5 ) <(0.7-1) Fr <(1-1.5 ) <(0.7-1) Cobis Fregene Ostia Roma Sud Roma Est Roma Nord WWTP < Turku 160 n.a <0.6 < WWTP 1 n.a. 5 <3 <2 <3 < Oslo TF <3 <3 < Evry Valenton Colombes TF Aheres WWTP n.a WWTP n.a. 8.0 < WWTP n.a. <1 <5 <1 < WWTP 4 6 n.a Eysines < Elbeuf 110 n.a. 1.9 <1.82 <4.76 < Rouen 450 n.a. <2.4 < < Tancarville n.a. n.a. 4.1 <5.3 <3.06 < WWTP < WWTP <1.4 < WWTP < WWTP 1 > <1 <2 < WWTP 2 > <1 <1 <1 < WWTP 3 > WWTP 4 > <4.7 < WWTP 5 > < WWTP 6 > <0.6 <3.3 < WWTP 7 > <3.3 < WWTP A <1.5 <2.5 < WWTP B <2.5 < WWTP C <1.5 <2.5 < WWTP D < < WWTP E < < WWTP F <1.5 <2.5 < WWTP G <1.5 <2.5 <

184 Country Canada (Fernandez et al. 2007) WWTP Name or Code Equiv. Citizens (thousands) Percentage of total concentration (%) N Concentration (ng/l) E1 E2 E3 EE2 E1 E2 E3 EE2 WWTP H < < WWTP I n.a <1.5 <2.5 < WWTP J <1.5 <2.5 < WWTP B TF * WWTP C <7.1 <1.5 < WWTP D <7.1 <1.5 < WWTP E W Average Median < %il max # - averages were calculated from minimal and maximal values reported in the study * - one out of 7 values was excluded from displayed data as outlier value n.a. - not available N - number of samples of which the average concentration is displayed TF - trickling filter technology W - wetland lagoons without any other treatment steps (17d hydraulic retention time) 29

185 Table SD 2. Concentrations of four main steroid estrogens (E1, E2, E3 and EE2) as measured in individual samples (or in the minimum number of samples reported in the cited literature) and the comparison of their relative contribution to total concentration. Country Italy, Roma (Baronti et al. 2000), (Johnson et al. 2000) Italy, Roma (Baronti et al. 2000), (Johnson et al. 2000) Italy, Roma (Baronti et al. 2000), (Johnson et al. 2000) Italy, Roma (Baronti et al. 2000), (Johnson et al. 2000) Italy, Roma (Baronti et al. 2000), (Johnson et al. 2000) Italy, Roma (Baronti et al. 2000), (Johnson et al. 2000) France (Muller et al. 2008) Austria (Clara et al. 2005) France (Labadie & Budzinski 2005a) WWTP Name or Code Equiv. Citizens (thousands) N Concentration (ng/l) Percentage of total concentration (%) E1 E2 E3 EE2 E1 E2 E3 EE2 Cobis 40 1 <0.5 < < < < Fregene < < Ostia < < < < Roma Sud < < < Roma Est < Roma Nord < < < WWTP < <0.5-1 < WWTP 4 a <5 < WWTP 4 b 1 <1 8 1 < WWTP 4 c <1 < Eysines <2 <1 < < <1.0 <1.0 <

186 Country France, Saine (Labadie & Budzinski 2005b) Slovenia (Avbersek et al. 2011) Canada (Fernandez et al. 2007) WWTP Name or Code Equiv. Citizens (thousands) N Concentration (ng/l) Percentage of total concentration (%) E1 E2 E3 EE2 E1 E2 E3 EE2 Elbeuf <2.0 <1.9 <4.5 < <3.8 <8.0 < <3.5 <0.6 <4.9 < <0.5 <0.4 <0.8 < <4.3 <2.4 <5.6 < Rouen <1.8 <1.9 <4.0 < <3.0 <3.8 <8.0 < >1 <3.3 < < <0.5 <0.4 <2.1 < <3.4 <2.5 <7.3 < Tancarville n.a. 1 <2.8 <2.5 <3.0 < >1 4.2 <0.8 <1.8 < >1 1.8 <0.3 <3.6 < >1 8.3 <0.3 <1.9 < >1 4.9 <1.4 <5.0 < WWTP 1 a < WWTP 1 b < WWTP 3 a <1.4 < WWTP 3 b < WWTP 3 c <0.4 <1.4 < WWTP B WWTP B <1.5 < WWTP B3 1 < < WWTP B4 1 <7.6 1 <1.5 < WWTP B5 1 <7.6 3 < WWTP B <1.5 < WWTP B < WWTP B8* < WWTP E <1.5 < WWTP E < WWTP E Average Median < %il max * - the measured sample was excluded from calculation of ratio of individual estrogens as outlier n.a. - not available N - number of samples of which the average concentration is displayed 31

187 Relative percentage contributions of four main steroid estrogens to the total calculated estrogenic equivalents in municipal WWTP effluents determined for different in vitro bioassays Table SD 3. Relative percentage contribution of four main steroid estrogens (E1, E2, E3 and EE2) to total concentrations of calculated estrogenic equivalents (ceeq) in municipal WWTP effluents determined for YES bioassay using 2 sets of EEFs reported in Aerny et al. (2004) and Rutishauer et al. (2004) and Svenson et al. (2003) Country Switzerland (Aerni et al. 2004)* France (Aerni et al. 2004)* Italy, Roma (Baronti et al. 2000), (Johnson et al. 2000) France (Muller et al. 2008) Finland (Bjorkblom et al. 2008) Greece (Pothitou & Voutsa 2008) Norway (Thomas et al. 2007) France (Cargouet et al. 2004) Austria (Clara et al. 2005) France (Labadie & Budzinski 2005a) France (Labadie & Budzinski 2005b) Slovenia (Avbersek et al. 2011) WWTP Name or Code YES assay (Aerni et al. 2004), (Rutishauser et al. 2004) (Svenson et al. 2003) YES assay ceeq # P-Percentage of total ceeq ceeq ## P-Percentage of total ceeq ng/l E1 E2 E3 EE2 ng/l E1 E2 E3 EE2 Glatt Rontal Surental Fr Fr Cobis Fregene Ostia Roma Sud Roma Est Roma Nord WWTP Turku WWTP 1 Oslo TF Evry Valenton Colombes TF Aheres WWTP WWTP WWTP 3 WWTP Eysines Elbeuf Rouen Tancarville WWTP

188 Country WWTP Name or Code YES assay (Aerni et al. 2004), (Rutishauser et al. 2004) (Svenson et al. 2003) YES assay ceeq # P-Percentage of total ceeq ceeq ## P-Percentage of total ceeq ng/l E1 E2 E3 EE2 ng/l E1 E2 E3 EE2 WWTP WWTP California WWTP 1 (Drewes et al. 2005) WWTP 2 WWTP WWTP WWTP WWTP 6 WWTP China, Chongqing WWTP A (Ye et al. 2012) WWTP B WWTP C WWTP D WWTP E WWTP F WWTP G WWTP H WWTP I WWTP J Canada WWTP B TF (Fernandez et al. 2007) WWTP C WWTP D WWTP E W AVERAGE MEDIAN %ile max ceeq - calculated Estrogenic Equivalent; ceeq = [E1] EEF E1 + [E2] EEF E2 + [E3] EEF E3 + [EE2] EEF EE2 where [E1],[E2],[E3] and [EE2] are concentrations of estrogens displayed in Table 2 and EEF s are in vitro potencies determined for individual bioassays # - EEF E1 was 0.38; EEF E2 was 1; EEF E3 was ; and EEF EE2 was 1.19 as determined by Aerny et al. (2004) and Rutishauer et al. (2004) ## - - EEF E1 was 0.19; EEF E2 was 1; EEF E3 was ; and EEF EE2 was 2.2 as determined by Svenson et al. (2003) * - averages were calculated from minimal and maximal values reported in the study TF - trickling filter technology W - wetland lagoons without any other treatment steps (17d hydraulic retention time) 33

189 Table SD 4. Relative percentage contribution of four main steroid estrogens (E1, E2, E3 and EE2) to the total calculated estrogenic equivalents (ceeq) in municipal WWTP effluents determined for YES bioassay using 2 sets of EEFs reported by Routledge et al. in Caldwell et al. (2012) and Fang et al. in Leusch et al. (2010) Country Switzerland (Aerni et al. 2004)* WWTP Name or Code YES assay (Caldwell et al. 2012) (Leusch et al. 2010) YES assay ceeq # P-Percentage of total ceeq ceeq ## P-Percentage of total ceeq ng/l E1 E2 E3 EE2 ng/l E1 E2 E3 EE2 Glatt Rontal Surental France Fr (Aerni et al. 2004)* Fr Italy, Roma Cobis (Baronti et al. 2000), (Johnson et al. 2000) Fregene Ostia Roma Sud Roma Est Roma Nord France (Muller et al. 2008) WWTP Turku Finland (Bjorkblom et al. 2008) Greece (Pothitou & Voutsa 2008) Norway (Thomas et al. 2007) France (Cargouet et al. 2004) Austria (Clara et al. 2005) France (Labadie & Budzinski 2005a) France (Labadie & Budzinski 2005b) Slovenia (Avbersek et al. 2011) California (Drewes et al. 2005) WWTP 1 Oslo TF Evry Valenton Colombes TF Aheres WWTP WWTP WWTP 3 WWTP Eysines Elbeuf Rouen Tancarville WWTP WWTP WWTP WWTP 1 WWTP 2 WWTP

190 Country WWTP Name or Code YES assay (Caldwell et al. 2012) (Leusch et al. 2010) YES assay ceeq # P-Percentage of total ceeq ceeq ## P-Percentage of total ceeq ng/l E1 E2 E3 EE2 ng/l E1 E2 E3 EE2 WWTP WWTP WWTP 6 WWTP China, Chongqing (Ye et al. 2012) WWTP A WWTP B WWTP C WWTP D WWTP E WWTP F WWTP G WWTP H WWTP I WWTP J Canada WWTP B TF (Fernandez et al. 2007) WWTP C WWTP D WWTP E W AVERAGE MEDIAN %ile max ceeq - calculated Estrogenic Equivalent; ceeq = [E1] EEF E1 + [E2] EEF E2 + [E3] EEF E3 + [EE2] EEF EE2 where [E1],[E2],[E3] and [EE2] are concentrations of estrogens displayed in Table 2 and EEF s are in vitro potencies determined for individual bioassays # - EEF E1 was 0.33; EEF E2 was 1; EEF E3 was 0.003; and EEF EE2 was 1 as determined by Routledge et al. in Caldwell et al. (2012) ## - EEF E1 was 0.096; EEF E2 was 1; EEF E3 was 0.006; and EEF EE2 was 0.89 as determined by and Fang et al. in Leusch et al. (2010) * - averages were calculated from minimal and maximal values reported in the study TF - trickling filter technology W - wetland lagoons without any other treatment steps (17d hydraulic retention time) 35

191 Table SD 5. Relative percentage contribution of four main steroid estrogens (E1, E2, E3 and EE2) to the total calculated concentrations of estrogenic equivalents (ceeq) in municipal WWTP effluents determined for ER-CALUX bioassay using 2 sets of EEFs reported in Sonneveld et al. (2006) and Avbersek et al. (2011) Country Switzerland (Aerni et al. 2004)* France (Aerni et al. 2004)* Italy, Roma (Baronti et al. 2000), (Johnson et al. 2000) France (Muller et al. 2008) Finland (Bjorkblom et al. 2008) Greece (Pothitou & Voutsa 2008) Norway (Thomas et al. 2007) France (Cargouet et al. 2004) Austria (Clara et al. 2005) France (Labadie & Budzinski 2005a) France (Labadie & Budzinski 2005b) Slovenia (Avbersek et al. 2011) California (Drewes et al. 2005) WWTP Name or Code ER-CALUX assay (Sonneveld et al. 2006) (Avbersek et al. 2011) ER-CALUX assay ceeq # P-Percentage of total ceeq ceeq ## P-Percentage of total ceeq ng/l E1 E2 E3 EE2 ng/l E1 E2 E3 EE2 Glatt Rontal Surental Fr Fr Cobis Fregene Ostia Roma Sud Roma Est Roma Nord WWTP Turku WWTP 1 Oslo TF Evry Valenton Colombes TF Aheres WWTP WWTP WWTP 3 WWTP Eysines Elbeuf Rouen Tancarville WWTP WWTP WWTP WWTP 1 WWTP 2 36

192 Country WWTP Name or Code ER-CALUX assay (Sonneveld et al. 2006) (Avbersek et al. 2011) ER-CALUX assay ceeq # P-Percentage of total ceeq ceeq ## P-Percentage of total ceeq ng/l E1 E2 E3 EE2 ng/l E1 E2 E3 EE2 WWTP WWTP WWTP WWTP 6 WWTP China, Chongqing WWTP A (Ye et al. 2012) WWTP B WWTP C WWTP D WWTP E WWTP F WWTP G WWTP H WWTP I WWTP J Canada WWTP B TF (Fernandez et al. 2007) WWTP C WWTP D WWTP E W AVERAGE MEDIAN %ile max ceeq - calculated Estrogenic Equivalent; ceeq = [E1] EEF E1 + [E2] EEF E2 + [E3] EEF E3 + [EE2] EEF EE2 where [E1],[E2],[E3] and [EE2] are concentrations of estrogens displayed in Table 2 and EEF s are in vitro potencies determined for individual bioassays # - EEF E1 was 0.016; EEF E2 was 1; EEF E3 was 0.036; and EEF EE2 was 1.86 as determined by Sonneveld et al. (2006) ## - EEF E1 was 0.4; EEF E2 was 1; EEF E3 was 0.14; and EEF EE2 was 1.68 as determined by Avbersek et al. (2011) * - averages were calculated from minimal and maximal values reported in the study TF - trickling filter technology W - wetland lagoons without any other treatment steps (17d hydraulic retention time) 37

193 Table SD 6. Relative percentage contribution of four main steroid estrogens (E1, E2, E3 and EE2) to the total calculated concentrations of estrogenic equivalents (ceeq) in municipal WWTP effluents determined for two individual bioassays using sets of EEFs reported in Houtman et al. (2004) and Pillon et al. in Leusch et al. (2010) Country Switzerland (Aerni et al. 2004)* France (Aerni et al. 2004)* Italy, Roma (Baronti et al. 2000), (Johnson et al. 2000) France (Muller et al. 2008) Finland (Bjorkblom et al. 2008) Greece (Pothitou & Voutsa 2008) Norway (Thomas et al. 2007) France (Cargouet et al. 2004) Austria (Clara et al. 2005) France (Labadie & Budzinski 2005a) France (Labadie & Budzinski 2005b) Slovenia (Avbersek et al. 2011) California (Drewes et al. 2005) WWTP Name or Code ER-CALUX assay (Houtman et al. 2004) (Leusch et al. 2010) MELN assay ceeq # P-Percentage of total ceeq ceeq ## P-Percentage of total ceeq ng/l E1 E2 E3 EE2 ng/l E1 E2 E3 EE2 Glatt Rontal Surental Fr Fr Cobis Fregene Ostia Roma Sud Roma Est Roma Nord WWTP Turku WWTP 1 Oslo TF Evry Valenton Colombes TF Aheres WWTP WWTP WWTP 3 WWTP Eysines Elbeuf Rouen Tancarville WWTP WWTP WWTP WWTP 1 WWTP 2 38

194 Country WWTP Name or Code ER-CALUX assay (Houtman et al. 2004) (Leusch et al. 2010) MELN assay ceeq # P-Percentage of total ceeq ceeq ## P-Percentage of total ceeq ng/l E1 E2 E3 EE2 ng/l E1 E2 E3 EE2 WWTP WWTP WWTP WWTP 6 WWTP China, Chongqing WWTP A (Ye et al. 2012) WWTP B WWTP C WWTP D WWTP E WWTP F WWTP G WWTP H WWTP I WWTP J Canada WWTP B TF (Fernandez et al. 2007) WWTP C WWTP D WWTP E W AVERAGE MEDIAN %ile max ceeq - calculated Estrogenic Equivalent; ceeq = [E1] EEF E1 + [E2] EEF E2 + [E3] EEF E3 + [EE2] EEF EE2 where [E1],[E2],[E3] and [EE2] are concentrations of estrogens displayed in Table 2 and EEF s are in vitro potencies determined for individual bioassays # - EEF E1 was 0.126; EEF E2 was 1; EEF E3 was 0.13; and EEF EE2 was 1.12 as determined by Houtman et al. (2004) ## - EEF E1 was 0.025; EEF E2 was 1; EEF E3 was 0.178; and EEF EE2 was as determined by Pillon et al. in Leusch et al. (2010) * - averages were calculated from minimal and maximal values reported in the study TF - trickling filter technology W - wetland lagoons without any other treatment steps (17d hydraulic retention time) 39

195 Table SD 7. Relative percentage contribution of four main steroid estrogens (E1, E2, E3 and EE2) to the total calculated concentrations of estrogenic equivalents (ceeq) in municipal WWTP effluents as determined for two individual bioassays using sets of EEFs reported in Cargouet et al. in Leusch et al. (2010) and Gutendorf and Westendorf (2001) Country Switzerland (Aerni et al. 2004)* France (Aerni et al. 2004)* Italy, Roma (Baronti et al. 2000), (Johnson et al. 2000) France (Muller et al. 2008) Finland (Bjorkblom et al. 2008) Greece (Pothitou & Voutsa 2008) Norway (Thomas et al. 2007) France (Cargouet et al. 2004) Austria (Clara et al. 2005) France (Labadie & Budzinski 2005a) France (Labadie & Budzinski 2005b) Slovenia (Avbersek et al. 2011) California (Drewes et al. 2005) WWTP Name or Code MELN assay (Leusch et al. 2010) (Gutendorf & Westendorf 2001) E-screen assay ceeq # P-Percentage of total ceeq ceeq ## P-Percentage of total ceeq ng/l E1 E2 E3 EE2 ng/l E1 E2 E3 EE2 Glatt Rontal Surental Fr Fr Cobis Fregene Ostia Roma Sud Roma Est Roma Nord WWTP Turku WWTP 1 Oslo TF Evry Valenton Colombes TF Aheres WWTP WWTP WWTP 3 WWTP Eysines Elbeuf Rouen Tancarville WWTP WWTP WWTP WWTP 1 WWTP 2 40

196 Country China, Chongqing (Ye et al. 2012) Canada (Fernandez et al. 2007) WWTP Name or Code MELN assay (Leusch et al. 2010) (Gutendorf & Westendorf 2001) E-screen assay ceeq # P-Percentage of total ceeq ceeq ## P-Percentage of total ceeq ng/l E1 E2 E3 EE2 ng/l E1 E2 E3 EE2 WWTP WWTP WWTP WWTP 6 WWTP WWTP A WWTP B WWTP C WWTP D WWTP E WWTP F WWTP G WWTP H WWTP I WWTP J WWTP B TF WWTP C WWTP D WWTP E W AVERAGE MEDIAN %ile max ceeq - calculated Estrogenic Equivalent; ceeq = [E1] EEF E1 + [E2] EEF E2 + [E3] EEF E3 + [EE2] EEF EE2 where [E1],[E2],[E3] and [EE2] are concentrations of estrogens displayed in Table 2 and EEF s are in vitro potencies determined for individual bioassays # - EEF E1 was 0.251; EEF E2 was 1; EEF E3 was 0.081; and EEF EE2 was as determined by Cargouet et al.in Leusch et al. (2010) ## - EEF E1 was 0.01; EEF E2 was 1; EEF E3 was 0.071; and EEF EE2 was as determined by Gutendorf and Westendorf (2001) * - averages were calculated from minimal and maximal values reported in the study TF - trickling filter technology W - wetland lagoons without any other treatment steps (17d hydraulic retention time) 41

197 Table SD 8. Relative percentage contribution of four main steroid estrogens (E1, E2, E3 and EE2) to the total calculated concentrations of estrogenic equivalents (ceeq) in municipal WWTP effluents determined for E-screen assay using 2 sets of EEFs reported in Drewes et al. (2005) and Fang et al. in Leusch (2010) Country Switzerland (Aerni et al. 2004)* France (Aerni et al. 2004)* Italy, Roma (Baronti et al. 2000), (Johnson et al. 2000) France (Muller et al. 2008) Finland (Bjorkblom et al. 2008) Greece (Pothitou & Voutsa 2008) Norway (Thomas et al. 2007) France (Cargouet et al. 2004) WWTP Name or Code E-screen assay (Drewes et al. 2005) (Leusch et al. 2010) E-screen assay ceeq # P-Percentage of total ceeq ceeq ## P-Percentage of total ceeq ng/l E1 E2 E3 EE2 ng/l E1 E2 E3 EE2 Glatt Rontal Surental Fr Fr Cobis Fregene Ostia Roma Sud Roma Est Roma Nord WWTP Turku WWTP 1 Oslo TF Evry Valenton Colombes TF Aheres Austria WWTP (Clara et al. 2005) WWTP WWTP 3 WWTP Eysines France (Labadie & Budzinski 2005a) France (Labadie & Budzinski 2005b) Elbeuf Rouen Tancarville Slovenia WWTP (Avbersek et al. 2011) WWTP WWTP California WWTP 1 (Drewes et al. 2005) WWTP 2 42

198 Country WWTP Name or Code E-screen assay (Drewes et al. 2005) (Leusch et al. 2010) E-screen assay ceeq # P-Percentage of total ceeq ceeq ## P-Percentage of total ceeq ng/l E1 E2 E3 EE2 ng/l E1 E2 E3 EE2 WWTP WWTP WWTP WWTP 6 WWTP China, Chongqing WWTP A (Ye et al. 2012) WWTP B WWTP C WWTP D WWTP E WWTP F WWTP G WWTP H WWTP I WWTP J Canada WWTP B TF (Fernandez et al. 2007) WWTP C WWTP D WWTP E W AVERAGE MEDIAN %ile max ceeq - calculated Estrogenic Equivalent; ceeq = [E1] EEF E1 + [E2] EEF E2 + [E3] EEF E3 + [EE2] EEF EE2 where [E1],[E2],[E3] and [EE2] are concentrations of estrogens displayed in Table 2 and EEF s are in vitro potencies determined for individual bioassays # - EEF E1 was 0.135; EEF E2 was 1; EEF E3 was 0.295; and EEF EE2 was as determined by Drewes et al. (2005) ## - EEF E1 was 0.044; EEF E2 was 1; EEF E3 was 0.251; and EEF EE2 was as determined by Fang et al. in Leusch (2010) * - averages were calculated from minimal and maximal values reported in the study TF - trickling filter technology W - wetland lagoons without any other treatment steps (17d hydraulic retention time) 43

199 Table SD 9. Relative percentage contribution of four main steroid estrogens (E1, E2, E3 and EE2) to the total calculated concentrations of estrogenic equivalents (ceeq) in municipal WWTP effluents determined for two individual bioassays using sets of EEFs reported in Leusch et al. (2010) and Gutendorf and Westendorf (2001) Country Switzerland (Aerni et al. 2004)* France (Aerni et al. 2004)* Italy, Roma (Baronti et al. 2000), (Johnson et al. 2000) France (Muller et al. 2008) Finland (Bjorkblom et al. 2008) Greece (Pothitou & Voutsa 2008) Norway (Thomas et al. 2007) France (Cargouet et al. 2004) Austria (Clara et al. 2005) France (Labadie & Budzinski 2005a) France (Labadie & Budzinski 2005b) WWTP Name or Code E-screen assay (Leusch et al. 2010) (Gutendorf & Westendorf 2001) MVLN assay ceeq # P-Percentage of total ceeq ceeq ## P-Percentage of total ceeq ng/l E1 E2 E3 EE2 ng/l E1 E2 E3 EE2 Glatt Rontal Surental Fr Fr Cobis Fregene Ostia Roma Sud Roma Est Roma Nord WWTP Turku WWTP 1 Oslo TF Evry Valenton Colombes TF Aheres WWTP WWTP WWTP 3 WWTP Eysines Elbeuf Rouen Tancarville Slovenia WWTP (Avbersek et al. 2011) WWTP WWTP California WWTP 1 (Drewes et al. 2005) WWTP 2 WWTP

200 Country WWTP Name or Code E-screen assay (Leusch et al. 2010) (Gutendorf & Westendorf 2001) MVLN assay ceeq # P-Percentage of total ceeq ceeq ## P-Percentage of total ceeq ng/l E1 E2 E3 EE2 ng/l E1 E2 E3 EE2 WWTP WWTP WWTP 6 WWTP China, Chongqing WWTP A (Ye et al. 2012) WWTP B WWTP C WWTP D WWTP E WWTP F WWTP G WWTP H WWTP I WWTP J Canada WWTP B TF (Fernandez et al. 2007) WWTP C WWTP D WWTP E W AVERAGE MEDIAN %ile max ceeq - calculated Estrogenic Equivalent; ceeq = [E1] EEF E1 + [E2] EEF E2 + [E3] EEF E3 + [EE2] EEF EE2 where [E1],[E2],[E3] and [EE2] are concentrations of estrogens displayed in Table 2 and EEF s are in vitro potencies determined for individual bioassays # - EEF E1 was 0.011; EEF E2 was 1; EEF E3 was 0.085; and EEF EE2 was as determined by Leusch et al.(2010) ## - EEF E1 was 0.01; EEF E2 was 1; EEF E3 was 0.083; and EEF EE2 was 1.25 as determined by Gutendorf and Westendorf (2001) * - averages were calculated from minimal and maximal values reported in the study TF - trickling filter technology W - wetland lagoons without any other treatment steps (17d hydraulic retention time) 45

201 Concentrations of in vitro estrogenic activity below which the PNECs of E1, E2, E3 and EE2 would not be exceeded Table SD 10. Concentrations of over-all estrogenic activity below which the in vivo derived PNECs for individual steroid estrogens would not be exceeded at any investigated municipal WWTP. longer-term exposures (ng/l EEQ) shorter-term exposures (ng/l EEQ) Assay EL E1 EL E2 EL E3 EL EE2 EL E1 EL E2 EL E3 EL EE2 (Aerni et al. 2004),( YES Rutishauser et al. 2004) YES (Svenson et al. 2003) YES (Caldwell et al. 2012) YES (Leusch et al. 2010) ER-CALUX (Sonneveld et al. 2006) ER-CALUX (Avbersek et al. 2011) ER-CALUX (Houtman et al. 2004) MELN (Leusch et al. 2010) MELN (Leusch et al. 2010) (Gutendorf & Westendorf E-screen 2001) E-screen (Drewes et al. 2005) E-screen (Leusch et al. 2010) E-screen (Leusch et al. 2010) MVLN* MVLN (Gutendorf & Westendorf 2001) EL - proposed safe levels of in vitro determined estrogenic activity (Routledge & Sumpter 1996) YES - yeast estrogenicity screening assay (Van der Burg et al. 2010) ER-CALUX - Estrogen Receptor mediated Chemical Activated LUciferase gene expression assay (Balaguer et al. 2000) MELN - MCF-7 cells stably transfected with the estrogen responsive gene ERE-betaGlob-Luc-SVNeo (Soto et al. 1998) E-SCREEN - the MCF7 cell proliferation assay (Demirpence et al. 1993) MVLN - MCF-7 cells stably transfected with luciferase gene under the control of estrogen receptor *Unpublished data - in vitro potencies were determined by the authors of the present study by comparing the EC50 values from dose-response curves of E2 and other estrogens 46

202 References Aerni, H.R., B. Kobler, B.V. Rutishauser, F.E. Wettstein, R. Fischer, W. Giger, A. Hungerbuhler, M.D. Marazuela, A. Peter, R. Schonenberger, A.C. Vogeli, M.J.F. Suter & R.I.L. Eggen Combined biological and chemical assessment of estrogenic activities in wastewater treatment plant effluents. Analytical and Bioanalytical Chemistry 378: Avbersek, M., B. Zegura, M. Filipic & E. Heath Integration of GC-MSD and ER- Calux (R) assay into a single protocol for determining steroid estrogens in environmental samples. Science of the Total Environment 409: Balaguer, P., H. Fenet, V. Georget, F. Comunale, B. Terouanne, R. Gilbin, E. Gomez, A.M. Boussioux, C. Sultan, M. Pons, J.C. Nicolas & C. Casellas Reporter cell lines to monitor steroid and antisteroid potential of environmental samples. Ecotoxicology 9: Baronti, C., R. Curini, G. D'Ascenzo, A. Di Corcia, A. Gentili & R. Samperi Monitoring natural and synthetic estrogens at activated sludge sewage treatment plants and in a receiving river water. Environmental Science & Technology 34: Bjorkblom, C., L. Salste, I. Katsiadaki, T. Wiklund & L. Kronberg Detection of estrogenic activity in municipal wastewater effluent using primary cell cultures from three-spined stickleback and chemical analysis. Chemosphere 73: Caldwell, D.J., F. Mastrocco, P.D. Anderson, R. Lange & J.P. Sumpter Predicted-noeffect concentrations for the steroid estrogens estrone, 17 beta-estradiol, estriol, and 17 alpha-ethinylestradiol. Environmental Toxicology and Chemistry 31: Cargouet, M., D. Perdiz, A. Mouatassim-Souali, S. Tamisier-Karolak & Y. Levi Assessment of river contamination by estrogenic compounds in Paris area (France). Science of the Total Environment 324: Clara, M., N. Kreuzinger, B. Strenn, O. Gans & H. Kroiss The solids retention time - a suitable design parameter to evaluate the capacity of wastewater treatment plants to remove micropollutants. Water Research 39: Demirpence, E., M.J. Duchesne, E. Badia, D. Gagne & M. Pons Mvln Cells - a Bioluminescent Mcf-7-Derived Cell-Line to Study the Modulation of Estrogenic Activity. Journal of Steroid Biochemistry and Molecular Biology 46: Drewes, J.E., J. Hemming, S.J. Ladenburger, J. Schauer & W. Sonzogni An assessment of endocrine disrupting activity changes during wastewater treatment through the use of bioassays and chemical measurements. Water Environment Research 77: Fernandez, M.P., M.G. Ikonomou & I. Buchanan An assessment of estrogenic organic contaminants in Canadian wastewaters. Science of the Total Environment 373: Gutendorf, B. & J. Westendorf Comparison of an array of in vitro assays for the assessment of the estrogenic potential of natural and synthetic estrogens, phytoestrogens and xenoestrogens. Toxicology 166: Houtman, C.J., A.M. Van Oostveen, A. Brouwer, M.H. Lamoree & J. Legler Identification of estrogenic compounds in fish bile using bioassay-directed fractionation. Environmental Science & Technology 38: Johnson, A.C., A. Belfroid & A. Di Corcia Estimating steroid oestrogen inputs into activated sludge treatment works and observations on their removal from the effluent. Science of the Total Environment 256:

203 Labadie, P. & H. Budzinski. 2005a. Determination of steroidal hormone profiles along the Jalle d'eysines River (near Bordeaux, France). Environmental Science & Technology 39: Labadie, P. & H. Budzinski. 2005b. Development of an analytical procedure for determination of selected estrogens and progestagens in water samples. Analytical and Bioanalytical Chemistry 381: Leusch, F.D.L., C. De Jager, Y. Levi, R. Lim, L. Puijker, F. Sacher, L.A. Tremblay, V.S. Wilson & H.F. Chapman Comparison of Five in Vitro Bioassays to Measure Estrogenic Activity in Environmental Waters. Environmental Science & Technology 44: Muller, M., F. Rabenoelina, P. Balaguer, D. Patureau, K. Lemenach, H. Budzinski, D. Barcelo, M.L. De Alda, M. Kuster, J.P. Delgenes & G. Hernandez-Raquet Chemical and biological analysis of endocrine-disrupting hormones and estrogenic activity in an advanced sewage treatment plant. Environmental Toxicology and Chemistry 27: Pothitou, P. & D. Voutsa Endocrine disrupting compounds in municipal and industrial wastewater treatment plants in Northern Greece. Chemosphere 73: Routledge, E.J. & J.P. Sumpter Estrogenic activity of surfactants and some of their degradation products assessed using a recombinant yeast screen. Environmental Toxicology and Chemistry 15: Rutishauser, B.V., M. Pesonen, B.I. Escher, G.E. Ackermann, H.R. Aerni, M.J.F. Suter & R.I.L. Eggen Comparative analysis of estrogenic activity in sewage treatment plant effluents involving three in vitro assays and chemical analysis of steroids. Environmental Toxicology and Chemistry 23: Sonneveld, E., J.A.C. Riteco, H.J. Jansen, B. Pieterse, A. Brouwer, W.G. Schoonen & B. van der Burg Comparison of in vitro and in vivo screening models for androgenic and estrogenic activities. Toxicological Sciences 89: Soto, A.M., T.M. Lin, H. Justicia, R.M. Silvia & C. Sonnenschein An "in culture" bioassay to assess the estrogenicity of xenobiotics (E-SCREEN). Journal of Clean Technology Environmental Toxicology and Occupational Medicine 7: Svenson, A., A.S. Allard & M. Ek Removal of estrogenicity in Swedish municipal sewage treatment plants. Water Research 37: Thomas, K.V., C. Dye, M. Schlabach & K.H. Langford Source to sink tracking of selected human pharmaceuticals from two Oslo city hospitals and a wastewater treatment works. Journal of Environmental Monitoring 9: Van der Burg, B., R. Winter, M. Weimer, P. Berckmans, G. Suzuki, L. Gijsbers, A. Jonas, S. van der Linden, H. Witters, J. Aarts, J. Legler, A. Kopp-Schneider & S. Bremer. Optimization and prevalidation of the in vitro ER alpha CALUX method to test estrogenic and antiestrogenic activity of compounds. Reproductive Toxicology 30: Ye, X., X.S. Guo, X. Cui, X. Zhang, H. Zhang, M.K. Wang, L. Qiu & S.H. Chen Occurrence and removal of endocrine-disrupting chemicals in wastewater treatment plants in the Three Gorges Reservoir area, Chongqing, China. Journal of Environmental Monitoring 14:

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205 Článek VI Příloha VI

206 BENCHMARKING ORGANIC MICROPOLLUTANTS IN WASTEWATER, RECYCLED WATER AND DRINKING WATER WITH IN VITRO BIOASSAYS Beate I. Escher, 1 * Mayumi Allinson, 2,3 Rolf Altenburger, 4 Peter A. Bain, 5 Patrick Balaguer, 6 Wibke Busch, 4 Jordan Crago, 7 Andrew Humpage, 8 Nancy D. Denslow, 9 Elke Dopp, 10 Klara Hilscherova, 11 Anu Kumar, 5 Marina Grimaldi, 6 B. Sumith Jayasinghe, 9 Barbora Jarosova, 11 Ai Jia, 12 Sergei Makarov, 13 Keith A. Maruya, 14 Alex Medvedev, 13 Alvine C. Mehinto, 14 Jamie E. Mendez, 15 Anita Poulsen, 1 Erik Prochazka, 16 Jessica Richard, 10 Andrea Schifferli, 17 Daniel Schlenk, 7 Stefan Scholz, 4 Fujio Shiraishi, 3 Shane Snyder, 12 Guanyong Su, 18 Janet Y.M. Tang, 1 Bart van der Burg, 19 Sander C. van der Linden, 19 Inge Werner, 17 Sandy D. Westerheide, 15 Chris K.C. Wong, 20 Min Yang, 21 Bonnie H.Y. Yeung, 20 Xiaowei Zhang, 18 and Frederic D.L. Leusch 16 1 The University of Queensland, National Research Centre for Environmental Toxicology (Entox), 39 Kessels Rd, Brisbane, QLD 4108, Australia; 2 Centre for Aquatic Pollution Identification and Management (CAPIM), School of Chemistry, The University of Melbourne, Grattan Street, Parkville, VIC 3010 Australia; 3 National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba Japan 4 ; UFZ - Helmholtz Centre for Environmental Research, Permoserstr. 15, Leipzig, Germany; 5 CSIRO Land and Water, Private Bag No. 2, Glen Osmond, SA 5064, Australia; 6 Cancer Research Institute Montpellier, CRLC Val, d Aurelle, Parc Euromédecine, Montpellier, Cedex 5, France; 7 Aquatic Ecotoxicology, Department of Environmental Sciences, University of California, Riverside, Riverside, CA 92521, USA; 8 Australian Water Quality Centre, 250 Victoria Square, Adelaide SA 5001; 9 University of Florida, Department of Physiological Sciences, PO Box , Gainesville, FL 32611, USA; 10 IWW Water Centre, Department of Toxicology, Moritzstrasse 26, Mülheim/Ruhr, Germany; 11 Research Centre for Toxic Compounds in the Environment (RECETOX), Masaryk University, Kamenice 753/5, 62500, Brno, Czech Republic; 12 University of Arizona, 1133 E. James E. Rogers Way, Harshbarger 108, Tucson, AZ ; 13 ATTAGENE, PO Box 12054, Research Triangle Park, NC 27709, USA; 14 Southern California Coastal Water Research Project Authority (SCCWRP), 3535 Harbor Blvd., Suite 110, Costa Mesa, CA , USA; 15 Department of Cell Biology, Microbiology and Molecular Biology, University of South Florida, 4202 E Fowler Ave, ISA 2015, Tampa, FL 33620, USA; 16 Smart Water Research Centre, Griffith University, Edmund Rice Dr, Griffith University Gold Coast Campus, Southport, QLD 4222, Australia; 17 Swiss Centre for Applied Ecotoxicology, Eawag-EPFL, Überlandstr. 133, 8600 Dübendorf, Switzerland; 18 State Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing , PR China; 19 BioDetection Systems, Science Park 406, 1098 XH, Amsterdam, The Netherlands; 20 Department of Biology, Croucher Institute for Environmental Sciences, Level 10, Science Tower, Ho Sin Hang Campus, Hong Kong Baptist University, 224 Waterloo Rd. Kowloon Tong, Kowloon, Hong Kong; 21 State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, PO Box 2871, Beijing , PR China.

207 Bioanalytical assessment of water quality Supporting Information KEYWORDS Adaptive stress response; adverse outcome pathway; bioanalytical tools, cytotoxicity; endocrine disruption; high-throughput screening; organic micropollutants; water quality; xenobiotic metabolism ABSTRACT Thousands of organic micropollutants and their transformation products occur in water. Although often present at low concentrations, individual compounds contribute to mixture effects. Cell-based bioassays that target health-relevant biological endpoints may therefore complement chemical analysis for water quality assessment. The objective of this study was to evaluate cell-based bioassays for their suitability to benchmark water quality and to assess efficacy of water treatment processes. The selected bioassays cover relevant steps in the toxicity pathway including induction of xenobiotic metabolism, specific and reactive modes of toxic action, activation of adaptive stress response pathways and system responses. Twenty laboratories applied 103 unique in vitro bioassays to a common set of ten water samples collected in Australia, including wastewater treatment plant effluent, two types of recycled water (reverse osmosis and ozonation/activated carbon filtration), stormwater, surface water and drinking water. Sixty-five bioassays (63%) showed positive results in at least one sample, typically in wastewater treatment plant effluent, and only five (5%) were positive in the control (ultrapure water). Each water type had a characteristic bioanalytical profile with particular groups of toxicity pathways either consistently responsive or not responsive across test systems. The most responsive health-relevant endpoints were related to xenobiotic metabolism (pregnane X and aryl hydrocarbon receptors), hormone-mediated modes of action (mainly related to the estrogen, glucocorticoid and anti-androgen activities), reactive modes of action (genotoxicity) and adaptive stress response pathway (oxidative stress response). This study has demonstrated that selected cell-based bioassays are suitable to benchmark water quality and it is recommended to use a purpose-tailored panel of bioassays for routine monitoring INTRODUCTION The Tox21, a joint program of the National Institutes of Health, US Environmental Protection Agency (EPA), and US Food and Drug Administration 1, 2 and the US EPA ToxCast Program 3, 4 aim to advance molecular toxicology, systems biology and computational toxicology to overcome shortcomings of traditional in vivo toxicity testing of chemicals. Parallel initiatives exist in Europe, e.g., the EU project ChemScreen 5. Jointly these programs bring a paradigm shift in toxicity testing as in vitro methods help Appendix VI p.2

208 Bioanalytical assessment of water quality Supporting Information elucidate mechanisms of toxicity, prioritize chemicals for further testing and develop predictive models in order to refine, reduce or replace future in vivo testing. These programs rely heavily on high-throughput screening (HTS) using cell-based and cell-free in vitro bioassays of large numbers of chemicals to elucidate their toxicity pathways. While Tox21 focuses on the bioanalytical profiling of individual chemicals, these tools should also be applicable to environmental samples of unknown and complex composition, and this study brings together for the first time selected bioassays from Tox21 with established bioassays for water quality assessment. 6 Cell-based bioassays have been developed to target all steps of the toxicity pathway (Figure 1). 7 While the induction of xenobiotic metabolism may not lead to cytotoxicity, it is an indicator of the presence of pollutants. Some bioassays provide measures of mechanisms of toxicity by visualizing the interaction of stressors, e.g., chemicals, with specific biological targets, e.g., binding to endocrine receptors or reaction with DNA. The exposed cells may respond through induction of adaptive stress response pathways, a feature that can be used for the assessment of environmental pollutants, although it is not an adverse effect per se. Cell viability, growth and/or proliferation are indicators of adverse effects on a cellular level. If the cell represents a specialized tissue, this may give an indication of tissue-specific impairment. Cellular responses will not always imply higher-level effects but are a prerequisite for whole organism and population responses. 8 The direct detection of initiating key events in a bioassay only provides a measure of a potential adverse effect because repair and defense mechanisms may ultimately prevent toxicity. From a precautionary perspective, however, the potential to cause an adverse effect is a crucial assessment endpoint. Cellbased bioassays are not suitable to replace regulatory in vivo tests but provide hazard information for screening and prioritization of chemicals Appendix VI p.3

209 Bioanalytical assessment of water quality Supporting Information Cellular toxicity pathway: Metabolism (toxification/ detoxification) Initiating event: interaction with target Defense mechanisms Cell death/ damage Associated in vitro bioassays: Induction of xenobiotic metabolism pathways Specific modes of action (receptor-mediated effects) endocrine receptors photosynthesis enzyme inhibition. Reactive modes of action DNA damage, protein depletion and lipid peroxidation Induction of adaptive stress response pathways Cell viability 102 System response Neurotoxicity Immunotoxicity Endocrine, reproductive and developmental effects Carcinogenicity Figure 1. Classification of in vitro bioassays according to cellular toxicity pathways. A large variety of cell-based bioassays have been applied for water quality assessment in the past 6 but many of the endpoints evaluated under HTS toxicology programs 10 are yet to be included. Many studies rely on a small set of bioassays and each study uses different types of water samples, sample preparation methods, bioassays, and data evaluation methods. Only a few cell-based bioassays have standardized protocols, such as the OECD or ISO guidelines. The goals of this study were to evaluate as many bioassays as practically achievable using one set of water samples with one sample preparation method and to recommend a screening test battery for water quality testing. We selected cell-based bioassays using three criteria. First, we selected bioassays that have previously been used for water quality assessment. Second, a comprehensive literature review allowed us to identify cell-based bioassays that responded to environmentally relevant organic micropollutants but had not been used for water quality assessment prior to this study. Third, for final selection of endpoints, we screened 25 nuclear receptors (NR) and 48 transcription factor (TF) response elements in HepG2 human liver carcinoma cell lines 11 to assure inclusion of endpoints relevant for the particular samples tested. We evaluated ten samples, including nine ambient water samples ranging from effluent, recycled water to drinking water, plus one procedural blank. The samples were extracted Appendix VI p.4

210 Bioanalytical assessment of water quality Supporting Information and concentrated with an optimized solid phase extraction (SPE) method and sent to a total of 20 worldwide laboratories applying 103 bioassays for bioanalytical testing. All experimental data were evaluated using a common method specifically developed for this study to harmonize the different approaches to data evaluation. The results were used not only to validate and compare the different bioassays for application with water samples but also to benchmark water quality. The data may also serve to compare the efficacy of different water treatment processes for removal of organic micropollutants. It was not the goal of this study to directly compare bioassay protocols and performance of bioassays but rather to obtain an overview of the biological endpoints responsive to typical water contaminants. One goal was to cover the major healthrelevant toxicity pathways introduced in Figure 1 and to evaluate which pathways were relevant for water quality testing. The study was further expected to identify the most robust and responsive bioassays, thus, not only mammalian but also bacterial assays were included. The outcome includes recommendations on the make-up of a screening test battery and on indicator bioassays that appear to be particularly relevant for further investigation in water quality monitoring programs Materials and Methods Samples. Ten grab samples of water were collected in December 2011 and January 2012 (Supporting Information, Section S1 and Table S1). Sample Eff1 is a secondary treated sewage effluent (activated sludge treatment) that serves as influent to a Water Reclamation Plant (WRP) that produces high quality recycled water for indirect potable reuse. Three samples were taken at different stages of treatment: after microfiltration (MF), reverse osmosis (RO) and advanced oxidation (AO) using H 2 O 2 /UV. Bioanalytical 12, 13 assessments had been previously undertaken at this WRP. The second investigated WRP treats secondary sewage effluent (Eff2) by ozonation followed by biologically activated carbon filtration (O 3 /BAC) to produce recycled water for irrigation and industrial usage. The fate of micropollutants in this plant has been previously characterized in more detail River water (RW) and drinking water (DW) samples were collected at the inlet and outlet of a metropolitan drinking water treatment plant applying chlorination and 12, 17 chloramination, which was also previously assessed with bioanalytical tools. The stormwater sample (SW) was collected from a stormwater drain in Brisbane, Australia, that receives runoff from a residential catchment. 18 The laboratory blank consisted of ultrapure water (milliq water) run through the same SPE process as the Appendix VI p.5

211 Bioanalytical assessment of water quality Supporting Information samples. Fourteen liters were collected for each of Eff1, MF, Eff2 and SW, while 28 L were collected for the remaining samples. Sample preparation and distribution to the participating laboratories. The SPE was performed according to Macova et al. 12 using the sorbent materials Oasis HLB (Waters) followed by Supelclean coconut charcoal (Sigma-Aldrich), a combination that was confirmed previously to extract a broad range of organic micropollutants. 19 Details and information on sample preparation and the logistics of sample distribution are summarized in the SI, Section S1. All distributed samples were labeled with codes for blind sample processing. Sample characterization. 293 organic micropollutants were previously characterized in these samples. 20 Dissolved organic carbon concentrations are reported in the SI, Table S1. Bioassays. The majority of selected bioassays was based on mammalian, bacterial or yeast cells. A zebrafish embryo test was included because testing with embryonic fish stages is considered an alternative testing method to conventional in vivo tests. 21 Only one bioassay employed a naked enzyme (acetylcholinesterase inhibition assay). All applied bioassays and their associated experimental methods are listed in Table 1 and categorized according to the toxicity pathways outlined in Figure 1. For bioassays where the protocol was modified or applied for the first time, Section S2 in the SI and Table S2 give additional information on the experimental procedures. Concentration-effect assessment. A critical aspect when working with diverse biological endpoints is a consistent data evaluation process. It was the goal of the present study to harmonize the data evaluation as much as possible, which is challenging given the different types of endpoints measured but a prerequisite for quantitative comparison between different bioassays. The concentrations of samples were expressed in units of relative enrichment factor REF. The REF is the product of the enrichment factor of the SPE process and the dilution of the extract in the bioassay (for derivation of equations, see SI, Section SI-3). A REF > 1 means that the sample is enriched in the bioassay (e.g., a REF of 10 means the sample was concentrated 10-fold in the bioassay), a REF < 1 means it was diluted in the bioassay, and a REF of 1 is equivalent to the organic micropollutants in the ambient (undiluted and un-concentrated) sample stripped from inorganics, metals and most colloidal organic matter by SPE. For each bioassay, the measured responses were plotted against the sample concentration expressed as REF (Figure 2). For assays with a known maximum response, responses were converted to percent of maximum effect. For all endpoints that relate to cell viability and cell population growth, the controls can be expressed as 0% effect, while 100% relates to no growth or all cells dead. For reporter gene assays that measure the binding to a receptor or the transactivation of a receptor, 0% refers to the Appendix VI p.6

212 Bioanalytical assessment of water quality Supporting Information basal activity of the receptor, while 100% is defined using an appropriate reference compound that can saturate the receptor without causing cytotoxicity Figure 2. Overview of the concentration-effect models applied to derive benchmark effect concentrations (EC) The ideal case would be a full concentration-effect curve covering 0% to 100% of effect (Figure 2A), which typically has a sigmoidal shape that can be described with a log-logistic equation. Any log-logistic concentration-effect curve will be linear with respect to (non-logarithmic) concentrations at low effect level (up to 20-30% effect). As the water samples investigated in the present study often showed only very low effect levels, the linear form of the concentration-effect curves was used for derivation of the effect concentration causing 10% of maximum effect (EC 10 ) of the samples (Figure 2C). A detailed derivation of EC 10 is provided in the SI, Section S3-A. For assays where the maximum response was unknown or unachievable, the responses were normalized to medium or solvent controls and assessed via the induction ratio (IR; i.e., fold induction relative to control). The maximum response was unknown if no appropriate reference compound existed, or if cytotoxicity quenched the reading of the Appendix VI p.7

213 Bioanalytical assessment of water quality Supporting Information reporter activity. The problem also arose if the endpoint is inducible or, by nature, there is no clear upper limit, e.g., for DNA damage or adaptive stress response. In practice, linear regression through the control effect level (IR = 1) was used for derivation of the effect concentration that causes an IR of 1.5, or EC IR1.5 (Figure 2D). A detailed derivation of EC IR1.5 is provided in the SI, Section S3-B together with a discussion of the comparability of EC 10 versus EC IR1.5 (Table S3). A bioassay can be run in antagonistic mode if the receptors are occupied with a constant concentration of a known and potent agonist. Varying concentrations of sample are added and if the signal of the control is suppressed the sample can be considered to exhibit an antagonistic effect. The effect concentration causing a suppression ratio SR of 0.2, EC SR0.2, was used to describe all antagonistic effects and correspondingly an EC CD0.2 was defined for endpoints that are based on chaperone dissociation (e.g., I B dissociation from NF B). A detailed derivation is provided in the SI, Section S3-C and Figure S1. Data presentation. A heatmap presenting all measured EC values was generated using the R Software package gplots ( Hierarchical clustering was performed using the complete linkage method to find similar clusters of water samples RESULTS Repeatability of bioassays. A number of bioassays were performed simultaneously in multiple laboratories. As discussed in detail in the SI, Section S4 and Table S4, the results were consistent between laboratories and therefore the results of the same bioassays were averaged. Initial screening of nuclear receptors and transcription factors. The FACTORIAL bioassays 11 were used for an initial profiling of the water samples after enrichment by SPE to a REF of 4. As discussed in the SI, Section S5 and Figure S2, an IR of 1.5 is regarded as the threshold for positive effects. In the SI, Figure S3, the activity profiles of all samples are depicted. The blank did not induce any of the tested endpoints indicating that the sample extraction and enrichment process did not negatively influence the test outcome. The Eff1 and Eff2 samples caused an activation of five of 25 nuclear receptors (NR) and five of 48 transcription factors (TF) tested (Figure S3A and C). The active NRs were the pregnane X receptor (PXR), the peroxisome proliferator-activated receptor (PPAR ), the estrogen receptor (ER ) and marginally the the glucocorticoid receptor (GR) and the liver X receptor (LXR). The active TFs were related to the aryl hydrocarbon receptor (AhR), Appendix VI p.8

214 Bioanalytical assessment of water quality Supporting Information PXR, the oxidative stress response (nrf2/are), the estrogen response element (ERE), and the RAR-related orphan receptor (RORE). The screening provides strong support to expand the test battery to include additional endpoints to those routinely employed. 6 Particularly the PXR and AhR, which are related to xenobiotic metabolism, warrant more attention as these had the highest activity in the pre-screening assay. The LXR is relevant as its activation induces the PPAR. 22 The PPAR pathway is related to obesity 23 and has gained much attention in recent years and therefore various PPAR-related endpoints have been included in the test battery if not specifically LXR. The oxidative stress response pathway appeared to be of high relevance and has rarely been investigated with water samples prior to this study. In response to the findings of this screening, the active three NRs and five TFs and two others associated to relevant pathways (CAR, PPAR, AR, GR, THR 1, ROR, HSE, HIF1a, NF B, p53) were included in the detailed dose-response analysis. Responsiveness of the bioassays. Figure 3 and Table S5 in the SI give an overview of all results of 101 different bioassays tested plus the two bacterial cytotoxicity assays. A positive response is defined here as EC IR1.5 or EC 10 lower than the highest tested REF, thus no extrapolations were performed. In some cases the REF could have been increased but was not in practice due to the limited volume of sample or limitations with respect to allowed solvent content in the bioassay. The first two questions that we have to answer to judge the suitability of bioassays for water quality assessment are (A) do polluted samples induce a response? and (B) is the response acceptably low in control samples? (A) Sixty-five bioassays showed a response in at least one of the water samples. For Eff2, which can be considered as a moderately polluted sample, the number of positive results was 60. (B) No solvent blank caused any effect and the procedural blank with ultrapure water only produced effect in five bioassays (4.9%). Procedural blank. Even small impurities leaching out of the material or present in the solvent would likely contribute to the nonspecific effect of the blank. Here we applied two different SPE sorbent materials (HLB and coconut charcoal), which were eluted separately and required twice the amount of solvent. This consideration rationalizes the low but positive results of the blanks in the two bioluminescence inhibition assays with marine luminescent bacteria, which were higher than previously seen when only one type of solid-phase material were applied. 12 Furthermore, the yeast-based assays AhR-yeast and CAR-yeast showed responses in the blanks but only at much higher REF than the samples. A positive blank value was Appendix VI p.9

215 Bioanalytical assessment of water quality Supporting Information observed in one of the various Ames assays and is most likely due to measurement uncertainty as this value was derived from only one data point. Bacterial cytotoxicity screening assays. The bacterial cytotoxicity assays with Vibrio fischeri and Photobacterium phosphoreum were used as quick bioanalytical assessment tools, as these tests are rapid with only 15 to 30 min of exposure. Bioluminescence tests are nonspecific assays, as all stressors can impair the energy production and thus decrease bioluminescence. They provide a high responsiveness, i.e., often the indicate effects for the diluted sample at REFs of less than 1. However, the high sensitivity if compared to other cellular assays may result from a higher bioavailability, i.e., absence of serum proteins typically used in in vitro assay. This increased bioavailability could results in a detection of trace amounts of coextracted dissolved organic carbon (DOC). In particular the low-molecular fraction of assimilable organic carbon can add to the observed effects as previously demonstrated. 24 However, the high sensitivity may also result from specific interactions with bacterial physiology. Therefore, and because control sample exhibited some effects as well, the luminescence assays have been excluded from the heatmap (see below). Heatmap. The summary of 101 EC values (excluding the two bacterial cytotoxicity assays) in each of the 10 samples is presented in form of a heatmap (Figure 3, data summarized in SI, Table S5). The similarity of bioanalytical fingerprints between different water samples was characterized by hierarchical clustering. Evidently, quantitative comparison is difficult because EC were expressed as EC 10 or EC IR1.5 and these two values are only directly comparable if the maximum IR is around 6 (see discussion in SI, Section S3-B). Therefore hierarchical clustering was only performed on samples and not on bioassays. Appendix VI p.10

216 Bioanalytical assessment of water quality Supporting Information EC<0.3 (REF) 0.3<EC<1 1<EC<3 3<EC<10 10<EC<30 30<EC Eff2 Eff1 MF SW DW RW O 3 /BAC RO Blank AO Androgen Glucocorticoid 50 Progesterone Cytotoxicity 100 Induction of xenobiotic metabolism Specific MOA: Photosynthesis Enzyme inhibition Endocrine receptors: Estrogen Thyroid Reproduction and development Reactive MOA: Genotoxicity Induction of adaptive stress response Figure 3. Summary of results in 101 bioassays (excluding inactive FACTORIAL and the bacterial cytotoxicity assays). Plotted are the effect concentrations (EC 10, EC IR1.5, or EC SR0.2 ) in units of REF (relative enrichment factors). The colors encode for the magnitude of the EC. Green stands for high effect concentrations (low potency) and transitions to red for low effect concentrations (high potency). Dark green are EC values that were >30 REF (which means that the sample that is enriched 30 times still does not show an effect), green from 10 to 30 REF, light green from 3 to 10 REF. A sample that has its EC at concentrations of the native sample up to three times enriched is denoted in yellow. Samples that have to be diluted for the EC are orange for up to 3 times diluted (REF 1 to 0.3) and red for over 3 times diluted. Numbers on the right refer to bioassay numbers in Table 1. Bioassay # The closest similarity existed between the blank and the highly treated AO sample, while the RO sample clustered with this group on the next level of hierarchy. Surface Appendix VI p.11

217 Bioanalytical assessment of water quality Supporting Information water and ozonated recycled water clustered together. Both of these groups (cluster RW + O 3 /BAC and cluster RO + Blank + AO) clustered closely on the next level of similarity. Of the more polluted samples, Eff1 and MF were highly similar. This is not unexpected, as microfiltration, the only treatment step separating the two samples, is ineffective at removing micropollutants. Slightly higher effects were, however, observed in the MF sample likely due to disinfection by chloramination of the membrane to avoid biofouling. 12 On the next level of hierarchical clustering, the two WWTP effluents Eff1 + MF and Eff2 showed high similarity. The largest separation was observed between the cluster of Eff1 + Eff2 + MF and all other samples, clearly demonstrating that cell-based bioassays can distinguish between wastewater and reclaimed water samples. The bioanalytical fingerprints can also help distinguish between different water types: WWTP effluents not only showed the highest effects but also distinct responses related to known environmental pollutants, including pesticides, industrial chemicals, pharmaceuticals and personal care products, e.g., the activation of the aryl hydrocarbon receptor by PAHs or methylmercaptoaniline, 25 the activation of the estrogen receptor by natural hormones and xenoestrogens, the activation of the glucocorticoid receptor by dexamethasone and organotin compounds, 26 or photosynthesis inhibition by herbicides. The specific effects, caused by chemicals that bind to receptors, were decreased substantially in the WRPs. Stormwater had a slightly different pattern to WWTP effluents but was also dominated by pesticides, as represented for example by herbicidal activity that was absent in other samples of its cluster. In other studies on stormwater one could even identify sewer crosscontamination by bioanalytical profiling. 18 In contrast, disinfection by chlorination lead to disinfection by-products, which showed distinct bioassay response patterns with clearly increased genotoxicity and oxidative stress response in DW as compared to its source water (RW), while specific-receptor mediated effects were low in RW and almost fully disappeared in DW. This is consistent with previous bioanalytical profiling of the drinking water treatment process. 17 DISCUSSION Multiplexed assays as a screening tool. The FACTORIAL assay was applied here for the first time to water samples and yielded interesting fingerprints of effects that were consistent with the results of the other bioassays. However, more work is required to implement reference chemicals and include a more rigorous dose-response assessment. The effect fingerprints were qualitatively consistent with responses seen in the initial Appendix VI p.12

218 Bioanalytical assessment of water quality Supporting Information ToxCast I screening of 320 pesticides, where 73% of the pesticides were responsive in PXR, 52% in Nrf2/ARE and 46% in PPAR. 11 Benchmarking water quality. A detailed discussion of the responses of each bioassay is provided in the SI, Section S6. Here follows a summary of the responsive and nonresponsive endpoints in relation to the associated step in the toxicity pathway (see also Table 2). Responsiveness is determined on one hand by the presence of triggering organic micropollutants in the water extracts: in absence of chemicals that trigger a certain toxicity pathway, even the most sensitive bioassay will not respond to a given water sample. On the other hand, the responsiveness is directly related to the sensitivity of a given bioassay. Absolute sensitivity can only be assessed by comparing the effect concentrations and limits of detection of reference chemicals but the results obtained in the present study can give some indication on the suitability of bioassays for monitoring purposes. Induction of xenobiotic metabolism pathways. Induction of metabolic pathways is not per se an indicator of toxicity but gives an indication of exposure to bioactive chemicals. Metabolism can detoxify or bioactivate chemicals. Omiecinski et al. 27 stressed the relevance and the toxicological implications of a number of xenobiotic metabolism pathways and associated NR, including the PXR, PPAR, and, AhR and CAR. Three and six bioassays were evaluated for the PXR and AhR, respectively, and all showed positive responses in less treated samples and negative responses in recycled water and the blank (Table 2, SI, Section S6-A, Figure S5). CAR plays a role in both Phase I and II metabolism and plays a protective role against toxicity induced by bile acids as well as regulation of physiological functions. The target chemicals for CAR are less clearly defined than for AhR and while a few pesticides (e.g., methoxychlor, carbaryl propazine, 6-deisopropylatrazine) induced the CAR in the CARtrans-FACTORIAL assay in previous work, 11 no response was detected in the water samples in the CAR-trans-FACTORIAL assay up to an REF of 4. In contrast, the CARyeast showed a response in all sample (EC IR1.5 from 0.1 to 9.4). For PPAR, only two of seven bioassays (PPAR -transfactorial and HELN- PPAR ) gave signals in the four most polluted samples. PPAR is strongly linked to the regulation of glucose and lipid metabolism as well as inflammation, and is less important for xenobiotic metabolism. 28 In a high throughput study of 3000 environmentally relevant chemicals, roughly 1% of the tested chemicals were PPAR agonists and 8% were PPAR antagonists. 29 Organotins 30 and polyhalogenated bisphenol A 31 were found to induce PPAR and. The higher activity of PPAR over PPAR for water samples is consistent with the finding that 146 of 309 ToxCast Phase I chemicals were active in PPAR - transfactorial, while the other isoforms were less responsive. 11 Appendix VI p.13

219 Bioanalytical assessment of water quality Supporting Information Specific modes of toxic action. Most specific modes of action involve binding to receptors or inhibition of enzymes. In the past, direct enzyme inhibition assays have been popular tools for water quality testing. Recent work on the influence of dissolved organic matter (DOM) on the acetylcholinesterase assay has demonstrated that DOM nonspecifically impacts the assay at relatively low concentrations. 32 The implication of these findings is that for most tests with naked enzymes, water samples cannot be concentrated above a REF of 2. In the present study, only the two wastewater samples produced a valid response in this assay. Despite the high relevance of this biological endpoint for many insecticides, it thus proves unsuitable to investigate recycled water samples. Photosynthesis inhibition: An important group of environmental contaminants are herbicides that inhibit photosynthesis. While they are specifically designed to target photosynthesis inhibition, herbicides can nevertheless be toxic to humans and are regulated in recycled and drinking water guidelines. The most sensitive assays to detect herbicides are algae, for which the inhibition of photosystem II by triazines and phenylurea herbicides can be specifically measured by pulse-amplitude modulated fluorometry, 33 which was very responsive in the water samples that were suspected to contain herbicides (Eff1, Eff2, MF, SW, SI, Table S5). Estrogen receptor. The most relevant receptor-mediated effects are related to endocrine disruption (SI, Section S6-B, Figure S6). Estrogenic effects are by far the most prominent and environmentally relevant endocrine effects for aquatic species but they are overshadowed by other endocrine endpoints when it comes to human health. Fourteen different bioassays indicative of estrogenic effects were evaluated and all were active in four to five samples (Table 2). The absolute responsiveness was highest for ER-CALUX and MCF7-ERE but the effect pattern across the different samples was similar for all bioassays (SI, Table S5). No anti-estrogenic activity could be detected in any of the samples, which is typical for samples that contain estrogenic chemicals. 19 Androgen receptor. Of seven bioassays (bioassay #. 37 to 43, Table 1), only the MDA-kb2 produced positive results in the wastewater samples. Both GR and AR are expressed in this cell line and they share the same DNA response element, so it is unclear if the activity in this assay is purely AR-mediated, although incubation with flutamide indicates that the contribution of AR to the overall effect is higher than of GR. Both bioassays for anti-androgenicity (anti-ar-calux and anti-mda-kb2) were positive in some samples although only at very high REF. The WWTP effluents, which typically have highest anti-androgenic effects, were not responsive in anti-mda-kb2, presumably due to the interfering agonistic response of effluent, similar to what has been observed with YAS and anti-yas in an earlier study. 34 Appendix VI p.14

220 Bioanalytical assessment of water quality Supporting Information Progesterone receptor. The two transactivation assays for the PR, PR-CALUX and PR-GeneBLAzer, did not exceed the 10% effect threshold in all samples. However, 19, 35, 36 progestagenic activity has been detected previously in aquatic samples. The anti-pr (anti-pr-calux) assay was also negative with samples tested to a REF of 2. The increased levels of progesterone and 17 -hydroxyprogesterone in the bioassay for steroidogenesis were most likely due to an inhibitory effect on CYP21A. Glucocorticoid receptor. ER, AR and PR are important for the development and functioning of the reproductive system. The GR is more abundant and found in all cell types. Given that the GR has important functions in glucose metabolism and the immune feedback mechanisms, it has been linked to a wide spectrum of diseases, including cardiovascular, inflammatory and immune disease, diabetes and obesity, and is therefore of high potential relevance. Five bioassays targeting activation of the GR were included in this study, all of which were active in one or more samples (SI, Figure S7). The 19, 35 observed GR activity is in agreement with previous studies on similar water types. Thyroid receptor. No assay indicative of modulation of the thyroid hormone system showed response to any of the water samples (SI, Table S5), which comes as no surprise because the most commonly observed thyroid agonists and goitrogens are oxyanions such as the perchlorate and nitrate 37, which act not via TR binding. RAR/RXR. The retinoic acid signaling pathway is crucial for reproduction and development as well as for cell homeostasis and immune function. 38 Two receptors are key to this pathway, the retinoic acid receptor (RAR) and the retinoic X receptor (RXR). RXR is a heterodimer partner not only for the RAR but also for other nuclear receptors including PPAR, PXR, CAR and TR. 39 We tested four bioassays that are connected to the retinoic acid-signaling pathway but only the two-hybrid assay, where RAR is inserted into yeast with lacz as reporter gene, showed activity in three samples. The ROR -transfactorial did not show any response with the water samples tested, although this endpoint tested positive in 30% of the ToxCast I chemicals. 11 Clearly, the role of RXR for water quality assessment should be further explored in the future. Reactive toxicity. Testing for reactive toxicity focused on genotoxicity and mutagenicity (Table 2, Figure S8). Only one bioassay, the micronucleus assay, detects DNA damage directly; the Ames test relies on reverse mutations and the umuc assay on detection of DNA repair. Three samples were active in the micronucleus assay, Eff2, RW and DW (SI, Figure S8). The SOS chromotest and umuc assays gave consistent results and were responsive at lower REFs but the Ames assay gave more variable responses and even false-positive responses (presumably due to the high inherent degree of endogenous gene mutation in bacteria). Appendix VI p.15

221 Bioanalytical assessment of water quality Supporting Information Tests for genotoxicity can be run in the presence and absence of a rat liver metabolic enzyme mix (S9 fraction) to differentiate between chemicals that require metabolic activation and those that are detoxified by metabolism. In the umuc and the Ames assay, there was no discernable difference between response with and without S9. The E.coli assay for protein damage relies on growth inhibition differences between a strain that is glutathione-deficient (GSH-) and the corresponding parent strain (GSH+). 40, 41 These assays were found to be unsuitable for samples with high organic matter content. 40 In the present study no effects could be detected although there appeared to be a qualitative difference in growth inhibition between the GSH- and the GSH+ strains. Only one assay attempted to quantify reactive oxygen species formation in RTG2 cells and results were positive and consistent with the activation of oxidative stress response pathway discussed below. Induction of adaptive stress response pathways. Both the heat shock response and the hypoxia induction were negative in all assays tested (SI, Table S5). No bioassay for endoplasmic reticulum stress could be identified and therefore this potentially relevant endpoint had to be omitted. Response to inflammation was tested by enzyme-linked immunosorbent assay (ELISA) in the human T-lymphoblast cell line Jurkat E6.1 by quantifying I B, which is a chaperone for NF- B that keeps NF- B inactive and prevents it from entering the nucleus. Five samples tested positive in this assay (SI, Table S5). In contrast the NF- B-CALUX, NF- B-GeneBLAzer and the NF- B-cisFACTORIAL did not respond to any of the samples. These latter assays are relatively new, have not yet been applied for water quality assessment and possibly require further validation work to improve their detection limits. Three of four bioassays indicative of the oxidative stress response were active in six to eight samples, highlighting the potential importance of this stress response pathway. The AREc32, Nrf2/ARE-cisFACTORIAL and the Nrf2-CALUX were all able to detect effects at low sample enrichment. The data also showed a wide dynamic range between different samples, which makes them ideal water quality indicators, although their relevance to health effects is less evident than for other bioassays. The p53 protein plays an important role as a tumor suppression factor but all evaluated assays did not show any effect, both, in presence and absence of S9. General cytotoxicity and models for system response. The overarching effect overlying each of the cellular toxicity pathways is cytotoxicity (Figure 1). As cytotoxicity normally manifests at higher concentrations than induction of response pathways, this endpoint is best implemented as a quality control measure for all induction assays to Appendix VI p.16

222 Bioanalytical assessment of water quality Supporting Information verify that cell vitality is not adversely affected. We did not complete full dose-response curves for cytotoxicity in all mammalian reporter gene assays apart from AREc32 for which cytotoxicity was similar to the targeted cytotoxicity assays in a human colon cancer cell line Caco 2 NRU. The fish cell line RTG2 was of relatively low responsiveness. Acute toxicity in the zebrafish embryo (DART 48h lethality) was only observed in two samples Eff2 and SW but at high enrichment factors (REF 5-6). Cytotoxicity assays may also give information about system toxicity if appropriate cell lines are used, although a recent report by the ACuteTox project suggests little difference in response using different cell lines in vitro. 42 Here we considered the sublethal endpoint in the zebrafish embryo toxicity test after 120 h of incubation as an indicator of developmental and potentially long-term apical effects. This effect was clearly more responsive than the 48 h acute lethality endpoint in the zebrafish embryo. The SK-N-SH neuroblastoma cell line 43 is sensitive to chemicals that block the sodium channels and similar cell lines have been used previously in an assay to evaluate paralytic shellfish poisons caused by neurotoxic freshwater cyanobacteria. 44 We used a simpler version of this assay in this study, evaluating cytotoxicity as a coarse measure of cellular neurotoxicity. This endpoint was not active for our water samples tested to a REF of 2. Expression of various cytokines in the human acute monocytic leukemia cell line THP- 1 gives an indication of potential immunotoxicity. 19 Although a previous study reported detectable inhibition of IL1 secretion in chlorinated waters, 19 we did not observe detectable effects in our study up to a REF of 2. Benchmarking treatment efficacy. The bioassay results can be used to assess and monitor treatment processes (see SI, Section S7 for more detail). Best suited for this purpose are bioassays that show a clear decrease in response with increasing treatment and will not fall below the detection limit after treatment. We refer to these assays as indicator bioassays from hereon. Reverse osmosis (RO) is known as highly efficient in removing trace constituents, and only 13 indicator bioassays remained above detection limit after RO (but below LOD after AO, SI, Figure S10). After ozonation and BAC treatment, (another) 13 indicator bioassays remained above detection limit (SI, Figured S11 and S12). Between the two water reclamation plants, 18 suitable indicator bioassays were identified, including those indicative of AhR, PXR, CAR, ER, algal toxicity, genotoxicity and oxidative stress (SI, Figures S11 and S12). In contrast, chlorination and chloramination increased the response in 15 of the 101 bioassays in drinking water samples (SI, Figure S13). The increased effect was most pronounced in the induction of xenobiotic metabolism and the reactive modes of action and oxidative stress response, which is consistent with the formation of chlorinated disinfection by-products that cause genotoxicity and oxidative stress. 17, 45 This comparison demonstrates that there is no single battery of bioassays that can be applied Appendix VI p.17

223 Bioanalytical assessment of water quality Supporting Information universally, but rather that a panel of assays should be tailored to fit the needs of each application. A routine test battery of indicator bioassays. Because a single bioassay is not capable of assessing water quality comprehensively, a small number of relevant biological endpoints that are sensitive to micropollutants typically encountered in water samples can be used collectively as indicators of water quality. A battery of bioassays should include relevant examples of endpoint categories that relate to different steps in the cellular toxicity pathway as is proposed in the following: 1. Induction of xenobiotic metabolism. Our results confirmed that activation of the aryl hydrocarbon receptor, already one of the most widely applied endpoints in water quality assessment, is a relevant indicator of the presence of chemicals and should be included in any routine test battery. The pregnane X receptor showed high responsiveness to water samples and responds to a wide range of chemicals and should be further explored for routine application. 2. Endocrine disruption. Specific receptor-mediated modes of action including estrogenic and androgenic effects showed the most promise for routine water quality screening applications. Recent work using GR-CALUX applied to various environmental chemicals and water samples 35 also support our findings that GR activity is present and could be detected in secondary treated effluent with the current battery of GR bioassays. In addition, the co-occurrence of progestins and synthetic estrogens in hormone replacement therapy, PR activity remains of interest, despite the negative findings here. Lastly, it is vital to test for antagonistic as well as agonistic effects. 3. Reactive modes of action. Genotoxicity as measured by well-established bioassays such as umuc or SOS chromotest served the purpose well. Bioassays derived from mammalian cells would be more relevant for human health and thus preferable to bacterial assays. As the p53 assays did not show the hoped-for responsiveness it is recommended to further evaluate alternative bioassays. 4. Adaptive stress response pathways. Oxidative stress response appears to be a highly sensitive and yet selective indicator of environmental pollution that responds to a wide range of chemicals as well as to transformation products and disinfection by-products. 46 This is consistent with previous chemical testing in Nrf2/ARE-cisFACTORIAL, where almost 50% of the ToxCast chemicals were active. 11 Thus this mode of action is recommended to be included in any routine test battery, especially if transformation reactions are expected. 5. Cytotoxicity and systemic response. The bacterial cytotoxicity assays (V. fischeri and P. phosphoreum) are very fast and sensitive screening assays but their high sensitivity and effects caused by controls indicated that the responses may not be of human health Appendix VI p.18

224 Bioanalytical assessment of water quality Supporting Information relevance. In contrast, cytotoxicity assays with mammalian cells are comparatively less sensitive and clearly the bioassays for toxicity pathways are more relevant. With limitations, specific cell lines may be used as indicators of organ/systemic response. Nevertheless, further work has to be invested in the selection of appropriate tests systems and protocols for cell-based bioassays for organ/systemic responses as these are much less developed than nonspecific cytotoxicity assays and bioassays targeting cellular toxicity pathways. The enzymatic AChE inhibition assay to test for one aspect of neurotoxicity failed completely but there is the potential to implement neurotoxicity endpoints in the zebrafish embryo toxicity test. 47 A whole organism in vitro assay, such as the zebrafish embryo assay may help to link specific responses from the cellular assays to systemic responses by the observed phenotypes. We also recommend that more attention be paid to the basal activities of cell lines in use. As metabolism is the most crucial modifier of toxicity, detoxifying many chemicals but activating others, the metabolic capacity of bioassay cell lines needs to be considered when selecting or designing a bioassay. Many available cell lines have low metabolic activity and for these it is advisable to run each experiment in parallel in the presence of an exogenous metabolic mixture, e.g., liver S9 fraction. In summary, an ideal battery of bioassays for water quality assessment and testing should contain sensitive bioassays that cover a wide range of cellular toxicity pathways (Figure 1). For induction of xenobiotic metabolism pathways, we recommend AhR and PXR. For specific modes of action, the receptor-mediated hormonal effects related to the estrogenic, glucocorticoid and anti-androgenic pathways appear to be most relevant as most are responsive to water samples. The oxidative stress response clearly stands out as a highly responsive defense mechanism. Cell viability ( cytotoxicity ) assays should be further developed with a focus on those representative of systemic responses. AUTHOR INFORMATION Corresponding Author B.I. Escher, The University of Queensland, National Research Centre for Environmental Toxicology (Entox), 39 Kessels Rd, Brisbane 4108, Australia, Telephone Fax: b.escher@uq.edu.au. Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. Conflict of Interest Disclosure Attagene and BDS are companies that market the bioassays applied by them in the present study. Appendix VI p.19

225 Bioanalytical assessment of water quality Supporting Information Funding Sources This work was supported, mainly, by the WateReuse Research Foundation (WRF 10-07), and, in part, by the California Water Resources Control Board (Agreement No ) and the European Union, project Demeau, grant agreement number ACKNOWLEDGMENT We thank Unitywater and Seqwater for access to their treatment plants. We acknowledge J.P. Giesy of University of Saskatchewan, Canada, for sharing the H4IIE-luc cells with RECETOX and M. Denison from University of California Davis, USA, for sharing the AhR-CAFLUX used at UQ and RECETOX. AREc32 cells were kindly provided by C.R. Wolf from University of Dundee, UK, to UQ. We thank Michael Bartkow for helpful discussions, Peta Neale, Julien Reungoat and Jatinder Sidhu for sampling assistance and Daniela Baumberger, Mriga Dutt, Eva Glenn, Ling Jin and Shane McCarty for experimental assistance. ABBREVIATIONS AO, advanced oxidation; AR, androgen receptor; ASR, adaptive stress response; ATG, Attagene; AWQC, Australian Water Quality Centre; BDS, BioDetection Systems; BEQ, Bioanalytical equivalent; CAPIM, Centre for Aquatic Pollution Identification and Management; CAR, constitutive androstane receptor; CSIRO, Commonwealth Scientific and Industrial Research Organisation; CT, cytotoxicity; CYP, cytochrome P450 monoxygenase ; DART, embryo toxicity test with the zebrafish Danio rerio ; DW, drinking water; EC, effect concentration; EEQ, estradiol equivalent; Eff, effluent; ER, estrogen receptor; GU, Griffith University; GR, glucocorticoid receptor; HK, Hong Kong Baptist University; HTS, high-throughput screening; IR, induction ratio; IRCM, Cancer Research Institute of Montpellier ; ISO, International Organization for Standardization; IWW, Institute for Water Research in North-Rhine Westfalia, Germany; MF, microfiltration; MOA, mode of action; MTT, (3-(4,5-dimethylthiazol -2-yl)-2,5- diphenyltetrazolium bromide; NJU, Nanjing University; NIH, National Institutes of Health; NWC, National Water Commission; NRU, neutral red uptake; OECD, Organisation for Economic Co-operation and Development; PPAR, peroxisome proliferator-activated receptor; PR, progesterone receptor; PXR, pregnane-x-receptor; RAR, retinoic acid receptor; RCEES, Research Center for Eco-Environmental Sciences; RECETOX, Research Centre for Toxic Compounds in the Environment ; REF, relative enrichment factor; RFU, relative fluorescence units; RLU, relative light units; RO, reverse osmosis; ROS, reactive oxygen species; RT-PCR, real-time polymerase chain reaction; RW, river water; SCCWRP, Southern California Coastal Water Research Project ; SPE, solid phase extraction; SW, stormwater; SWISS, Centre for Applied Ecotoxicology; TEQ, toxic equivalent; UA, University of Arizona; UCR, University of California Riverside; UF, University of Florida; UFZ, Helmholtz Centre for Appendix VI p.20

226 Bioanalytical assessment of water quality Supporting Information Environmental Research ; UQ, The University of Queensland; USF, University of South Florida; WRP, water reclamation plant; WWTP, wastewater treatment plant; XM, xenobiotic metabolism. Table 1. Bioassays used and their toxicity pathway classifications. Literature references are provided for the method development and for how the assay was performed. Modifications of the assays are summarized in the Supporting Information. Assay numbers (#) are equivalent to the numbers in Figure 3. Method modifications are listed in the SI, Table S2. # Laboratory Bioassay Reference for method developm ent Experimental approach (literature reference/more information SI) in Xenobiotic metabolism 1 ATG PXR-cisFACTORIAL 2 ATG PXR-transFACTORIAL 3 IRCM HG5LN PXR 4 ATG CAR-transFACTORIAL 5 CAPIM CAR-yeast 6 ATG PPAR -transfactorial 7 ATG PPAR -transfactorial 8 IRCM HELN-PPAR 9 BDS CALUX-PPAR 10 BDS, CSIRO CALUX-PPAR 2 11 HK MCF7-PPAR 12 GU PPAR -GeneBLAzer 13 GU Anti-PPAR -GeneBLAzer 14 CAPIM AhR-yeast 15 UQ, RECETOX CAFLUX 16 RECETOX H4IIEluc 17 HK MCF7DRE 18 ATG AhR-cisFACTORIAL 19 UFZ DART cyp1a induction Specific modes of action 20 UQ, SWISS Algae photosynthesis inhibition 21 UQ Acetylcholinesterase inhibition Specific MOA: ER 22 GU, CSIRO, ER-CALUX 23 UQ E-SCREEN 24 SWISS, CSIRO, YES Appendix VI p See SI Section S2- See SI Section S and SI Section S2-B RECETOX: UQ: 62 61,

227 Bioanalytical assessment of water quality Supporting Information 25 CAPIM her yeast 26 CAPIM meder yeast IRCM HELN-ER IRCM HELN-ERß ATG ERE-cisFACTORIAL RECETOX her -HeLa HK MCF7-ERE ATG ER -transfactorial NJU Steroidogenesis (estrogens) UFZ DART cyp19a1b UF, USF, UCR, ER -GeneBLAzer 29 57, see SI, Section SCCWRP S2-C. 36 CSIRO, GU Anti ER-CALUX Specific MOA: AR 37 GU, BDS, CSIRO AR-CALUX 68, IRCM HELN-AR HK MCF7-ARE UA, CSIRO YAS UF, USF, UCR, AR-GeneBLAzer 29 57, see SI, Section SCCWRP S2-C. 42 ATG AR-transFACTORIAL RECETOX MDA-kb RECETOX Anti-MDA-kb CSIRO, GU Anti-AR-CALUX 68, Specific MOA: GR 46 GU, BDS, CSIRO GR-CALUX UA GR Switchgear See SI Section S2-D. 48 ATG GR-transFACTORIAL RECETOX GR-MDA-kb GU, UF, USF, GR-GeneBLAzer GU Anti-GR-GeneBLAzer GU Anti-GR-CALUX Specific MOA: PR 53 UF, USF, UCR, PR-GeneBLAzer 29 57, see SI, Section SCCWRP S2-B. 54 GU, BDS, CSIRO PR-CALUX GU Anti-PR-CALUX NJU Steroidogenesis (progesterone) NJU Steroidogenesis (17a 77 OH- 78 Specific MOA: TR 58 BDS, GU TR-CALUX UQ T-SCREEN ATG THR 1-transFACTORIAL IRCM HELN-TR 88 Specific MOA: Reproductive and developmental effects Appendix VI p

228 Bioanalytical assessment of water quality 62 HK MCF7-RARE 63 UQ P19/A15 64 ATG RORß-transFACTORIAL 65 CAPIM hrar-yeast Assay Reactive MOA 66 UQ, RCEES umuc TA1535/pSK1002 Supporting Information See SI Section S2- E. UQ: 92, RCEES: UQ umuc TA1535/pSK1002 +S9 68 RCEES umuc NM RECETOX SOS chromotest UA, IWW Ames TA98 96 IWW: UA, IWW Ames TA98+ S9 96 IWW: 97, UA Ames TAmix UA Ames TAmix +S UQ, IWW Ames TA UQ: 99, IWW: AWQC Micronucleus assay CSIRO ROS formation RTG UQ Protein damage E.coli Adaptive stress response 78 ATG HSE-cisFACTORIAL UFZ hspb11 induction DART ATG HIF-1a-cisFACTORIAL UA Hypoxia-Switchgear See SI Section S2- G. 82 ATG NF-kB-cisFACTORIAL UQ NF-kB-Geneblazer 29 57, see SI, Section S2-B. 84 BDS NF-kB-CALUX GU Jurkat E6.1 IkB None See SI Section S2- G. 86 UQ AREc UA Nrf2-keap 107 See SI Section S2- H. 88 ATG Nrf2/ARE-cisFACTORIAL BDS Nrf2-CALUX ATG p53-cisfactorial BDS p53-calux BDS p53-calux +S UF p53-geneblazer 29 57, see SI, Section S2-B. Cytotoxicity and indicators of system response 94 UQ AREc32 cell viability GU Caco 2 NRU , see SI Section S2-I. 96 CSIRO RTG2 MTT 110 Appendix VI p.23

229 662 Bioanalytical assessment of water quality 97 UFZ DART 48h lethality 98 UFZ DART 120h sublethal 99 GU SK-N-SH cytotoxicity 10 GU THP1 cytokine 0 10 UQ Algae growth inhibition 1 10 UQ, SWISS Vibrio fischeri (Microtox) 2 10 RCEES Photobacterium phosphoreum 3 Supporting Information See SI Section S , see SI Section S2-K. SWISS: 71, UQ: 20 Appendix VI p.24

230 Bioanalytical assessment of water quality Supporting Information Table 2. Summary of responsive and non-responsive bioassays (total = number of bioassays, in parenthesis number of replicates), + = number of positive responses, - = number of negative responses). Toxici ty pathw ay MOA Inducing chemicals/ positive controls tot al + - Positive response Negative response Pregnane X receptor (PXR) Steroids/ PXRcisFACTORIAL, PXRtransFACTORIAL, HG5LN PXR - Constitutiv e androstane receptor (CAR) Phenobarbi tol, various pharmaceuticals 2 (1 ) 1 1 CAR-yeast CARtransFACTORIA L Peroxisom e proliferator -activated receptor (PPAR) Phthalates, fibrate pharmaceut icals 7 (1 ) 2 5 PPAR - transfactorial, HELN-PPAR PPAR - transfactoria L, CALUX- PPAR, CALUX- PPAR, PPAR GeneBLAzer, MCF7-PPAR (transient) PPAR suppressio n Anti-PPAR GeneBLAzer Xenobiotic metabolism Aryl hydrocarbo n receptor (AhR) PAHs, PCDDs, coplanar PCBs 6 (1 ) 6 0 AhR-yeast, CAFLUX, H4IIEluc, MCF7- DRE (transient), AhRcisFACTORIAL, DART cyp1a induction - Appendix VI p.25

231 Bioanalytical assessment of water quality Supporting Information Acetylcholi n-esterase (AChE) Insecticide s AChE enzyme inhibition Specific MOA Photosyste m II Estrogen receptor (ER) Herbicides 1 (1 ) Human hormones and industrial chemicals (xenoestro gens), 17 estradiol 14 (9 ) 1 0 IPAM ER-CALUX, E- SCREEN, YES, HELN_ER, HELN_ERß, EREcisFACTORIAL, her -HeLa-9903, MCF7-ERE, ER - transfactorial, Steroidogenesis, DART cyp19a1b (aromatase), ER- GeneBLAzer, her yeast, meder yeast ER suppressio n 4-Hydroxytamoxifen 1 (1 ) 1 0 Anti-ER-CALUX - Specific receptor-mediated MOA Androgen Receptor (AR) AR suppresion (Dihydro)- testosteron e 7 (6 ) Flutamide 2 (1 ) 1 6 MDA-kb2 (but coexpression with GR) 2 0 Anti-AR-CALUX, anti MDA-kb2 AR-CALUX, HELN-AR, MCF7-ARE (transient), Yeast Androgen Screen (YAS), AR- GeneBLAzer, ARtransFACTORIA L Appendix VI p.26

232 Bioanalytical assessment of water quality Supporting Information Progestero ne receptor (PR) Levonorges trel 4 (5 ) 2 2 Steroidogenesis, induction of progesterone and of 17a OHprogesterone PR-CALUX, PR-GeneBLAzer PR suppressio n Mifepriston e Anti-PR-CALUX - Glucocorti coid receptor (GR) Dexametha sone 5 (6 ) 5 0 GR-CALUX, GR Switchgear, GRtransFACTORIAL, GR-MDA-kb2 (AR suppressed), GR- GeneBLAzer - GR suppressio n Mifepriston e Anti-GR-CALUX, anti-gr- GeneBLAzer - Thyroid receptor (TR) 3,3 5- Triiodothyronine 4 (1 ) TR-CALUX, T- SCREEN, THR 1- transfactoria L, HELN-TR RAR/RXR (Reproduct ive and developme ntal effects) Retinoic acid hrar-yeast Assay MCF7-RARE, P19/A15, RORßtransFACTORIA L, Reactive modes of action Genotoxici ty Oxidative stress 4- Nitroquino line-noxide PAH, electrophili c chemicals, 11 (4 ) 11 0 umuc +/-S9, SOS chromotest, Ames +/-S9, micronucleus assay Oxidative stress in RTG2 cells - Appendix VI p.27

233 Bioanalytical assessment of water quality Supporting Information t-butyl hydroquino ne Protein damage Sea-Nine Protein damage E.coli GSH+/- Heat shock response Hypoxia Oxygen depletion (can be caused by metals) Tunicamyc in, caplain HSEcisFACTORIAL, hspb11 induction in DART after 120h HIF-1acisFACTORIAL, Hypoxia- Switchgear Endoplasm ic reticulum stress High glycol salt, Inflammati on Metals, PCBs, smoke, particles Jurkat E6.1 IkB NF-kB-CALUX, NF-kB- GeneBLAzer, NF-kBcisFACTORIAL Adaptive stress response pathway Oxidative Stress DNA damage Reactive oxygen species,, t- butyl hydroquino ne Electrophil ic chemicals, UV radiation, nutlin AREc32, Nrf2/AREcisFACTORIAL, Nrf2-CALUX 4 (1 ) Nrf2-keap 0 4 p53- cisfactorial, p53-calux-s9, p53-calux +S9, p53- GeneBLAzer Appendix VI p.28

234 Bioanalytical assessment of water quality Supporting Information Bacterial cytotoxicit y All 2 (1 ) 2 0 Vibrio fischeri (Microtox), Photobacterium phosphoreum - Algal growth All (+herbicide s) 1 (1 ) 1 0 Algae growth inhibition Cytotoxicity indicative of system response Cytotoxicit y (mammalia n cells) Developme nt Neurotoxic ity Immunotox icity All AREc32 cell viability, Caco 2 NRU, RTG2 MTT, DART 48h lethality All DART 120h sublethal Insecticide s Immunosu ppressive chemicals SK-N-SH cytotoxicity THP1 cytokine Appendix VI p.29

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242 Bioanalytical assessment of water quality Supporting Information 107. Villeneuve, N. F.; Du, Y.; Wang, X. J.; Sun, Z.; Zhang, D. D. In High-throughput screening of chemopreventive compounds targeting Nrf2, rd IEEE International Conference on Nano/Micro Engineered and Molecular Systems, Vols 1-3, New York, NY, USA, 2008; IEEE: New York, NY, USA, 2008; pp Van der Linden, S.; von Bergh, A.; Van Vugt-Lussenburg, B.; Jonker, L.; Brouwer, A.; Teunis, M.; Krul, C.; van der Burg, B., Development of a panel of high throughput reporter gene assays to detect genotoxicity and oxidative stress. Mutat. Res. 2013, submitted for publication Konsoula, R.; Barile, F. A., Correlation of in vitro cytotoxicity with paracellular permeability in Caco-2 cells. Toxicol. Vitro 2005, 19, Mosmann, T., Rapid colorimetric assay for cellular growth and survival: Application to proliferation and cytotoxicity assays. J. Immun. Meth. 1983, 65, Küster, E.; Altenburger, R., Comparison of cholin- and carboxylesterase enzyme inhibition and visible effects in the zebra fish embryo bioassay under short-term paraoxon-methyl exposure. Biomarkers 2006, 11, Gündel, U.; Kalkhof, S.; Zitzkat, D.; von Bergen, M.; Altenburger, R.; Küster, E., Concentrationresponse concept in ecotoxicoproteomics: Effects of different phenanthrene concentrations to the zebrafish (Danio rerio) embryo proteome. Ecotox. Environ. Saf. 2012, 76, Knöbel, M.; Busser, F. J. M.; Rico-Rico, A.; Kramer, N. I.; Hermens, J. L. M.; Hafner, C.; Tanneberger, K.; Schirmer, K.; Scholz, S., Predicting adult fish acute lethality with the zebrafish embryo: relevance of test duration, endpoints, compound properties, and exposure concentration analysis. Environ. Sci. Technol. 2012, 46, Manger, R. L.; Leja, L. S.; Lee, S. Y.; Hungerford, J. M.; Hokama, Y.; Dickey, R. W.; Granade, H. R.; Lewis, R.; Yasumoto, T.; Wekell, M. M., Detection of paralytic shellfish poison by rapid cell bioassay: antagonism of voltage-gated sodium channel active toxins in vitro. J. AOAC Int. 1995, 78, Baqui, A.; Meiller, T. F.; Chon, J. J.; Turng, B. F.; Falkler, W. A., Granulocyte-macrophage colony-stimulating factor amplification of interleukin-1 beta and tumor necrosis factor alpha production in THP-1 human monocytic cells stimulated with lipopolysaccharide of oral microorganisms. Clin. Diagn. Lab. Immunol. 1998, 5, OECD Test guideline no Alga, growth inhibition test. ; Environmental Directorate, Organisation for Economic Co-operation and Development: Paris, France, ISO , Water quality determination of the inhibitory effect of water samples on the light emission of Vibrio Fischeri (luminescent bacteria test). In International Organization for Standardization (ISO): Geneva, Switzerland, GB/T Water quality determination of the acute toxicity Luminescent bacteria test; National Standard of China, ttp://kjs.mep.gov.cn/hjbhbz/bzwb/shjbh/sjcgfffbz/199508/t _67352.htm: 1995 Appendix VI p.37

243 1019 Bioanalytical assessment of water quality Supporting Information Supporting Information Benchmarking organic micropollutants in wastewater, recycled water and drinking water with in vitro bioassays Beate I. Escher, Mayumi Allinson, Rolf Altenburger, Peter A. Bain, Patrick Balaguer, Wibke Busch, Jordan Crago, Andrew Humpage, Nancy D. Denslow, Elke Dopp, Klara Hilscherova, Anu Kumar, Marina Grimaldi, B. Sumith Jayasinghe, Barbora Jarosova 1 Ai Jia, Sergei Makarov, Keith A. Maruya, Alex Medvedev, Alvine C. Mehinto, Jamie E. Mendez, Anita Poulsen, Erik Prochazka, Jessica Richard, Andrea Schifferli, Daniel Schlenk, Stefan Scholz, Fujio Shiraishi, Shane Snyder 2 Guanyong Su, Janet Y.M. Tang, Bart van der Burg, Sander C. van der Linden, Inge Werner, Sandy D. Westerheide, Chris K.C. Wong, Min Yang, Bonnie H.Y. Yeung, Xiaowei Zhang, and Frederic D.L. Leusch Table of contents Section S1. Additional information on collected water samples Table S1. Description of samples and concentration of dissolved organic carbon (DOC, mg. C L -1 ) Section S2. Additional information on the bioassay methods Table S2. Modifications in the bioassay methods in comparison to the literature references. Section S3. Additional information on data evaluation Table S3. Comparison of 10% effect level with IR1.5 effect level. Figure S1. Derivation of EC SR0.2. Section S4. How robust were bioassays performed in different laboratories? Table S4. Comparison of bioassay results for the same bioassay performed in different laboratories. Section S5. Initial screening of nuclear receptors and transcription factors Figure S2. Limit of detection (LOD). Figure S3. Screening of 25 nuclear receptors and 48 transcription factors with the FACTORIAL bioassay. Section S6. Additional information on bioassay results Figure S4. Presentation of bioassay results. Figure S5. Results of bioassays indicative of induction of xenobiotic metabolism pathways. Figure S6. Results of bioassays indicative of estrogenicity. Figure S7. Results of bioassays indicative of glucocorticoid receptor (GR) activation. Appendix VI p.38

244 Bioanalytical assessment of water quality Supporting Information Figure S8. Results of bioassays indicative of reactive modes of action. Figure S9. Results of bioassays indicative of adaptive stress response pathways. Table S5. Summary of all EC values. Section S7. Monitoring treatment efficacy Figure S10. Bioanalytical fingerprint of the water from the WRP process using reverse osmosis. Figure S11. Bioanalytical fingerprint of the water treated with ozonation and biological activated carbon. Figure S12. Percent treatment efficiency in the 13 bioassays that did not fall below limit of detection after treatment. Figure S13. Bioanalytical fingerprint of the drinking water treatment. Appendix VI p.39

245 Bioanalytical assessment of water quality Supporting Information Section S1. Additional information on collected water samples The water samples were collected across a subset of sites in Southeast Queensland, Australia (Table S1), where previous water collections and bioanalytical characterization have taken place (Macova et al., 2011). Table S1. Description of samples and concentration of dissolved organic carbon (DOC). Sample Site description DOC (mg C L -1 ) Collected amount of water Water Reclamation Plant 1 Eff1 WWTP effluent from a municipal sewage treatment plant that 8.0 ± L uses activated sludge treatment, taken at the influent of the WRP MF Water sample taken after microfiltration (MF) using filters 7.7 ± L disinfected by chloramination to avoid biofouling RO Permeate after the reverse osmosis (RO) process 0.3 ± L AO Final recycled water after RO and treatment with UV/H 2 O 2 (indirect potable reuse quality) 0.2 ± L Water Reclamation Plant 2 Eff2 WWTP effluent from a municipal sewage treatment plant that uses activated sludge treatment, taken at the influent of the WRP 11.5 ± L O 3 / BAC RW DW SW H 2 O Recycled water after ozonation and biologically activated carbon filtration (for industrial reuse and irrigation) River water taken at the influent of a metropolitan drinking water treatment plant Drinking water treated by coagulation, chlorination and chloramination Collected after a rain event on the 25 th of January 2012 from a stormwater drain that receives runoff from a residential catchment. Ultrapure water (milliq water) run through the same SPE as all other water samples 4.8 ± L 5.6 ± L 3.0 ± L 4.2 ± 2.0 a 14 L a Average of eight measurements collected at the same site during 16/03/2011 to 17/04/2012, as SW collected 25/01/2013 yielded invalid DOC results. SPE = solid phase extraction, WRP = water reclamation plant, WWTP = wastewater treatment plant. The water samples were collected in 1 L amber glass bottles and transported to the laboratory within 2 h where they were acidified to ph 3 with concentrated hydrochloric acid (HCl). Samples containing chlorine were quenched with sodium thiosulphate (1 g/l). Most samples underwent solid phase extraction (SPE) immediately. As the sample volume was high, some samples could not be processed immediately and these were cooled to 4 C and stored for less than a week before SPE was performed. The SPE was performed according to Macova et al. (2011) with the sorbent material validated in NWC (2011). All samples were filtered with a 1.6 µm glass fiber filter (GF/A Whatman) before extraction. Fourteen one-liter batches of Eff1, MF, Eff2 28 L Appendix VI p.40

246 Bioanalytical assessment of water quality Supporting Information and SW and 28 one-litre batches of RO, AO, O 3 /BAC, RW, DW and Blank (defined in Table S1) were extracted by passing each through two 6 cc solid phase cartridges in series, first an Oasis HLB (500 mg, Catalogue Number , Waters) followed by a Supelclean coconut charcoal cartridge (2 g, Catalogue Number U, Sigma- Aldrich). Both types of cartridges were individually preconditioned prior to extraction with 10 ml of 1:1 acetone:hexane mixture, followed by 10 ml methanol and 10 ml of 5 mm HCl in MilliQ water. This resulted in 28/14 pairs of cartridges per sample (28 pairs for the cleaner samples and controls, 14 pairs of the WWTP effluent samples, MF and SW). All cartridges were sealed individually and kept at -20 C until elution. Before elution the cartridges were defrosted and dried completely under vacuum, then elution was carried out with 10 ml of methanol and 10 ml of acetone:hexane. The eluate of 8/4 pairs of cartridges per sample were combined and evaporated under purified nitrogen gas before being solvent exchanged to methanol at a final volume of 1 ml. The SPE extracts were aliquoted and tested in four laboratories (ATG, GU, UA, UQ). The extracts were dried as described below to send to ATG and were sent as methanolic extracts to UA. After the initial positive results, the remaining 20/10 pairs of cartridges, which had been stored for 5 months, were eluted. The extracts were combined and aliquoted for the remaining 16 laboratories, and were evaporated under purified nitrogen gas before being solvent exchanged to dimethyl sulfoxide (DMSO) at a final volume of 2 µl for shipping. The 2 µl samples in Agilent high-recovery HPLC vials (Catalogue Number ) were flushed with purified argon gas. The samples were shipped at room temperature with express mail to all laboratories, where they were reconstituted upon arrival (after 1 day (Australia) to 3-5 days (overseas)) with appropriate solvent and stored at -20 C until bioanalysis. For practicality while all water samples were collected and enriched on SPE cartridges together, the cartridges were eluted in two batches. The first batch was used in four laboratories (UQ, UA, GU and ATG). Only after the appropriateness of the 10 samples were assessed in this initial stage by comparison with historic data, the second batch was extracted, aliquoted and sent out to the remaining 16 laboratories. To assure that the storage of cartridges had not changed the samples, the Microtox assay (see below) was performed on both batches and there was good agreement (paired t-test, paring was effective with a P= and r= and a log-log linear regression with a r 2 of ). Appendix VI p.41

247 Bioanalytical assessment of water quality Supporting Information Section S2. Additional information on the bioassay methods In Table 1 of the main article, all bioassay methods are referenced. In some cases, small modifications were made to the protocols and these are listed in Table S2. If modifications were more extensive or the protocols were unpublished, these are detailed in the following paragraphs and referred to in Table S2. Table S2. Modifications in the bioassay methods in comparison to the literature references. Only modified assays are included in this Table. # Laboratories Bioassay Method modification 5 CAPIM CAR-yeast Section S2-A. 9 BDS CALUX-PPARα BDS: Assay performed at 1% DMSO and in 384-well format. 10 BDS, CALUX-PPARγ BDS: Assay performed at 1% DMSO and in CSIRO 384-well format, CSIRO: Cells were lysed in 50 µl of Triton lysis buffer. Luciferase assay substrate was prepared according to Brasier and Fortin (2001). 12 GU PPARγ- Section S2-B. GeneBLAzer 13 GU Anti-PPARγ- Section S2-B. GeneBLAzer 15 UQ, RECETOX CAFLUX 19 UFZ DART cyp1a induction 22 GU, ER-CALUX CSIRO, BDS, IWW RECETOX: seeded at 30000/well, 24h of exposure; cells washed with PBS, 100 μl PBS added to each well, measured by fluorometer. Different exposure times (0-120 hpf) were used. BDS: Assay performed at 1% DMSO and in 384-well format, CSIRO: Cells were lysed in 50 µl of Triton lysis buffer. Luciferase assay substrate was performed according to Brasier and Fortin (2001). IWW: (Richard, 2012). 30 RECETOX herα-hela-9903 Medium DMEM-F12 (Sigma Aldrich, USA), 10% dialyzed fetal calf serum treated with dextran coated charcoal. Each plate exposed to: medium, solvent control, 17β-estradiol (1-500 pm) in triplicates, for 24h, 37 C. 34 UFZ DART cyp19a1b Different exposure time (0-120 hpf) was used. 35 UF, USF, UCR, ERα- GeneBLAzer 96-Well format, Section S2-C. Appendix VI p.42

248 Bioanalytical assessment of water quality Supporting Information # Laboratories SCCWRP 37 GU, BDS, CSIRO 41 UF, USF, UCR, SCCWRP Bioassay AR-CALUX AR-GeneBLAzer Method modification BDS: Assay performed at 1% DMSO and in 384 well format. 96-Well format, Section S2-C. 43 RECETOX MDA-kb2 Cells seeded at 50000/well; solvent control, medium and dihydrotestosterone (DHT 1 pm µm) tested on each plate. 44 RECETOX Anti-MDA-kb2 Competing androgenic ligand: 0.1 nm DHT, agonist controls (0.01 µm and 0.1 nm DHT), medium, solvent control, and standard antiandrogen flutamide (10 nm - 10 µm) tested at each plate. 46 GU, BDS, CSIRO GR-CALUX BDS: Assay performed at 1% DMSO and in 384-well format, CSIRO: Cells were lysed in 50 µl of Triton lysis buffer. Luciferase assay substrate according to Brasier et al. (2001). 47 UA GR Switchgear Section S2-D. 49 RECETOX GR-MDA-kb2 10 μm Flutamide was added to each sample dilution and agonist control (10 μm DHT) to inhibit androgenic activity; solvent control, medium and DHT (1 pm µm) tested on each plate. 50 GU, UF, USF, SCCWRP GR-GeneBLAzer 51 GU Anti-GR- GeneBLAzer 53 UF, USF, PR-GeneBLAzer UCR, SCCWRP 54 GU, BDS, PR-CALUX CSIRO 96-Well format, see SI, Section S2-C; GU: ran as 384-well plate format, no change from original protocol. Agonist 0.4 nm mifepristone. 96-Well format, Section S2-C. BDS: Assay performed at 1% DMSO and in 384-well format, CSIRO: Cells were lysed in 50 µl of Triton lysis buffer. Luciferase assay substrate according to Brasier et al. (2001).. 58 BDS, GU TR-CALUX BDS: Assay performed at 1% DMSO and in 384-well format. Appendix VI p.43

249 Bioanalytical assessment of water quality Supporting Information # Laboratories Bioassay Method modification 59 UQ T-SCREEN BDS: Assay performed at 1% DMSO and in 384-well format. 63 UQ P19/A15 Section S2-E. 70 UA, IWW Ames TA98 According to Xenometric manual ( 71 UA, IWW Ames TA98+ S9 IWW: (Richard, 2012). 74 UQ, IWW Ames TA100 UQ: none, IWW: (Richard, 2012). 79 UFZ hspb11 induction Different exposure time (0-120 hpf) was used. DART 81 UA Hypoxia- Section S2-F. Switchgear 83 UQ NF B - 96-Well format, Section S2-C. Geneblazer 84 BDS NF B -CALUX Assay performed at 1% DMSO and in 384- well format. 85 GU Jurkat E6.1 IkB Section S2-G. 87 UA Nrf2-keap Section S2-H. 89 BDS Nrf2-CALUX Assay performed at 1% DMSO and in 384- well format. 91 BDS p53-calux Assay performed at 1% DMSO and in 384- well format. 92 BDS p53-calux +S9 Assay performed at 1% DMSO and in 384- well format. 93 UF p53-geneblazer 96-well format, Section S2-B. 97 GU Caco 2 NRU Section S2-I. 98 CSIRO RTG2 MTT Exposure media were exchanged with media containing 0.5 mg/ml MTT rather than adding MTT solution directly to the wells. Incubation was for 3 hours at 22degC. MTT was solubilized with DMSO and absorbance determined at 540 nm. 101 GU SK-N-SH Section S2-J. cytotoxicity 102 GU THP1 cytokine Section S2-K. S2-A. Two-hybrid CAR yeast assay The experiments were performed according to Shiraishi et al. (2000) with the following modifications: Yeast cells that were introduced human constitutive androstane receptor Appendix VI p.44

250 Bioanalytical assessment of water quality Supporting Information (CAR) were cultured (30 o C, overnight; Sanyo Incubator, Tokyo, Japan) in a modified SD medium supplemented with 0.88% glucose, lacking tryptophan and leucine. After centrifuge at 2000 rpm for 20 minutes, the medium was replaced by a fresh MSD medium. The yeast solution cell density was measured (595 nm), and, if necessary, cell density adjusted by diluting with MSD medium to readings to a constant MSD solution (60 µl) was added to each well of the first row of a 96-well culture plate (Sumilon 96F disposable plates; Sumilon Bakelite Co., Tokyo, Japan). Thereafter, 2% DMSO / MSD solution (60 µl) was automatically added (Nichiryo NSP-7000 Multichannel Auto Sampling System, Nichiryo Co., Tokyo, Japan) to each well of the 2nd - 8th rows of the plate. Six samples were run on each plate, with aliquots of each sample (60 µl) added to two neighboring wells of the 1st row of the plate. An aliquot was removed from each well of row 1 and added to row 2 to dilute 2-fold. This process was repeated from rows 2 7. No sample solution from row 7 was added to the 8th row. Thereafter, yeast solution (60 µl) was added to all wells, the plate shaken (30s; Taiyo S Automatic Mixer, Taiyo, Tokyo, Japan) and then incubated (30 C, 4 h). After incubation, a mixed solution (80 µl) for inducing chemiluminescence and for enzymatic digestion (Aurora GAL-XE Reaction Buffer containing GalactaLux substrate, MP Biomedicals Inc., CA, USA and Zymolyase 100T diluted with Z buffer (a mixture of 21.5 g Na 2 HPO 4 12H 2 0; 6.2 g Na 2 HPO 4 2H 2 0; 0.75g KCl; g MgSO 4 7H 2 0 in 1 L deionised water)) was then added to each well, and the plate incubated (37 C, 1 h; Ikemoto Scientific Technology Co, Tokyo, Japan). Thereafter, a light emission accelerator solution (50 µl; Aurora Accelerator, MP Biomedicals Inc., CA, USA) was added to each well, and the chemiluminescence produced by released β- galactosidase measured with a 96-well plate luminometer (Luminescencer-JNR AB-2100, ATTO Bioinstruments, Tokyo, Japan). 4-tert-octylphenol (Wako Pure Chemical Industries Ltd, Osaka, Japan) was used as positive control. A solvent (vehicle) control (DMSO, Nakalai Tesque Co., Kyoto, Japan) was also used. S2-B. PPARγ-GeneBLAzer assay The commercially available PPARγ-GeneBLAzer assay (Life Technologies, Vic, Australia) is based on a human embryonic kidney cell line (HEK 293H cells) modified to express a fusion protein combining the ligand binding domain of the human peroxisome proliferator-activated receptor γ (PPARγ) fused with the DNA binding domain of the GAL4 gene, and stably transfected with a β-lactamase reporter gene downstream of a GAL4 activator sequence. When an agonist binds to the ligand-binding domain of the PPARγ-GAL4 fusion protein, the protein binds to the activator sequence and stimulates expression of β-lactamase. The division arrested (DA) kit was used here (cat no K1419, Life Technologies, Vic, Australia). In brief, the DA cell aliquot was thawed quickly in a 37ºC water bath, transferred to 10 ml of assay medium, and centrifuged at 200 g for 5 min. The Appendix VI p.45

251 Bioanalytical assessment of water quality Supporting Information supernatant was discarded, and the cell pellet reconstituted to a cell density of cells/ml (determined using a Millipore Scepter Handheld Automated Cell Counter). Using a multi-channel pipette, 32 µl of assay medium was added to the "cell-free control" wells, and 32 µl of the cell suspension was added to all the other wells (30,000 cells/well) of a black wall clear bottom poly-d-lysine coated 384-well plate (cat no , BD, NSW, Australia). In agonist mode, 8 µl of 5 0.5% DMSO (solvent control), 5 rosiglitazone (reference compound, final concentration range from 7 pm to 2 µm) or 5 test samples were added to their respective wells (maximum 0.1% solvent in the final well for all test samples). In antagonist mode, 10 solutions of 0.5% DMSO (solvent control), 10 GW9662 (reference compound, final concentration range from 13 pm to 3.6 µm) or 10 test samples were pre-mixed 1:1 with 10 rosiglitazone agonist (for a final concentration in the well of 32 nm), and 8 µl of the resulting mix added to the respective wells for solvent control, reference compound or sample (maximum 0.1% solvent in the final well for all test samples). The plate was then incubated for 16 h in a humidified 37ºC/5% CO 2 incubator. At the end of incubation, 8 µl of 6 substrate mixture (provided in the kit) was added and the plate incubated for a further 2 h in the dark at room temperature. Fluorescence was then read with a plate reader (BMG Fluostar Omega; BMG Labtech, Vic, Australia) at 460 and 530 nm after excitation at 409 nm. Background fluorescence (determined in the cell-free control wells) was subtracted from all readings, and a β-lactamase expression ratio calculated by dividing the net fluorescence at 460 by net fluorescence at 530 nm. Samples were deemed as positive in agonist mode when they exceeded the 10 % effect concentration (EC 10 ; determined from the rosiglitazone standard curve) and in antagonist mode when they exceeded the 20 % inhibitory concentration (IC 20 ; determined from the GW9662 standard curve). S2-C. GeneBLAZER assay panel Reference chemicals were 17 -estradiol (E2), levonorgestrel (LEV), dexamethasone (DEX), and R1881 for the estrogen, progesterone, glucocorticoid and androgen receptors (ER-, PR, GR and AR), respectively. Chemicals were purchased from Sigma Aldrich (E2, LEV, DEX) or PerkinElmer (R1881). Reference chemicals were diluted in assay-specific assay medium from a stock solution (E2: 2 μm, LEV: 20 μm, DEX, 0.1mM, R1881: 20 μm) prepared in DMSO. Nine dilutions, plus a DMSO-only control were made, and were based on previous optimization of reference compounds to include the entire linear range of fluorescent induction. Final DMSO concentration in diluted reference chemicals was 0.5%. Water extracts were reconstituted in a total of 300 µl of DMSO. Four dilutions of each of the 10 water extracts were prepared by adding 5 μl of reconstituted water extract to assay-specific assay medium to the first dilution and then serial diluting 50 μl of first Appendix VI p.46

252 Bioanalytical assessment of water quality Supporting Information dilution and adding it to 47.5 μl of assay media and 2.5 μl of DMSO to the second and so forth. Final DMSO concentration in diluted reconstituted water extract was 0.5%. Plate set-up was uniform across all laboratories, except in the case of USF, who did not have DMSO-control wells on the second plate. Reference chemicals and water extract dilutions were assayed simultaneously across two 96 well plates. Each reference chemical and water extract dilution was assayed in triplicate. Cell-free media, DMSOcontrol, and DMSO-free control were assayed in triplicate on each plate (except at USF). The four reporter assays used in this assessment were GeneBLAzer ER-Alpha, PR, GR and AR Division Arrested Assay Kits (Life Technologies, Carlsbad, CA). All kits were commercially bought except for the AR assay, which was manufactured for this assessment. Assays were bought as kits and optimized for use in a 96-well plate format, rather than the manufacturer suggested 384-well format. All procedures were performed in a Class II biological safety cabinet using sterile techniques. All media, chemicals and materials used in these assays were from manufacturer recommended sources. Modifications to the manufacturer s protocol were made to cell number, and media/dose volume to optimize the assay for 96-well format. Cells stored under liquid nitrogen vapor were quickly thawed and transferred, drop-wise, into 10 ml of assay medium in a sterile 15-mL conical tube and centrifuged at 200 g for 5 minutes. Supernatant was aspirated and cell pellet was resuspended in 6 ml fresh assay medium. Cells were counted and diluted in assay medium to a density of cells/ml. Ninety μl (50,000 cells) of cell suspension or assay medium (cell-free control wells) were added to each well. Ten µl of appropriate 10X reference chemical, diluted water extract, or DMSO-added assay media were added to corresponding wells. Cells were incubated overnight (~ 16 h) at 37 C with 5% CO 2. On the following day, 20 μl of six times concentrated loading solution, prepared according to the manufacturer s protocol, was added to each well. The plate was covered to protect from light and evaporation, and incubated at room temperature for 2 h in the dark. Fluorescent measurements were made according to manufacturer s instructions. S2-D. Switchgear Assay for the Glucocorticoid Receptor A commercially available GR assay kit (Switchgear Genomics, California) was used to evaluate the GR activity in water samples. The GR-Switchgear assay integrates the signal from four validated pathway-specific reporter vectors using the RenSP reporter gene. This is important, and unique to this assay, since there are numerous endogenous promoters for the gene and no single promoter can respond to all potential agonists and antagonists. Multiple validated house-keeping reporters, using the CLuc reporter gene, are also applied to monitor cell health during the assay, also unique to this particular assay. The assay is a transient-transfection assay, which means that plasmids containing the reporter genes are freshly transfected each time the assay is performed. A human fibrosarcoma cell line (HT1080) was maintained in standard growth medium composed of 500 ml minimal essential media (MEM), 5 ml GlutaMax, 50 ml Appendix VI p.47

253 Bioanalytical assessment of water quality Supporting Information Fetal Bovine Serum (FBS) (Heat inactivated) and 5 ml Pen/Strep. Cells were thawed from liquid nitrogen and passaging was carried out in 75 cm 2 flasks every 2-3 days. The 2 nd generation cells were used in this assay when they reached greater than 80% confluence. Cell density was controlled at cells/ml in stripped growth medium (charcoal stripped FBS, without antibiotics). The transfection reagent containing the 4 GR plasmid constructs and housekeeping constructs were thawed, mixed, and incubated for 30 min at room temperature. The transfection mix was then added to cell medium, thoroughly mixed, and 100 μl added to each well of a 96-well white tissue culture (TC) plate. In a separate 96-well clear TC plate, an aliquot of 100 µl was added to cells in 12 wells for visual monitoring of cell viability and growth. Both plates were incubated at 37 C in a CO 2 incubator for h. After overnight culture, the medium was replaced by 90 µl fresh stripped FBS growth medium and 10 µl of water sample extract diluted in 10% of stripped medium. After h of exposure, 10 µl of the cell supernatant was transferred to a secondary white 96-well TC plate and both plates were frozen at -80ºC. Substrate and buffer solutions were added after the plates were thawed. Luminescence was measured to determine for the luciferase reporter gene activity (LightSwitch Dual Assay System). DEX was used as the positive control and a negative control and solvent control were also included for quality control. S2-E. p19/a15 assay for induction of the retinoic acid receptor (RAR) p19/a15 Cells were grown in Dulbecco s MEM with sodium pyruvate and L-glutamine, high glucose, 10% FBS, 1% penicillin-streptomycin, 1.6% non essential amino acid (NEAA) was obtained from Gibco, Australia. Cells were grown in T75 flasks in 11 ml Dulbecco modified minimal essential medium (DMEM) and incubated at 37ºC and 5% CO 2 and passaged every 2-3 days when cells were 70% confluent. For an exposure experiment, cell concentration was adjusted to 100,000 cells/ml and 100 µl was transferred in each well of a white polystyrene tissue culture treated 96- well microplate (Corning). The plates were then incubated for 24h at 37ºC and 5% CO 2 and dosed with the appropriate amount of chemical or extract. Each plate should include one serial dilution of atra ( M to M) or 9-cis RA ( M to M) as positive control and one row of medium only. The plates were then covered with PCR-SP plate sealer from Axygen and incubated for 24 h before cytotoxicity or induction was assessed. A typical experiment consists of two steps, where each step is performed in duplicate. First, a range finder with a serial (2-fold) dilution series was performed, where induction of RAR pathway and cytotoxicity were evaluated. Interference by cytotoxicity causes a suppression of the induction signal and such concentrations cannot be used for the induction data evaluation. Second, non-cytotoxic concentrations/dilutions of the water sample were selected and a linear dose-response curve was measured for induction only. Often the window between induction and cytotoxicity is small and no maximum Appendix VI p.48

254 Bioanalytical assessment of water quality Supporting Information induction can be reached, therefore concentrations should be selected in a way that the maximum induction ratio is 5. As a control, the cell viability was assessed with the MTS assay. MTS (tetrazolium) is bioreduced by cells into an aqueous, soluble formazan product by dehydrogenase enzymes found in metabolically active cells (Mosmann, 1983). When cells die, the ability to reduce these products is rapidly lost due to mitochondrial dysfunction. The absorbance of the formazan product at 490 nm can be measured directly from 96-well assay plates without additional processing, and the amount is directly proportional to the number of living cells in culture. After 24 h incubation the medium in each plate was replaced by 120 µl MTS (CellTiter 96 AQ ueous One Solution Cell Proliferation Assay (Promega) with MTS and phenazine methosulfate as the electron coupling reagent) in Hyclone DMEM without phenol red (Thermo Scientific) and absorbance at 492 nm was read after 2 h incubation. S2-F. Switchgear Assay for Hypoxia The commercially available hypoxia assay kit (Switchgear Genomics, California) uses the HT1080 cell line with transient transfection of three reporter constructs including lactate dehydrogenase (LDHA) promoter, H1F1a promoter, housekeeping gene ACTB (ACTB_PROM) from Switchgear, in which H1F1a is a well-known hypoxia inducible transcription factor. In brief, transfection reagent, which contained the three plasmid constructs (LDHA, H1F1a, and ACTB), were first thawed from -20ºC and incubated for 30 min at room temperature. The human fibrosarcoma cell line HT1080 was thawed quickly in a 37ºC water bath from the -80ºC freezer, and the thawed cells were immediately added to the growth medium which was composed of Eagle s minimum essential medium (EMEM, ATCC # ), 10% normal FBS, 1% of GlutaMax and 1% of PenStrep. To get 20,000 cells per well, cell density was maintained at cells/ml. Then the transfection reagents were mixed with the cell and medium solution at a ratio of 5:95. Using a multi-channel pipette, 100 µl of the transfected cell mixture was aliquoted to each well of a white 96-well tissue culture plate. In a separate clear 96-well tissue culture plate, 100 µl of cells were aliquoted to 12 wells for visual monitoring of cell viability and growth. Both plates were incubated at 37 ºC in a CO 2 incubator for h. After overnight culture, the medium was replaced by 90 µl of fresh charcoal-stripped FBS growth medium and 10 µl of sample, which was diluted in 10% of stripped medium in advance. After 24 h of exposure, 10 µl of the supernatant was transferred to a secondary white 96-well tissue culture plate, and both of the plates were frozen in -80ºC for better sensitivity. Substrate and buffer solution were then added after the plates were thawed, and luminescence was quantified as a measure of luciferase activity (LightSwitch Dual Assay System, available in the kit). Desferrioxamine (DFO) was used as the positive control. Negative control and solvent control were included for quality control. Appendix VI p.49

255 Bioanalytical assessment of water quality Supporting Information S2-G. Jurkat E6.1 IkB In the assay Jurkat E6.1, cells were resuspended in Roswell Park Memorial Institute medium (RPMI without phenol red supplemented with 5% charcoal-stripped fetal bovine serum) at cells/ml (determined using a Millipore Scepter Handheld Automated Cell Counter). Cells were then seeded at 200,000 cells/well by adding 200 µl of cell suspension to the 48 inner wells of a flat bottom standard 96-well plate, and the test samples were added in 50 µl of white media (maximum 0.1% final solvent concentration). The remaining wells were filled with 250 µl of phosphate buffered saline (PBS) to act as a humidity barrier, and the plate incubated for 24 h in a humidified 37ºC/5% CO 2 incubator. A geometric dilution series of phorbol-12-myristate-13-acetate (PMA) was used as a reference compound, with final concentrations in the well ranging from 0.2 nm to 0.2 µm. After incubation, the content of each well was gently mixed and 200 µl was transferred to a v-bottom 96-well plate. The plate was centrifuged at 300 g for 5 min, and 150 µl of the supernatant was discarded (paying particular attention not to disturb the cell pellet). The pellet was rinsed with 100 µl of warm sterile PBS and the plate centrifuged again at 300 g for 5 min. After centrifugation, 100 µl of the supernatant was discarded (again paying particular attention not to disrupt the cell pellet). IκB concentration in the cell pellet was then determined using a commercially available ELISA kit (IκBα Total InstantOne ELISA; cat no , ebioscience), with minor modifications. In brief, cells were lysed with 1.5 lysis mix added in the v-bottom 96- well plate directly and mixed by aspirating/dispensing with a multi-channel pipette, then placed on an orbital shaker at 300 RPM for 10 min at room temperature. Then, 50 µl of cell lysate were transferred into the InstantOne assay plate (provided with the kit) followed by 50 µl of IκB antibody cocktail (provided with the kit). A negative and positive IκB control, provided with the kit, were also tested with every ELISA run. The plate was covered with an adhesive seal and incubated for 1 h at room temperature on a microplate shaker at 300 RPM. The wells were washed with 200 µl of wash buffer (provided with the kit), all liquid removed by inverting on a paper towel, and 100 µl of detection reagent (provided with the kit) was added to each well. The plate was incubated for 10 min at room temperature on a microplate shaker at 300 RPM, and the reaction stopped by adding 100 µl of stop solution. The absorbance of each well was then measured with a plate reader (BMG Fluostar Omega; BMG Labtech, Vic, Australia) at 450 nm. S2-H. Nrf2-keap cell line The human breast cancer cell line MDA-MB , which was transfected with the antioxidant response element (ARE) luciferase plasmid (Villeneuve et al., 2008), was donated by Prof. Donna Zhang at Department of Pharmacy, the University of Arizona. The standard growth medium was composed of minimal essential medium (MEM, Life Appendix VI p.50

256 Bioanalytical assessment of water quality Supporting Information Tech, # ), 10% FBS, 1% L-glutamine, 0.1% Gentamycin, 6 ng/ml Insulin, 2 mm HEPES and 1.5 µg/ml puromycin. Cells were thawed from liquid nitrogen and passaging was carried out in 75 cm 2 flasks every fourth day. The 4 th generation cells at more than 80% confluence were used in this assay. Cell density was controlled at cells/ml. Using a 8-channel pipette, 100 µl of the cell solution were seeded into one white 96-well plates and one clear 96-well plate (cytotoxicity test). After overnight culture in a CO 2 incubator for 16 h (5% CO 2, 90% humidity), the medium was replaced by 90 µl of fresh growth medium and 10 µl of sample, which was diluted in 10% of growth medium in advance. All samples were tested in triplicate including the medium blank and solvent blank. Tert-butylhydroquinone (tbhq) was used as the positive control and the solvent used was methanol. After another 16 h of exposure in the CO 2 incubator, the medium in the white plates was removed, and washed with PBS. Twenty-five microlitres of Passive Lysis Buffer (PLB) was then added and the plates were shaken for 15 min before luciferase analysis. Gen5 micro-plate reader with a delivery pump was used for the measurement and the luminescence was read directly by well after luciferase buffer (ph=7.8) was added. For the cytotoxicity test, after 16 h exposure the medium was replaced by 100 µl of clear fresh medium (without phenol red) and 20 µl of MTS solution (Promega, #G3580). Absorbance at 492 nm was read after 2 h of incubation. S2-I. CaCo2 NRU assay The Caco2-NRU (neutral red uptake) test is a measure of non-specific cytotoxicity. It is used to determine if the test sample impacts the viability of Caco2 (human epithelial colorectal adenocarcinoma) cells after 21h of exposure. Cell viability at the end of the incubation period is determined by adding neutral red, a dye that stains only live cells, and measuring the amount of dye taken up by the cell culture. The method was adapted from Konsoula and Barile (2005). In brief, Caco2 cells were grown in DMEM/F12 with phenol red supplemented with 8% FBS and 100 μm non-essential amino acids. For the assay, cells were seeded at 20,000 cells/well in 100 μl assay medium (DMEM/F12 medium without phenol red supplemented with 5% stripped FBS (CD-FBS) and 100 μm non-essential amino acids) in 96-well plates and incubated for approximately 24h at 37ºC 5% CO 2. When the cells reached confluence (usually about 24h), the medium was removed and replaced by 150 μl of fresh assay medium and 50 μl of assay medium containing the model compound or water extract to be tested (final methanol concentration in the assay plate 0.1%). After 21 h of incubation at 37º C 5% CO 2, the medium was removed, the wells rinsed with 150 μl PBS, and the PBS was replaced by 150 μl of neutral red media (50 μg/ml neutral red in assay media, made fresh). After a further 3h incubation at 37ºC 5% CO 2, the medium was aspirated and replaced with 150 μl of neutral red desorbing fixative (1% acetic acid, 50% ethanol, in deionized water). The plate was placed on an orbital shaker at 600 rpm for 10 min at room temperature and absorbance was read in a plate absorbance reader (BMG FluoSTAR Omega) at 540 nm. Appendix VI p.51

257 Bioanalytical assessment of water quality Supporting Information S2-J. Human neuroblastoma (SK-N-SH) cytotoxicity Human neuroblastoma cells (SK-N-SH cells) were resuspended in white medium (DMEM/F12 without phenol red supplemented with 5% FBS, 1 non-essential amino acids and 2 mm Glutamax; Life Technologies, Vic, Australia) at cells/ml (determined using a Millipore Scepter Handheld Automated Cell Counter). Using a multi-channel pipette, 200 µl of cell suspension was added to every well (20,000 cells/well) of a standard flat bottom 96-well plate, and the plate was incubated for 24 h in a humidified 37ºC/5% CO 2 incubator. The medium was then removed by aspiration and replaced with 200 µl of fresh white media containing the test sample (maximum solvent concentration of 0.5%), and the plate incubated 21 h in a humidified 37ºC/5% CO 2 incubator. The media was then aspirated, the wells rinsed with 150 µl of PBS, the PBS aspirated, and 150 µl of neutral red media (50 µg/ml neutral red solution, prepared fresh) was added. The plate was then incubated a further 3 h in a humidified 37ºC/5% CO 2 incubator. At the end of the incubation, the medium was aspirated, the wells rinsed with 150 µl PBS, the PBS was aspirated and 150 µl of neutral red desorbing fixative (1% acetic acid, 50% ethanol, prepared in ultrapure water) was added. The plate was placed on an orbital shaker at 600 rpm for 10 min and the absorbance was read at 540 nm in a plate reader (BMG Fluostar Omega; BMG Labtech, Vic, Australia). DMSO was used as a reference compound, with an IC 10 and IC 50 of approximately 50 and 500 mm, respectively. Samples were deemed as "neurotoxic", when cytotoxicity exceeded IC 10 (determined from the DMSO standard curve). S2-K. THP1 cytokine assay The THP1 cytokine assay provides a measure of immunotoxicity. For this assay, we monitored interleukin 1β (IL1β). The assay was run in antagonist mode, by measuring the inhibition of the normal production of IL1β by THP1 cells exposed to E. coli lipopolysaccharide (LPS) after exposure to the sample for 24h. The methods were adapted from Baqui et al. (1998). In brief, THP1 cells were cultured in growth medium (DMEM/F12 medium with phenol red supplemented with 8% FBS and 100 μm nonessential amino acids). For the assay, cells were seeded at 200,000 cells/well in 200 μl of growth media (with 1 μg/ml LPS in antagonist mode) and 50 μl of assay medium containing the model compound or water extract to be tested (final methanol concentration in the assay plate 0.1%). After 24 h incubation at 37ºC 5% CO 2, cells were transferred to a V-bottom 96-well plate, centrifuged at 300 g for 5 min, and the supernatant was transferred to a fresh 96-well plate. IL1β concentration in the supernatant was assayed by ELISA (Human IL1β quantikine ELISA, RnD Systems), following the supplier s instruction. Appendix VI p.52

258 Bioanalytical assessment of water quality Supporting Information Section S3. Additional information on data evaluation The dose-metric of the concentration-effect curves is the relative enrichment factor REF, which is the combination of the enrichment of the extraction and the dilution in the bioassay (Eq. 1), thereby representing the enrichment (REF > 1) or dilution (REF < 1) of the original sample in each bioassay. The REF is expressed in the units of [L water sample /L bioassay ]. REF dilution factor bioassay enrichment factor SPE (1) The enrichment factor of the SPE enrichment factor SPE was calculated using Eq. 2 from the volume of extracted water to the volume of resulting extract (in solvent) enrichment factor SPE V water V extract The dilution factor of each bioassay was calculated using Eq. 3. volume of extract added to bioassay dilution factor bioassay total volume of bioassay (2) (3) Appendix VI p.53

259 Bioanalytical assessment of water quality S3-A. EC 10 (10% effect concentration) Supporting Information EC 10 values were reported for the cytotoxicity bioassays and for receptor-mediated effects and were obtained from a log-logistic fit of the concentration-effect curves (Figure 2A in the main article). The % effect was calculated with Eq. 4 %effect signal signal sample control signal max signal control (4) Adjustable parameters were the slope and the effect concentration causing 50% reduction of maximum effect, EC 50. %effect slope logec 50 logconcentration The EC 10, the effect concentration causing 10% reduction of cell viability, was derived from the EC 50 and the slope s (Eq. 6). logec 10 logec 50 1 (6) s log æ 1 æ9 æ In many cases, no full concentration-effect curves were obtained for the sample extracts. Partial concentration-effect curves can only be fitted if the slope is fixed at 1 or at the slope of the reference compound. Alternatively, because the lower portion of the log-logistic concentration effect curves is linear with respect to non-logarithmic concentrations, the EC 10 can also be derived from a linear concentration-effect curve with intercept zero up to 20% of maximum effect (Eq. 7, Figure 2C in the main article). %effect slope concentration (7) EC 10 10% slope The EC 10 values derived with the linear method agreed well with the log-logistic derivation and the final results of the samples were derived from the linear concentrationeffect curves, although the EC 10 values of the reference compounds were from the full log-logistic fit. S3-B. EC IR1.5 (effect concentration causing an induction ratio IR of 1.5) The EC IR1.5 was derived for all reporter gene assays where no maximum response could be obtained. By nature of the endpoint the IR approach applies to genotoxicity and most adaptive stress responses such as the oxidative stress response. In addition, a few of the endpoints assessed had no reference compounds, e.g., the FACTORIAL. For all endpoints where no reference compounds were tested, the EC IR1.5 was deduced. The IR is the ratio of the measured signal (e.g., absorbance, relative light units (RLU), relative fluorescence units (RFU)) to its control value (Eq. 9). An analogous equation can be used for the number of revertants in the Ames assay, hence called revertant ratio (RR). (5) (8) Appendix VI p.54

260 Bioanalytical assessment of water quality Supporting Information IR signal sample (9) signal control Concentration-effect (IR) curves would show the typical log-logistic form but the maximum is hard to establish due to cytotoxicity interference or it may not even exist (Figure 2B in the main article). Therefore only the linear portion of the concentrationeffect curves was evaluated up to an IR of 5 (Eq. 10, Figure 2D in the main article). IR = 1 slope concentration (10) The assessment endpoint is the concentration that induces an IR of 1.5 (EC IR1.5 ). The EC IR1.5 can be derived using the linear regression function with Eq. 11 (and analogously for the revertant ratio in the Ames test with Eq. 12). EC IR1.5 = 0.5 slope EC RR1.5 = 0.5 slope (12) The threshold of 1.5 was selected because (a) it is employed in several guideline documents, e.g., umuc genotoxicity assay, (b) it is very close to the limit of detection in many cases (control plus 3 standard deviations) (Escher et al., 2012), (c) it is an interpolation not an extrapolation such as the EC 50, and (d) it can be applied if the maximum of the dose-response curve is not known. The disadvantage of using IR is that depending on the bioassay, maximum response can be at IR of 2 up to over 100. If the maximum IR reaches 6, then the EC IR1.5 is equivalent to the EC 10, if the maximum ER is 2, the EC IR1.5 is equivalent to the EC 50, and for IRs that level off at 100 or more, the EC IR1.5 is often close to the limit of detection. For the 22 assays for which the maximum effect and EC 10 were derived, it was possible to calculate what % effect would be equivalent to IR 1.5 (Table S3). For 13 of these bioassays, the max IR fell between 3 and 15 allowing the EC 10 and the EC IR1.5 to be directly compared. For nine, the maximum IR was well above 15 up to 940 and in these cases the EC 10 would be inherently less responsive than the EC IR1.5. Table S3. Comparison of maximum IR with effect level at IR 1.5. # Laboratories Bioassay Maximum IR Effect level at IR BDS CALUX-PPARα 5 13% 10 BDS, CSIRO CALUX-PPARγ 20 3% 12 GU PPARγ GeneBLAzer 3 25% 15 UQ, RECETOX AhR-CAFLUX 13, 2 4%, 50% 16 RECETOX H4IIEluc 5 to 11 5 to 13 % 22 GU, CSIRO, BDS, IWW ER-CALUX 15, 15, 5, 15 3, 3, 11, 3% (11) Appendix VI p.55

261 Bioanalytical assessment of water quality Supporting Information # Laboratories Bioassay Maximum IR Effect level at IR UQ E-SCREEN 3 to 26 2 to 23% 24 Swiss, CSIRO, UA YES % 30 RECETOX herα-hela to 5 13 to 25% 31 HK MCF7-ERE 6 10% 35 UFL, USF, UCR, SCCWRP ER-GeneBLAzer 24, 27, 5 3, 3, 13% 37 GU, BDS, CSIRO AR-CALUX 10 to 60, 45, 20 1 to 60, 1, 3% 40 UA, CSIRO YAS 100, 54 1, 1% 41 UFL, USF, UCR, SCCWRP AR-GeneBLAzer 3 26% 43 RECETOX MDA-kb GU, BDS, CSIRO GR-CALUX 15 to 40, 15, 20 1 to 4, 4, 3% 47 UA GR Switchgear 15 4% 50 GU, UFL, USF, UCR, SCCWRP GR-GeneBLAzer 22, 25, 20, 50, 22 2, 3, 3, 1, 2% 53 UFL, USF, UCR, SCCWRP PR-GeneBLAzer 6, 9, 3, 5 10, 6, 25, 15% 54 GU, BDS, CSIRO PR-CALUX 50, 110, 940 1, 0.5, 0.05% 58 BDS, GU TR-CALUX 940, , 1% 59 UQ T-Screen 5 12% S3-C. EC SR0.2 (effect concentration causing a suppression ratio SR of 0.2) for all antagonistic effects and chaperon dissociation. A receptor-binding bioassay is run in antagonistic mode if the receptors are saturated or occupied with a constant concentration of an agonist (positive control). In an antagonistic mode experiment, varying concentrations of sample are added, while the concentration of the agonist is kept constant. If the signal of the agonist is suppressed the sample has an antagonistic effect (Figure S1). The suppression ratio SR is defined by Eq. 13. The analogous equation was used for endpoints that are based on chaperon dissociation (CD). SR 1 signal sample signal control signal agonist signal control Signal agonist refers to the signal (relative fluorescence/light units (RFU, RLU), etc.) measured in presence of the agonist (positive control), which is normally the highest signal obtained unless the agonist was not added at saturating concentrations and the sample also had an agonistic effect. If signal agonist >> signal control, Eq. 13 simplifies to Eq. 14. SR 1 signal sample signal agonist In most cases no full concentration-effect curves were obtained for antagonistic effects. Therefore, we used only the initial linear part of the concentration-effect curves (13) (14) Appendix VI p.56

262 Bioanalytical assessment of water quality Supporting Information up to a suppression ratio of 0.3 (Figure S1). The EC SR0.2 is calculated from a linear regression through the zero point (Eq. 15). The 20% suppression level (SR 0.2) was chosen to derive the EC SR0.2 (Eq. 16) because the variability is typically larger than in the agonist mode and the 10% suppression level (SR 0.1) is often not above the variability of the controls, which would produce false-positive results. SR = slope concentration (15) EC SR0.2 = 0.2 slope Analogously, an EC CD0.2 was defined for chaperone dissociation. EC CD slope (16) (17) signal agonist signal signal control log concentration (REF) control agonist SR SR 1 signal sample signal control signal agonist signal control EC SR0.2 log concentration (REF) Figure S1. Derivation of EC SR0.2. suppression ratio SR EC SR0.2 = 0.2 slope CA EC SR0.2 concentration (REF) SR = slope concentration Appendix VI p.57

263 Bioanalytical assessment of water quality Supporting Information Section S4. How robust were bioassays performed in different laboratories? A number of bioassays were performed in multiple laboratories. In the following sections only mean results per bioassay are reported. For bioassays that had some positive and some negative results in two or more laboratories, the reported mean was obtained as follows: (a) If no effects were observed until the highest REF tested in one laboratory but the maximum experimental REF used in that laboratory was lower than the REF in another laboratory, then the results from the laboratory with lower maximum enrichment was ignored. (b) If the maximum REF were similar but some laboratories reported effects, others not, then the data without observed effect was not used to calculate the mean if it was only one laboratory out of three or four. If the test was only performed by two laboratories, and one was >highest REF tested, the other one was not, then the positive data were used. The bioassays listed in Table S4 were performed multiple times and a repeated measures one-way ANOVA followed by the Bonferroni multiple comparison post-test was performed to assess if the results matched between the different laboratories and if it was legitimate to report mean values for each endpoint only (if only two laboratories were involved, then a paired t-test was used). We did not use ANOVA per se to quantify the distribution of the ten samples. Clearly, we cannot assume that these 10 samples follow a Gaussian distribution, and we did not target a true mean of all samples, but we can assume that if thousands of water samples of these types were tested they would follow a Gaussian distribution. Therefore a non-parametric test was not suitable for this analysis. ANOVA is suitable in this case as with the independent testing in two or more laboratories the circularity assumption is fulfilled. Table S4. Comparison of the bioassay results for the same bioassay performed in different laboratories. Bioassay Is there significant pairing? Photosynthesis inhibition Algae growth inhibition AhR- CAFLUX UQ, Swiss UQ, Swiss UQ, RECETOX Laboratory Test # Sample s compared (>LOD) Paired t-test Paired t-test Paired t-test P r2 (r for t-test) 4 yes yes yes Bonferroni post test Appendix VI p.58

264 Bioanalytical assessment of water quality Supporting Information ER-CALUX ER- GeneBLAzer GR- GeneBLAzer GR-CALUX GU, BDS, CSIRO, IWW UF, USF, UCR, SCCWRP UF, USF, UCR, SCCWRP BDS, CSIRO Microtox UQ (1+2) Swiss Repeated measures ANOVA Repeated measures ANOVA Repeated measures ANOVA Paired t-test Repeated measures ANOVA a LOD = limit of detection, b REF = relative enrichment factor. 3 yes CSIRO vs. BDS significantly different 4 yes yes <0.00 <LOD a All laboratories not significantly different; the non-detects were included in the analysis because there were too few detects 2 no GU used lower REF b (and results were below LOD), therefore only BDS and CSIRO compared. 8 yes All laboratories not significantly different Also, data were log-transformed before the test was performed to assure that small values had equal weight. We used this test to obtain P values that test the null hypothesis of the population row means being equal. Although the maximum amount of sample extract to be dosed was not prescribed, which lead to different laboratories testing different highest doses, we found generally good consistency between the results of the different laboratories. Four laboratories performed the ER-CALUX and their results paired up although the CSIRO vs. BDS results were significantly different but the two other datasets lay well in the middle and therefore all four were averaged. For the YES assay, two laboratories were below detection limits in all samples but the dataset of a third laboratory showed clear and differentiated results and high quality Appendix VI p.59

265 Bioanalytical assessment of water quality Supporting Information raw data. In this case therefore only the positive results of the third laboratory were used despite violation of the above rules. Working with a semi-standardized protocol was beneficial as the four laboratories that performed the ER-GeneBLAzer assay achieved consistent results despite the fact that the assay was newly established in all laboratories. All ER-GeneBLAzer results were averaged. The bioassays for androgenicity, e.g., the AR-CALUX and the YAS, as well as for the progesterone receptor, PR-CALUX, and for the thyroid receptor, TR-CALUX, did not the effect threshold of 10% at the highest REF in any of the laboratories where the test was applied. The AR-GeneBLAzer and the PR-GeneBLAzer were performed in four and three laboratories, respectively. In a few cases individual samples were just above detection limit but in each case they were below detection limit in all other laboratories and they were therefore assigned as non-detects. It must be noted that this study was limited by the amounts distributed to each laboratory. Therefore it was not possible to do more repetitions, which one might normally do with results close to the detection limit. The GR-GeneBLAzer assay was consistent between four laboratories showing positive results in the same two samples and with all other samples below the significance threshold of effect of 10%. The results were averaged. The GR-CALUX was one of the few assays where the different laboratories did not agree although the relative effect pattern was consistent. One laboratory tested much lower concentrations that the others and did not detect any effect, the two other laboratories showed two samples that were positive (MF and Eff2) but a third sample (Eff1) that was cytotoxic in one laboratory and inducing in another lab. The effects of the two positive samples differed more than in other bioassays and pairing could not be established. Therefore only the data set from the laboratory that reported highest activation and no cytotoxicity was reported in the final table. For reactive toxicity, we tested a large variety of Ames strains with slightly different properties and therefore were unable to narrow down specific patterns, although similar samples caused induction. IWW duplicated some of the tests but obtained no responses due to smaller REFs applied and these datasets were omitted as other laboratories had positive results with the same strains. For adaptive stress response pathways, the only assay performed in duplicate was the p53-calux, which was not responsive. Appendix VI p.60

266 Bioanalytical assessment of water quality Supporting Information Section S5. Initial screening of nuclear receptors and transcription factors The FACTORIAL bioassays were applied here for the first time to screen water samples. The raw water samples did not show any effects (data not shown), the responses discussed in this section relate to water samples after enrichment by SPE to a REF of 4. As no reference compounds were measured and the maximum response was not known, only induction ratios could be calculated from the raw response data. For more than 90% of the tested endpoints, the limit of detection (LOD; IR of control plus 3 times standard deviation) fell below an IR of 1.5 (Figure S2). A fixed threshold has the advantage that datasets of variable size can be compared, while the LOD is dependent on the number of datapoints from which it is derived. For example, in Figure S2 the LOD calculations for the nuclear receptors (NR) was based on 24 control data points while the LOD for the transcription factors (TF) was based on 48 datapoints. The latter yielded much lower variability and lower LODs. Therefore we opted to use the IR 1.5 as a threshold of effect for the FACTORIAL bioassays but also for all other bioassays where no % effect could be calculated Figure S2. Limit of detection (LOD) 1646 calculated from the induction ratio (IR) of control plus 3 times standard 1648 deviation for the 25 nuclear receptors 1.6 threshold IR (NR) and 48 transcription factors (TF) of the FACTORIAL bioassay All samples were screened with the FACTORIAL bioassays and the results are depicted in Figure S3. NR TF 1654 The highest induction was seen for the 1655 pregnane X receptor PXR both in the NR and TF assay and in all samples but the blank (H 2 O) (Figure S3). As expected the Limit of detection (LOD) : IR of control plus 3 times standard deviation estrogen receptor ER was activated but not the estrogen related receptors ERR and ERR in the NR assay and the estrogen response element ERE was activated in the TF assay (Figure S3). In the NR assay, the peroxisome proliferator activated receptor PPAR was active but with a lower IR around or below 2 in the samples Eff1, Eff2, MF. The glucocorticoid receptor responded weakly in the NR assay (IR of 1.4 at an REF of 4, i.e. just below the threshold of effect) but showed no response in the TF assay. The highest induction in the TF assay was observed for the arylhydrocarbon response element, which does not come as a surprise as a large number of chemicals activate this xenobiotic metabolism pathway. Activity measured in Effl1, Eff2 and MF Appendix VI p.61

267 Bioanalytical assessment of water quality Supporting Information disappeared after further treatment, and drinking water treatment marginally increased the effect. The next highest activity was caused by the response element associated with the PXR and this is consistent with the high activity in the NR assay. Third in activity was the antioxidant response element (ARE) that is activated through the Keap-Nrf2 pathway. Then came the response elements for ER (ERE), the retinoic acid receptor (RAR)-related orphan receptor (RORE) and response element for the PPAR (PPRE; IR 1.4 just below effect threshold). Nuclear receptors RORg PPARa HNF4a RXRb CAR LXRb THRa1 Nuclear receptors RORg PPARa PPARd1 VDR NURR1 10 HNF4a RXRb CAR LXRb IR 1 PXR ERRa IR PPARd1 VDR NURR THRa1 PXR ERRa 0.1 FXR FXR AR ERa LXRa AR RARg IR 1.5 RARg IR 1.5 ERa LXRa GAL4 RORb RXRa ERRg GAL4 RORb GR RARb RARa PPARg RXRa ERRg GR RARb RARa PPARg A PBREM C/EBP E2F GATA NRF1 samples Eff1 H 2 O B samples MF RO AO Myb GLI Ets RORE FoxO DR5 AP-2 IR1 VDRE HIF1a Pax6 BRE p53 PBREM Myb C/EBP E2F GATA NRF1 GLI Ets RORE FoxO DR5 AP-2 IR1 VDRE HIF1a Pax6 BRE p53 IR Sox Sp1 Myc 10 1 TGFb HNF6 TCF/b-cat E-Box PPRE NFI PXR GRE 0.1 IR 1.5 TA SREBP ERE HSE Oct-MLP DR4/LXR -MLP Sox Sp1 Myc SREBP IR Transcription factors CRE Ahr EGR NRF2/ARE AP-1 ISRE MRE STAT3 TAL NF-kB FoxA2 CMV Xbp1 Transcription factors TGFb HNF6 TCF/b-cat E-Box PPRE 10 NFI PXR IR 1.5 GRE AP-1 1 ISRE MRE STAT3 0.1 TAL NF-kB FoxA2 CMV Xbp1 CRE Ahr EGR NRF2/ARE ERE TA HSE Oct-MLP DR4/LXR -MLP Appendix VI p.62

268 Bioanalytical assessment of water quality Supporting Information Nuclear receptors RXRb RORg PPARa HNF4a CAR PPARd1 VDR NURR1 10 LXRb THRa1 Nuclear receptors RORg PPARa HNF4a RXRb CAR LXRb Nuclear receptors RORg PPARa IR 1 PXR ERRa PPARd1 VDR NURR1 10 HNF4a RXRb CAR LXRb IR THRa1 PXR ERRa IR PPARd1 VDR NURR THRa1 PXR ERRa 0.1 FXR FXR FXR AR ERa LXRa AR RARg IR 1.5 ERa LXRa AR RARg IR 1.5 GAL4 RORb RXRa ERRg GAL4 RORb GR RARb RARa PPARg RXRa ERRg RARg GAL4 IR 1.5 ERa LXRa RORb GR RARb RARa PPARg RXRa ERRg GR RARb RARa PPARg C Figure S3. Screening of 25 nuclear receptors and 48 transcription factors with the FACTORIAL bioassay. The induction ratios (IR) are depicted on the radar scale and the effect threshold of IR 1.5 is depicted with a green dashed circle. Activity profile of the induction ratios IR of nuclear receptors (left) and transcription factors (right) in HepG2 cells incubated for 24h with water samples at a REF of 4; (A) wastewater treatment plant PBREM C/EBP E2F GATA NRF1 Myb GLI samples Eff2 O 3 /BAC D samples RW DW E samples SW H 2 O Ets RORE Appendix VI p.63 FoxO DR5 AP-2 IR1 VDRE HIF1a Pax6 BRE p53 VDRE HIF1a Pax6 BRE p53 IR Sox Sp1 Myc Sp1 Myc Sox FoxO DR5 AP-2 IR1 PBREM Myb C/EBP E2F GATA NRF1 GLI Ets RORE VDRE HIF1a Pax6 BRE p53 TGFb HNF6 TCF/b-cat E-Box PPRE 10 NFI PXR IR 1.5 GRE AP-1 1 ISRE 0.1 TA SREBP ERE HSE Oct-MLP DR4/LXR -MLP SREBP SREBP IR Sp1 Myc Sox FoxO DR5 AP-2 IR1 PBREM Myb C/EBP E2F GATA NRF1 GLI Ets RORE Transcription factors CRE Ahr EGR NRF2/ARE MRE STAT3 TAL NF-kB FoxA2 CMV Xbp1 Transcription factors TGFb HNF6 TCF/b-cat E-Box PPRE 10 NFI PXR IR 1.5 GRE AP-1 1 ISRE MRE STAT3 0.1 TAL NF-kB FoxA2 CMV Xbp1 CRE Ahr EGR NRF2/ARE ERE TA HSE Oct-MLP DR4/LXR -MLP IR Transcription factors TGFb HNF6 TCF/b-cat E-Box PPRE 10 NFI PXR IR 1.5 GRE AP-1 1 ISRE MRE STAT3 0.1 TAL NF-kB FoxA2 CMV Xbp1 CRE Ahr EGR NRF2/ARE ERE TA HSE Oct-MLP DR4/LXR -MLP

269 Bioanalytical assessment of water quality Supporting Information effluent (Eff1) and the blank (milliq water) (B) microfiltration (MF), reverse osmosis (RO), advanced oxidation (AO), (C) Eff2 and ozone/biologically activated carbon (O 3 /BAC), (D) river water (RW) and drinking water (DW), (E) stormwater (SW) and laboratory blank (H 2 O). Appendix VI p.64

270 Bioanalytical assessment of water quality Supporting Information Section S6. Additional information on the bioassay results Details of the bioassay results are depicted in plots that are structured as shown in Figure S4. The EC values were plotted in an inverse scale so that the most toxic ECs were on the top and the least toxic ECs on the bottom (Figure S4-A). The samples were grouped according to the treatment processes (Figure S4-B). Sensitivity cannot be compared directly because of the two different endpoints (EC 10 and EC IR1.5 ) but these plots give an indication about the responsiveness and thus the suitability of the bioassays for water quality assessment. A EC IR1.5 or EC 10 (REF) sample needs to be 10x diluted to cause IR 1.5 or 10% of maximum effect native sample would cause IR 1.5 or 10% of maximum effect sample needs to be 10x enriched to cause IR 1.5 or 10% of maximum effect sample needs to be 100x enriched to cause IR 1.5 or 10% of maximum effect Eff1 MF RO AO Eff2 O 3 /BAC RW DW SW Figure S4. Presentation of bioassay results (EC = effect concentration, IR = induction ratio, REF = relative enrichment factor, for sample abbreviation see Table S1). S6-A. Induction of xenobiotic metabolism pathways H 2 O high effect low effect Eff1 MF RO AO Eff2 O 3 /BAC RW DW SW H 2 O The three bioassays for PXR and the six bioassays for AhR all showed positive responses in less treated samples and negative responses in recycled water and the blank (Figure S5). For the PXR (Figure S5-A), the FACTORIAL assays were most responsive with an EC IR1.5 below a REF of 1, i.e., this effect would be observable in the ambient water sample. The HG5LN-hPXR (Seimandi et al., 2005; Lemaire et al., 2006) reporter gene assay has been applied widely in water quality monitoring including for testing of wastewater, surface water and reclaimed water (Mahjoub et al., 2009; Creusot et al., 2010; Kinani et al., 2010; Mnif et al., 2010; Mnif et al., 2011). This assay was responsive to the same samples as the two PXR-FACTORIAL endpoints. B EC IR1.5 or EC 10 (REF) WRP using micro/nanofiltration followed by reverse osmosis and H 2 O 2 /UV WRP using ozonation and BAC Drinking Water Treatment Plant Stormwater umltrapure water Appendix VI p.65

271 Bioanalytical assessment of water quality Supporting Information Figure S5. Results of bioassays indicative of induction of xenobiotic metabolism pathways. The red symbols are EC 10 values the black symbols are EC IR1.5 values. The six AhR-related bioassays all showed consistent effect-patterns for the different samples and similar range of sensitivity although quantitative comparison is not possible because two bioassays yielded EC 10 and four EC IR1.5 values (Figure S5-B). The AhR-yeast had a remarkable dynamic range of EC over more than two orders of magnitude. A very responsive endpoint for induction of AhR was the CYP1a transcription in zebrafish embryos measured by RT-PCR. Only four samples (Eff1, MF, Eff2 and SW) were tested with RT-PCR but they all responded at low REF. The resulting EC IR1.5 ranged from 0.06 to 0.16 REF (i.e., responsive even in diluted samples). CAR was tested in two bioassays but only the CAR-yeast gave a response already at low REFs (Figure S5-C). For PPAR, only two of seven bioassays gave signals in the four most polluted samples (Figure S5-D). Both active PPAR assays related to PPARγ (PPARγ-transFACTORIAL and HELN-PPARγ). We detected no PPAR antagonism but samples were only tested up to a REF of 2. S6-B. Endocrine disruption All bioassays for estrogenicity were active in four to five samples. Blanks, RO and AO did not induce any estrogenic in vitro effects, and only two bioassays gave very low effects for samples DW and O 3 /BAC (Table S5, Figure S6). The results are consistent with a previous interlaboratory comparison study of five different bioassays for estrogenicity (GWRC, 2008), where the effects observed in the ER-CALUX, the YES, the E-SCREEN and the T47KBluc (not assessed here) were highly correlated. Leusch et al. (2010) also showed that the yeast-based assays have higher detection limits and therefore are not suitable for highly treated water but for the present applications they could still be used as the REF could be increased without cytotoxicity occurring and EC values obtained for MF and Eff2 were in the same range as for other endpoints. Again it must be cautioned that a quantitative comparison between EC 10 and EC IR1.5 is not possible but as Figure S6 demonstrates they are in the same range of relative sensitivity. Appendix VI p.66

272 Bioanalytical assessment of water quality Supporting Information EC IR1.5 or EC 10 (REF) Eff1 MF RO AO Eff2 O 3 /BAC RW DW SW H 2 O Figure S6. Results of bioassays indicative of estrogenicity. The red symbols are EC 10 values the black symbols are EC IR1.5 values. The anti-er test quantifies how the sample influences the effect of a constant concentration of estradiol that is typically spiked at concentrations that would elicit 50 to 80% of maximum effect. If the effect of the constant concentration of estradiol was suppressed and the sample was not cytotoxic, the sample can be considered to act as an anti-estrogen. No anti-estrogenic activity could be detected with the anit-er-calux in any of the samples. It should be noted that agonistic and antagonistic activity may be occurring simultaneously in these assays, masking any such individual response of these activities. The steroidogenesis pathway represents the biosynthesis route of steroid hormones from cholesterol via a battery of oxidative enzymes (Zhang et al., 2005). The H295R steroidogenesis assay is an OECD validated bioassay used to evaluate the endocrine disrupting effects by chemicals via non-receptor mediated mechanisms. As this pathway directly affects the hormone system function, we have classified it with the receptor-mediated hormonal effects rather than with xenobiotic metabolism. The steroidogenesis assay showed increased concentrations of estrone and estradiol, which could be associated with a decreased estradiol metabolism, as well as increase in progesterone and 17 -hydroxyprogesterone, which is most likely due to an inhibitory effect on CYP21A. A similar effect was observed when oil sand product water was assessed with the steroidogenesis assay: the raw water increased the estradiol levels and the effect disappeared after ozonation (He et al., 2010). In the same way that the effect of sample Eff2 went below the limit of detection when it was ozonated. The effect pattern of the sample Eff1 was similar to what has been observed when dosing with bisphenol A (Zhang et al., 2011). In relation to activation of the glucocorticoid receptor, GR-CALUX was the most responsive of these assays, followed by GR-transFACTORIAL (Figure S7). Their EC values were roughly ten times lower than the GR-Switchgear and GR-MDA-kb2 assays. The GR-GeneBLAzer was positive in MF, Eff2 and SW but the potency did not correlate well with the other assays. YES E-SCREEN ER-CALUX HELN_ERα HELN_ERß herα-hela-9903 MCF7-ERE ER-GeneBLAzer her yeast meder yeast ERE-cisFACTORIAL ERα-transFACTORIAL Steroidogenesis DART cyp19a1b Appendix VI p.67

273 Bioanalytical assessment of water quality Supporting Information EC IR1.5 or EC 10 (REF) 3 30 Eff1 MF RO >LOD >LOD >LOD AO Eff2 O 3 /BAC Figure S7. Results of bioassays indicative of glucocorticoid receptor (GR) activation. The red symbols are EC 10 values the black symbols are EC IR1.5 values. No assay indicative of modulation of the thyroid hormone system showed response to any of the water samples, even at high REF. The T-Screen is a cell proliferation assay where the cells only proliferate in the presence of thyroid hormones (Gutleb et al., 2005). This assay has been mainly applied for chemical dose-response tests and only few of the environmentally relevant chemicals showed activity. Accordingly it was not surprising that no effects were detected in the water samples. Many of the thyroid-active chemicals appear to need metabolic activation, and thus a combination with a system for metabolic activation may be beneficial (Taxvig et al., 2011). Inoue et al. (2009) observed activity lower than 10% of maximum effect at a REF of 100 with a two-hybrid yeast assay in surface waters; a greater response (>10%) was observed for a WWTP influent but these effects disappeared in the effluent (Inoue et al., 2011). In a different yeast-based assay, Li et al. (2011) did not observe any TR agonistic effect in water samples, and attributed anti-tr activity to phthalates (Li et al., 2010). The P19/A15 cell line was developed by transfecting an embryonic mouse carcinoma cell line with a plasmid carrying the retinoic acid response element (Novak et al., 2007). This cell line has not been tested with water samples prior to this study and did not show any effects with water samples but the water samples enhanced the effect of constant concentrations of 9-cis retinoic acid slightly (data not shown). This effect could be caused by mixture effect or by the organic micropollutants acting as solubilizer for the very lipophilic RA. S6-C. Reactive toxicity RW DW SW >LOD H 2 O GR-CALUX GR-transFACTORIAL GR-MDA-kb2 GR Switchgear GR-GeneBLAzer Three samples were active in the micronucleus assay, Eff2, RW and DW (Figure S8). This is a different profile as compared to the receptor-mediated modes of action, where the DW typically did not show any response and the activity in the DW sample is presumably due to disinfection by-products formed during chlorination. Both the SOS chromotest, based on induction of SOS repair in Escherichia coli (Quillardet et al., 1982), and the umuc assays with Salmonella typhimurium (Oda et al., 1985) are reporter gene assays, while the Ames test uses histidine-deficient S. Appendix VI p.68

274 Bioanalytical assessment of water quality Supporting Information typhimurium that can only grow if a reverse mutation occurs. The umuc and Ames tests utilize different strains of S. typhimurium, so the seven genotoxicity assays in Table 1 (main article) in fact only represents four different assay types. All umuc assays showed activity only at high REFs around 20 (Figure S8). The SOS chromotest gave very similar responses as the umuc. The Ames assay responded generally at lower REFs but suffered from high variability between the different bacterial strains (Figure S8). One problem was that several samples (e.g., RO, AO, SW and H 2 O) showed detectable yet inconsistent activity in the Ames assay, which was not apparent in the other genotoxicity assays. The dynamic range of these genotoxicity assays was relatively small and effects were only observed at relatively high enrichments (REF up to 20). EC IR1.5 (REF) Eff1 MF RO AO Eff2 O 3 /BAC RW DW Figure S8. Results of bioassays indicative of reactive modes of action. S6-D. Adaptive stress response SW H 2 O Ames TA98+ S9 Ames TAmix +S9 Ames TAmix -S9 Ames TA100 -S9 Ames TA98 -S9 umuc -S9 umuc +S9 umuc NM5004 umuc TA1535/pSK1002 SOS chromotest micronucleus assay These bioassays are discussed in more detail in the main manuscript. EC IR1.5 or EC DR0.2 (REF) Eff1 MF RO AO Eff2 O 3 /BAC RW DW SW H 2 O Jurkat E6-I AREc32 nrf2-calux NRF2/AREcisFACTORIAL Figure S9. Results of bioassays indicative of adaptive stress response pathways. Appendix VI p.69

275 Bioanalytical assessment of water quality Supporting Information Table S5. Summary of all EC values measured in all water samples (see Table S1 for definition of sample abbreviations). The errors represent the propagated standard error of the concentration-effect curve if only one laboratory performed the assay, and standard deviation of the mean results from different laboratories if the bioassay was performed by several laboratories (see also Section S4 for details on treatment of bioassays that were measured by multiple laboratories). # Class of Lab(s) Bioassay EC MOA a (REF) 1 XM 2 XM ATG PXRcisFACTORIAL ATG PXRtransFACTORIAL ECIR ECIR XM IRCM HG5LN PXR EC XM ATG CARtransFACTORIAL ECIR1.5 >4 Eff1 MF RO AO Eff2 O3/ BAC RW DW SW H2O 0.4 >4 > >4 0.6 >4 > > >12 > >4 >4 >4 >4 >4 >4 >4 >4 >4 5 XM CAPIM CAR-yeast ECIR XM ATG PPARαtransFACTORIAL ECIR1.5 >4 >4 >4 >4 >4 >4 >4 >4 >4 >4 7 XM ATG PPARγtransFACTORIAL ECIR >4 >4 1.3 >4 >4 2.3 >4 >4 8 XM IRCM HELN-PPARγ EC 10 > >12 > >12 >12 > >12 9 XM BDS CALUX-PPARα EC 10 >30 >30 >30 >30 >30 >30 >30 > >30 10 XM BDS, CALUX-PPARγ EC10 >30 >30 >30 >30 >30 >30 >30 >30 >30 >30 CSIRO 11 XM HK MCF7-PPAR ECIR1.5 n.t. n.t. >20 >20 n.t. n.t n.t. n.t. > XM GU PPARγ EC10 >2 >2 >2 >2 >2 >2 >2 >2 >2 >2 GeneBLAzer >12 Appendix VI p.70

276 Bioanalytical assessment of water quality Supporting Information # Class of Lab(s) Bioassay EC MOA a (REF) 13 XM GU Anti-PPARγ GeneBLAzer ECSR0.2 >2 14 XM CAPIM AhR-yeast ECIR XM UQ, RECET OX 16 XM RECET OX AhR-CAFLUX 24h Eff1 MF RO AO Eff2 O3/ BAC RW DW SW H2O >2 >1 >1 >2 >1 >1 >1 >2 > EC H4IIEluc EC > > >30 > > > >27 17 XM HK MCF7-DRE ECIR > >18 18 XM ATG AhRcisFACTORIAL ECIR >4 >4 0.1 > >4 19 XM UFZ DART cyp1a induction 20 Specific MOA 21 Specific MOA 22 Specific MOA: ER 23 Specific MOA: ER UQ, Swiss Algae photosynthesis inhibition UQ Acetylcholinesterase inhibition GU, CSIRO, BDS, IWW ECIR ER-CALUX EC10 b UQ E-SCREEN EC Specific Swiss, Yeast Estrogen EC10 c EC >20 > >20 EC >2 >2 > > >25 >30 > > >20 > >20 >2 >2 >2 > > >25 > > >30 > > > >30 >30 Appendix VI p.71

277 Bioanalytical assessment of water quality Supporting Information # Class of Lab(s) Bioassay EC MOA a (REF) MOA: ER 25 Specific MOA: ER 26 Specific MOA: ER 27 Specific MOA: ER 28 Specific MOA: ER 29 Specific MOA: ER 30 Specific MOA: ER 31 Specific MOA: ER 32 Specific MOA: ER 33 Specific MOA: Eff1 MF RO AO Eff2 O3/ BAC RW DW SW H2O CSIRO, Screen (YES) UA CAPIM her yeast ECIR1.5 > >30 > >30 >30 >30 >30 > CAPIM meder yeast ECIR IRCM HELN-ERα EC IRCM HELN-ER EC ATG EREcisFACTORIAL RECET OX herα-hela-9903 EC HK MCF7-ERE EC ATG ERαtransFACTORIAL >30 > > >12 > >12 > ECIR >4 > > >10 >27 > >20 > ECIR >4 > >4 >12 >30 >30 >30 >12 >12 >6 >12 >12 >12 >12 >6 >12 > NJU Steroidogenesis EC IR >20 > > >20 >4 >4 >4 > >27 >20 >20 >10 >20 >4 >4 >4 >4 > >20 Appendix VI p.72

278 Bioanalytical assessment of water quality Supporting Information # Class of Lab(s) Bioassay EC MOA a (REF) ER 34 Specific MOA: ER 35 Specific MOA: ER 36 Specific MOA: ER 37 Specific MOA: AR 38 Specific MOA: AR 39 Specific MOA: AR 40 Specific MOA: AR 41 Specific MOA: AR UFZ DART cyp19a1b (aromatase) UF, USF, UCR, SCCWR P CSIRO, GU Eff1 MF RO AO Eff2 O3/ BAC RW DW SW H2O ECIR1.5 >1.2 > > ER-GeneBLAzer EC10 b >20 > >20 >20 >20 >20 >20 Anti-ER-CALUX EC SR0.2 >8 >8 >15 >15 >8 >15 >15 >15 >8 >15 GU, AR-CALUX EC 10 >30 >30 >30 >30 >30 >30 >30 >30 >30 >30 BDS, CSIRO IRCM HELN-AR EC10 >6 >6 >12 >12 >6 >12 >12 >12 >6 >12 HK MCF7-ARE ECIR1.5 >10 UA, CSIRO UF, USF, UCR, SCCWR Yeast Androgen Screen (YAS) EC10 >30 AR-GeneBLAzer EC10 >10 >10 >20 >20 >10 >20 >20 >20 >10 >20 >30 >30 >30 >30 >30 >30 >30 >30 >30 >10 >20 >20 >10 >20 >20 >20 >10 >20 - Appendix VI p.73

279 Bioanalytical assessment of water quality Supporting Information # Class of Lab(s) Bioassay EC MOA a (REF) 42 Specific MOA: AR 43 Specific MOA: AR/GR 44 Specific MOA: AR/GR 45 Specific MOA: AR 46 Specific MOA: GR 47 Specific MOA: GR 48 Specific MOA: GR 49 Specific MOA: GR 50 Specific MOA: GR P ATG ARtransFACTORIAL RECET OX RECET OX CSIRO, GU ECIR1.5 >4 MDA-kb2 EC Eff1 MF RO AO Eff2 O3/ BAC RW DW SW H2O >4 >4 >4 >4 >4 >4 >4 >4 >4 > >27 >27 >27 >13 >27 Anti-MDA-kb2 ECSR0.2 >13 >13 >30 >30 >13 > > Anti-AR-CALUX EC SR >15 > > GU, >30 >20 GR-CALUX EC 10 d >30 > BDS, CSIRO UA GR Switchgear EC >20 > ATG GRtransFACTORIAL RECET OX GU, UF, USF, UCR, ECIR >30 > >15 >30 >30 >30 >30 >20 >20 >10 > >4 >4 1.4 >4 >4 >4 >4 >4 GR-MDA-kb2 (AR EC10 > >27 - > suppressed with Flutamide) GR-GeneBLAzer EC 10 b > >20 >20 >10 >20 >20 >20 >10 > Appendix VI p.74

280 Bioanalytical assessment of water quality Supporting Information # Class of Lab(s) Bioassay EC MOA a (REF) 51 Specific MOA: GR 52 Specific MOA: GR 53 Specific MOA: PR 54 Specific MOA: PR 55 Specific MOA: PR 56 Specific MOA: PR 57 Specific MOA: PR 58 Specific MOA: TR SCCWR P GU Anti-GR- GeneBLAzer ECSR0.2 >2 GU Anti-GR-CALUX EC SR0.2 >2 Eff1 MF RO AO Eff2 O3/ BAC RW DW SW H2O >2 >1 >1 >2 >1 >1 >1 >2 >1 >2 >1 >1 >2 >1 >1 >1 >2 >1 UF, PR-GeneBLAzer EC10 >10 >20 >20 >20 >20 >20 >20 >20 >10 >20 USF, UCR, SCCWR P GU, PR-CALUX EC10 >30 >30 >30 >30 >30 >30 >30 >30 >30 >30 BDS, CSIRO GU Anti-PR-CALUX ECSR0.2 >2 >2 >1 >1 >2 >1 >1 >1 >2 >1 NJU Steroidogenesis, ECIR >10 > >10 >10 >10 >10 >10 induction of progesterone NJU Steroidogenesis, ECIR >10 > >10 >10 >10 >10 >10 induction of 17α OH-progesterone BDS, TR-CALUX EC 10 >30 >30 >30 >30 >30 >30 >30 >30 >30 >30 GU Appendix VI p.75

281 Bioanalytical assessment of water quality Supporting Information # Class of Lab(s) Bioassay EC MOA a (REF) 59 Specific MOA: TR 60 Specific MOA: TR 61 Specific MOA: TR UQ T-Screen EC10 ATG THRα1- transfactorial ECIR1.5 >4 Eff1 MF RO AO Eff2 O3/ RW DW SW H2O BAC >30 >30 >30 >30 >30 >30 >30 >30 >30 >30 >4 >4 >4 >4 >4 >4 >4 >4 >4 IRCM HELN-TR EC10 >6 >6 >12 >12 >6 >12 >12 >12 >6 >12 62 Repro HK MCF7-RARE ECIR1.5 >10 63 Repro UQ P19/A15 ECIR1.5 >30 64 Repro ATG ROR transfactorial ECIR1.5 >4 >10 >20 >20 >20 >20 >20 >20 >20 >20 >30 >30 > >30 >30 >30 >30 > >4 >4 >4 >4 >4 >4 >4 >4 >4 65 Repro CAPIM hrar-yeast Assay ECIR >30 > >30 >30 >30 66 Reactive MOA 67 Reactive MOA 68 Reactive MOA 69 Reactive MOA 70 Reactive MOA RCEES, UQ umuc TA1535/pSK1002 UQ umuc TA1535/pSK1002 +S9 ECIR1.5 b ECIR RCEES umuc NM5004 ECIR RECET OX UA, IWW SOS chromotest ECIR > >30 > > >30 > >27 > >30 >30 >30 >30 >30 >30 >30 >30 >30 >30 >30 >30 >30 > >30 >30 >27 >27 >27 >13 >27 Ames TA98 -S9 ECRR1.5 e >30 > > >30 71 Reactive UA, Ames TA98+ S9 ECRR1.5 e > Appendix VI p.76

282 Bioanalytical assessment of water quality Supporting Information # Class of Lab(s) Bioassay EC MOA a (REF) MOA IWW 72 Reactive MOA 73 Reactive MOA 74 Reactive MOA 75 Reactive MOA 76 Reactive MOA 77 Reactive MOA 78 ASR UA, Ames TAmix -S9 ECRR >20 IWW UA, IWW UQ Ames TA100 -S9 ECRR1.5 e AWQC Micronucleus ECRR1.5 e assay CSIRO ROS formation in RTG2 cells Eff1 MF RO AO Eff2 O3/ BAC RW DW SW H2O > >30 > >30 >30 Ames TAmix +S9 ECRR1.5 e > > >30 >30 UQ Protein damage E.coli GSH+/- ATG HSEcisFACTORIAL > > >20 >30 > > >20 >30 ECRR >30 > >30 ECIR1.5 >30 ECIR1.5 >4 79 ASR UFZ hspb11 induction in DART after 120h 80 ASR ATG HIF-1acisFACTORIAL ECIR1.5 >4 81 ASR UA Hypoxia- ECIR1.5 >10 Switchgear 82 ASR ATG NF BcisFACTORIAL ECIR1.5 >4 83 ASR UQ NF B-Geneblazer ECIR1.5 > ± ASR BDS NF B-CALUX ECIR1.5 >30 >30 > >30 >30 >30 >30 >30 >30 >30 >30 >30 >4 >4 >4 >4 >4 >4 >4 >4 >4 ECIR1.5 >1.2 > > >2.2 - >4 >4 >4 >4 >4 >4 >4 >4 >4 >10 >20 >20 >10 >20 >20 >20 >10 >20 >4 >4 >4 >4 >4 >4 >4 >4 >4 >20 > ±2.2 >20 >30 >30 >20 >20 >20 >20 >30 >30 >30 >30 >30 >30 >30 >30 >30 Appendix VI p.77

283 Bioanalytical assessment of water quality Supporting Information # Class of Lab(s) Bioassay EC MOA a (REF) 85 ASR GU Jurkat E6.1 I B ECCD Eff1 MF RO AO Eff2 O3/ BAC RW DW SW H2O 1.4 >2 >2 1.6 >2 > > >30 86 ASR UQ AREc32 ECIR1.5 f >30 > ASR UA Nrf2-keap ECIR1.5 >10 >10 >20 >20 >10 >20 >20 >20 >10 >20 88 ASR ATG Nrf2/AREcisFACTORIAL ECIR >4 > > >4 89 ASR BDS Nrf2-CALUX ECIR > >30 90 ASR ATG p53- ECIR1.5 >4 >4 >4 >4 >4 >4 >4 >4 >4 >4 cisfactorial 91 ASR BDS, p53-calux EC IR1.5 >30 >30 >30 >30 >30 >30 >30 >30 >30 >30 IWW 92 ASR BDS p53-calux +S9 ECIR1.5 >30 >30 >30 >30 >30 >30 >30 >30 >30 >30 93 ASR UF p53-geneblazer ECIR1.5 >10 >10 >20 >20 >10 >20 >20 >20 >10 >20 94 CT UQ AREc32 cell EC >30 >30 > >30 >30 >30 >30 >30 viability 95 CT GU Caco 2 NRU EC >20 > >20 >20 >20 >20 >10 96 CT CSIRO RTG2 MTT EC10 >30 >30 >30 > >30 >30 >30 >30 > CT UFZ DART 48h EC10 >10 >10 >10 > >30 >30 > >30 lethality 98 CT UFZ DART 120h EC >10 > >30 >30 > >30 sublethal 99 CT GU SK-N-SH EC10 >1 >1 >2 >2 >1 >2 >2 >2 >2 >2 cytotoxicity 100 CT GU THP1 cytokine EC10 >1 >1 >2 >2 >1 >2 >2 >2 >2 >2 101 CT UQ algae growth EC > >20 > >20 inhibition Appendix VI p.78

284 Bioanalytical assessment of water quality Supporting Information # Class of Lab(s) Bioassay EC MOA a (REF) 102 CT UQ, Swiss Vibrio fischeri (Microtox) 103 CT RCEES Photobacterium phosphoreum T3 Eff1 MF RO AO Eff2 O3/ BAC RW DW SW H2O EC10 b,g EC # refers to the number in the heatmap. a MOA= mode of action, XM = xenobiotic metabolism, Repro = reproductive and developmental effects, ASR = adaptive stress response, CT = cytotoxicity. b Bioassays that were performed by several laboratories and the error denotes the standard deviation of the mean of different laboratories results; c only CSIRO results; d only BDS; e only UA, f previous published (Escher et al., 2013). g Previously published (Tang et al., 2013). Appendix VI p.79

285 Bioanalytical assessment of water quality Supporting Information Section S7. Monitoring treatment efficacy In this section we discuss the bioassays in the light of their suitability to serve as process monitoring tools. Of course one cannot say a priori that a bioassay is good or sensitive if it still measures an effect in treated waters. Effects can disappear if all chemicals that are responsive in this endpoint are well removed in the particular treatment process. The dynamic range between the effect of the product water and the blank is decisive for the suitability of an assay for assessing treatment efficacy (provided that reproducibility, repeatability and sensitivity have been already established with reference chemicals). S7-A. Advanced water treatment plant using reverse osmosis The investigated water reclamation plant (WRP) uses microfiltration followed by reverse osmosis and finished with advanced oxidation. The micropollutant flow in this plant has been characterized in detail in previous work by both chemical and bioanalytical tools (Escher et al., 2011; Macova et al., 2011). In the present study, we selected only four sampling points before and after critical treatment steps, the WRP inflow (WWTP effluent, sample Eff1), after microfiltration (sample MF), after reverse osmosis (sample RO) and after advanced oxidation combining hydrogen peroxide and UV irradiation (sample AO). Effects were detected in Eff1 in 51 of 101 bioassays (Figure S10, red symbols and line, excluding the bacterial cytotoxicity assays). Subsequent treatment steps greatly reduced the effect burden caused by micropollutants. After MF (Figure, S10, blue symbols and line) 52 bioassays tested positive (not exactly the same ones), but RO decreased the number of positives sharply to 11. After AO, only three bioassays tested positive and these also tested positive in the ultrapure water blank. In 12 bioassays, the effect after MF increased by more than 20%, i.e., more than the variability of the assay response. In 20 bioassays the effect remained constant ( 20%) and in 15 bioassays the effect decreased substantially already in the MF step. The five times increase in effect in the Ames TA mix S9 is presumably an artifact of the large variability of the results of this endpoint. To avoid biofouling, the MF membranes are chloraminated, which causes the formation of disinfection by-products that can cause effects in some of the bioassays for reactive modes of action (Neale et al., 2012). Appendix VI p.80

286 Bioanalytical assessment of water quality Supporting Information Figure S10 Bioanalytical fingerprint of the water from the WRP process using reverse osmosis. The red diamonds represent the Eff1, blue squares are MF, green triangles RO and yellow circles AO. The numbers refer to the bioassay numbers in Table 1 or Table S5. The effects were greatly reduced after reverse osmosis (Figure S10). In 31 of 52 bioassays the effect disappeared to below detection limit and in most bioassays the effective response was reduced by an order of magnitude. There was no preferred type or group of effects removed. The bioassays with high variability, e.g., the Ames assay, seem unsuitable for reliable assessment. The bioassays that showed reduction of effect but are sufficiently sensitive to respond after RO, are best suited as indicator bioassays. These include algae growth inhibition, the xenobiotic metabolism indicators, AhR-CAFLUX, H4IIEluc and MCF7-DRE. Of specific receptormediated modes of action, MDA-kb2 and herα-hela-9903 were able to show the dynamics of treatment. In the group of adaptive stress responses, the AREc32 and Nrf2-CALUX showed a distinct reduction pattern but were still above the LOD in RO water and are thus suitable as sensitive screening tool for process control. S7-B. Water reclamation plant using ozonation and biologically activated carbon filtration The second investigated WRP produces recycled water from secondary treated wastewater plant effluent using ozonation and activated carbon filtration (van Leeuwen et al., 2003). The WRP has a capacity of 10 ML d -1 and provides water to industry for non-potable uses. Whilst the plant Appendix VI p.81

287 Bioanalytical assessment of water quality Supporting Information provides water for non-potable applications, it has been designed to meet drinking water standards. The treatment process incorporates biological denitrification, pre-ozonation, coagulation/ flocculation/dissolved air flotation-sand filtration (DAFF), ozonation, biological activated carbon treatment and ozone disinfection. The removal efficiency of micropollutants has been analysed in detail in a series of studies that combined chemical analysis with bioanalytical tools (Macova et al., 2010; Reungoat et al., 2010; Reungoat et al., 2011; Reungoat et al., 2012a; Reungoat et al., 2012b). In the present study, two points in the treatment train were targeted: the WRP influent (secondary treated effluent, Eff2) and the product water after ozonation and biological activated carbon treatment (O 3 /BAC) /EC WWTP Eff2 Ozonation Biological activated carbon filtration O 3 /BAC Figure S11. Bioanalytical fingerprint of the water treated with ozonation and biological activated carbon. As is shown in Figure S11, 58 bioassays were above detection limit in the Eff2, similar to what was found with Eff1. The treatment reduced the number of responses to 11 and the effects in these positive bioassays were also greatly reduced (Figure S12). As was the case for the other facility, the bioassays that still showed an effect in the treated water are suitable as indicator bioassays to benchmark treatment efficiency. Appendix VI p.82

288 Bioanalytical assessment of water quality Supporting Information Reduction of effect 100% 80% 60% 40% 20% 0% ER-CALUX AhR-yeast MCF7DRE AREc32 PXR-cisFACTORIAL PXR-transFACTORIAL HG5LN PXR Ames TAmix +S9 CAR-yeast V. fischeri (Microtox) P. phosphoreum Figure S12. Percent treatment efficiency in the bioassays that did not fall below limit of detection (LOD) after treatment. S7-C. Drinking water treatment plant For comparison, we assessed treatment in a drinking water (DW) treatment plant. This plant has also been evaluated previously and applies coagulation and filtration followed by chlorination and finishing with chloramination (Macova et al., 2011; Neale et al., 2012). Here, only the feed water and the final drinking water were evaluated. The feed water is drawn from a river (RW) and the levels of micropollutants and effects (Figure S13) were low (Tang et al., 2013). In RW and DW, 25 and 22 of 101 bioassays were positive but only 17 positive bioassays in DW were identical to those positive in the RW, for the remaining positives different biological endpoints were triggered in RW and DW. The effects in the E-SCREEN, the AhR-CAFLUX and the MCF7-DRE remained the same or were reduced indicating that chlorination degraded or did not change existing micropollutants but did not produce specifically acting compounds. However drinking water treatment with chlorination and chloramination increased the non-specific and reactive toxicity (Figure S13) due to the formation of disinfection by-products, which is consistent with previous findings and chemical analysis of formed disinfection by-products (Neale et al., 2012). Appendix VI p.83

289 Bioanalytical assessment of water quality Supporting Information /EC Brisbane River Coagulation RW Chlorination Chloramination DW Figure S13. Bioanalytical fingerprint of the drinking water treatment. Of the bioassays that increased in the toxicity, only one represents a specific mode of action, the herα-hela As expected, the majority of these positive assays targeted xenobiotic metabolism, reactive modes of action and adaptive stress responses. Increase was most pronounced in the reactive modes of action (Ames TA98+ and S9, Ames TA100 -S9, umuc NM5004 and micronucleus assay). There was a detectable but small increase by up to a factor of 2 for the bioassays indicative of xenobiotic metabolism, with a preference for the PXR (HG5LN PXR, PXR-transFACTORIAL, PXR-cisFACTORIAL). The responses in all three bioassays for the oxidative stress response (Nrf2-CALUX, Nrf2/ARE-cisFACTORIAL and AREc32) increased by a factor of 2.4 to 4.2. References Appendix VI p.84