Characterizing the Influence of Metabolism on the Halogenated

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Characterization of Natural and Affected Environments

Characterizing the Influence of Metabolism on the Halogenated Organic Contaminant Biomagnification in Two Artificial Food Chains Using Compound- and Enantiomer-Specific Stable Carbon Isotope Analysis Bin Tang, Xiaojun Luo, Chen-Chen Huang, Zi-He Ren, Yan-Hong Zeng, and Bi-Xian Xian Mai Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b03922 • Publication Date (Web): 30 Aug 2018 Downloaded from http://pubs.acs.org on August 31, 2018

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Environmental Science & Technology

Characterizing the Influence of Metabolism on the Halogenated Organic Contaminant Biomagnification in Two Artificial Food Chains Using Compound- and Enantiomer-Specific Stable Carbon Isotope Analysis Bin Tang †, ‡, Xiao-Jun Luo*,†, Chen-Chen Huang†, ‡, Zi-He Ren†, ‡, Yan-Hong Zeng †, Bi-Xian Mai †



State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of

Environmental Resources Utilization and Protection, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, 510640, P. R. China ‡

University of Chinese Academy of Sciences, Beijing, 100049, P. R. China

* Corresponding author Phone: +86-20-85297622; Fax: 86-20-85290706; E-mail address: [email protected].

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ABSTRACT

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Two artificial food chains, food–tiger barb (TB)–oscar fish (OF) and food–TB

3

–redtail catfish (RF), were established in laboratory. The species-specific

4

biotransformation of ortho, para'-dichlorodiphenyltrichloroethane (o,p’-DDT), twelve

5

polychlorinated biphenyl, and five polybrominated diphenyl ether congeners were

6

characterized by measuring the compound- and enantiomer-specific stable carbon

7

isotope composition (δ13C), enantiomeric fraction (EF) of the chiral chemicals, and

8

metabolites in the fish. Compound- and enantiomer-specific biotransformations were

9

revealed by the alteration of δ13C and EF in both the predator fish species. Significant

10

correlations between the carbon stable isotope signatures and the depuration rates (kd)

11

and biomagnification factors (BMF) were observed. Chemicals that exhibited changes

12

in δ13C during the experiment have higher kd and lower BMF values than those with

13

unchanged δ13C. Specifically, the difference between the predicted BMF based on the

14

log Kow and the measured BMF, ∆BMF, was significantly positively and linearly

15

correlated to the change in the δ13C (expressed by ∆δ13C/δ13Cinitial, the percentage of

16

∆δ13C: δ13Cending-δ13Cinitial to the initial δ13Cinitial) in both the food chains. These results

17

indicated that the impact of metabolism on the bioaccumulation potential of organic

18

contaminants can be predicted by the stable carbon isotope fractionation of chemicals

19

in the fish.

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INTRODUCTION Organisms can be exposed to organic contaminants as a result of various human

22 23

activities.1 A certain chemical in an organism can achieve a level that exceeds that

24

present in the respiratory medium (e.g., water for a fish or air for a mammal), the diet,

25

or both. 1-3 This phenomenon is variously referred to as bioconcentration,

26

biomagnification, and bioaccumulation, which are normally used as the assessment

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end points during risk assessment of chemicals in aquatic organisms.2 Of particular

28

concern are contaminants that are conserved as they pass from organism to organism

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in a food chain or food web, possibly resulting in progressively higher concentrations

30

at higher trophic levels.4 Metabolism (specifically referred to as biotransformation) is

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an important phenomenon that should be appropriately recognized in chemical

32

evaluation schemes because biotransformation greatly modifies the internal

33

concentrations of organic chemicals for various biological species.2 However, no

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standard test method for measuring or calculating biotransformation rate exists to

35

date.

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During the last decades, compound-specific isotope analysis (CSIA) has

37

undergone rapid development as an effective technique to characterize (bio)chemical

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transformation reactions of organic contaminants.5, 6 The approach of CSIA is based

39

on the fact that bonds formed by heavy isotopes (e.g., 13C) are cleaved at a slower rate

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than bonds between lighter isotopes (e.g.,

41

heavier isotopes in the residual phase where transformation take place.5, 7, 8 Moreover,

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the extent of the isotope fractionation can serve as an indicator for the extent of the

12

C),5 thus leading to an enrichment of

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biotransformation process. CSIA has been applied to differentiate transformation mechanisms of simpler

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contaminants

dibromoethane,14 and chlordecone.15 However, applications and concepts of CSIA for

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persistent organic pollutants (POPs) are still in the early stages,

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data

49

hexachlorocyclohexanes,21,

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polybrominated diphenyl ethers (PBDEs).19, 25, 26 Additionally, most of these studies

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are related to microbial or chemical degradation; however, our recent studies have

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demonstrated the possibility for using CSIA to trace the biotransformation and trophic

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dynamics of PCBs and PBDEs in fish. 8, 18-20

e.g., 22

for

chlorinated

MTBE,13

46

available,

as

ethenes,10-12

organic

are

such

BTEX,9

45

polychlorinated

polychlorinated

6

and only scattered

biphenyls

(PCBs),16-20

dibenzo-p-dioxins,23,

24

and

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In recent years, enantiomer-specific isotope analysis (ESIA), the combination of

55

carbon isotope fractionation studies with enantiomeric fractionation, has become a

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promising new approach that could provide more information on the uptake, binding

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and catalysis upon stereoselective biodegradation of environmental organic

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contaminants.6, 19, 27 The stereoselective biodegradation of α-hexachlorocyclohexane,

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galaxolide, phenoxy acids, and phenoxy alkanoic methyl herbicides has been

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investigated by using ESIA.6 Our recent study has shown that different biochemical

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enzymatic reaction mechanisms might exist for individual PCB congeners and

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atropisomers of chiral PCBs;19 additionally, species-specific debromination of PBDEs

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was observed among different fish species based on the results of CSIA.8

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PCBs, PBDEs, and dichlorodiphenyltrichloroethane (DDT) are three typical

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persistent, bioaccumulative, and toxic halogenated organic contaminants, and thus

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have been regulated by the Stockholm Convention on POPs. Despite their persistence

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in the environment, PCBs, PBDEs and DDTs can undergo species-specific

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biotransformations in the biota, including fish, and stereoselective biotransformations

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of o,p’-DDT and chiral PCBs have been observed.19, 28

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In the present study, two artificial food chains were established in the laboratory.

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Two predatory species, the oscar fish (Astronotus ocellatus; OF) and the redtail

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catfish (Phractocephalus hemiliopterus; RF), were fed with tiger barbs (Barbus

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tetrazona; TB) that had been fed with food spiked with certain PCB and PBDE

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congeners and o,p’-DDT. After a 21-day exposure, a depuration period of 70 days was

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conducted during which the OF and RF were fed non-exposed TBs. TB and RF

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belong to the cyprinidae family and pimelodidae family, respectively, which are

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common freshwater fishes. However, the OF belongs to the cichlid family and is

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usually found in South America. Same food chains using these three fish species have

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been built to investigate the species-specific debromination of PBDEs in fish in our

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previous study.8

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The bioaccumulation parameters, such as assimilation efficiency (α), depuration

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rate (kd), and biomagnification factor (BMF), of chemicals in the two predatory fish

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species were calculated. The biotransformation of chemicals in the two predatory fish

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species

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atropisomeric/enantiomeric composition of chiral chemicals, and the stable carbon

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isotopic composition of each compound and atropisomer/enantiomer in the fish. The

was

characterized

by

measuring

metabolites

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chemicals,

the

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metabolites detected in the present study included hydroxylated (OH-PCBs) and

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methylsulfonyl (MeSO2-PCBs) PCBs, hydroxylated (OH-PBDEs) and debrominated

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products of PBDEs, and o,p’-DDD and o,p’-DDE for o,p’-DDT.

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The primary aims of the present study were to further investigate species-specific

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biotransformation of halogenated organic contaminants in fish by using CSIA and

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ESIA and to quantify the influence of chemical metabolism on the BMF based on

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laboratory CSIA and ESIA.

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MATERIALS AND METHODS

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Food Preparation and Fish Exposure. TB, RF, and OF with average initial

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lengths of 1.1 ± 0.2 cm (mean ± SD, similarly hereafter), 20.2 ± 0.4 cm, and 15.9 ±

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0.3 cm, respectively, and weights of 1.3 ± 0.4 g, 70.4 ± 3.3 g, and 79.3 ± 5.8 g,

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respectively, were purchased from an aquarium market in Guangzhou, China. Twelve

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PCB congeners (CB8, 18, 28, 45, 52, 91, 95, 101, 132, 136, 138, and 149), five PBDE

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congeners (BDE85, 99, 100, 153, and 154), and o,p'-DDT was spiked in food of the

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TB. The preparation of spiked food for TB was described previously 19, 29 and detailed

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in the supporting information (SI). The nominal concentrations of each PCB congener

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and o,p’-DDT in the spiked food were 24.0 µg g-1 dry weight (dw) and 40.0 µg g-1 dw

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for each PBDE congener.

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The TB, RF, and OF were kept in separate glass tanks. Each tank was filled with

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filtered dechlorinated tap water (maintained at 24°C–25°C, pH 6.5–7.5, 7.8–8.4 mg/L

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of dissolved oxygen, and with a 12-h light: 12-h dark cycle). Fish were first

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acclimated to a non-spiked diet in the laboratory for two weeks prior to exposure.

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Then, 500 TBs were exposed to artificially contaminant food (5 g food per day) in one

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tank for 5 days; the exposure was stopped and the TBs were collected and stored at

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−20 °C. After five batches of exposure, a total of 2,500 TBs was obtained. Of these,

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2240 were used for feeding RF (n = 28) and OF (n = 28), at a rate of 2 TBs/d for each

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predator fish. The remaining 260 TBs were pooled into three composite samples and

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kept stored at −20°C until further treatment.

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After 21 days of exposure (uptake period), the RF and OF were fed non-exposed

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TBs for 70 days (depuration period). Fish were sampled on days 14 and 21 of the

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uptake period, and on days 14, 28, 42, 56, and 70 of the depuration period. On each

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sampling day, four RFs and four OFs were randomly chosen from the exposed group,

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then fork length and weight were determined. Blood samples were obtained from the

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dorsal aorta using syringes, transferred into 5-mL Teflon tubes, and centrifuged at

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3000 rpm for 30 min to obtain the serum. Then, the fish was dissected, and fish liver

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and carcass (whole fish minus the gill and gut) were harvested. The sera and liver of

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each group of fish sampled on the same day were weighed and respectively pooled

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into one sample to ensure the detection of PCB and PBDE metabolites. Carcasses

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were analyzed separately for quantification, then combined correspondingly to form

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two samples prior to extraction for CSIA to obtain sufficient amounts of compounds

127

for CSIA. All samples were freeze-dried, ground into powder, weighed, and stored at

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−20 °C prior to being analyzed.

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Before exposure, five RFs, five OFs, and five composited TB samples (pooled

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from 20 individual fish) were used for background level analysis. Fourteen

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individuals from the RFs and OFs were designated as the control groups, respectively,

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in which fish were fed non-exposed TB throughout the experiment. On each sampling

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day, two RFs and two OFs were randomly collected from the control group and

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treated in the same way as those in the exposure group.

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Sample Preparation and Extraction. The liver and an aliquot of the carcass of

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RF, OF, and TB samples were used to quantify DDTs (o,p’-DDT, o,p’-DDD, and

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o,p’-DDE), PCB, PBDE, and MeSO2-PCB, and the sera were used to quantify DDTs,

138

PCBs, PBDEs, OH-PCBs, and OH-PBDEs. Details of the chemicals used and

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detected in the present study are given in the SI. The remainder of the carcasses of RF,

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OF, and TB was respectively combined into two samples and used for CSIA. The

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extraction and cleanup procedures used for fish tissues (liver and carcass) and sera

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were similar to those described previously,30, 31 with minor modifications, and detailed

143

in the SI.

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Approximately 30 g dw for each RF sample, and 40 g dw for each OF sample

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was used for stable carbon isotope analysis. The method for purifying the PCBs,

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PBDEs and o,p’-DDT in fish for CSIA was described previously,

147

modifications. The detailed descriptions of the extraction and purification procedures

148

are given in the SI. No significant isotope fractionation of the target compounds was

149

observed during the purification process.18, 32

18, 32

with minor

150

Instrumental Analysis. PCB and DDTs were determined by GC/MS (Agilent

151

7890A /5975C MSD, Agilent Technology, CA) with an electron impact ion source in a

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selective-ion monitoring (SIM) mode. GC separation was performed using a DB-5

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MS column (60 m × 0.25-mm i.d. × 0.25-µm film thickness). A Chirasil-Dex column

154

(25 m × 0.25-mm i.d. × 0.25-µm film thickness) was used to separate PCB 91, 95,

155

132, 136, and 149 atropisomers. A BGB-172 column (30 m × 0.25-mm i.d. × 0.18-µm

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film thickness) was used to separate o,p’-DDT and o,p’-DDD enantiomers, and a

157

Cyclosil-B column (30 m × 0.25-mm i.d. × 0.25-µm film thickness) was used to

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separate PCB 45 atropisomers. Enantiomeric compositions were expressed as

159

enantiomer fractions (EFs), which were defined as follows:

160

EF =

A A+B

161

where A and B respectively represent the areas of the (+)- and the

162

(-)-atropisomer/enantiomer peaks in the stereoselective chromatograph column, and

163

particularly, of the first eluting (E1) and the second-eluting (E2) atropisomers for

164

CB45, as the eluting orders for CB45 atropisomers were unknown. The oven

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temperature programs are given in detail in the SI.

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To quantify PBDEs, MeSO2-PCBs, OH-PCBs, and OH-PBDEs (OH-PCBs and

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OH-PBDEs, they were first derivatized to their methoxy analogues by diazomethane.

168

Instrumental analysis (details in SI) was performed by using GC/MS (Agilent 6890N

169

/5975B MSD; Agilent Technology, CA) with an electron capture negative ionization

170

ion source in a SIM mode. Separations were achieved with a DB-XLB capillary

171

column (30 m × 0.25-mm i.d. × 0.25-µm film thickness). Details of the GC conditions

172

and oven temperature programs are given in the SI.

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CSIA of PCBs, PBDEs, and o,p’-DDT were performed using a method similar to

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that used in our previous studies,19, 20 with minor modifications. The same columns

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were used for CSIA as those used for quantification analysis. Detailed descriptions of

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the CSIA procedures are given in the SI.

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Bioaccumulation Parameters. The bioaccumulation parameters, including α, kd,

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half-lives (t1/2), and BMFs of DDTs, PCB and PBDE congeners, and each

179

enantiomer/atropisomer were calculated according to equations described in our

180

previous study,19 and given in detail in the SI.

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Carbon Stable Isotope Calculations. The carbon isotope compositions were

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reported in δ notation in parts per thousand (‰), according to the following equation

183

(Eqn. (1)):

δ13C =

184

R sample − R standard R standard

×1000

(1),

185

where Rsample and Rstandard represent the 13C/12C ratios of the sample and the standard

186

(Vienna Pee Dee Belemnite, V-PDB), respectively.

187 188

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The isotope fractionation upon biodegradation can be quantified by a Rayleigh equation: R   δ 13C+1   Ct  ln  t  = ln  t 13  = ε C ln    R0   δ 0 C+1   C0 

(2), 13

C/12C) of the target

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where Rt and R0 are the isotopic compositions (ratio of

191

compounds at time t and 0 of the depuration period, εC is the carbon isotope

192

enrichment factor, and Ct and C0 are the concentrations of the substrate at time t and 0

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of the depuration period, respectively.

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Statistical Analysis. Statistical analyses were performed using the SPSS 21

195

software for Windows (SPSS). The statistical differences in the EFs of o,p’-DDT,

196

o,p’-DDD and chiral PCBs, and δ13C values of each compound between different

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sampling time points for each fish species were determined by one-way analysis of

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variance (ANOVA) with Tukey’s post-hoc test. An independent-samples t-test was

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used to examine the differences between the α, kd, t1/2, and εC for each chemical,

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enantiomer/atropisomer in RF and OF. The level of significance was set at p = 0.05

201

throughout the study.

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Background Levels and Quality Control. The background concentrations of

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PCBs (sum of 12 congeners), DDTs (o,p’-DDT, o,p’-DDD and o,p’-DDE) and PBDEs

204

(sum of 10 congeners) ranged, respectively, from 0.53 to 2.75 ng g-1 lipid weight (lw),

205

0.35 to 0.79 ng g-1 lw, and 0.47 to 0.55 ng g-1 lw in the TB; from 1.40 to 7.06 ng g-1,

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0.33 to 2.45 ng g-1 lw, and 0.16 to 1.59 ng g-1 lw in the RF; and from 0.97 to 3.32 ng

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g-1 lw, 0.79 to 1.30 ng g-1 lw, and 0.06 to 0.18 ng g-1 lw in the OF. No OH-PCBs,

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OH-PBDEs, and MeSO2-PCBs were detected in the background or control samples.

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The DDTs, PCBs and PBDEs levels in the background samples were two to three

210

orders of magnitudes lower than those in the exposed fish. Furthermore, a spiking test

211

confirmed that the influence of background DDTs, PCBs and PBDEs on the isotopic

212

composition of the target compounds in the exposure group was negligible.19 The

213

concentrations of PCB congeners and o,p’-DDT in the spiked food pellet homogenate

214

ranged from 20.04 ± 0.26 to 26.59 ± 0.40 µg g-1 dw, and from 32.84 ± 2.54 to 35.87 ±

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1.45 µg g-1 dw for PBDE (Figure S1), respectively, which were very close to the 12

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nominal concentrations. Trace amounts of o,p’-DDD (57.17 ± 6.43 ng g-1 dw) and

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o,p’-DDE (8.11 ± 1.66 ng g-1 dw) were also detected in the spiked food (Figure S1),

218

which were three to four orders of magnitude lower than that for o,p’-DDT. More

219

details regarding quality assurance and control are given in the SI.

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RESULTS AND DISCUSSION

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Bioaccumulation Parameters of Chemicals in Fish. The concentrations of

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PCB congeners in TBs ranged from 8870 ± 467 ng g-1 lw (CB8) to 12990 ± 675 ng g-1

223

lw (CB95); whilst much lower concentrations were found for o,p'-DDT (4019 ± 320

224

ng g-1 lw), which could be related to its readiness to be metabolized to form o,p’-DDD

225

(654 ± 87 ng g-1 lw) and o,p’-DDE (154 ± 11 ng g-1 lw) (Figure S1). Some chemicals

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that were not spiked in the food were detected in the TBs. These chemicals, including

227

BDE28 (95.4 ± 10.8 ng g-1 lw), BDE42/66 (456 ± 63 ng g-1 lw), BDE47 (18460 ±

228

2067 ng g-1 lw), BDE49 (95.0 ± 10.4 ng g-1 lw), and BDE101 (330 ± 30 ng g-1 lw)

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(Figure S1), were the result of debromination of BDE85, 99, and 153, which is just as

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we reported in our previous study,8, 19 The metabolic debromination resulted in the

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lower concentrations for BDE85 (750 ± 76.5 ng g-1 lw), BDE99 (4294 ± 308 ng g-1

232

lw), and BDE153 (7672 ± 157 ng g-1 lw) compared to BDE100 ( 13966 ± 1245 ng g-1

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lw) and BDE154 (13121 ± 1474 ng g-1 lw), which were resistant to debromination in

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the TB.8

235 236

The uptake and depuration curves of all compounds for muscles of RF and OF feeding on TB are presented in Figures S2 and S3. All chemicals reached their highest 13

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concentrations at the end of the uptake period, and the depuration curves commonly

238

follow first-order kinetics (Figures S2 and S3). Generally, the assimilation efficiencies

239

of all chemicals, with the exception of CB8, 18, and the debromination products

240

(BDE28, 47, 49, and 101), were higher in the muscles of RF than in those of OF

241

(Figure 1). The α of BDE49 and 101 in the OF even exceeded 100% (Figure 1). The α

242

of BDE42/66 in the OF was the same as that in the RF, since BDE66 can be

243

debrominated to BDE28 in the OF. 33 Except for o,p'-DDD, BDE85, 99, and 153, all

244

chemicals exhibited higher kd in the RF than in the OF (The kd of BDE85 in the OF

245

was not calculated due to the rapid metabolism of BDE85 in the OF) (Figure 1). The

246

higher α of debromination products along with the higher kd values of reactants of

247

debromination in the OF were due to the debromination metabolism of BDE

248

congeners in the OF, which has been demonstrated in our previous studies.8, 19, 33, 34

249

Oscar fish can debrominate BDE85, 99, and 153 to form BDE47, 49, 42/66, and 101

250

with a similar PBDE debromination mechanism as that in the TB and common carp.8,

251

19

Meanwhile, PBDEs were not debrominated in the RF.8

252

Although there are differences in α and kd, the calculated BMFs for all PCBs,

253

o,p'-DDT, BDE100 and 154 of the RF/TB feeding relation were similar to those in the

254

OF/TB feeding relation (Figure 1). The calculated BMFs based on RF/TB for

255

o,p'-DDE, o,p'-DDD, BDE85, 99 and 153 were higher than those based on OF/TB,

256

whereas the opposite result was found for BMFs of the five debromination products

257

(Figure 1). As mentioned above, debromination metabolism of PBDEs occurred in the

258

OF, but was absent in the RF. This resulted in an increase in the BMF for

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debromination products and a decrease in the BMF for reactants of debromination. As

260

for o,p'-DDE and o,p'-DDD, the assimilation efficiencies of these two metabolites

261

were much higher in the RF than in the OF (Figure 1), which could be due to the

262

higher metabolism capacity for o,p'-DDT in RF, thereby resulting in the higher BMFs

263

for o,p'-DDE and o,p'-DDD in this fish.

264

Enantiomer/Atropisomer

Composition

and

Enantiomer-specific

265

Bioaccumulation Signatures. Although the preferential biotransformation of

266

(-)-o,p’-DDT to (-)-o,p'-DDD was observed, no enantioselective biotransformation of

267

chiral PCBs was observed in the TB (Figure S4). During the whole experimental

268

period, the enantiomeric composition of o,p’-DDT in the RF and the OF were similar

269

to that in the TB (Figure S4), implying no enantioselective biotransformation. No

270

significant change for EF of o,p’-DDD was found in the RF during the whole

271

experiment, whereas selective metabolism of (+)-o,p’-DDD was observed in the OF

272

(Figure S4).

273

Regarding chiral PCBs, enantioselective biotransformation was not significant in

274

both the RF and OF during the exposure period for all chiral chemicals, except for

275

CB45 and 136 in the RF, (Figure S4). However, during the depuration period, a

276

preferential metabolism of E2-CB45, (+)-CB91, (-)-CB95, (-)-CB132, (+)-CB136,

277

and (+)-CB149 in the RF and a preferential metabolism of E2-CB45, (+)-CB91,

278

(-)-CB132, and (+)-CB136 in the OF were observed (Figure S4). CB95 and 149 were

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still racemic in the OF at the end of the experiment (Figure S4). In a previous study,

280

E2-CB45, (+)-CB91, and (−)-CB95 were preferentially metabolized by common

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carp,18, 19 which agrees with the results in the RF. Buckman et al.35 observed that

282

(+)-CB91 (E1-CB91) and (+)-CB136 were preferentially biotransformed by rainbow

283

trout (Oncorhynchus mykiss), whereas CB95 was racemic, which is consistent with

284

observations in the OF. These results suggest that the metabolism of chiral PCBs in

285

fish was species-specific.18, 19 Moreover, for each chiral PCB congener, the extent of

286

change in EF values was higher in the RF than in the OF, suggesting the higher

287

atropisomer-selective biotransformation ability in the RF, and its possibly higher

288

biotransformation capacity for chiral PCBs.

289

Of the eight chiral chemicals, only o,p'-DDD in the OF exhibited difference in α

290

between two enantiomers (t-test, p = 0.021, Figure 2). On the contrary, all chiral

291

chemicals with the exception of o,p'-DDD in the RF showed more or less differences

292

in a values between the two enantiomers (t-test, p = 0.541 for o,p'-DDD, and

293

0.001–0.032 for the others, Figure 2). This result indicates that the enantioselective

294

absorption occurring in the RF is completely different from that in the OF. Differences

295

in the kd values were observed between the two enantiomers for the six chiral PCBs

296

(t-test, p = 0.0001–0.022), but not for o,p'-DDD (t-test, p = 0.82) and o,p'-DDT (t-test,

297

p = 0.97) in the RF. As for the OF, enantiomer-specific kd was found in all chiral

298

chemicals (t-test, p = 0.001–0.028) except for CB95 (t-test, p = 0.696) and 149 (t-test,

299

p = 0.832) (Figure 2).

p=

300

Contributing to the enantiomer-specific assimilation efficiencies and depuration

301

rates, enantiomer-specific BMF was found in the two food chains (Figure 2). Kd plays

302

a more crucial role than α in determining the enantioselective accumulation in the

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predator fish. For example, (+)-CB95 exhibited much higher α than (-)-CB95 in the

304

RF. However, the BMF of (+)-CB95 was lower than that of (-)-CB95 (Figure 2). This

305

is because (-)-CB95 has lower kd than (+)-CB95. Only when the depuration rates were

306

same between two enantiomers, was EF determined by α, just as o,p'-DDD and

307

o,p'-DDT in the RF (Figure 2).

308

Biotransformation Revealed by Compound-Specific Stable Carbon Isotope

309

Signatures. Five MeSO2-CBs (4-MeSO2-CB91, 3'-MeSO2-CB95, 4'-MeSO2-CB95,

310

3'-MeSO2-CB132, and 4'-MeSO2-CB132) were detected in the livers of both RF and

311

OF throughout the experiment (Table S1). Meanwhile, seven OH-BDEs

312

(2'-OH-BDE28,

313

6-OH-BDE99, and 5'-OH-BDE99) were frequently detected in the serum (Table S1).

314

These

315

biotransformation of certain PCB and PBDE congeners in fish species.

6-OH-BDE47,

metabolites

provided

5-OH-BDE47,

important

but

4-OH-BDE49,

limited

4-OH-BDE42,

information

on

the

316

To get more insight into the biotransformation of chemicals in fish in the present

317

study, stable carbon isotopic compositions of the chemicals were determined (Figure

318

3). The stable carbon isotope compositions of all chemicals in the RF and OF were the

319

same as those in their prey (TB) during the exposure period (Figure 3). However, a

320

heavy isotope enrichment trend with depuration time was observed for all PCB

321

congeners except for CB28, 52, 101, and 138 in the RF, and CB28, 52, 101, 138 and

322

149 in the OF (Figure 3). CB28, 52, 101, and 138 are all indicator PCB congeners35

323

that showed no significant isotopic fractionation (one-way ANOVA, p = 0.086–0.415

324

for RF/TB, and p = 0.076–0.312 for OF/TB), indicating that no biotransformation

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occurred, or the biotransformation occurred with no detectable isotope fractionation.6,

326

18, 19

327

Of all the BDE congeners that could be measured for δ13C, only BDE153 in the

328

OF showed a heavy carbon isotope enrichment during the depuration period (Figure

329

3). This was attributed to the debromination of BDE153 in the OF, just as in the

330

common carp.18 The concentrations of BDE99 and BDE85 in the OF were too low to

331

measure δ13C due to debromination. No obvious isotope fractionation was observed

332

for BDE100 (one-way ANOVA, p = 0.121) and BDE154 (one-way ANOVA, p =

333

0.577) in the OF (Figure 3), as these two congeners are structurally resistant to

334

debromination in fish.33, 36 A slight increase in δ13C of BDE99 in the TB (−27.6 ±

335

0.2‰) compared with the spiked food (−28.5 ± 0.3‰) was also contributed by

336

debromination, which was similarly observed in our previous study.8 The

337

conservation of δ13C of BDE congeners in the RF during the whole experiment further

338

confirms that no or only minor debromination occurred in the RF.17 As a congener

339

accumulated through absorption from the prey and in vivo debromination of highly

340

brominated congeners occurred, the δ13C values of BDE 47 followed a decreasing

341

trend from the TB to the OF (one-way ANOVA, p < 0.001), but did not change from

342

the TB to the RF (one-way ANOVA, p = 0.361) (Figure 3). This result is consistent

343

with the hypothesis that debromination occurred in the OF but not in RF because

344

BDE47 can be derived from BDE153, which was first debrominated to BDE99 and

345

the initial δ13C value of BDE153 was lower than that of BDE99. Although two

346

metabolites of BDE47 were detected in the present study (Table S1), the δ13C of

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BDE47 did not increase during the depuration period in both the RF and OF. This

348

result indicates that hydroxylation of BDE47 did not result in significant isotope

349

fractionation, probably due to the relatively low contribution of hydroxylation to the

350

metabolism of PBDEs in fish.34

351

The εC values calculated from the Rayleigh Equation for chemicals in the OF and

352

the RF are given in Figure S5 and Table 1. The εC values for o,p’-DDT and CB8 and

353

18 are comparable between the RF and the OF (t-test, p = 0.377 and 0.722 for CB8

354

and 18, respectively), suggesting similar biotransformation mechanism for these

355

compounds; whereas the εC values for CB45, 91, 95, 132 and 136 (from 2.34‰ to

356

3.1‰) in the OF are approximately two times those (from 1.22‰ to 1.69‰) in the RF

357

(t-test, p = 0.001–0.012), implying different biotransformation mechanisms exist for

358

these chemicals in these two fish species.

359

Enantiomer-Specific Stable Carbon Isotope Signatures. Carbon isotope

360

compositions were obtained for each atropisomer of CB45, 91, 95, 132, 136, and 149,

361

and (+)-o,p’-DDT in the RF and OF (Figure S6). In the RF, they were absent from the

362

last four sampling points of E2-CB45 and (+)-CB136; and from the last one and two

363

point(s) of (-)-CB132 and (-)-CB95, respectively, due to the low concentrations. The

364

initial δ13C values were the same for the pair of atropisomers of each chiral PCB

365

congener (Figure S6). No changes in EFs for CB149 were found in the OF, in which

366

the isotopic composition also remained unchanged for either atropisomer (Figure S6).

367

This result further verified that no biotransformation occurred for CB149 in the OF. In

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contrast, significant isotope fractionation was observed for (+)-o,p’-DDT, both

369

atropisomers of CB45, 91, 95, 132, and 136 in RF and OF, and for both atropisomers

370

of CB149 in RF (Figure S6), indicating that both atropisomers of these PCBs were

371

involved in metabolic processes in both RF and OF. Additionally, the changes in δ13C

372

value (∆δ13C = δ13Ct-δ13Cinitial) for more metabolized atropisomers (according to the

373

EF value) were larger than the other atropisomers in both RF and OF at each sampling

374

point (Figure S6), further implying the high relevance between the changes in EF

375

value and the metabolism for PCB in fish.

376

The εC values were absent for E2-CB45 and (+)-CB136 in the RF, as δ13C values

377

were detected only in one (the first) sampling point of the depuration period. Similar

378

to their racemates, the εC values of each atropisomer of chiral PCBs in the OF were

379

higher than those in the RF, suggesting that the reaction mechanisms of PCBs are

380

different between the two fish species (Figure S7 and Table 1). Comparable εC values

381

for both (+)- and (-)-atropisomer were found for chiral PCB in both the RF and the

382

OF (Table 1). These results indicated that both atropisomers of each PCB congener

383

were metabolized by similar reaction mechanisms in each fish species. The isotope

384

sensitive carbon bond cleavage might not be the cause for the enantioselective

385

biotransformation of chiral PCBs. Other steps, such as substrate uptake into the cell

386

and binding of the substrate to enzyme, were the rate limiting steps for

387

biotransformation of chiral PCBs. Similar result was found for CB45 in common carp,

388

19

389

and presented in Table 1 as comparison. However, it should be noted that the εC values for chemicals in the present study

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are small (ranged from 1-2.5‰), which means that changes in carbon isotope ratios

391

can be detected only when significant part of initial compound is biotransformed. As

392

thus, the distinction of the metabolism using CSIA/ESIA in organisms might be not

393

always possible when the biotransformation of organic contaminants is accompanied

394

by an insignificant carbon isotope fractionation. In the future, it is expected that using

395

CSIA/ESIA for a multi-element isotope analysis (i.e. H vs. C vs. Cl or Br) could be

396

developed for a better characterization of transformation pathways of organic

397

contaminant.

398

Relationship between the BMF and the Compound-Specific Isotope

399

Signatures. Generally, bioaccumulation parameters, such as the bioconcentration

400

factor, bioaccumulation factor, and BMF can be predicted by their octanol-water

401

partition coefficient (Kow), since bioaccumulation parameters are linear or

402

parabolically correlated with the log Kow.35, 37 The biotransformation process would

403

result in the underestimation for the BMF of more metabolically labile chemicals.

404

CB28, 52, 101, and 138 and BDE100 and 154 in both the RF and the OF were

405

recalcitrant to metabolism according to the results of both the δ13C and metabolite

406

measurement in the present study. Indeed, the BMF of these chemicals is significantly

407

correlated to the log Kow in the two food chains in the present study (Figure S8). On

408

the contrary, the BMF of the chemicals that are readily metabolized in fish were

409

generally lower than their expected values according to the log Kow, whilst higher

410

BMFs were found for the metabolism products (e.g., o,p'-DDE in RF, and BDE28, 47,

411

49 and 101 in OF, Figure S8). The influence of biotransformation on the BMF for

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PCB congeners can be characterized by the difference (∆BMF = BMFpredicted -

413

BMFmeasured) between the BMFmeasured and the BMFpredicted. The BMFpredicted for PCB

414

congener was calculated from the correlation between BMF and log Kow of four

415

recalcitrant PCB congeners (CB28, 52, 101, and 138) in the present study. Similarly,

416

the fraction of depuration that is due to biodegradation and biotransformation can also

417

be determined by the difference between predicated kd and the measured Kd (∆kd =

418

kmeasured -kpredicted). The fractions of depuration rate derived from biotransformation

419

accounted for 19% to 58% of the total depuration rate for PCB congeners.

420

The isotope fractionation is related to the extent of metabolism of a chemical in

421

organisms. The percentage of ∆δ13C (δ13Cending-δ13Cinitial) to the initial δ13Cinitial

422

(∆δ13C/δ13Cinitial, %) was used as an indicator of the extent of metabolism of the

423

chemical in fish. As clearly shown in Figure 4, the depuration rates of chemicals that

424

had no isotope fractionation were all lower, but the BMF were all higher than those of

425

chemicals that had significant isotope fractionation. A significant positive correlation

426

between the kd and the ∆δ13C/δ13Cinitial (Figure 4a), and a significant negative

427

correlation between the BMF and the ∆δ13C/δ13Cinitial (Figure 4b) were observed for

428

chemicals that had significant alterations in isotopic composition in both the RF and

429

OF (all p < 0.001). Meanwhile, significant linear positive correlations were also

430

observed between the ∆BMF/∆kd and ∆δ13C/δ13Cinitial for PCB congeners (Figures 5b

431

and 5e, p < 0.05) and atropisomers (Figures 5c and 5f, p < 0.01) in the RF and the OF.

432

These results suggest that the influence of biotransformation of chemicals on the BMF

433

in the two food chains can be predicted by the stable carbon isotope fractionation of

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chemicals in the predator fish.

435

In the present study, we further demonstrated the species-specific and compound

436

specific biotransformation of PCBs, PBDEs, and o,p'-DDT in fish by using

437

CSIA/ESIA. More important, the extent of biotransformation of organic contaminants

438

in fish was characterized using the changes of carbon isotopic ratio and the linkage

439

between metabolism and bioaccumulation parameter was established. This make it

440

possible to predict the influence of metabolism on the biomagnification factor in food

441

chain. To the best of our knowledge, this is a first study to quantitatively describe the

442

influence of chemical biotransformation on biomagnification in food chains.

443

Supporting Information

444

Additional details regarding the standards and reagents, food preparation for TB,

445

chemical and instrumental analysis procedures, quality assurance and control, and the

446

calculation formulas for bioaccumulation parameters. Figures showing the

447

concentrations of chemicals in TB; accumulation and depuration curves of chemicals

448

in carcass of RF and OF; enantiomer compositions of chiral chemicals in spiked food

449

and the three fish species; the isotopic values (δ13C) of each enantiomer/atropisomer

450

of chiral chemicals; linearized Rayleigh Equation plots showing the carbon isotope

451

fractionation for the biotransformation of each chemical and enantiomer/atropisomer;

452

BMFs vs log Kow for chemicals in carcass of RF and OF. Table showing the

453

concentrations of OH-PBDEs in serum and MeSO2-PCBs in liver of the RF and the

454

OF.

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Acknowledgements This work was financially supported by the National Basic

456

Research Program of China (2015CB453102), the National Nature Science

457

Foundation of China (Nos. 41673100, 41473102), the Chinese Academy of Sciences

458

(Project XDB14020301, QYZDJ-SSW-DQC018), and Science and Technology

459

Project of Guangdong Province, China (2014B030301060).

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(36) Roberts, S. C.; Noyes, P. D.; Gallagher, E. P.; Stapleton, H. M. Species-specific differences and

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structure-activity relationships in the debromination of PBDE congeners in three fish species. Environ.

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Sci. Technol. 2011, 45 (5), 1999-2005.

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(37) Fisk, A. T.; Norstrom, R. J.; Cymbalisty, C. D.; Muir, D. C. G. Dietary accumulation and

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depuration of hydrophobic organochlorines: Bioaccumulation parameters and their relationship with

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the octanol/water partition coefficient. Environ. Toxicol. Chem. 1998, 17 (5), 951-961.

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(38) Hawker, D. W.; Connell, D. W. Octanol-water partition coefficients of polychlorinated biphenyl

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congeners. Environ. Sci. Technol. 1988, 22 (4), 382-387.

573 574

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575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609

Figure Captions Figure 1. Assimilation efficiency, depuration rate, and biomagnification factor of chemicals in carcasses of the redtail catfish and the oscar fish (error bar indicated ± SE). Figure 2. A comparison in assimilation efficiency, depuration rate, and biomagnification factor between two enantiomers/atropisomers of chiral PCBs and DDTs in carcasses of the redtail catfish and the oscar fish (error bar indicated ± SE). Figure 3. The δ13C of PCBs and o,p’-DDT in the spiked food, the tiger barb, the redtail catfish (closed symbols with solid lines) and the oscar fish (open symbols with dash lines) (a–d); and the δ13C of PBDE congeners in redtail catfish (e) and oscar fish (f). Figure 4. Depuration rates (kd) and BMFs versus the relative increase in δ13C values (∆δ13C/δ13Cinitial, %) for PCBs and o,p’-DDT and their enantiomers/atropisomers, and BDE153 in redtail catfish and oscar fish carcasses (error bar indicated ± SE). ∆δ13C is expressed as the isotopic differences of chemicals in fish at the end of depuration relative to those at the start of depuration. Chemicals in the dotted outline are those recalcitrant to metabolism in fish. Figure 5. Correlation between biomagnification factors (BMFs) or depuration rates (kd) of four recalcitrant PCBs (CB28, 52, 101, and 138) and log Kow in the redtail catfish and the oscar fish (a, d); and the correlation between the relative changes of δ13C (∆δ13C/δ13Cinitial) and the ∆BMF (BMFpredicted-BMFmeasured) or ∆kd (kd(measured) -kd(predicted) ) for PCBs (b, e) and chiral PCB atropisomers (c, f) in the redtail catfish and the oscar Fish. Log Kow values for PCBs are taken from Hawker and Connell38; ∆δ13C is expressed as the isotopic differences of PCBs in fish at the end of depuration relative to those at the start of depuration; BMFpredicted and kd(predicted) were determined from the equations in a) and in d), respectively; kd(measured) and BMFmeasured were calculated from Eq. S2 and Eq. S5, respectively.

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610 611 612 PC PC B 8 B PC 18 B PC 28 B4 PC 5 B PC 52 B PC 91 PC B 95 B PC 101 B PC 132 B1 PC 36 B PC 138 B o,p 149 'o,p DDE '-D o,p DD '-D BD DT E BD 28 E BD 47 E BD 49 E BD 42 E BD 101 E BD 85 BD E 99 E1 BD 00 E BD 153 E1 54

Biomagnification factor

160

24

21

18

c) PC PC B 8 B PC 18 B PC 28 B4 PC 5 B PC 52 B PC 91 PC B 95 B1 PC 01 B PC 132 B PC 136 B PC 138 B1 o,p 49 'o,p DDE 'o,p DDD '-D BD DT E BD 28 E BD 47 E BD 49 BD E 42 E1 BD 01 E BD 85 BD E 99 E1 BD 00 E BD 153 E1 54

Assimilation efficiency (%)

a)

140

120

100 80

60

40

20

Depuration rate (10-2/day)

Environmental Science & Technology

180 7

9

6

6

b)

5

4

3

0 2

1

15

12

Redtail catfish Oscarfish

3

0

Figure 1

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-2 -1 Biomagnification factor Depuration rate (10 day ) Assimilation efficiency (%)

613 60 Redtail vatfish/tiger barb (+) Atropisomer/enantiomer (-) Atropisomer/enantiomer

50

Oscar fish/tiger barb (+)Atropisomer/enantiomer (-)Atropisomer/enantiomer

40 30 20 10 16 14 12 10 8 6 4 2 4 3 2 1

614 615 616 617

Figure 2.

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o,p'-DDT

o,p'-DDD

PCB149

PCB136

PCB132

PCB95

PCB91

PCB45

o,p'-DDT

o,p'-DDD

PCB149

PCB136

PCB132

PCB95

PCB91

PCB45

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13

δ C(‰)

618 -23 -24 -25 -26 -27 -28 -29 -30 -31 -32 -33 -23 -24 -25 -26 -27 -28 -29 -30 -31 -32 -33 -22 -23

a

Depuration

Depuration

b

PCB8 PCB18 PCB45

PCB28 PCB101

PCB52 PCB138

d

c

DDT PCB95 PCB132

e

BDE47 BDE99 BDE154

-24 -25

PCB91 PCB136 PCB149

BDE100 BDE85 BDE153

f

BDE47 BDE99 BDE154

BDE100 BDE85 BDE153

-26 -27 -28 -29 -30 -31 Food

619 620 621

TB

14 21

35

49

63

77

91 Food TB

14

21

Time (day)

Figure 3

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35

49

63

77

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3.6

Y = 0.181X + 1.526, R2= 0.433, p = 0.0013

3.2

5 BDE 153

2.8

Y= -0.13X + 3.87, R2= 0.506, p < 0.0005

BMF

Depuration rate (kd,10-2/d)

4.0

Redtail Catfish Oscar Fish

6

4

2.4 2.0

3

1.6 1.2

2

Y = 0.270X - 1.093, R2= 0.768, p < 0.0001

-1 0

623 624

Y = -0.101X + 2.786, R2= 0.507, p < 0.0005

0.4

1

622

BDE 153

0.8

8

10

12

14

16

18

20

22

-1 0

8

∆ δ13C/ δ13Cinitial (%)

10

12

14

16

18

20

∆ δ13C/ δ13Cinitial (%)

Figure 4.

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625 Redtail catfish/tiger barb Oscar fish/tiger barb

3.0

2.5

4.0

y = 0.876x - 2.17, R2 = 0.95, p = 0.05 3.2

2.8

2.4

c)

b) 2.5 2.0

y = 0.152x - 1.20, R2 = 0.85, p < 0.01

1.5 1.0 0.5

y = 0.512x - 0.62, R2 = 0.85, p = 0.14 0.0

2.0 5.6

6.4 log KOW

15 13

1.0

0.5

18

21

12

2.0 1.5 y = -0.398x + 4.10, R2 = 0.87, p = 0.04

0.5 6.4 log KOW

6.8

21

f) y = 0.229x - 1.98, R2=0.674, p < 0.001

3

y = 0.201x - 1.67, R2 = 0.46, p = 0.03

2

1

3

2

1

0

0

6.0

18

4

∆Kd =Kdmeasured- Kdpredicted (10-2)

2.5

∆Kd =Kdmeasured- Kdpredicted (10-2)

3.0 y = -0.819x + 7.69, R2 = 0.79, p = 0.07

15

∆ δ13C/ δ13Cinitial (%)

13

e)

d)

5.6

y = 0.119x - 0.651, R2=0.83, p < 0.01

∆ δ C/ δ Cinitial (%)

1.0

626 627

1.5

0.0 12

6.8

2.0

4

3.5 Depuration rate (Kd, 10-2)

6.0

∆ BMF = BMFpredicted - BMFmeasured

3.6

∆ BMF = BMFpredicted - BMFmeasured

Biomagnification factor

a)

12

15 13

18

21

13

∆ δ C/ δ Cinitial (%)

Figure 5.

628

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15

18

∆ δ13C/ δ13Cinitial (%)

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629 630

. Table 1. Isotope enrichment factor of chemicals in the redtail catfish and the oscar fish (± SE)

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Common Carpa

Oscar Fish

Redtail Catfish Compounds

εC (‰)

R2

εC (‰)

R2

o,p’-DDT

−1.96 ± 0.12

0.99

−2.2 ± 0.17

0.98

/

/

(+)-o,p’-DDT (-)-o,p’-DDT CB 8 CB18

−1.95 ± 0.28 / −2.42 ± 0.19 −2.14 ± 0.15

0.94 0.98 0.98

−1.94 ± 0.19 / −2.53 ± 0.25 −2.29 ± 0.33

0.96 / 0.96 0.92

/ / −1.99 ± 0.08 −1.84 ± 0.16

/ / 0.99 0.98

CB 45 E1-CB 45 E2-CB 45

−1.41 ± 0.24 −1.64 ± 0.23 /

0.89 0.92 /

−2.34 ± 0.21 −2.06 ± 0.16 −2.51 ± 0.28

0.97 0.97 0.95

−1.70 ± 0.12 −1.64 ± 0.36 −1.74 ± 0.24

0.96 0.93 0.97

CB 91 (+)-CB 91 (-)-CB 91

−1.74 ± 0.19 −1.17 ± 0.28 −1.42 ± 0.24

0.95 0.81 0.89

−3.1 ± 0.18 −2.26 ± 0.19 −3.0 ± 0.26

0.99 0.97 0.97

/ −1.53 ± 0.21 /

/ 0.99 /

CB 95 (+)-CB 95

−1.22 ± 0.20 −1.53 ± 0.24

0.90 0.91

−2.79 ± 0.23 −2.5 ± 0.19

0.97 0.98

/ /

/ /

(-)-CB 95

−1.06 ± 0.26

0.89

−2.44 ± 0.06

0.99

−0.77 ± 0.06

0.87

CB 132

−1.69 ± 0.14

0.97

−2.56 ± 0.25

0.96

/

/

(+)-CB 132 (-)-CB 132 CB 136

−1.87 ± 0.31 −1.91 ± 0.33 −1.47 ± 0.04

0.94 0.99 0.99

−2.72 ± 0.32 −2.27 ± 0.11 −2.78 ± 0.24

0.94 0.99 0.97

/ / /

/ / /

(+)-CB 136 (-)-CB 136

/ −1.56 ± 0.09

/ 0.99

−1.92 ± 0.24 −2.69 ± 0.18

0.93 0.98

/ /

/ /

CB 149 (+)-CB 149 (-)-CB 149

−1.49 ± 0.12 −1.41 ± 0.32 −1.28 ± 0.31

0.97 0.82 0.80

/ / /

/ / /

/ / /

/ / /

BDE 153

/

/

−1.60 ± 0.25

0.98

−0.86 ± 0.11

0.99

a : Data for common carp as comparison was cited from previous study. 19

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εC (‰)

R2