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Effect-directed analysis of aryl hydrocarbon receptor agonists in sediments from the Three Gorges Reservoir, China Hongxia Xiao, Martin Krauss, Tilman Floehr, Yan Yan, Arnold Bahlmann, Kathrin Eichbaum, Markus Brinkmann, Xiaowei Zhang, Xingzhong Yuan, Werner Brack, and Henner Hollert Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b03231 • Publication Date (Web): 18 Sep 2016 Downloaded from http://pubs.acs.org on September 20, 2016

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Environmental Science & Technology

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Effect-directed analysis of aryl hydrocarbon receptor agonists in sediments

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from the Three Gorges Reservoir, China

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Hongxia Xiao1, Martin Krauss2, Tilman Floehr1, Yan Yan1, Arnold Bahlmann2, Kathrin

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Eichbaum1, Markus Brinkmann1,3, Xiaowei Zhang4, Xingzhong Yuan5, Werner Brack1,2,

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Henner Hollert1,4,5,6*

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1

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Biology and Biotechnology, RWTH Aachen University, Aachen 52074, Germany

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2

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UFZ, Leipzig 04318, Germany

Department of Ecosystem Analysis, Institute for Environmental Research, ABBt – Aachen

Department of Effect-Directed Analysis, Helmholtz Centre for Environmental Research–

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3

11

Canada

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4

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Nanjing University, Nanjing 210046, China

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5

15

China

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6

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Shanghai 200092, China

School of Environment and Sustainability, University of Saskatchewan, Saskatoon S7N 5B3

State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment,

College of Resources and Environmental Science, Chongqing University, Chongqing 400030,

Key Laboratory of Yangtze Water Environment, Ministry of Education, Tongji University,

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*Corresponding author:

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Henner Hollert

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Worringerweg 1, 52074 Aachen, Germany

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Phone: +49 (0)241 – 80 / 26669, Fax: +49 (0)241 – 80 / 22182

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E-mail: [email protected] (H.Hollert);

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ABSTRACT

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The construction of the Three Gorges Dam (TGD) in the Yangtze River raises great concern

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in ecotoxicological research since large amounts of pollutants enter the Three Gorges

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Reservoir (TGR) water bodies after TGD impoundment. In this work, effect-directed analysis

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(EDA) combining effect assessment, fractionation procedure, target and non-target analyses,

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was used to characterize aryl hydrocarbon receptor (AhR) agonists in sediments of the TGR.

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Priority polycyclic aromatic hydrocarbons (PAHs) containing four to five aromatic rings were

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found to contribute significantly to the overall observed effects in the area of Chongqing. The

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relatively high potency fractions in the Kaixian area were characterized by PAHs and

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methylated derivatives thereof and heterocyclic polycyclic aromatic compounds (PACs) such

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as dinaphthofurans. Benzothiazole and derivatives were identified as possible AhR agonists in

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the Kaixian area based on non-target liquid chromatography-high resolution mass

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spectrometry (LC-HRMS). To our knowledge, this study is the first one applying the EDA

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approach and identifying potential AhR agonists in TGR.

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Key words: Effect-directed analysis (EDA); aryl hydrocarbon receptor agonists; Three

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Gorges Reservoir (TGR); non-target analysis; QSAR

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TOC/Abstract art:

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Introduction

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The Three Gorges Reservoir (TGR), created in consequence of the Yangtze River’s

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impoundment by the Three Gorges Dam (TGD), spreads over a distance of 663 km between

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the town of Sandouping, Hubei Province, and the Jiangjin district of Chongqing Municipality.

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Besides the obvious benefits of the TGD, such as hydroelectricity, navigation, and flood

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control, construction of the TGD also poses great challenges to the unique ecosystem,1

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particularly

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industrialization, and intensified shipping activities.2 Furthermore, construction of the dam

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reduced the river’s flow velocity,3,

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suspend particles and adhering contaminants.5

when

facing

numerous

4

anthropogenic

impacts,

e.g.,

overpopulation,

and consequently increased the sedimentation rate of

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Sediments are considered as the final sink of persistent and lipophilic pollutants in the

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environment.6 They can become a potential source of pollutants through resuspension of

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particulate matter, e.g., during flood events.7-9 Frequently occurring floods in the water

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fluctuation zone of TGR may increase the pollutants bioavailability through remobilization

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and direct exposure to benthic organisms.9, 10 To ensure the environmental and public health,

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suitable and effective monitoring strategies of sediments in TGR are urgently demanded.

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Extensive chemical-analytical research has been performed on TGR, indicating that the

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sediments in TGR are polluted with a mixture of persistent organic pollutants (POPs), such as

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polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs) and polycyclic aromatic

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hydrocarbons (PAHs).3,14,15 Most of these compounds are known to induce cytochrome P450

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1A (CYP1A) by ligand-activation of the aryl hydrocarbon receptor (AhR).11, 12 It has been

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reported that the binding of xenobiotics to the AhR can trigger a broad spectrum of adverse 3 ACS Paragon Plus Environment


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effects, such as on biochemistry, physiology and reproduction in many organisms.12-14

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Furthermore, exposure of early life stage of fish to AhR agonists may cause increased

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mortality in further developmental stages15-18 and adverse outcomes in wild fish

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populations.19-23. This is of particular concern, as the Yangtze River plays an important role

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for fishery production in China. 24, 25

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As recently shown in a review,26 only limited research was done on bioassays to

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determine AhR-mediated activity in this area. Moreover, chemical analysis of target

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compounds provides only limited information on adverse biological effects of complex

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mixture.2,

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fractionation, chemical analysis and bioassays, has been demonstrated to be a suitable tool for

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the identification of causative toxicants in complex environmental samples. This approach is

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directed by the biotests (in vitro or in vivo assays), through the assignment of toxicity to

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several groups of toxicants by separation steps including extraction, clean up, and

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fractionation. The aim is to remove compounds without significant contribution to sample

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toxicity and to identify the predominant toxicants using chemical analytical tools. EDA can be

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particularly useful for addressing the effects on ecological health and environmental

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management of contamination source, thus further supporting the prioritization and regulation

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of environmental contaminants.29-31 Although this approach has been successfully used for

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toxicant identification in various environmental matrices,28, 32-37 the application of EDA in

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China is still quite limited.38-40, and few research has been done in the TGR.

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The concept of effect-directed analysis (EDA)28, featuring a combination of

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In our previous studies, sampling sites along the TGR were screened according to the triad

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approach 41 to achieve a comprehensive perspective on ecotoxicological status of this area.2, 42

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Two sites – close to the cities of Chongqing and Kaixian – were identified as regional “hot-

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spots” with respect to dioxin-like activity and mutagenicity. The present study aimed to


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characterize and identify individual AhR agonist in the sediments extracts in support of the

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prioritization and regulation of environmental contaminants present in sediments of the TGR.

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Material and methods

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Sample Collection and Preparation

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Sediment samples were collected using a Van-Veen sampler in September 2011. Three

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samples were collected at the mainstream close to Chongqing – upstream (CNG-U),

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downstream (CNG-D) and directly at the tributary’s inlet (CNG-T), as well as one sample

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from Hanfeng Lake (HF-L) in Kaixian. For detailed information see Support Information (SI,

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Figure S1).

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All sediments were freeze-dried, sieved (≤ 0.2 cm), and thoroughly homogenized by

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using pestle and mortar. Thereafter, the applied EDA strategy followed the flowchart as

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shown in Figure 1. Sediments (20 g each) were extracted per run, with acetone: hexane (1:1;

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v:v) in a pressurized liquid extractor (PLE) (Speed Extractor E-916, Büchi Labortechnik AG)

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at 100°C and 120 bar in two cycles (heat up 1 min; hold 10 min; discharge 2 min; flush with

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solvent 1 min; flush with gas 4 min), as described in detail in a previous study.42 Parent

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extracts were rotary-evaporated close to dryness and re-dissolved in acetone: hexane (1:1; v:v )

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to a final concentration of 20 g sediment equivalents (SEQ) per mL solvent. The parent

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extracts were kept in amber glass at 4°C for fractionation.

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Fractionation of Samples

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To reduce the interference of non-toxic substances such as minerals, salts and large

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biogenic organic molecules, parent extracts were solvent exchanged to dichloromethane 5 ACS Paragon Plus Environment


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(DCM), and purified by gel-permeation chromatography (GPC) (Biobeads SX3, Bio Rad) as

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described elsewhere.43 The purified extracts were evaporated close to dryness, and re-

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dissolved in hexane: DCM (9:1; v:v) for fractionation.

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The fractionation step was performed on three coupled normal-phase high

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performance liquid chromatography (NP-HPLC) columns, including cyanopropyl (CN),

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nitrophenyl (NO) and porous graphitized carbon (PGC), which has been described in detail in

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Lübcke-von Varel et. al.44 Polar polycyclic aromatic compounds (PACs) were trapped on and

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eluted from CN column, while nonpolar compound groups were retained on NO and PGC

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columns. The fractionation windows and eluting compounds in respective fractions according

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to Lübcke-von Varel et al.44 are given in SI (Table S1). Extract amounts of 40 — 60 g SEQ

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were fractioned per run. Each fraction was rotary-evaporated close to dryness and re-

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dissolved in acetone: hexane (1:1; v:v) to a final concentration of 20 g SEQ per mL solvent.

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Subsequently, 1 mL sub-fractions were solvent exchanged with dimethyl sulfoxide (DMSO)

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and tested for their AhR-mediated activities as described below. The remaining sub-fractions

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were stored in amber glass vials at –20°C for chemical analysis. It should be noted here that

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the whole sample preparation and fractionation procedure is dedicated towards hydrophobic

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and polyaromatic compound. Thus, this study might potentially exclude other, more polar

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AhR agonists present in sediments.

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Ethoxyresorufin-O-deethylase (EROD) induction assay

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In order to avoid cytotoxic effects in the EROD assay, the neutral red retention assay

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(NR) was carried out with RTL-W1 cells according to the method described by Babich and

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Borenfreund.45 The AhR-mediated activity was determined by the EROD induction assay

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using rainbow trout (Oncorhynchus mykiss) liver cells (RTL-W1) according to previously


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described methods by Gustavsson et al.46 with slight modifications.2 Samples were analyzed

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in three replicates, each with three internal replicates serially diluted with medium in seven

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1:2 steps. The well characterized substance 2,3,7,8-tetrachlorodibenzo-p-dioxin (2,3,7,8-

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TCDD) was used in a test concentration range from 3.13 to 100 pM on each plate as a

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reference standard. EROD activity was determined fluorometrically via a multiwell plate

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reader (Infinite M200, Tecan Austria GmbH, Grödig). The artificial substrate 7-

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ethoxyresorufin (7-EXT) was deethylated to resorufin by cytochrome P450 (CYP) enzymes.

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Fluorescence of resorufin was measured with excitation/emission wavelength of 544/590 nm,

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whereas the amount of protein was detected by fluorescence with excitation/emission wave-

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length of 360/460 nm. EROD activity was determined based on the quantity of produced

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resorufin per total amount protein and reaction time. Dose–response curves for EROD

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induction were computed by log concentration (agonist) vs. response with variable slope

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using Prism 6.0 (GraphPad Software Inc., San Diego). In order to provide comparability with

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other research, bioassay-derived TCDD equivalents (BEQs) were calculated on the basis of a

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fixed effect level of EC25 of the maximum response caused by the samples to those of the

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standard compound 2,3,7,8-TCDD, using the formula BEQsample (pgTCDD/gSEQ) =

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EC25TCDD(pgTCDD/mL) / EC25sample(gSEQ/mL). Moreover, the measured BEQs in

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fractions were compared to the TCDD equivalents (TEQs), which were obtained by

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multiplying the concentration of each compound in each sample by its relative potency (REP),

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and summing up these values. This comparison enables an estimation of the contribution of

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the analyzed chemical contaminants to the measured AhR-mediated activity.11

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Targeted Analysis of PACs by GC-MS

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A list of 32 PACs including priority PAHs, alkylated PAHs and heterocycle

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polyromatic chemicals (oxygen, and sulfur-containing PAHs) was selected for measurement 7 ACS Paragon Plus Environment


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based on their occurrence in sediments (SI, Table S5). The identification and quantification of

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PACs were performed with a GC (Agilent 6890) equipped with an auto sampler (Agilent

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7683) and coupled with a mass spectrometer (Agilent 5973) with electron ionization source.

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Aliquots of 1 µl of sample were injected in splitless mode at an injector temperature of 250°C.

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After sample injection, the analytes were separated on capillary column (HP5MS,

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35 m × 0.25 mm, i.d., 0.25 µm, Agilent) using helium as carrier gas at a constant flow rate of

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1.3 mL/min. The oven temperature started at 60°C and ramped with 30°C/min until 150°C,

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then with 6°C/min up to 186°C, followed by 4°C/min to 280°C held for 21.5 min. For priority

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16 EPA-PAHs, quantification was performed in selected ion monitoring (SIM) mode using

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external standards and corrected by means of the injection standards, i.e., 13C benzo[a]pyrene.

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The concentration of substituted PAHs as well as heterocyclic aromatic compounds were

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calculated based on methods described elsewhere.47

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Non-target Analysis in polar fractions by LC-HRMS

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The liquid chromatography separation was performed with an Agilent 1200 system

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equipped with a Kinetex Core-Shell C18 column (100 mm × 3.0 mm; 2.6 µm; Phenomenex).

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A linear gradient elution with water and methanol both containing 0.1 % formic acid at a flow

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rate of 0.2 mL/min was used. The LC system was connected to an ion trap-Orbitrap hybrid

182

instrument (LTQ Orbitrap XL, Thermo Scientific). Analytes were ionized by electrospray

183

ionization (ESI) and atmospheric pressure chemical ionization (APCI) in separate runs, both

184

in positive and negative ion mode, respectively. Details on instrument settings are given in the

185

supporting information (SI, Table S1). Full scan spectra were recorded at nominal resolving

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power of 100,000 (referenced to m/z 400) at a mass range of m/z 100 – 1000. High resolution

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product ion spectra (HRMS/MS) were acquired data-dependent for the two most intense

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precursor ions of the full scan at a nominal resolving power of 15,000, using an isolation 8 ACS Paragon Plus Environment

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width of 1.3 m/z, a minimum precursor ion intensity of 50,000 and a dynamic exclusion time

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of 20 s. Both collision induced dissociation (CID) at 35% and higher-energy collisional

191

dissociation (HCD) at 100% were used for fragmentation.

192 193

Processing of HRMS data for compound identification

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The MZmine 2.10 software48 was used for peak detection and peak lists (consisting of m/z

195

values, retention times, and signal intensities) obtained from full scan chromatograms of the

196

samples, solvent and processing blanks. The processing steps and settings of MZmine were

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given in SI (SI, Table S2). The peak lists were further processed using a R script to remove

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background contamination peaks occurring in solvent and processing blanks (intensity ratio of

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sample to blank < 10), and those originating from background signals not resembling

200

Lorentzian or Gaussian peak shapes (details are given in Hug et al.49 ).

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To further narrow down the peak lists to containing only compounds potentially being

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hydrophobic or polyaromatic AhR agonists, which were targeted by the sample preparation

203

procedure, the following filtering steps were applied:

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(i)

205

all peaks with retention times > 15 minutes were kept, as the active sediment fractions of interest should comprise compounds exerting certain hydrophobicity;

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(ii)

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all peaks were kept, which showed an at least five times higher intensity in the active fractions F13 to F15 than in any of the non-active fractions F16 to F18;

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(iii)

all peaks were kept, which had a mass defect below an upper boundary defined by

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the molecular formula CnH (2n-6-0.5n) (n is an even number), as most AhR

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receptor agonists should be of polyaromatic nature or contain at least a certain

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number of double bonds. This upper boundary corresponds to 6.5 double-bond

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equivalents (DBEs) for n = 10 and 7.0 for n = 12, etc. 9 ACS Paragon Plus Environment


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The filtered peak lists of potential AhR agonists of the active fractions were processed

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using the R “nontarget” package.40, 41 This allowed searching for bounds of isotope peaks (13C,

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15

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M+Na+, M+K+, M+NH4+ in positive mode; M-H− [M+formate]− in negative mode)

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considering single and double charged ions. Peaks were finally grouped into components,

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encompassing the monoisotopic peak and its associated isotope or adduct peaks representing

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an individual chemical compound. The package’s settings are given in the SI (Table S3).

N,

34

S,

37

Cl, and

81

Br) with a rule-based algorithm and peaks of relevant adducts (M+H+,

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Starting from these annotated component lists, a determination of molecular formulas was

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done based on the raw data file using the QuanBrowser of the Xcalibur software (Thermo

222

Scientific). For obtained molecular formulas, the Chemspider compound database50 was

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searched to retrieve candidate structures. Plausible candidate compounds were identified

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based on the number of references in Chemspider as an indicator of human use and

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commercial importance. For these compounds reference standards were obtained if possible

226

and used for confirmation based on retention times and MS/MS spectra. For compounds

227

without reference compound, a tentative identification was done based on an interpretation of

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MS/MS spectra in comparison to those of known compounds.

229 230

QSAR modeling using VirtualToxLab

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The AhR binding affinities of candidate compounds, which were identified from both

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target and non-target analysis were simulated by VirtualToxLab. The VirtualToxLab is an in

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silico tool for predicting the toxic potential of chemicals by simulating and quantifying their

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interactions towards a series of proteins, which are known to trigger biological effects using

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automated, multi-dimensional QSAR.51

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Statistical analysis

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Statistical analyses were performed using SigmaPlot 12.0 (Systat Software Inc). Non-

239

parametric Shapiro-Wilk ANOVA on ranks followed by Holm-Sidak’s post hoc test (p ≤ 0.05)

240

was used to determine significant differences in the EROD induction of fractions compared to

241

the process control.

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Results and discussion

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Bioassay-Derived induction equivalent quantities

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AhR-mediated activity of all sub-fractions, parent- (par) and reconstituted extracts (rec), and

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arithmetic sum (sum) of all fractions was examined in the EROD assay with RTL-W1 cells

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(Figure 2). BEQs showed significant fraction-specific differences, but followed the same

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relative distribution pattern in all four samples. The observation was in accordance with other

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studies which applied the same automated on-line fractionation method as the present study.47,

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52, 53

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naphthalenes (PCNs), coplanar PCBs, polychlorinated dibenzo-p-dioxins (PCDDs) and

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dibenzofurans (PCDFs), caused no or very low AhR-mediated activity, suggesting low levels

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of these compounds in TGR sediments. This result was in accordance with previous findings

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that only low levels of PCBs and PCDD/Fs were detected in water and sediments of the

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TGR.4,

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fractions F7 – F10, characterized by PAHs with four to six aromatic rings, as well as fractions

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F13 – F15, mostly characterized by intermediately polar to polar PACs (SI, Table S1). The

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highest BEQs were detected in HF-L, ranging from 42 to 177 pg BEQ/SEQ g and 69 to

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109 pg BEQ/SEQ g in fractions F7-F10 and F13-F15, respectively.

The fractions F3-F5, co-eluting with typical AhR agonists such as polychlorinated

42, 54

Significantly greater EROD inducing potency (p ≤ 0.05) was detected in



259

In order to determine eventual losses of activity during sample processing, all fractions

260

were combined to form reconstituted extracts and were tested with the same procedure.

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Recovery was estimated on the basis of reconstituted fractions of the parent extracts, and was

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67% for HF-L, 57% for CNG-T, and 93% for CNG-D. Due to limited sample amount, BEQs

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of the parent extract CNG-U were not available, and thus no recovery could be determined.

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Our results indicated good chemical recoveries, in which typical chemically analyzed

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standard compound concentration recoveries of 60 – 80% were reported.55

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The total response to exposure with these fractions was site-specific. The sample from

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the mainstream (CNG-U) exhibited higher levels of contaminants than the samples originating

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from tributaries (CNG-T) and downstream regions (CNG-D), but with similar fractionation

269

patterns. Thus, higher levels of contamination in the upstream of Yangtze river at Chongqing

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area may be diluted by sediments of the less contaminated tributary, the Jialing River. This

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results in lower concentrations of contaminants downstream of Chongqing, which is in

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agreement with previous findings.2, 56 The artificial Hanfeng Lake at Kaixian exhibited the

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highest AhR-mediated activity, which could be attributed to a lower dilution of discharged

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contamination compared to the Chongqing area, and a potential accumulation of

275

contamination in the lake.2

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Target Chemical Analysis

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The PAH fractions (F7 – F10), which exhibited significant EROD induction activity

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(Figure 2), were selected for priority PAH analysis. Moreover, the highest potency fractions

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HF-L-F9 – F10 were scanned for methylated PAHs as well as heterocyclic aromatic

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compounds (SI, Table S4). The fractions in the Chongqing area exhibited similar PAHs

282

profiles, which were characterized by four– and five– ringed PAHs. In addition, the


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concentration of CNG-U showed a higher contamination than the tributaries (CNG-T) and

284

downstream (CNG-D), which is in accordance with the bio-analytical results of the present

285

study. The fractions from the Kaixian area showed a contamination with pyrogenic five– and

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six– ringed PAHs, together with some methylated PAHs, and their oxygen (O-) and sulfur (S-)

287

heterocyclic aromatic compounds.

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The total priority EPA-PAHs ranged from 9 — 101 ng/g sediment (SI, Table S4).

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Among the parent PAHs, fluoranthene was measured at the highest concentrations

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(56.6 ng/g sediment in CNG-U-F7). Levels of PAHs with EROD induction capacity,57

291

including

292

indeno[1,2,3-c,d]pyrene, benzo[b]fluoranthene, chrysene, and benzo[a]anthracene were

293

detected up to 40.2 ng/g sediment. The concentrations of heterocyclic aromatic compounds

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were detected up to 5 ng/g sediment. The analytical results revealed that relatively low levels

295

of priority PAHs in TGR, which are one to two orders of magnitude lower in comparison to

296

levels detected in the Mulde River58, Danube River52, and Oslo harbour. 59

benzo[k]fluoranthene,

dibenzo[a,h]anthracene,

benzo[a]pyrene,

297 298

Contribution of PACs to the EROD induction potency of fractions

299

To estimate the fraction of activity explained by priority PAHs, we compared TEQs,

300

calculated using the REP values given by Bols, et al.57, to BEQs from EROD assay (SI,

301

Figure S2). The results revealed that the contribution of priority PAHs contributed up to 43%

302

of the AhR-mediated activity of responding fractions. Low contributions of chemically

303

derived TEQs were found in F7 and F8 of CNG-U, where priority PAHs such as fluoanthene

304

and pyrene were detected, which have been reported as non-inducers and weak AhR-agonists

305

in previous studies.57,

306

chrysene,

60

Four– to six– ringed parent PAHs such as benzo[a]anthracene,

benzo[b+k]fluoranthene,

benzo[a]pyrene

were


commonly

found

in

F9,


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indeno[1,2,3-cd]pyrene, dibenz[a,h]anthracene were found in F10 of CNG-U and HF-L.

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Especially the four– to six– ringed PAHs, which have been confirmed as AhR agonists,35, 48, 49

309

accounted for 43% of the BEQs in CNG-U-F9, thus likely being the main contributors.

310

Similar results were observed in CNG-D-F9 (28%) and CNG-T-F9 (40%). In the significant

311

high potency of fractions HF-L-F9 and HF-L-F10, the priority PAHs accounted for only about

312

9% and 12% of BEQs. The remainder of the activity was investigated and the potentially

313

active chemicals presented below.

314

In the faction of HF-L-F10, we hypothesize that me-PAHs and heterocycles detected

315

may account for a part of the observed effects in the fraction. Dinaphtho[1,2-b;1’,2’-d]furan

316

and dinaphtho[1,2-b;2’,3’-d]furan were identified as potent inducers of EROD activity in the

317

RTL-W1 cell line58 and rat hepatoma H4IIEGud.Luc 1.1 cell line.61 Based on the REP values

318

from

319

8.7 pg TEQ / g SEQ, corresponding to 7% of the BEQ in HF-L-F10. Methylated

320

benzo[a]pyrenes were detected in the fraction. Due to too many isomers present in the sample,

321

concentrations of each compound were hard to quantify. Methylated PAHs were shown to

322

significantly induce AhR-mediated activity in reporter gene assays,62 and have been reported

323

to be responsible for large portions of AhR activity in sediments.52,

324

benzo[a]anthracenes were reported to be significantly more potent AhR inducers than their

325

parent compounds.63 Brack and Schirmer58 identified methylation of chrysene in the 1-

326

position and of benzo[a]anthracene in the 9-position to enhance the EROD induction potency

327

by one to two orders of magnitude. Thus, we hypothesize that methylated benzo[a]pyrenes

328

play a role of the AhR-mediated activity in the bioactive fraction. Due to a lack of respective

329

REP values, the AhR binding affinities of heterocyclic PACs were simulated using QSAR (SI,

330

Table S5). Most of the PACs were predicted to have a binding affinity to the AhR, thus taken

Brack

and

Schirmer,58

the

TEQ

of

dinaphthofurans


was

calculated

58

as

Methylated

Page 15 of 34


331

as tentative compounds. To confirm the contribution of PACs, the relative potency of

332

heterocycles compounds should be an aim of further research.

333 334

Non-target analysis of polar fractions

335

In addition to the high potency fractions F7 to F10, the polar fractions, mainly eluting

336

with mono-nitro- PAHs (F13) as well as (hydroxyl-) quinones, keto-, dinitro-, hydroxyl-

337

PAHs and N-heterocycles (F14 – F15) showed relatively high AhR-mediated effects. Thus,

338

we also focused on characterizing the AhR agonists in polar fractions (F13 – F15) using LC-

339

HRMS. Because of the relatively low effects in samples CNG-D and CNG-T, we focused on

340

characterizing the AhR agonists in the higher effects of fraction F13 – F15 in the samples of

341

Chongqing upstream (CNG-U) and the Kaixian area (HF-L).

342

After peak detection using MZmine 2.10 and the removal of background peaks,

343

typically several hundred peaks remained in the peak lists for ESI+ and APCI+ mode, except

344

for fraction HF-L-F14, in which about 60 and 40 peaks could be detected (Table S5). In

345

APCI- and particularly ESI- mode, a significantly lower amount (< 90) of peaks remained.

346

The numbers of peaks were further reduced by an additional filtering step targeting likely

347

AhR agonists based on retention times, mass defects and absence in the non-active fraction

348

F16 – F18 (SI, Table S6). Nevertheless, in individual fractions more than 100 candidate peaks

349

remained. Thus, priority for identification was given to the most intense peaks in the active

350

fraction HF-L-F13.

351 352

Identification and selection of candidate AhR agonists

353

Based on accurate mass and isotope patterns, a plausible molecular formula could be

354

determined in ESI+ mode of all intense peaks (>106 a.u. intensity) in fraction HF-L-F13 (SI, 15 ACS Paragon Plus Environment


Page 16 of 34

355

Table S7). No additional compounds could be detected in APCI+ mode. While benzothiazole,

356

2-mercaptobenzothiazole and 2-(methylthio)benzothiazole were confirmed by reference

357

standards, MS/MS spectra of several other compounds suggests the occurrence of further

358

benzothiazole derivatives as indicated by fragments characteristic for a benzothiazole or a

359

mercaptobenzothiazole moiety (Table S7, Figure S3 – S6).

360

Benzothiazole derivatives are widely used as vulcanization accelerators and

361

antioxidants in rubber64,

65

and have been detected in water and sediments.49,

66, 67

362

compound at m/z 300.9923 and RT 27.4 was tentatively assigned as 2,2’-sulfanediylbis-(1,3-

363

benzothiazole), which could be a by-product of mercaptobenzothiazole use. Two isobaric

364

peaks at m/z 239.0669, RT 16.2 and 16.7, respectively, showed almost identical MS/MS

365

spectra with an intensive fragment at m/z 72.0803, which corresponds to a C4H10N group (SI,

366

Figure S5). This suggested N-t-butyl-2-benzothiazolesulphenamide, which is a vulcanization

367

accelerator as well, and a closely related isomer as further plausible candidates. He et al.

368

identified benzothiazole derivatives as AhR-active compounds in tire extracts by a toxicant-

369

identification-evaluation (TIE) approach.68 The study presented the ability of 2-

370

mercaptobenzothiazole to induce AhR-dependent gene expression, as well as benzothiazole to

371

be a weak AhR agonist in mammalian cell bioassays. In a previous study, both 2-

372

mercaptobenzothiazole and benzothiazole were shown as a relative potent AhR agonist of the

373

human AhR expressed in yeast.69

The

374

Another group of compounds in fraction HF-L-F13 were likely benzylamines, among

375

them the confirmed compound tribenzylamine, and several other compounds showing similar

376

MS/MS spectra with characteristic fragments C14H16N+ and C7H7+ (Table S7, Figure S7) were

377

found. The complete absence of the C6H7N+ ion (m/z 93.0573) suggests that no aniline

378

structure was present in these molecules.


Page 17 of 34


379

Among the tentative identified toxicants, 2-mercaptobenzothiazole, benzothiazole

380

2-(methylthio)benzothiazole and tribenzylamine were predicted to have a binding affinity to

381

the AhR by QSAR (Table 1). Thus, we assume benzothiazole and its derivates to be important

382

pollutants in the Kaixian area.

383 384

Source of contamination and environmental significance

385

Through target chemical analysis, high molecular weight PAHs (four- to six- ringed PAHs)

386

(Figure. 3) contributed significant to the responding fractions, thus are taken as significant

387

AhR-active compounds inducing AhR-mediated activity in the Chongqing section. As

388

Chongqing is the most important industrial center in the TGR region, the origins of identified

389

pollutants are possibly from urban traffic emissions and runoff, coal combustion, as well as

390

intensified shipping activities since the impoundment of the reservoir3 Further research is

391

required to identify the causative toxicants for unexplained effects in this area. In the Kaixian

392

area, only a minor part of the EROD inducing potency of tested sediment extracts could be

393

explained by the priority PAHs. The bioactive fractions of PAHs were characterized by a

394

broad variety of heterocycles and methylated PAHs. Dinaphthofurans were identified as

395

pollutants to contribute part of the EROD induction potency in the bioactive fraction. The

396

methylated PAHs were hypothesized as contributors to the toxicity in the Kaixian area. PACs

397

originate from incomplete combustion and industrial processes or fossil fuels as well as from

398

natural sources like volcanic eruptions.70 Methylated benzo[a]pyrenes have been identified as

399

components from cigarette smoke, urban air particulates, gasoline engine, diesel exhaust, and

400

forest fire smoke, as well as in a variety of coal-derived liquids and tars.71-74 Biomass burning

401

such as wood fuel used for cooking or heating, or the burning of straw residues in the fields

402

has caused serious pollution in the southeast of China,75, 76 and should be considered since the

403

Kaixian area constitutes a rather rural area. Benzothiazole is an aromatic heterocyclic 17 ACS Paragon Plus Environment


Page 18 of 34

77

404

compound, which is used as parent compounds for the synthesis of larger structures

. The

405

compound 2-mercaptobenzothiazole (MBT) and its derivatives such as N-t-butyl-2-

406

benzothiazolesulfenamide (Figure. 3) are used in industry as accelerators for the vulcanization

407

of rubber.65, 78 It is documented that benzothiazoles are not be tightly bound in the rubber

408

matrix, and thus may leach into waste effluents, which enter sediments via runoff and reach

409

surface water via drainage systems.65 Evidence for large amount of MBT and other

410

benzothiazoles are released from vehicle tire rubber into the environment as a result of the

411

weathering and leaching of tire rubber,65, 79 the biological activity of benzothiazoles are still

412

limited. MBT was reported to show acute toxic to fish,80 micrograms,67 and cells.79 Industrial

413

wastewater and street runoff from impervious urban surface are taken as significant source of

414

benzothiazoles in the environment. As the location of sampling site located in a rather rural

415

area, we assume that benzothiazoles in our study most likely originated from an identified

416

rubber factory nearby. Tribenzylamine are well-known extractants in industrial wastewater.81-

417

83

418

Dibenzylamine has been reported to be detected in environment samples, such as surface

419

water84 and wastewater.85 It was reported as by-product during the rubber vulcanization

420

process.86

Thus, the compound was hypothesized to be associated with wastewater treatment.

421

The present investigation integrated a biological-chemical approach for the

422

characterization of AhR agonists in the sediment of TGR. To the best of our knowledge, this

423

is the first time that AhR agonists were analyzed in TGR in more detail using EDA. Our study

424

strongly supports that focus on prioritized pollutants may result in inadequate assessment of

425

complex

426

concentrations were detected in the present study, the vulnerable TGR ecosystem might still

427

be of concern for its absolute pollution mass.26 Long-term monitoring programs including the

428

causative compounds should be employed parallel to the proceeding economic and

environmental

mixtures.36,51,87

Although

relatively


low

target

chemical

Page 19 of 34


429

demographic development due to the rapid industrialization and increased urbanization in

430

TGR. EDA is a suitable methodology to be included in monitoring programs to avoid

431

monitoring irrelevant compounds.

432

EDA has been proven to be useful for toxicant identification in the present study; however,

433

the approach is still not widely applied in environmental routine monitoring programs. With

434

respect to a tedious evaporation and solvent exchange steps, as well as large number of

435

fractions for bioassays, the relative laborious work largely limits a wider applicability of EDA.

436

Thereafter, workflows that can lead to a rapid assessment of the key toxicants are demanded30,

437

88

438

assessment and chemical identification are currently performed, with the aim to be applied as

439

a routine monitoring program, in order to support the prioritization of environmental

440

contaminants and the regulatory decisions in TGR.

. Correspondent studies in high throughput EDA integrating micro-fractionation, effect

441

442

Acknowledgements

443

This study has been carried out as part of the Yangtze-Hydro project (No. FKZ 02WT)

444

supported by the Germany Federal Ministry of Education and Research (BMBF),

445

SOLUTIONS project supported by the European Union Seventh Framework Programme

446

(FP7-ENV-2013-two-stage Collaborative project) under grant agreement No. 603437, and the

447

EDA-EMERGE project supported by the European Union Seventh Framework Programme

448

(FP7-PEOPLE-2011-ITN) under the grant agreement No. 290100. We also want to express

449

our gratitude to Dr. Niels Bols and Dr. Lucy Lee from the University of Waterloo, Canada,

450

who kindly provided the CYP1A expressing fibroblast-like permanent cell line RTL-W1 from

451

primary hepatocytes of rainbow trout (Oncorhynchus mykiss). We thank Marion Heinrich and

452

Lena Schinkel for conducting the analysis of polycyclic aromatic compounds by GC-MS. In 19 ACS Paragon Plus Environment


453

addition, Hongxia Xiao received a personal grant supported by the scholarship program

454

Chinese Scholarship Council. Markus Brinkmann was supported by the German National

455

Academic Foundation (‘Studienstiftung des deutschen Volkes’) and is a Banting Fellow of the

456

Natural Sciences and Engineering Resarch Council of Canada (NSERC).

457 458

Supporting Information Available

459

Detailed information on the sampling information, LC-HRMS analysis, target chemical

460

analysis data, as well as the identification of non-target compounds is available in the

461

Supplementary Information. This information is available free of charge via the Internet at

462

http://pubs.acs.org.


Page 20 of 34

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720


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721

Table 1. Nontarget compounds identified in the sediments of Kaixian Compound

Identification level

89

Molecular formula

Chemspider

CAS

50

ID

Exact

Use/origin

AhR binding

Mass

Experimental

Predicted a

- 90

+

[amu] 2-mercaptobenzothiazole

1

C7H5NS2

608157

149-30-4

167.251

Rubber additive

(MBT)

+

79

benzothiazole

1

C7H5NS

6952

95-16-9

135.186

Rubber additive

+79 69

+

N-t-butyl-2-

2

C11H14N2S2

6960

95-31-8

238.372

Rubber additive

n.e

-

1

C8H7NS

11494

615-22-5

181.278

Rubber additive

+

2

C14H8N

746290

n.a

300.422

Byproduct

benzothiazolesulfenamide (TBBS) 2-(methylthio)benzothiazole

79

+

(MTBT) 2,2’-sulfanediylbis(1,3benzothiazole)

of

n.e

+

mercaptobenzothiazole

tribenzylamine

1

C21H21

22739

620-40-6

287.398

Electroplating extractant

n.e

+

dibenzylamine

2

C14H15

7373

103-49-1

197.276

Byproduct

n.e

-

of

rubber

vulcanization

722 723 724 725 726 727

Identification level based on Schymanski et al., 1= confirmed, 2=probable structure. n.a: no available. n.e. indicates that no literature was found related to the AhR-mediated activity of the compound. a Estimated by QSAR -: Not AhR agonist reported in literature or predicted to have no binding affinity to the AhR by QSAR modeling; +: AhR agonist reported in literature or predicted to have binding affinity to the AhR by QSAR modeling; A compound was considered as potentially AhR agonist, either reported in literature or predicted as positive by QSAR modeling.

29

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728

Figure captions

729

Figure 1: Flowchart of the applied EDA strategy. NP-HPLC: Normal Phase-High Performance

730

Liquid Chromatography; F: Fraction; GC/MS: Gas Chromatography-mass spectrometry; LC-HRMS:

731

Liquid Chromatography-High Resolution Mass Spectrometry; QSAR: Quantitative Structure-Activity

732

Relationships.

733

Figure 2: Aryl hydrocarbon receptor-mediated activities of parent (par), reconstituted (rec)

734

extracts, arithmetic sum of fraction BEQs (sum) and fraction activities (1-18) of four sediment

735

extracts. Asterisks denote significant differences between fractions and process control (Non-

736

parametric Shapiro-Wilk ANOVA on ranks with Holm-Sidak’s post hoc test, p≤0.05). dw: dry weight.

737

N.A.-No data available.

738

Figure 3: Structures of compounds identified and tentatively identified by target and nontarget

739

screening. 1# Benzo[a]anthracene; 2# Chrysene; 3# Benzo[b]fluoranthene: 4# Benzo[k]fluoranthene:

740

5# Indeno[1,2,3-cd]pyrene; 6# dibenz[a,h]anthracene: 7# benzo[g,h,i]perylene; 8# Dinaphtho[1,2-

741

b;1’,2’-d]furan; 9# Dinaphtho[1,2-b;2’,3’-d]furan; 10#2-mercaptobenzothiazole ; 11# benzothiazole;

742

12#2-(methylthio)benzothiazole; 13#2,2’-sulfanediylbis(1,3-benzothiazole); 14# tribenzylamine.

743


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744 745 746 747

Figure 1. Flowchart of the applied EDA strategy. NP-HPLC: Normal Phase-High Performance Liquid Chromatography; F: Fraction; GC/MS: Gas Chromatography-mass spectrometry; LC-HRMS: Liquid Chromatography-High Resolution Mass Spectrometry; QSAR: Quantitative Structure-Activity Relationships.

748



749 750 751 752 753

Figure 2. Aryl hydrocarbon receptor-mediated activities of parent (par), reconstituted (rec) extracts, arithmetic sum of fraction BEQs (sum) and fraction activities (1-18) of four sediment extracts. Asterisks denote significant differences between fractions and process control (Non-parametric Shapiro-Wilk ANOVA on ranks with Holm-Sidak’s post hoc test, p≤0.05). dw: dry weight. N.A.-No data available.

754


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755 756

757 758 759 760 761 762 763

Figure 3: Structures of compounds identified and tentatively identified by target and nontarget screening. 1# Benzo[a]anthracene; 2# Chrysene; 3# Benzo[b]fluoranthene: 4# Benzo[k]fluoranthene: 5# Indeno[1,2,3cd]pyrene; 6# dibenz[a,h]anthracene: 7# benzo[g,h,i]perylene; 8# Dinaphtho[1,2-b;1’,2’-d]furan; 9# Dinaphtho[1,2-b;2’,3’-d]furan; 10#2-mercaptobenzothiazole ; 11# benzothiazole; 12#2(methylthio)benzothiazole; 13#2,2’-sulfanediylbis(1,3-benzothiazole); 14# tribenzylamine.



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