A Reduced Transcriptome Approach to Assess Environmental

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A Reduced Transcriptome Approach to Assess Environmental Toxicants Using Zebrafish Embryo Test Pingping Wang, Pu Xia, Jianghua Yang, Zhihao Wang, Ying Peng, Wei Shi, Daniel.L Villeneuve, Hongxia Yu, and Xiaowei Zhang Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b04073 • Publication Date (Web): 11 Dec 2017 Downloaded from http://pubs.acs.org on December 11, 2017

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A Reduced Transcriptome Approach to Assess Environmental Toxicants Using Zebrafish Embryo Test

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Pingping Wang†1, Pu Xia†1, Jianghua Yang†, Zhihao Wang†, Ying Peng†, Wei Shi†,

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Daniel L. Villeneuve ‡,Hongxia Yu†, Xiaowei Zhang†*

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

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Environment, Nanjing University, Nanjing, P. R. China, 210023 ‡

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United States Environmental Protection Agency, Mid-Continent Ecology Division,

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Duluth, MN, USA.

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1

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*Correspondence:

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Xiaowei Zhang, PhD, Prof

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School of the Environment

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Nanjing University

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Nanjing, 210089, China;

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Tel.: 86-25-89680623

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Fax: 86-25-89680623

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E-mail: [email protected]

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[email protected]

, these two authors contributed equally to this paper

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ABSTRACT

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Omics approaches can monitor responses and alterations of biological pathways at

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genome-scale, which are useful to predict potential adverse effects by environmental

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toxicants. However, high throughput application of transcriptomics in chemical

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assessment is limited due to the high cost and lack of “standardized” toxicogenomic

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methods. Here, a reduced zebrafish transcriptome (RZT) approach was developed to

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represent the whole transcriptome and to profile bioactivity of chemical and

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environmental mixtures in zebrafish embryo. RZT gene set of 1637 zebrafish Entrez

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genes was designed to cover a wide range of biological processes, and to faithfully

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capture gene-level and pathway-level changes by toxicants compared with the whole

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transcriptome. Concentration-response modeling was used to calculate the effect

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concentrations (ECs) of DEGs and corresponding molecular pathways. To validate the

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RZT approach, quantitative analysis of gene expression by RNA-ampliseq technology

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was used to identify differentially expressed genes (DEGs) at 32 hpf following

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exposure to seven serial dilutions of reference chemical BPA (10~10E-5µM) or each

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of four water samples ranging from wastewater to drinking water (relative enrichment

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factors 10~6.4E-4). The RZT-ampliseq-embryo approach was both sensitive and able

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to identify a wide spectrum of biological activities associated with BPA exposure.

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Finally, water quality was benchmarked based on the sensitivity distribution curve of

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biological pathways detected using RZT-ampliseq-embryo, and the most sensitive

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biological pathways were identified, including those linked with adverse reproductive

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outcomes, genotoxicity and development outcomes. RZT-ampliseq-embryo approach

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provides an efficient and cost-effective tool to prioritize toxicants based on

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responsiveness of biological pathways.

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1. INTRODUCTION

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A major challenge with regard to prioritizing environmental chemicals and/or

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assessing the hazard of complex mixtures is the lack of sufficient toxicological

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information for thousands of chemicals and endless possibility of mixtures. Toxicity

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pathway profiling could help to predict potential apical toxicity and prioritize and

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guide subsequent testing of the chemicals.1 Traditionally, monitoring and assessment

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of mixtures have relied on chemistry analyses. Although high throughput targeted and

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non-targeted analytical methods have been developed for detection of hundreds of

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chemicals present in complex environmental samples, chemical-focused analyses

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cannot detect contaminants with unknown structure, and cannot explain the

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cumulative toxicity of mixtures.2 Effect-based approaches, such as high content

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screening, can provide assessments of biological activity of environmental mixture.2

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However, most current cell-based HTS assays are limited in their coverage of

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biological pathways, and consequently their ability to predict a wide range of potential

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adverse outcomes.

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Our previous development on the reduced human transcriptome (RHT), which

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integrated a panel of 1200 core toxicologically relevant genes and dose-response

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modeling, has been shown to be an efficient and cost-effective approach to benchmark

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the water quality from wastewater to drinking water using human cell-based tests.3 To

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overcome the inherent limitations of single cell type and broaden the coverage of

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biological pathways in assessing toxicants, here a reduced transcriptome approach

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was developed using the zebrafish embryo as a multicellular test system. Zebrafish is

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an excellent experimental model to study chemical induced toxicity, because of its

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genetic similarity to humans and other vertebrates as well as its well characterized

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genome. Zebrafish embryo in particular has received considerable attention as an

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efficient alternative model that can be used to monitor altered molecular response

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induced by environmental stimuli, and linked with apical endpoints such as

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developmental and neuro toxicities. However, the utility of zebrafish model was

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significantly constrained in omics-based toxicological research due to the high cost

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and the lack of standardized bioinformatics protocols for dose-response modelling.

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Integrating genomic dose-response modeling into the hazard characterization with

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wide-range doses, particularly in lower, environmentally-relevant doses, has been

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seen to be valuable in risk assessment4. Genomic studies on a wide-range doses could

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help to determine new biomarkers and to derive point of departure for chemical risk

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assessment. For instance, certain endocrine disrupting chemicals have been reported

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to alter gene expression in a non-monotonic manner at low dose, which indicate

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potential novel molecular mechanism.5 In addition, application of multiple doses with

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single replicate using zebrafish embryo has been shown to effectively identify

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androgen-responsive genes.6 Concentration-dependent bioactivity of water samples

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could indicate potential early responses.7 Pathway analysis based on the active values

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of differentially concentration-dependent genes implicate the potential bioactivity of

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samples, which can be used in diagnostic analysis of chemical profiles.3 However,

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utilization of biological pathway responses derived from dose-dependent genomic

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data is still limited in hazard characterization.6, 8, 9

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The objectives of this study were three fold. The first was to curate a reduced gene

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list from zebrafish transcriptome (RZT) that can comprehensively represent biological

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pathways and toxicologically relevant processes, and be quantified by Ion Ampliseq

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Technology (RZT-ampliseq) (Figure 1). Second, we aimed to develop a chemical test

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protocol integrating RZT-ampliseq and dose-response modeling in zebrafish embryo

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(RZT-ampliseq-embryo). Bisphenol A (BPA), a well-studied endocrine disruptor

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frequently detected in water samples, was selected as a reference chemical. Finally,

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we wanted to evaluate the performance of RZT-ampliseq-embryo for use in hazard

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assessment of environmental mixtures. The mixture samples tested in this study were

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a set of water extracts which have been previously characterized by a battery of in

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vitro assays10 and reduced human transcriptome (RHT) method3.

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2. MATERIALS &METHODS

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2.1. Design of a gene set for reduced zebrafish transcriptome. The RZT gene set

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was selected to represent the key biological pathways and toxicologically relevant

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processes in zebrafish (Danio rerio) genome (Figure 1).

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associated with key biological pathways (in Entrez ID formats) was curated from

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three databases, including Kyoto Encyclopedia of Genes and Genomes (KEGG),11

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zebrafish orthologs of L1000 landmark genes12 and zebrafish orthologs of pathway

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reporter genes (Table 1).13 The centrality values of genes were calculated using

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CentiScaPe in Cytoscape software.14 Centrality values are node parameters

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demonstrating the relevant position of nodes in a whole network. Higher centrality

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First, a list of genes

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value suggests more central roles of a gene in biological pathways. Then the numbers

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of significantly enriched KEGG pathways and GO terms (adjusted p-value 0, Reads > 20) and the coefficient of

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variation (CV) (SD/Mean) of each gene’s expression abundance. For each gene, the

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relationship between CV and sequencing depth was fitted with loess model and then

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the minimum sequencing depth of ensuring CV < 15 % was calculated. To evaluate

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the mRNA profiling performance of ampliseq on the RZT gene set, the number of

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detected and undetected genes, as well as the each gene expression abundance

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measured by RZT-ampliseq were compared to that by microarray platform

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(GSE43186) and RNA-seq30 platform on 36 hpf zebrafish embryo. Correlations of the

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gene expression abundance between different technologies were calculated using

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number of reads per amplicon for RZT-ampliseq, RPKM (reads per kilo base per

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million reads) values for RNA-seq and signal intensity values for microarray

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technology. Finally, to evaluate the repeatability of RZT-ampliseq, the CV of RZT

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gene set in zebrafish embryos of 0.1% DMSO (n=3) from six batches were analyzed

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using the edge package.27

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Pathway-level and biological process validation. For single dose experiment,

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functional enrichment analysis of identified DEGs was performed using a one-sided

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Fisher’s exact test on GO of Biological Process (BP), and KEGG pathways with RZT

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gene list (Table S5) as background. For full dose experiment, the EC values of GO

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terms and KEGG pathways were calculated as the geometric mean of EC values of

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matched DEGs. Only GO terms or KEGG pathways matched by at least three genes

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were included in EC calculation and further analysis. Finally, to analyze overall

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biological potency of each sample, the proportionally ranked distribution of GO and

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KEGG of EC values was fitted with a four-parameter dose-response curve using

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GraphPad Prism 5.0 software (San Diego, CA, U.S.A.).

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The molecular responses profiling (DEGs, KEGG pathways of DEGs) of 0.1 µM

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BPA treatment by RZT-ampliseq were compared with whole transcriptome analysis

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of BPA archived in NCBI.31 To compare RZT-ampliseq-embryo approach with

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existing Toxcast high throughput in vitro assays with regard to biological activities

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associated with BPA exposure, the responsive gene endpoints and molecular

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pathways (KEGG, GO BP terms) identified by the both methods were evaluated. The

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responsive molecular gene endpoints were DEGs captured by dose-response model

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analysis of RZT- ampliseq-embryo. The responsive genes of Toxcast in vitro assay

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were

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(https://www.epa.gov/chemical-research/toxicity-forecaster-toxcasttm-data).

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responsive molecular endpoints were converted to zebrafish orthologous genes.

download

from The

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2.5 Comparison of RZT with in vitro bioassays & RHT method on mixtures. A

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supervised approach was used to assess the RZT representation of the previous in

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vitro bioassays. First, gene sets associated with cellular toxicity pathways tested by in

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vitro bioassays were manually curated from Wiki Pathways and Gene Ontology,

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KEGG (Table S6). Then the EC of each pathway was calculated by the geometric

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mean of the ECs of matched DEGs. Pathway patterns identified by the RZT approach

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was shown by heatmap using gplot package.32 The hierarchical clusters of water

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samples identified by RZT analysis were compared with the results of in vitro

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bioassays.

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To evaluate the sensitivity and specificity of RZT-ampliseq-embryo in

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identification of bioactivity of mixtures, the results of RZT-ampliseq-embryo were

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compared to that by RHT-ampliseq using human HepG2 and MCF7 cells3 on the

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same sample set. Briefly, the sensitivity of 50% biological potency of water samples

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identified by RZT were compared with those identified by RHT in HepG2 and MCF7

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cells in terms of KEGG or GO. In addition, linear regression was conducted on values

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of 50% biological potency identified by RZT and RHT. Finally, the coverage of most

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sensitive pathways (top 20 sensitive KEGG pathways) of Eff2, the sample with

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potential highest and broadest bioactivity were compared between RZT and RHT

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approaches.

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3. RESULTS AND DISCUSSION

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3.1. Development of RZT testing method using zebrafish embryo

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In silico validation of RZT gene set. The developed RZT gene set consists of 1637

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zebrafish Entrez ID genes, including a list of 1000 genes with greatest pathway

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centrality scores and a list of 724 toxicology-relevant genes. The 1000

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pathway-central genes were shown to be the minimum number of genes representing

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the maximum biological pathways in terms of GO BP terms and KEGG pathways

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(Figure 2A). Toxicology-relevant genes (n=724) were selected to provide linkages

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between molecular mechanism and apical endpoints (Table 1). Then 44 genes were

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removed by the online designer either because their background expression was too

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high or too low, or because effective multiplexed primers could not be designed

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(Table S7). This resulted in 1637 genes as the final RZT gene set (Table S5).

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The RZT gene set showed a broad coverage of biological pathways, where 95%

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KEGG pathways and 94% GO BP terms were represented by at least one gene in RZT

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gene set (Figure 2B and C). The uncovered pathways were mainly associated with

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basic metabolic processes (Table S8). Furthermore, the RZT gene set of 1637 genes

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were significantly enriched in 29 KEGG pathways and 839 GO BP terms (adjusted

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p0) were detected in all 32hpf embryo RNA samples (n=18)

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under sequencing depth of one million (Figure S5A). Of the 179 genes not detected

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(count=0) in 32 hpf embryo by RZT-ampliseq, 47 genes were consistently undetected

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in 36 hpf embryo in a previous RNA-seq study

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detected by RNA-seq instead of RZT-ampliseq platform, 86% (93 out of 108) had

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normalized reads less or equal than 10 counts (RPKM), among which 72% (79 out of

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108 genes) had a sequence read below 1 count. Nine genes weren’t detected by

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RNA-seq but were detected by RZT-ampliseq platform, among which 5 genes had a

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normalized read below 10. The mRNA expression abundances quantified by

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RZT-ampliseq and RNA-seq platform showed a nearly linear relation (R= 0.81)

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between two platforms for the 1270 gene transcripts detected by both (counts>0)

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(Figure S5B). Moreover, out of 82 transcripts that were not detected by RZT-ampliseq

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but were detected by microarray, only 29 were above 8 on log2 scale (Figure S5C, D).

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A similar linear relationship (R=0.77) was observed for the 1254 common genes

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between the RZT-ampliseq approach and a microarray platform (Figure S5D).

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. Among the other 108 genes

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3.2. RZT assessment of a classical chemical: BPA.

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The RZT approach showed good repeatability for quantifying transcriptional

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response to chemical by zebrafish embryo. Common CV of 32 hpf embryo mRNA

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samples exposed to 0.1% DMSO from 8-32 hpf were 13% (biological replication

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within

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RZT-ampliseq-embryo (Figure S6). This variation was acceptably low when

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compared with other RNA profiling technology, such as qPCR (CV: 1% ~ 15%),

one

batch),

14%

(biological

replication

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batch)

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microarray (CV:5% ~ 15%) or RNA-seq (CV:10% ~ 15%).33 After exposure of two

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independent batches of embryos to a single dose of 10 µM BPA, 67, 45 DEGs

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(ANOVA, p=3) were identified in two platforms, but these

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were only involved in fundamental apoptosis process (FoxO signaling pathway, p53

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signaling pathway) and regulation of actin cytoskeleton (Figure S8). However, 98

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DEGs were identified by dose-response analysis of the embryo exposed to the seven,

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10-fold, dilutions of BPA (10 E-5 ~10 µM). Three and five of the DEGs identified by

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dose-response analysis were also detected as DEGs in embryos exposed to 10 and 0.1

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µ M, respectively (Figure S7A).

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One significant advantage of dose-response analysis by RZT-ampliseq is the

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sensitivity analysis of genes and biological pathways in response to chemicals, which

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could aid inference regarding the potentially sensitive apical endpoint effects. The

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responsive DEGs were mainly fitted with U-shaped models, which suggest that the

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mode of hormesis dominates the low dose response of transcriptome (Figure S7C).

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However, there are alternative interpretations other than true hormesis. For example,

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the time-course of dynamic transcriptional response may be different at different

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doses, such that at higher doses, the transcript abundance may have peaked earlier but

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has fallen by 32 h.

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higher doses, associated with triggering more and more AOPs in the organism,

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thereby causing more and more disruption of normal development. What is effectively

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a monotonic response to the chemical may produce a non-monotonic dose-response

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for a given snap-shot in time. The response genes (ECRW >DW). The EC values of the most sensitive

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KEGG or GO pathways of DW samples were 1-2 orders of magnitude higher than

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those of effluent samples, suggesting relatively weak biological effects were induced

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by DW. (Figure S14)

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The enriched pathways in RZT analysis could be used to prioritize potential

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biological endpoints for future assessment. Specifically, the most sensitive KEGG or

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GO BP pathways may be linked with adverse outcome. For instance, the top 20%

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sensitive KEGG or GO BP pathways of Eff2 were mainly associated with adverse

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reproductive outcomes, genotoxicity and development outcomes (Figure S10). The

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most sensitive RZT profile of MF samples was associated with the adverse outcome

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of endocrine system disturbance and development. For DW, the most sensitive

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responses were also associated with genotoxicity, which might be due to the fact that

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the samples of metropolitan drinking water treatment plant contained toxic

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“byproduct” chemicals from chlorination9. All development relevant pathways (GO

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terms, each covered at least 3 DEGs suggested Eff2 and MF samples might induce

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potential development toxicity while RW and DW samples may not (Figure 4A). The

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predicted adverse outcomes were corroborated by zebrafish embryo 48hpf lethality

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and 120hpf sub-lethal development experiment 9(Figure 4A).

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The RZT-ampliseq-embryo method provided more sensitive pathway profiles for

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the four water samples comparable to the previous 103 in vitro bioassays. (Figure

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S11) First, the RZT profiling analysis revealed similar pattern although with greater

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sensitivity than the in vitro bioassays. Similar to the in vitro cell-based bioassays,

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RZT-ampliseq-embryo approach could clearly distinguish wastewater (Eff2, MF)

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from reclaimed or clean water samples (DW, RW). Biological responses associated

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with genotoxicity and oxidative stress responses, xenobiotic metabolism, PR,

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RAR/RXR were identified using both RZT-ampliseq-embryo and in vitro bioassays.

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However, the RZT method identified weak TR and hypoxia-related responses (RPE:

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0-10), which were not detected in the in vitro assays. The sensitive detection on the

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thyroid hormone signaling pathways by the RZT-ampliseq-embryo method might be

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contributed by the active involvement of TR pathway during zebrafish embryo

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development. However, the RZT profile showed low sensitivity for ER and GR,

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which comes as no surprise, because ER and GR would show high sensitivity at 48hpf

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or later phase zebrafish embryo37.

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The RZT approach provided a broader biological coverage than in vitro cell-based

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bioassays which focused on preselected biomarkers assessment. Thus, the RZT

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approach could support more comprehensive assessment of biological effects of

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environmental samples. Beside the responsive endpoints in vitro bioassays, the RZT

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approach also identify other biological responses such as development and

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reproduction-related pathways, some of which might be linked to AOPs of regulatory

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concerns. For example, profiling analysis on the enriched KEGG pathways (Figure

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S12) indicated that Eff2, MF samples other than RW, DW samples exhibited potential

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development toxicity by inducing several relevant pathway responses, including

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VEGF signaling pathway, Hedgehog signaling pathway and Vascular smooth muscle

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contraction. An established AOPs “disruption of VEGFR signaling leading to

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developmental defects” ( https://aopwiki.org/wiki/index.php/Aop:43) might be used to

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guide the prediction of developmental risk by the observed molecular event.

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Additionally, Hedgehog pathway was verified to play an essential role in

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cardiomyocyte differentiation and heart morphogenesis in model species including

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mouse38 and zebrafish39. Furthermore, wastewater Eff2 and MF samples showed

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prominent pathway effects involved in the reproductive axis including oocyte meiosis,

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TGF-beta signaling pathway, progesterone-mediated oocyte maturation, GnRH

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signaling pathway, ErbB signaling pathway. However, inlet and outlet samples of

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metropolitan drinking water treatment plant (RW, DW) showed very weak

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reproduction-related effects.

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3.4 Comparison between RZT-embryo and RHT cells profiles of water samples.

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Although only four common water samples were tested by RZT and RHT

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approaches, the water quality of four water samples ranked by 50% biological potency

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identified by RZT-embryo were consistent with those by RHT in MCF7 and HepG2

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cells (Figure S13,S14). The values of 50% biological potency by RZT-embryo

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correlated well with those by RHT in MCF7 (R2=0.95) in terms of GO (Figure S13),

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and correlated well with those by RHT in HepG2 (R2=0.95) in terms of KEGG

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(R2=0.99) (Figure S14).

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RZT-embryo also provided different profiles of altered genes & pathways of the

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four water samples from that by RHT approach, which might be due to the greater

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biological complexity represented by a fish embryo, compared to a single cell type.

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The most sensitive pathways identified by RZT following exposure to the water

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samples was distinct with those by RHT in HepG2 and MCF7. Take Eff2 for example

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(Figure 4B), only four KEGG pathways were overlapped between the 20 most

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sensitive pathways (with lowest EC values) identified by RZT-embryo and RHT in

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HepG2 and MCF7 cells. Nine of the 20 most sensitive pathways uniquely identified

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by RZT-embryo were associated with basic biological processes, which may suggest

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that rapidly developing and differentiating zebrafish embryos were more sensitive to

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alterations of basic processes, such as oxidative phosphorylation, than the single

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cell-type in vitro system. Moreover, the most sensitive KEGG pathways identified by

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RHT in HepG2 and RHT in MCF7 showed cell-type responses, such as pathways

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involved in immune response and cellular communication, which were not among in

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the most sensitive KEGG pathways by RZT-embryo assay. However, some cell-type

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specific responses, including endocrine response in MCF7 and metabolism response

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in HepG2, were also identified by RZT as sensitive KEGG pathways responding to

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Eff2.

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The RZT-embryo approach was more sensitive than RHT in HepG2 and MCF7

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cells in terms of estimating 50% biological potency of water samples. The value of 50%

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biological potency of each sample identified by RZT was generally one order of

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magnitude less than that identified by RHT in either HepG2 or MCF7 (Figure S13,14,

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Table S3A, B). Furthermore, a distinct pathway sensitivity distribution in response to

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the MF sample was identified by RZT-embryo compared to RHT in HepG2 and

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MCF7 cells. Although the potency of the median sensitive pathway (50% biological

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potency) following exposure to MF was lower than that of RW and DW in

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RZT-embryo, MF was more potent than that of RW and DW at the most sensitive

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pathways which were profiled by the RZT-embryo. (Figure 13, 14) These highly

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sensitive biological responses induced by MF were primarily related to embryo

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(eg.

heart

jogging,

embryo

pattern

specification,

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development

notochord

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development, determination of left/right symmetry) (Figure 4A), which might be

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related to developmentally toxic pollutants present in the MF sample. The MF sample

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was water taken after microfiltration using filters disinfected by chlorination to avoid

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biofouling in a water reclamation plant, in which micro-pollutants of such as

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carbamazepine, a teratogen, with the highest detected concentrations (1.9 µg / L) out

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of ten sample24 were present. Carbamazepine has been reported to disturb embryonic

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development with increasing hatching rate, body length, swim bladder appearance and

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yolk sac absorption rate at 1µg/L.40 However, knowledge gaps associated with

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unknown chemicals present in the mixtures and their potential combined effects still

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exist in toxicological assessment of these environmental samples. An effect-directed

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analysis (EDA) integrating extract fractionation and instrument analysis with the

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sensitive RZT approach may be used to identify the chemicals responsible for the

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observed effect in future.

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In conclusion, we developed a RZT approach by integrating reduced transcriptome,

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RNA-ampliseq technology and a zebrafish embryo test as a novel approach to assess

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environmental toxicant. First, the RZT approach by multiple dose-response analysis

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could identify early molecular response and molecular mechanism of single chemical

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which would help to predict apical effect. Additionally, the RZT approach has

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potential to be used to evaluate and prioritize chemicals for further testing and

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potentially to predict adverse outcomes. Second, RZT-ampliseq-embryo approach

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effectively discriminated relatively clean from more polluted environmental samples,

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and the responsive pathways revealed by RZT analysis could help to prioritize

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targeted biological end points for future assessment. Future studies should explore the

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utility of other stages, such as 48hpf (sensitivity for endocrine disrupting effects), in

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the identification of early molecular response for assessing the hazard potencies of

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environmental toxicants in early developmental stage.

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Acknowledgements. For support, we thank National Natural Science Foundation of

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China (Grant No. 21322704), Environmental Protection Foundation of Jiangsu

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(ZX2015009) and the European Union Seventh Framework Programme (The

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SOLUTIONS project, grant 603437). P.X. was supported by Program B for

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Outstanding Ph.D. Candidates of Nanjing University (No. 201701B018). X.Z. was

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supported by the Fundamental Research Funds for the Central Universities. Thanks

539

Professor Beate Escher and Eutox, UQ for provision of the water samples and for

540

helpful discussion. Mention of trade names or commercial products does not

541

constitute endorsement or recommendation for use by the U.S. Environmental

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Protection Agency.

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Supporting Information

545 546 547

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.est.xxxxx. Description of methods for estimating transcriptional point of departure (PODt); S2,

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CV change with different reads count of all genes; fourteen figures and eight tables

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(PDF, XLSX)

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REFERENCE 1.

Kavlock, R.; Chandler, K.; Houck, K.; Hunter, S.; Judson, R.; Kleinstreuer, N.; Knudsen, T.; Martin,

M.; Padilla, S.; Reif, D.; Richard, A.; Rotroff, D.; Sipes, N.; Dix, D., Update on EPA's ToxCast Program: Providing High Throughput Decision Support Tools for Chemical Risk Management. Chem. Res. Toxicol. 2012, 25, (7), 1287-1302. 2.

Altenburger, R.; Ait-Aissa, S.; Antczak, P.; Backhaus, T.; Barcelo, D.; Seiler, T.-B.; Brion, F.; Busch,

W.; Chipman, K.; Lopez de Alda, M.; de Aragao Umbuzeiro, G.; Escher, B. I.; Falciani, F.; Faust, M.; Focks, A.; Hilscherova, K.; Hollender, J.; Hollert, H.; Jaeger, F.; Jahnke, A.; Kortenkamp, A.; Krauss, M.; Lemkine, G. F.; Munthe, J.; Neumann, S.; Schymanski, E. L.; Scrimshaw, M.; Segner, H.; Slobodnik, J.; Smedes, F.; Kughathas, S.; Teodorovic, I.; Tindall, A. J.; Tollefsen, K. E.; Walz, K.-H.; Williams, T. D.; Van den Brink, P. J.; van Gils, J.; Vrana, B.; Zhang, X.; Brack, W., Future water quality monitoring - Adapting tools to deal with mixtures of pollutants in water resource management. Sci. Total Environ. 2015, 512, 540-551. 3.

Xia, P.; Zhang, X.; Zhang, H.; Wang, P.; Tian, M.; Yu, H., Benchmarking Water Quality from

Wastewater to Drinking Waters Using Reduced Transcriptome of Human Cells. Environ. Sci. Technol. 2017, 51, (16), 9318-9326. 4.

Beausoleil, C.; Ormsby, J.-N.; Gies, A.; Hass, U.; Heindel, J. J.; Holmer, M. L.; Nielsen, P. J.; Munn,

S.; Schoenfelder, G., Low dose effects and non-monotonic dose responses for endocrine active chemicals: Science to practice workshop: Workshop summary. Chemosphere 2013, 93, (6), 847-856. 5.

Faulk, C.; Kim, J. H.; Jones, T. R.; McEachin, R. C.; Nahar, M. S.; Dolinoy, D. C.; Sartor, M. A.,

Bisphenol A-associated alterations in genome-wide DNA methylation and gene expression patterns reveal sequence-dependent and non-monotonic effects in human fetal liver. Environ. Epigenet. 2015, 1, (1). 6.

Fetter, E.; Smetanova, S.; Baldauf, L.; Lidzba, A.; Altenburger, R.; Schuettler, A.; Scholz, S.,

Identification and Characterization of Androgen-Responsive Genes in Zebrafish Embryos. Environ. Sci. Technol. 2015, 49, (19), 11789-11798.

ACS Paragon Plus Environment

Page 28 of 36

Page 29 of 36

Environmental Science & Technology

598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640

7.

Berninger, J. P.; Martinovic-Weigelt, D.; Garcia-Reyero, N.; Escalon, L.; Perkins, E. J.; Ankley, G. T.;

Villeneuve, D. L., Using Transcriptomic Tools to Evaluate Biological Effects Across Effluent Gradients at a Diverse Set of Study Sites in Minnesota, USA. Environ. Sci. Technol. 2014, 48, (4), 2404-2412. 8.

Thomas, R. S.; Allen, B. C.; Nong, A.; Yang, L.; Bermudez, E.; Clewell, H. J., III; Andersen, M. E., A

method to integrate benchmark dose estimates with genomic data to assess the functional effects of chemical exposure. Toxicol. Sci. 2007, 98, (1), 240-248. 9.

Smetanova, S.; Riedl, J.; Zitzkat, D.; Altenburger, R.; Busch, W., High-throughput

concentration-response analysis for omics datasets. Environ. Toxicol. Chem. 2015, 34, (9), 2167-2180. 10. Escher, B. I.; Allinson, M.; Altenburger, R.; Bain, P. A.; Balaguer, P.; Busch, W.; Crago, J.; Denslow, N. D.; Dopp, E.; Hilscherova, K.; Humpage, A. R.; Kumar, A.; Grimaldi, M.; Jayasinghe, B. S.; Jarosova, B.; Jia, A.; Makarov, S.; Maruya, K. A.; Medvedev, A.; Mehinto, A. C.; Mendez, J. E.; Poulsen, A.; Prochazka, E.; Richard, J.; Schifferli, A.; Schlenk, D.; Scholz, S.; Shiraish, F.; Snyder, S.; Su, G.; Tang, J. Y. M.; van der Burg, B.; van der Linden, S. C.; Werner, I.; Westerheide, S. D.; Wong, C. K. C.; Yang, M.; Yeung, B. H. Y.; Zhang, X.; Leusch, F. D. L., Benchmarking Organic Micropollutants in Wastewater, Recycled Water and Drinking Water with In Vitro Bioassays. Environ. Sci. Technol. 2014, 48, (3), 1940-1956. 11. Collins, F. S.; Gray, G. M.; Bucher, J. R., Toxicology. Transforming environmental health protection. Science 2008, 319, (5865), 906-7. 12. Duan Q, R., SP, Clark NR, Wang Z, Fernandez NF, Rouillard AD, Readhead B, Tritsch SR, Hodos R, Hafner M, Niepel M, Sorger PK, Dudley JT, Bavari S, Panchal RG, Ma’ayan A, L1000CDS2: LINCS L1000 characteristic direction signatures search engine. NPJ. Syst. Biol. Appl. 2016, 2, (16015). 13. Zhang, J. D.; Küng, E.; Boess, F.; Certa, U.; Ebeling, M., Pathway reporter genes define molecular phenotypes of human cells. BMC Genomics 2015, 16, (1), 342. 14. Scardoni, G.; Petterlini, M.; Laudanna, C., Analyzing biological network parameters with CentiScaPe. Bioinformatics 2009, 25, (21), 2857. 15. Yu, G.; Wang, L. G.; Han, Y.; He, Q. Y., clusterProfiler: an R package for comparing biological themes among gene clusters. Omics : a journal of integrative biology 2012, 16, (5), 284-7. 16. Villeneuve, D. L.; Garcia-Reyero, N.; Martinović-Weigelt, D.; Li, Z.; Watanabe, K. H.; Orlando, E. F.; Lalone, C. A.; Edwards, S. W.; Burgoon, L. D.; Denslow, N. D., A graphical systems model and tissue-specific functional gene sets to aid transcriptomic analysis of chemical impacts on the female teleost reproductive axis. Mutat. Res. 2011, 746, (2), 151-162. 17. Jiang, J.; Wu, S.; Wu, C.; An, X.; Cai, L.; Zhao, X., Embryonic exposure to carbendazim induces the transcription of genes related to apoptosis, immunotoxicity and endocrine disruption in zebrafish (Danio rerio). Fish Shellfish Immunol. 2014, 41, (2), 493-500. 18. Li, Y.; Qi, X.; Yang, Y.-W.; Pan, Y.; Bian, H.-M., Toxic effects of strychnine and strychnine N-oxide on zebrafish embryos. Chin. J. Nat. Med. 2014, 12, (10), 760-767. 19. Guiu, J.; Bergen, D. J. M.; De Pater, E.; Islam, A. B. M. M. K.; Ayllon, V.; Gama-Norton, L.; Ruiz-Herguido, C.; Gonzalez, J.; Lopez-Bigas, N.; Menendez, P.; Dzierzak, E.; Espinosa, L.; Bigas, A., Identification of Cdca7 as a novel Notch transcriptional target involved in hematopoietic stem cell emergence. J. Exp. Med. 2014, 211, (12), 2411-2423. 20. Verleyen, D.; Luyten, F. P.; Tylzanowski, P., Orphan G-Protein Coupled Receptor 22 (Gpr22) Regulates Cilia Length and Structure in the Zebrafish Kupffer's Vesicle. PLoS One 2014, 9, (10) :e110484.

ACS Paragon Plus Environment

Environmental Science & Technology

641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683

21. Wanglar, C.; Takahashi, J.; Yabe, T.; Takada, S., Tbx Protein Level Critical for Clock-Mediated Somite Positioning Is Regulated through Interaction between Tbx and Ripply. PLoS One 2014, 9, (9) :e107928. 22. Xu, M.; Liu, D.; Dong, Z.; Wang, X.; Wang, X.; Liu, Y.; Baas, P. W.; Liu, M., Kinesin-12 Influences Axonal Growth During Zebrafish Neural Development. Cytoskeleton 2014, 71, (10), 555-563. 23. Xu, M.; Liu, D.; Dong, Z.; Wang, X.; Wang, X.; Liu, Y.; Baas, P. W.; Liu, M., Kinesin-12 influences axonal growth during zebrafish neural development. Cytoskeleton 2014, 71, (10), 555-63. 24. Bluhm, K.; Otte, J. C.; Yang, L.; Zinsmeister, C.; Legradi, J.; Keiter, S.; Kosmehl, T.; Braunbeck, T.; Straehle, U.; Hollert, H., Impacts of Different Exposure Scenarios on Transcript Abundances in Danio rerio Embryos when Investigating the Toxicological Burden of Riverine Sediments. PLoS One 2014, 9, (9) :e106523. 25. Robinson, M. D.; McCarthy, D. J.; Smyth, G. K., edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010, 26, (1), 139-40. 26. Farmahin, R.; Williams, A.; Kuo, B.; Chepelev, N. L.; Thomas, R. S.; Barton-Maclaren, T. S.; Curran, I. H.; Nong, A.; Wade, M. G.; Yauk, C. L., Recommended approaches in the application of toxicogenomics to derive points of departure for chemical risk assessment. Arch. Toxicol. 2017, 91, (5), 2045-2065. 27. Robinson, M. D.; McCarthy, D. J.; Smyth, G. K., edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010, 26, (1), 139-140. 28. Ritz, C.; Streibig, J. C.; Leeuw, J. D.; Zeileis, A., Bioassay Analysis Using R. J. STAT. SOFTW. 2005, 12, (i05), 1-22. 29. Bornkamp, B.; Pinheiro, J.; Bretz, F., DoseFinding: Planning and Analyzing Dose Finding experiments. 2016. 30. Yang, H.; Zhou, Y.; Gu, J.; Xie, S.; Xu, Y.; Zhu, G.; Wang, L.; Huang, J.; Ma, H.; Yao, J., Deep mRNA Sequencing Analysis to Capture the Transcriptome Landscape of Zebrafish Embryos and Larvae. PLoS One 2013, 8, (6) :e64058. 31. Saili, K. S.; Tilton, S. C.; Waters, K. M.; Tanguay, R. L., Global gene expression analysis reveals pathway differences between teratogenic and non-teratogenic exposure concentrations of bisphenol A and 17 beta-estradiol in embryonic zebrafish. Reprod. Toxicol. 2013, 38, 89-101. 32. Warnes, G. R.; Bolker, B.; Bonebakker, L.; Gentleman, R.; Huber, W.; Liaw, A.; Lumley, T.; Maechler, M.; Magnusson, A.; Moeller, S., gplots: various R programming tools for plotting data. 2016. 33. Zhang, J. D.; Schindler, T.; Kueng, E.; Ebeling, M.; Certa, U., Highly sensitive amplicon-based transcript quantification by semiconductor sequencing. BMC Genomics 2014, 15 :565. 34. Kinch, C. D.; Ibhazehiebo, K.; Jeong, J.-H.; Habibi, H. R.; Kurrasch, D. M., Low-dose exposure to bisphenol A and replacement bisphenol S induces precocious hypothalamic neurogenesis in embryonic zebrafish. Proc. Natl. Acad. Sci. U. S. A. 2015, 112, (5), 1475-1480. 35. Wang, C.; Zhang, J.; Li, Q.; Zhang, T.; Deng, Z.; Lian, J.; Jia, D.; Li, R.; Zheng, T.; Ding, X.; Yang, F.; Ma, C.; Wang, R.; Zhang, W.; Wen, J. G., Low concentration of BPA induces mice spermatocytes apoptosis via GPR30. Oncotarget 2017, 8(30):49005-49015. 36. Wu, M.; Pan, C.; Chen, Z.; Jiang, L.; Lei, P.; Yang, M., Bioconcentration pattern and induced apoptosis of bisphenol A in zebrafish embryos at environmentally relevant concentrations. Environ. Sci. Pollut. Res. Int. 2017, 24, (7), 6611-6621.

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Environmental Science & Technology

684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708

37. Schiller, V.; Wichmann, A.; Kriehuber, R.; Schaefers, C.; Fischer, R.; Fenske, M., Transcriptome alterations in zebrafish embryos after exposure to environmental estrogens and anti-androgens can reveal endocrine disruption. Reprod. Toxicol. 2013, 42, 210-223. 38. Zhang, X. M.; Ramalho-Santos, M.; McMahon, A. P., Smoothened mutants reveal redundant roles for Shh and Ihh signaling including regulation of L/R asymmetry by the mouse node. Cell 2001, 105, (6), 781-792. 39. Hami, D.; Grimes, A. C.; Tsai, H.-J.; Kirby, M. L., Zebrafish cardiac development requires a conserved secondary heart field. Development 2011, 138, (11), 2389-2398. 40. Qiang, L.; Cheng, J.; Yi, J.; Rotchell, J. M.; Zhu, X.; Zhou, J., Environmental concentration of carbamazepine accelerates fish embryonic development and disturbs larvae behavior. Ecotoxicology 2016, 25, (7), 1426-1437.

Table 1. Sources and selection criteria of reduced zebrafish transcriptome (RZT) gene panel. 1000 core genes were selected by their central roles in the network of genes collected from public databases. A final list was union of the 1000 core genes and toxicology-relevant genes. Category of genes

Public databases Core genes

Toxicology-relevant genes RZT gene panel

Number of zebrafish orthologs 4260 1022 1019 1000 326 173 176 152 1637

Sources KEGG database18 L1000 landmark genes19 Pathway reporter genes20 Selected by their central roles in the gene network ToxCast AOP wiki Graphical gene model23 Retrieved from references24-31 Core genes + toxicology-relevant genes

709 710 711

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712 713 714 715 716 717 718 719 720 721 722 723 724 725 726

Table 2. Treatments and exposure design for the validation of reduced zebrafish transcriptome (RZT) approach using embryo test with exposure time of 8-32hpf. Type

Treatment

Solvent

DMSO

Single Chemical

Exposure level

Dimethyl Sulfoxide

0.1% DMSO (6 batches, n=3)

BPA

Bisphenol A

Eff2

Secondary sewage effluent Microfiltration treated effluent River water

MF Mixture

Description

25

RW DW a

10~10E-5 (µM) with 10-fold dilution, 0.1, 10 µM (n=3) b, 10 µM (n=3 of second batch)

10~6.4E-4 (REFa) with 5-fold dilution

Drinking water b

REF: relative enrichment factor. If not otherwise stated, all treatment groups were with a single replicate in addition to three vehicle controls (0.1% DMSO)

727

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Figure 1. Design and workflow of the reduced zebrafish transcriptome (RZT) approach. RZT-ampliseq, RZT genes were quantified by Ion Ampliseq Technology; RZT-ampliseq-embryo, a chemical test protocol integrating RZT-ampliseq and dose-response modeling in zebrafish embryo; EC, effect concentration; DEGs, differentially expressed genes. 83x156mm (300 x 300 DPI)

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Figure 2. Selection and in silico validation of RZT gene set list. (A) Investigation of minimum number of candidate genes for representing the maximal biological pathways including KEGG pathways and GO BP terms. The number of significantly enriched biological pathways was according to the number of candidate genes ranked by their centrality scores. The curves were fitted into Gaussian model. The red dash line means the cut-off of 1000, where the number of top ranked candidate genes may be low enough for representing maximal biological pathways. The percentage of biological pathways coverage of (B) KEGG pathways and (C) GO BP terms by 1637 genes from RZT gene set. (D, E) Comparison on the point of departure (PODt) estimated by RZT gene and the whole transcriptome in previously published studies (EMTAB-832 and GSE55618, respectively). The distributions of PODt estimated by ten approaches using RZT gene set (blue) and whole zebrafish genome (yellow) were showed in boxplot. The black bold lines represent PODt. The number represents the ratio of PODt between by RZT gene set and whole genome (larger value to smaller value). In plot (D), the solid lines represent LOAEL (13.5 µM) for pericardial edema (green line), and LOAEL (28 µM) for malformed heart (red line) induced by flusilazole in zebrafish embryo at 24 hpf. The

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dashed lines represent 3-fold ranges of corresponding LOAELs. In plot (E), the solid and dashed red lines represent 1/3 and 1/10 values of LOAEL (8 mM) for liver damage induced by isoniazid in zebrafish embryo reported by Zhang12.

83x139mm (300 x 300 DPI)

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Figure 3. Concentration-dependent network of differentially expressed genes (DEGs) (p=3 were included in this analysis. Common molecular endpoints were labeled by red triangle. Pathway scores (EC or AC50 value) were the geometric mean of the effect concentrations (ECs) (RZT-ampliseq-embryo) or AC50 (Toxcast) values of the relevant genes. The horizontal distance of 50% biological potency between RZT-ampliseq-embryo and Toxcast in vitro assays was labeled in red.

72x260mm (300 x 300 DPI)

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Figure 4. (A) Development-related biological processes affected by four water samples from RZT-ampliseqembryo in 32 hpf. Plotted were log 10 EC values with a unit of REF (relative enrichment factor). (B) Venn diagram of top 20 sensitive KEGG pathways ranked by EC values identified by RZT, RHT in HepG2 and RHT in MCF7, respectively, for Eff2 sample. The labels of “zebrafish” in blue, “HepG2” in yellow and “MCF7” in green stand for approaches of RZT, RHT in HepG2 and RHT in MCF7, respectively. The labels in red stand for the main function of KEGG pathways. 84x196mm (300 x 300 DPI)

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