The emerging PFOS alternative OBS exposure induced gut microbiota dysbiosis and hepatic metabolism disorder in adult zebrafish

Comparative Biochemistry and Physiology, Part C 230 (2020) 108703

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The emerging PFOS alternative OBS exposure induced gut microbiota dysbiosis and hepatic metabolism disorder in adult zebrafish Caiyun Wang, Yao Zhao, Yuanxiang Jin

T

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College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou 310032, China

A R T I C LE I N FO

A B S T R A C T

Keywords: OBS Zebrafish Gut microbiota Metabolism Gene expression

Sodium ρ-perfluorous nonenoxybenzene sulfonate (OBS), as a novel the alternatives of PFASs, is widely used in many fields of life. Here, adult male zebrafish selected were exposed to OBS at concentrations of 3, 30 and 300 μg/L for 7 and 21 days, respectively. Based on the gut microbiota analysis, at genus level, the relative abundance of the Flavobacterium, Hyphomicrobium, Paracoccus, Lawsonia, Plesiomonas and Vibrio changed significantly in the gut of zebrafish after exposure to 300 μg/L OBS. In addition, the liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis suggested that a total of 1077 metabolites in pos-model and a total of 706 metabolites in neg-model changed significantly from the liver, and these changed metabolites were tightly related to several pathways including amino acid, pyrimidine and purine metabolism, etc. Furthermore, the changed gut bacteria including Flavobacterium, Hyphomicrobium, Paracoccus, Lawsonia, Plesiomonas and Vibrio at genus level were significantly correlated with various metabolites (succinic acid, leucine, xanthine, orotic acid, nicotinic acid, etc.). Taken together, all the results showed that low dose of OBS exposure could induce the dysbiosis of gut microbiota and disturbed the hepatic metabolism balance in adult male zebrafish.

1. Introduction Since the 1950s, because of their excellent thermal stability, high surface activity and hydrophobic oleophobic properties (Z. Wang et al., 2017), polyfluoroalkyl/perfluoroalkyl substances (PFASs) have been widely used in chemical plating, coatings, textiles, leather, synthetic detergents, etc. Recently, with more and more research on PFAS, it has been found that they have the property of refractory, long-distance migration, bioaccumulation and cause the various toxic effects to animals. As a consequence, most PFASs have been banned from production in some countries now. However, PFASs still were detected in various environmental media worldwide (Chen et al., 2016; Ge et al., 2017; Jovicic et al., 2018; Fagbayigbo et al., 2018) owing to their characteristics. Toxicological studies have shown that PFASs have organ toxicity, immune toxicity, endocrine toxicity, etc. to animals (Rand and Mabury, 2017; Elcombe et al., 2012; Viberg et al., 2013). And some PFASs, which are listed as persistent organic pollutants (POPs) in Annex B under the Stockholm Convention (UNEP-POPS, 2009), have been extensively detected in environment, wildlife and even human (Giesy and Kannan, 2001;Olsen et al., 2003; Olsen et al., 2005; Lau et al., 2007; Cui et al., 2018). Recently, Perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) are the most productive PFASs (Liu et al., 2017a), which ⁎

are widely detected in the environment (Wang et al., 2014; Liu et al., 2015). Due to the long carbon chain and high energy fluorocarbon bonds of PFOS/PFOA, they were highly stable and also known as persistent organic pollutants (Zhang et al., 2019). Therefore, some commercial substitutes for short carbon chain or semi-fluorinated analogues with transfer characteristics are emerging (Zhou et al., 2018). The novel PFASs compound, sodium ρ-perfluorous nonenoxybenzene sulfonate (OBS), is one of the widely used alternatives. With the lower production costs and relatively higher cost performance, it is often used in the fire protection industry, oil extraction, steel plate cleaning, printing, electroplating and other industrial fields (Bao et al., 2017). Subsequently, the environmental pollution problems inevitably followed. It had been detected in the lake near the first oil well of the Daqing oil field, and the highest concentration of OBS even reached 3.2 × 103 ng/L (Xu et al., 2017). The previous study preliminarily evaluated the persistent, bioaccumulation and toxicity of OBS, and found that it could not rapidly be biodegraded, it had the feature of bioaccumulation, and had low toxicity to fish and earthworm acute toxicity. Compared with the PBT characteristics of PFOS/PFOA, OBS has not significantly improved in this respect (Hwang, 2016). As for the zebrafish, OBS is similar to PFOS in acute toxicity according to the Globally Harmonized System criteria for the classification of chemicals (Wang et al., 2013; W. Wang et al., 2019). In a previous work, we exposed the male mice to 0, 0.1, 1

Corresponding author. E-mail address: [email protected] (Y. Jin).

https://doi.org/10.1016/j.cbpc.2020.108703 Received 11 November 2019; Received in revised form 19 December 2019; Accepted 2 January 2020 1532-0456/ © 2020 Elsevier Inc. All rights reserved.

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or 10 μg/L of OBS for 6 weeks through drinking water. It was found that OBS could bioaccumulate in the gut, live, kidney, serum and feces in mice, resulting in gut barrier dysfunction and impairing the liver function (C.Y. Wang et al., 2019). However, it did not discuss the effect of OBS on the gut microbiota and there are few studies on the toxicity of OBS to aquatic animals. Zebrafish, as an ideal experimental model with a well characterized genome, has been used to assess the toxicity effect of environmental pollutants, for example heavy metals (Lee and Freeman, 2014; Xia et al., 2018), fungicides (C.Y. Jin et al., 2017), herbicide (Liu et al., 2017b), microplastic (Y.X. Jin et al., 2018; Wan et al., 2019) and perfluorinated compound (PFASs) (Cheng et al., 2016). Now, a host studies reported that the nutritional status and stress response of the host could be affected by the gut microbiota (Ley et al., 2006; Dibaise et al., 2008; Dinan and Cryan, 2012). And the gut microbiota played an important role in resistance to pathogens, inflammatory reaction, immune function, metabolism, etc. (Sanz et al., 2010; Spencer et al., 2011; Hofer, 2014; Kan et al., 2016; Hoyles et al., 2018; Jin et al., 2019). Here, we exposed the adult male zebrafish to 0, 3, 30 and 300 μg/L OBS for 7 and 21 days, respectively, to analyze the effects on gut microbiota and metabolism. The results obtained in our study would provide some new insights into the potential health risks of aquatic organisms caused by short-chain PFASs.

2.3. DNA extraction, PCR amplification, quantification and 16S rRNA gene sequencing The fish gut samples (6 whole guts from each group) were obtained for DNA extraction using a commercial magnetic bead DNA isolation kit provided by Hangzhou Foreal Nanotechnology (Hangzhou, China). The V3–V4 region of the bacterial 16S rRNA gene was amplified by s common primer pair. Moreover, we also amplified some gDNA with bacterial phylum-specific primers by Real-Time qPCR (C.Y. Jin et al., 2016), the following cycling conditions were performed according the previous study (Engevik et al., 2013). 2.4. Total RNA extraction and gene expression analysis To analyze gene expression, total RNA (3 fish were collected as one liver sample) was extracted using the Biozol reagent. cDNA synthesis and relative quantitative RT-qPCR were performed as previous report (C.Y. Jin et al., 2018). The levels of 18 s transcripts were determined as a housekeeping gene (Table S1) in each sample, and the specific sequences of the target genes (including the genes involved in glycolipid metabolism) according to a previous study (C.Y. Jin et al., 2017). The program for amplifying cDNA is based on previous reports (Jin et al., 2010). Real-Time qPCR and quantification of relative expression of genes were performed as previously described (Livak and Schmittgen, 2001).

2. Materials and methods 2.5. Determination of the levels of T-CHO, TG, GLU and pyruvate in the liver

2.1. Chemical The OBS (Sodium ρ-perfluorous nonenoxybenzene sulfonate, C9F17OC6H4SO3Na, CAS No.: 70829-87-7) was obtained from Yongshen Trading Co., Ltd. (Ningbo, China) with purity of 98%.

The hepatic parameters, total cholesterol (T-CHO), triglycerides (TG), glucose (Glu) and Pyruvate, were detected according to the manufacturer's instructions. We purchased the corresponding kits from the Nanjing Jiancheng Institute of Biotechnology (Nanjing, China). The total protein level was determined in using a commercial BCA protein assay kit provided by Sangon Biotech (Shanghai, China). To detect the hepatic parameters, 5 samples (3 fish were collected as one liver sample) in each group were homogenized on ice with 120 μL PBS (NaCl 1.36 M, KCl 26.8 M, Na2HPO4 81.0 mM, KH2PO4 17.6 mM, pH 7.2–7.4). The homogenate was centrifuged at 3000 ×g at 4 °C for 10 min to obtain the supernatant. The collected supernatant was used for determination the indexes of (T-CHO, TG, Glu, Pyruvate) levels.

2.2. Experimental fish and protocol The healthy six-month-old male adult zebrafish (AB strain) were used in the present study. The average body weights and lengths of fish selected randomly were 311.68 ± 8.05 mg and 13.71 ± 0.37 mm. All fish were kept in zebrafish aquarium facilities with ambient temperature (26 ± 1 °C), photoperiod consisting of 14 h light/10 h dark and normal diet. It is report that LC50 value of OBS for zebrafish is about 25.5 mg/L, indicating that OBS has low toxicity to zebrafish (United Nations, 2011) and the residual concentration of OBS in river has reached 3.2 μg/L (Xu et al., 2017). In present experiment, the randomly selected experimental zebrafish (in total 280) were respectively exposed to 0, 3, 30 and 300 μg/L OBS in tap water for 7 and 21 days to analyze. In each group, a total of 35 fish were equally reared in five separately glass aquaria with 3 L of the indicated solutions (7 fish from each aquarium). To ensure the exposure concentration of the experimental group, we replaced the water every two days. After exposure, we anesthetized the zebrafish on ice and dissected. The whole gut was excised from each fish and collected as one sample and 6 whole guts from each group were used for DNA extraction (2 fish from each aquarium). The liver excised from 3 fish was collected as one sample and a total of 5 samples were collected for gene expression analysis. For Metabolites analysis, the selected experimental zebrafish in total 128 were respectively exposed to 0 and 300 μg/L OBS in tap water for 21 days. About 8 glass aquaria were placed glass aquaria with 3 L of the indicated solutions (8 fish from each aquarium) for the two groups, respectively. After 21 days of exposure, a total of 8 liver samples (each beaker as one sample) were prepared and stored at −80 °C until analysis. All experiments were carried out according to the guiding principles of toxicity in Zhejiang University of Technology.

2.6. Hepatic metabolomics analysis The collected 8 liver samples (8 fish were collected as one liver sample) were thawed on ice and metabolite was extracted with 50% methanol Buffer. The samples were stored at −80 °C to the LC-MS analysis. All samples were acquired by the liquid chromatographytandem mass spectrometry (LC-MS/MS) system followed machine orders. The first, all chromatographic separations were performed using an ultra-performance liquid chromatography (UPLC) system (SCIEX, UK). We detected metabolites eluted form the column by a high-resolution tandem massed spectrometer TripleTOF5600plus (SCIEX, UK). The Q-TOF was operated in both positive and negative ion modes. We acquired the mass spectrometry data in IDA mode. The second, the acquired MS data pretreatments were performed using XCMS software. Each ion was identified by combining retention time (RT) and m/z data. The online KEGG (http://www.kegg.jp/), HMDB (http://www.hmdb. ca/) database was used to annotate the metabolites by matching the exact molecular mass data (m/z) of samples with those from database. When the mass observed are different from the database value and was < 10 ppm, we annotated the metabolite and their molecular formula would further be identified and validated by the isotopic distribution measurements. Quantitative information for metabolites comes from the peak area of the primary chromatogram of the substance. We used XCMS software to extract the intensity information of 2

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Bacteroidetes and Actinobacteria (Fig. 1B).

each substance in each sample and performed quality control on the extracted data by metaX software. PCA was performed for outlier detection and batch effects evaluation using the pre-processed dataset. Moreover, we calculated the relative standard deviations of the metabolic features across all QC samples and removed those > 30%. Finally, Student t-tests (P value) were conducted to detect differences in metabolite concentrations between 2 phenotypes. The Q value was corrected for multiple tests using an FDR (Benjamini–Hochberg). Supervised PLS-DA was conducted through metaX to distinguish between the treated group and the control group. The VIP value was calculated and use the VIP cutoff value of 1.0 as important features for screening.

3.3. Effects of OBS on the composition of gut microbiota analyzed by 16S rRNA gene sequencing To investigate the effect of 300 μg/L OBS on the composition of gut microbiota in zebrafish after 21 days exposure, the high-throughput sequence of the V3-V4 region of the 16S rRNA gene was employed (Fig. 2). At genus level, the relative abundance of the Flavobacterium, Hyphomicrobium, Paracoccus, Lawsonia, Plesiomonas and Vibrio were dramatically changed in OBS treated zebrafish (Fig. 2A). Among the 759 Operational taxonomic units (OTUs) identified with gut microbiota of zebrafish, there were 84 OTUs and 382 OTUs with different levels of abundance compared with the control (Fig. 2B). Interestingly, the percentage of Fusobacteria and Proteobacteria in the entire gut microbiota also changed obviously after exposure to 300 μg/L OBS the phylum level (Fig. 2C). And the differential microbiota patterns of gut microbiota could also be observed by using a principal component analysis (PCA) between the control group and the 300 μg/L OBS treated group (Fig. 2D).

2.7. Data analysis The SPSS 13.0 (SPSS, Chicago, Illinois) and GraphPad Prism version 7 (GraphPad Software) were used to analyze the differences between the control group and the treated group by one-way ANOVA. When necessary, logarithmic transformation was performed for the data normalization to reduce the heterogeneity of variance. Results are given as mean ± SEM. Differences were considered significant when p ≤ 0.05. The correlation analysis of the gut microbiota and metabolites were investigated by nonparametric Spearman's rank test (**p < 0.01 versus control) (Qi et al., 2019).

3.4. Effects of OBS exposure on the transcription of genes related to glycolipid metabolism in the liver As shown in Fig. 3, the transcriptional levels of the key genes related to glucose and lipid metabolism were analyzed in the livers of zebrafish exposed to OBS for 7 days and 21 days, respectively. The mRNA level of HK1 increased significantly from the liver of zebrafish when exposed to 300 μg/L OBS for 7 days (Fig. 3A). Interestingly, no significant change was observed in the zebrafish after exposure to 21 days (Fig. 3B). However, the mRNA levels of cytosolic phosphoenolpyruvate carboxykinase (Pepckc) decreased significantly in the liver of zebrafish when exposed to 3, 30 and 300 μg/L OBS for 21 days. In addition, we evaluated the transcription levels of lipid metabolism-related genes. Among them, the mRNAs levels of fatty acid synthase (Fas), acetyl-CoA carboxylase 1 (Acc1), diacylglycerolacyltransferase (Dgat) and sterol regulatory element binding protein (SREBP) increased significantly when exposed to 300 μg/L OBS for 7 days and decreased after exposure to 300 μg/L OBS for 21 days. However, the mRNA levels of acyl-CoA oxidase (Aco) and apolipoprotein (Apo) increased obviously in the liver of zebrafish when exposed to 300 μg/L OBS for 7 days and 21 days, meanwhile the mRNA levels of peroxisome proliferator-activated receptor alpha (PPARα) tended to decrease in zebrafish when exposed to both 30 and 300 μg/L OBS for 7 and 21 days.

3. Result 3.1. Phenotypic analysis and determination of biochemistry indexes in the liver The body weight, length and the ratio of body weight/length of zebrafish had no obvious change when the zebrafish were exposed to 3, 30 and 300 μg/L OBS for 21 days (Fig. S1). As shown in Table 1, the levels of Glu, Pyruvate and TG showed no marked changes in the liver of zebrafish exposed to 3, 30 and 300 μg/L OBS for 7 and 21 days. Surprisingly, the hepatic T-C HO levels decreased significantly in the group after exposure to OBS for 21 days. 3.2. Effects of OBS on the composition of gut microbiota at the phylum level At the phylum level (Fig. 1), the different types of gut microbiota had the tendency to decrease in zebrafish when exposed to various concentrations of OBS for both 7 and 21 days (Fig. 1). The relative abundances of β-Proteobacteria, Bacteroidetes and Actinobacteria reduced significantly in the gut of zebrafish after exposure to 300 μg/L OBS for 7 days (Fig. 1A). However, the relative abundances of α-Proteobacteria, γ-Proteobacteria and Verrucomicrobia decreased in the gut of zebrafish after exposure to 300 μg/L OBS for 21 days, except for β-Proteobacteria,

3.5. Effects of OBS on hepatic metabolism We further used LC-MS/MS to detect the hepatic metabolites

Table 1 Effects of OBS exposure on the biochemical indexes in the liver of adult zebrafish. OBS (μg/l) 0

3

30

300

7 d-liver index Glu (mmol/g pro) Pyruvate (μmol/mg pro) TC (mmol/g pro) TG (mmol/g pro)

1.64 0.07 0.30 0.42

± ± ± ±

0.084 0.014 0.045 0.079

1.89 0.11 0.33 0.42

± ± ± ±

0.202 0.028 0.041 0.061

2.02 0.10 0.35 0.59

± ± ± ±

0.226 0.044 0.056 0.120

1.56 0.07 0.34 0.39

± ± ± ±

0.083 0.021 0.021 0.055

21 d-liver index Glu (mmol/g pro) Pyruvate (μmol/mg pro) TC (mmol/g pro) TG (mmol/g pro)

1.31 0.06 0.34 0.51

± ± ± ±

0.047 0.007 0.034 0.184

1.52 0.06 0.22 0.28

± ± ± ±

0.116 0.012 0.025* 0.055

1.15 0.06 0.15 0.23

± ± ± ±

0.011 0.009 0.012** 0.043

1.32 0.05 0.23 0.31

± ± ± ±

0.075 0.007 0.031* 0.043

The presented values are the mean ± SE (n = 5). The asterisk indicates a significant difference between the control and OBS-treated groups (* at 0.01 < p ≤ 0.05, ** at 0.001 < p ≤ 0.01). 3

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Fig. 1. Effects of OBS on the composition of microbiota at the phylum level in the gut. (A) Relative abundance of various gut microbiota in the guts of zebrafish after exposure to 3, 30 and 300 μg/L OBS for 7 days. (B) Relative abundance of various bacteria in the guts of zebrafish after exposure to 3, 30 and 300 μg/L OBS for 21 days. The presented values are the mean ± SE (n = 6). The asterisk represents a statistically significant difference when compared with the control (* at 0.01 < p ≤ 0.05, ** at 0.001 < p ≤ 0.01).

between the control group and 300 μg/L OBS groups (n = 8). Supervised analysis techniques of partial least-squares discriminant analysis (PLS-DA) were used. The quality of the model was described by the cross-validation parameters R2 = (0.0, 0.86), Q2 = (0.0, −0.686) in pos-model and R2 = (0.0, 0.8707), Q2 = (0.0, −0.693) in neg-model (Fig. S2). The expression patterns of metabolites were significantly different from both pos-model and neg-model between the control and 300 μg/L OBS groups (Fig. 4A and B). As shown in Fig. 4C and D, various metabolites changed after exposure to 300 μg/L OBS for 21 days, among of the high quality feature, a total of 713 metabolites were upregulated and 364 metabolites were downregulated in posmodel, a total of 450 metabolites were increased and 256 metabolites were decreased in neg-model (Table S2). According to the HMDB database, we screened metabolites (Ratio ≥ 2 or ≤1/2, VIP ≥ 1, Q value ≤ 0.05) obtained from level-two identification and observed that there had significant changes in organic acids and derivatives, organoheterocyclic compounds, lipids and lipid-like molecules, organic nitrogen compounds, organic oxygen compounds, Nucleosides, nucleotides, and analogues, and others (Fig. 5A and Table S3). We performed KEGG pathway analysis on these metabolites and found that they

involved in 25 pathways (Table S4). According to KEGG functional annotations, top 14 KEGG pathways were arginine biosynthesis, aminoacyl-tRNA biosynthesis, nicotinate and nicotinamide metabolism, histidine metabolism, etc. (Fig. 5B).

3.6. Gut microbiota-differential metabolites correlation analysis To confirm the relationship between gut microbiota and metabolism, we further analyzed the correlation between the gut microbiota changed at the genus level and differential metabolites by nonparametric Spearman's test. As shown in Fig. 6, N-Acetylvaline, Nicotinic acid, Acetaldehyde were positively related to Flavobacterium and DLPipecolinic acid, Lysine were negatively related to it. Many metabolites were a significant correlation with Hyphomicrobium and Vibrio. Among them, the 8 metabolites of organic acids and derivative, 13 metabolites of organoheterocyclic compounds, 7 metabolites of lipids and lipid-like molecules, 5 metabolites of organic nitrogen compounds, 2 metabolites of organic oxygen compounds, 2 metabolites of Nucleosides, nucleotides, and analogues, and 6 metabolites of others were positively related to Flavobacterium, Hyphomicrobium, Paracoccus, Plesiomonas and were 4

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Fig. 2. Effects of OBS on the composition of gut microbiota in the zebrafish after exposure to 300 μg/L OBS for 21 days. (A) The proportion of each gut microbiota at the genus level (every color represents a kind of bacterial genus). (B) Change in Operational Taxonomic Units (OTUs) in the gut microbiota. (C) The proportion of each gut microbiota at the phylum level (every color represents a kind of bacterial phylum). (D) UniFrac principal coordinates analysis (PCoA) estimates of gut microbiota from control and treated group. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

4.1. Effect of OBS on phenotypic and biochemistry indexes in the liver

negatively related to Vibrio and Lawsonia. The remaining metabolites were negatively correlated with Flavobacterium, Hyphomicrobium, Paracoccus, Plesiomonas and were positively related to Vibrio and Lawsonia.

Recently, it is reported that relative high concentrations PFASs (PFOS, F-53-B, OBS) did not marked affect the body weight and body length of zebrafish larval (Tu et al., 2019). Here, we got the same result in adult zebrafish and observed that body weight and length of zebrafish had no obvious change when exposed OBS for 21 days. In toxicological research on rodents and monkeys, it was observed that PFOA and PFOS could induce hepatomegaly, reduce the serum TG and T-CHO levels, alter lipid metabolism (Seacat et al., 2003). Therefore, we further detected some biochemistry indexes in the liver and the levels of Glu, Pyruvate and TG showed no obviously changes, however, T-CHO level was significantly downregulated (Table 1).

4. Discussion Recently, studies on the toxicity of perfluorinated compound to zebrafish suggested that F-53B, as the substitute for PFOS, is bioaccumulative and persistent in zebrafish, and further induced oxidative stress responses (C.Y. Wu et al., 2019; X.Y. Wu et al., 2019). However, OBS, which is also a substitute for PFOS, has rarely been reported on the toxicity of zebrafish. Here, we observed that OBS exposure not only induced gut microbiota dysbiosis but also caused hepatic metabolism disorder in adult zebrafish.

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Fig. 3. Effects of OBS exposure on the transcription of genes related to glycolipid metabolism in the liver of zebrafish. (A) The relative mRNA level of genes related to glycose and lipid metabolism after exposure to OBS for 7 days. (B) The relative mRNA level of genes related to glycose and lipid metabolism after exposure to 300 μg/ L OBS for 21 days. The presented values are the mean ± SE (n = 5). The asterisk represents a statistically significant difference when compared with the control (* at 0.01 < p ≤ 0.05, ** at 0.001 < p ≤ 0.01).

indicating that OBS could interfere with liver lipid metabolism. However, TG level in zebrafish liver did not obviously change after OBS (3, 30, 300 μg/L) exposure in the present study, suggesting that the mechanism, OBS at certain low concentrations affected lipid metabolism, is different from other compounds (Zhang et al., 2018; Wang et al., 2015). Subsequently, the LC-MS/MS was used to detect the hepatic metabolites and we found that the expression patterns of metabolites were significantly different from the control and 300 μg/L OBS groups (Fig. 4). Among them, the cholesterol detected by the metabolome, like the results of previous, also kept reduced. We also found that various amino acids (Arginine, Lysine, Leucine, etc.) have changed. It is known that amino acids are used to synthesize proteins and other biomolecules or are oxidized to urea and carbon dioxide as a source of energy (Sakami and Harrington, 1963). The changes also mean that the relevant metabolism had been affected. In addition, we had also seen the certain changes in hepatic metabolites. For example, the succinic acid involved in TCA cycle (Hijaz and Killiny, 2019); the orotic acid, uridine involved in nucleotide metabolism (Fan et al., 2019); citrulline is a substance involved in the urea cycle (Gramaglia et al., 2019); etc. These metabolites seem to have their own roles in the metabolism. Therefore, the results of metabolomic analysis indicated that OBS exposure disrupts metabolism in zebrafish. Moreover, it was observed that there are

4.2. OBS altered the hepatic metabolism at the gene level and metabolite level Cholesterol played very important role of in fatty acid, lipid metabolism and the synthesis of steroid hormones (Azhar and Reaven, 2002; Gross et al., 2019). And the liver also acts as the primary organ that metabolizes environmental pollutants and plays a key role in metabolism (Nguyen et al., 2008; Lu et al., 2018; X.Y. Wang et al., 2019; Ni et al., 2020). It was reported that perfluorinated compounds could also disturb hepatic metabolism balance in zebrafish (Du et al., 2009; Cheng et al., 2016). We further analyzed that the changes in the metabolism of the liver at the transcription level. We observed that the mRNA levels of gene related glucose metabolism (PK, GK, HK, PEPCKC) didn't significantly change after exposure to OBS. The result corresponded to the levels biochemistry indexes (Glucose, Pyruvate, TG) in the liver without marked difference. However, the mRNA levels of genes related lipid metabolism (APO, ACO, FAS, ACC1, DAGT, SREPB) had the significant difference compared with the control after exposure to OBS (Fig. 3). These genes are key genes in regulating host energy metabolism (Bäckhed et al., 2004; Y.X. Jin et al., 2016), could directly affect the glycolysis and change the levels of endogenous fatty acid (Shieh et al., 2010; Baldini et al., 2016). The level of liver T-CHO decreased and the change of gene levels related lipid metabolism under OBS exposure, 6

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Fig. 4. Effects of OBS exposure on the hepatic metabolome of zebrafish. OPLS-DA score plots of liver samples from the control and OBS groups (A) In pos-model, (B) In neg-model. Different metabolite levels in the liver from the control and 300 μg/L OBS groups for 21 days (C) In pos-model, (D) In neg-model.

rRNA gene were performed. The differential gut microbiota patterns were found between the control group and the 300 μg/L OBS treated group (Fig. 2D). The OTUs identified with gut microbiota of zebrafish in 300 μg/L OBS treated group presented difference compared with the control (Fig. 2B). Moreover, it was also observed that the relative abundances of Flavobacterium, Hyphomicrobium, Paracoccus, Lawsonia, Plesiomonas, and Vibrio were significantly changed at genus level after exposure to 300 μg/L OBS for 21 days (Fig. 2A). The previous studies also indicated that gut microbiota alterations or dysbiosis might contribute to metabolic abnormalities (Wu et al., 2018). These five species also played very important role in the health on animals. Among them, the Flavobacterium could illustrate the immunometabolic changes of fish and indicate the immune response, nutrient metabolism and related signaling pathways (Guo et al., 2019); the Hyphomicrobium could provide carbon sources for the body and is a major player in the denitrification system (Martineau et al., 2015); the Paracoccus could balance metabolic flux between energy and biosynthesis (Kremer et al., 2019); the Plesiomonas played the important in transporting mannose via a phosphoenolpyruvate-dependent phosphotransferase system producing mannose 6-phosphate (Rager et al., 2000). the Vibrio could secrete both chitinase and chitin oligosaccharide deacetylase and produces β-Nacetyl-D-glucosaminyl-(1,4)-D-glucosamine (GlcNAc-GlcN) from chitin (Hirano et al., 2019); the Lawsonia was the aetiological of proliferative enteropathy (Watson et al., 2014). Hence, we speculated that OBS, as a kind of PFASs, was non-readily biodegraded (Bao et al., 2017) and could induce gut microbiota dysbiosis in adult zebrafish.

more differential metabolites, which participated in arginine biosynthesis, aminoacyl-tRNA biosynthesis, nicotinate and nicotinamide metabolism, histidine metabolism, glycerophospholipid metabolism, arginine and proline metabolism, pyrimidine and purine metabolism, in the KEGG pathway enrichment map. Importantly, these metabolisms were indispensable for maintaining the biological response and homeostasis of the organism (Wang et al., 2012), indicating that OBS could induce the hepatotoxicity and disturb hepatic metabolism balance in zebrafish. 4.3. OBS altered the composition of gut microbiota Because metabolism in the body is a complex network and a number of previous studies had also showed that the gut microbiota alterations or dysbiosis might contribute to metabolic abnormalities (Goodrich et al., 2014; Ba et al., 2017). The gut microbiota participated in host metabolism by interacting with host signaling pathways (Martin et al., 2007). Therefore, we started to pay attention to the change of gut microbiota after exposure to OBS. In our experiment, the relative abundance of β-Proteobacteria, Bacteroidetes and Actinobacteria at the phylum level reduced significantly after exposure to 300 μg/L OBS for 7 and 21 days. In addition, the relative abundances of α-Proteobacteria, γProteobacteria and Verrucomicrobia also reduced when exposed to 300 μg/L OBS for 21 days. Generally speaking, the gut microbiota in adult zebrafish is relatively stable without external stimulus, however, it can be affected by medicine, environmental pollutant, age, etc. (Dehler et al., 2017; A.R. Wang et al., 2017; C.Y. Jin et al., 2017). Therefore, high-throughput sequencing of the V3-V4 region of the 16S 7

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Fig. 5. Effects of OBS exposure on the detected metabolites in zebrafish liver. (A) Heat map for the differential metabolites (Ratio ≥ 2 or ≤1/2, VIP ≥ 1, Q value ≤ 0.05) identified between the control OBS-treated group. (B) Identified metabolites classified into the top 14KEGG pathways (the x-axis represents the top 14 KEGG pathways and the y-axis represents number of identified metabolites involved in this pathway).

and the Vibrio can secrete chitinase and chitin oligosaccharide deacetylase (Martineau et al., 2015; Hirano et al., 2019). Thus, it was possible that OBS induced gut microbiota dysbiosis was tightly related to some basic metabolic pathways in zebrafish.

4.4. Relationship between differential metabolites and gut microbiota The function of gut microbiota cannot be neglected. A host of study indicated that the gut microbiota can regulate a variety of metabolic pathways and homeostasis (Neis et al., 2015; Honda and Littman, 2016; Lu et al., 2019). We furthered analyzed the correlation between gut microbiota with differential metabolites and found that there was a significant correlation between them (Fig. 6). It was found that differential metabolites were positively correlated with Flavobacterium, Hyphomicrobium, Paracoccus, Plesiomonas and negatively correlated with Vibrio, Lawsonia, and vice versa. We thought that the phenomenon was inseparably related to the role of each gut microbiota and metabolite. Interestingly, many of the differential metabolites detected had an obvious correlation with Hyphomicrobium and Vibrio. It is report that the Hyphomicrobium has ability to provide a carbon source for the organism

5. Conclusion According to the above the results, we got a conclusion that the toxicity of OBS, as a Category III chemical according to the Globally Harmonized System (GHS) criteria for the classification of chemicals (Xu et al., 2017; United Nations, 2011), to aquatic animals could not be ignored. Although, OBS did not cause the visible change such as body weight, body length, or some hepatic biochemical index, however, it still induced the dysbiosis of gut microbiota and disturbed the metabolism balance of the liver in adult male zebrafish. We believed that 8

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Fig. 6. Correlations of the gut microbiota with level of hepatic differential metabolites, as determined by Spearman's rank test. X-axe was the changed gut microbiota at the genus level, y-axe was the differential metabolites (**p < 0.01).

these acquired results could provide new insight for evaluating the aquatic toxicity of OBS and a certain reference for the use of OBS. Supplementary data to this article can be found online at https:// doi.org/10.1016/j.cbpc.2020.108703.

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