Article pubs.acs.org/est
Identifying Health Effects of Exposure to Trichloroacetamide Using Transcriptomics and Metabonomics in Mice (Mus musculus) Yan Zhang, Zongyao Zhang, Yanping Zhao, Shupei Cheng, and Hongqiang Ren* State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, Jiangsu 210023, China S Supporting Information *
ABSTRACT: Microarray-based transcriptomics and one-dimensional proton nuclear magnetic resonance (1H NMR) based metabonomics approaches were employed to investigate the health effects of nitrogenous disinfection byproducts (NDBPs) of trichloroacetamide (TCAcAm) on mice. Mice were exposed to TCAcAm at concentrations of 50, 500, and 5000 μg/ L for 90 days, and hepatic transcriptome and serum metabonome and histopathological parameters were detected in comparison with those of control. TCAcAm esposures resulted in liver inflammation, weight loss (in 5000 ug/L TCAcAm group), and alterations in hepatic transcriptome and serum metabonome. Based on the differentially expressed genes and altered metabolites, several significant pathways were identified, which are associated with lipid, xenobiotics, amino acid and energy metabolism, and cell process. Moreover, integrative pathway analyses revealed that TCAcAm exposure in this study induced hepatotoxicity and cytotoxicity. These results also highlight the noninvasive prospect of transcriptomic and metabonomic approaches in evaluating the health risk of emerging N-DBPs.
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INTRODUCTION In recent years, many utilities have used chloramines disinfection instead of chlorine to remove the conventional disinfection byproducts (DBPs), such as trihalomethanes (THMs) and haloacetic acids (HAAs).1,2 However, several classes of emerging DBPs are still unintentionally formed with the use of the alternative disinfectants, including nitrogenous disinfection byproducts (N-DBPs).3−5 These N-DBPs, such as haloacetonitriles (HANs), halonitromethanes (HNMs), haloamides, and nitrosamines, are not regulated, but they have been widely detected in finished drinking water with concentrations of 14 μg/L, 10 μg/L, 9.4 μg/L, and 530 ng/ L, respectively, and are more cytotoxic and genotoxic than those without nitrogen.6−9 Haloacetamides (HAcAms), an emerging class of halogenated N-DBPs, have been identified and quantified as part of the U.S. nationwide DBP occurrence study, and the highest level of HAcAms sum was 14 μg/L in finished drinking water.10 In China, trace determination of 13 HAcAms in drinking water was conducted and the sum concentration of HAcAms ranged from 0.76 μg/L to 8.18 μg/L.11 It was reported that most of chlorinated HAcAms are less cytotoxic and genotoxic than their brominated and iodinated analogs.12 Nevertheless, to-date, most studies on HAcAms in drinking water still focused on the chlorinated species.13−15 Trichloroacetamide (TCAcAm), a kind of chlorinated HAcAms, is typically present at higher levels in finished water than other HAcAms.16 A toxicological study © 2013 American Chemical Society
indicated that TCAcAm can induce chronic cytotoxicity and genotoxicity on the Chinese hamster ovary (CHO) cells, and the lowest concentrations for cytotoxicity and genotoxicity were 5 × 10 −4 M and 5 × 10 −3 M, respectively.12 Although many efforts have been made to understand the cytotoxicity and genotoxicity of TCAcAm,12,17 very little information is available about the health risk of TCAcAm on mammals, depending on more sensitive and comprehensive approaches. Omics techniques have provided the opportunity to unravel the complex effect pathways of chemical contaminants and significantly enhance our understanding of their effects on the health of organisms.18,19 This study was designed to reveal the potential health effects of TCAcAm on mice. Mice were exposed to three concentrations of TCAcAm for 90 days, and transcritptomic and metabonomic changes as well as histopathological parameters were detected. Integrated analyses were conducted on all data obtained to identify the molecular pathways related to adverse health effects. Received: Revised: Accepted: Published: 2918
November 30, 2012 February 13, 2013 February 13, 2013 February 13, 2013 dx.doi.org/10.1021/es3048976 | Environ. Sci. Technol. 2013, 47, 2918−2924
Environmental Science & Technology
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Article
Metabonomic Analysis. A total of 300 μL phosphate sodium buffer (70 mM Na2HPO4; 0.025 (w/v) NaN3; 20% (v/ v) D2O; 3 mM sodium trimethylsilyl [2,2,3,3-2H4] proionate (TSP); pH 7.4) was added to 300 μL of each serum sample. This mixture was homogenized and centrifuged at 10000 rpm for 10 min and then 550 μL of the supernatants were transferred into 5 mm NMR tubes for analysis. 1 H NMR spectra were acquired using a Bruker AV600 spectrometer (Bruker Co., Germany) at 298 K. Water resonances were suppressed by Carr−Purcell−Merbom−Gill (CPMG) spin−echo pulse sequence with 32 free induction decays collected into 64K data points. Exponential line broadenings of 0.3 Hz were applied before Fourier transformation, and spectra were phase and baseline corrected using MestRec software. All the spectra were referenced to TSP (δ = 0.00 ppm). Each spectrum was segmented into 0.04 ppm chemical shift bins corresponding to the range from 0.20 to 10.00 ppm. The region (4.5−5.0 ppm) was excluded to remove the variation in water suppression efficiency. Then, all remaining regions were scaled to the total integrated area of the spectra to facilitate comparison among the samples. The metabolite resonances were identified according to previous studies.22 Significance Analysis of Microarrays (SAM) software was used to identify significantly changed metabolites between the control and exposed groups with appropriate false discovery rate (FDR) < 0.01.18,23 The z-scores of individual metabolite were calculated with the formula z-score = (treatment metabolite abundance − control mean)/standard deviation of control.24 The calculated z-scores were used to generate a heatmap. Partial least-squares discriminant analysis (PLS-DA) was used to explore the main effects in the NMR data sets by using SIMCA-P software (Umertric, Umeå, Sweden). Biological Pathway Analysis. Furthermore, an integrative analysis based on the significantly changed genes and metabolites was performed to reveal the major perturbed biological pathways induced by TCAcAm exposure. For the differentially expressed genes, the functional classification and biological pathway analysis were conducted based on Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database (http://www.genome.ad.jp/kegg/pathway.html) using Molecule Annotation System (MAS) 3.0 (http:// bioinfo.capitalbio.com/mas/). Metabolic pathways analysis was performed on the selected differential metabolites using MetaboAnalyst 2.0 (http://www.metaboanalyst.ca/ MetaboAnalyst/) to identify the metabolic pathway perturbations. Statistical Analysis. Statistical differences of biological parameters between TCAcAm-treated groups and control group were evaluated using one-way ANOVA test. All analyses were performed by SPSS 15 software (SPSS Inc., U.S.A.). Pvalue
