Mice In Vivo Toxicity Studies for Monohaloacetamides Emerging

Jun 18, 2014 - Haloacetamides (HAcAms) as a new class of nitrogenous disinfection byproducts (N-DBPs) have been widely detected in drinking water and ...
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Mice In Vivo Toxicity Studies for Monohaloacetamides Emerging Disinfection Byproducts Based on Metabolomic Methods Yongfeng Deng,† Yan Zhang,† Rui Zhang, Bing Wu, Lili Ding, Ke Xu, 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: Haloacetamides (HAcAms) as a new class of nitrogenous disinfection byproducts (N-DBPs) have been widely detected in drinking water and reclaimed water. Cytotoxicity and genotoxicity of monoHAcAms are determined by the leaving tendency of the halogens and decrease following a rank order of iodoacetamide (IAcAm) > bromoacetamide (BAcAm) ≫ chloroacetamide (CAcAm). However, the in vivo toxicity date for monoHAcAms is limited. In this study, hepatic oxidative stress and metabolomics responses in mice corresponding to monoHAcAms exposure were investigated. Exposure to the monoHAcAms decreased the activities of catalase (CAT), superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) and the levels of malonaldehyde (MDA) and increased the level of 8-hydroxy-2deoxyguanosine (8-OHdG), indicating that each exposure generated oxidative stress in mice liver. Metabolomic alterations were also induced by each monoHAcAms exposure. In addition, disruptions of metabolic pathways, related to amino acid, energy and lipid metabolism, were identified based on the significantly changed metabolites. These data, for the first time, provide a comprehensive view for the toxic effects of monoHAcAms.

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INTRODUCTION In recent years, many utilities have used chloramines disinfection to replace chorine to reduce the traditional disinfection byproducts (DBPs), especially carbonaceous disinfection byproducts (C-DBPs),1−3 such as trihalomethanes (THMs), haloacetic acides (HAAs), and mutagen X (MX). Unfortunately, nitrogenous disinfection byproducts (N-DBPs), as a new class of DBPs,4−6 can also be formed, such as halonitromethanes (HNMs),7 haloacetonitriles (HANs),4 N-nitrosamines (NMs)8 and haloacetamides (HAcAms).5,9 These emerging N-DBPs have been widely detected in drinking waters.10 However, most previous studies mainly focused on the toxicity of HNMs, HANs, and NMs, toxicological studies for HAcAms are relatively rare. Actually, five HAcAms have been frequently detected in drinking water in United States, including chloroacetamide (CAcAm), dichloroacetamide (DCAcAm), trichloroacetamide (TCAcAm), bromoacetamide (BAcAm), and dibromoacetamide (DBAcAm), and the sum concentration of HAcAms is 14 μg/L2. In China, a total of 13 HAcAms in drinking water were detected and the sum concentration ranged from 0.75 to 8.18 μg/L.11 Although HAcAms only accounted for 0.5% of the quantified DBPs,2,12,13 they are more genotoxic, cytotoxic, and carcinogenic than many C-DBPs, which have been documented in previous research.14 In addition, the genotoxic and cytotoxic of HAcAms are also higher than many other N-DBPs, such as HNMs and HANs.15 Several previous seminal studies have been conducted to elucidate the cytotoxicity and genotoxicity of monohaloacetamides (monoHAcAms),9,15 including CAcAms, BAcAm and iodoacetamide (IAcAm). For monoHAcAms, the toxicity has close ties with alkylation by the SN2 reaction at the α carbon. It © 2014 American Chemical Society

has been demonstrated that the cytotoxicity and genotoxicity of monoHAcAms were primarily determined by the leaving tendency of the halogens in alkyl halides and followed the order I > Br ≫ Cl.9 This pattern of I > Br > Cl toxicity was also observed with other DBP classes.16,17 For example, the molecular mechanism of the toxicity of the monoHAAs based on this halogen pattern was resolved using nontransformed human cells.18,19 Oxidative stress is one mechanism that could explain the toxic effects of DBPs. Reactive oxygen species (ROS) can induce oxidative stress and lead to cellular dysfunction and disease. It has been demonstrated that monohalogenated acetic acids (monoHAAs) can inhibit glycolysis and generate ROS, which is involved in the induction of genotoxicity.18 Accumulating evidence indicates that monoHAcAms can also induce cytotoxicity and genotoxicity and share a similar mode of action. It was demonstrated that exposure to the monoHAAs induced oxidative stress based on the alterations of the transcription levels of multiple oxidative stress responsive genes.19 However, whether there are similar mechanisms for the in vivo toxicity of monoHAcAms is still unknown. Therefore, it is particular interest to compare the comprehensive toxic effects of different monoHAcAms. In addition, we have conducted preliminary study to evaluate the toxicity of TCAcAm on mice using transcriptomic and Received: Revised: Accepted: Published: 8212

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metabolomic methods,20 and it was demonstrated that TCAcAm could induce hepatotoxicity and cytotoxicity in mice. Likewise, omics methods can also be used to evaluate the comprehensive toxic effects of monoHAcAms with different halogen substituents. We assume that monoHAcAms could induce alterations of bio-omic profiles in mice. In this aspect, nuclear magnetic resonance (NMR)-based metabolomics profiling is highly attractive because of its no trauma and high sensitivity, and is able to simultaneously detect a variety of metabolites. In addition, data reduction and pattern recognition analysis, such as principal components analysis (PCA) and partial least-squaresdiscriminant analysis (PLS-DA), can be helpful to reduce the highly multidimensional data set of NMR spectrum and identify potential patterns for the variations of metabolites associated with toxic effects. The objective of this research was to evaluate the in vivo toxicity of monoHAcAms in mice. We used oxidative stress analysis to determine if oxidative stress were generated after monoHAcAms exposure. Subsequently, we employed metabolomics methods to determine if individual monoHAcAms induce different metabolomic alterations.

the supernatants were detected following the modified method described in the previous study.21 The activities of SOD, GSHPx, and CAT, and the level of MDA were determined by using commercial kits (NanJing Jiancheng Bioeng. Inst., China), and standardized by protein content. Each assay was run in quintuplicate. In addition, to indicate hepatic oxidative DNA damage, a mouse 8-hydroxy-2-deoxyguanosine (8-OHdG) enzyme-linked immunosorbent assay (ELISA) kit (NanJing Jiancheng Bioeng. Inst., China) was used to detect the level of 8OHdG in mice livers. The genomic DNA of liver was first isolated using Genomic DNA Mini Preparation Kit (Beyotime, China) and then the level of 8-OHdG was detected according to the manufacture’s protocol of ELISA kit. Each assay was run in quintuplicate to calculate the average level of 8-OHdG per microgram of DNA for each group. Metabolomic Analysis. A total of 320 μL phosphate sodium buffer (70 mM Na2HPO4, 0.025 (w/v) NaN3, 20% (v/v) D2O, 3 mM sodium trimethylsily [2,2,3,3,-2H4] proionate (TSP), pH 7.4) was added to 250 μL of each serum sample. The mixture was homogenized and centrifuged at 12 000 rpm for 10 min and then 520 μL of the supernatants were transferred into 5 mm NMR tubes for analysis. The detailed detection methods and spectral processing were described in our previous study.20 The metabolite resonances were identified according to the information from the previous studies22 and the Human Metabolome Database (HMDB, http://www.hmdb.ca/). PLSDA was used to explore the main effects in the NMR data sets and calculated with SIMCA-P software (Umertric, umeå, Sweden). The significantly changed metabolites (SCMs) between the control and treatment groups were identified by significance analysis of microarrays (SAM) software with false discovery rate (FDR) < 0.01 and the variable influence on projection (VIP) score >1 (which contributed relative large to the PLS-DA). The SCMs were selected for all treatments with all concentrations. In order to visualize the variations of metabolites between different groups, heat maps were generated based on zscores. The z-scores of the SCMs were calculated with the following formula: z-score = (treatment metabolite abundance− control mean)/standard deviation of control.23 Metabolic Pathway Analysis. The SCMs were selected for further metabolic pathway enrichment analysis using MetaboAnalyst 2.0 (http://www.metaboanalyst.ca/MetaboAnalyst/). The impact-value threshold calculated for pathway identification was set as 0.10.24 Statistical Analysis. One-way ANOVA test was used to evaluate the statistical differences of biological parameters between control group and monoHAcAms-treated groups. The results were expressed as mean ± standard deviation (SD). All analyses were performed by SPSS 15 software (SPSS Inc.). Pvalue BAcAm > CAcAm. In 8214

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Figure 3. Heat map for all significantly changed metabolites among the monoHAcAms-treated groups calculated by z-scores (A) and fold changes of metabolites (B) (L-0.75 μg/L, M-300 μg/L, H-120 000 μg/L).

results suggested that monoHAcAms induced oxidative stress in mice liver and shared a common mechanism. Metabolomic Alterations Induced by monoHAcAms. Serum metabolomic profiles were measured by 1H NMR in this research. PLS-DA was used to analyze the NMR data set. For each monoHAcAms, the scores plots of PLS-DA showed that mice exposed to different dose of monoHAcAms (0.75, 300, 120 000 μg/L) were not only clearly separated with the control mice, but also separated within individual monoHAcAms-treated mice (Figure 2A). In addition, even exposed to the same dose of compounds, the data points were also successfully separated within each monoHAcAms-treated groups (Figure 2B). The validation of the models was evaluated by the default leave-oneout procedure with the parameters of R2X, R2Y, and Q2, and all these models were applicable and had predictability values (Figure 2). These results suggested that the three monoHAcAms could induce alterations of metabolic profiles in mice, but the patterns and dose−response were different according to different halogen substituents. Actually, these variations and differences of metabolic profile were contributed by the SCMs, which need further discussion. According to the different monoHAcAms exposure, some SCMs were identified (FDR < 0.01 and VIP > 1). As a result, a

addition, the monoHAcAms increased the level of 8-OHdG followed a similar rank order. This rank order was observed with other toxicological end points.9 Liver is sensitive to oxidative stress, and CAT, SOD, and GSHPx are all antioxidases, which play important roles in liver antioxidant defense system to inactivate the ROS produced by environmental chemicals.27 Oxidative stress will be induced when ROS generation overloads antioxidant defenses, and then affect the normal function of lipid, protein and nucleic acid.28,29 In this study, the decreased activities of CAT, SOD, and GSH-Px indicated that monoHAcAms induced oxidative stress in mice livers. In addition, lipid peroxidation might be induced in the livers of monoHAcAms-treated mice according to the significantly decreased MDA, which is considered as one of the endproducts in the lipid peroxidation process.30,31 Furthermore, 8OHdG is an oxidation product of DNA, which is oxidized by various ROS. 32−34 The dramatically increased 8-OHdG combined with the inhibition of CAT, SOD, and GSH-Px and decreased MDA demonstrated that oxidative stress and DNA damage in mice livers were induced due to the monoHAcAms exposure. Similar results have been found that monoHAAs can induce oxidative stress and lead to genotoxicity.18,19 These 8215

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total of 37 metabolites were significantly changed in the monoHAcAms-treated groups, and 33, 19, and 11 SCMs were identified in CAcAm, BAcAm, and IAcAm treated groups, respectively (SI Figure S2). Among these SCMs, only seven metabolites were shared by all three monoHAcAms groups. The fold changes of the SCMs were list in Table S2. In addition, the zscores of the SCMs were calculated to generate the heat map to illustrate the variation of individual metabolite responding to different chemical exposure and the result was presented in Figure S3. As a result, the z-scores of valine, glutamine, isoleucine, leucine, succinate, threonine, proline, taurine, lactate, pyruvate, glutamate, acetate, ethanol, and 2-oxoglutarate were significantly decreased in all monoHAcAms groups. However, the z-scores of glycine and glycerol were significantly increased in all monoHAcAms groups (Figure 3A). These results were consistent with the fold change of SCMs (SI Table S2). In addition, the alterations of lactate, pyruvate, and glycine followed a certain dose−response manner with a rank order of effect expressed as IAcAm > BAcAm > CAcAm (Figure 3B). This rank order of monoHAcAms may be related to their SN2 reactivity.9 It has been demonstrated that monoHAAs can inhibit glycolysis and generate ROS.19 Likewise, ROS induced oxidative stress was also detected in the monoHAcAms-treated mice as mentioned above. Furthermore, lactate and pyruvate are primary products of glycolysis, and the significant reduction of these metabolites confirmed the inhibition of glycolysis. These results support the hypothesis that the monoHAcAms exert their toxic effects based on ROS activity and glycolysis inhibition. Biological Pathways Affected by HAcAms Exposure. Metabolomic profiling can not only identify alteration of individual metabolites as mentioned above, but also provide comprehensive views for the toxic effects of monoHAcAms. Many SCMs identified in this study are linked with important metabolic process. For example, valine, isoleucine, leucine, threonine and proline are related to amino acid metabolism, succinate, lactate, pyruvate, acetate, ethanol, and 2-oxoglutarate are related to energy metabolism, taurine and glycerol are related to lipid metabolism, glutamine and glutamate are related to amino acid and energy metabolism, and glycine is related to amino acid, energy and lipid metabolism (Figure 3A). In order to effectively identify comprehensive toxic effects of monoHAcAms, all the SCMs were selected and used for biological pathway analysis. As a result, 14 metabolic pathways were filtered out as potential target pathways corresponding to monoHAcAms exposure. These results suggested that monoHAcAms exposure significantly changed amino acid metabolism (nine pathways), energy metabolism (three pathways), lipid metabolism (one pathway) and carbohydrate metabolism (one pathway) (Table 1 and SI Table S3). Nine pathways, related to amino acid metabolism, were identified, including glycine, serine, and threonine metabolism, D-glutamine and D-glutamate metabolism, alamine, aspartate, and glutamate metabolism and so on. The related metabolites of glutamine, glutamate, leucine, isoleucine, valine, arginine, proline, glycine, and threonine were significantly altered due to monoHAcAms exposure (SI Table S3). Amino acid metabolism is important for liver function to regulate nonessential amino acid synthesis, ammonia metabolism, interconversion of protein, carbohydrates and lipids, and oxidation for energy.35−37 It has been demonstrated that the pathway of glycine, serine, and threonine metabolism plays an important role in cancer metabolism.38 Furthermore, according to previous studies, several amino acids have been considered as antioxidant (such

Table 1. Altered Pathways Identification Based on Significantly Changed Metabolites (SCMs) Due to MonoHAcAms Exposure number of SCMs classes amino acid metabolism

pathways

CAcAm BAcAm

IAcAm

4

4

1

3

2

1

4

3

2

3

1

1

5

0

1

3

0

1

1 1

2 1

2 1

0

1

1

glycolysis or gluconeogenesis citrate cycle nitrogen metabolism

3

3

2

2 2

2 2

2 1

lipid metabolism

primary bile acid biosynthesis

2

3

3

carbohydrate metabolism

butanoate metabolism

2

2

2

energy metabolism

glycine, serine and threonine metabolism D-glutamine and D-glutamate metabolism alanine, aspartate and glutamate metabolism valine, leucine and isoleucine biosynthesis arginine and proline metabolism valine, leucine and isoleucine degradation glutathione metabolism cyanoamino acid metabolism taurine and hypotaurine metabolism

as glutathione and glutamine),39 and the intense of antioxidant would lead to imbalance between the body’s normal oxidation and antioxidation system.40 As mentioned above, after monoHAcAms exposure, the alterations of SOD, CAT, GSHPx, MAD, and 8-OHdG in livers indicated the imbalance oxidative stress and oxidative damage in mice liver. The alterations of these pathways demonstrated that monoHacAms exposure can alter the amino acid metabolism in mice liver. Changes in the pathways of citrate cycle (TCA cycle), glycolysis or gluconeogenesis, and nitrogen metabolism at metabolome level were identified by using MetaboAnaylst 2.0, and these pathways are important for energy metabolism (Table 1). The related SCMs included glutamine, glycine, ethanol, lactate, acetate, pyruvate, succinate, and 2-oxoglutarate (SI Table S3). In TCA cycle, succinate and pyruvate are essential intermediates, which play important roles in energy metabolism.41−43 In this study, succinate and pyruvate were decreased in monoHAcAm-treated groups (Figure 3A and SI Table S2). In our previous study, it was demonstrated that TCAcAm exposure could induce alterations in hepatic transcriptome and serum metabolome related to energy metabolism.20 Although these altered pathways were not detected on transcriptomic level in this study, the metabolomic changes suggested that energy metabolism was disrupted following monoHAcAms exposure. In addition, the pathway of primary bile acid biosynthesis, related to lipid metabolism, was significantly disturbed due to monoHAcAms-treatment (Table 1). It has been demonstrated that bile acid synthesis plays an important role in lipid metabolism.44 Likewise, the abnormal of lipid metabolism also affects the bile acid biosynthesis.45 Some SCMs, related to lipid metabolism, were also identified, such as taurine, glycine and 8216

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(8) Zhao, Y.-Y.; Boyd, J.; Hrudey, S. E.; Li, X.-F. Characterization of new nitrosamines in drinking water using liquid chromatography tandem mass spectrometry. Environ. Sci. Technol. 2006, 40 (24), 7636− 7641. (9) Plewa, M. J.; Muellner, M. G.; Richardson, S. D.; Fasano, F.; Buettner, K. M.; Woo, Y.-T.; McKague, A. B.; Wagner, E. D. Occurrence, synthesis, and mammalian cell cytotoxicity and genotoxicity of haloacetamides: An emerging class of nitrogenous drinking water disinfection byproducts. Environ. Sci. Technol. 2008, 42 (3), 955−961. (10) Hrudey, S. E. Chlorination disinfection by-products, public health risk tradeoffs and me. Water Res. 2009, 43 (8), 2057−2092. (11) Chu, W.; Gao, N.; Krasner, S. W.; Templeton, M. R.; Yin, D. Formation of halogenated C-, N-DBPs from chlor (am) ination and UV irradiation of tyrosine in drinking water. Environ. Pollut. 2012, 161, 8− 14. (12) Weinberg, H. S.; Krasner, S. W.; Richardson, S. D.; Thruston Jr., A. D. The Occurrence of Disinfection by-Products (DBPs) of Health Concern in Drinking Water: Results of a Nationwide DBP Occurrence Study; National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, 2002. (13) Richardson, S. D.; Postigo, C. Drinking water disinfection byproducts. In Emerging Organic Contaminants and Human Health; Springer: 2012; pp 93−137. (14) Shah, A. D.; Mitch, W. A. Halonitroalkanes, halonitriles, haloamides, and N-nitrosamines: A critical review of nitrogenous disinfection byproduct formation pathways. Environ. Sci. Technol. 2011, 46 (1), 119−131. (15) Plewa, M. J.; Wagner, E. D.; Muellner, M. G.; Hsu, K. M.; Richardson, S. D. Comparative mammalian cell toxicity of N-DBPs and C-DBPs. In Disinfection by-Products in Drinking Water: Occurrence, Formation, Health Effects, and Control; Karanfil, T., Krasner, S. W., Xie, Y., Eds.; American Chemical Society: Washington, DC, 2008; Vol. 995, pp 36−50. (16) Plewa, M. J.; Simmons, J. E.; Richardson, S. D.; Wagner, E. D. Mammalian cell cytotoxicity and genotoxicity of the haloacetic acids, a major class of drinking water disinfection by-products. Environ. Mol. Mutagen. 2010, 51, 871−878. (17) Attene-Ramos, M. S.; Wagner, E. D.; Plewa, M. J. Comparative human cell toxicogenomic analysis of monohaloacetic acid drinking water disinfection byproducts. Environ. Sci. Technol. 2010, 44 (19), 7206−7212. (18) Pals, J. A.; Ang, J. K.; Wagner, E. D.; Plewa, M. J. Biological mechanism for the toxicity of haloacetic acid drinking water disinfection byproducts. Environ. Sci. Technol. 2011, 45 (13), 5791−5797. (19) Pals, J.; Attene-Ramos, M. S.; Xia, M. H.; Wagner, E. D.; Plewa, M. J. Human cell toxicogenomic analysis linking reactive oxygen species to the toxicity of monohaloacetic acid drinking water disinfection byproducts. Environ. Sci. Technol. 2013, 47 (21), 12514−12523. (20) Zhang, Y.; Zhang, Z.; Zhao, Y.; Cheng, S.; Ren, H. Identifying health effects of exposure to trichloroacetamide using transcriptomics and metabonomics in mice (Mus musculus). Environ. Sci. Technol. 2013, 47 (6), 2918−24. (21) Lowry, O. H.; Rosebrough, N. J.; Farr, A. L.; Randall, R. J. Protein measurement with the Folin phenol reagent. J. biol. Chem. 1951, 193 (1), 265−275. (22) Lindon, J. C.; Nicholson, J. K.; Everett, J. R. NMR spectroscopy of biofluids. Annu. Rep. NMR Spectrosc. 1999, 38, 1−88. (23) Jordan, J.; Zare, A.; Jackson, L. J.; Habibi, H. R.; Weljie, A. M. Environmental contaminant mixtures at ambient concentrations invoke a metabolic stress response in goldfish not predicted from exposure to individual compounds alone. J. Proteome Res. 2011, 11 (2), 1133−1143. (24) Xia, J.; Wishart, D. S. MSEA: A web-based tool to identify biologically meaningful patterns in quantitative metabolomic data. Nucleic Acids Res. 2010, 38, W71−W77. (25) Murphy, P. A.; Craun, G.; Amy, G.; Krasner, S.; Dundorf, S. Enhanced evaluation of disinfectant by-product exposures for the reanalysis of cancer risks in previously conducted epidemiologic studies. Epidemiology 2000, 11 (4), S129−S129.

glycerol (SI Table S3). Taurine is important for lipid metabolism and regulation of hepatic lipid content.46 It was supported that taurine was significantly decreased in monoHAcAms treatment groups (Figure 3A and SI Table S2). In conclusion, these data support our hypothesis that the monoHAcAms can induce oxidative stress in mice and the rank order of IAcAm > BAcAm > CAcAm is consistent with other toxicological end points.9,47,48 In addition, metabolomic alterations were also found in mice treated with each of the monoHAcAms. Furthermore, the alterations of pathways related to amino acid metabolism, energy metabolism and lipid metabolism were identified based on SCMs. In this study, metabolomic methods were proved to be helpful to provide comprehensive views for the toxic effects of monoHAcAms.

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ASSOCIATED CONTENT

S Supporting Information *

Additional information as noted in the text. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Author Contributions †

Y.D. and Y.Z. contributed equally to all aspects of conceptualizing planning, sample and data collection, data analysis and preparation of the manuscript. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This research work was financially supported by the National Natural Science Foundation of China (51348009) and Natural Science Foundation of Jiangsu Province of China (BK20130559).

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dx.doi.org/10.1021/es502010v | Environ. Sci. Technol. 2014, 48, 8212−8218