Disruption of Kidney Metabolism in Rats after Subchronic Combined

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Disruption of Kidney Metabolism in Rats after Subchronic Combined Exposure to Low-Dose Cadmium and Chlorpyrifos Ming-Yuan Xu, Pan Wang, Ying-Jian Sun, and Yi-Jun Wu Chem. Res. Toxicol., Just Accepted Manuscript • DOI: 10.1021/acs.chemrestox.8b00219 • Publication Date (Web): 30 Nov 2018 Downloaded from http://pubs.acs.org on December 5, 2018

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Chemical Research in Toxicology

Disruption of Kidney Metabolism in Rats after Subchronic Combined Exposure to Low-Dose Cadmium and Chlorpyrifos

Ming-Yuan Xu †, Pan Wang †, Ying-Jian Sun †, ‡, Yi-Jun Wu †, * †

Laboratory of Molecular Toxicology, State Key Laboratory of Integrated

Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, PR China ‡

Department of Veterinary Medicine and Animal Science, Beijing University of

Agriculture, Beijing 102206, PR China

*Author

for correspondence: Yi-Jun Wu, Institute of Zoology, CAS, 1-5 Beichenxilu

Rd., Chaoyang, Beijing 100101, P. R. China E-mail: [email protected]; Tel: 86-10-64807251; Fax: 86-10-64807099.

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Chemical Research in Toxicology 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Table of Contents Graphic

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ABSTRACT Cadmium (Cd) and chlorpyrifos (CPF) often coexist in the environment and induce combined toxicity to organisms. Here we studied the combined nephrotoxicity of environmentally relevant low doses of Cd and CPF. We treated the mice for 90 days with different doses of Cd and CPF and their mixtures via oral gavage. Then histopathological evaluation and biochemical analysis for kidney tissues were carried out. The change of metabolites in kidney was detected by using a metabolomics approach using GC-MS. We found that Cd, CPF, and their mixtures caused oxidative damage, as well as disturbance of renal amino acid metabolism. We identified potential metabolite biomarkers in kidney, which included acetic acid for CPF treatment, glycerol and carboxylic acid for Cd treatment, and L-ornithine for the mixture of CPF and Cd treatment, respectively. In addition, we found that Cd promoted the metabolism of CPF in kidney. This may contribute to the result that the toxicity of the mixtures was lower than the sum of the toxicities of Cd and CPF alone. In conclusion, our results indicated that CPF and Cd could disrupt the kidney metabolism in rats even when they were exposed to very low dose of CPF and Cd. Key words: pesticide; heavy metal; metabolomics; kidney toxicity; combined toxicity

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1. INTRODUCTION Cadmium (Cd) is a widely used metal in industry. Cd has a long half-life of 20-30 years in human bodies.

1

Chronic exposure to Cd could induce hepatotoxicity, renal

dysfunction, and osteoporosis. insecticide

targeting

a

wide

2-4

Chlorpyrifos (CPF) is an organophosphorus

variety

of

pest

insects.

CPF

can

inhibit

acetylcholinesterase activity, which leads to cholinergic neurotoxicity. 5, 6 In addition, CPF could induce nephrotoxicity in both humans and experimental animals.7, 8 Thus, the environmental residues of both Cd and CPF are detrimental to human health. CPF and Cd accumulate in water, air, and soil, and humans can be simultaneously exposed to both CPF and Cd from food or environment.

9, 10

Since living organisms

are often exposed to multiple types of pollutants, it is crucial to study the combined toxicity of the mixtures. In addition, more and more studies suggest that one pollutant can potentiate the toxicity of another pollutant.

7, 11, 12

However, it is still not clear

whether chlorpyrifos and cadmium may cause nephrotoxicity at relatively low doses with chronic exposure. It is also important to investigate the subchronic combined nephrotoxicity of the compounds at low doses. Metabolomics is a systemic study of small molecule metabolites present in a biological samples by using analytical chemistry approaches.13 It has become a very useful tool to characterize the metabolic changes induced by toxic chemicals, and to identify the chemical-specific putative biomarkers.14-16 Gas chromatography-mass spectrometry (GC-MS) can analyze and quantify each individual components within the complex chemical mixtures of biological samples. Thus, GC-MS is widely used in

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metabolomics studies. 17, 18 In the present study, we sought to determine the combined subchronic nephrotoxicity of CPF and Cd at their low doses, and we also used metabolomics analysis to identify potential kidney biomarkers for intoxication of CPF and Cd.

2. MATERIALS AND METHODS 2.1. Chemicals Chlorpyrifos (purity > 96%) and cadmium chloride were obtained from Nantong Shuangma Fine Chemical Co., Ltd (Jiangsu, China) and Sigma-Aldrich Chemical Company

(St

Louis,

MO,

USA),

respectively.

Hexane

and

methanol

(chromatographic grade) were obtained from Dikma Technologies Inc. (Beijing, China). Thiobarbituric acid, hexane, 3, 4, 5-trichloropyrindinol, guanidine hydrochloride, methoxyamine, methyl-trimethyl-silyl-trifluoroacetamide (MSTFA), and trimethylchlorosilane (TMCS) were purchased from J & K Chemical Ltd (Beijing,

China).

Sodium

4-[3-(4-iodophenyl)-2-(4-nitrophenyl)-2H-5-tetrazolio]-1, (WST-1)

was

purchased

from

Dojindo

salt 3-benzene

Laboratories

of disulfonate

(Kumamoto,

Japan).

Paraformaldehyde, hematoxylin, and eosin were purchased from Solarbio Chemical Company (Beijing, China). Hydrogen peroxide, 2, 4-dinitrophenylhydrazine (DNPH), nitric acid, heptadecanoic acid, methanol, and chloroform were of analytical grade and purchased from Beijing Chemical Corporation (Beijing, China).

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2.2. Animals and treatment Eighty male Sprague-Dawley rats (Beijing HFK Bioscience Co., Ltd, Beijing, China) were used in the study and the rats were 6-8 weeks old with body weight around 200 g at the beginning of the study. The animal room where the rats were housed was maintained under the specific-pathogen-free condition with 22 ± 2°C, 50%-60% humidity and a light/dark cycle of 12 h. Animals had free access to water and commercially prepared laboratory animal diet. The rats were randomly assigned to different groups and treated with Cd, CPF, or their mixtures. The acute half-lethal doses (LD50) of CPF and Cd in rats by oral gavage were 229 mg/kg body weight (BW) and 88 mg/kg BW, respectively. 2, 19 In this study, the doses of 1/135 LD50, 1/45 LD50, and 1/15 LD50 of each chemical were used as low-, middle-, and high-dose for the treatment groups, respectively. Thus, the low, middle, and high doses used in the experiments were 0.7, 2.0, and 6.0 mg/kg BW/day for Cd; and 1.7, 5.0, and 15.0 mg/kg BW/day for CPF, respectively. Experimental design was shown in Suppl. Table S1. The low doses of Cd and CPF used in this study (0.7, 1.7 mg/kg BW/day, respectively) were chosen based on possible human exposure to Cd and CPF. The detailed calculation was illustrated in our previous study. 20 Cadmium chloride (Cd) and chlorpyrifos (CPF) were dissolved in deionized water and corn oil, respectively, and given to rats via oral gavage (the volume doses were both 0.5 ml/kg BW/day) for 5 consecutive days every week. The 2 days off per week for oral gavage was used to avoid the possible esophagus injury. The rats in

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Cd-groups were treated with cadmium chloride and were also given equivalent volume of corn oil, the CPF vehicle, in the meantime, and the rats in CPF-groups were treated with CPF and were also given equivalent volume of the Cd vehicle deionized water. The animals in Cd plus CPF groups received both cadmium chloride and CPF. The control group rats received the same volume of corn oil and water. The whole experiment lasted for 90 days. All animal procedures were performed according to the applicable Chinese legislation and the study was approved by the Chinese Academy of Sciences Institute of Zoology’s Animal and Medical Ethics Committee with the approval number “IOZ-2014-0014”.

2.3. Sample preparation After the 90-day experimental treatment, animals were fasted for 12 h overnight, anesthetized with phenobarbital by intraperitoneal injection and then decapitated. Blood samples were collected. Parts of the kidney tissues were snap-frozen in liquid nitrogen and stored at -80°C until they were used for metabolomic and biochemical analyses. The rest of the kidney tissues were fixed with 4% paraformaldehyde buffered in 0.1 M phosphate buffered saline (pH 7.4) for further histopathological examination.

2.4. Histopathology After fixation, the kidney tissues were dehydrated in alcohol and xylene, and then

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embedded in paraffin. The sections with 4-µm thickness were then rehydrated and stained with hematoxylin and eosin, and then observed with microscope (Olympus, Tokyo, Japan). The histological changes observed in the kidney tissue sections were evaluated by a blinded pathologist.

2.5. Determination of oxidative damage parameters Spectrophotometric methods were used to determine four oxidative damage parameters. WST-1 reduction rate was measured to reflect superoxide dismutase (SOD) activity.

21

Hydrogen peroxide removal (HPR) activity was measured by the

disappearance rate of H2O2.

22

The reaction mixture contains 0.1 ml of the diluted

kidney homogenate (300 µg/ml), 0.5 ml of 0.01 M phosphate buffer (pH7.0), and 0.4 ml of 0.2 M H2O2. The unit of HPR activity was µmoles of H2O2 consumed/min/mg protein. Malondialdehyde (MDA) is one of the small molecule end products of the decomposition of lipid peroxidation products. MDA was used to reflect lipid peroxidation level. MDA was determined by the reaction with thiobarbituric acid (TBA).23 It is of note that although the MDA determination using TBA is not absolutely specific for lipid peroxidation, since TBA can react with substances other than MDA and MDA is not generated exclusively through lipid peroxidation, the TBA test offers an empirical estimation of the lipid peroxidation status.24 Protein carbonyl (PCO) was products of protein oxidation, and PCO was determined by the reaction with DNPH. 25

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2.6. Sample processing for GC-MS analysis The kidney tissues were ground in liquid nitrogen and 100 mg of the tissues were used

for

metabolites

extraction.

Six

hundred

microliters

(600

µl)

of

methanol/chloroform/water (5:1:1, v: v: v) was added to homogenize the tissues. Ten microliters of 6 mg/mL heptadecanoic acid was added as the internal standard. Then, the homogenate was incubated for 15 min on ice. The homogenate was centrifuged at 15,000 g for 15 min at 4°C and the supernatant (250 µl) was collected, and dried in a vacuum concentrator. Methoxyamine in pyridine (50 µl) was added to the dried metabolites extract and incubated for 16 h at room temperature. Then 100 µl of MSTFA with 1% TMCS was added to the samples and the samples were incubated for another 1 hour. Finally, 200 µl of hexane was added to the samples and the samples were centrifuged at 15,000 g for 15 min. The supernatant was collected for GC-MS analysis.

2.7. GC-MS analysis A 6890N Agilent gas chromatograph system (Agilent Co., Palo Alto, CA, USA) with a HP-5 MS capillary column (60 m × 0.25 mm × 0.25 µm) was used for gas chromatography. The injection temperature was 250°C and the carrier gas flow rate was 1 ml/min. The column temperature was 90°C for 1 min and then raised to 175°C at 5°C/min and held for 3 min. The temperature was then raised to 270°C at 3°C/min and then raised to 310°C at 20°C/min. And then it was maintained at 310°C for 15 min. The temperature of the transfer interface was 250°C and the ion source was

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200°C. A 70 eV electron source generated ions at the full scan mode (m/z 40–600) and the acquisition rate was 20 spectra/s.

2.8. Metabolomics data analysis NIST library 2005 was used to identify the metabolites in the rat kidney samples. And automatic mass spectral deconvolution and identification system (AMDIS) was used to address spectral convolution. Peaks with signal-to-noise ratio higher than 3 were selected. Data pretreatment procedures for metabolites were performed by using Matlab 7.1 (The MathWorks, Inc., Natick, MA, USA). Multivariate statistical analysis was carried out using partial least squares discriminant analysis (PLS-DA) with SIMCA-P 11.5 software (Umetrics, Umeå, Sweden). In order to select the candidate biomarkers, SIMCA-P software was used to calculate the variable importance in the project (VIP) values. The data of metabolites levels were checked to have a normal distribution by using SPSS18.0 software (SPSS, Inc., Chicago, MI, USA). Thus, analysis of variance (ANOVA) F-test in SPSS 18.0 software was used to calculate the significance among groups for these candidate biomarkers and only those with P < 0.05 were selected. Finally, to determine the accuracy of the biomarkers to distinguish the treated groups from the control group, the area under the curve (AUC) value for receiver-operating characteristic (ROC) curve was calculated by using SPSS 18.0 software. Metabolites with AUC > 0.9 or AUC < 0.1 had high accuracy and were selected as potential biomarkers. 26

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2.9. Cd determination in kidney The levels of Cd in the kidneys of rats were determined by using the inductively coupled plasma-mass spectrometry (ICP-MS) (Agilent 7500, USA).

27

Briefly, 100

mg kidney samples were digested in 500 μL of nitric acid and hydrogen peroxide (3:2) for 20 min at 180°C in microwave. Calibration standards of Cd were prepared with concentrations ranging from 0.05 to 100 μg/mL. The limit of detection (LOD) and the limit of quantitation (LOQ) were calculated by using a reported method. 28 LOD for Cd was 0.5 ng/L and LOQ for Cd was 2 ng/L.

2.10.

Determination of CPF and TCP level in the kidney

The quantification of CPF and 3, 4, 5-trichloropyrindinol (TCP), the metabolite of CPF, was carried out using an Agilent 1100 series HPLC system (Agilent Co., USA). 29

Briefly, about 100 mg of kidney tissues were ground in 500 μL methanol. The

supernatants were collected after centrifugation, and then dried under nitrogen and then dissolved in 150 μl methanol. Calibration standards of CPF and TCP were prepared in acetonitrile with concentrations ranging from 0.1 to 10 mg/mL. LOD for CPF was 0.05 mg/mL and LOQ for CPF was 0.1 mg/mL.

2.11.

Statistical analysis

Statistical evaluation was carried out using SPSS 18.0 software (SPSS, Inc., Chicago, MI, USA). The raw data were checked to have a normal distribution by

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using SPSS. For the data analysis except for the metabolomics data, the significance among the groups was determined by ANOVA test, followed by post hoc Turkey’s test. P value less than 0.05 indicated that the difference was significant.

3. RESULTS 3.1. Kidney weights and histological changes of rats exposed to CPF, Cd, and their mixtures Body weight increase of rats in high-dose CPF group was smaller compared with that of the control rats, probably due to the reduced food intake (data not shown). No deaths were found during the course of the experiment. To investigate the general nephrotoxicity of CPF, Cd, and CPF plus Cd, we measured kidney weights. Relative kidney weights were not changed in the Cd-, CPF- or their mixtures-treated rats compared to those of the control rats (data not shown). To determine whether CPF and Cd caused kidney damage, we examined the histopathological changes of the kidneys in the rats treated with CPF, Cd, and CPF plus Cd. However, CPF or Cd did not induce prominent histopathological changes in kidney compared with the control (Figure 1 and Suppl. Figure S1).

3.2. CPF, Cd, and CPF plus Cd induced kidney oxidative damage Oxidative stress was crucial for CPF- and Cd-induced renal damage.

30, 31

To

determine the oxidative damage induced by CPF and Cd in rats, we determined the indicators of oxidative damage in the kidneys from the rats treated with CPF, Cd or

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CPF plus Cd. CPF, Cd, and CPF plus Cd at higher doses could inhibit the SOD activity in kidney. However, the effect of CPF plus Cd on SOD was similar to that of CPF or Cd alone (Figure 2A). The decrease of HPR activity in kidney was prominent in the rats treated with only high-dose of CPF or Cd. Compared with the control, no alterations of HPR activity were found in any doses of CPF plus Cd-treated rats (Figure 2B). The contents of MDA and PCO in kidney were determined to reflect the change of lipid and protein peroxidation, respectively. We found that CPF, Cd, and CPF plus Cd could increase MDA and PCO levels, albeit without significant difference among different groups (Figure 3A and B). We used the design-expert software to analyze the relationship between the factors (CPF and Cd) and responses [four reactive damage related parameters]. To analyze the interaction of CPF and Cd, the quadratic equation for CPF and Cd was used as follows: Y = β0 + β1X1 + β2X2 + β3X1X2 + β4X12 + β5X22, where β0 is the intercept which represents the arithmetic averages; X1 and X2 are the doses of CPF and Cd, respectively; β1 to β5 are coefficients, and β1 and β2 represent the main effect of CPF and Cd, respectively. If the P values for β3 are less than 0.05, the two factors have an interaction. When an interaction is present, the main effect parameters (β1 and β2) with the same algebraic signs indicate synergism, and the opposite signs indicate antagonism. However, in this study, the P values for β3 for the responses (four reactive damage related parameters SOD, HPR, MDA and PCO) were not significant (P = 0.5589, 0.5506, 0.2330, and 0.3720, respectively), which indicated that CPF and Cd had no interaction on the reactive damage-related parameters in kidney tissues.

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3.3. CPF and Cd treatment altered metabolic profiles in kidney Multivariate analysis on the metabolic data was performed to assess the metabolomic changes of the kidney from the rats treated with chemicals. The score plots from PLS-DA for the kidney showed that the treatment groups separated from the control group, suggesting that kidney metabolism was altered upon treatment with Cd, CPF, and CPF plus Cd (Figure 4A and Suppl. Figure S2). The mixture-treated groups were different than the Cd- or CPF-treated groups, especially for middle- and high-doses groups, which suggested that Cd plus CPF induced different changes of metabolites compared with individual Cd and CPF.

3.4. Identification and validation of the kidney metabolites biomarkers CPF, Cd, and CPF plus Cd induced the alteration of metabolites and tissue damage in organisms. However, no biomarkers in kidney were available for the diagnosis of the poisoning of CPF, Cd, or their combinations. To identify the potential biomarkers in kidney, the VIP values were calculated and ANOVA was performed among all of the groups. The metabolites with VIP values > 1 and significant differences among all groups (P < 0.05) were selected as candidate biomarkers. Total 45 metabolites which met these two criteria were picked in this screening step. These metabolites were displayed in the heat map and their levels were converted into z-scores [z-scores = (value − mean)/ standard variation] (Figure 4B).

32

In kidney, most of metabolite

levels decreased after the treatment with CPF or Cd alone compared to control.

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However, after the CPF plus Cd treatment, the metabolites levels increased in general. A large part of these differential metabolites were amino acids, which indicated that the metabolism of amino acids was disturbed by the treatment of CPF, Cd, and CPF plus Cd (Figure 4B). Finally, we performed a ROC analysis for the 45 biomarker candidates to find potential metabolite biomarkers for CPF, Cd, and CPF plus Cd (Figure 5 and Table 1). If a metabolite has 0.9 < AUC < 1 or 0 < AUC < 0.1, it can predict the intoxication with high accuracy.

25

Total seven potential biomarkers were identified and two of

them (L-tyrosine and L-phenylalanine) were common biomarkers for all treatment groups. Acetic acid, L-tyrosine, and L-phenylalanine could distinguish CPF-treated groups from the control groups (Figure 5). Increased concentrations of glycerol, L-tyrosine, and L-phenylalanine, and decreased level of carboxylic acid could indicate the intoxication of Cd (Figure 5). L-Ornithine, L-tyrosine, and L-phenylalanine also had a high sensitivity and specificity for the discrimination of CPF plus Cd from other groups (Figure 5). Thus, the unique potential biomarkers for CPF, Cd, and their mixtures were acetic acid, glycerol and carboxylic acid, and L-ornithine, respectively.

3.5. The metabolism of CPF in kidney was affected by Cd To investigate the mechanism of CPF and Cd’s interaction in kidney, we determined whether CPF and Cd’s metabolism was affected by each other. We found that the concentration of CPF decreased in CPF plus Cd-treated rats, compared with that in the CPF alone-treated rats. And the level of TCP, the final product of CPF

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metabolism by cytochrome P450 (CYP450), increased in the kidney of CPF plus Cd-treated rats, compared with that in the CPF alone-treated rats (Figure 6A and B). The kidney concentration of Cd in the rats treated with CPF plus Cd was not altered compared with that of the rats treated with Cd alone (Figure 6C). Thus, it is suggested that Cd affected the metabolism of CPF, but CPF did not affect Cd level in kidney.

4. DISCUSSION Currently, given that organophosphates and metals are common pollutants in the environment, more research is needed to study the combined toxic effect of organophosphates and metals. 33, 34 Both CPF and Cd had nephrotoxicity, 34-36 and the induction of oxidative stress is pivotal for their nephrotoxicity.

37, 38

Generally

speaking, additive responses, which means that the toxicity of combinations of chemicals equals to the sum of individual chemical response, would be expected. 39 Although no statistical interaction was present between the CPF and Cd in kidney, the combination of CPF and Cd was still less toxic than the sum of the two chemical alone. This may be largely caused by the fact that Cd promoted the degradation of CPF in kidney (Figure 6), which may cause that CPF plus Cd had lower toxicity compared with the sum of the individual toxicity of CPF and Cd. The underlying mechanism of how Cd accelerates CPF metabolism, and whether Cd and CPF affected the absorption, distribution and excretion of each other merits further investigation. Since CPF is mainly metabolized by cytochrome P450 (CYP450), 40 it is possible that Cd affected CPF metabolism by the induction of CYP450 activity. Indeed, a previous 16


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report has shown that Cd induced CYP450 activity in kidney of rats. 41 The 2 days off per week for oral gavage of the chemicals was used to avoid the injury of the esophagus. CPF had a rapid clearance with half-life about 30 hours. 42 Thus, 2 days off per week may lead to the reduced toxicity of CPF. However, due to the fact that Cd has a much longer half-life, 2 days off per week had little effect on the toxicity of Cd. By using a GC-MS-based metabolomic approach, for the first time, we demonstrated that CPF and Cd significantly altered the metabolic profiles in the kidney of rats. Forty-five metabolites were significantly altered in kidney after CPF and Cd treatments. In the kidneys from the rats treated with CPF, Cd, and CPF plus Cd, we detected the prominent alterations of a number of metabolites, which were mainly involved in the amino acids metabolism. A few changes in energy metabolism and lipid metabolism were also identified. Three doses of CPF and Cd were used in our study and the low doses (1.7 and 0.7 mg/kg BW/day, respectively) are similar to the levels of human occupational exposure as well as environmental exposure.

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The data of kidney weight in the rats

suggested that CPF and Cd could not cause obvious kidney toxicity, except at high dose of CPF. In addition, the histopathological damage of the kidneys after Cd or CPF treatment was not evident. Previous reports have shown that chronic exposure to Cd could induce atrophy in renal proximal tubules and interstitial fibrosis, and exposure to CPF could induce epithelial cells edema in the glomeruli and tubular space reduction. 43, 44 The reason why the histopathological changes were not detected in our

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study may be due to the low doses we used. However, the metabolites in kidneys had significant changes at the low dose of CPF, Cd and their combinations while the toxic signs and the histopathological damage could not be observed. Thus, the metabolites changes were more sensitive to toxicants compared with other pathological parameters. Compared with our earlier metabolomics results in liver,

45

we found that the

potential biomarkers in liver and kidney were very different. The biomarkers in liver after CPF, Cd, and CPF plus Cd treatment, except L-phenylalanine, were different with the biomarkers in kidney. The unique biomarker in liver for Cd was L-aspartic acid, which was not unique biomarker for Cd in kidney (carboxylic acid and glycerol). Compared with another metabolomics study in brain reported earlier, 46 we found that the sixteen biomarkers in brain, except L-tyrosine, were also different from the biomarkers in kidney. These results indicate that changes in metabolites induced by CPF and Cd are tissue-specific. Thus, it is necessary to identify the tissue-specific biomarkers. In conclusion, CPF, Cd, and CPF plus Cd induced the oxidative damage in the kidney. With the use of GC-MS, we identified the potential biomarkers for CPF, Cd, and CPF plus Cd in kidney. The unique potential biomarkers in kidney for CPF, Cd, and CPF plus Cd were acetic acid, glycerol and carboxylic acid, and L-ornithine, respectively.

Supporting Information

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Table S1 shows animal experimental design for combined toxicity of CPF and Cd.

Figure S1 shows Cd- and CPF-induced histopathological changes in kidney of

rats. Figure S2 shows score plots of PLS-DA for kidney metabolites identified with GC-MS in rats. Rats were treated with Cd and CPF at 0.7 and 1.7 mg/kg/day (L), 2 and 5 mg/kg/day (M), and 6 and 15 mg/kg/day (H) and their mixtures by oral gavage for 90 days. The kidney pathological slices were stained with hematoxylin and eosin (Figure S1). Blank ellipse, control group; blue ellipse, Cd-treated groups; red ellipse, CPF-treated groups; green ellipse, combination treatment groups. Abbreviations: CON, control; L, low dose; M, middle dose; H, high dose; Cd, cadmium; CPF, chlorpyrifos. This material is available free of charge via the Internet at http://pubs.acs.org.

Declaration of conflicting interests The authors declare that there are no conflicts of interest.

Acknowledgments This work was supported in part by the grants from the CAS Strategic Priority Research Program (No. XDB14040203), and the National Natural Science Foundation of China (No. 31472007).

Abbreviations AMDIS, automatic mass spectral deconvolution and identification system;

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ANOVA, analysis of variance; AUC, the area under the curve; BW, body weight; Cd, cadmium;

CPF,

chlorpyrifos;

CYP450,

cytochrome

P450;

DNPH,

2,

4-dinitrophenylhydrazine; GC-MS, gas chromatography-mass spectrometry; HPR, hydrogen peroxide removal; ICP-MS, inductively coupled plasma-mass spectrometry; LD50, half-lethal doses; LOD, limit of detection; LOQ, limit of quantitation; MDA, malondialdehyde; MSTFA, methyl-trimethyl-silyl-trifluoroacetamide; PCO, protein carbonyl;

PLS-DA,

Partial

least

squares

discriminant

analysis;

ROC,

receiver-operating characteristic; SOD, superoxide dismutase; TBA, thiobarbituric acid; TCP, 3, 4, 5-trichloropyrindinol; TMCS, trimethylchlorosilane; VIP, variable importance

in

the

project;

WST-1,

4-[3-(4-iodophenyl)-2-(4-nitrophenyl)-2H-5-tetrazolio]-1, 3-benzene disulfonate.

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Table 1. The AUC values of the 45 metabolites that changed significantly in the kidney of the treated rats compared with those in the control group No.

Metabolites

Retention time (min)

P valuea

AUCb Cd

CPF

Cd plus CPF

1

Acetic acid

9.118

0.000

0.844

0.917

0.835

2

Carboxylic acid

13.668

0.016

0.031

0.139

0.205

3

L-Leucine

14.355

0.000

0.625

0.722

0.631

4

Sorbitol

15.207

0.000

0.234

0.306

0.364

5

Dihydroxybutanoic acid

16.211

0.003

0.375

0.611

0.347

6

Homocysteine

17.893

0.015

0.281

0.278

0.318

7

Methyltyrosine

19.626

0.002

0.609

0.778

0.665

8

Malic acid

19.982

0.01

0.609

0.778

0.614

9

Methionine

20.308

0.001

0.391

0.528

0.46

10

Glutamine

20.434

0.001

0.125

0.111

0.273

11

Proline

20.552

0.000

0.172

0.139

0.318

12

Hydroxyglutaric acid

22.007

0.000

0.359

0.333

0.46

13

Creatinine

22.281

0.000

0.563

0.639

0.693

14

L-phenylalanine

24.411

0.003

0.938

0.917

0.903

15

L-aspartic acid

26.251

0.011

0.359

0.333

0.369

16

Galactitol

27.267

0.002

0.703

0.722

0.892

17

Galactose

27.956

0.001

0.875

0.806

0.585

18

Ribonic acid

29.503

0.000

0.25

0.194

0.449

19

L-Ornithine

30.895

0.032

0.797

0.889

0.909

20

Citrate

31.11

0.011

0.266

0.194

0.409

21

Fructose

32.513

0.007

0.438

0.333

0.494

22

D-Glucose

33.818

0.039

0.438

0.472

0.432

23

L-Lysine

34.38

0.002

0.813

0.75

0.886

24

Tyrosine

34.907

0.000

0.984

0.972

0.932

25

D-Gluconic acid

36.312

0.000

0.719

0.889

0.881

26

Palmitelaidic acid

37.056

0.001

0.703

0.444

0.739

27

Myo-Inositol

38.14

0.000

0.484

0.361

0.574

28

D-Mannitol

41.604

0.000

0.781

0.722

0.79

29

9,12-Octadecadienoic acid

42.767

0.000

0.844

0.722

0.858

30

Oleic acid

42.928

0.007

0.344

0.306

0.432

31

Phosphoric acid

43.142

0.003

0.234

0.333

0.358

32

D-Galactofuranose

43.618

0.033

0.375

0.417

0.597

33

α-Glycerophosphoric acid

43.746

0.000

0.297

0.306

0.432

34

D-Glucopyranuronic acid

44.484

0.000

0.125

0.111

0.352

35

Lanthionine

44.551

0.000

0.641

0.583

0.795

36

N-Acetyl glucosamine

44.837

0.002

0.656

0.528

0.81

37

Arachidonic acid

47.146

0.000

0.719

0.472

0.693

28


Page 29 of 39 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


38

Uridine

47.868

0.000

0.656

0.611

0.699

39

Glycerol

48.569

0.057

0.969

0.889

0.818

40

Threitol

51.133

0.016

0.328

0.333

0.398

41

Linolenic acid

52.506

0.000

0.219

0.278

0.381

42

Glucuronolactone

53.349

0.000

0.859

0.778

0.705

43

Maltose

56.544

0.000

0.281

0.25

0.409

44

Inosine

59.284

0.000

0.094

0.194

0.278

45

Cholesterol

61.873

0.000

0.438

0.722

0.597

a

P values (treatment vs control) were calculated using ANOVA.

b

AUC values (treatment vs control) were calculated using ROC analysis. Metabolites with 0.9
0.9 were increased in the treatment groups. And levels of biomarkers with AUC < 0.1 were decreased in the treatment groups compared to control group.

29



Figure legends

Figure 1. Chlorpyrifos (CPF) and cadmium (Cd) did not induce prominent histological changes in kidney of rats. Representative images of the H & E stained sections of kidney from the rats treated with vehicle (A), CPF at high dose of 15 mg/kg body weight /day (B), Cd at high dose of 6 mg/kg body weight /day (C), and CPF plus Cd at their high doses (D), respectively, by oral gavage for 90 days. Scale bar = 50 µm. The images at the lower left corner are four times enlarged images of the area within the black rectangle.

Figure 2. CPF and Cd treatment reduced SOD activity (A) and HPR activity (B) in kidney of rats. Sprague-Dawley rats were treated with CPF, Cd at doses of 1.7 and 0.7 mg/kg BW/day (L), 5 and 2 mg/kg BW/day (M), 15 and 6 mg/kg BW/day (H), respectively, and their mixtures by oral gavage for 90 days. Data were expressed as mean ± SE (n = 5) and significance among groups was evaluated by ANOVA. Different letters (a, b, c, and d) indicate a significant difference among groups (P < 0.05), while the same letters indicate no significant difference among groups (P > 0.05). Abbreviations: BW, body weight; L, low dose; M, middle dose; H, high dose; CPF, chlorpyrifos; Cd, cadmium; HPR, hydrogen peroxide removal activity; SOD, superoxide dismutase.

Figure 3. CPF and Cd treatment induced MDA (A) and PCO level (B) in kidney of

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rats. Sprague-Dawley rats were treated with CPF, Cd at 1.7 and 0.7 mg/kg BW/day (L), 5 and 2 mg/kg BW/day (M), 15 and 6 mg/kg BW/day (H), respectively, and their mixtures by oral gavage for 90 days. Data were expressed as mean ± SE (n = 5) and significance among different groups was evaluated by ANOVA. Different letters (a, b, c, and d) indicate a significant difference among groups (P < 0.05), while the same letters indicate no significant difference among groups (P > 0.05). Abbreviations: BW, body weight; L, low dose; M, middle dose; H, high dose; Cd, cadmium; CPF, chlorpyrifos; MDA, malondialdehyde; PCO, protein carbonyls.

Figure 4. CPF and Cd changed kidney metabolic profiles. The Sprague-Dawley rats were treated with CPF, Cd at 1.7 and 0.7 mg/kg BW/day (L), 5 and 2 mg/kg BW/day (M), 15 and 6 mg/kg/day (H), respectively, and their mixtures by oral gavage for 90 days. (A) The representative PLS-DA score plots for the rats treated with CPF, Cd at 1.7 and 0.7 mg/kg/day, respectively, and their mixtures for 90 days (n = 5). Blank ellipse: control group; Red ellipse: CPF groups; Blue ellipse: Cd groups; Green ellipse: Cd plus CPF groups. (B) The levels of 45 kidney metabolites that changed significantly by the treatments were shown in hierarchically clustered heat map. Each metabolite is represented by a single row of colored boxes, whereas columns represented different treatment groups. Different colors indicate different metabolite levels. The z score was defined by the observed value subtracted by the average, and then divided by the standard deviation. Candidate biomarkers in kidney: 1: Acetic acid; 2: Carboxylic acid; 3: L-Leucine; 4: Sorbitol; 5: Dihydroxybutanoic acid; 6:

31



Page 32 of 39

Homocysteine; 7: Methyltyrosine; 8: Malic acid; 9: Methionine; 10: Glutamine; 11: Proline; 12: Hydroxyglutaric acid; 13: Creatinine; 14: L-phenylalanine; 15: L-Aspartic acid; 16: Galactitol; 17: L-Ornithine; 18: Citrate; 19: Fructose; 20: D-Glucose; 21: Galactose; 22: L-Lysine; 23: L-Tyrosine; 24: D-Gluconic acid; 25: Palmitelaidic acid; 26: Myo-inositol; 27: Ribonic acid; 28: D-Mannitol; 29: 9,12-Octadecadienoic

acid;

30:

Oleic

acid;

31:

Phosphoric

acid;

32:

D-Galactofuranose; 33: α-Glycerophosphoric acid; 34: D-Glucopyranuronic acid; 35: Lanthionine; 36: N-Acetyl-glucosamine; 37: Arachidonic acid; 38: Uridine; 39: Glycerol; 40: Threitol; 41: Linolenic acid; 42: Glucuronolactone; 43: Maltose; 44: Inosine; 45: Cholesterol. Abbreviations: BW, body weight; CPF, chlorpyrifos; Cd, cadmium; L, low dose; M, middle dose; H, high dose. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article).

Figure 5. Potential kidney biomarkers for CPF-, Cd-, and CPF plus Cd-treated rats. The metabolites could distinguish CPF- (Red), Cd- (Blue) and CPF plus Cd-treated (Yellow) groups from control group. The metabolites which lie in areas of circles other than the overlapping areas are the unique biomarkers for different treatments. The upward and downward arrows indicate that the biomarkers increased or decreased in the treatment groups, respectively. Abbreviations: Cd, cadmium; CPF, chlorpyrifos. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article).

32


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Figure 6. The metabolism of CPF was affected by Cd in rat kidneys. Sprague-Dawley rats were treated with CPF, Cd at doses of 1.7 and 0.7 mg/kg BW/day (L), 5 and 2 mg/kg BW/day (M), 15 and 6 mg/kg BW/day (H), respectively, and their mixtures by oral gavage for 90 days. The levels of CPF (A), TCP (B), and Cd (C) in kidneys of rats in different treatments were shown in bar graphs. Data were expressed as mean ± SE (n = 5) and significance among different groups was evaluated by ANOVA. Different letters (a, b, c, and d) indicate a significant difference among groups (P < 0.05), while the same letters indicate no significant difference among groups (P > 0.05). Abbreviations: BW, body weight; L, low dose; M, middle dose; H, high dose; Cd, cadmium; CPF, chlorpyrifos; TCP, 3, 4, 5-trichloropyrindinol.

33



Figure 1

34


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Figure 2

35



Figure 3

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Figure 4

37



Figure 5

38


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Figure 6

39


Disruption of Kidney Metabolism in Rats after Subchronic Combined

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