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Abstract

The present study aims to investigate the protective effect of quercetin against the joint toxic action induced by the mixture of four organophosphate pesticides (mixture-OPs) (dimethoate, acephate, dichlorvos, and phorate) at their corresponding no observed adverse effect level (NOAEL) using metabonomics. Rats were randomly divided into control, quercetin-treated, mixture-OPs-treated, and quercetin plus mixture-OPs-treated groups. Mixture-OPs and quercetin were given to the rats daily through drinking water and intragastric administration, respectively, for 90 days. The metabonomic profiles of rat urine were analyzed using ultra-performance liquid chromatography–mass spectrometry (UPLC/MS). The 14 metabolites significantly changed in the treatment groups compared with the control group, including the biomarkers of OPs exposure (dimethylphosphate, dimethyldithiophosphate, diethylphosphate) and the metabolites of quercetin (quercetin and isorhamnetina). The intensities of gentisic acid, creatinine, suberic acid, hippuric acid, uric acid, and citric acid significantly decreased, whereas the intensities of 7-methylguanine, estrone sulfate, and cholic acid significantly increased, in the mixture-OPs-treated group compared with the control group (p < 0.01). The variation tendency of the aforementioned metabolites was significantly ameliorated in the high-dose quercetin (50 mg/(kg bw day)) plus mixture-OPs-treated group compared with the mixture-OPs-treated group (p < 0.05). However, the intensities of these metabolites in the high-dose quercetin plus mixture-OPs-treated group were still significantly different from those of the control group (p < 0.05). Results indicated that high dose of quercetin elicits a partial protective effect on the toxicity induced by mixture-OPs, including fatty acid and energy metabolism, antioxidant defense system, DNA damage, and liver and kidney function.

Keywords

Quercetin mixture of organophosphate pesticides NOAEL rat urine metabonomics

Introduction

Organophosphate pesticides (OPs) have been widely used in agriculture, industry, public health, and domestic application for several decades because of their highly effective insecticidal activities, low cost, and wide varieties. However, the wide use of OPs causes varying degrees of environmental pollution, including air, drinking water, and soil pollution.¹ People are inevitably exposed to OPs from various sources. The characteristic of exposure is long-term and low-dose oral intake. The primary route of OPs exposure for nonoccupational populations may be through residues in food and/or water and exposure to more than one kinds of OP simultaneously. Therefore, the influence of the mixture of OPs (mixture-OPs) on human health has gained the attention of researchers worldwide.

OPs is a well-known acetylcholinesterase inhibitor, which induced specific neurobehavioral effects, including cholinergic signs of toxicity and behavioral effects. The joint toxic action of OPs has been studied since the 1950s.² Until now, numerous studies have demonstrated that the joint toxic action of OPs includes interaction, independence, synergism, antagonism, and additivity.³ Therefore, reducing the toxicity caused by mixture-OPs has become the focus of researchers.

Quercetin is the major flavonoid that belongs to the class called flavonols. Quercetin is found in many common foods including apples, tea, onions, nuts, berries, cauliflower, cabbage, and other foods. Numerous studies have shown that quercetin can elicit antioxidant, anti-inflammatory, anticancer, immunomodulatory, antiaggregatory, and vasodilating effects in vivo and in vitro.^4,5 Furthermore, epidemiological studies have found that increased intake of quercetin can reduce the incidence of cardiovascular disease, hypertensive disease, cancer, neurodegenerative diseases, and gastrointestinal diseases.^6,7 Some researchers have found that the biological activity of quercetin may be closely related to its antioxidant action.⁸ In addition, animal experiments have proven that quercetin protects organisms against the toxicity of exogenous poisons, including OPs, polyaromatic hydrocarbons, and hazardous metals.^9

–12 Uzun et al.^9,10 have investigated the protective effect of quercetin against chlorpyrifos-induced lung toxicity, hepatotoxic, and hematologic changes in rats. The results indicated that quercetin has improved the cellular antioxidant status in the lung and liver. However, these studies have focused mainly on the protective property of quercetin on one or two kinds of pesticides, and mostly concerning the tissues at the organ level rather than at the organism level in rats. Therefore, a systemic approach is necessary to determine whether quercetin protects against the joint toxic action induced by mixture-OPs.

Metabonomics is defined as “the quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification.”¹³ Low-molecular-weight (typically < 1500 Da) metabolites (e.g. plasma, urine, synovial fluid) are measured to analyze metabolites and identify the biomarkers in biofluids or tissues. The metabolic pathways and networks altered by biological effects can also be identified. Metabonomics couples advanced spectroscopic techniques with multivariate or chemometric analysis to study the global alteration of metabolism in biofluids and tissues in response to external stimulus, offering a promising scientific platform for safety assessment.¹³ In our previously studies,^14

–17 the toxicity of dichlorvos, acephate, dimethoate, and phorate were evaluated using metabonomics. The results showed that metabonomics can offer more toxicology information than the conventional toxicology method. Metabonomics has been widely used in many fields owing to its advantages.^18,19

Dichlorvos, phorate, dimethoate, and acephate are the most widely used OPs in agriculture and public health programs in China. Therefore, residues of these insecticides are commonly found in foods.²⁰ The toxicity of OPs is influenced by several factors, such as nature of OPs, exposure level, and exposure time. Humans are usually exposed to multiple chemicals simultaneously, which may interact with each other. Interaction between these chemicals may enhance or reduce their toxicity. Quercetin is contained in our diet, and may be metabolized by the same pathway as pesticides.²¹ Therefore, we speculated that dietary quercetin may affect the toxicity of mixture-OPs at the body metabolism level. In our previously published articles,^22,23 the toxicity of the mixture of four aforementioned OPs at their corresponding no observed adverse effect level (NOAEL) on rats was evaluated using metabonomics. The results suggest that exposure to multipesticides with a common mechanism of toxicity causes joint toxic action. The current study aims to investigate the protection effect of quercetin against the joint toxic action induced by the mixture of the four OPs at the body metabolism level using metabonomics and elucidate the mechanism underlying such protective effect.

Materials and methods

Chemicals and reagents

Dimethoate (purity > 98%), acephate (purity > 95%), dichlorvos (purity > 95%), and the analytical standard of phorate were purchased from Hunan Haili Changde Pesticides Chemical Industry, Ltd. (Hunan, China), Nantong Weilike Chemical Industry, Ltd. (Nantong, China), Hebei Century Insecticides, Ltd. (Hebei, China), and Sigma–Aldrich (St. Louis, Missouri, USA), respectively. 7-Methylguanine (purity ≥ 98.0%), uric acid (purity ≥ 99%), suberic acid (purity ≥ 98.0%), estrone sulfate (purity ≥ 98.0%), citric acid (purity ≥ 99.5%), gentisic acid (purity ≥ 95%), isorhamnetin (purity ≥ 95%), quercetin (purity ≥ 95%), creatinine (purity > 99.7%), and leucine enkephalin (purity ≥ 97.0%) were produced from Sigma–Aldrich. Hippuric acid (purity ≥ 99.0%) and cholic acid (purity ≥ 98.0%) were produced from National Standard Substance Research Center (Beijing, China). The dimethylphosphate (DMP) and diethylphosphate (DEP) standards were obtained from AccuStandard, Inc. (New Haven, Connecticut, USA). Dimethyldithiophosphate (DMTP) (99%, purity) was purchased from Applichem (Germany). Ultra-performance liquid chromatography (UPLC)-grade acetonitrile and methanol were obtained from Dikma Science and Technology, Co. Ltd. (Canada). Distilled water was prepared using a Milli-Q system (Millipore, Billerica, Massachusetts, USA).

Lymphocyte separation medium (TBD) was purchased from Tianjin Haoyang Biological Manufacture Co., Ltd. (Tianjin, China). Dimethylsulfoxide (DMSO) was purchased from Tianjin Bodi Chemical Holding Co., Ltd. (Tianjin, China). Low melting point (LMP) and normal melting point (NMP) agarose were produced from Invitrogen (California, California, USA). Ethylendiaminetetracetice acid (EDTA-Na₂), Triton X-100, and hydroxymethylaminomethane (Tris Base) were obtained from Amresco (Solon, OH, USA). All other chemicals, reagents, and buffers were analytical grade supplied by Amresco Llc. (Solon, OH, USA).

Animal treatment

Sixty male Wistar rats aged 6 weeks, 180–220 g, were procured from Vital River Laboratory Animal Technology Co. Ltd. (Beijing, China). The study was approved by the Institute of Zoology Animal and Medical Ethics Committee of Harbin Medical University. The animals were housed in stainless steel mesh cages individually and kept in rooms with 12-h light/12-h dark cycle, with a controlled humidity (50–60%) and temperature (22 ± 2°C). They had access freely to AIN-93 M diets and drinking water.

After acclimatization for 1 week, the rats were randomly divided into six groups (10 animals per group). Average initial body weight of each groups was no significantly different (p > 0.05). These treatment groups were designated as group C (control group), group Q1 (low-dose quercetin-treated group, 10 mg/(kg bw day)), group Q2 (high-dose quercetin-treated group, 50 mg/(kg bw day)), group P (mixture-OPs-treated group), group PQ1 (low-dose quercetin plus mixture-OPs-treated group), and group PQ2 (high-dose quercetin plus mixture-OPs-treated group). The low dose of quercetin was equal to the Chinese exposed dose.²⁴ The dose of mixture-OPs was according to our previously published articles,²² which has confirmed that joint toxic action was caused by the mixture-OPs (dichlorvos, dimethoate, acephate, and phorate) at their corresponding NOAEL (2.4, 0.5, 0.04, and 0.05 mg/(kg bw day), respectively). Quercetin was dissolved in 0.5% carboxyl methyl cellulose (CMC) according to the expected dose of the treatment groups and was given to the rats via intragastric administration, whereas the rats of groups C and P were given 0.5% CMC through the same administration method. The mixture-OPs were diluted in drinking water, whereas the rats in the remaining groups were only given drinking water instead. The body weight (BW) of all rats was recorded weekly. Daily water consumption of each rats was recorded, and not significantly different between control group and treatment group (p > 0.05). Mixture-OPs and quercetin were administered to the rats between 09:00 a.m. and 11:00 a.m. once a day for 12 weeks.

Sample collection and preparation

Urine samples were collected over 24 h in the metabolism cages over ice packs at each time point (24 h predose, 4-week, 8-week, and 12-week postdose) and centrifuged at 10,000 r/min for 10 min. The supernatants were transferred to polypropylene tubes and stored at −80°C for the metabonomics study. Prior to analysis, urine sample of each rat was thawed and centrifuged at 12,000 r/min for 10 min. The supernatants were diluted with distilled water in a 1:3 (v/v) ratio, and vortex for UPLC/MS analysis. A representative pooled quality control (QC) sample was prepared by mixing equal volumes of the urine samples from sixty rats to verify the reproducibility and reliability of the data; this was analyzed as every 15th sample throughout the analytical run.

After the rats were anesthetized with pentobarbital via intraperitoneal injection, the blood samples were obtained from the aorta abdominalis. The blood sample was added to a tube containing an anticoagulant (EDTA-K₂) and shaken to mix the anticoagulant with the blood. Blood samples, 2 ml, diluted with phosphate-buffered saline (PBS) at 1:1. The diluted blood was layered on the top of TBD solution slowly at 1:1. The leukocytes was removed though sedimentation of erythrocytes after centrifuge at 2000 r/min for 10 min at room temperature. Peripheral blood lymphocyte were isolated at the interface of the TBD layers, and washed twice with PBS. The cell viability of lymphocyte was determined using Trypan Blue staining and found to be about 95%. The final concentration of the lymphocytes was adjusted to 1 −3 × 10⁵ cells/ml for comet assay.

Single-cell gel electrophoresis (SCGE) or comet assay

The suspension of lymphocytes was used in comet assay. The frosted slide were prepared by coating 100 µl of 80% NMP agarose, and the 25 µl lymphocytes suspension was mixed with 75 µl LMP agarose were layered on it. Slides were covered with coverslips and cooled at 4°C for 30 min, then uncovered and immersed in the lysis buffer (2.5 M NaCl, 100 mM Na₂EDTA, 10 mM Trizma, 10% DMSO, and 1% Triton X-100, pH 10) for 1.5 h at 4°C in the dark. The next step for comet assay followed by the method of Singh et al.²⁵

Chromatography

The separation system was performed on a 1.8 µm T₃ column (ACQUITY (HSS); Waters Corp., Milford, Massachusetts, USA; 2.1 mm × 100 mm) equipped with a UPLC system (ACQUITY UPLC; Waters Corp., USA). A 2 µl aliquot of each urine supernatant sample was injected into the column at a flow rate at 0.35 ml/min for 18 min kept at 35°C. The UPLC mobile phase was as follows: water containing 0.1% formic acid (solution A) and acetonitrile (solution B). The duration of the elution gradient program was as follows: 0–5 min, 0–20% B; 5–9 min, 20–70% B; 9–12 min, 70–98% B; 12–13 min, 98–70% B; 13–16 min, 70–20% B; 16–18 min, 20–0%B. After chromatographic separation, the eluent was directed to the MS system in split mode.

Mass spectrometry

MS was performed on a Micromass Q-TOF MS (Waters Corp., Manchester, UK), which equipped with electrospray ionization (ESI). The ESI source operated in the negative ion mode (ESI⁻) and positive (ESI⁺), and in full scan mode from m/z 50–1000 for 0–18 min. The optimum analytical parameters were as follows: capillary voltage was set at 2.8 kV and 3.0 kV in negative and positive ion mode, respectively; collision energy, 6 eV; sample cone voltage, 35 V; source temperature, 100°C; desolvation temperature, 300°C; desolvation gas (nitrogen) flow, 650 L/h; cone gas (nitrogen) flow, 50 L/h; collision gas, argon; For accurate mass acquisition, a concentration of 200 pg/ml leucine-enkephalin was used as lock mass (m/z 554.2615) in ESI⁻ and (m/z 556.2771) in ESI⁺. The lock spray frequency was set at 0.48 s. The lock mass data were averaged over 10 scans for correction.

Metabolite identification and metabolic pathway analysis

The raw data of UPLC/MS were imported into MarkerLynx Application Manager version 4.1 (Waters Corp., USA) for all the peaks detection, which allowed data deconvolution, alignment, and reduction to create a table of mass and retention time (RT). The data matrix including RT and m/z pairs, sample names, and ion intensities were introduced into the EZinfo 2.0 software for multivariate statistical analysis via principal component analysis (PCA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA). To identify the difference in metabolites between the control group and treated groups, variable importance parameter (VIP) values for biomarker identification were applied to position the distance from the different treated groups and identify the metabolites according to the orders of their contributions to the clustering separation. Combining the results of OPLS-DA and the ion intensity variation plots for each group, metabolite ions with VIP greater than 1.0 were individually selected from urine samples for further investigation. The structure of metabolite was elucidated by tandem MS/MS fragmentation with collision energy ramping from 15 to 35 eV. For identifying the potential biomarkers, first, exact molecular mass data, which from redundant m/z peaks corresponding to the formation of different parent (e.g., RT, anions in the negative ion mode, cations in the positive ion mode) and product ions, were used to help confirm the metabolite molecular mass. Second, to obtain mol file, which includes the structural information of ions, the information was uploaded to database searching, either in-house or using the online Chemispider database searching, and then importing the mol file into the corresponding MS/MS spectra to evaluate and compare the possibility of group fragment and structural information, and screen out one or several probable compounds. Third, MS/MS data analysis highlights neutral losses or product ions, which are characteristic of metabolite groups, can serve to discriminate between database hits. Fourth, metabolites were identified on the basis of the accurate mass, RT, and matching MS spectra of the unknown with the standard MS spectra in the database, such as the Human Metabolome Database (HMDB, http://www.hmdb.ca), Metlin (http://metlin.scripps.edu/), and MassBank (http://www.massbank.jp/). Finally, all the biomarkers were confirmed by authentic chemical standards based on both MS/MS spectra and RT.

The pathways of biomarkers were interpreted using databases, including HMDB and Kyoto Encyclopedia of Genes and Genomes (KEGG, http://www.genome.jp/kegg/), to identify the top altered pathway analysis and visualization.²⁶ Then, other implicated pathways of biomarkers were further interpreted using references.

Data processing and analysis

Collection parameters of EZinfo software for multivariate statistical analysis were set as follows: RT window, 0.2 min; mass window, 0.05 Da; and mass tolerance, 10 mDa. The high and low mass ranges were set at 1000 Da and 50 Da, respectively, and the initial and final RTs to 0.5 min and 14 min, respectively, minimum intensity, 80; noise elimination level, 6.0; deisotope data, Yes. After being recognized and aligned, low-molecular weight metabolites were presented as chromatographic peaks in the base peak intensity (BPI) chromatograms. Pareto-scaled was used before multivariate statistical analysis to avoid chemical noise. To identify the difference in metabolites between each group, PCA and OPLS-DA models were constructed for all time points. Specificity and sensitivity of the potential biomarkers were assessed using the area under the curve (AUC) of the receiver operator characteristic (ROC) curve.

The data of SCGE were processed by CASP (version 1.2.1; Krzysztof Konca, Poland) software to measure the tail DNA% and tail length, which are the parameters of deoxyribonucleic acid (DNA) damage.

The analysis of one-way analysis of variance was used for statistical analysis by SPSS (version 13.0; Beijing Stats Data Mining Co. Ltd., China), and p < 0.05 was considered statistically significant.

Results

Body weight change

The BW of all rats was recorded at each time point and each group (see Additional file 1). The BW noticeably increased in the first 8 weeks, and then slowly increased in the last 4 weeks. The BW change in rats in the experimental groups was not significantly different compared with the time-matched control group at each time point (p > 0.05).

Analysis of urine samples

Urine samples from the control and experimental groups were analyzed in both positive and negative ionization modes using UPLC/MS. Representative BPI chromatograms of urine in the positive mode in the control and mixture-OPs-treated groups at week 12 are shown in Figure 1. In this study, PCA was performed using UPLC coupled with electrospray ionization quadrupole time-of-flight MS (UPLC/ESI-Q-TOF/MS) to differentiate the distinct metabolite profiles of urine samples from all groups. An initial overview of the quality of the run, including all the QC injections, was obtained by core plot from PCA in the positive and negative mode (see Additional file 2). The result demonstrated that the data points of QC samples were clustered tightly, which provides some evidence that the UPLC/MS system was stable, and the reliable data were suitable for further statistical analysis. The score plot from PCA in the positive mode at each time point (0–12 weeks) is shown in Figure 2. The PCA scores collected from four different time points demonstrated time- and dose-dependent alterations. Figure 2(a) (0 weeks before treatment) shows that the data points did not separate from each other. Figure 2(b) (4 weeks after treatment) shows that the data points of the treatment groups tend to deviated from those of the control group; Figure 2(c) (8 weeks after treatment) shows that the data points of the treatment groups were completely separated from those of the control group. Figure 2(d) (12 weeks after treatment) shows that the data points of the treatment groups were clearly separated from those of the control group and the clusters of each group were close, however, overlaps were observed between groups PQ1 and P.

Figure 1.

The representative BPI chromatograms of urine in positive mode in the control (a) and treatment group (b) at week 12. BPI: base peak intensity.

Figure 2.

PCA scores plots derived from the UPLC/ESI-Q-TOF/MS of the urine in positive mode. C (box), control group; P (inverted triangle), mixture-OPs-treated group; PQ1 (dot), low-dose quercetin plus mixture-OPs-treated group; PQ2 (star), high-dose quercetin plus mixture-OPs-treated group; Q1 (triangle), low-dose quercetin-treated group; Q2 (diamond), high-dose quercetin-treated group; (a–d) 0, 4, 8, and 12 weeks after treatment. PCA: principal component analysis; UPLC/ESI-Q-TOF/MS: ultra-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry; OPs: organophosphate pesticides.

Fourteen metabolites exhibited statistically significant differences between the treated and the control groups (Table 1). These metabolites strongly influenced the patterns of each group in the score plot and were responsible for the separation between the control and the experiment groups. Eight of these metabolites were the loading plot of positive ions in the 12th week (Figure 3). The intensity value of these metabolites in the positive and negative modes at the 12th week is shown in Tables 2 and 3, respectively. Among these 14 metabolites, DMP, DMTP, uric acid, hippuric acid, and quercetin were identified both in positive and negative modes. DMP (ESI⁺ and ESI⁻), DMTP (ESI⁺ and ESI⁻), and DEP (ESI⁻) were only increased in groups P, PQ1, and PQ2 compared with the control group (p < 0.01). Quercetin (ESI⁺ and ESI⁻) and isorhamnetin (ESI⁺) only increased in groups Q1, Q2, PQ1, and PQ2 compared with the control group (p < 0.01).

Table 1.

Urinary biomarkers identified after treatment in positive and negative mode.

RT (min)	Measured mass	Calculated mass	Error m/z (Da)	Elemental composition	Scan mode	Metabolites
0.76	124.9981	124.9983	0.0002	C₂H₆O₄P	−	DMP
8.12	140.9781	140.9850	0.0069	C₂H₆O₃PS	−	DMTP
3.21	169.0104	169.0094	−0.0010	C₄H₁₁O₃PS	−	DEP
2.94	164.0495	164.0573	0.0078	C₆H₆N₅O	−	7-Methylguanine
1.16	167.0188	167.0205	0.0017	C₅H₃N₄O₃	−	Uric acid
6.99	173.0775	173.0819	0.0044	C₈H₁₃O₄	−	Suberic acid
5.25	178.0478	178.0510	0.0032	C₉H₈NO	−	Hippuric acid
1.26	191.0156	191.0192	0.0036	C₆H₇O₇	−	Citric acid
5.87	349.1101	349.1115	0.0014	C₁₈H₂₁O₅S	−	Estrone sulfate
9.08	407.2800	407.2798	−0.0002	C₂₄H₃₉O₅	−	Cholic acid
8.29	301.0315	301.0349	0.0034	C₁₅H₉O₇	−	Quercetin
0.83	127.0420	127.0483	0.0063	C₂H₆O₄P	+	DMP
5.21	143.1141	143.1139	−0.0002	C₂H₈O₃PS	+	DMTP
1.53	155.0521	155.0344	−0.0177	C₇H₇O₄	+	Gentisic acid
1.16	169.0437	169.0361	−0.0076	C₅H₅N₄O₃	+	Uric acid
4.82	180.0740	180.0660	−0.0080	C₉H₁₀NO₃	+	Hippuric acid
0.67	114.0680	114.0667	−0.0013	C₄H₈N₃O	+	Creatinine
8.02	303.0607	303.0505	−0.0102	C₁₅H₁₁O₇	+	Quercetin
8.66	317.0711	317.0661	−0.0050	C₁₆H₁₃O₇	+	Isorhamnetin

RT: retention time; DMP: dimethylphosphate; DEP: diethylphosphate; DMTP: dimethyldithiophosphate.

Figure 3.

Loading plot based on the urine profiling of the control and treatment group in positive mode at week 12.

Table 2.

Summary of intensity values of biomarkers detected in positive ESI mode in rats urine (mean ± SD, n = 10).

Group	DMP	DMTP	Gentisic acid	Uric acid	Hippuric acid	Creatinine	Quercetin	Isorhamnetin
C	0	0	1.93 ± 0.53	26.25 ± 2.41	13.10 ± 2.05	39.12 ± 3.86	0	0
Q1	0	0	1.89 ± 0.63	28.07 ± 3.22	12.98 ± 2.40	37.45 ± 3.40	1.57 ± 0.68^b	13.36 ± 7.27^b
Q2	0	0	2.00 ± 0.64	28.26 ± 3.03	14.02 ± 1.75	40.03 ± 3.63	4.04 ± 1.39^b	45.26 ± 13.88^b
P	15.78 ± 2.77^b	27.79 ± 3.50^b	0.64 ± 0.51^b	20.71 ± 2.81^b	7.98 ± 2.37^b	30.89 ± 3.42^b	0	0
PQ1	15.21 ± 2.01^b	24.64 ± 2.47^b	0.90 ± 0.53^b	21.36 ± 2.15^b	8.88 ± 1.29^b	32.99 ± 3.20^b	1.43 ± 0.40^b,d	11.05 ± 5.44^b,d
PQ2	14.29 ± 1.99^b	22.63 ± 3.66^b	1.29 ± 0.44^a,c	23.15 ± 2.01^a,c	10.45 ± 1.95^a,c	35.03 ± 3.49^a,c	2.45 ± 1.33^b,d	30.65 ± 13.88^b,d

ESI: electrospray ionization; DMP: dimethylphosphate; DMTP: dimethyldithiophosphate; C: control group; Q1: low-dose quercetin-treated group; Q2: high-dose quercetin-treated group; P: mixture-OPs-treated group; PQ1: low-dose quercetin plus mixture-OPs-treated group; PQ2: high-dose quercetin plus mixture-OPs-treated group; ANOVA: analysis of variance.

^aSignificantly different from control rats at p < 0.05 (ANOVA).

^bSignificantly different from control rats at p < 0.01 (ANOVA).

^cSignificantly different from P rats at p < 0.05 (ANOVA).

^dSignificantly different from P rats at p < 0.01 (ANOVA).

Table 3.

Summary of intensity values of biomarkers detected in negative ESI mode in rats urine (mean ± SD, n = 10).

Group	DMP	DMTP	DEP	7-Methylguanine	Uric acid	Suberic acid	Hippuric acid	Citric acid	Estrone sulfate	Cholic acid	Quercetin
C	0	0	0	0.47 ± 0.22	58.83 ± 5.02	52.92 ± 9.55	66.22 ± 6.46	158.75 ± 19.54	77.24 ± 24.87	12.17 ± 4.12	0
Q1	0	0	0	0.46 ± 0.23	59.08 ± 6.94	53.37 ± 9.81	65.91 ± 7.24	168.76 ± 23.15	76.25 ± 23.88	11.93 ± 5.17	19.61 ± 6.16^b
Q2	0	0	0	0.45 ± 0.22	58.60 ± 7.41	54.09 ± 7.46	67.83 ± 6.42	174.82 ± 16.06	75.16 ± 24.73	10.90 ± 4.76	56.11 ± 9.40^b
P	28.57 ± 9.71^b	0.50 ± 0.08^b	0.58 ± 0.08^b	1.25 ± 0.37^b	43.64 ± 6.20^b	32.13 ± 9.35^b	48.35 ± 8.46^b	117.09 ± 13.16^b	147.60 ± 30.52^b	24.23 ± 6.06^b	0
PQ1	26.13 ± 9.99^b	0.49 ± 0.11^b	0.54 ± 0.09^b	1.01 ± 0.37^b	44.78 ± 7.71^b	36.04 ± 8.98^b	52.45 ± 8.50^b	130.02 ± 23.75^b	122.11 ± 29.87^b	20.34 ± 5.17^b	12.26 ± 3.98^b,d
PQ2	25.16 ± 9.02^b	0.43 ± 0.11^b	0.53 ± 0.09^b	0.87 ± 0.19^a,c	50.76 ± 6.01^a,c	42.54 ± 8.27^a,c	57.51 ± 7.00^a,c	138.89 ± 23.47^a,c	110.08 ± 23.82^a,c	18.13 ± 5.20^a,c	43.03 ± 9.61^b,d

ESI: electrospray ionization; DMP: dimethylphosphate; DEP: diethylphosphate; DMTP: dimethyldithiophosphate; C: control group; Q1: low-dose quercetin-treated group; Q2: high-dose quercetin-treated group; P: mixture-OPs-treated group; PQ1: low-dose quercetin plus mixture-OPs-treated group; PQ2: high-dose quercetin plus mixture-OPs-treated group; ANOVA: analysis of variance.

^aSignificantly different from control rats at p < 0.05 (ANOVA).

^bSignificantly different from control rats at p < 0.01 (ANOVA).

^cSignificantly different from P rats at p < 0.05 (ANOVA).

^dSignificantly different from P rats at p < 0.01 (ANOVA).

In the positive mode (ESI⁺), the intensities of gentisic acid, creatinine, hippuric acid, and uric acid significantly decreased in group P compared with the control group (p < 0.01). The intensities of the aforementioned metabolites increased in groups PQ1 and PQ2, especially in group PQ2 (p < 0.05), compared with group P.

In the negative mode (ESI⁻), the intensities of suberic acid, citric acid, hippuric acid, and uric acid significantly decreased in group P compared with the control group (p < 0.01). The intensities of the aforementioned metabolites increased in groups PQ1 and PQ2, especially in the group PQ2 (p < 0.05), compared with group P. The intensities of 7-methylguanine, estrone sulfate, and cholic acid significantly increased in group P compared with the control group (p < 0.01). The intensities of the aforementioned metabolites decreased in groups PQ1 and PQ2, especially in group PQ2 (p < 0.05), compared with group P.

Comparing the intensities of the metabolites in the positive and negative modes, groups Q1 and Q2 had no significant difference compared with the control group (p > 0.05), except for quercetin and isorhamnetin (p < 0.01).

ROC curve analysis

ROC curves were used to appraise the specificity and sensitivity. AUCs have been used as useful indexes for evaluating the diagnostic values of markers. If the AUC is greater than 0.7, the biomarkers are relatively exclusive.²⁷ ROC curves were plotted by entering data from control verses treated rats in urine. The ROC curve analysis of potential urine biomarker is shown in Additional file 3. The AUC of biomarkers were more than 0.7.

SCGE or comet assay

Comet assay is a versatile and sensitive method for measuring single strand breaks in DNA. The percentage of DNA in the tail (tail DNA%) and tail length, which are the most frequently used parameters in DNA strand breaks, provide a clear indication of the appearance of the comets and linearly related to DNA break frequency over a wide range of damage levels. The results of tail DNA% and tail length in each treatment group are shown in Table 4. These two parameters were not statistically significant change in groups Q1 and Q2 compared with the control group (p > 0.05). However, the tail DNA% and tail length significantly increased in group P compared with the control group (p < 0.01). The corresponding parameter was ameliorative in groups PQ1 and PQ2, especially in group PQ2 (p < 0.05), compared with group P.

Table 4.

DNA damage in each group in rat lymphocyte.

Group	Tail DNA%	Tail length
C	5.06 ± 1.76	19.54 ± 7.56
Q1	4.86 ± 1.85	20.86 ± 8.91
Q2	4.90 ± 1.88	17.92 ± 7.88
P	8.38 ± 3.09^b	29.94 ± 7.47^b
PQ1	7.93 ± 3.2^b	28.84 ± 8.52^b
PQ2	6.49 ± 2.70^a,c	24.72 ± 7.47^a,c

C: control group; Q1: low-dose quercetin-treated group; Q2: high-dose quercetin-treated group; P: mixture-OPs-treated group; PQ1: low-dose quercetin plus mixture-OPs-treated group; PQ2: high-dose quercetin plus mixture-OPs-treated group; ANOVA: analysis of variance.

^aSignificantly different from control rats at p < 0.05 (ANOVA).

^bSignificantly different from control rats at p < 0.01 (ANOVA).

^cSignificantly different from P rats at p < 0.05 (ANOVA).

Discussion

Fourteen metabolites in urine were detected by UPLC/Q-TOF/MS analysis, and the ROC curve analysis of potential urine biomarker indicated its specificity and sensitivity. The changes in the intensities of these metabolites in each group in the positive and negative ESI modes are shown in Tables 2 and 3, respectively. DMP, DMTP, and DEP are metabolites of OPs.²⁸ In the present study, DMP, DMTP, and DEP were only detected in groups exposed to mixture-OPs (P, PQ1, and PQ2), which showed high sensitivity and can be considered as biomarkers for rats exposed to mixture-OPs. Meanwhile, the intensities of quercetin and isorhamnetin significantly only increased in the quercetin-treated and quercetin plus mixture-OPs-treated groups. Their intensities positively correlated with the dosage of quercetin, in agreement with our previous research.²⁴

Tables 2 and 3 show that the intensities of estrone sulfate and cholic acid significantly increased, whereas gentisic acid, creatinine, suberic acid, and citric acid significantly decreased in group P compared with the control group (p < 0.01). The change tendency of the aforesaid metabolites was significantly ameliorated in group PQ2 compared with group P (p < 0.05). The results indicated that quercetin protects against the toxicity induced by mixture-OPs. Based on the index of the database (HMDB and KEGG) and website of MetaboAnalyst 3.0, the biological relationships between the potential biomarkers and toxic effects induced by mixture-OPs, as well as the mechanism by which quercetin affects such toxicity, are discussed according to the four pathways shown in Figure 4.

Figure 4.

The pathways in response to mixture-OPs and/or quercetin treatment. Upwards arrow or downwards arrow represents that the intensities of metabolites were significantly increased or decreased in the mixture-OPs-treated group compared with the control group; upwards dashed arrow or downwards dashed arrow represent the intensities of metabolites were significantly increased or decreased in the high-dose quercetin plus mixture-OPs-treated group compared with the mixture-OPs-treated group. OPs: organophosphate pesticides.

The first pathway is involved in fatty acids, energy, and sex hormone metabolism. Cholic acid is a major primary bile acid produced in the liver and usually conjugated with glycine or taurine. Bile acids are physiological detergents that facilitate excretion, absorption, and transport of fats and sterols in the intestine and liver. Bile acids are also steroidal amphipathic molecules derived from the catabolism of cholesterol. In the present study, cholic acid significantly increased in group P (p < 0.01), indicating that cholic acid and cholesterol metabolism were disturbed by mixture-OPs. Suberic acid is a dicarboxylic acid that is mainly metabolized in the liver by the ω-oxidation pathway and present in the urine of patients with fatty acid oxidation disorders.²⁹ Therefore, the intensity changes of the aforementioned metabolites (cholic acid and suberic acid) in group P indicated that mixture-OPs can disrupt fatty acid metabolism. However, these metabolites in group PQ2 were significantly different from those in group P (p < 0.05), indicating that quercetin can ameliorate mixture-OPs-induced fatty acid metabolism disorder. This results can be explained by the fact that quercetin upregulate hepatic lipid metabolism, especially ω-oxidation,³⁰ as well as the genes of lipid metabolism in vivo, such as cytochrome P450 (Cyp) 4a10, Cyp4a14, Cyp4a31, and Acyl-CoA thioesterase 3.³¹

Citric acid is an organic acid that exists in various foods such as fruits, vegetables, and milk, and commonly found as a natural metabolite in living cells. Under aerobic conditions, citric acid is dissimilated by the tricarboxylic acid cycle (TCA cycle). Citric acid metabolism contributes to energy production by providing a major alternative pathway for NAD⁺ regeneration and allowing acetyl phosphate to yield acetate/adenosine triphosphate (ATP).³² Creatine is an amino acid that exists in vertebrate tissues and urine. In muscle tissue, creatine occurs as phosphocreatine. Creatine is excreted as creatinine in urine, which functions as part of the cell energy shuttle. The high-energy phosphate group of ATP is transferred to creatine to form phosphocreatine through the following reaction: ATP + creatine ↔ ADP + phosphocreatine. This reaction is reversibly catalyzed by creatine kinase. In this study, the two metabolisms (citric acid and creatinine) significantly decreased in group P compared with the control group (p < 0.01), suggesting that energy metabolism is disturbed by mixture-OPs. However, citric acid and creatinine significantly increased in group PQ2 compared with group P (p < 0.05). This increase may due to the fact that quercetin has the capacity to increase the level of ATP in the mitochondria by modulating TCA in rats.³³ Above result suggest that quercetin can alleviate energy metabolism disturbed by mixture-OPs.

Estrone sulfate is a sulfated estrone derivative that can be converted to the more active estradiol as needed. Estradiol plays a critical role on reproductive and sexual functioning in women and affects other organs including the bones. A number of studies confirmed that concentrations of the biologically active estrogen, estradiol, are higher in malignant than in normal breast tissue.³⁴ In this study, the intensities of estrone sulfate significantly increased in group P compared with the control group (p < 0.01), suggesting that the sex hormone metabolism was perturbed by mixture-OPs. This result is consistent with a recent report that the endocrine system is impacted by OPs.³⁵ However, change in estrone sulfate in urine is significantly decreased in group PQ2 compared with group P (p < 0.05). This effect can be explained by the fact that quercetin can specifically and negatively modulate estrogen receptor α membrane starting rapid signaling.³⁶

The second pathway is involved in antioxidant system. Gentisic acid is an active metabolite of salicylic acid degradation, which has a broad spectrum of biological activities, including the function of efficiently scavenge hydroxyl radicals. Uric acid is the final oxidation product of purine metabolism and the end product of nitrogen metabolism. Uric acid has strong antioxidant capacity and has been suggested to function as an antioxidant in vivo. In this study, the intensities of uric acid and gentisic acid significantly decreased in group P compared with the control group (p < 0.01). These results indicated that body oxidative stress was induced by mixture-OPs. However, the intensities of these metabolites significantly increased (uric acid and gentisic acid) in group PQ2 compared with group P (p < 0.05). These changes may be explained by the fact that quercetin has powerful radical scavenging activities and can inhibit oxidative stress caused by mixture-OPs.⁸

The third pathway is involved in DNA damage. 7-Methylguanine, a metabolite of DNA methylation, is potentially the most useful marker of exposure to endogenous and exogenous methylation agent. The intensities of 7-methylguanine significantly increased in group P compared with the control group (p < 0.01). This result indicated that DNA damage may be induced by mixture-OPs. To verify this hypothesis, comet assay was applied in rat lymphocyte. The results showed that the tail DNA% and tail length of comet in group P is significantly higher than the control group (p < 0.01), further supporting our hypothesis. While compared with group P, the intensities of 7-methylguanine and the parameters of comet assay (tail DNA% and tail length) significantly decreased in group PQ2 (p < 0.05). This result may be explained by the protective effect of quercetin on against adduct formation and intervention exogenous substance-induced lymphocytic DNA damage.³⁷ In addition, previously published articles confirmed that DNA damage was caused in large part by oxidative stress.³⁸ In the second pathway of this article, it is showed that mixture-OPs can induce body oxidative stress, as well as the protective effect of quercetin on antioxidant defense system. These results further confirmed the results that quercetin can protect against DNA damage induced by mixture-OPs.

The fourth pathway concerns the liver and kidney function. Hippuric acid is the glycine-conjugated metabolite of benzoic acid in liver mitochondria used to evaluate liver function.³⁹ This study shows that hippuric acid significantly decreased in group P compared with the control group (p < 0.01), indicating that hepatic mitochondrial dysfunction was caused by mixture-OPs. In addition, numerous published articles have demonstrated that the level of cholic acid, suberic acid, and estrone sulfate in urine reflect the fatty acid and sex hormone metabolism balance, which also reflect liver function.^29,40,41 Changes in the abovementioned metabolites in the present study further support the fact that liver function was perturbed by mixture-OPs. In addition, some studies have confirmed that the change in uric acid, citric acid, and creatinine are closely related to antioxidant system and energy metabolism, as well as the biomarker of kidney function.^42
–44

In this study, the abovementioned biomarker of liver and kidney dysfunction in group PQ2 was alleviated compared with group P (p < 0.05). This result may be explained by the potency of quercetin protective effect against kidney and liver failure by scavenging free radical, enhancing the activity of antioxidant enzymes, downregulating the expression of the fibrotic marker MMP-9, and reducing the peroxidative marker malonaldehyde and inflammatory marker nitric oxide.^45

–48

Although the intensities of the identified metabolites (creatinine, citric acid, estrone sulfate, cholic acid, suberic acid, uric acid, gentisic acid, 7-methylguanine, and hippuric acid) were significantly ameliorated in group PQ2 compared with the group P (p < 0.05), the biomarkers in group PQ2 were significantly different from those in the control group (p < 0.05). This result indicated that quercetin can only partially attenuate the toxic effect caused by mixture-OPs.

Conclusion

A metabonomics-based systems approach was used to investigate the effect of quercetin on mixture-OPs-induced toxicity in rats. A high dose of quercetin (50 mg/(kg bw day)) has partial protective property on the toxicity induced by chronic exposure to low-level mixture-OPs, including metabolism of fatty acid, energy and sex hormone, antioxidant defense system, DNA damage, as well as liver and kidney function (Figure 4). Antioxidant activity is the most important among these protective effects of quercetin. This study has one limitation that the mechanism of interaction between quercetin and mixture-OPs was not studied. Further research is necessary, especially using molecular biology approaches, to address this point.

The proposed systems toxicity approach based on metabonomic profiling was able to reveal novel information of the protective effect of quercetin against the joint toxic action induced by the mixture of four OPs. Therefore, metabonomics has shown particular promise in the area of toxicology as a systems toxicity approach. However, bottlenecks of metabonomics, such as the lack of extensive and comprehensive metabolite databases, the nonautomated structure assignments, the limitations in data analysis interpretation restrict the throughput and hinder its broader use.

Footnotes

Acknowledgments

The Laboratory of Nutrition and Food Hygiene in Harbin Medical University is the key laboratory of Heilongjiang Province and Heilongjiang Higher Education Institutions.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Financial support from the National Natural Science Foundation of China (81172672) is gratefully acknowledged.

Supplemental material

The online [appendices/data supplements/etc] are available at .

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Supplementary Material

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Metabonomic analysis of the protective effect of quercetin on the toxicity induced by mixture of organophosphate pesticides in rat urine

Abstract

Keywords

Introduction

Materials and methods

Chemicals and reagents

Animal treatment

Sample collection and preparation

Single-cell gel electrophoresis (SCGE) or comet assay

Chromatography

Mass spectrometry

Metabolite identification and metabolic pathway analysis

Data processing and analysis

Results

Body weight change

Analysis of urine samples

ROC curve analysis

SCGE or comet assay

Discussion

Conclusion

Footnotes

Acknowledgments

Declaration of Conflicting Interests

Funding

Supplemental material

References

Supplementary Material