Revised: 12 May 2020

Check for updates

Four cypermethrin isomers induced stereoselective metabolism in H295R cells

Chenyang Ji1 Bingqi Zhou1

Chang Yu1

Jianqiang Zhu1

Yafei Cheng1

Tian Tian1

Jinping Gu2

Jun Fan3 İD Meirong Zhao1 ® |

1College of Environment, Zhejiang University of Technology, Hangzhou, China

2College of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou, China

3School of Chemistry and Environment, South China Normal University, Guangzhou, China

Correspondence

Meirong Zhao, College of Environment, Zhejiang University of Technology, Hangzhou 310032, China. Email: zhaomr@zjut.edu.cn

Jun Fan, School of Chemistry and Environment, South China Normal University, Guangzhou 510006, China. Email: fanj@scnu.edu.cn

Funding information

National Natural Science Foundation of China, Grant/Award Numbers: 21906147, 21976162; Program for Changjiang Scholars and Innovative Research Team in University, Grant/Award Number: IRT_17R97

Abstract

Cypermethrin (CP) is widely used for controlling agricultural and indoor vermin. Previous studies have reported the stereoselective difference of CP in biological activities. However, little is known about their potential mechanisms between metabolic phenotypes and endocrine-disrupting effects. Herein, nuclear mag- netic resonance (NMR)-based metabolomics combining metabolite identification and pathway analysis were applied to evaluate the stereoselective metabolic cdisorders induced by CP isomers in human adrenocortical carcinoma cells (H295R) culture medium. Then, gene expression levels related to disturbed metabolic pathways were assessed to verify according to metabolic phenotypes. Metabolomics profiles showed that [(S)-cyano(3-phenoxyphenyl)methyl](1R,3R)- 3-(2,2-dichloroethenyl)-2,2-dimethylcyclopropane-1-carboxylate [(1R,3R,«S)-CP] induced the most significant changes in metabolic phenotypes than did the other stereoisomers. There are 10 differential metabolites (isoleucine, valine, leucine, ethanol, alanine, acetate, aspartate, arginine, lactate, and glucose) as well as two significantly disturbed pathways, including “pyruvate metabolism” and “alanine, aspartate, and glutamate metabolism,” that were confirmed in H295R cells culture medium of (1R,3R,«S)-CP compared with other stereoisomers. Polymer- ase chain reaction (PCR) array also confirmed the results of metabolomics. Our results can help to understand the potential mechanisms between the isomer selectivity in metabolic phenotypes and endocrine-disrupting effects. Data provided here not only lend authenticity to the cautions issued by the scientists and researchers but also offer a solution for the balance between environment and political regulations.

KEYWORDS

cypermethrin, H295R cells, isomers, NMR-based metabolomics, stereoselective

1 INTRODUCTION |

The frequent application of pesticides in all sorts of agri- cultural and indoor environments is leading to extensive contaminations in the environment.1 Even though the intended applications of pesticides are of economic

benefits, adverse effects on human beings and the ecolog- ical environment are a global concern. Cypermethrin (CP), a representative type II pyrethroid, is widely applied in vermin control.2 CP consumption in China has taken up over 50% of the pyrethroid market in 2006.3 The residues of CP have been widely detected in water

and sediment samples from agricultural districts with mean concentrations of 0.038 µg/L and 160 µg/kg, respec- tively.4,5 The detected concentration of CP in human plasma was even beyond the allowable daily intake in factory workers in Pakistan.6 CP has been reported to be highly toxic to the aquatic organism.7 Also, it has been considered as a well-known endocrine-disrupting chemi- cal (EDC), which could result in a disturbance in endo- crine systems as well as abnormal phenotypes.8,9

Synthetic pyrethroids (SPs) belong to the family of chiral pesticides with a large number of isomers for their chiral centers.1º Isomers of a chiral pesticide share general differences in biological properties owing to the enantioselective interactions with biological macromole- cules.11,12 CP, as a chiral pesticide with three chiral centers, has eight isomers sharing different environmental behavior and biological activities.13,14 Among these iso- mers, [(S)-cyano(3-phenoxyphenyl)methyl](1R,3R)-3-(2,2- dichloroethenyl)-2,2-dimethylcyclopropane-1-carboxylate [(1R,3R,«S)-CP] and [(S)-cyano-(3-phenoxyphenyl)methyl] (1R,3S)-3-(2,2-dichloroethenyl)-2,2-dimethylcyclopropane- 1-carboxylate [(1R,3S,«S)-CP] are the only isomers with an insecticidal activity, and (1R,3R,«S)-CP has the lowest deg- radation rate, whereas (1R,3S,«S)-CP degrades the fastest.14,15 With regard to toxicity, previous studies also illuminated that (1R,3R,«S)-CP and (1R,3S,«S)-CP were of high toxicity to Ceriodaphnia dubia, whereas the other ste- reoisomers were expected to have minimal toxicity.14 (1R,3R,«S)-CP and (1R,3S,«S)-CP also posed more potent acute toxicity to zebrafish than [(R)-cyano- (3-phenoxyphenyl)methyl](1S,3S)-3-(2,2-dichloroethenyl)- 2,2-dimethylcyclopropane-1-carboxylate [(1S,3S,«R)-CP] and [(R)-cyano-(3-phenoxyphenyl)methyl](1S,3R)-3-(2,2- dichloroethenyl)-2,2-dimethylcyclopropane-1-carboxylate [(1S,3R,«R)-CP].14,16,17 Our previous study also reflected that CP isomers exhibited isomer selectivity in endocrine- disrupting effects. (1R,3R,«S)-CP and (1R,3S,«S)-CP could pose profound disrupting effect on numerous nuclear receptors, including glucocorticoid receptor (GR), mineral- ocorticoid receptor (MR), thyroid receptor (TR), androgen receptor (AR), and estrogen receptor (ER).18 However, quite a few is known about the metabolic consequences of endocrine-disrupting effects induced by EDCs concerning both molecular mechanisms and metabolic phenotypes.19

The increasing incidence of metabolic diseases correlating with EDCs has given rise to the hypothesis that EDCs can interfere with various aspects of metabo- lism.20,21 However, EDCs’ interference with nuclear receptors implicated in metabolism has been barely studied, given their strong implications with metabolic disorders as well as their affinity with a diverse array of compounds.19 Metabolic phenotypes, the coactive outcomes of the diversified stimulus,22 serves as a

momentous molecular marker in evaluating the activa- tion of the endocrine-disrupting effects by EDCs owing to their particular sensitivity to environmental stress.23,24 Nuclear magnetic resonance (NMR)-based metabolomics, an effective tool to systematically analyze potential alters and unsuspected biological processes for its untargeted and holistic characteristics, has been broadly applied for a thorough investigation of the dynamic metabolic responses to the various stimulus.25,26

Herein, NMR-based metabolomics profile combining metabolite identification and pathway analysis was applied to evaluate the isomer selectivity in metabolic disorders induced by CP isomers in the culture medium from human adrenocortical carcinoma cells (H295R). These results can help to understand the potential mechanism between the stereoselective difference in endocrine-disrupting effects and distinct metabolic phe- notypes. Data provided here not only lend authenticity to the cautions issued by the scientists and researchers but also offer a solution for the balance between environment and political regulations.

2 MATERIALS AND METHODS |

2.1 | Chemicals and regents

(1R,3R,«S)-CP (purity 98.4%), (1S,3S,«R)-CP (purity 98.3%), (1R,3S,«S)-CP (purity 94.0%), and (1S,3R,«R)-CP (purity 95.8%) were synthesized and separated by super- critical fluid chromatography (SFC) in our lab. 14,18,27 Detailed information of the CP isomers is listed in Table 1. Stocking solutions of 10-1 M (equivalent to 41.6 g/L) for the four CP isomers were prepared in dimethyl sulfoxide (DMSO; Sigma-Aldrich). Then, required concentrations for the following experiments were diluted accordingly. NaH2PO4.2H2O and K2HPO4.3H2O (Sinopharm Chemi- cal Reagent CO., Ltd., Shanghai, China) used in the experiment were all of analytical grade. D2O (purity 99.9%) was purchased from the Cambridge Isotope Labo- ratories, Inc. (Tewksbury, USA). UP water was acquired by the Milli-Q system (Millipore, USA).

2.2 | Cell treatment

Human adrenocortical carcinoma cell line (H295R cells; ATCC CRL-2128, ATCC, Manassas, VA, USA) were kindly provided by Prof. Zhou Qunfang (Research Center for Eco-Environmental Sciences, Chinese Academy of Sci- ence). H295R cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM)/F12 (HyClone, Logan, UT) containing 1% L-glutamine, 1% penicillin-streptomycin,

TABLE 1 Detailed information of four cypermethrin isomers

ChemicalsChemical structure
(1R,3R,«S)-CPH3C CH3 H H CI (R) CN C 3 1 (R) (S) O CI H O O H
(1S,3S,«R)-CPCI H3C CH3 O H C=CH (R) α O CI O (S) H 3 1 S CN H
(1R,3S,«S)-CPCI H3C CH3 C=CH H CI (S) (R) (S) CN H 3 1 CE O O O H
(1S,3R,«R)-CPH3C CH3 O H H (R) CL O CI (R O c= 3 1 (S) CN CI H H

Note: Structure of cypermethrin showing asymmetric carbon posi- tions at 1C, 3C, and &C.

1% insulin-transferrin-selenium, and 1% serum substitute for animal cell culture (Ultroser G; Pall Corporation, Port Washington, NY, USA). The culture medium was replaced regularly to maintain cell vitality. Cells were kept in a 37℃ incubator adjusted with 5% CO2 and saturating humidity.

When the cell density reaches 80-90%, 106 H295R cells were seeded into each well of a 6-well plate overnight. The exposure concentrations of target CP isomers (10-5 M; equivalent to 4.16 mg/L) were determined according to our previous study.18 After 48 h, the culture medium was collected and kept in -20℃ refrigerator for NMR measurements, and the cells were collected for RNA isolation.

2.3 | Sample preparation and NMR measurements

Sample preparation and NMR measurements were carried out according to our previous study.28 Briefly, 450 ul of thawed culture medium containing 50 ul of D2O was centrifuged at 12 000 g at 4℃ for 15 min. After centrifugation, 450 ul of supernatant was collected into NMR tubes (5 mm) for sample measurements by the Bruker Avance III HD 600-MHz spectrometer (Bruker BioSpin, Germany), after precool at 4ºC.

2.4 | Multivariate statistical analysis

Multivariate statistical analysis was carried out according to our previous study.28 Prior to multivariate statistical

analysis, the NMR spectrum was preprocessed by divid- ing into 0.001-ppm segments individually. The divided spectrum between 8 9.00 and 0.20 was kept as an effec- tive area, whereas the area between 8 5.02 and 4.68 was wiped off to exclude the aberrant baseline. The remaining NMR spectra were normalized by global normalization prior to Pareto scaling.29,30

Principal component analysis (PCA) was operated by the SIMCA-P+ 12.0 software package (Umetrics AB, Umea, Sweden) for removal of error from reveal treats, stress outliers, and display groups. PCA model separated clusters from the MATLAB (The MathWorks, Inc., USA) in the minimum volume enclosing ellipsoid (MVEE). Then, partial least-squares discriminant analysis (PLS-DA)31 and orthogonal signal correction PLS-DA (OPLS-DA)32 were processed to distinguish the samples and explore potentially involved variables between different groups.

2.5 | Metabolite assignment and comparison

The robustness of the PLS-DA model was reexamined by response permutation testing (RPT) prior to the identifi- cation of the differential metabolites. The differential metabolites were identified by the variable importance in the projection (VIP)28 and the correlation coefficients (r) for the variables related to the first predictive compo- nent (tp1) in OPLS-DA model.33 The loading plots of OPLS-DA model were reconstructed by MATLAB using two criteria (VIP and |r|), and the peaks were colored accordingly (graduated red: |r| > 0.623 and VIP > 1; graduated orange: 0.497 < |r| < 0.623 and VIP > 1; graduated blue: |r| < 0.497 or VIP < 1).

The concentrations of detected metabolites are presented as the mean ± standard error (SE) by defining the percent of positive control as 100%. The univariate analysis was processed by MATLAB Statistics Toolbox, and statistical significance between groups was analyzed using one-way ANOVA (*p < 0.05; ** p < 0.01; *** p < 0.001).

2.6 | Metabolic pathway analysis

The metabolic pathway analysis combining the metabo- lite set enrichment analysis (MSEA) and pathway topology analysis was processed using Pathway Analysis module in MetaboAnalyst 3.0.34 MSEA, which sets its metabolite collection as libraries, is the metabolomics version for the popular gene sets enrichment analysis.35 MSEA, which can distinguish “consistent but subtle”

changes from relevant metabolites to investigate the metabolites alerts in biologically meaningful types, was used to assess the significantly enriched group of func- tional metabolites according to p values. On the other hand, pathway topology analysis, which focuses on the metabolic alerts in significant nodes of the metabolic net- work, was used to analyze the pathway impact values (PIVs) with relative-betweenness centrality arithmetic. Metabolic pathways with significant disturbance were identified based on the p values and PIVs.

2.7 | Quantitative reverse transcriptase- polymerase chain reaction

Total RNA in H295R cells were lysed in TRIzol reagent (Invitrogen, USA) to isolate total RNA according to our previous study.18 After quantification on a ND-1000 Nanodrop (Thermo, USA), the total RNA was reverse- transcribed into cDNA using an M-MLV reverse tran- scriptase (Takara Biochemicals, China). Then, cDNA was amplified on a Real-Time polymerase chain reaction (PCR) system (Bio Rad, USA) using a SYBR® Green Real- time PCR Master Mix (Toyobo Co., Ltd, Japan). Primer sequences of target genes are listed in Table S1. The PCR program is as follows: 95℃ for 1 min; 40 cycles of 95℃ for 15 s; and 60℃ for 1 min.36 Relative gene expression levels were normalized according to the threshold cycles (Ct value) using the 2-44Ct method with GAPDH as a housekeeping gene.37 37

Results of PCR, presented as means ± standard devia- tion (SD), were statistically analyzed by Origin 8.0 (OriginLab, USA). Statistical significance between groups was analyzed by one-way analysis of variance (*p < 0.05; ** p < 0.01; *** p < 0.001). The statistical significance among isomers was analyzed by one-way ANOVA (*p < 0.05).18

3 RESULTS AND DISCUSSION |

3.1 Isomer selectivity of CP in metabolic phenotypes and metabolites

The typical NMR spectrum of the culture medium from H295R cells after exposure to four CP isomers is shown in Figure 1. Each peak in the spectrum represents the individual metabolite, which was identified by the public NMR database (Human Metabolome Database, www. hmdb.ca; BMRB Metabolomics, http://www.bmrb.wisc. edu/metabolomics/) and Chenomx NMR Suite 8.0 (Chenomx Inc. Canada) (Table 2). Then PCA was assigned to investigate the changed metabolic profiles and evaluate the holistic metabolic phenotypes. According to the PCA scores (Figure 2), the metabolic phenotypes of the culture medium from H295R cells after exposure to the four CP isomers were distinguishable. Among them, (1R,3R,«S)-CP has induced the most signif- icant changes in metabolic phenotypes with a 54.5% con- tribution to the first principal component as well as a 12.7% contribution to the second principal component. This is consistent with our previous findings that (1R,3R,«S)-CP induced the most significant endocrine- disrupting effects than did the other stereoisomers.18 The different metabolic profiles between each isomer are shown in Figure S1.

PLS-DA was applied to assess the distinct metabolic phenotypes between each isomer on the basis of the NMR data sets. As shown in Figure 3, the metabolic phe- notypes of the four isomers could be distinctly separated by the score plots of the PLS-DA models, based on the automatic computation of the predictive principal com- ponents. Then, the RPT was applied to confirm the robustness of corresponding PLS-DA models. The RPT validation plots reflected the rationality of the distin- guished results of the PLS-DA models (Figure S2). The

FIGURE 1 Typical 600-MHz 1D 1H spectrum of the culture medium from H295R cells

10

9

10

8

7

6

5

6

4

2

3

6

11

8

12

7

5

2

9

3

1

1

4

12

0

5.5

5.0

4.5

4.0

3.5

3.0

2.5

2.0

1.5

1.0

ppm

TABLE 2 Information regarding the identified metabolites in the typical nuclear magnetic resonance (NMR) spectrum of the culture medium from H295R cells
MetabolitesChemical shift (ppm)
Lipid0.82-0.90 (bar), 1.24-1.31 (bar)
Isoleucine0.92 (t), 1.00 (d), 1.45 (m), 1.97 (m), 3.66 (d)
Leucine0.95 (t), 1.70 (m), 3.73 (m)
Valine0.98 (d), 1.03 (d),2.26 (m),3.61 (d)
Ethanol1.18 (t), 3.64 (dd)
Lactate1.33 (d), 4.12 (dd)
Alanine1.48 (d)
Acetate1.92 (s)
Glutamine2.13 (m), 2.45 (m)
Aspartate2.67 (dd), 2.81 (dd), 3.89 (dd)
Arginine1.64 (m), 1.72 (m), 3.21 (t), 3.77 (t)
Glucose3.23 (m), 3.40 (m), 3.46 (m), 3.53 (dd), 3.72 (m), 3.89 (dd), 4.64 (d), 5.22 (d)

corresponding PRTs with 200 iterations showed that these PLS-DA modules were not overfitted. Based on the multivariate statistical analysis, all the four CP isomers could result in alerts in the metabolic profiles of culture medium from H295R cell plots. OPLS-DA models were constructed on account of the NMR data sets to distin- guish these isomers by making further verification of dif- ferential metabolites (Figure 4). Significant isomer selectivity in separations was observed according to the OPLS-DA score plot (Figure S3).

Loading plots of OPLS-DA structured by the tp1 were used to confirm the differential metabolites, which could conduce to the separation of metabolic profiles (Figure 5). There are 10 differential metabolites (isoleu- cine, valine, leucine, ethanol, alanine, acetate, aspartate, arginine, lactate, and glucose) were confirmed in the

FIGURE 2 Principal component analysis (PCA) score plot for nuclear magnetic resonance (NMR) data derived from the culture medium of H295R cells after exposure to four cypermethrin (CP) isomers

culture medium from H295R cells after exposure to (1R,3R,«S)-CP as compared with the other stereoisomers (Figure 5A-C). Six metabolites increased and four metabolites decreased in the (1R,3R,«S)-CP group compared with the (1S,3S,«R)-CP group (Figure 5A), whereas half of the differential metabolites increased with the rest decreased in the (1R,3R,«S)-CP group com- pared with (1R,3S,«S)-CP and (1S,3R,«R)-CP groups (Figure 5B and C). (1S,3S,«R)-CP exposure significantly increased isoleucine and lipid in the culture medium as compared with (1R,3S,«S)-CP and (1S,3R,«R)-CP group, respectively, whereas the other metabolites (valine, leu- cine, ethanol, alanine, acetate, aspartate, and arginine) were all decreased (Figure 5D and E). When compared with the (1S,3R,«R)-CP group, there is only one metabolite (glucose) down-regulated in the (1R,3S,«S)-CP treatment (Figure 5F). The minute information about distinguishing metabolites on the OPLS-DA models is shown in Tables S2-S7.

The results of NMR-based metabolomics showed that (1R,3R,«S)-CP had the most profound effects on metabo- lism. (1R,3R,«S)-CP also had been proved to be of the most potent persistence and toxicity among the iso- mers.14,15 Thus, the disturbed metabolites not only con- firmed the ecological risks of (1R,3R,«S)-CP but also provided potential molecular marker for the identifica- tion of potential adverse isomers.

3.2 | Isomer selectivity of CP in disturbed metabolic pathways

The affected ingredients of endogenic metabolites indi- cated disturbed biological metabolic networks. The results of the pathway analysis showed that the CP iso- mers have stereoselective effects on the biological meta- bolic network (Figure 6). In the (1R,3R,«S)-CP exposed culture medium, there are two significantly disturbed

DMSO

6

· (1R,3R,aS)-CP

· (15,3S,a.R)-CP

4

· (1R,3S,a.S)-CP

· (1S,3R,a.R)-CP

2

20

-2

-4

-6

-8

-15

-10

-5

0

5

10

t[1]

R2X[1] = 0.545

R2X[2] = 0.127

Ellipse: Hotelling’s T2 (95%)

FIGURE 3 Partial least-squares discriminant analysis (PLS-DA) scores plots for nuclear magnetic resonance (NMR) data derived from the culture medium of H295R cells between each isomer treatment, A, (1R,3R,«S)-CP vs. (1S,3S,«R)-CP; B, (1R,3R,«S)-CP vs. (1R,3S,«S)- CP; C, (1R,3R,«S)-CP vs. (1S,3R,«R)-CP; D, (1S,3S,«R)-CP vs. (1R,3S,«S)-CP; E, (1S,3S,«R)-CP vs. (1S,3R,«R)-CP; F, (1R,3S,«S)-CP vs. (1S,3R,«R)-CP

(A)

(IR3RAS)-CP

(1535,ak)-CP

(B)

(IR3RAS)-CP

4

(IRAS,AS)-CP

3

4

2

2

1

..

50

-1

-2

-2

-3

-4

-4

-5

-25

-20

-15

-10

-5

0

5

10

15

20

-6

[1]

-20

-15

-10

-5

.

[1]

$

10

15

R2X[1]-0.774

R2X121- 0.0469

Ellipse: Hetelling’s T2 (95%)

R2X[1]-0.725

R2X[2]-0.0659

Ellipsez Hotelling’s T2 (95%)

(C)

(R3RAS)-C

(D)

(153SAR)-CP

4

(153R,AR)-C.

(18,3505)-CP

3

4

2

2

1

E

-1

-2

-2

J

4

4

5

-25

-20

-15

-10

-5

.

$

10

15

20

-6

-10

-S

.

5

10

R2X[1] - 0.809

R2X[2] - 0.0413

([!]

-15

Ellipse: Hotelling’s T2 (95%)

R2X[1]-0.508

R2X[2]- 0.124

( !!!

Ellipse: Hotelling’s T2 (95%)

(E)

(15.35,ak)-CP

(F

(ISJR,AR)-CP

(IRJSAS)-CP

4

4

(153RAR)-CP

3

3

2

2

1

#

5

+1

-1

-2

-2

.3

3

-4

-4

-5

-15

-10

.

$

10

-$

-19

-8

-2

.

2

4

6

8

R2X[1]-0.469

R2X[2]- 0.11

( !!!

4

Ellipse: Hotelling’s T2 (95%)

(11

R2X[1]=0.416

R2X[2]= 0.104

Ellipse: Hotelling’s T2 (95%)

pathways, including “pyruvate metabolism” and “ala- nine, aspartate, and glutamate metabolism,” compared with the other stereoisomer groups (Figure 6A-C). There are more pathways disturbed in (1S,3S,«R)-CP group when compared with (1R,3S,«S)-CP and (1S,3R,« R)-CP groups, which were “arginine and proline metabolism,” “pyruvate metabolism, and alanine,” and “aspartate and glutamate metabolism” (Figure 6D and E). The only disturbed pathway between (1R,3S,«S)-CP and (1S,3R,«R)-CP was “starch and sucrose metabo- lism” (Figure 6F).

As the interactive products of various environmental factors,22 metabolic phenotypes are considered an impor- tant molecular marker in evaluating the endocrine- disrupting effects of xenobiotic for their particularly sen- sitive to environmental stress.23,24 Isomers of chiral pesti- cide share different biological properties. Sometimes, an isomer with high environmental risks has no insecticidal activity, whereas an isomer with an insecticidal activity is relatively nontoxic. Thus, it is of great importance to dis- tinguish isomers with an insecticidal activity but low toxicity. In this way, both health concerns and economic

benefit are satisfied. Previous studies have reported that endocrine disruptors are vital inducers of metabolic dis- orders because the endocrine system plays a profound function in the homeostasis of metabolism and energy balance.38,39 CP has been proved to be an EDC,40 and the CP isomers exhibited different potential endocrine- disrupting effects for their different activities in biologic systems.1,41 The stereoselective endocrine disturbances of CP isomers are sure to result in differential metabolic phenotypes. Results of pathway analysis showed that all the CP isomers significantly disturbed the pathways of “pyruvate metabolism” and “alanine, aspartate and gluta- mate metabolism.” As the end-product of glycolysis, pyruvate works as the keystone intermediate critical for intracellular metabolism, as well as the fundamental fuel input enhancing citric acid cycle carbon flux in mito- chondria.42 Glycolysis, oxidation of lactate, and transami- nation of alanine are the potential sources of pyruvate, whereas pyruvate would be converted to acetyl-CoA or oxaloacetate in the matrix.42,43 Pyruvate and alanine are also fundamental substrates in the alanine cycle.44 Alanine and aspartate can be converted to pyruvate and

FIGURE 4 Orthogonal signal correction partial least-squares discriminant analysis (OPLS-DA) scores plots for nuclear magnetic resonance (NMR) data derived from the culture medium of H295R cells between each isomer treatment: A, (1R,3R,«S)-CP vs. (1S,3S,«R)- CP; B, (1R,3R,«S)-CP vs. (1R,3S,«S)-CP; C, (1R,3R,«S)-CP vs. (1S,3R,«R)-CP; D, (1S,3S,«R)-CP vs. (1R,3S,«S)-CP; E, (1S,3S,«R)-CP vs. (1S,3R,«R)-CP; F, (1R,3S,«S)-CP vs. (1S,3R,«R)-CP

(A)

(RJR.AS)-CP

(B)

(IRJRAS)-CP

x

(15,3S,ak)-CP

8

(IR.35,45)-CP

6

6

4

4

Tile . 91685’1

2

11les - 29095’1

1

·

·

-2

-2

+4

4

6

6

.8

-8

-10

-20

-15

-10

-5

.

5

10

15

-10

1.00023 * * [1]

-20

-15

-10

-5

1.00003 * * [1]

·

5

10

15

R2X[1] = 0.673

R2Xe[1]=0.124

Ellipse: Hetelling’s T2 (95%)

RIX[1]- 0.619

R2Xo[1]=0.146

Ellipse: Hotelling’s T2 (95%)

(C)

(ARJR.AS)-CP

(D

(15Jak)-CP (1RJS,a.S)-CP

(IS3RAR)-CP

*

6

6

4

4

files . FINSSI

2

2

·

0

-2

2

-A

-4

-6

-8

-6

-19

-20

-15

-10

-5

.

5

10

15

-8

-15

-19

5

R2X[1]- 0.699

1.00001 * * [1]

-5

.

10

R2Xe[1]=0.136

Ellipse: Hetelling’s T2 (95%)

RIX[1] - 0.439

1.00017 * * [1]

R2Xe[1]=0.189

Ellipse: Hotelling’s T2 (95%)

(E)

(1535,aR)-CP

(F

(153R,AR)-CP

(IRAS,AS)-CP (153R.aR)-CP

6

6

4

4

1.29205 * to[1]

:

0

B

·

-2

2

-4

-4

-6

-8

-10

-5

-4

-2

.

2

4

6

8

8

1 ** [1]

-10

-S

-6

2

.

2

4

6

8

R2X[1] - 0.39

R2Xe[1]=0.171

Ellipse: Hotelling’s T2 (95%)

R2X[1]-0.316

R2Xe[1]=0.193

1 . 4[1]

Ellipse: Hotelling’s T2 (95%)

oxaloacetate, respectively, which are crucial metabolites in the tricarboxylic acid (TCA) cycle and glycolysis.45 Glutamate is an amino acid that serves as a fundamental substrate in energy metabolism.46 Pyruvate is the catabo- lism product of various amino acids, including alanine, serine, and threonine.41 Alanine is considered as one of the crucial gluconeogenic precursors.47 Alanine and a-ketoglutarate can be reversibly transaminated to gluta- mate and pyruvate under the catalysis of alanine amino- transferase (ALT). These four intermediates work closely between carbohydrate and amino acid metabolism.41 Hormonal control of enzyme-catalyzed reactions on major routes of metabolism in cells is realized by chang- ing the concentration of activators and inhibitors.48 Pyruvate kinase (PK), which acts on the dephosphoryla- tion of phosphoenolpyruvate into pyruvate, is regulated by various hormones at the transcriptional and posttran- scriptional levels.49 (1R,3R,«S)-CP, which has been reported to exhibit endocrine-disrupting effects according to our previous study, also has predominately disturbed the pathways of “pyruvate metabolism” and “alanine, aspartate and glutamate metabolism.”

The expression levels of genes related to disturbed meta- bolic pathways were assessed to verify the disturbed met- abolic phenotypes. As shown in Figure 7, the expression levels of metabolic-related genes showed significantly stereoselective differences after exposure. The expression levels of ALT showed stereoselective difference between each CP isomers, (1R,3R,«S)-CP and (1S,3S,«R)-CP, up- regulated ALT expression levels with 2.07- and 2.25-fold, respectively, whereas (1R,3S,«S)-CP and (1S,3R,«R)-CP decreased ALT expression to 0.78- and 0.66-fold. All the CP isomers significantly up-regulated the expression levels of GDH, PFL1, and P4H; however, they suppressed PDK1 expression with the fold ranging from 0.67 to 0.62. (1R,3R,«S)-CP, (1S,3S,«R)-CP, and (1R,3S,«S)-CP all enhanced SRM expression with (1R,3R,«S)-CP inducing the highest fold of 5.00, and only (1S,3R,«R)-CP decreased its expression to 0.48-fold (Table S8).

ALT, which mediates the reversible conversion of a-amino group of alanine to «-ketogroup of ketoglutaric

FIGURE 5 Identified significantly differential metabolites from orthogonal signal correction partial least-squares discriminant analysis (OPLS-DA) loading plots between each isomer treatment. A, (1R,3R,«S)-CP vs. (1S,3S,«R)-CP; B, (1R,3R,«S)-CP vs. (1R,3S,«S)-CP; C, (1R,3R,«S)-CP vs. (1S,3R,«R)-CP; D, (1S,3S,«R)-CP vs. (1R,3S,«S)-CP; E, (1S,3S,«R)-CP vs. (1S,3R,«R)-CP; F, (1R,3S,«S)-CP vs. (1S,3R,«R)- CP. The graduated red represents notable significance in variables with |r| > 0.708 and variable importance in the projection (VIP) > 1; the graduated orange represents significance in variables with 0.576 < |r| < 0.708 and VIP > 1; the graduated blue represents no significance in variables with |r| < 0.576 or VIP < 1

(A)

lactate

(B)

lactate

0.6

VIP> 1

0.4

VIP >1

0.5

and

and

[r]> 0.708

0.4

0.3

[r]> 0.708

aspartate

aspartate

2

0.3

acetate

isoleucine

VIP> 1

0.2

isoleucine

VIP> 1

leucine

and

2

leucine

and

0.2

0.708 >||>0.576

alanine

0.1

alanine

0.708 >[r]>0.576

0.1

(15,3S,aR)-CP

VIP < 1

(1R,3S,a.S)-CP

VIP < 1

0

or

0

or

(1R,3R,a.S)-CP

glucose

arginine

ethanol

valine

[r] < 0.576

(1R,3R,a.S)-CP

glucose

arginine acetate ethanol

valine

[r]< 0.576

-0.1

5.5

5

4.5

4

3.5

3

2.5

2

1.5

1

5.5

5

4.5

4

3.5

3

2.5

2

1.5

1

ppm

ppm

lactate

(C)

(D)

0.4

VIP> 1

0.1

(1R,3S,aS)-CP

isoleucine

VIP> 1 and [r] > 0.708

and

0

0.3

|r]> 0.708

(1S,3S,aR)-CP

lactate

0.2

aspartate

isoleucine

VIP> 1 and

-0.1

glucose

acetate

ethanol

VIP> 1 and

2

leucine

2

arginine

-0.2

alanine

0.708 >|r|>0.576

0.1

alanine

0.708 >[r]>0.576

(15,3R,aR)-CP

VIP < 1

-0.3

aspartate

lactate

VIP < 1 or

0

or

(1R,3R,a.S)-CP glucose

arginine acetate ethanol

valine

[r]<0.576

-0.4

[r] <0.576

5.5

5

4.5

4

3.5

3

2.5

2

1.5

1

0.5

5.5

5

4.5

4

3.5

3

2.5

2

1.5

1

ppm

ppm

(E)

(E)

0.1

isoleucine

VIP>1

0.2

(15,3R,aR)-CP

and

VIP> 1 and [r]> 0.708

0

[r]> 0.708

0.15

(15,3S,aR)-CP

lactate

aspartate

-0.1

glucose

acetate

ethanol

VIP>1

0.1

lactate

arginine

VIP> 1 and

2

alanine

and

2

lactate

alanine

-0.2

0.708 >|r]>0.576

0.05

(1S,3R,aR)-CP

arginine

acetate

lipid

0.708>[r]>0.576

-0.3

aspartate

lactate

VIP < 1

0

VIP < 1

or

glucose

-0.4

[r] < 0.576

-0.05

(1R,3S,aS)-CP

ethanol

or

[r]< 0.576

5.5

5

4.5

4

3.5

3

2.5

2

1.5

1

5.5

5

4.5

4

3.5

3

2.5

2

1.5

1

0.5

ppm

ppm

acid to synthesize glutamate and pyruvate, plays a major role in gluconeogenesis and amino acid metabolism.50 Glutamate dehydrogenase (GDH) serves as the catalyst for the conversion of glutamate to a-ketoglutarate.51 Pyruvate dehydrogenase kinase (PDK1) catalyzes the phosphorylation and inactivation of mitochondrial pyru- vate dehydrogenase (PDH) complex. PDK1 can inhibit the conversion of pyruvate to acetyl-CoA by suppressing PDH.52 Pyruvate formate lyase (PFL1) serves as a consid- erable contributor for disintegrating pyruvate into acetyl coenzyme A (acetyl-CoA) and formate.53 Proline- 4-hydroxylase (P4H) is responsible for the hydroxylation of proline; thus, it is closely related to metabolism, protein synthesis, osmoprotection, and catabolismand anabolism.54 Spermidine synthase (SRM) is one of the enzymes involved in the biosynthesis of the natural polyamines (putrescine, spermidine, and spermine).55 Metabolic homeostasis is controlled by many enzymes,

and the aberrant metabolism arises from disturbances in genes coding for enzymes that control it.

3.4 | Endocrine disruption to metabolic disruption

The increasing incidence of metabolic diseases correlat- ing with EDCs has given rise to the hypothesis that EDCs can interfere with various aspects of metabo- lism.20,21 Glucocorticoids can promote gluconeogenesis, increase blood glucose levels, and mobilize the oxidation of fatty acids through GRs to regulate metabolism.56 MR also has been proved to represent a considerable element at the crossroads of fat metabolism.57 Thyroid hormones (THs) are well known for their role in metabolism. Elevated TH levels can result in metabolism accelera- tion, lipolysis gain, and hepatic cholesterol biosynthesis

FIGURE 6 Significantly disturbed metabolic pathways identified from pathway analysis by using the web service of MetaboAnalyst 4.0. A, (1R,3R,«S)-CP vs. (1S,3S,«R)-CP; B, (1R,3R,«S)-CP vs. (1R,3S,«S)-CP; C, (1R,3R,«S)-CP vs. (1S,3R,«R)-CP; D, (1S,3S,«R)-CP vs. (1R,3S,«S)-CP; E, (1S,3S,«R)-CP vs. (1S,3R,«R)-CP; F, (1R,3S,«S)-CP vs. (1S,3R,«R)-CP. Pathway impact values were derived from the pathway topology analysis, and the p values were derived from the metabolite set enrichment analysis

(A)

(B)

15

Alanine, aspartate and glutamate metabolism

15

Alanine, aspartate and glutamate metabolism

-In(p)

10

Pyruvate metabolism

-In(p)

10

Pyruvate metabolism

5

10

0.00 0.05 0.10 0.15 0.20 0.25 0.30

0.00 0.05 0.10 0.15 0.20 0.25 0.30 Pathway Impact

Pathway Impact

(C)

(D)

15

Alanine, aspartate and glutamate metabolism

12

10

Pyruvate metabolism

-In(p)

Arginine and proline metabolism

Alanine, aspartate and glutamate metabolism

-In(p)

10

8

Pyruvate metabolism

0

5

4

N

0.00 0.05 0.10 0.15 0.20 0.25 0.30

0.00

0.05 0.10 0.15 0.20 0.25 0.30

Pathway Impact

Pathway Impact

(E)

(F)

14

6.5

12

Alanine, aspartate and glutamate metabolism

6.0

10

-In(p)

Arginine and proline metabolism

-In(p)

5.5

80

Pyruvate metabolism

Starch and sucrose metabolism

0

5.0

4

4.5

2

4.0

0.00 0.05 0.10 0.15 0.20 0.25 0.30

0.00

0.10

0.20

0.30

0.40

Pathway Impact

Pathway Impact

and excretion.58 Given the tight association between hormones and energy homeostasis, it is reasonable for (1R,3R,«S)-CP to induce the aberrant metabolism of alanine, aspartate, lactate, glucose, and the pathways of “pyruvate metabolism” and “alanine, aspartate and glutamate metabolism” for its profound endocrine- disrupting effects. ERs and estrogens impact many aspects of metabolism, including glucose transport, gly- colysis, fatty acid oxidation, and mitochondrial structure

and activity.59 (1R,3S,«S)-CP, which had been proved to exhibit endocrine-disrupting effects,18 also has greatly disturbed the metabolism of glucose and the pathway of “starch and sucrose metabolism.” Despite the widely accepted endocrine-disrupting effects, CP has been rev- ealed to disturb carbohydrates and fatty acids in earth- worms.60 Recent studies also reported that several EDCs (phthalates and organotins) interfered with peroxisome proliferator-activated receptors (PPARs) and thereby

FIGURE 7 Heat map showing fold changes of genes related to significantly disturbed metabolic pathways. Fold changes were calculated versus the control group (0.1% DMSO). Color scale ranges from red to white, which respectively denote the up-regulation and down-regulation of the genes

(1R,3R,a.S)-CP (1S,3S,aR)-CP (1R,3S,a.S)-CP (1S,3R,a.R)-CP

ALT

GDH

PDK1

PFL1

P4H

SRM

5

4

3

2

1

0

disturbed metabolic homeostasis.61,62 Therefore, expo- sure to EDCs may not only increase endocrine disorder but also be an exacerbating factor for metabolic syndrome.

(1R,3R,«S)-CP and (1R,3S,«S)-CP are the only isomers with an insecticidal activity.14 Herein, NMR-based met- abolomics and related gene expression level showed that (1R,3R,«S)-CP has the strongest influence on metabolism. Given the metabolic disruption and endocrine-disrupting effects of (1R,3R,«S)-CP, (1R,3S,«S)-CP should be used as the active ingredient in commercial pesticide reagent to avoid potential environmental and health risks.

4 CONCLUSION |

Metabolic disorders are only the tip of the iceberg of EDC-related problems. In the present context of frequent exposure to EDCs and metabolic disruption, resulting in severe economic and healthy consequences, every effort aiming to understand and manage the risk factors is favorable from stem to stern. Herein, NMR-based met- abolomics indicated the stereoselective metabolic distur- bance of CP isomers. (1R,3R,«S)-CP, with the most potent endocrine-disrupting effects, induced the most sig- nificant metabolic disruption. Altogether, we strongly believe that metabolic phenotype is a considerable end- point for EDCs and that it is extremely important to apply NMR-based metabolomics as an effective tool for the risk assessment of EDCs.

ACKNOWLEDGMENTS

This work was supported by Program for Changjiang Scholars and Innovative Research Team in University (IRT_17R97) and the National Natural Science Founda- tion of China (21976162 and 21906147).

CONFLICT OF INTEREST

The authors declare that they have no competing interests.

ORCID

Jun Fan ® https://orcid.org/0000-0003-2986-8551 Meirong Zhao ® https://orcid.org/0000-0003-3132-9223

REFERENCES

1. Liu H, Zhao M, Zhang C, Ma Y, Liu W. Enantioselective cytotoxicity of the insecticide bifenthrin on a human amnion epithelial (FL) cell line. Toxicology. 2008;253(1):89-96.

2. Shi X, Gu A, Ji G, et al. Developmental toxicity of cypermethrin in embryo-larval stages of zebrafish. Chemosphere. 2011;85(6): 1010-1016.

3. Zhong H. Studies of producing technology of beta- cypermethrin. Agric Sci Guangdong. 2006;5:94-95.

4. Vryzas Z, Alexoudis C, Vassiliou G, Galanis K, Papadopoulou- Mourkidou E. Determination and aquatic risk assessment of pesticide residues in riparian drainage canals in northeastern Greece. Ecotoxicol Environ Saf. 2011;74(2):174-181.

5. Marino D, Ronco A. Cypermethrin and chlorpyrifos concentra- tion levels in surface water bodies of the Pampa Ondulada, Argentina. Bull Environ Contam Toxicol. 2005;75(4):820-826.

6. Khan D, Hashmi I, Mahjabeen W, Naqvi T. Monitoring health implications of pesticide exposure in factory workers in Pakistan. Environ Monit Assess. 2010;168(1-4):231-240.

7. Das B, Mukherjee S. Toxicity of cypermethrin in Labeo rohita fingerlings: biochemical, enzymatic and haematological conse- quences. Comp Bioch Physiol C: Toxicol Pharm. 2003;134(1): 109-121.

8. Elbetieha A, Da’As S, Khamas W, Darmani H. Evaluation of the toxic potentials of cypermethrin pesticide on some repro- ductive and fertility parameters in the male rats. Arch Environ Con Tox. 2001;41(4):522-528.

9. Zhao M, Zhang Y, Zhuang S, Zhang Q, Lu C, Liu W. Disrup- tion of the hormonal network via estrogen receptors and the enantioselectivity of bifenthrin: maternal-fetal health risk of chiral pesticides. Environ Sci Technol. 2014;48(14):8109-8116.

10. Qin S, Budd R, Bondarenko S, Liu W, Gan J. Enantioselective degradation and chiral stability of pyrethroids in soil and sedi- ment. J Agr Food Chem. 2006;54(14):5040-5045.

11. Lu H. Stereoselectivity in drug metabolism. Expert. Opin Drug Met. 2007;3(2):149-158.

12. Ye J, Wang L, Zhang Z, Liu W. Enantioselective physiological effects of the herbicide diclofop on cyanobacterium. Microcystis aeruginosa. Environ Sci Technol. 2013;47(8):3893-3901.

13. Niu L, Xu C, Yao Y, et al. Status, influences and risk assess- ments of hexachlorocyclohexanes in agricultural soils across China. Environ Sci Technol. 2013;47(21):12140-12147.

14. Liu W, Gan J, Lee S, Werner I. Isomer selectivity in aquatic toxicity and biodegradation of cypermethrin. J Agr Food Chem. 2004;52(20):6233-6238.

15. Naumann K. Synthetic pyrethroids insecticides: structures and properties. Springer-Verlag. 1990;116-141.

16. Mu X, Shen G, Huang Y, et al. The enantioselective toxicity and oxidative stress of beta-cypermethrin on zebrafish. Environ Pollut. 2017;229:312-320.

17. Xu C, Tu W, Lou C, Hong Y, Zhao M. Enantioselective separa- tion and zebrafish embryo toxicity of insecticide beta- cypermethrin. J Environ Sci. 2010;22(5):738-743.

18. Ji C, Yu C, Yue S, et al. Enantioselectivity in endocrine dis- rupting effects of four cypermethrin enantiomers based on in vitro models. Chemosphere. 2019;220:766-773.

19. Casals-Casas C, Feige J, Desvergne B. Interference of pollutants with PPARs: endocrine disruption meets metabolism. Int J Obe- sity. 2008;32(S6):S53-S51.

20. McAllister E, Dhurandhar N, Keith S, et al. Ten putative contributors to the obesity epidemic. Crit Rev Food Sci. 2009; 49(10):868-913.

21. Baillie-Hamilton P. Chemical toxins: a hypothesis to explain the global obesity epidemic. J Altern Complem Med. 2002;8(2): 185-192.

22. Holmes E, Loo R, Stamler J, et al. Human metabolic phenotype diversity and its association with diet and blood pressure. Nature. 2008;453(7193):396-400.

23. Wang C, Qian Y, Zhang X, et al. A metabolomic study of fipronil for the anxiety-like behavior in zebrafish larvae at envi- ronmentally relevant levels. Environ Pollut. 2016;211:252-258.

24. Yan L, Gong C, Zhang X, Zhang Q, Zhao M, Wang C. Perturba- tion of metabonome of embryo/larvae zebrafish after exposure to fipronil. Environ Toxicol Phar. 2016;48:39-45.

25. Duarte I. Following dynamic biological processes through NMR-based metabonomics: a new tool in nanomedicine? J Control Release. 2011;153(1):34-39.

26. Zhao L, Huang Y, Hu J, Zhou H, Adeleye A, Keller A. 1H NMR and GC-MS based metabolomics reveal defense and detoxification mechanism of cucumber plant under nano-Cu stress. Environ Sci Technol. 2016;50(4):2000-2010.

27. Liu W, Gan J, Qin S. Isolation, identification and aqueous toxicity of enantiomers of cypermethrin and cyfluthrin. Chiral- ity. 2005;17(S1):S127-S133.

28. Gu J, Ji C, Yue S, Shu D, Zhao M. Enantioselective effects of metalaxyl enantiomers in adolescent rat metabolic profiles using NMR-based metabolomics. Environ Sci Technol. 2018; 52(9):5438-5447.

29. Frank D, Alfred R, Götz S, Hans S. Probabilistic quotient nor- malization as robust method to account for dilution of complex

biological mixtures. Application in 1H NMR metabonomics. Anal Chem. 2006;78(13):4281-4290.

30. Andrew C, Olivier C, Elaine H, Nicholson J, Lindon J. Scaling and normalization effects in NMR spectroscopic metabonomic data sets. Anal Chem. 2006;78(7):2262-2267.

31. Haili W, Tso V, Slupsky C, Fedorak R. Metabolomics and detection of colorectal cancer in humans: a systematic review. Future Oncol. 2010;6(9):1395-1406.

32. Trygg J, Holmes E, Lundstedt T. Chemometrics in meta- bonomics. J Proteome Res. 2007;6(2):469-479.

33. Olivier C, Dumas M, Johan T, et al. Evaluation of the orthogo- nal projection on latent structure model limitations caused by chemical shift variability and improved visualization of bio- marker changes in 1H NMR spectroscopic metabonomic stud- ies. Anal Chem. 2005;77(2):517-526.

34. Xia J, Sinelnikov I, Han B, Wishart D. MetaboAnalyst 3.0- making metabolomics more meaningful. Nucleic Acids Res. 2015;43(W1):W251-W257.

35. Goeman J, Bühlmann P. Analyzing gene expression data in terms of gene sets: methodological issues. Bioinformatics. 2007; 23(8):980-987.

36. Ji C, Yan L, Chen Y, et al. Evaluation of the developmental tox- icity of 2,7-dibromocarbazole to zebrafish based on trans- criptomics assay. J Hazard Mater. 2019;368:514-522.

37. Ji C, Yue S, Gu J, et al. 2,7-Dibromocarbazole interferes with tube formation in HUVECs by altering Ang2 promoter DNA methylation status. Sci Total Environ. 2019;697:134-156.

38. Khan A, Park H, Lee H, et al. Elevated metabolites of steroido- genesis and amino acid metabolism in preadolescent female children with high urinary bisphenol A levels: a high- resolution metabolomics study. Toxicol Sci. 2017;160(2): 371-385.

39. Ortiz-Villanueva E, Jaumot J, Martínez R, Navarro-Martín L, Piña B, Tauler R. Assessment of endocrine disruptors effects on zebrafish (Danio rerio) embryos by untargeted LC-HRMS metabolomic analysis. Sci Total Environ. 2018;635:156-166.

40. Al-Hamdani N, Narasinhachary Y. Endocrine disruptive action of cypermethrin in male mice. Toxicol Environ Heal Sci. 2011; 3(2):69-79.

41. Cai X, Liu W, Shen G. Enantioselective degradation and ecotoxicity of chiral herbicide diclofop in three freshwater algae cultures. J Agric Food Chem. 2008;56(6):2139-2146.

42. Gray L, Tompkins S, Taylor E. Regulation of pyruvate metabo- lism and human disease. Cell Mol Life Sci. 2014;71(14):2577- 2604.

43. Schiller C, Fowler B, Woods J. Pyruvate metabolism after in vivo exposure to oral arsenic. Chem Biol Interact. 1978;22(1): 25-33.

44. Felig P. Amino acid metabolism in man. Annu Rev Biochem. 1975;44(44):933-951.

45. Maus A, Peters G. Glutamate and «-ketoglutarate: key players in glioma metabolism. Amino Acids. 2017;49(1):21-32.

46. Groot J, Sontheimer H. Glutamate and the biology of gliomas. Glia. 2011;59(8):1181-1189.

47. Terrettaz J, Jeanrenaud B. Contribution of glycerol and alanine to basal hepatic glucose production in the genetically obese (fa/fa) rat. Biochem J. 1990;270(3):803-807.

48. Randle P. Endocrine control of metabolism. Annu Rev Physiol. 1963;25(1):291-324.

49. Yamada K, Noguchi T. Nutrient and hormonal regulation of pyruvate kinase gene expression. Biochem J. 1999;337(1):1-11.

50. Lindblom P, Rafter I, Copley C, et al. Isoforms of alanine ami- notransferases in human tissues and serum-differential tissue expression using novel antibodies. Arch Biochem Biophys. 2007; 466(1):66-77.

51. Tanous C, Kieronczyk A, Helinck S, Chambellon E, Yvon M. Glutamate dehydrogenase activity: a major criterion for the selection of flavour-producing lactic acid bacteria strains. Lactic Acid Bacteria: Genetics, Metabolism and Applications, Springer. 2002;271-278.

52. Kim J, Dang C. Cancer’s molecular sweet tooth and the War- burg effect. Cancer Res. 2006;66(18):8927-8930.

53. Hemschemeier A, Jacobs J, Happe T. Biochemical and physio- logical characterization of the pyruvate formate-lyase Pfl1 of Chlamydomonas reinhardtii, a typically bacterial enzyme in a eukaryotic alga. Eukaryot Cell. 2008;7(3):518-526.

54. Falcioni F, Blank L, Frick O, Karau A, Bühler B, Schmid A. Proline availability regulates proline-4-hydroxylase synthesis and substrate uptake in proline-hydroxylating recombinant Escherichia coli. Appl Environ Microbiol. 2013;79(9):3091-3100.

55. Kauppinen L, Myöhänen S, Halmekytö M, Alhonen L, Jänne J. Transgenic mice over-expressing the human spermidine synthase gene. Biochem J. 1993;293(2):513-516.

56. Brockman R, Laarveld B. Hormonal regulation of metabolism in ruminants; a review. Livest Prod Sci. 1986;14(4):313-334.

57. Marzolla V, Armani A, Zennaro M, et al. The role of the miner- alocorticoid receptor in adipocyte biology and fat metabolism. Mol Cell Endocrinol. 2012;350(2):281-288.

58. Hulbert A. Thyroid hormones and their effects: a new perspec- tive. Biol Rev. 2000;75(4):519-631.

59. Chen J, Brown T, Russo J. Regulation of energy metabolism pathways by estrogens and estrogenic chemicals and potential implications in obesity associated with increased exposure to endocrine disruptors. BBA-Mol Cell Res. 2009;1793(7):1128- 1143.

60. Ch R, Singh A, Pandey P, Saxena P, Mudiam M. Identifying the metabolic perturbations in earthworm induced by cypermethrin using gas chromatography-mass spectrometry based metabolomics. Sci Rep. 2015;5(1):15674-15686.

61. Grun F, Watanabe H, Zamanian Z, et al. Endocrine-disrupting organotin compounds are potent inducers of adipogenesis in vertebrates. Mol Endocrinol. 2006;20(9):2141-2155.

62. Feige J, Gelman L, Rossi D, et al. The endocrine disruptor monoethyl-hexyl-phthalate is a selective peroxisome proliferator-activated receptor y modulator that promotes adipogenesis. J Biol Chem. 2007;282(26):19152-19166.

SUPPORTING INFORMATION

Additional supporting information may be found online in the Supporting Information section at the end of this article.

How to cite this article: Ji C, Yu C, Zhu J, et al. Four cypermethrin isomers induced stereoselective metabolism in H295R cells. Chirality. 2020;32: 1107-1118. https://doi.org/10.1002/chir.23254