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. Author manuscript; available in PMC: 2020 Sep 5.
Published in final edited form as: J Hazard Mater. 2019 Oct 28;385:121534. doi: 10.1016/j.jhazmat.2019.121534

Prenatal low-dose DEHP exposure induces metabolic adaptation and obesity: Role of hepatic thiamine metabolism

Yun Fan 1,2,†, Yufeng Qin 3,†, Minjian Chen 1,2,†, Xiuzhu Li 1,2, Ruohan Wang 4, Zhenyao Huang 1,2, Qiaoqiao Xu 1,2, Mingming Yu 1,2, Yan Zhang 5, Xiumei Han 1,2, Guizhen Du 1,2, Yankai Xia 1,2, Xinru Wang 1,2, Chuncheng Lu 1,2
PMCID: PMC7220048  NIHMSID: NIHMS1575901  PMID: 31706747

Abstract

Di-(2-ethylhexyl)-phthalate (DEHP) is a ubiquitous environmental pollutant and is widely used in industrial plastics. However, the long-term health implications of prenatal exposure to DEHP remains unclear. We set out to determine whether prenatal DEHP exposure can induce metabolic syndrome in offspring and investigate the underlying mechanisms. A mouse model of prenatal DEHP exposure (0.2, 2, and 20 mg/kg/day) was established to evaluate the long-term metabolic disturbance in offspring. The mice were profiled for the hepatic metabolome, transcriptome and gut microbiota to determine the underlying mechanisms. Thiamine supplementation (50 mg/kg/day) was administered to offspring to investigate the role of thiamine in ameliorating metabolic syndrome. Prenatal exposure to low-dose DEHP (0.2 mg/kg/day) resulted in metabolic syndrome, including abnormal adipogenesis, energy expenditure and glucose metabolism, along with dysbiosis of the gut microbiome, in male offspring. Notably, hepatic thiamine metabolism was disrupted in these offspring due to the dysregulation of thiamine transport enzymes, which caused abnormal glucose metabolism. Prenatal low-dose DEHP exposure caused life-long metabolic consequences in a sex-dependent manner, and these consequences were be attenuated by thiamine supplementation in offspring. Our findings suggest low-dose DEHP exposure during early life stages is a potential risk factor for later obesity and metabolic syndrome.

Keywords: DEHP, prenatal exposure, gut microbiota, thiamine, obesity

1. Introduction

The prevalence of obesity is an emerging health concern as obesity is clearly linked to numerous diseases including cancer [1]. The evidence linking endocrine disrupting chemicals (EDCs) and obesity is increasing [2]. Perinatal exposure to EDCs is of particular, interest given the extreme susceptibility of the developing organism during this stage. Exposures during this window induces important morphological and functional changes that persist through the organism’s life [3, 4]. Diethylhexyl phthalate (DEHP), one of the most widely used EDCs, is used primarily in the preparation of flexible polyvinyl chloride (PVC) plastics for food packaging, cosmetics, medical devices, building materials as well as children’s toys [5]. DEHP is produced at more than several million tons every year worldwide [6, 7]. It can penetrate the placental barriers leading to fetal exposure [8], and is recognized as environmental obesogen. DEHP exposure has been shown to induce adverse effects on energy balance and glucose homeostasis [9–12]. Due to ubiquitous exposure of DEHP and its ability to penetrate the placental barriers leading to fetal exposure [8], it is critical to understand whether prenatal exposure to DEHP at low concentrations influences obesity in offspring obesity rates.

Obesity is the result of the perturbation of the balance of energy intake and energy expenditure. However, environmental EDCs can disrupt this balance in a number ways [13, 14]. One possible mechanism by which prenatal DEHP exposure contributes to the development of obesity is through the disturbance of liver energy metabolism, as it has been previously reported that DEHP can induce hepatotoxicity and glucose metabolic disorder [10, 15].

In addition to disruption of liver metabolic pathways, alterations of the gut microbiota have also been shown to induce obesity and metabolic syndromes [16–18]. Many studies have shown that changing the ratio of Firmicutes to Bacteroidetes in the gut is related to increased energy harvesting [19–22]. Accumulating evidence shows that drug, antibiotic and chemical exposure in early life alters resident gut microbiota and enhances future susceptibility to numerous diseases [23–25]. Early life is vulnerable to external stimuli since the homeostasis of microbiota develops at this stage [25–27]. Notably, exposure to chemicals at this sensitive window can disturb intestinal flora and result in metabolic disorders later in life [23, 24]. However, little is known about the gut microbiota’s role in the induction of a prenatal imbalance of offspring energy storage and body composition following prenatal DEHP exposure.

Here, we investigated the long-term metabolic effect of prenatal DEHP exposure (0.2, 2, and 20 mg/kg/day) in a mouse model. The toxic effects of DEHP on metabolic phenotypes in offspring were explored and a sex dependence was discovered. Prenatal low dose DEHP exposure triggers a constellation of adverse effects on hepatic function, overall energy homeostasis and gut microbiota composition in male offspring. Subsequently it was demonstrated that thiamine supplementation (50 mg/kg/day) ameliorates lipid and glucose metabolism in male offspring. Our study bridges the research gap between DEHP exposure during sensitive window and offspring health. Particularly, we also provide evidences that thiamine supplementation can be a strategy for the prevention of DEHP exposure.

2. Materials and methods

2.1. Animals and treatment

All animal experiments were conducted with the approval of the Institutional Animal Care and Use Committee (IACUC) of Nanjing Medical University. Seven-week-old ICR mice were purchased from Shanghai SLAC Laboratory Animal Co., Ltd. (Shanghai, China). Glass water bottles were used in this study to avoid potential DEHP-related compound leakage from plastic water bottles.

The dosage of DEHP exposure was selected based on the United States Environmental Protection Agency (EPA) reference dose and previous studies [9, 28]. In the prenatal DEHP exposure model, seven-week-old female mice were randomly divided into four groups (N = 24, n = 6 per cage) and exposed them to different concentrations of DEHP (DEHP-low: 0.2 mg/kg/day; DEHP-medium: 2 mg/kg/day; DEHP-high: 20 mg/kg/day) dissolved in 1% DMSO (vehicle) continuously for 28 days by oral gavage starting 7 days prior to parental mating (Figure 1). For thiamine-supplementation, eight-week-old male offspring of DEHP-treated mothers were dosed with thiamine (50 mg/kg/day) for four weeks by oral gavage. The mice were then euthanized at the age of 12 weeks, and all samples were frozen in nitrogen until analysis.

Figure 1. The Experimental Scheme of Mouse Prenatal Low-Dose Exposure to DEHP.

Figure 1.

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Seven-week-old female mice received daily oral administration with different concentrations of DEHP (DEHP-low: 0.2 mg/kg/day; DEHP-medium: 2 mg/kg/day; DEHP-high: 20 mg/kg/day) dissolved in 1% DMSO (vehicle) starting 7 days prior to parental mating continuously for 28 days. Offspring at 12 weeks old underwent further analysis.

2.2. Body composition and indirect calorimetry

Body fat and lean body mass were assessed using magnetic resonance imaging (MRI, Biospec 7T/20 USR, Bruker, Germany). Mice were anesthetized with 2% isoflurane and the MRI images acquisition was synchronized with its respiration. For metabolic rates measurement, 12-week-old male mice were acclimated in metabolic chambers (TSE Phenomaster, Germany) for 3 days before recordings and measured for 3 days. Energy expenditure (EE), oxygen consumption (VO2), carbon dioxide release (VCO2), and the respiratory exchange ratio (RER) were analyzed by a combined indirect calorimetry system (TSE Phenomaster, Germany) as previously described [29, 30]. This system can handle 12 mice simultaneously and each mouse remained in their home cage placed within the system in order to reduce potential stress. Before conducting each experiment, a Siemens High-Speed Sensor Unit containing the O2 and CO2 sensors with two highly defined mixtures of O2 and CO2 was calibrated to prevent dilution of the sample with reference air. The RER was estimated by calculating the ratio of VCO2/VO2. In addition, EE was normalization by body weight.

2.3. Serum lipid profile analysis

Blood samples were collected from live mice through the intraocular iliac vein. After clotting and centrifugation, the serum was isolated, and the serum levels of total cholesterol (TC), triglycerides (TGs), high-density lipoprotein (HDL), low density lipoprotein (LDL) and glucose were measured through the use of a 7100 blood automatic biochemical analyzer (Hitachi, Inc., Kyoto, Japan) as previously described [31]. Serum levels of TC and TG were measured by enzymatic methods. Serum levels of HDL were tested after precipitation of apolipoprotein B-containing lipoproteins via dextran sulphate/magnesium chloride. Serum LDL levels were assessed using the Friedewaid formula.

2.4. Histology and staining

Fat and liver tissues were immediately fixed in 4% formaldehyde (PFA), incubated overnight at 4°C, and transferred to 70% ethanol. Multiple sections were prepared and stained with hematoxylin and eosin (H&E). For oil red-O (ORO) staining, liver tissues were fixed with 4% PFA. Staining images were obtained and analysis were performed using a light microscope (Olympus, Tokyo, Japan).

2.5. Glucose and insulin tolerance test

For the intraperitoneal glucose tolerance test (IPGTT), animals were fasted overnight for 12 h. The animals were then bolus-injected intraperitoneally with glucose at 1.5 g/kg body weight. Blood glucose levels were determined at the indicated intervals (0, 30, 60, 90 and 120 min). The intraperitoneal insulin tolerance test (IPITT) was performed in mice that were fasted for 6 h. The glucose level of each mouse was measured 0, 30, 60, 90 and 120 min after the intraperitoneal injection of human insulin at 1.75 IU/kg body weight. All blood glucose concentrations were measured using a portable glucometer (Roche, Madrid, Spain).

2.6. Metabolomic profiling

Seven liver samples per group were randomly selected for metabolomic analysis according to our previous study [32]. Briefly, to extract the metabolites in liver, 50 mg of representative livers was fragmented and then sonicated for 5 min in a water and methanol mixture, and then centrifuged at 16000 g for 15 min. The isolated supernatant was dried and the residue was reconstituted for instrumental analysis. LC-HRMS analysis was conducted on an UPLC Ultimate 3000 system (Dionex, Germering, Germany), coupled with a Q-Exactive mass spectrometer in both positive and negative modes simultaneously (Thermo Fisher Scientific, Bremen, Germany). A 1.9 μm Hypersile Gold C18 column (100 mm × 2.1 mm) was used to perform the chromatographic separation (Thermo Fisher Scientific). A multistep gradient was used with a mobile phase A of 0.1% formic acid in ultra-pure water and a mobile phase B of acetonitrile acidified with 0.1% formic acid; the gradient operated at a flow rate of 0.4 ml /min over a run time of 15 min. The instrument operated at the resolution of 70 000 with full-scan acquisition ranging from 70 to 1050 m/z. Each sample was analyzed randomly to avoid bias from the injection order. Metabolite identification was based on the retention time and the accurate mass of commercial standards.

2.7. Hepatic gene expression profiling

A total of 3 μg of RNA extracted from liver samples from 12-week-old mice was used as input material for the RNA sample preparations. RNA sequencing was performed in Novogene using TruSeq Stranded mRNA Library Preparation (Novogene Bioinformatics Technology Co. Ltd, Beijing, China). Cuffdiff (v2.1.1) was used to calculate FPKMs of coding genes in each sample [33]. The resulting P-values were adjusted using Benjamini and Hochberg’s approach to control the false discovery rate (FDR). The significance of the gene expression difference was indicated by an adjusted P value < 0.05, as determined by Cuffdiff. Some of the differentially expressed genes were validated by qPCR. The sequences of the primers used in this study are listed in Supplementary Table S1.

2.8. Gut microbiota profiling

Fecal samples were collected fresh from individual male offspring and stored at – 80°C until DNA was extracted with the E.Z.N.A. Stool DNA kit (Omega Biotek) according to the protocol provided. PCR was used to amplify variable regions 3 and 4 (V3-V4) of the 16S rRNA gene for sequencing using modified 338F and 806R (338F: ACTCCTACGGGAGGCAGCAG, 806R: GGACTACHVGGGTWTCTAAT). Purified positive amplicons with different index sequences were pooled in equimolar amounts and then sequenced on a MiSeq platform (Illumina, San Diego, CA). 16S rRNA gene amplicon sequence results were mapped to the Green genes database (version 13.8) and analyzed based on the MOTHUR platform [34]. Operational Taxonomic Unit (OTUs) were selected against the Green genes database with a similarity threshold of 0.97. Notably, all samples were normalized to the same number in the following analysis to adjust for differences in sequencing depth. The Shannon index was calculated to assess alpha diversity within control and DEHP-exposed samples. Beta diversity [weighted UniFrac, principal coordinate analysis (PCoA)] was analyzed using MOTHUR. Linear discriminant analysis (LDA) effect size (LEfSe) analyses were performed to compare the different bacterial abundance in the study samples with default settings [35].

2.9. Statistical analysis

All the data are presented as the means ± SEM. Differences between various treatments were analyzed by ANOVA or Student’s t-test (Prism 7.0 software, GraphPad Software, San Diego, CA). The OPLS-DA model was established by SIMCA (version 14.0, Umetrics, Sweden). The Mann-Whitney U test was used to analyze differences in gut microbiota abundance. For LEfSe analysis, the Kruskal-Wallis rank sum test was applied to detect significantly different abundances, and LDA scores were determined to assess the effect size (threshold: ≥2. The level of significance was set at * p < 0.05; ** p < 0.01; *** p < 0.001; and **** p < 0.0001.

3. Results

3.1. Effect of prenatal DEHP exposure on adiposity and metabolism in offspring

To investigate whether prenatal DEHP exposure causes adiposity in offspring, female mice were treated with DEHP at multiple doses continuously for 28 days starting 7 days before parental mating. Prenatal exposure to low-dose DEHP (0.2 mg/kg/day) significantly increased body weight in male offspring only, without affecting food intake (Figure 2A–C), indicating that DEHP exposure induced weight gain in a sex-dependent manner (Figure S1A–C). Thus, only male offspring were included the subsequent analyses. MRI was used to determine the body composition of male mice at 12 weeks of age, and fat mass was significantly higher in the offspring of mothers treated with a low-dose of DEHP (Figure 2D). Consistent with the MRI results, histological analysis showed white adipocyte hypertrophy (Figure 2E).

Figure 2. Effect of Prenatal Low-Dose DEHP Exposure on Adiposity and Metabolism in Offspring.

Figure 2.

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(A) The cumulative food intake of male offspring was measured from week 5 to week 11 (6 times); n= 8–10 mice/group. (B) The body weights of male offspring were measured for 12 weeks (84 days). (C) The body weights of male offspring were measured at 12 weeks. (D) Body composition was measured by MRI at 12 weeks. (E) Representative images of H&E staining of WAT sections from the control (upper) and DEHP-exposed (lower) groups. Scale bars = 100 μm (F) Energy expenditure normalized to total body weight for 72 h and the calculated AUC (n = 6 per group). 12-week-old male mice were acclimated in metabolic chambers (TSE) for 72 h before recordings and measured for 72 h (G-I) Representative thermogenic mRNA (Ucp1, Cidea, Adbr3) expression in the brown fat pads of 12-week-old male mice (n = 6 per group). The 2−ΔΔCt method was used to calculate the relative expression of mRNA. Data shown are mean ± SEM. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001 compared with the control group. DEHP-low: 0.2 mg/kg/day; DEHP-medium: 2 mg/kg/day; DEHP-high: 20 mg/kg/day

To further assess whether prenatal low-dose DEHP exposure affects the energy expenditure of offspring, metabolic activity using metabolism cages (TSE Systems Phenomaster) were measured. As shown in Figure 2F, the prenatal low-dose DEHP-exposed group exhibited significantly lower energy expenditure compared to that exhibited by the control group. Slight reductions in VO2, VCO2, and the respiratory exchange ratios (RER) were observed for both light and dark cycles, but the differences were not statistically significant (Figure S1D–F). Lean mass is known to contribute more to energy expenditure than adipose tissue [36, 37], which is consistent with our hypothesis that a DEHP-induced increase in fat mass leads to a decrease in overall energy expenditure.

In mammals, brown adipose tissue (BAT) is considered to be a key site of heat production, and its thermogenic function is partly mediated by the action of thermogenic genes [38, 39]. Therefore, to investigate whether reduced energy expenditure in the prenatal low-dose DEHP-exposed group was due to the downregulation of thermogenic genes, qPCR was performed. The results demonstrated that the expression levels of several thermogenic genes (Ucp1, Cidea and Adrb3) were significantly lower in the prenatal low-dose DEHP-exposed group than in the control group (Figure 2G–I). Together, these findings indicated that the effect of prenatal low dose DEHP exposure on body weight gain and energy expenditure was likely due to the suppression of thermogenic genes in BAT in male offspring.

3.2. Effect of prenatal low-dose DEHP exposure on metabolic syndrome in offspring

To identify the effect of prenatal low-dose DEHP exposure on the development of metabolic syndrome, total cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL) and low-density lipoprotein (LDL) levels in the plasma were measured in male offspring. Prenatal low-dose DEHP exposure significantly elevated the levels of all markers (TC, TGs, HDL and LDL) (Figure 3A–D). HDL plays a vital role in the process of reverse cholesterol transport into the liver [40, 41]. To further assess the accumulation of fat in liver tissue, oil red O and H&E staining of liver sections was performed in prenatal low-dose DEHP exposed and control male offspring. As shown in Figure 3E, prenatal low-dose DEHP exposure resulted in an increase in lipid deposits in liver cells of the offspring. These observations suggested that prenatal low-dose DEHP exposure facilitated a general effect on plasma lipid levels and further dysregulated metabolism related to body adiposity. Collectively, these results suggested that prenatal low-dose DEHP exposure induced hyperlipidemia in male offspring.

Figure 3. Effect of Prenatal Low-Dose DEHP Exposure on Metabolic Syndrome.

Figure 3.

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(A-D) Quantification of plasma TC (A), TG (B), HDL (C), and LDL (D)level. (E) Representative images of H&E and oil red O staining of liver sections from the control (left) and DEHP-exposed (right) groups. Scale bars = 100 μm. (F) The volcano plots of mRNA expression. The plots were constructed using fold-change and p values (p < 0.05, FC ≥ 1-fold). (G) A cluster heatmap of the differential expression of hepatic genes of 12-week-old male mice (DEHP-exposed vs. control). (H) The top 20 KEGG terms enriched among the differentially expressed hepatic genes (p < 0.05). The data shown are the mean ± SEM. The data were analyzed by unpaired two-tailed Student’s t test; *p<0.05, **p<0.01.

3.3. Transcriptome analysis of the effect of prenatal low-dose DEHP exposure on the livers of male offspring

Next, adiposity in prenatal low-dose DEHP exposed mice was related to the dysregulation of genes in the liver was investigated. RNA-seq data showed that prenatal low-dose DEHP exposure induced significant transcriptional changes, including increasing the mRNA expression of 932 genes and decreasing the mRNA expression of 794 genes with decreased mRNA expression in male mice (Figure 3F–G). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that these 1726 differentially expressed genes were mainly enriched in metabolism-related pathways, including the fatty acid metabolism pathway (Figure 3H). Collectively, these results suggested that prenatal low-dose DEHP exposure reprogrammed hepatic gene expression, especially the expression of metabolism-related genes, in male offspring.

3.4. Metabolome analysis of the effect of prenatal low dose DEHP exposure on the livers of male offspring

Hepatic energy metabolism is a major determinant of total body adiposity and lipid levels as well as of systemic glucose. These are in turn, risk factors for cardiovascular and metabolic diseases [42, 43]. To determine whether prenatal low-dose DEHP exposure affects hepatic metabolites, ultra-high performance liquid chromatography (U-HPLC) in tandem with high resolution mass spectrometry (HRMS) based metabolomic screening was applied to the livers of prenatal low-dose DEHP exposed and control male offspring. Orthogonal projection to latent structures discriminant analysis (OPLS-DA) (R2X=0.663 Q2=0.843) showed clear differences in the hepatic metabolome between these two groups (Figure 4A). Prenatal low-dose DEHP exposure changed numerous hepatic metabolites, including N-acetylglutamic acid, D-glucuronic acid, thiamine and glucose 6-phosphate (Table S2) (VIP > 1, p < 0.05). Then, metabolic pathway analysis based on the identified differentially generated metabolites showed that ascorbate and aldarate metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, and thiamine metabolism were the most greatly impacted with scores higher than 0.4 (Figure 4B, Table S3).

Figure 4. Hepatic Thiamine Deficiency Impaired Glucose Metabolism.

Figure 4.

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(A) Orthogonal projection to latent structure-discriminant analysis (OPLS-DA) scores of the livers of mice after prenatal low-dose DEHP exposure (n = 7 mice/group). (B) The top 43 metabolic pathways enriched among the differential hepatic metabolites. (C) Relative levels of hepatic thiamine quantified by LC-HRMS analysis (n= 7 mice/group). (D) Relative levels of hepatic G-6-P quantified by LC-HRMS analysis (n= 7 mice/group). (E) IPGTT results for mice fasted for 14 h, adjusted for baseline and the associated glucose AUC (n = 6 mice/group). Animals were bolus-injected intraperitoneally with glucose at 1.5 g/kg body weight. (F) IPITT results for mice fasted for 6 h and the associated glucose AUC (n = 6 mice/group). Animals were bolus-injected intraperitoneally with human insulin at 1.75 IU/kg body weight. (G) Quantification of plasma glucose (GLU) levels. (H-J) Representative mRNA (Slc2a2, Slc19a2, Slc19a3) expression levels of various thiamine transporters in the livers of mice. The 2−ΔΔCt method was used to calculate the relative expression of mRNA. The data shown are the mean ± SEM. The data were analyzed by unpaired two-tailed Student’s t test; *p<0.05, **p<0.01.

Thiamine, which was decreased in the prenatal low-dose DEHP exposed group (Figure 4C), is an important cofactor in glucose metabolism as well as in the production of the primary source of energy for cells (ATP). Its deficiency is associated with obesity [44]. Interestingly, glucose-6-phosphate (G-6-P), which is involved in the hepatic glycolysis and gluconeogenesis pathways, was significantly increased in the prenatal low-dose DEHP exposure group (Figure 4D). To investigate whether prenatal low dose DEHP exposure induced hepatic thiamine deficiency resulting in modulation of glucose metabolism in male offspring, the intraperitoneal glucose tolerance test (IPGTT) and insulin tolerance test (IPITT) were applied in the prenatal low-dose DEHP exposed and control groups. There was a pronounced increase in blood glucose levels and overall glucose AUC in the prenatal DEHP low-dose exposed group (Figure 4E), and the IPITT showed a modest increase in blood glucose levels and overall glucose AUC (Figure 4F). In line with this finding, plasma glucose levels were higher in prenatal low-dose DEHP exposed male offspring (Figure 4G). These results suggested that hepatic thiamine deficiency disrupted glucose metabolism.

Slc2a2 mediates glucose secretion from the liver as well as the uptake of blood glucose into hepatocytes [42]. Its expression was significantly upregulated in the prenatal low-dose DEHP-exposure group, potentially explaining the higher circulating glucose observed in these animals (Figure 4H). Slc19a2 and Slc19a3 are two high affinity thiamine transporters [45, 46]. Gene ontology (GO) enrichment analysis showed that thiamine transport genes were differentially expressed in prenatal low-dose DEHP-exposed and control male mice (Table S4). Notably, the Slc19a2 gene was significantly downregulated, but the change in the Slc19a3 gene did not reach statistical significance in the prenatal low-dose DEHP-exposed group compared to the control group (Figure 4I–J). Together, these results indicated that prenatal low-dose DEHP exposure induced the dysregulation of thiamine transport enzymes, leading to hepatic thiamine deficiency and impaired glucose metabolism.

3.5. Effect of thiamine supplementation on male offspring

To further determine the effect of thiamine on adiposity and glucose metabolism, the diet of male offspring were supplemented with thiamine (50 mg/kg/day) from 8 weeks to 12 weeks by oral gavage. The three treatment groups (control, DEHP and DEHP + thiamine) showed no difference in cumulative food intake (Figure 5A). However, the body weight gain of the DEHP group was increased significantly at 12 weeks, in line with our previous data. Intriguingly, the thiamine supplemented group showed a significant reduction in body weights compared to the DEHP group (Figure 5B). Furthermore, MRI also indicated a higher percent lean mass and lower fat mass in the DEHP exposure plus thiamine supplementation group compared to the DEHP exposure alone group (Figure 5C). Consistent with this finding, histological analysis showed that thiamine supplementation inhibited adipocyte hypertrophy and hepatic lipid droplet accumulation (Figure 5D). Thiamine supplementation also improved hyperlipidemia, decreasing the levels of TC, TGs and HDL (Figure 5E–G). Additionally, the level of LDL showed a modest decrease (Figure 5H).

Figure 5. Thiamine Supplementation Improved Adiposity and Metabolism.

Figure 5.

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(A) The cumulative food intake of male offspring was measured from week 7 to week 12 (5 times) (n= 7 mice/group). (B) The body weight of male offspring was measured at 12 weeks. (C) Body composition was measured by MRI at 12 weeks. (D) Representative images of H&E staining of WAT sections and oil red O staining of liver sections from the control (left),DEHP-exposed (middle) and DEHP + thiamine (right) groups. Scale bars = 100 μm. (E-H) Quantification of plasma TC (E), TG (F), HDL (G), and LDL (H)levels. The data shown are the mean ± SEM. The data were analyzed by unpaired two-tailed Student’s t test; *p<0.05, **p<0.01.

The results of the IPGTT and IPITT suggested that thiamine supplementation following prenatal DEHP exposure improved insulin tolerance significantly compared to the unsupplemented DEHP exposed mice (Figure 6A–B). Corresponding to the improved glucose and insulin tolerance, plasma glucose levels were significantly decreased in the thiamine supplementation group (Figure 6C). Furthermore, the expression of the Slc2a2 gene was significantly downregulated in the thiamine supplementation group (Figure 6D). These observations suggested that thiamine supplementation ameliorated metabolic syndrome caused by prenatal low-dose DEHP exposure in male offspring.

Figure 6. Thiamine Supplementation Ameliorated Glucose Metabolism Impairment.

Figure 6.

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(A) IPGTT results for male offspring fasted for 14 h adjusted for baseline and the associated glucose AUC (n = 6 mice/group). Animals were bolus-injected intraperitoneally with glucose at 1.5 g/kg body weight. (B) IPITT results for male offspring fasted for 6 h and the associated glucose AUC (n = 6 mice/group). Animals were bolus-injected intraperitoneally with human insulin at 1.75 IU/kg body weight. (C) Quantification of plasma glucose (GLU)levels. (D) Slc2a2 mRNA expression level of thiamine transporter in the livers of mice. The 2−ΔΔCt method was used to calculate the relative expression of mRNA. The data shown are the mean ± SEM. The data were analyzed by unpaired two-tailed Student’s t test; *p<0.05, **p<0.01, ***p<0.001.

3.6. Gut microbiota analysis of the feces of male offspring that thiamine supplementation

Given that dysbiosis of the microbiota is related to metabolic syndrome and obesity, the gut microbiome was profiled by 16S rDNA gene amplicon sequencing of fecal samples. Notably, we found that prenatal low-dose DEHP exposure had long-term effects on the offspring microbiome. The alpha diversity of the gut microbial community was modestly increased at 4 weeks and 6 weeks of age (Figure 7A), while it was slightly decreased at 10 and 12 weeks of age (Figure S2A). At the phylum level, no significant change was observed in the relative microbial abundance in the prenatal low-dose DEHP exposed group compared to the control group (Figure 7B). However, it was found that prenatal low dose-DEHP exposure in dams caused alterations in the gut microbial community at 6 weeks of age, as indicated by weighted UniFac-based PCoA (Figure 7C), and this change was still be seen in male offspring at 12 weeks of age(Figure S2B). To further investigate the specific bacterial taxa related to prenatal low-dose DEHP exposure, linear discriminant effect size (LEfSe) analysis was performed to elucidate distinctive features at all levels. At the phylum level to the genus level, 16 features were significantly different between the prenatal low-dose DEHP exposure and control groups according to linear discriminant analysis (LDA) scores of the two groups (Figure 7D). The taxonomic structure and predominant bacterial presence of the gut microbiota in the two groups are represented in a cladogram in Figure 7E. These results demonstrate that the pattern and homeostasis of fecal microbiota were altered by low-dose DEHP exposure during early development, and that this alteration might result in altered adiposity metabolism later in life. Consistent with the results in Figure 7B, the gut microbiota was dominated by Bacteroidetes and Firmicutes in both the thiamine supplementation group and the control group (Figure S2C), indicating that thiamine supplementation orchestrates adiposity metabolism independent of a specific gut microbiotal profile.

Figure 7. Dynamics of the Effects of Prenatal Low-Dose DEHP Exposure on Microbiota Homeostasis.

Figure 7.

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(A-E) Fecal samples were collected from male mice at 4, 6, 8, 10 and 12 weeks (the terminal week), and the intestinal flora was examined by 16S rDNA sequencing. (A) The alpha diversity of the community of the control and DEHP-exposed groups was analyzed by the Shannon diversity index; *p < 0.05 compared with the control group. (B) Prenatal low-dose DEHP exposure affected the relative abundance of predominant bacteria at the phylum level in control and DEHP-exposed male offspring. (C) The plots were generated by the weighted UniFrac-based PCoA at each time point (4 weeks and 6 weeks). Note: PCoA1 and PCoA2 are the two dimensions with the most significant differences in the analysis. (D) The most differentially abundant taxa between the control and DEHP-exposed groups were identified through the LDA score, which was generated from LEfSe analysis. (E) The enriched taxa the fecal microbiota of the control and DEHP-exposed groups at 6 are represented in the cladogram. The central point represents the root of the tree (Bacteria), and each ring represents the next lower taxonomic level (phylum to genus: p, phylum; c, class; o, order; f, family; g, genus). The diameter of each circle represents the relative abundance of the taxon.

4. Discussion

Exposure to DEHP is ubiquitous. Thus, it is important to elucidate the relationship between prenatal low-dose DEHP exposure and offspring health. This study indicates that early life exposure to low-dose DEHP results in adverse effects on adiposity metabolism in a sex-dependent manner. Hepatic thiamine deficiency was found to be an underlying mechanism for the phenotypes related to prenatal low dose DEHP exposure. These findings also suggest that prenatal low dose DEHP exposure had long-term effects on the offspring gut microbiota, potentially contributing to the observed adiposity phenotype. Intriguingly, thiamine supplementation was able to ameliorate adiposity and changes in glucose metabolism but these effects were independent of shaping of the gut microbiota. This study suggests that thiamine supplementation may serve as a strategy for the prevention of metabolic disorders following prenatal low dose DEHP exposure.

According to the United States Environmental Protection Agency (EPA), the reference dose (RfD) of DEHP is 20 μg/kg of body weight per day. However, the estimated daily intake of DEHP has been estimated to be approximately 2.7 mg/kg/day [28, 47, 48], which is more than 10 times the low dose used in the present study, which demonstrated a significant effect. We observed that prenatal DEHP exposure at a low level can result in metabolic syndrome in offspring in a sex-dependent manner, which is consistent with the findings of other groups [49].

Thiamine (vitamin B-1) is an essential micronutrient that triggers several key biochemical reactions important for glucose metabolism [44, 50]. Prenatal low dose DEHP exposure induced hepatic thiamine deficiency and downregulation of the thiamine transport gene (Slc19a2) in obese male offspring. As the active metabolite of thiamine, thiamine pyrophosphate (TPP) is an indispensable cofactor for pyruvate dehydrogenase (PDH) and α-ketoglutarate dehydrogenase (α-KGDH), which exert fundamental roles in regulating cellular energy metabolism [45]. In the process of pyruvate oxidative decarboxylation, reduced levels of the cofactor TPP in prenatal low dose DEHP exposed mice disrupted hepatic energy homeostasis. PDH is a key enzyme for the glucose-fatty acid cycle [51, 52]. Its activity is altered by reduced TPP, resulting in lower hepatic ATP production via the tricarboxylic acid (TCA) cycle, suggesting that a lower hepatic energy status is a result of prenatal low dose DEHP exposure.

Hepatic glycolysis and gluconeogenesis are two incomplete reversible biochemical pathways that are reciprocally regulated and highly dependent on the availability of gluconeogenic substrates involved in hepatic glucose metabolism [42]. Previous studies have shown that reduced PDH activity leads to a high level of pyruvate [52, 53]. This study indicated that increased G-6-P and production of hepatic glucose resulted from redundant pyruvate contributions to the stimulation of hepatic gluconeogenesis [42, 54]. In turn, increased hepatic glucose levels drive the process of glycolysis, which results in excess pyruvate levels. Thus, increased pyruvate and decreased PDH activity further inhibit hepatic glucose utilization while increasing plasma glucose levels via elevated hepatic glucose transport gene expression. Although there was suppression of the pyruvate oxidative decarboxylation process, the levels of acetyl-CoA were increased due to a shift in the major hepatic energy source from glucose to fatty acids under the specific environment generated by obesogen exposure. Higher levels of acetyl-CoA, as the precursor for cholesterol synthesis, represent the underlying mechanisms; they led to greater rates of hepatic cholesterol production, which resulted in higher cholesterol and LDL levels in the plasma. Prenatal low-dose DEHP exposure caused impairments in glucose metabolism, contributing to host hyperinsulinemia and hyperglycemia, potentially resulting in aberrantly increased adiposity. Additionally, high insulin levels could induce a reduction in the transition of fatty acids to the liver, dependent on the increasing storage of TGs as well as suppression of lipolysis in peripheral adipose tissue. Importantly, previous studies have shown that chronic insulin administration can lead to the accumulation of adipose mass resulting from the suppression of lipolysis and increased lipid storage [55, 56]. Based on the present findings, it should be noted that hepatic thiamine deficiency leads to aberrantly increased adiposity subsequent to the disruption of hepatic energy homeostasis, emphasizing the importance of this profound metabolic crosstalk between the liver and adipose tissue. This study also demonstrates that environmental obesogen exposures, specifically DEHP, can disrupt this conversation resulting in an obesity phenotype.

Findings from recent studies have emphasized that dysbiosis of gut microbiota during early life can have lasting metabolic consequences [25, 26]. The present study provides interesting results, suggesting that the alteration or dysbiosis of the gut microbiome, such as that induced by prenatal low-dose DEHP exposure, may be related to the development of obesity in male offspring. At the phylum level, approximately 90% of the gut microbiome is either Bacteroidetes or Firmicutes. In particular, Firmicutes generates more harvestable energy than Bacteroidetes [57, 58]. Consequently, prenatal low-dose DEHP exposure induces a fecal microbiome dominated by Bacteroidetes and Firmicutes in obese male mice. These findings reinforce the hypothesis that interactions between the host and gut microbiota effect many aspects of energy metabolism [20, 59].

Notably, a potentially therapeutic role for small metabolites (vitamins, amino acids, and short-chain fatty acids) in the treatment of diseases (obesity and diabetes) is associated with fundamental dynamics of gut microbial community composition [60, 61]. Both our study and a previous study have demonstrated that thiamine deficiency is associated with obesity [44, 50]. Published studies in animals and humans have indicated that thiamine supplementation might improve blood lipid profiles in a manner similar to our results [62, 63]. The change in gut microbiota diversity is consistent with another recent study of early life environmental obesogen exposure [64]. In contrast, there was no observed difference in the gut microbiota composition following the special small metabolite (thiamine) treatment, suggesting that the gut microbiota orchestrates adiposity metabolism independent of thiamine supplementation in obese male mice.

However, the cumulative results from several studies to date suggest that most cases (>90%) using 16S rRNA gene sequencing can provide genus identification but less so with regard to species (65 to 83%), with from 1 to 14% of the isolates remaining unidentified [65–68]. Given that it is currently only an association study between the gut microbiota and chemical exposure, a better application of genome-wide sequencing to find out if there is DEHP exposure induced specific alteration of bacteria and how to change liver metabolism, which provide the potential mechanism into chemical exposure and human health.

5. Conclusion

In summary, this study demonstrated that prenatal low dose DEHP exposure triggers a constellation of adverse effects on hepatic function, overall energy homeostasis and gut microbiota composition in male offspring through the integration of the hepatic metabolome, transcriptome, and gut microbiome. Futhermore, this study demonstrates that majority of the metabolic effects can be attenuated by thiamine supplementation in the offspring. These changes appear to be predominantly related to changes in liver metabolism not by alterations of the gut microbiome. These findings provide new mechanistic insights into how low-dose DEHP exposure at an early life stage promotes obesity in the next generation of animals.

Supplementary Material

Supplemental materials
Supplemental table 4

Acknowledgements

This work was supported by the National Natural Science Foundation of China (81671461, 81330067 and 81872650), Natural Science Foundation of Jiangsu Province of China (BK20181366), the Key Natural Science Foundation of the Jiangsu Higher Education Institutions of China (18KJA320003) and the Priority Academic Program for the Development of Jiangsu Higher Education Institutions (Public Health and Preventive Medicine).

Footnotes

Supplemental Data

The supplemental Data include two figures and four tables.

Conflicts of interest

None.

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Supplementary Materials

Supplemental materials
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Supplemental table 4
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