- Open Access
Estrogen-mediated gut microbiome alterations influence sexual dimorphism in metabolic syndrome in mice
© The Author(s). 2018
- Received: 23 June 2018
- Accepted: 30 October 2018
- Published: 13 November 2018
Understanding the mechanism of the sexual dimorphism in susceptibility to obesity and metabolic syndrome (MS) is important for the development of effective interventions for MS.
Here we show that gut microbiome mediates the preventive effect of estrogen (17β-estradiol) on metabolic endotoxemia (ME) and low-grade chronic inflammation (LGCI), the underlying causes of MS and chronic diseases. The characteristic profiles of gut microbiome observed in female and 17β-estradiol-treated male and ovariectomized mice, such as decreased Proteobacteria and lipopolysaccharide biosynthesis, were associated with a lower susceptibility to ME, LGCI, and MS in these animals. Interestingly, fecal microbiota-transplant from male mice transferred the MS phenotype to female mice, while antibiotic treatment eliminated the sexual dimorphism in MS, suggesting a causative role of the gut microbiome in this condition. Moreover, estrogenic compounds such as isoflavones exerted microbiome-modulating effects similar to those of 17β-estradiol and reversed symptoms of MS in the male mice. Finally, both expression and activity of intestinal alkaline phosphatase (IAP), a gut microbiota-modifying non-classical anti-microbial peptide, were upregulated by 17β-estradiol and isoflavones, whereas inhibition of IAP induced ME and LGCI in female mice, indicating a critical role of IAP in mediating the effects of estrogen on these parameters.
In summary, we have identified a previously uncharacterized microbiome-based mechanism that sheds light upon sexual dimorphism in the incidence of MS and that suggests novel therapeutic targets and strategies for the management of obesity and MS in males and postmenopausal women.
- Gut microbiome
- Metabolic syndrome
- Chronic inflammation
Metabolic syndrome (MS) is a cluster of metabolic abnormalities including obesity, visceral adiposity, hyperinsulinemia, hyperglycemia, hypertension, and hypercholesterolemia . It is a leading health issue facing western societies owing to the high sucrose, high saturated fat content, and elevated omega-6/omega-3 fatty acid ratio of the western diet (WD) . Sexual dimorphism in obesity and metabolic dysfunction are observed in both experimental animal models of MS [3–5] and in humans . In fact, in many rodent models, insulin resistance occurs rarely in females or exclusively in males . Moreover, protection from severe high-fat diet (HFD)-induced obesity and MS in C57BL/6 female mice precludes the interrogation of disease pathogenesis in a sex-independent manner . Sex steroid hormones are believed to underlie sexual dimorphism in metabolic outcomes in response to stressors such as the WD, with estrogens theorized to protect women until menopause . Supporting this position, the prevalence of MS is higher in men than in similarly aged pre-menopausal women  and a higher level of adiposity is required in women to elicit metabolic disturbances . Conversely, following the menopause, women tend to accumulate visceral fat and become more insulin resistant, with a consequent increase in the risk of type 2 diabetes . An increasing body of evidence suggests that estrogens also have important beneficial effects on body fat and metabolism in males [10, 11].
The gut microbiota comprises trillions of bacteria that contribute to nutrient acquisition and energy regulation [12, 13]. Growing evidence indicates that obesity is closely linked with low-grade chronic inflammation (LGCI), which can lead to MS [14, 15]. In addition, changes in the composition of the gut microbiota are known to be associated with the development of obesity and its associated metabolic disorders . Interestingly, an increased ratio of the major phyla Firmicutes and Bacteroidetes (FIR/BAC ratio) and depletion of several bacterial species (e.g., Akkermansia mucinophilia) can promote the development of obesity in both dietary and genetic models of obesity in mice [17–19]. Other studies in animal models of obesity suggest that obesity-induced gut dysbiosis caused by either environmental or genetic factors increase populations of bacteria that produce the endotoxin lipopolysaccharide (LPS)  and decrease LPS-suppressing bacteria [20, 21]. This process leads to impaired gut barrier integrity and release of LPS from intestinal gram-negative bacteria into the bloodstream [14, 22] which in turn leads to Toll-like receptor 4 (TLR4)-mediated metabolic endotoxemia (ME), LGCI and insulin resistance in obese mice [23, 24]. Moreover, chronic injection of LPS in mice causes mild obesity and insulin resistance , highlighting a possible role for microbiota-derived LPS in obesity-induced inflammation.
The causative role of the gut microbiota in the context of MS is well characterized [14, 20, 21], but the role of sexual dimorphism on the composition of gut microbiota in the context of MS, and the associated mechanisms underlying such differences, are still unclear. Here, we report that sexual dimorphism in MS is associated with estrogen-mediated changes in the gut microbiome, ME and LGCI, and that 17β-estradiol (17β-E) (E2) treatment prevents MS in male and ovariectomized (OVX) mice by altering gut microbiome and intestinal alkaline phosphatase (IAP), a major gut microbiota-modifying enzyme. Our results shed light on distinct male and female profiles for gut microbiome, IAP, and markers of ME and LGCI that may contribute to sexual dimorphism in MS, revealing new possibilities for preventing and controlling human obesity-related metabolic dysfunction in males and postmenopausal women.
Sex differences in ME and LGCI are associated with sexual dimorphism in MS
Gut microbiome mediates the development of metabolic syndrome in a sex-specific manner
Isoflavones produce microbiome modifying effects similar to estrogen and reverse MS in male mice
Intestinal alkaline phosphatase (IAP) drives sexual dimorphism in gut microbiota
Network interactions reveal host-microbiome interactions (HMI) driven by estrogen status
To date, the mechanisms underlying the reported sexual dimorphism in MS have remained enigmatic. The present study demonstrates for the first time that sex-dependent effects on the gut microbiome mediate sexual dimorphism in MS in C57BL/6 mice and sex-specific expression and activity of IAP, a major gut microbiota-modifying factor [31–33]. Given the causative role of ME originating from dysbiotic gut microbiota and LGCI induced by ME in the context of WD-induced obesity and MS [14–16], the novel findings in our study are as follows: (1) sex-specific differences in the gut microbiota composition (e.g., Proteobacteria, FIR/BAC ratio, B/E ratio, and Akkermansia) and functions (e.g., LPS biosynthesis and LPS-related proteins) and markers of ME and LGCI induced by WD are associated with sexual dimorphism in MS. (2) Male mice are markedly susceptible to ME and LGCI and female mice are exclusively protected from ME and LGCI. (3) Gut microbiota, especially LPS-related bacteria, mediate the sexual dimorphism in MS, reflected by the fact that male mice microbiota transplants induced ME, LGCI, and MS in the female recipients and that ABX abolished the sexual dimorphism and worsened the MS markers in female mice. (4) 17β-E induces gut microbiome changes, which is associated with lower susceptibility to WD-induced ME, LGCI, and MS in the male and OVX mice. Moreover, 17β-E-induced gut microbiome changes and protection against MS are associated with elevation of activity and expression of IAP. (5) Estrogen-like compounds (e.g., isoflavones) had gut microbiome-modifying effects similar to estrogens and prevented WD-induced ME, LGCI, and MS in male mice by elevating IAP, indicating that dietary supplementation of isoflavones could be a potential alternative to 17β-E to treat men and postmenopausal women who are affected by obesity and MS. (6) IAP could largely mediate the 17β-E and ISO-induced gut microbiome changes, and this might be due to the E2-mediated upregulation of transcription factors that target IAP such as KLF4 and CDX1.
It is important to note that the major gut microbiota findings (changes in Proteobacteria, FIR/BAC ratio, B/E ratio, and Akkermansia) reported here regarding sexual dimorphism have been studied extensively in animals and also in the humans in the context of obesity and MS [17–19]. Data obtained from animal models identified consistent differences in the two major bacterial phyla, with a significant increase in Firmicutes and decrease in Bacteroidetes levels in genetically obese mice compared to wild-type mice despite similarities in their diet and activity levels . Consistent with pre-clinical data, numerous human studies have consistently demonstrated that the FIR/BAC ratio is specifically increased in obese people [17–19]. Metabolic endotoxemia derived from gut dysbiosis is central to the pathogenesis of chronic low-grade inflammation, a factor underlying many current chronic diseases [9, 22]. Metabolic endotoxemia can be determined by the abundance of bacteria affecting LPS production and gut barrier function. It is therefore conceivable that the 17β-E-induced marked reductions in LPS-producing bacteria (e.g., Proteobacteria) and increases in LPS-suppressing bacteria (e.g., Bifidobacterium and A. mucinophila) [14, 25–27] significantly suppressed the development of endotoxemia and inflammation. Recent clinical studies have shown that LPS-producing bacteria are abundant in obese subjects with type 2 diabetes [14, 16, 38–40]. It has also been shown that male mice fed a WD rich in milk fat and omega-6 fatty acids exhibit overgrowth of LPS-producing Proteobacteria and reduction of LPS-suppressing Bifidobacterium spp [27, 41, 42]. Along these lines, the WD diet used in the present study induced a dramatic increase in Proteobacteria and a decrease in Bifidobacterium in male and OVX mice (Fig. 3 and 5). In this context, decreasing the abundance of LPS-producing bacteria and increasing the LPS-suppressing bacteria may be a key mechanism for the reduction of metabolic endotoxemia. Another potential mechanism contributing to the reduction of serum LPS may be a decrease in gut permeability, due to the observed elevation of gut barrier-protecting bacteria such as Bifidobacterium [14, 43] by estrogen in our study.
In postmenopausal women and in female animal models, lower estrogen levels are associated with increased visceral adiposity  and estrogen replacement improves glucose-insulin homeostasis . We have shown here for the first time the effects of E2 replacement on gut microbiota and metabolic endotoxemia in OVX mice, which mimics the postmenopausal state. There is growing evidence for a fundamental role of estrogen in the regulation of obesity and related metabolic disorders in males [11, 45], and recent data from rodent studies suggest that hepatic estrogen signaling has a key role in the prevention of high-fat diet-induced insulin resistance in males. However, it is not known whether estrogen treatment in males protects MS by modulating gut microbiota. Our novel results show that estrogen treatment in males is associated with the modulation of gut microbiota and improvement in ME and LGCI, which is associated with improvements in weight management and obesity-induced metabolic changes (Fig. 7), supporting the concept that estrogen plays an important role in the control of serum LPS levels by affecting LPS-related gut microbiota.
IAP is an endogenous antimicrobial peptide with numerous physiological functions [46, 47]. It is highly expressed in the small intestine, secreted from apical enterocytes into the lumen in microvilli vesicles, and travels to the large intestine . IAP is known to inhibit the growth of E. coli and gram-negative bacteria by dephosphorylating LPS located in the outer membrane [32, 48–51]. IAP is also able to dephosphorylate ATP , which has been shown to reduce the survival of gram-positive bacteria (46), and to support the growth of gram-negative bacteria such as E. coli . Oral IAP supplementation has also been shown to prevent E. coli overgrowth . We recently found in our fat-1 mice model (transgenic mice with elevated tissue n-6/n-3 fatty acid ratio) that elevated endogenous IAP activity and expression is associated with lower levels of LPS-producing bacteria and higher levels of LPS-suppressing bacteria . Moreover, we found that inhibition of IAP by phenylalanine, a frequently used specific inhibitor of endogenous IAP activity [14, 15, 34, 35], caused ME, LGCI, and MS by increasing the growth of LPS-producing Proteobacteria and reducing the growth of LPS-suppressing Bifidobacterium spp in a mouse model of elevated endogenous IAP activity [14, 15]. It is clear that IAP expression in the intestine is a critical determinant of the gut microbiota profile. Our findings indicate that IAP may be a primary factor partially mediating the effects of estrogen on gut microbiota because IAP inhibition in the female mice led to the development of ME, LGCI, and MS, associated with dramatic increase of Proteobacteria and reduction of the B/E ratio and A. mucinophila abundance (Fig. 6n–q). The mechanism by which estrogen may modulate IAP expression is possibly due to its regulatory effect on the KLF4 transcription factor, which has been shown to target IAP .
Isoflavones (ISO) are non-steroidal compounds that can bind to both ER-α and ER-β due to their ability to mimic the conformational structure of estradiol [54, 55], and thereby imitate the actions of estrogens on target tissues . Isoflavones are found in many legumes and are particularly abundant in soy products. Genistein (G) and daidzein (D), two major soy isoflavone glucosides, are present at high concentrations in soybeans and soybean-derived products and are a major source of xenoestrogen exposure in both humans (e.g., soy-based formula for infants, tofu) and animals (most commercially available diets). G and D are widely used as dietary supplements in the USA for various presumed health benefits . Ferguson et al.  administered a low-dose endotoxin (LPS 1 ng/kg) to induce postprandial transient endotoxemia in young, healthy volunteers and found that subjects with a high-isoflavone diet were protected against inflammation-induced decline in insulin sensitivity. Meals high in fat, or fat and simple carbohydrates, are known to induce metabolic endotoxemia , as characterized by increased circulating markers of inflammation, and hypothesized to be linked to transient bacteremia due to reduced gut barrier function . Most importantly, ISO has been shown to have E2 mimetic effects in preventing ovariectomy-induced metabolic dysfunctions , adipose deposition , hypertriglyceridemia, and hepatic status  in animal studies. Isoflavones have been shown to improve intestinal barrier integrity  and reduce colitis in animal models  potentially through modulation of the gut microbiome . ISO may therefore confer protection against diet-induced metabolic dysfunction and reduce the development of insulin resistance in males and post-menopausal women, therefore supporting our proposal that ISO could be an effective alternative to E2 treatment.
Although we claim to explain the metabolic sexual dimorphism by effects of E2 through gut microbiota, we acknowledge that many other studies in the field showed that the major impact of estrogens on the metabolism are through estrogen receptor expression in metabolic tissues [66–69]. Clinical trials revealed that hormone replacement therapy (HRT) in postmenopausal women reduced the features of MS and inflammation . Conversely, findings from Women’s Health Initiative clinical trials (WHI-CT)  did not support use of HRT for chronic disease prevention . However, the WHI-CT results were based on a group of women who were much older than those normally treated with HRT and who had other numerous risk factors . Noticeably, there were very limited surveys performed addressing the effects on the metabolic syndrome components in postmenopausal women . Early treatment with low-dosage HRT in healthy perimenopausal women was found to have beneficial effects on the components of metabolic syndrome and could decrease the risk of cardiovascular events  since the absolute risk of CVD events were markedly lower in younger, compared to older, women .
Although our results from FMT (Fig. 3) and antibiotics (Fig. 4) experiments contradict the protective effect of endogenous estrogen against obesity in female mice, it is well known that antibiotic usage  or gut dysbiosis  impacts estrogen metabolism mediated by microbiota Consequently, changes in circulating levels of estrogen (Additional file 1 Figure S3m and Additional file 1: Figure S4e) were found in female mice that received male microbiota transplants or antibiotic treatment. We hypothesize that estrogen-mediated gut microbiome changes may be the cause for sex differences in obesity and MS in this study. It is important to note the estrogen-mediated sex differences and the role of the microbiome have been linked in other disease conditions (e.g., autoimmunity) . The bacterial changes reported here are similar to previous studies where ovariectomy or estrogen supplementation was performed. A study with OVX animals showed elevated Firmicutes to Bacteroidetes ratio  and Escherichia coli  compared to normal females. Likewise, it was shown that E2 supplementation elevated the relative abundance of Akkermansia and Bifidobacterium in the male and OVX mice respectively [80–82]. Estrogen inhibited the overgrowth of Proteobacteria and E. coli and decreased the levels of LBS and LBP under simulated microgravity . In addition, E2 supplementation in male  or OVX mice  prevented obesity and MS, and genistein prevented obesity and metabolic dysfunction in the mice, which was similar to E2 supplementation in the same study [60, 61].
Our novel data demonstrate that the gut microbiome mediates sexual dimorphism in MS. Overall measures of correlation, pairwise correlations, and multivariate correlation analyses between the microbiota and host parameters that we performed provided novel insight into the host–microbiota system in the context of sexual dimorphism in WD-induced MS. Estrogen or estrogen-like compounds induced elevated IAP levels likely by upregulating the function of the KLF4 transcription factor that targets IAP and subsequent gut microbiome changes lower LPS production and gut permeability, resulting in reduced ME and systemic LGCI with subsequent reduction in the susceptibility to develop WD-induced MS in estrogen-treated males and post-menopausal women. Because exogenous estrogen administration to male causes deleterious effects (e.g., feminization and cardiac dysfunction) , compounds with estrogen-like activity (e.g., isoflavones and 17α-estradiol ) and non-feminizing effects may represent an alternative approach to the management of obesity and MS in males. Understanding the molecular basis of estrogen-mediated changes in IAP activity and gut microbiome may provide new approaches to the management of obesity-associated metabolic disease in men and menopausal women with estrogen deficiency, a condition that can last approximately 30 years of a woman’s life .
Animals and diets
All the mice used in this study were wild-type (WT) on a C57BL/6 background and bred at the Massachusetts General Hospital (MGH) animal facility or purchased from Charles River Laboratories. Mice were housed in a biosafety level 2 room in hard top cages with two or three mice per cage. Mice were maintained in a temperature-controlled room (22–24 °C) with a 12-h light/12-h dark diurnal cycle and allowed for food and water ad libitum. Diets used in this study were either normal chow diet (CD) (Laboratory Rodent Diet 5001) from LabDiet or western diet (WD) (D12079B) from Research diets, Inc., NJ, USA. All animal procedures in this study were carried out in accordance with the guidelines approved by the MGH Subcommittee on Research Animal Care.
Determination of sexual dimorphism in metabolic endotoxemia, low-grade chronic inflammation, and metabolic syndrome: Male (M) WT (n = 11) and female (F) (n = 11) mice were weaned and switched to western diet (WD) until the age of 20 weeks to induce severe WD-induced obesity and MS. Both groups were subjected to analysis of markers of metabolic endotoxemia (ME) (including LPS, LBP, sCD14, and intestinal permeability), systemic low-grade chronic inflammation (LGCI) (including TNF-α, IL-1β, IL-6, MCP-1, and IL-10), and metabolic syndrome (MS) (including weight gain, glucose tolerance test with area under the curve, insulin resistance index assessed by HOMA-IR, serum lipid profile including total cholesterol (TC), triglyceride (TG), low-density lipoprotein-C (LDL-C) and high-density lipoprotein-C (HDL-C) and atherogenic index, non-alcoholic fatty liver score and serum aspartate transaminase (AST) and alanine transaminase (ALT), and analysis of fecal microbiota by 16S rRNA gene sequencing and serum LPS levels by LAL assay. The mice were then euthanized and white adipose tissue (WAT), which includes visceral (vWAT), subcutaneous (sWAT), and epididymal (eWAT) fat pads, and liver weights were taken. A portion of the liver was stored in 10% formalin for histological analysis. Tissues were snap frozen in liquid nitrogen and then stored at − 80 °C for future analyses.
Determination of 17β-estradiol effects on gut microbiome, metabolic endotoxemia, low-grade chronic inflammation, and metabolic syndrome: Ten-week-old male (M), female (F), and ovariectomized (OVX) mice maintained on control diet were purchased from Charles River Laboratories and divided in to five groups (n = 5/group), and were fed WD and 17β-estradiol (E2) from week 11 to week 17. The five groups are (1) M, (2) F, (3) M+E2, (4) OVX, and (5) OVX+E2. E2 (Sigma, USA) was prepared and given to groups 3 and 5 in the drinking water as described previously . E2 was dissolved in 95% ethanol (5 mg/mL). Solubilized E2 was added to the drinking water to produce concentration of 4000 ng E2/mL water with final ethanol concentration of 0.1%. Groups 1, 2, and 4 received a normal drinking water bottle with 0.1% ethanol. The water bottles were changed every week for all the groups. After 6 weeks, mice were subjected to analysis for markers of ME and systemic LGCI and MS as mentioned in section 1. The mice were then euthanized and WAT and liver weights were taken. A portion of the liver and duodenum was stored in 10% formalin for histological analysis. Tissues were snap frozen in liquid nitrogen and then stored at − 80 °C for future analyses.
Fecal microbiota transplantation (FMT): Mice from each group were individually housed for receiving antibiotic treatment to the end of the experiment. Fecal microbiota in place of cecal microbiota was transplanted for convenience and in order to minimize the number of animals used as donors. FMT with fecal content from donor male (M) mice that were fed WD for 10 weeks was performed on female 10-week-old mice . Before the microbial transplantation, recipient mice (M → F) were treated with a 200 μL antibiotic cocktail (ampicillin, 1 g/l; metronidazole, 1 g/l; vancomycin, 0.5 g/l; neomycin, 0.5 g/l) (Sigma, USA) administrated by oral gavage once a day for 3 days. During the last 8 h of antibiotic treatment, mice were fed a WD to facilitate subsequent colonization. Fresh fecal pellets from donors were immediately weighed and placed into Ringer’s solution and then diluted to 10 mg/mL. Immediately after diluting the fecal materials, fecal solutions were gavaged (200 μL per mouse) to 4-h-fasted female recipients. Control groups of mice (males and females) were force-fed with 200 μL of transfer buffer alone to eliminate the effects of gavage per se. Two days later, these mice received another gavage to exclude possibility of any unsuccessful inoculation. We conducted this FMT procedure once a week for the next 3 weeks. After the first microbiota gavage, all mice were fed a WD for 20 weeks. Measurement of body composition (fat mass) was performed using nuclear magnetic resonance (NMR) technique (minispec Body Composition Analyzer based on Time Domain NMR) that provides noninvasive and rapid measurement without anesthetics. Fecal samples from these three groups (M/F/M → F; n = 5 per group) were collected after WD feeding for 20 weeks and three fecal samples from each group were subjected to 16S rRNA sequencing.
Antibiotic (ABX) treatment: 10-week-old male (n = 5) and female (n = 5) mice maintained on chow diet were switched to a WD until the age of 20 weeks to induce sexual dimorphism in MS. After collecting serum and stool for baseline measurements, both males and females receiving a WD started receiving a broad spectrum antibiotic cocktail (ABX) containing ampicillin (1 g/l), vancomycin (500 mg/l), neomycin sulfate (1 g/l) (added to the drinking water), and metronidazole (100 mg/kg) (orally gavaged every 12 h) for 6 weeks to deplete the gut microbiota . Validation of successful depletion of gut microbiota after the antibiotic treatment was performed as described previously . Briefly, bacterial cultivation (both aerobic and anaerobic bacteria) of feces was performed on day 24 of the antibiotic treatment mice as described previously . The detection limit of the assay (successful depletion) was defined as 1 cfu/mg feces. In addition, the bacterial genomic DNA was extracted from fresh stool samples of these mice and 16S rRNA gene copies for all bacteria (Table S4) was measured with qPCR method as described below. Both bacterial cultivation (cfu/mg feces) and qPCR results (Ct values) were compared with results from pre-antibiotic treatment fecal samples to confirm a significant depletion of gut microbiota. Mice with antibiotic treatment were subjected to analysis for markers of ME and systemic LGCI and MS as mentioned in section 1.
Analysis of the effects of isoflavones (ISO) on gut microbiome, ME, LGCI, and MS: Ten-week-old male (M) mice were fed a WD for 4 months to induce MS and then divided into two groups: group 1: M, (n = 4), and group 2: M+ISO (n = 6). ISO such as genistein and daidzein (Cayman, USA) were supplemented at 0.1% in the WD, the M group was fed a WD, and the M+ISO group was fed a WD supplemented with ISO for the next 5 weeks. Mice were then subjected to analysis for markers of ME and systemic LGCI and MS as mentioned in section 1. The mice were then euthanized and white adipose tissue (WAT) and liver weights were taken. A portion of the liver and duodenum was stored in 10% formalin for histological analysis. Tissues were snap frozen in liquid nitrogen and then stored at − 80 °C for future analyses.
Analysis of the effects of intestinal alkaline phosphatase (IAP) inhibition on gut microbiome, ME, LGCI, and metabolic abnormalities: To determine the effects of inhibiting endogenous IAP activity, 12-week-old WT mice on a WD were divided into three groups ((male (M), female (F), and F+L-phe)) (n = 5 per group) and allowed to drink autoclaved water alone or water containing 10 mM L-phenylalanine (L-phe) (Sigma, USA). After 8 weeks, the serum and fecal samples were collected to analyze the markers of ME, LGCI, and MS.
Extraction of genomic DNA and profiling of the 16S rRNA gene by next generation
Fecal DNA extraction and 16S rRNA gene sequencing
Bacterial genomic DNA was extracted from fresh stool samples (100–180 mg) using the QIAamp DNA Stool Mini Kit (Qiagen, Valencia, CA), following the manufacturer’s instructions. To increase effectiveness, the lysis temperature was increased to 95 °C. Eluted DNA was treated with RNase and analyzed using a Nanodrop spectrophotometer (Biotek, Winooski, VT). Sample concentration and purity was determined by absorbance at 260 nm and the A260/A280 ratio, respectively. DNA samples packed with dry ice were shipped to APC Microbiome Institute (University College Cork, Cork, Ireland), and samples were sequenced as previously mentioned . Briefly, V3–V4 amplicons for Illumina sequencing were generated according to the 16S metagenomic sequencing library protocol (Illumina). An initial PCR reaction utilized primers specific for amplification of the V3–V4 region of the 16S rRNA gene, (Forward primer 5′TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG; reverse primer 5′ GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC). PCR product clean-up and purification was achieved using the Agencourt AMPure XP system (Labplan, Dublin, Ireland). A second PCR incorporated a unique indexing primer pair for each sample (Illumina Nextera XT indexing primers, Illumina, Sweden). The products were again purified using the Agencourt AMPure XP system. Samples were quantified using the Qubit broad range DNA quantification assay kit (Bio-Sciences, Dublin, Ireland). Following quantification, samples were pooled in equimolar amounts (4 nM) and sequenced at Clinical Microbiomcs, Copenhagen, Denmark, using Illumina MiSeq 2 × 300 bp paired end sequencing.
Three hundred-base pair paired-end reads were assembled using FLASH with parameters of a minimum overlap of 20 bp and a maximum overlap of 120 bp . The QIIME suite of tools, v1.8.0, was used for further processing of paired-end reads, including quality filtering based on a quality score of > 25 and removal of mismatched barcodes and sequences below length thresholds . Denoising, chimera detection, and operational taxonomic unit (OTU) grouping were performed in QIIME using USEARCH v7 . Taxonomic ranks were assigned by alignment of OTUs using PyNAST to the SILVA SSURef database release 111 . Generation of α and β diversities and analysis and visualization of principal coordinate analysis (PCoA) plots were performed using PAST and XLSTAT software. The α-diversity of each group was calculated based on the annotated data using the diversity indices of the PAST version 2.17 software program . Based on a non-parametric two-sample t-test using the default number of Monte Carlo permutations (999), comparative analyses of the group-specific α-diversity indices were performed. Ordinations are the dimensional-reduction techniques which are commonly used to visualize complex relationships between communities between groups (β-diversity). Dimensional reduction of the Bray-Curtis distance between microbiome samples using PCoA ordination method (PAST software) was done and significant differences among groups were tested with permutational multivariate analysis of variance (PERMANOVA), a multivariate non-parametric one-way ANOVA, which utilizes the sample-to-sample Bray-Curtis distance matrix directly. Taxa which were primarily responsible for an observed difference between groups were identified by SIMPER (similarity percentage analysis) method and their contribution to groups (between and within groups) were analyzed using the PCA variance-covariance type ordination (PAST software) method. Differential abundance analysis (non-parametric ANOVA with Benjamini-Hochberg FDR-corrected P values < 0.05) was performed on the RA of microbiota data at different levels of taxonomy to identify taxa with FDR-corrected P values < 0.05 (XLSTAT software; Addinsoft, USA)  and then their RA (normalized to percentage) were shown by a heat map with hierarchal clustering (HCN) analysis  using GraphPad Prism version 7.01 (La Jolla, CA). Linear discriminant analysis (LDA) effect size (LEfSe) is a biomarker discovery and explanation tool for high-dimensional data. It couples statistical significance with biological consistency and effect size estimation . Microbiota-based biomarker discoveries were done with LEfSe using the online galaxy server (https://huttenhower.sph.harvard.edu/galaxy/), and the LDA scores derived from LEfSe analysis  were used to show the relationship between taxon using a cladogram (circular hierarchical tree) of significantly increased or decreased bacterial taxa in the gut microbiota between groups. Levels of the cladogram represent, from the inner to outer rings, phylum, class, order, family, and genus. Color codes indicate the groups, and letters indicate the taxa that contribute to the uniqueness of the corresponding groups at an LDA of > 2.0. Unweighted pair-group method with arithmetic means (UPGMA) hierarchical clustering analysis diagram based on Bray-Curtis distance matrix was obtained using PAST version 3.11. Class trees were used to demonstrate similarity between samples, the clustering tree branch length was a measure of the cluster effect.
b)Putative metagenome identification
Microbial functions were predicted using 16S ribosomal RNA sequencing and phylogenetic reconstruction of unobserved states (PICRUSt) software (version 1.0.0) as described . The predicted genes and functions were aligned to the KEGG database (version 66.1, May 1, 2013). PCA and PERMANOVA statistics were applied to check whether the groups were clustered according to predicted gene enrichments for microbial functions. LEfSe analysis  was utilized to determine significant putative KEGG orthologs and pathway analyses .
Lipopolysaccharide (LPS) concentration
Serum LPS concentrations were measured with a Toxin Sensor Chromogenic Limulus Amebocyte Lysate (LAL) Endotoxin Assay Kit (GenScript, Piscataway, NJ), following the manufacturer’s instructions . Briefly, serum samples were diluted 10- to 50-fold with endotoxin-free water, adjusted to the recommended pH, and heated for 10 min at 70 °C to minimize inhibition or enhancement by contaminating proteins. LAL reagents were added to serum and incubated at 37 °C for 45 min, and the absorbance was read at 545 nm. All samples were validated for recovery and internal coefficient variation using known amounts of LPS.
Intestinal permeability was determined as previously described . Briefly, mice were gavaged with phosphate buffered saline (PBS, pH 7.2) containing 600 mg/kg body weight FITC-dextran (40 kDa, Sigma-Aldrich, USA). Blood samples (120 μL) were collected after 90 min. Serum was diluted with an equal volume of PBS, and fluorescence intensity was measured using a fluorospectrophotometer (excitation wavelength 480 nm and emission wavelength 520 nm; Perkin-Elmer, Waltham, MA). Serum FITC-dextran concentrations were calculated from a standard curve of serially diluted FITC-dextran in PBS.
Measurement of intestinal alkaline phosphatase (IAP) level and activity
Small intestinal IAP specific activity (as it relates to protein) was measured as previously described  and expressed as picomoles pNPP hydrolyzed/min/μg of protein. Briefly, thoroughly washed duodenal tissues were homogenized with lysis buffer (150 mM NaCl, 10 mM Tris·HCl, pH 7.5, 1% sodium deoxycholate, 1% Nonidet P-40, 10 mM EDTA, 0.1% SDS, including protease inhibitor mixture; Sigma) followed by incubation on ice for 30 min. Thereafter, the homogenates were centrifuged twice at 4 °C at 15,000g for 15 min, and the supernatants were collected to determine IAP activity as well as protein concentration. The Coomassie Blue Protein Assay (Bradford) kit from Fisher Scientific was used for protein quantification. For IAP assay, 25 μL of supernatant was mixed with 175 μL phosphatase assay reagent containing 5 mM of p-nitrophenyl phosphate (pNPP) followed by determining optical density at 405 nm. The specific activity of the enzyme was expressed as picomoles pNPP hydrolyzed/min/μg of protein. Protein concentration in a specific sample was determined using the protein assay reagents from Fisher Scientific.
Cell culture experiments
The human colon carcinoma cell line (Caco-2) was obtained from American Type Culture Collection (ATCC) (Rockville, MD) and cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM) (Corning Inc., NY, USA) containing 4.5 g/l glucose, 4 mmol/l l-glutamine, and 1 mmol/l sodium pyruvate, and supplemented with 10% fetal bovine serum (Cell Applications, Inc., San Diego, CA), 100 U/mL penicillin, and 100 μg/mL streptomycin (Gibco, NY, USA) in a humidified atmosphere of 5% CO2 at 37 °C. They were routinely subcultured when they were about 80% confluent. The culture medium was changed every other day. Cells were always > 90% viable, as shown by trypan blue (Invitrogen, Carlsbad, CA, USA) exclusion. Cells were passaged every 3–4 days by treatment with 0.1% trypsin (Gibco) and 0.04% ethylenediaminetetraacetic acid (EDTA) and then plated at a density of 1.3–2 × 104 cells/cm2. Cells at passage number 17 were used for the experiments. All assays were done using only differentiated Caco-2. Cells were seeded in to six-well plates at 2 × 104 cells per well and treated with vehicle (ethanol or DMSO) or 10 nM 17β-estradiol (E2) for 24, 48, and 72 h or each 25 μM genistein (G) or daidzein (D) or G+D mixture for 72 h. In a subset of experiments, Caco-2 cells were pre-treated with L-phenylalanine (10 mM) for 24 h and then they were treated with either vehicle or each 25 μM G+D mixture or 10 nM E2 for 72 h. Medium was removed and cells were washed twice with ice-cold PBS, scraped, lysed in Trizol (Invitrogen), and stored at − 80 °C until mRNA was isolated or homogenized with 200 μL radioimmunoprecipitation assay (RIPA) buffer (50 mM Tris-HCl, pH 7.4, 150 mM NaCl, 1% Triton X-100, 1% sodium deoxycholate, 0.1% sodium dodecyl sulfate) containing protease inhibitor cocktail (Sigma), incubated on ice for 30 min, centrifuged at 14,000g for 10 min at 4 °C and the supernatant was collected and stored at − 80 °C for western blotting analysis.
Western blotting analysis of IAP
Western blotting on tissues and Caco-2 cell lysates was performed as previously described . After thawed, the protein samples derived from Caco-2 cells, the homogenates were centrifuged at 15,000g at 4 °C for 15 min, and the supernatants were collected. The duodenum section of small intestinal tissues was harvested and cut open longitudinally and luminal contents were removed. The tissues were washed with PBS and homogenized with liquid nitrogen, and homogenates were mixed with RIPA buffer, incubated on ice for 30 min, and centrifuged at 14,000g for 10 min at 4 °C, and the supernatant was collected. Protein concentration of Caco-2 and tissue homogenates was quantified by the Coomassie blue protein assay (Thermo Scientific, Rockford, IL, USA) using bovine serum albumin (BSA) as the standard. Proteins (30 μg) were resolved on SDS-PAGE gels and transferred onto nitrocellulose membranes (Osmonics, Minnetonka, MN, USA). The membranes were blocked with 5% nonfat dry milk in Tris-buffered saline with 0.05% Tween 20 (TBS-T) for 1 h at room temperature and then probed with IAP primary antibodies (GTX27322, GeneTex, San Antonio, TX, USA) in 5% non-fat dry milk in TBS-T at 4 °C overnight. After washing three times in TBS-T, the blots were further incubated with the corresponding secondary antibodies conjugated with horseradish peroxidase for 1 h at room temperature (Santa Cruz Biotechnology, Santa Cruz, CA). Chemiluminescence was detected with Pierce ECL western blotting substrate (Thermo Scientific, Rockford, IL, USA) and visualized by ChemiDoc MP Imaging System (Bio-Rad, Hercules, CA, USA).
Immunohistochemical analysis of IAP
Formalin-fixed duodenal tissues and IAP primary antibodies (GTX27322, GeneTex)  were given to MGH core (Boston, MA). Prepared IHC slides were analyzed under light microscope and images of IAP staining and localization was taken by using × 20 magnifications. All pictures were taken with the same exposure conditions without autoscaling.
The RV coefficient was calculated between the microbial genera (FDR-corrected P value < 0.05) and the host parameters (markers of ME, LGCI and MS). The RV coefficient is a multivariate generalization of the Pearson correlation coefficient .
Correlation network analysis
Network-based analytical approaches have the potential to help disentangle complex host-microbe interactions . Pairwise correlations between each microbiota (genera that are present at < 0.1% relative abundance in > 75% samples have been removed to avoid detecting spurious correlations among low-abundance OTUs) and host parameter (markers of ME, LGCI, and MS) were calculated using Spearman’s nonparametric rank correlation coefficient . Using those significant (P < 0.05) correlation coefficients, a correlation network (Fruchterman Reingold and label adjust layout) was built where nodes represent either a microbiota or a host parameter. For each microbiota and a host parameter, an undirected edge was added between the corresponding nodes in the correlation network. Edges (light black links indicate positive and blue links indicate negative associations) represent statistically significant correlations (P < 0.05). Correlations were calculated using the PAST software version 2.17 and the network was visualized in Gephi Graph Visualization and Manipulation software version 0.9.2 . Nodes were colored based on “data type” and sized based on “betweeness centrality (BC).” BC is a network centrality measure that quantifies the influence of a node in connecting other nodes in a network. It represents the fraction of all shortest paths in the network that pass through a given node. The nodes with the highest BC are usually known as highly central or hubs. A “module or component” in the network is a set of nodes connected to each other by many links, while connected by few links to nodes of other groups, so modules are elementary units of any biological network, and their identification and characterization provides us with more information about the local interaction patterns in the network and their contribution to the overall structure, connectivity, and function of the network. Modules are biologically important when considered as isolated, taxonomic, evolutionary, or functional modules. High modularity indicates that the network has dense connections within certain groups of nodes and sparse connections between these groups.
Multivariate statistical analysis
Partial least square regression (PLS-R) was used to associate the microbial composition to host parameters including jackknife-based variable selection . PLS-R is recommended in cases of regression where the number of explanatory variables is high, and where it is likely that the explanatory variables are correlated. Leave one-out cross-validation (LOO-CV) was applied. The Q2 cumulated index (Q2cum) measures the global goodness of fit and the predictive quality of the models. Q2cum is also used to test the validity of the model against over-fitting. The cumulated R2Y and R2X cum that corresponds to the correlations between the explanatory (X) and dependent (Y) variables with the components are very close to one with two components in all the models. This indicates that the two components generated by the PLR-R summarize well both the Xs and the Ys. The results are also presented in PLS scatter plots for subject clustering and variables. The R2 (coefficient of determination) indicates the % of variability of the dependent variable (Y) which is explained by the explanatory variables (X). Parameters (variable importance in the projection values 1 or > 1.0) contributing to the multivariate PLS models were compared with the corresponding identified modules (Fig. 7b–d) in the correlation networks. All analyses were performed using precise algorithm in the XLSTAT software version 2017.6.
Data was shown as mean ± standard error of mean (SEM). Box-plots (box showing the median, and the 25th and 75th percentiles, and the whiskers of the graph show the largest and smallest values) were also used to express the data. Unpaired Student’s t test was performed for experiments having only two groups. Either ordinary or repeated measures one-way or two-way analysis of variance (ANOVA) with Tukey’s or Sidak’s multiple comparisons post-test were used for experiments having more than two groups. If unequal variance was detected, data were analyzed using non-parametric tests. Differences were considered significant at P < 0.05. Statistical analyses, including heat-map preparation, were performed using GraphPad Prism version 7.01 (GraphPad Software, La Jolla, CA). Differential expression analysis on 16S sequencing data was conducted using XLSTAT software program . Multivariate statistical analyses and power analyses (alpha = 0.05; effect size = 0.8) were conducted using PAST (version 2.17)  and XLSTAT (version 2017.6) software products.
We thank Neil McKenna and Nicola Donelan (English language editors) for proofreading this manuscript. The authors are also grateful to Marina Kang for her editorial assistance and Jennifer Bian for her experimental assistance. The authors declare no competing financial interests.
This study was supported by generous funding from Sansun Life Sciences and the Fortune Education Foundation.
Availability of data and materials
OTU tables, raw data, taxonomy, FASTA files, scripts, PLS tables, and metadata for 16S rRNA gene sequence analysis performed in this study have been made publicly available in Figshare.
JXK and KK conceived and designed the study; KK conducted all the mouse studies, collected serum and fecal and tissue samples, and performed biochemical and host-microbiota interaction analyses; RR, KM, and CS performed the 16S sequencing part of the study; CK, BW, and KK performed the predicted functional analysis using 16S sequencing data; KK and JXK analyzed the metagenomic sequencing data; AKB performed the histopathological analyses of liver samples; KK and LH performed the cell culture experiments; KK and JXK wrote the manuscript; All authors approved the final version of the manuscript.
All animal procedures in this study were performed in accordance with the ethical guidelines approved by the MGH Subcommittee on Research Animal Care.
The authors declare that they have no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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