During menopausal transition, the imbalance of estrogen causes body weight gain. Although gut microbiome dysbiosis has been reported in postmenopausal obesity, it is not clear whether there is any difference in the microbiome profile between dietary-induced obesity and postmenopausal obesity. Theref...
During menopausal transition, the imbalance of estrogen causes body weight gain. Although gut microbiome dysbiosis has been reported in postmenopausal obesity, it is not clear whether there is any difference in the microbiome profile between dietary-induced obesity and postmenopausal obesity. Therefore, in this study, we analyzed intestinal samples from ovariectomized mice and compared them with those of mice with high-fat diet-induced obesity. To further evaluate the presence of menopause-specific bacteria-gene interactions, we also analyzed the liver transcriptome. Investigation of the 16S rRNA V3-V4 region amplicon sequence profile revealed that menopausal obesity and dietary obesity resulted in similar gut microbiome structures. However, Bifidobacterium animalis was exclusively observed in the ovariectomized mice, which indicated that menopausal obesity resulted in a different intestinal microbiome than dietary obesity. Additionally, several bacterial taxa (Dorea species, Akkermansia muciniphila, and Desulfovibrio species) were found when the ovariectomized mice were treated with a high-fat diet. A significant correlation between the above-mentioned menopause-specific bacteria and the genes for female hormone metabolism was also observed, suggesting the possibility of bacteria-gene interactions in menopausal obesity. Our findings revealed the characteristics of the intestinal microbiome in menopausal obesity in the mouse model, which is very similar to the dietary obesity microbiome but having its own diagnostic bacteria.
During menopausal transition, the imbalance of estrogen causes body weight gain. Although gut microbiome dysbiosis has been reported in postmenopausal obesity, it is not clear whether there is any difference in the microbiome profile between dietary-induced obesity and postmenopausal obesity. Therefore, in this study, we analyzed intestinal samples from ovariectomized mice and compared them with those of mice with high-fat diet-induced obesity. To further evaluate the presence of menopause-specific bacteria-gene interactions, we also analyzed the liver transcriptome. Investigation of the 16S rRNA V3-V4 region amplicon sequence profile revealed that menopausal obesity and dietary obesity resulted in similar gut microbiome structures. However, Bifidobacterium animalis was exclusively observed in the ovariectomized mice, which indicated that menopausal obesity resulted in a different intestinal microbiome than dietary obesity. Additionally, several bacterial taxa (Dorea species, Akkermansia muciniphila, and Desulfovibrio species) were found when the ovariectomized mice were treated with a high-fat diet. A significant correlation between the above-mentioned menopause-specific bacteria and the genes for female hormone metabolism was also observed, suggesting the possibility of bacteria-gene interactions in menopausal obesity. Our findings revealed the characteristics of the intestinal microbiome in menopausal obesity in the mouse model, which is very similar to the dietary obesity microbiome but having its own diagnostic bacteria.
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문제 정의
Although there have been many studies on the microbiome profile of animal models and humans, it is not known whether postmenopausal weight gain induces the same changes in the gut microbiome as dietary-induced obesity does. Therefore, the objective of this study was to investigate the effect of menopausal body weight gain on the gut microbiome in an ovariectomized animal model in controlled experiments. To this end, we analyzed the gut microbiome of ovariectomized mice and compared it with that of mice with high-fat diet-induced obesity.
제안 방법
The mice were kept under controlled environmental conditions (22 ± 2℃, 50–60% humidity, 12-h light/dark cycle) in the Animal Care Facility at the National Institute of Agricultural Sciences (Korea). After 1 week of acclimatization, the mice were divided into four groups: SHAM (sham-operated mice; n = 3), OVX (ovariectomized mice; n = 5), SHAM-HF (sham-operated mice given a high-fat diet; n = 3), and OVX-HF (ovariectomized mice given a high-fat diet; n = 5). The low-fat diet groups (SHAM and OVX) were fed with Normal Chow diet (+40 RMM) purchased from Central Laboratory Animal, Inc.
1. Differences in the microbiome between samples quantified using the weighted UniFrac distance and principal coordinate analysis.
The gene-specific forward primer (5’-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG-CCTACGGGNGGCWGCAG; with the underline indicating the Illumina overhang adapter sequence) and reverse primer (5’-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG-GACTACHVGGGTATCTAATCC) were used for 1st stage PCR to amplify the 16S rRNA gene. To add dual indices and Illumina sequencing adapters to the 1st stage amplicons, 2nd stage PCR was performed using the Nextera XT Index Kit (Illumina). The prepared libraries were then pooled and sequenced using the MiSeq sequencer with 2 × 250-bp paired-end option (Illumina).
대상 데이터
The prepared libraries were then pooled and sequenced using the MiSeq sequencer with 2 × 250-bp paired-end option (Illumina). The sequence data have been deposited in the NCBI Short Read Archive under the accession number SRX3195509. The resultant sequencing reads were analyzed using the QIIME pipeline [25] and Greengenes 16S database 13_8 [26].
데이터처리
05 were selected. Pearson correlation coefficients were calculated between pairs of expression level and bacterial abundance (%). Permutation was performed 1,000 times, and the p value was corrected using the Benjamin method using the R program [33], and gene-bacterial pairs with p-values < 0.
The differences in taxa abundance, depending on categorical metadata, were evaluated using Hotelling’s t-test (p-value ≤ 0.05) and LEfSe analyses (LDA score ≥ 2.50) [29].
The statistical significance was calculated using the modified Fisher’s exact test.
이론/모형
RNA labeling and hybridization were performed using the Agilent One-Color Microarray-Based Gene Expression Analysis protocol (ver. 6.5; Agilent Technologies, USA).
The beta-diversity of the microbiome was calculated using Fast UniFrac interface [28] and visualized using principal coordinate analysis (PCoA). The Unifrac distance-based inter- and intra-dissimilarity depending on experimental groups was determined using the ANOSIM test. The differences in taxa abundance, depending on categorical metadata, were evaluated using Hotelling’s t-test (p-value ≤ 0.
All the data presented in this study were calculated from this subset data. The beta-diversity of the microbiome was calculated using Fast UniFrac interface [28] and visualized using principal coordinate analysis (PCoA). The Unifrac distance-based inter- and intra-dissimilarity depending on experimental groups was determined using the ANOSIM test.
성능/효과
Desulfovibrio abundance was found to be positively correlated with Cfp (complement factor properdin), a component of the innate immune system that has been reported to show upregulation upon ovariectomy [43]. Furthermore, A. muciniphila abundance showed a negative correlation with two genes, Pik3ca (phosphatidylinositol 3-kinase catalytic alpha polypeptide) and Lfg1 (insulin-like growth factor 1), but more correlation was observed with metabolic pathway genes (Cyp26b1, Nnmt, Pnpla3, and Ptgds) whose expression is related to a high-fat diet than with genes related to ovariectomy. With regard to Dorea species, although their proportion increased in the OVX-HD group, the gene-bacterial correlation was for genes of the metabolic pathways.
043). The OVX-HF group was characterized by increased abundance of Lactobacillus (LDA = 4.68, p-value = 0.05), Dorea (LDA = 3.56, p-value = 0.024), Akkermansia muciniphila (LDA = 4.37, p-value = 0.043), and Desulfovibrio species (LDA = 4.12, p-value = 0.05).
The obesity-related indices measured in this study revealed phenotypic similarities between the ovariectomized and high-fat diet groups. The final body weight and amount of adipose tissue in mice in the OVX, SHAM-HF, and OVX-HF groups were significantly increased relative to the SHAM group (Table 1). The highest weight gain was observed in the OVX-HF group, followed by the SHAM-HF and OVX groups.
The obesity-related indices measured in this study revealed phenotypic similarities between the ovariectomized and high-fat diet groups. The final body weight and amount of adipose tissue in mice in the OVX, SHAM-HF, and OVX-HF groups were significantly increased relative to the SHAM group (Table 1).
This phenomenon was in line with the microbiome data. The overall bacterial profiles showed a significant difference in the comparison of OVX with SHAM, but the bacterial profiles of SHAM_HF and OVX_HF were similar.
4). The result of the enrichment map test using KEGG pathways showed that 177 metabolic pathways differed in the OVX group compared with that in the SHAM control group. In particular, the gene expression of estrogen signaling pathways differed significantly in the OVX group compared with the SHAM control group.
animalis appeared to be specifically correlated with female estrogen metabolism. The results of this study indicate that menopausal obesity is characterized by marker species that differ from those of diet-induced obesity, and that these marker species show correlation with female hormone metabolism genes.
The experimental treatments had a large impact on the bacterial community structure. The similarities in the microbiome among samples were estimated based on weighted UniFrac distance, and the results of PCoA showed that the overall bacterial communities of the experimental groups were clearly differentiated from the control group (ANOSIM statistic R = 0.4509, p-value = 0.001) (Fig. 1). Remarkably, the differences in the microbiome caused by ovariectomy (red spots) were very similar to those caused by the high-fat diet (blue spots) (ANOSIM p > 0.
후속연구
animalis. The gene-bacterial correlation observed here suggests a possible role of B. animalis in female hormone regulation; however, further studies are required to confirm this possibility.
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