Gut microbiome responds to alteration in female sex hormone status and exacerbates metabolic dysfunction

ABSTRACT

Women are at significantly greater risk of metabolic dysfunction after menopause, which subsequently leads to numerous chronic illnesses. The gut microbiome is associated with obesity and metabolic dysfunction, but its interaction with female sex hormone status and the resulting impact on host metabolism remains unclear. Herein, we characterized inflammatory and metabolic phenotypes as well as the gut microbiome associated with ovariectomy and high-fat diet feeding, compared to gonadal intact and low-fat diet controls. We then performed fecal microbiota transplantation (FMT) using gnotobiotic mice to identify the impact of ovariectomy-associated gut microbiome on inflammatory and metabolic outcomes. We demonstrated that ovariectomy led to greater gastrointestinal permeability and inflammation of the gut and metabolic organs, and that a high-fat diet exacerbated these phenotypes. Ovariectomy also led to alteration of the gut microbiome, including greater fecal β-glucuronidase activity. However, differential changes in the gut microbiome only occurred when fed a low-fat diet, not the high-fat diet. Gnotobiotic mice that received the gut microbiome from ovariectomized mice fed the low-fat diet had greater weight gain and hepatic gene expression related to metabolic dysfunction and inflammation than those that received intact sham control-associated microbiome. These results indicate that the gut microbiome responds to alterations in female sex hormone status and contributes to metabolic dysfunction. Identifying and developing gut microbiome-targeted modulators to regulate sex hormones may be useful therapeutically in remediating menopause-related diseases.

KEYWORDS:

• Gut microbiota
• estrogen
• ovarian deficiency
• menopause
• metabolic health

Acknowledgments

We thank Alvaro Hernandez, PhD and Chris Wright from the DNA Services of the Roy J. Carver Biotechnology Center at the University of Illinois for expertise and help with the Mi-Seq Illumina sequencing. We thank Mark Band, PhD from the Functional Genomics Unit of the Roy J. Carver Biotechnology Center at the University of Illinois for expertise and help with the Fluidigm Access Array and Expression Array assays. We thank George Fahey, Jr, PhD, Maria Godoy, PhD, Michael Miller, PhD, and Victoria Vieira-Potter, PhD for their advice on data analysis and interpretations.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contributions

T.-W. L. C., K. S. S., and F. E. R. conceived the project; T.-W. L. C., C.-Y. L., E. R. N., A. P. B., S. J. P., B. R. L., M. A. W. conducted the research; T.-W. L. C., A. P. B., M. A. W., M. R. R., F. E. R., and K.S.S. interpreted the results; T.-W. L. C. and A. P. B. prepared figures; T.-W. L. C., K. S. S., and F.E.R. wrote the manuscript. All authors have read, edited, and approved the final manuscript.

Data availability statement

The raw sequences that support the findings of this study are available at the NCBI sequences read archive at https://www.ncbi.nlm.nih.gov/sra/, reference number BioProject ID PRJNA994490.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/19490976.2023.2295429.

Additional information

Funding

This work was supported by the National Institutes of Health, under Ruth L. Kirschstein National Research Service Award T32 HL 007936 from the National Heart Lung and Blood Institute to the University of Wisconsin-Madison Cardiovascular Research Center (to T.-W. L. C.) and under grants HL144651 (to F.E.R), HL148577 (to F.E.R).