Endometriosis is a pathological condition of the female reproductive tract characterized by the existence of endometrium-like tissue at ectopic sites, affecting 10% of women between the age 15 and 49 in the USA. However, currently there is no reliable non-invasive method to detect the presence of endometriosis without surgery and many women find hormonal therapy and surgery as ineffective in avoiding the recurrences. There is a lack of knowledge on the etiology and the factors that contribute to the development of endometriosis. A growing body of recent evidence suggests an association between gut microbiota and endometriosis pathophysiology. However, the direct impact of microbiota and microbiota-derived metabolites on the endometriosis disease progression is largely unknown. To understand the causal role of gut microbiota and endometriosis, we have implemented a novel model using antibiotic-induced microbiota-depleted (MD) mice to investigate the endometriosis disease progression. Interestingly, we found that MD mice showed reduced endometriotic lesion growth and, the transplantation of gut microbiota by oral gavage of feces from mice with endometriosis rescued the endometriotic lesion growth. Additionally, using germ-free donor mice, we indicated that the uterine microbiota is dispensable for endometriotic lesion growth in mice. Furthermore, we showed that gut microbiota modulates immune cell populations in the peritoneum of lesions-bearing mice. Finally, we found a novel signature of microbiota-derived metabolites that were significantly altered in feces of mice with endometriosis. Finally, we found one the altered metabolite, quinic acid promoted the survival of endometriotic epithelial cells in vitro and lesion growth in vivo, suggesting the disease-promoting potential of microbiota-derived metabolites. In summary, these data suggest that gut microbiota and microbiota-derived metabolome contribute to lesion growth in mice, possibly through immune cell adaptations. Of translational significance, these findings will aid in designing non-invasive diagnostics using stool metabolites for endometriosis.
© 2023. The Author(s).