What is it about?

The vagina and cervix (cervicovaginal microenvironment) contain a complex ecosystem that serves as an interface between human cells and bacteria that can be harmful (pathogens) or peacefully coexist (commensals). Dissecting these host-microbe interactions can be challenging, yet omics technologies provide a powerful tool to shed light on the structure of cervicovaginal microenvironment in health and disease. This paper employs a multi-omics approach and examines relationships between human papillomavirus, vaginal bacteria, and host defense and immune responses in women at different stages of cervical dysplasia or cancer.

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Why is it important?

This work provides new mechanistic insights by linking specific metabolites and immune mediators with resident bacterial communities and cervical disease. We also learned that the metabolome was highly predictive of the local microenvironment, such as genital inflammation and the microbiome. Yet, the integration of multi-omics allowed us to yield mechanistic insights that would not have been possible by single omics approaches. Further improvement of multi-omics data integration methods will advance our ability to pinpoint constituents of the human microbiome contributing to health or disease in the female reproductive tract and beyond.


This study wouldn’t be possible without our long-standing collaborators and experts in bioinformatics and gynecologic oncology who we are thankful to work with. In this article, using clinical specimens and machine learning, we discovered interconnections between vaginal microbes and pro-oncogenic metabolites, which gave us a deeper understanding of clinical relevance of the vaginal microbiome in HPV infection and cervical cancer. This study also encouraged me to further investigate how specific vaginal microorganisms, such as Sneathia, impact women’s health outcomes.

Paweł Łaniewski
University of Arizona

Read the Original

This page is a summary of: Multi-omics data integration reveals metabolome as the top predictor of the cervicovaginal microenvironment, PLoS Computational Biology, February 2022, PLOS, DOI: 10.1371/journal.pcbi.1009876.
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