New perspectives into the vaginal microbiome with systems biology. Issue 4 (April 2023)

• Record Type: Journal Article
• Authors: Lee, Christina Y.; Dillard, Lillian R.; Papin, Jason A.; Arnold, Kelly B.
• Is Part Of: Trends in microbiology. Volume 31:Issue 4(2023)
• Page Start: 356
• Page End: 368
• Publication Date: 2023-04
• Subjects: vaginal microbiome -- systems biology; Microbiology -- Periodicals; Infection -- Periodicals; Virulence (Microbiology) -- Periodicals; Infection -- Periodicals; Microbiology -- Periodicals; Virulence -- Periodicals; Microbiologie -- Périodiques; Infection -- Périodiques; Virulence (Microbiologie) -- Périodiques; Infection; Microbiology; Virulence (Microbiology); 579
• DOI: 10.1016/j.tim.2022.09.011
• Languages: English
• ISSNs: 0966-842X

Abstract

Abstract: The vaginal microbiome (VMB) is critical to female reproductive health; however, the mechanisms associated with optimal and non-optimal states remain poorly understood due to the complex community structure and dynamic nature. Quantitative systems biology techniques applied to the VMB have improved understanding of community composition and function using primarily statistical methods. In contrast, fewer mechanistic models that use a priori knowledge of VMB features to develop predictive models have been implemented despite their use for microbiomes at other sites, including the gastrointestinal tract. Here, we explore systems biology approaches that have been applied in the VMB, highlighting successful techniques and discussing new directions that hold promise for improving understanding of health and disease. Highlights: The vaginal microbiome (VMB) is a key contributor to women's health, but the exact definition and dynamics of an optimal VMB are not yet clear. The recent emergence of rich data sets detailing the composition and characteristics of the VMB highlight the need for systems biology approaches to unravel the complex microbial dynamics involved in health and disease. Statistical data-driven modeling via dimensionality reduction has provided a structure for defining community state types and revealed cornerstone species and metabolism associated with vaginal health. Mechanistic modeling has the potential to define community dynamics within the VMB and link them to variability in disease-related outcomes. Multi-omic integration methodologies previously applied in the gut microbiome, as well as novel approaches, hold promise for future understanding of vaginal health and therapeutic efficacy.