Answering the burning question: How can we computionally research the interactome of the urogentital biome?

Abstract

Urinary tract infection forms a significant disease burden for the female population, with 50 – 70% of women experiencing a UTI at least once in their lifetime. UTIs are commonly treated with the use of antibiotics. However, an increasing amount of UTIs are caused by antibiotic resistant bacterial species. It is therefore important to better understand the pathogenesis of UTI to identify new therapeutic targets which do not require the application of antibiotics. It has been well demonstrated that UTI in post-menopausal women occurs because of dysbiosis in the urogenital biome, i.e., the community of microbes residing in the urinary tract. Understanding how microbes of the urogenital biome interact with one another may allow us to gain insight into how changes in the urogenital microenvironment may led to dysbiosis. Here, I review the information currently known about UTI and discuss different computational methods through which the metabolic network of the urogenital biome can be studied, and microbial interaction patterns can be identified. By combining computational approaches with different focusses, we can gain a better understanding of the underlying mechanisms of the urogenital interactome.