Niche-specific metabolic phenotypes can be used to identify antimicrobial targets in pathogens.

Bacterial pathogens pose a major risk to human health, leading to tens of millions of deaths annually and significant global economic losses. While bacterial infections are typically treated with antibiotic regimens, there has been a rapid emergence of antimicrobial resistant (AMR) bacterial strains due to antibiotic overuse. Because of this, treatment of infections with traditional antimicrobials has become increasingly difficult, necessitating the development of innovative approaches for deeply understanding pathogen function.

Psychosocial impact of recurrent urogenital infections: a review.

Recurrent urogenital infections such as bacterial vaginosis, vulvovaginal candidiasis, and urinary tract infections have a high prevalence and pronounced psychosocial impact. However, no review has compared the psychosocial impacts across infection types. This narrative review discusses the impact of common recurrent urogenital infections on psychosocial aspects, including quality of life, stress, mental health, sexual health, work productivity, race and ethnicity, and satisfaction of medical care.

Metabolic Network Models of the Pangenome Identify Key Interactions with the Vaginal Environment.

is the primary pathogenic bacterial genus present in the polymicrobial condition known as bacterial vaginosis (BV). Despite BV's high prevalence and associated chronic and acute women's health impacts, the pangenome is largely uncharacterized at both the genetic and functional metabolic levels. Here, we used genome-scale metabolic models to characterize the pangenome metabolic content.

New perspectives into the vaginal microbiome with systems biology.

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.

Mechanistic models of microbial community metabolism.

Microbial communities affect many facets of human health and well-being. Naturally occurring bacteria, whether in nature or the human body, rarely exist in isolation. A deeper understanding of the metabolic functions of these communities is now possible with emerging computational models.