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Dillard, L. R.

Publications and source records attributed to Dillard, L. R..

2 recordsLinked to original sources

Physiological niche informs evolution of metabolic function and corresponding drug targets of pathobionts

Treatment of infections with traditional antimicrobials has become difficult due to the growing antimicrobial resistance crisis, necessitating the development of innovative approaches for deeply understanding pathogen function. Here, we generated a collection of genome-scale metabolic network reconstructions to gain insight into evolutionary drivers of metabolic function. We determined physiological location is a major driver of evolution of metabolic function. We observed that stomach-associated pathobionts had the most unique metabolic phenotypes and identified three essential genes unique to stomach pathobionts across diverse phylogenetic relationships. We demonstrate that inhibition of one such gene, thyX, inhibited growth of stomach- specific pathobionts exclusively, indicating possible physiological niche-specific targeting. This pioneering approach is the first step to using unique metabolic signatures to inform targeted antimicrobial therapies. One sentence summaryA data-driven approach to drug target discovery through metabolic signatures of diverse pathogens conserved across body-sites.

systems biology↗

Metabolic network models of Gardnerella pangenome identify interactions in the vaginal environment

Gardnerella is the primary pathogenic bacterial genus present in the polymicrobial infection known as bacterial vaginosis (BV). Despite BVs high prevalence and associated chronic and acute womens health impacts, the Gardnerella pangenome is largely uncharacterized at both the genetic and functional metabolic level. Here, we used genome scale metabolic models to characterize in silico the Gardnerella pangenome metabolic content and assessed metabolic functional capacity within a BV positive cervicovaginal fluid context. Metabolic capacity varied widely across the pangenome, with 38.15% of all reactions as core to the genus, compared to 49.6% of reactions identified as unique to a smaller subset of species. Four genes - gpsA, fas, suhB, psd - were identified as core essential genes, critical for in silico metabolic function of all analyzed bacterial species in the Gardnerella genus. Further understanding of these core essential metabolic functions could inform novel therapeutic strategies to treat BV. These data represent the first metabolic modelling of the Gardnerella pangenome and illustrate strain-specific interactions with the vaginal metabolic environment across the pangenome.

systems biology↗