Metabolic modeling predicts specific gut bacteria as key determinants for Candida albicans colonization levels.

ABSTRACT: Candida albicans is a leading cause of life-threatening hospital-acquired infections and can lead to Candidemia with sepsis-like symptoms and high mortality rates. We reconstructed a genome-scale C. albicans metabolic model to investigate bacterial-fungal metabolic interactions in the gut as determinants of fungal abundance. We optimized the predictive capacity of our model using wild type and mutant C. albicans growth data and used it for in silico metabolic interaction predictions. Our analysis of more than 900 paired fungal-bacterial metabolic models predicted key gut bacterial species modulating C. albicans colonization levels. Among the studied microbes, Alistipes putredinis was predicted to negatively affect C. albicans levels. We confirmed these findings by metagenomic sequencing of

SUBMITTER: Mirhakkak MH 

PROVIDER: S-EPMC8115155 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature