Transcriptome-guided parsimonious flux analysis improves predictions with metabolic networks in complex environments.

ABSTRACT: The metabolic responses of bacteria to dynamic extracellular conditions drives not only the behavior of single species, but also entire communities of microbes. Over the last decade, genome-scale metabolic network reconstructions have assisted in our appreciation of important metabolic determinants of bacterial physiology. These network models have been a powerful force in understanding the metabolic capacity that species may utilize in order to succeed in an environment. Increasingly, an understanding of context-specific metabolism is critical for elucidating metabolic drivers of larger phenotypes and disease. However, previous approaches to use network models in concert with omics data to better characterize experimental systems have met challenges due to assumptions necessary by the var

SUBMITTER: Jenior ML 

PROVIDER: S-EPMC7188308 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature