Using genome-scale metabolic models to compare serovars of the foodborne pathogen Listeria monocytogenes.

ABSTRACT: Listeria monocytogenes is a microorganism of great concern for the food industry and the cause of human foodborne disease. Therefore, novel methods of control are needed, and systems biology is one such approach to identify them. Using a combination of computational techniques and laboratory methods, genome-scale metabolic models (GEMs) can be created, validated, and used to simulate growth environments and discern metabolic capabilities of microbes of interest, including L. monocytogenes. The objective of the work presented here was to generate GEMs for six different strains of L. monocytogenes, and to both qualitatively and quantitatively validate these GEMs with experimental data to examine the diversity of metabolic capabilities of numerous strains from the three different serovar grou

SUBMITTER: Metz ZP 

PROVIDER: S-EPMC6012718 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature