title: Genome-scale reconstruction of metabolic networks of Lactobacillus casei ATCC 334 and 12A.
abstract: Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications.
authors.affiliation: Department of Food Science, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
authors.forename: Elena
authors.initials: E
authors.lastname: Vinay-Lara
authors.affiliation: Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
authors.forename: Joshua J
authors.initials: JJ
authors.lastname: Hamilton
authors.affiliation: DuPont Nutrition and Health, Madison, Wisconsin, United States of America.
authors.forename: Buffy
authors.initials: B
authors.lastname: Stahl
authors.affiliation: Utah State University Department of Nutrition, Dietetics, and Food Sciences, Logan, Utah, United States of America.
authors.forename: Jeff R
authors.initials: JR
authors.lastname: Broadbent
authors.affiliation: Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
authors.forename: Jennifer L
authors.initials: JL
authors.lastname: Reed
authors.affiliation: Department of Food Science, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
authors.forename: James L
authors.initials: JL
authors.lastname: Steele
mesh_terms: D050260:Carbohydrate Metabolism; D019295:Computational Biology; D017353:Gene Deletion; D016680:Genome, Bacterial; D055106:Genome-Wide Association Study; D059014:High-Throughput Nucleotide Sequencing; D007780:Lacticaseibacillus casei / Q000235:genetics* / Q000378:metabolism*; D053858:Metabolic Networks and Pathways; D058977:Molecular Sequence Annotation; D008969:Molecular Sequence Data