Dataset Information

Teusink2006 - Genome-scale metabolic network of Lactobacillus plantarum (iBT721)

ABSTRACT: Teusink2006 - Genome-scale metabolic network of Lactobacillus plantarum (iBT721) This model is described in the article: Analysis of growth of Lactobacillus plantarum WCFS1 on a complex medium using a genome-scale metabolic model. Teusink B, Wiersma A, Molenaar D, Francke C, de Vos WM, Siezen RJ, Smid EJ. J. Biol. Chem. 2006 Dec; 281(52): 40041-40048 Abstract: A genome-scale metabolic model of the lactic acid bacterium Lactobacillus plantarum WCFS1 was constructed based on genomic content and experimental data. The complete model includes 721 genes, 643 reactions, and 531 metabolites. Different stoichiometric modeling techniques were used for interpretation of complex fermentation data, as L. plantarum is adapted to nutrient-rich environments and only grows in media supplemented with vitamins and amino acids. (i) Based on experimental input and output fluxes, maximal ATP production was estimated and related to growth rate. (ii) Optimization of ATP production further identified amino acid catabolic pathways that were not previously associated with free-energy metabolism. (iii) Genome-scale elementary flux mode analysis identified 28 potential futile cycles. (iv) Flux variability analysis supplemented the elementary mode analysis in identifying parallel pathways, e.g. pathways with identical end products but different co-factor usage. Strongly increased flexibility in the metabolic network was observed when strict coupling between catabolic ATP production and anabolic consumption was relaxed. These results illustrate how a genome-scale metabolic model and associated constraint-based modeling techniques can be used to analyze the physiology of growth on a complex medium rather than a minimal salts medium. However, optimization of biomass formation using the Flux Balance Analysis approach, reported to successfully predict growth rate and by product formation in Escherichia coli and Saccharomyces cerevisiae, predicted too high biomass yields that were incompatible with the observed lactate production. The reason is that this approach assumes optimal efficiency of substrate to biomass conversion, and can therefore not predict the metabolically inefficient lactate formation. This model is hosted on BioModels Database and identified by: MODEL1507180045. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

SUBMITTER: Nicolas Le Novère

PROVIDER: MODEL1507180045 | BioModels | 2015-07-30

REPOSITORIES: BioModels

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Analysis of growth of Lactobacillus plantarum WCFS1 on a complex medium using a genome-scale metabolic model.

Teusink Bas B Wiersma Anne A Molenaar Douwe D Francke Christof C de Vos Willem M WM Siezen Roland J RJ Smid Eddy J EJ

The Journal of biological chemistry 20061024 52

A genome-scale metabolic model of the lactic acid bacterium Lactobacillus plantarum WCFS1 was constructed based on genomic content and experimental data. The complete model includes 721 genes, 643 reactions, and 531 metabolites. Different stoichiometric modeling techniques were used for interpretation of complex fermentation data, as L. plantarum is adapted to nutrient-rich environments and only grows in media supplemented with vitamins and amino acids. (i) Based on experimental input and output ...[more]

PMID: 17062565

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Project description:Background: Lactobacillus plantarum is found in a variety of fermented foods and as such, consumed for centuries. Some strains are natural inhabitants of the human gastro-intestinal tract and like other Lactobacillus species, L. plantarum has been extensively studied for its immunomodulatory properties and its putative health-promoting effects (probiotic). Being the first line of host defense intestinal epithelial cells (IEC) are key players in the recognition and initiation of responses to gut microorganisms. Results: Using high-density oligonucleotide microarrays we examined the gene expression profiles of differentiated Caco-2 cells exposed to various doses of L. plantarum. In addition, the effects were correlated to monolayer permeability studies and measurement of lactic acid production. A transcriptional dose-dependent IEC response to L. plantarum was found. Incubation of Caco-2 with a low bacterial dose induced a specific response, not due to cytotoxicity or production of lactic acid, including modulation of cell cycle and cell signaling functions. Exposure of Caco-2 cells to larger amounts of bacteria, accompanied by the production of lactic acid and glucose depletion, provoked increased permeability and supposed non-specific defense responses. Conclusions: These results suggest that IEC are able to sense and react to the presence of gut bacteria. This study provides the first description of global transcriptional response of human IEC to a commensal lactic acid bacterium, and it shows the importance of choosing physiological bacterial doses to prevent the observation of non-specific host reactions. Caco-2 cells were exposed for 10h to Lactobacillus. Fourteen samples are analyzed: 4 control Caco-2, 4 Caco-2 exposed to a low dose (10) of Lactobacillus, 4 Caco-2 exposed to a medium dose (100) of Lactobacillus, 2 Caco-2 exposed to a high dose (1000) of Lactobacillus. All 14 RNA samples are labeled with Cy5 and hybridized to a common reference (undifferentiated Caco-2, untreated) RNA labeled with Cy3