Oliveira2005 - Genome-scale metabolic network of Lactococcus lactis (iAO358)
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ABSTRACT:
Oliveira2005 - Genome-scale metabolic network
of Lactococcus lactis (iAO358)
This model is described in the article:
Modeling Lactococcus lactis
using a genome-scale flux model.
Oliveira AP, Nielsen J, Förster
J.
BMC Microbiol. 2005; 5: 39
Abstract:
BACKGROUND: Genome-scale flux models are useful tools to
represent and analyze microbial metabolism. In this work we
reconstructed the metabolic network of the lactic acid bacteria
Lactococcus lactis and developed a genome-scale flux model able
to simulate and analyze network capabilities and whole-cell
function under aerobic and anaerobic continuous cultures. Flux
balance analysis (FBA) and minimization of metabolic adjustment
(MOMA) were used as modeling frameworks. RESULTS: The metabolic
network was reconstructed using the annotated genome sequence
from L. lactis ssp. lactis IL1403 together with physiological
and biochemical information. The established network comprised
a total of 621 reactions and 509 metabolites, representing the
overall metabolism of L. lactis. Experimental data reported in
the literature was used to fit the model to phenotypic
observations. Regulatory constraints had to be included to
simulate certain metabolic features, such as the shift from
homo to heterolactic fermentation. A minimal medium for in
silico growth was identified, indicating the requirement of
four amino acids in addition to a sugar. Remarkably, de novo
biosynthesis of four other amino acids was observed even when
all amino acids were supplied, which is in good agreement with
experimental observations. Additionally, enhanced metabolic
engineering strategies for improved diacetyl producing strains
were designed. CONCLUSION: The L. lactis metabolic network can
now be used for a better understanding of lactococcal metabolic
capabilities and potential, for the design of enhanced
metabolic engineering strategies and for integration with other
types of 'omic' data, to assist in finding new information on
cellular organization and function.
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MODEL1507180014.
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SUBMITTER: Nicolas Le Novère
PROVIDER: MODEL1507180014 | BioModels | 2015-07-30
REPOSITORIES: BioModels
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