Ontology highlight
ABSTRACT:
PROVIDER: PRJNA857681 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR20749146_1.fastq.gz | Fastqsanger.gz | |||
| SRR20749146_2.fastq.gz | Fastqsanger.gz | |||
| SRR20749147_1.fastq.gz | Fastqsanger.gz | |||
| SRR20749147_2.fastq.gz | Fastqsanger.gz | |||
| SRR20749148_1.fastq.gz | Fastqsanger.gz |
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Project description:Becker2005 - Genome-scale metabolic network
of Staphylococcus aureus (iSB619)
This model is described in the article:
Genome-scale reconstruction
of the metabolic network in Staphylococcus aureus N315: an
initial draft to the two-dimensional annotation.
Becker SA, Palsson BØ.
BMC Microbiol. 2005; 5: 8
Abstract:
BACKGROUND: Several strains of bacteria have sequenced and
annotated genomes, which have been used in conjunction with
biochemical and physiological data to reconstruct genome-scale
metabolic networks. Such reconstruction amounts to a
two-dimensional annotation of the genome. These networks have
been analyzed with a constraint-based formalism and a variety
of biologically meaningful results have emerged. Staphylococcus
aureus is a pathogenic bacterium that has evolved resistance to
many antibiotics, representing a significant health care
concern. We present the first manually curated elementally and
charge balanced genome-scale reconstruction and model of S.
aureus' metabolic networks and compute some of its properties.
RESULTS: We reconstructed a genome-scale metabolic network of
S. aureus strain N315. This reconstruction, termed iSB619,
consists of 619 genes that catalyze 640 metabolic reactions.
For 91% of the reactions, open reading frames are explicitly
linked to proteins and to the reaction. All but three of the
metabolic reactions are both charge and elementally balanced.
The reaction list is the most complete to date for this
pathogen. When the capabilities of the reconstructed network
were analyzed in the context of maximal growth, we formed
hypotheses regarding growth requirements, the efficiency of
growth on different carbon sources, and potential drug targets.
These hypotheses can be tested experimentally and the data
gathered can be used to improve subsequent versions of the
reconstruction. CONCLUSION: iSB619 represents comprehensive
biochemically and genetically structured information about the
metabolism of S. aureus to date. The reconstructed metabolic
network can be used to predict cellular phenotypes and thus
advance our understanding of a troublesome pathogen.
This model is hosted on
BioModels Database
and identified by:
MODEL1507180070.
To cite BioModels Database, please use:
BioModels Database:
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quantitative kinetic models.
To the extent possible under law, all copyright and related or
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