Mus musculus
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA255772 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR1521510_1.fastq.gz | Fastqsanger.gz | |||
| SRR1521510_2.fastq.gz | Fastqsanger.gz | |||
| SRR1521511_1.fastq.gz | Fastqsanger.gz | |||
| SRR1521511_2.fastq.gz | Fastqsanger.gz | |||
| SRR1521512_1.fastq.gz | Fastqsanger.gz |
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Project description:Raghunathan2009 - Genome-scale metabolic
network of Salmonella typhimurium (iRR1083)
This model is described in the article:
Constraint-based analysis of
metabolic capacity of Salmonella typhimurium during
host-pathogen interaction.
Raghunathan A, Reed J, Shin S,
Palsson B, Daefler S.
BMC Syst Biol 2009; 3: 38
Abstract:
BACKGROUND: Infections with Salmonella cause significant
morbidity and mortality worldwide. Replication of Salmonella
typhimurium inside its host cell is a model system for studying
the pathogenesis of intracellular bacterial infections.
Genome-scale modeling of bacterial metabolic networks provides
a powerful tool to identify and analyze pathways required for
successful intracellular replication during host-pathogen
interaction. RESULTS: We have developed and validated a
genome-scale metabolic network of Salmonella typhimurium LT2
(iRR1083). This model accounts for 1,083 genes that encode
proteins catalyzing 1,087 unique metabolic and transport
reactions in the bacterium. We employed flux balance analysis
and in silico gene essentiality analysis to investigate growth
under a wide range of conditions that mimic in vitro and host
cell environments. Gene expression profiling of S. typhimurium
isolated from macrophage cell lines was used to constrain the
model to predict metabolic pathways that are likely to be
operational during infection. CONCLUSION: Our analysis suggests
that there is a robust minimal set of metabolic pathways that
is required for successful replication of Salmonella inside the
host cell. This model also serves as platform for the
integration of high-throughput data. Its computational power
allows identification of networked metabolic pathways and
generation of hypotheses about metabolism during infection,
which might be used for the rational design of novel
antibiotics or vaccine strains.
This model is hosted on
BioModels Database
and identified by:
MODEL1507180058.
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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
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