Dataset Information

Salmonella Modulates Metabolism during Growth under Conditions that Induce Expression of Virulence Genes

ABSTRACT: Salmonella enterica serovar Typhimurium (S. Typhimurium) is a facultative pathogen that uses complex mechanisms to invade and proliferate within mammalian host cells. To investigate possible contributions of metabolic processes to virulence in S. Typhimurium grown under conditions known to induce expression of virulence genes, we used a metabolomics-driven systems biology approach coupled with genome scale modeling. First, we identified distinct metabolite profiles associated with bacteria grown in either rich or virulence-inducing media and report the most comprehensive coverage of the S. Typhimurium metabolome to date. Second, we applied an omics-informed genome scale modeling analysis of the functional consequences of adaptive alterations in S. Typhimurium metabolism during growth under our conditions. Modeling efforts highlighted a decreased cellular capability to both produce and utilize intracellular amino acids during stationary phase culture in virulence conditions, despite significant abundance increases for these molecules as observed by our metabolomics measurements. Furthermore, analyses of omics data in the context of the metabolic model indicated rewiring of the metabolic network to support pathways associated with virulence. For example, cellular concentrations of polyamines were perturbed, as well as the predicted capacity for secretion and uptake.

INSTRUMENT(S): 5975C Series GC/MSD (Agilent)

SUBMITTER: Tom Metz

PROVIDER: MTBLS35 | MetaboLights | 2013-05-02

REPOSITORIES: MetaboLights

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Dataset's files

Source:

			Action	DRS
	MTBLS35	Other
	FILES	Other
	a_MTBLS35_salmonella.txt	Txt
	i_Investigation.txt	Txt
	m_MTBLS35_salmonella_modulates_metabolism_during_growth_under_conditions_that_induce_expression_of_virulence_genes_metabolite_profiling_mass_spectrometry_v2_maf.tsv	Tabular

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Publications

Salmonella modulates metabolism during growth under conditions that induce expression of virulence genes.

Kim Young-Mo YM Schmidt Brian J BJ Kidwai Afshan S AS Jones Marcus B MB Deatherage Kaiser Brooke L BL Brewer Heather M HM Mitchell Hugh D HD Palsson Bernhard O BO McDermott Jason E JE Heffron Fred F Smith Richard D RD Peterson Scott N SN Ansong Charles C Hyduke Daniel R DR Metz Thomas O TO Adkins Joshua N JN

Molecular bioSystems 20130405 6

Salmonella enterica serovar Typhimurium (S. Typhimurium) is a facultative pathogen that uses complex mechanisms to invade and proliferate within mammalian host cells. To investigate possible contributions of metabolic processes to virulence in S. Typhimurium grown under conditions known to induce expression of virulence genes, we used a metabolomics-driven systems biology approach coupled with genome-scale modeling. First, we identified distinct metabolite profiles associated with bacteria grown ...[more]

PMID: 23559334

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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. 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.