Dataset Information

A pathogen-specific isotope tracing approach reveals metabolic activities and fluxes of intracellular Salmonella

ABSTRACT:

Pathogenic bacteria proliferating inside mammalian host cells need to rapidly adapt to the intracellular environment. How they achieve this and scavenge essential nutrients from the host has been an open question due to the difficulties in distinguishing between bacterial and host metabolites in situ. Here we capitalized on the inability of mammalian cells to metabolize mannitol to develop a stable isotopic labeling approach to track Salmonella enterica metabolites during intracellular proliferation in host macrophage and epithelial cells. By measuring label incorporation into Salmonella metabolites with liquid chromatography-mass spectrometry, and combining it with metabolic modeling, we identify relevant carbon sources used by Salmonella, uncover routes of their metabolization, and quantify relative reaction rates in central carbon metabolism. Our results underline the importance of the Entner-Doudoroff pathway and the phosphoenolpyruvate carboxylase for intracellularly proliferating Salmonella. More broadly, our metabolic labeling strategy opens novel avenues for understanding the metabolism of pathogens inside host cells.

INSTRUMENT(S): Liquid Chromatography MS - negative - hilic

SUBMITTER: Karin Mitosch

PROVIDER: MTBLS1275 | MetaboLights | 2023-08-02

REPOSITORIES: MetaboLights

ACCESS DATA

Similar Datasets

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.

Dataset Information

A pathogen-specific isotope tracing approach reveals metabolic activities and fluxes of intracellular Salmonella

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure