Research article

Constraint-based analysis of metabolic capacity of Salmonella typhimurium during host-pathogen interaction

Anu Raghunathan^{* 1} , Jennifer Reed^{* 2} , Sookil Shin¹ , Bernhard Palsson³ and Simon Daefler¹

¹Department of Infectious Diseases, Mount Sinai School of Medicine, New York, USA

²Department of Chemical and Biological Engineering, University of Wisconsin, Madison, USA

³Department of Bioengineering, University of California San Diego, San Diego, USA

author email corresponding author email* Contributed equally

BMC Systems Biology 2009, 3:38doi:10.1186/1752-0509-3-38

Published:	8 April 2009

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.