Insight into human alveolar macrophage and M. tuberculosis interactions via metabolic reconstructions.

TitleInsight into human alveolar macrophage and M. tuberculosis interactions via metabolic reconstructions.
Publication TypeJournal Article
Year of Publication2010
AuthorsBordbar A, Lewis NE, Schellenberger J, Palsson BØ, Jamshidi N
JournalMolecular systems biology
PubMed Date2010 Oct 19
KeywordsAdenosine Triphosphate, Computational Biology, Computer Simulation, Databases, Genetic, Genes, Bacterial, Host-Pathogen Interactions, Humans, Macrophages, Alveolar, Metabolic Networks and Pathways, Models, Biological, Monte Carlo Method, Mycobacterium tuberculosis, Nitric Oxide

Metabolic coupling of Mycobacterium tuberculosis to its host is foundational to its pathogenesis. Computational genome-scale metabolic models have shown utility in integrating -omic as well as physiologic data for systemic, mechanistic analysis of metabolism. To date, integrative analysis of host-pathogen interactions using in silico mass-balanced, genome-scale models has not been performed. We, therefore, constructed a cell-specific alveolar macrophage model, iAB-AMØ-1410, from the global human metabolic reconstruction, Recon 1. The model successfully predicted experimentally verified ATP and nitric oxide production rates in macrophages. This model was then integrated with an M. tuberculosis H37Rv model, iNJ661, to build an integrated host-pathogen genome-scale reconstruction, iAB-AMØ-1410-Mt-661. The integrated host-pathogen network enables simulation of the metabolic changes during infection. The resulting reaction activity and gene essentiality targets of the integrated model represent an altered infectious state. High-throughput data from infected macrophages were mapped onto the host-pathogen network and were able to describe three distinct pathological states. Integrated host-pathogen reconstructions thus form a foundation upon which understanding the biology and pathophysiology of infections can be developed.

Alternate JournalMol. Syst. Biol.
PubMed ID20959820



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