A systems perspective of host-pathogen interactions: predicting disease outcome in tuberculosis
Autor: | Ashwini G. Bhat, Nagasuma Chandra, Karthik Raman |
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Rok vydání: | 2010 |
Předmět: |
Virulence Factors
Disease Computational biology Biology Phagolysosome Interactome Models Biological Mycobacterium tuberculosis Gene Knockout Techniques Immune System Phenomena Immune system Interaction network Humans Tuberculosis Computer Simulation Molecular Biology Pathogen Systems Biology biology.organism_classification Boolean network Immunology Host-Pathogen Interactions Cytokines Biotechnology Signal Transduction |
Zdroj: | Molecular bioSystems. 6(3) |
ISSN: | 1742-2051 |
Popis: | The complex web of interactions between the host immune system and the pathogen determines the outcome of any infection. A computational model of this interaction network, which encodes complex interplay among host and bacterial components, forms a useful basis for improving the understanding of pathogenesis, in filling knowledge gaps and consequently to identify strategies to counter the disease. We have built an extensive model of the Mycobacterium tuberculosis host-pathogen interactome, consisting of 75 nodes corresponding to host and pathogen molecules, cells, cellular states or processes. Vaccination effects, clearance efficiencies due to drugs and growth rates have also been encoded in the model. The system is modelled as a Boolean network. Virtual deletion experiments, multiple parameter scans and analysis of the system's response to perturbations, indicate that disabling processes such as phagocytosis and phagolysosome fusion or cytokines such as TNF-alpha and IFN-gamma, greatly impaired bacterial clearance, while removing cytokines such as IL-10 alongside bacterial defence proteins such as SapM greatly favour clearance. Simulations indicate a high propensity of the pathogen to persist under different conditions. |
Databáze: | OpenAIRE |
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