Modeling Systems-Level Regulation of Host Immune Responses
| Autor: | Eric T. Harvill, Girish S. Kirimanjeswara, Mylisa R. Pilione, Réka Albert, Juilee Thakar |
|---|---|
| Rok vydání: | 2005 |
| Předmět: |
Bordetella
Secondary infection Immunology Virulence Computational biology Biology Mice 03 medical and health sciences Cellular and Molecular Neuroscience 0302 clinical medicine Immune system Genetics Animals Immunologic Factors Computer Simulation lcsh:QH301-705.5 Molecular Biology Ecology Evolution Behavior and Systematics Bordetella Infections 030304 developmental biology Regulation of gene expression 0303 health sciences Ecology 030302 biochemistry & molecular biology Models Immunological Computational Biology Respiratory infection Mus (Mouse) Immunity Innate Complement system Eubacteria Infectious Diseases Gene Expression Regulation lcsh:Biology (General) Computational Theory and Mathematics Modeling and Simulation biology.protein Host adaptation Antibody Research Article 030215 immunology |
| Zdroj: | PLoS Computational Biology, Vol 3, Iss 6, p e109 (2007) PLoS Computational Biology |
| ISSN: | 1553-7358 1553-734X |
| Popis: | Many pathogens are able to manipulate the signaling pathways responsible for the generation of host immune responses. Here we examine and model a respiratory infection system in which disruption of host immune functions or of bacterial factors changes the dynamics of the infection. We synthesize the network of interactions between host immune components and two closely related bacteria in the genus Bordetellae. We incorporate existing experimental information on the timing of immune regulatory events into a discrete dynamic model, and verify the model by comparing the effects of simulated disruptions to the experimental outcome of knockout mutations. Our model indicates that the infection time course of both Bordetellae can be separated into three distinct phases based on the most active immune processes. We compare and discuss the effect of the species-specific virulence factors on disrupting the immune response during their infection of naive, antibody-treated, diseased, or convalescent hosts. Our model offers predictions regarding cytokine regulation, key immune components, and clearance of secondary infections; we experimentally validate two of these predictions. This type of modeling provides new insights into the virulence, pathogenesis, and host adaptation of disease-causing microorganisms and allows systems-level analysis that is not always possible using traditional methods. Author Summary The immune response is a complex network of processes activated in a host upon infection. Pathogens seek to disrupt or evade these processes to ensure their own survival and proliferation. This article provides a systems-level analysis of the immune response against two related bacterial species in the Bordetella genus, B. bronchiseptica and B. pertussis. B. pertussis, the causative agent of whooping cough, has lost many of the virulence factors of its B. bronchiseptica–like progenitor, and is using different strategies for the modulation of the immune system. We have synthesized two separate network models for the interaction of these pathogens with their hosts. Each network is then translated into a predictive dynamic model and is validated by comparison with available experimental data. The model offers predictions regarding cytokine regulation and the effects of perturbations of the immune system, as well as the time course of infections in hosts that had previously encountered the pathogens. We experimentally validate the prediction that convalescent hosts can rapidly clear both pathogens, while antibody transfer cannot substantially reduce the duration of a B. pertussis infection. This type of modeling provides new insights into the virulence, pathogenesis, and host adaptation of disease-causing microorganisms and can be readily extended to other pathogens. |
| Databáze: | OpenAIRE |
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