Modeling systems-level regulation of host immune responses.
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.
Thakar
Juilee
J
Department of Physics, Pennsylvania State University, University Park, Pennsylvania, United States of America.
Pilione
Mylisa
M
Kirimanjeswara
Girish
G
Harvill
Eric T
ET
Albert
Réka
R
D000818:Animals; D001884:Bordetella / Q000276:immunology*; D001885:Bordetella Infections / Q000276:immunology* / Q000382:microbiology*; D003198:Computer Simulation; D005786:Gene Expression Regulation / Q000276:immunology*; D007113:Immunity, Innate / Q000276:immunology*; D007155:Immunologic Factors / Q000276:immunology*; D051379:Mice; D018448:Models, Immunological
D007155:Immunologic Factors