title: A spatial model of the efficiency of T cell search in the influenza-infected lung.
abstract: Emerging strains of influenza, such as avian H5N1 and 2009 pandemic H1N1, are more virulent than seasonal H1N1 influenza, yet the underlying mechanisms for these differences are not well understood. Subtle differences in how a given strain interacts with the immune system are likely a key factor in determining virulence. One aspect of the interaction is the ability of T cells to locate the foci of the infection in time to prevent uncontrolled expansion. Here, we develop an agent based spatial model to focus on T cell migration from lymph nodes through the vascular system to sites of infection. We use our model to investigate whether different strains of influenza modulate this process. We calibrate the model using viral and chemokine secretion rates we measure in vitro together with values taken from literature. The spatial nature of the model reveals unique challenges for T cell recruitment that are not apparent in standard differential equation models. In this model comparing three influenza viruses, plaque expansion is governed primarily by the replication rate of the virus strain, and the efficiency of the T cell search-and-kill is limited by the density of infected epithelial cells in each plaque. Thus for each virus there is a different threshold of T cell search time above which recruited T cells are unable to control further expansion. Future models could use this relationship to more accurately predict control of the infection.
authors.affiliation: Department of Computer Science, University of New Mexico, Albuquerque, NM, USA. Electronic address: drew@cs.unm.edu.
authors.forename: Drew
authors.initials: D
authors.lastname: Levin
authors.affiliation: Department of Computer Science, University of New Mexico, Albuquerque, NM, USA.
authors.forename: Stephanie
authors.initials: S
authors.lastname: Forrest
authors.affiliation: Department of Computer Science, University of New Mexico, Albuquerque, NM, USA.
authors.forename: Soumya
authors.initials: S
authors.lastname: Banerjee
authors.affiliation: Lovelace Respiratory Research Institute, Albuquerque, NM, USA.
authors.forename: Candice
authors.initials: C
authors.lastname: Clay
authors.affiliation: Department of Molecular Genetics & Microbiology, Department of Pathology, University of New Mexico, Health Sciences Center, Albuquerque, NM, USA.
authors.forename: Judy
authors.initials: J
authors.lastname: Cannon
authors.affiliation: Department of Computer Science, University of New Mexico, Albuquerque, NM, USA.
authors.forename: Melanie
authors.initials: M
authors.lastname: Moses
authors.affiliation: Department of Computer Science, University of New Mexico, Albuquerque, NM, USA; Lovelace Respiratory Research Institute, Albuquerque, NM, USA.
authors.forename: Frederick
authors.initials: F
authors.lastname: Koster
mesh_terms: D016207:Cytokines / Q000378:metabolism; D006801:Humans; D053118:Influenza A Virus, H1N1 Subtype / Q000276:immunology; D053124:Influenza A Virus, H5N1 Subtype / Q000276:immunology; D007251:Influenza, Human / Q000453:epidemiology / Q000276:immunology* / Q000821:virology*; D008168:Lung / Q000276:immunology / Q000821:virology*; D008198:Lymph Nodes / Q000473:pathology / Q000821:virology; D018448:Models, Immunological; D012621:Seasons; D013045:Species Specificity; D013601:T-Lymphocytes / Q000276:immunology* / Q000821:virology*
chemical_list: D016207:Cytokines
keywords: Agent-based model; Computational biology; Immunology; Systems biology; Virology