Literature DB >> 28904202

Discrete Dynamical Modeling of Influenza Virus Infection Suggests Age-Dependent Differences in Immunity.

Ericka Keef1, Li Ang Zhang2, David Swigon3,4, Alisa Urbano5, G Bard Ermentrout3, Michael Matuszewski2, Franklin R Toapanta6, Ted M Ross6, Robert S Parker2,7,8,4, Gilles Clermont2,7,8,4.   

Abstract

Immunosenescence, an age-related decline in immune function, is a major contributor to morbidity and mortality in the elderly. Older hosts exhibit a delayed onset of immunity and prolonged inflammation after an infection, leading to excess damage and a greater likelihood of death. Our study applies a rule-based model to infer which components of the immune response are most changed in an aged host. Two groups of BALB/c mice (aged 12 to 16 weeks and 72 to 76 weeks) were infected with 2 inocula: a survivable dose of 50 PFU and a lethal dose of 500 PFU. Data were measured at 10 points over 19 days in the sublethal case and at 6 points over 7 days in the lethal case, after which all mice had died. Data varied primarily in the onset of immunity, particularly the inflammatory response, which led to a 2-day delay in the clearance of the virus from older hosts in the sublethal cohort. We developed a Boolean model to describe the interactions between the virus and 21 immune components, including cells, chemokines, and cytokines, of innate and adaptive immunity. The model identifies distinct sets of rules for each age group by using Boolean operators to describe the complex series of interactions that activate and deactivate immune components. Our model accurately simulates the immune responses of mice of both ages and with both inocula included in the data (95% accurate for younger mice and 94% accurate for older mice) and shows distinct rule choices for the innate immunity arm of the model between younger and aging mice in response to influenza A virus infection.IMPORTANCE Influenza virus infection causes high morbidity and mortality rates every year, especially in the elderly. The elderly tend to have a delayed onset of many immune responses as well as prolonged inflammatory responses, leading to an overall weakened response to infection. Many of the details of immune mechanisms that change with age are currently not well understood. We present a rule-based model of the intrahost immune response to influenza virus infection. The model is fit to experimental data for young and old mice infected with influenza virus. We generated distinct sets of rules for each age group to capture the temporal differences seen in the immune responses of these mice. These rules describe a network of interactions leading to either clearance of the virus or death of the host, depending on the initial dosage of the virus. Our models clearly demonstrate differences in these two age groups, particularly in the innate immune responses.
Copyright © 2017 American Society for Microbiology.

Entities:  

Keywords:  host-pathogen interactions; immunosenescence; influenza; mathematical modeling; viral clearance

Mesh:

Substances:

Year:  2017        PMID: 28904202      PMCID: PMC5686742          DOI: 10.1128/JVI.00395-17

Source DB:  PubMed          Journal:  J Virol        ISSN: 0022-538X            Impact factor:   5.103


  41 in total

Review 1.  Antibodies, viruses and vaccines.

Authors:  Dennis R Burton
Journal:  Nat Rev Immunol       Date:  2002-09       Impact factor: 53.106

Review 2.  Innate immunity in aging: impact on macrophage function.

Authors:  Julie Plowden; Mary Renshaw-Hoelscher; Carrie Engleman; Jacqueline Katz; Suryaprakash Sambhara
Journal:  Aging Cell       Date:  2004-08       Impact factor: 9.304

Review 3.  Human immunosenescence: the prevailing of innate immunity, the failing of clonotypic immunity, and the filling of immunological space.

Authors:  C Franceschi; M Bonafè; S Valensin
Journal:  Vaccine       Date:  2000-02-25       Impact factor: 3.641

4.  Effect of aging on the modulation of macrophage functions by neuropeptides.

Authors:  M De la Fuente; S Medina; M Del Rio; M D Ferrández; A Hernanz
Journal:  Life Sci       Date:  2000-09-15       Impact factor: 5.037

Review 5.  Clinical relevance of age-related immune dysfunction.

Authors:  S C Castle
Journal:  Clin Infect Dis       Date:  2000-09-14       Impact factor: 9.079

6.  Production of IL-10 by human natural killer cells stimulated with IL-2 and/or IL-12.

Authors:  P T Mehrotra; R P Donnelly; S Wong; H Kanegane; A Geremew; H S Mostowski; K Furuke; J P Siegel; E T Bloom
Journal:  J Immunol       Date:  1998-03-15       Impact factor: 5.422

7.  Effects of aging on influenza virus infection dynamics.

Authors:  Esteban A Hernandez-Vargas; Esther Wilk; Laetitia Canini; Franklin R Toapanta; Sebastian C Binder; Alexey Uvarovskii; Ted M Ross; Carlos A Guzmán; Alan S Perelson; Michael Meyer-Hermann
Journal:  J Virol       Date:  2014-01-29       Impact factor: 5.103

8.  Impaired innate mucosal immunity in aged mice permits prolonged Streptococcus pneumoniae colonization.

Authors:  Cassandra L Krone; Krzysztof Trzciński; Tomasz Zborowski; Elisabeth A M Sanders; Debby Bogaert
Journal:  Infect Immun       Date:  2013-09-30       Impact factor: 3.441

Review 9.  The role of immunity in susceptibility to respiratory infection in the aging lung.

Authors:  K C Meyer
Journal:  Respir Physiol       Date:  2001-10

10.  Experimental design schemes for learning Boolean network models.

Authors:  Nir Atias; Michal Gershenzon; Katia Labazin; Roded Sharan
Journal:  Bioinformatics       Date:  2014-09-01       Impact factor: 6.937

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Journal:  Immunol Rev       Date:  2018-09       Impact factor: 12.988

2.  Antiviral Gene Expression in Young and Aged Murine Lung during H1N1 and H3N2.

Authors:  Rebecca Harris; Jianjun Yang; Kassandra Pagan; Soo Jung Cho; Heather Stout-Delgado
Journal:  Int J Mol Sci       Date:  2021-11-09       Impact factor: 5.923

3.  Short Communication: Oral Administration of Heat-killed Lactobacillus brevis KB290 in Combination with Retinoic Acid Provides Protection against Influenza Virus Infection in Mice.

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Journal:  Nutrients       Date:  2020-09-24       Impact factor: 5.717

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