Literature DB >> 11160244

A model to predict cell-mediated immune regulatory mechanisms during human infection with Mycobacterium tuberculosis.

J E Wigginton1, D Kirschner.   

Abstract

A key issue for the study of tuberculosis infection (TB) is to understand why individuals infected with Mycobacterium tuberculosis experience different clinical outcomes. Elaborating the immune mechanisms that determine whether an infected individual will suffer active TB or latent infection can aid in developing treatment and prevention strategies. To better understand the dynamics of M. tuberculosis infection and immunity, we have developed a virtual human model that qualitatively and quantitatively characterizes the cellular and cytokine control network operational during TB infection. Using this model, we identify key regulatory elements in the host response. In particular, factors affecting cell functions, such as macrophage activation and bactericidal capabilities, and effector T cell functions such as cytotoxicity and cytokine production can each be determinative. The model indicates, however, that even if latency is achieved, it may come at the expense of tissue damage if the response is not properly regulated. A balance in Th1 and Th2 immune responses governed by IFN-gamma, IL-10, and IL-4 facilitate this down-regulation. These results are further explored through virtual deletion and depletion experiments.

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Year:  2001        PMID: 11160244     DOI: 10.4049/jimmunol.166.3.1951

Source DB:  PubMed          Journal:  J Immunol        ISSN: 0022-1767            Impact factor:   5.422


  63 in total

1.  Macrophage polarization drives granuloma outcome during Mycobacterium tuberculosis infection.

Authors:  Simeone Marino; Nicholas A Cilfone; Joshua T Mattila; Jennifer J Linderman; JoAnne L Flynn; Denise E Kirschner
Journal:  Infect Immun       Date:  2014-11-03       Impact factor: 3.441

Review 2.  New insights into mathematical modeling of the immune system.

Authors:  Penelope A Morel; Shlomo Ta'asan; Benoit F Morel; Denise E Kirschner; Joanne L Flynn
Journal:  Immunol Res       Date:  2006       Impact factor: 2.829

3.  A comparison of random vs. chemotaxis-driven contacts of T cells with dendritic cells during repertoire scanning.

Authors:  Thomas Riggs; Adrienne Walts; Nicolas Perry; Laura Bickle; Jennifer N Lynch; Amy Myers; Joanne Flynn; Jennifer J Linderman; Mark J Miller; Denise E Kirschner
Journal:  J Theor Biol       Date:  2007-10-18       Impact factor: 2.691

4.  Modeling the immune rheostat of macrophages in the lung in response to infection.

Authors:  Judy Day; Avner Friedman; Larry S Schlesinger
Journal:  Proc Natl Acad Sci U S A       Date:  2009-06-22       Impact factor: 11.205

5.  A review of computational and mathematical modeling contributions to our understanding of Mycobacterium tuberculosis within-host infection and treatment.

Authors:  Denise Kirschner; Elsje Pienaar; Simeone Marino; Jennifer J Linderman
Journal:  Curr Opin Syst Biol       Date:  2017-05-22

6.  A population model capturing dynamics of tuberculosis granulomas predicts host infection outcomes.

Authors:  Chang Gong; Jennifer J Linderman; Denise Kirschner
Journal:  Math Biosci Eng       Date:  2015-06       Impact factor: 2.080

7.  Global sensitivity analysis used to interpret biological experimental results.

Authors:  Angela M Jarrett; Yaning Liu; N G Cogan; M Yousuff Hussaini
Journal:  J Math Biol       Date:  2014-07-25       Impact factor: 2.259

8.  Modelling the interaction between the host immune response, bacterial dynamics and inflammatory damage in comparison with immunomodulation and vaccination experiments.

Authors:  Angela M Jarrett; N G Cogan; M E Shirtliff
Journal:  Math Med Biol       Date:  2014-05-08       Impact factor: 1.854

9.  Differential responses of bovine macrophages to Mycobacterium avium subsp. paratuberculosis and Mycobacterium avium subsp. avium.

Authors:  Douglas J Weiss; Oral A Evanson; Andreas Moritz; Ming Qi Deng; Mitchell S Abrahamsen
Journal:  Infect Immun       Date:  2002-10       Impact factor: 3.441

10.  Dynamic models of immune responses: what is the ideal level of detail?

Authors:  Juilee Thakar; Mary Poss; Réka Albert; Gráinne H Long; Ranran Zhang
Journal:  Theor Biol Med Model       Date:  2010-08-20       Impact factor: 2.432

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