Macrophage response to Mycobacterium tuberculosis infection

The immune response to Mycobacterium tuberculosis (Mtb) infection is the formation of multicellular lesions, or granolomas, in the lung of the individual. However, the structure of the granulomas and the spatial distribution of the immune cells within is not well understood. In this paper we develop...

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Bibliographic Details
Published in:Journal of mathematical biology 2004-02, Vol.48 (2), p.218-242
Main Authors: Gammack, D, Doering, C R, Kirschner, D E
Format: Article
Language:English
Subjects:
Algorithms
Cell Count
Cell Death - immunology
Cell Movement - immunology
Chemokines - immunology
Chemotaxis, Leukocyte - immunology
Granuloma - immunology
Granuloma - microbiology
Granuloma - pathology
Humans
Immunity, Innate - immunology
Macrophages - cytology
Macrophages - immunology
Macrophages - microbiology
Models, Immunological
Mycobacterium tuberculosis
Mycobacterium tuberculosis - cytology
Mycobacterium tuberculosis - growth & development
Mycobacterium tuberculosis - immunology
Phagocytosis - immunology
Tuberculosis - immunology
Tuberculosis - microbiology
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Summary:The immune response to Mycobacterium tuberculosis (Mtb) infection is the formation of multicellular lesions, or granolomas, in the lung of the individual. However, the structure of the granulomas and the spatial distribution of the immune cells within is not well understood. In this paper we develop a mathematical model investigating the early and initial immune response to Mtb. The model consists of coupled reaction-diffusion-advection partial differential equations governing the dynamics of the relevant macrophage and bacteria populations and a bacteria-produced chemokine. Our novel application of mathematical concepts of internal states and internal velocity allows us to begin to study this unique immunological structure. Volume changes resulting from proliferation and death terms generate a velocity field by which all cells are transported within the forming granuloma. We present numerical results for two distinct infection outcomes: controlled and uncontrolled granuloma growth. Using a simplified model we are able to analytically determine conditions under which the bacteria population decreases, representing early clearance of infection, or grows, representing the initial stages of granuloma formation.
ISSN:0303-6812
DOI:10.1007/s00285-003-0232-8