The contribution of a murine CNS-TB model for the understanding of the host–pathogen interactions in the formation of granulomas

Central nervous system (CNS) tuberculosis (TB) is the most severe form of TB, characterized morphologically by brain granulomas and tuberculous meningitis (TBM). Experimental strategies for the study of the host–pathogen interaction through the analysis of granulomas and its intrinsic molecular mech...

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Veröffentlicht in:Journal of neuroscience methods 2012-04, Vol.206 (1), p.88-93
Hauptverfasser: Zucchi, Fabíola C.R., Pelegrini-da-Silva, Adriana, Neder, Luciano, Silva, Célio L., Tsanaclis, Ana Maria C., Takayanagui, Osvaldo M.
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Sprache:eng
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Zusammenfassung:Central nervous system (CNS) tuberculosis (TB) is the most severe form of TB, characterized morphologically by brain granulomas and tuberculous meningitis (TBM). Experimental strategies for the study of the host–pathogen interaction through the analysis of granulomas and its intrinsic molecular mechanisms could provide new insights into the neuropathology of TB. To verify whether cerebellar mycobacterial infection induces the main features of the disease in human CNS and better understand the physiological mechanisms underlying the disease, we injected bacillus Calmette-Guerin (BCG) into the mouse cerebellum. BCG-induced CNS-TB is characterized by the formation of granulomas and TBM, a build up of bacterial loads in these lesions, and microglial recruitment into the lesion sites. In addition, there is an enhanced expression of signaling molecules such as nuclear factor-κB (NF-κB) and there is a presence of inducible nitric oxide synthase (iNOS) in the lesions and surrounding areas. This murine model of cerebellar CNS-TB was characterized by cellular and biochemical immune responses typically found in the human disease. This model could expand our knowledge about granulomas in TB infection of the cerebellum, and help characterize the physiological mechanisms involved with the progression of this serious illness that is responsible for killing millions people every year.
ISSN:0165-0270
1872-678X
DOI:10.1016/j.jneumeth.2012.02.015