Published online before print May 14, 2009

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(American Journal of Pathology. 2009;174:2190-2201.)
© 2009 American Society for Investigative Pathology
DOI: 10.2353/ajpath.2009.081075

Dominant Role of the sst1 Locus in Pathogenesis of Necrotizing Lung Granulomas during Chronic Tuberculosis Infection and Reactivation in Genetically Resistant Hosts

Alexander V. Pichugin^*, Bo-Shiun Yan^*, Alex Sloutsky, Lester Kobzik and Igor Kramnik^*

From the Departments of Immunology and Infectious Diseases,^* and Environmental Health, Harvard School of Public Health; the Department of Pathology, Brigham and Women’s Hospital; and the University of Massachusetts Medical School, Boston, Massachusetts

Significant host heterogeneity in susceptibility to tuberculosis exists both between and within mammalian species. Using a mouse model of infection with virulent Mycobacterium tuberculosis (Mtb), we identified the genetic locus sst1 that controls the progression of pulmonary tuberculosis in immunocompetent hosts. In this study, we demonstrate that within the complex, multigenic architecture of tuberculosis susceptibility, sst1 functions to control necrosis within tuberculosis lesions in the lungs; this lung-specific sst1 effect is independent of both the route of infection and genetic background of the host. Moreover, sst1-dependent necrosis was observed at low bacterial loads in the lungs during reactivation of the disease after termination of anti-tuberculosis drug therapy. We demonstrate that in sst1-susceptible hosts, nonlinked host resistance loci control both lung inflammation and production of inflammatory mediators by Mtb-infected macrophages. Although interactions of the sst1-susceptible allele with genetic modifiers determine the type of the pulmonary disease progression, other resistance loci do not abolish lung necrosis, which is, therefore, the core sst1-dependent phenotype. Sst1-susceptible mice from tuberculosis-resistant and -susceptible genetic backgrounds reproduce a clinical spectrum of pulmonary tuberculosis and may be used to more accurately predict the efficacy of anti-tuberculosis interventions in genetically heterogeneous human populations.