Vaccines against many infectious diseases are effective because prior infection with the pathogen also induces sterilizing immunity. In contrast, there are numerous reports in the literature of disease caused by reinfection with Mycobacterium tuberculosis in those who have previously had tuberculosis, and in fact, prior tuberculosis increases the risk of subsequent disease, either through relapse or reinfection. In addition, mixed infections in tuberculosis patients have also been reported. However, seminal epidemiologic studies suggested that people with clinically latent M. tuberculosis infection can protect against development of tuberculosis due to reinfection. A review of the literature reveals that the effects of prior M. tuberculosis infection on subsequent infection are poorly studied and not well understood. In this application, we undertake a detailed study of the consequences of reinfection with M. tuberculosis. We bring together cutting edge technology for analysis of bacterial populations and immune responses in individual granulomas in an established non-human primate model of tuberculosis to address how a primary infection influences a secondary infection. We hypothesize that primary infection and the ensuing immune response will impair progression of the secondary infection at the granuloma level. We will dissect the immune responses in primary and secondary lesions to identify those factors that mediate killing of bacteria in the lesions. Finally, we will investigate clinically relevant scenarios of reinfection: challenge with a heterologous lineage of M. tuberculosis and treatment of M. tuberculosis infection prior to reinfection. The studies here will uncover basic and novel aspects of tuberculosis biology and immunology, as well as provide key translational insights into vaccine development and the consequences of treating latent infections in humans.

Public Health Relevance

Tuberculosis is endemic in many areas of the world, and people can be exposed to the bacterium that causes this disease many times throughout their lifetime. Almost nothing is known about the consequences of reinfection with tuberculosis, in terms of protection against disease or the interaction between the infections. Understanding how a previous infection influences a reinfection is crucial for identifying protective factors tha can be used for development of new vaccines and treatments against this disease.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI114674-05
Application #
9616229
Study Section
Host Interactions with Bacterial Pathogens Study Section (HIBP)
Program Officer
Eichelberg, Katrin
Project Start
2015-07-01
Project End
2019-12-31
Budget Start
2019-01-01
Budget End
2019-12-31
Support Year
5
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Pittsburgh
Department
Genetics
Type
Schools of Medicine
DUNS #
004514360
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Maiello, Pauline; DiFazio, Robert M; Cadena, Anthony M et al. (2018) Rhesus Macaques Are More Susceptible to Progressive Tuberculosis than Cynomolgus Macaques: a Quantitative Comparison. Infect Immun 86:
Lin, Philana Ling; Flynn, JoAnne L (2018) The End of the Binary Era: Revisiting the Spectrum of Tuberculosis. J Immunol 201:2541-2548
Cadena, Anthony M; Fortune, Sarah M; Flynn, JoAnne L (2017) Heterogeneity in tuberculosis. Nat Rev Immunol 17:691-702
Martin, Constance J; Cadena, Anthony M; Leung, Vivian W et al. (2017) Digitally Barcoding Mycobacterium tuberculosis Reveals In Vivo Infection Dynamics in the Macaque Model of Tuberculosis. MBio 8:
Cadena, Anthony M; Flynn, JoAnne L; Fortune, Sarah M (2016) The Importance of First Impressions: Early Events in Mycobacterium tuberculosis Infection Influence Outcome. MBio 7:e00342-16
Martin, Constance J; Carey, Allison F; Fortune, Sarah M (2016) A bug's life in the granuloma. Semin Immunopathol 38:213-20
Steel, J Jordan; Geiss, Brian J (2015) A novel system for visualizing alphavirus assembly. J Virol Methods 222:158-63