Tuberculosis is responsible for 2 million deaths every year. Even after decades of research, there are still numerous gaps in our understanding of the mechanisms that provide protection against tuberculosis in humans. In this proposal, we take a unique multipronged systems biology approach, combining a non-human primate model of M. tuberculosis infection that closely mimics all aspects of human M. tuberculosis infection, with a vaccine that is only partially effective (resulting in protected and non-protected animals), and state-of- the-art live animal imaging, immunologic monitoring, and computational models, to identify and predict the immunologic mechanisms that are protective against TB. This proposal will develop a multi-disciplinary """"""""tool- box"""""""" for dissecting human immune responses that provide protection against bacterial infections, even beyond TB. We build on considerable experience in computational modeling of tuberculosis and will generate a first- time 3 physiologic compartment model of blood, lung, lymph node with multi-scale interactions (molecular to cellular to organ to host scales), incorporating data generated in this project from the non-human primate, as well as our previous data and that from the literature. These models will be used to identify surrogate markers of protection, which will be used to predict the animals that are protected by this vaccine. In turn, the experimental animals will be the source of granuloma and lymph node tissue to probe the actual protective responses at the site of infection, studies that are impossible to do in humans. Through iteration between computational and experimental models, we will identify the factors that together can contribute to a protective immune response. These studies are a necessary step to a more detailed understanding of host immune responses protective against tuberculosis, and development and testing of new therapeutic and intervention strategies to prevent this disease.

Public Health Relevance

Tuberculosis is a deadly infection that kills 2 million people every year, despite availability of drugs to treat the disease. This systems biology proposal combines computational and experimental approaches to identify the host immune responses that can be exploited to control this infection and protect humans against disease. These studies will identify mechanisms to target for new intervention or therapeutic strategies against tuberculosis.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
1R01HL110811-01A1
Application #
8332906
Study Section
Special Emphasis Panel (ZRG1-VH-D (50))
Program Officer
Peavy, Hannah H
Project Start
2012-08-13
Project End
2017-06-30
Budget Start
2012-08-13
Budget End
2013-06-30
Support Year
1
Fiscal Year
2012
Total Cost
$1,252,487
Indirect Cost
$280,032
Name
University of Pittsburgh
Department
Genetics
Type
Schools of Medicine
DUNS #
004514360
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
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DiFazio, Robert M; Mattila, Joshua T; Klein, Edwin C et al. (2016) Active transforming growth factor-? is associated with phenotypic changes in granulomas after drug treatment in pulmonary tuberculosis. Fibrogenesis Tissue Repair 9:6
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Pienaar, Elsje; Matern, William M; Linderman, Jennifer J et al. (2016) Multiscale Model of Mycobacterium tuberculosis Infection Maps Metabolite and Gene Perturbations to Granuloma Sterilization Predictions. Infect Immun 84:1650-69

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