This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. A major hurdle in combating TB is the fact Mycobacterium tuberculosis (Mtb) is able to persist for long periods of time in host tissues, in a quiescent state. These bacilli are able to reactivate and cause pulmonary TB, when the immune system is compromised. Hence, a complete understanding of TB latency and reactivation is required for the effective control of TB. Nonhuman Primates (NHPs) are excellent models of TB, especially to study the progression of experimental infection to latency, and to study the pathology and biology of granulomatous lesions. We will leverage our highly tractable model to identify host signatures and mediators of this process. We show that pro-inflammatory immune signaling pathways, initially induced in NHP TB lesions, are overwhelmingly silenced over the course of next several weeks. This reprogramming could be a host response to changes in bacterial replication and physiology. Further, these responses could reflect the efforts of the pathogen to prevent excessive immunopathology during the infection of lungs. The central hypothesis of our proposal is that host granuloma responses can be used to predict latent and reactivation TB. We propose to perform a systematic study of the """"""""transcriptome"""""""" and the """"""""miRNAome"""""""" of NHP lung lesions. Temporal profiles will be obtained from infected NHPs modeling long-term latent infection. Profiles will also be obtained from NHPs in which latent TB is reactivated by simian AIDS. These profiles will generate statistical learning algorithms and mixed effects computational models of latent and reactivation TB. The relevance of some of the most informative set of genetic predictors available from the data collected will be tested back in both the NHP model, as well as in human patients. These systems-biology studies will enhance our understanding of TB latency and reactivation in a host that mimics both TB and AIDS in the closest possible manner to humans.
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