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"SIGMA FACTOR NETWORK OF MYCOBACTERIUM TUBERCULOSIS"

by
Rinki S. Chauhan
Microbiology and Molecular Genetics Program
M.Sc., B R Ambedkar University, India
B.Sc., B R Ambedkar University, India


Thesis Advisor: Marila Gennaro, M D.
Professor
Public Health Research Institute

Thursday, April 18, 2013
11:00 A.M., ICPH-Auditorium


Abstract

Accessory sigma factors are critical proteins that mediate stress response in Mycobacterium tuberculosis. The stress response is directly associated with the ability of the pathogenic bacteria to survive in the host. By changing the sigma factor subunit, the bacterial RNA polymerase (RNAP) holoenzyme reprograms itself to transcribe sets of genes expressing cellular functions that are critical for bacterial survival. Thus, coordinated expression of these sets of genes controlled by sigma factors allows the bacteria to adapt and survive in the changing environmental conditions. The high number of accessory sigma factors in M. tuberculosis suggests the need for complex gene expression in response to stress. Therefore, it is imperative to unravel M. tuberculosis sigma factor biology to understand the stress response of this pathogen. Understanding the regulation of sigma factors is key to deciphering sigma factor biology. Since only a few inter-sigma factor regulatory interactions are known, reconstructing the sigma factor transcriptional regulatory network is critical for understanding sigma factor regulation and function. In this work we reconstruct the sigma factor network using two-plasmid method, an experimental strategy that tests direct, inter-sigma factor interactions in E. coli. We measured the effect of inducing expression of a test M. tuberculosis sigma factor sigma factor gene on the -galactosidase activity expressed by promoter-lacZ fusion of another sigma factor gene in E. coli. After reconstruction of the sigma factor network, we validated few direct interactions of the reconstructed sigma factor network in M. tuberculosis. We validated that sigC is target of sigK during logarithmic growth in M. tuberculosis. We used logarithmic growing culture to validate this interaction because the conditions under which sigK is induced is not known. Another result of the reconstructed network was the identification of targets of sigma factor, sigB. To test the effect of overexpression of sigB on the expression of downstream sigma factors in M. tuberculosis, we utilized anhydrotetracycline (ATC)-inducible system. All the target sigma factors were induced in response to induction of sigB gene in M. tuberculosis. One of the important results obtained from reconstructed network, was autoregulation of sigma factor, sigE. Since sigE has three promoters, deletion constructs were made to test individual promoter response in E. coli overexpression strains and also in M. tuberculosis during surface stress. We used surface stress because it has already been reported in previous findings that sigE is induced during surface stress. In our work, we identified that sigE is autoregulated through promoter P2.


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