(623a) A Systems Approach to Decipher Stress Response Networks In Mycobacteria

The repertoire of Mycobacteria includes both pathogenic and non-pathogenic bacteria. Despite a century of research, the mechanism of survival of mycobacteria within the host and the host-pathogen interaction has not been understood completely. Inside the macrophage, the bacteria encounter many environmental stresses such as acidic pH and reactive oxygen. A complex network of sigma factors and two-component systems with extensive cross-talk is involved in the survival of the bacteria. In response to each stress, a variety of proteins are induced that help mycobacteria adapt to the new environment.

The objective of this work is to characterize this regulatory network in response to single and multiple stresses using M. smegmatis as a model system.  Both exponentially growing cells and cells from stationary phase were subjected to different kind of stresses, including acid shock, starvation, heat shock and ethanol stress. Cell viability was measured after a defined period of exposure. The stresses are applied either alone or in combinations. Surprisingly, in certain cases, viability increases in the presence of multiple stresses, as opposed to a single stress alone.  It is hypothesized that the presence of a stress helps the bacteria to adapt to the other stress condition. To identify the molecular basis of this adaptation, transcriptional profile of key sigma factors is measured.

Based on the current knowledge of the stress response transcriptional networks in Mycobacteria, a Boolean model is developed considering six types of stresses – hypoxia, heat shock, surface stress, nutrient stress, oxidative stress and cold shock. The model is simulated to evaluate the ability of this network to differentiate between stresses. The model suggests that in addition to induction of a sigma factor, the concentration levels distinguish between multiple stress combinations. Further, a robustness analysis is performed to identify the key nodes of the network.