Project 2: Response to Treatment

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Abstract – Project 2 The responses of Mtb to individual drugs and regimens and their relationship to treatment outcome remains variable and poorly understood. Our premise is that knowledge of bacterial networks and their regulatory controls constitute a powerful but underexplored window to novel targets and treatment strategies. The major goal of this project is to identify strain-independent and strain-specific cellular networks associated with varying drug responses in Mtb, and their regulation. In Aim 1 this project will utilize carefully selected clinical drug-sensitive Mtb isolates exhibiting varying responses to treatment to characterize the genetic, transcriptional, and metabolic differences revealed by exposure to important anti-TB drugs, and then to map those changes to condition-specific drug tolerance phenotypes. We will subject each strain to detailed analyses including transcriptomics, metabolomics, and regulator-based genetic screens in response to front line antibiotics and in conditions that promote tolerance. In Aim 2 we will employ the data from Aim 1 to build and refine regulatory network models that elucidate both common and strain-specific Mtb strategies to subvert drug action. These models will be refined by testing model driven predictions through an iterative series of multi-omic analyses and perturbations including more focused experiments such as targeted protein interaction studies, bacterial cell sorting and solid-phase time-lapse microscopy. Ultimately, in Aim 3 we will test the extent to which the drug-response network models generated in Aims 1 and 2 predict clinical treatment outcomes, and identify potential strategies to interfere with adaptive drug-response network states to improve the efficacy of chemotherapy. We will further test the relevance of identified drug response networks in targeted studies of Mtb isolates from treatment failures in humans. The outcome of this project will be the identification and validation of the specific cellular networks associated with varying drug responses in Mtb and their regulation.