Cells have a remarkable ability to sense and respond to changes in their environment. This sensory capability often relies on membrane-embedded protein kinases that can relay information about the environment to intracellular effectors. In bacteria, such information transfer frequently involves two-component signal transduction pathways that transfer the signals from the outside to the interior of the cell. The signal transfer activates a specific transcription factor, which, in turn, will activate a set of genes that are necessary to respond to the specific environmental changes. In his previous work, the investigator studied the signal transfer system on the protein level and discovered four amino acid residues that are necessary for the two-component signal transduction partners to interact and subsequently activate the appropriate set of target genes. This is remarkable because bacterial cells have many such highly homologous parallel signal transduction systems that are dedicated to activate a highly diverse set of gene systems. This raises the question of how these pathways maintain their specificity with apparent minimal cross talk between them. The focus of this study is to assess how these four specificity residues ensure that the signal-receiving component of the system finds the cognate response regulator.
Protein-protein interactions are critical to the operation and functions of all cells. The specificity of these interactions is often dictated at the level of molecular recognition, meaning proteins have an intrinsic ability to discriminate cognate from non-cognate partners. Understanding precisely how this discrimination is accomplished remains a major problem in biology. In particular, delineating the set of amino acids that contribute to a protein-protein interaction, and elucidating their individual and collective contributions are significant experimental challenges. Directed mutagenesis studies can help elucidate the function of individual residues, but such efforts have traditionally been limited by the number of mutants constructed and tested, thus precluding truly systematic studies of protein-protein interactions. To tackle this challenge, the investigator will leverage the power of next-generation sequencing to comprehensively map the sequence space underlying a protein-protein interaction critical to signal transduction in bacteria. Using the E. coli pathway PhoQ-PhoP as a model system, libraries of possible amino acid combinations at four key specificity residues (separately in either the kinase or regulator) will be developed. A high-throughput flow cytometry-based screen and next-generation sequencing will identify all combinations that support a functional PhoQ-PhoP interaction. The resulting data, and subsequent bioinformatic analyses, will reveal the degeneracy of this protein-protein interaction. Individual mutants identified as signal-responsive will be characterized in detail using a battery of in vitro and in vivo assays to assess how they impact the quantitative output and dynamics of the PhoQ-PhoP signaling pathway. This project will include also a detailed quantitative, differential equation-based model of two-component signaling pathways, which will be used to dissect the data resulting form the high-throughput screen to learn at each step of the pathway how autophosphorylation, phosphotransfer, and dephosphorylation, contribute to the complex, nonlinear signaling dynamics observed in vivo. The model will drive testable predictions of the behavior of other two-component pathways, thereby broadening the scope and generalizability of our findings to a wide range of organisms in bacteria, fungi, and plants, all of which rely on two-component signaling pathways for survival in the wild.
