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The M. tuberculosis phosphosignaling network. Bacteria transmit signals through reversible phosphorylation using the classic two component systems. However, recent genomic data, for example from the Ocean Genome Sampling Initiative, have shown that bacteria also rely on Ser/Thr/Tyr kinases for cell signaling. A case in point is Mtb, which codes for the same number of two component systems as Ser/Thr/Tyr kinases. These systems are less well understood, and our view of Ser/Thr/Tyr signaling is largely shaped by what is known in the equivalent eukaryotic systems. However, bacteria very likely evolved their own components and mechanisms to signal through phosphate. We are exploring these possibilities by using unbiased, systems-wide approaches to uncover new, uniquely bacterial themes in Mtb phosphorylation and its cellular effects.
Knowing the parts. More than 30% of all Mtb genes are hypothetical or unknown. This black hole of annotation is a bottleneck for studying Mtb on every level. Discovering the function of unknown proteins is difficult, particularly for species-specific proteins, for which sequence-based methods of annotation fail. We are using high-throughput experimental tools to find biochemical functions of proteins. By using chemical probes that detect activity coupled to mass spectrometric identification of target proteins, we survey the proteome for unknown activities. We provided the most comprehensive description of the ATPase family in Mtb, a large and central protein family. Combined with structural biology, we discover new protein families and explore even the most divergent sequence space. Some microbial pathogens pose even bigger annotation challenges: Only about half of all proteins in Plasmodium falciparum, for example, have known functions. We are now extending our chemical proteomic platform to also annotate unknown Plasmodium proteins and to discover enzymes that control life cycle decisions.
Copyright © 2003-2014 Molecular & Cellular Biology Program, University of Washington
Fred Hutchison Cancer Research Center | University of Washington
Institute for Systems Biology | Seattle Biomed