Connecting the Sequence-Space of Bacterial Signaling Proteins to Phenotypes Using Coevolutionary Landscapes.
Two-component signaling (TCS) is the primary means by which bacteria sense and respond to the environment. TCS involves two partner proteins working in tandem, which interact to perform cellular functions whereas limiting interactions with non-partners (i.e., cross-talk). We construct a Potts model for TCS that can quantitatively predict how mutating amino acid identities affect the interaction between TCS partners and non-partners. The parameters of this model are inferred directly from protein sequence data. This approach drastically reduces the computational complexity of exploring the sequence-space of TCS proteins. As a stringent test, we compare its predictions to a recent comprehensive mutational study, which characterized the functionality of 204mutational variants of the PhoQ kinase in Escherichia coli We find that our best predictions accurately reproduce the amino acid combinations found in experiment, which enable functional signaling with its partner PhoP. These predictions demonstrate the evolutionary pressure to preserve the interaction between TCS partners as well as prevent unwanted cross-talk. Further, we calculate the mutational change in the binding affinity between PhoQ and PhoP, providing an estimate to the amount of destabilization needed to disrupt TCS.
Center for Theoretical Biological Physics, Rice University, Houston, TX ryan.r.cheng@gmail.com jonuchic@rice.edu faruckm@utdallas.edu.
R R
RR
Cheng
Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden.
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O
Nordesjö
Department of Biophysics, University of Michigan, Ann Arbor, MI.
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RL
Hayes
Center for Theoretical Biological Physics, Rice University, Houston, TX.|Department of Bioengineering, Rice University, Houston, TX.
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H
Levine
Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden.
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SC
Flores
Center for Theoretical Biological Physics, Rice University, Houston, TX ryan.r.cheng@gmail.com jonuchic@rice.edu faruckm@utdallas.edu.|Department of Physics and Astronomy, Rice University, Houston, TX.|Department of Chemistry, and Biosciences, Rice University, Houston, TX.
J N
JN
Onuchic
Department of Biological Sciences and Center for Systems Biology, University of Texas at Dallas, Dallas, TX ryan.r.cheng@gmail.com jonuchic@rice.edu faruckm@utdallas.edu.
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F
Morcos
D000595:Amino Acid Sequence; D001419:Bacteria / Q000235:genetics* / Q000378:metabolism*; D001426:Bacterial Proteins / Q000235:genetics* / Q000378:metabolism*; D003198:Computer Simulation; D015964:Gene Expression Regulation, Bacterial; D010641:Phenotype; D011485:Protein Binding; D011494:Protein Kinases / Q000378:metabolism; D020539:Sequence Analysis, Protein / Q000379:methods; D015398:Signal Transduction / Q000235:genetics*
D001426:Bacterial Proteins; D011494:Protein Kinases
bacterial signaling.; epistasis; fitness landscape; interaction specificity; mutational phenotypes; statistical inference