Connecting the Sequence-Space of Bacterial Signaling Proteins to Phenotypes Using Coevolutionary Landscapes

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dc.citation.firstpage3054
dc.citation.issueNumber12
dc.citation.journalTitleMolecular Biology and Evolution
dc.citation.lastpage3064
dc.citation.volumeNumber33
dc.contributor.authorCheng, R.R.
dc.contributor.authorNordesjӧ, O.
dc.contributor.authorHayes, R.L.
dc.contributor.authorLevine, H.
dc.contributor.authorFlores, S.C.
dc.contributor.authorOnuchic, José Nelson
dc.contributor.authorMorcos, F.
dc.contributor.orgCenter for Theoretical Biological Physics
dc.date.accessioned2017-05-05T19:00:53Z
dc.date.available2017-05-05T19:00:53Z
dc.date.issued2016
dc.description.abstractTwo-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 204 mutational 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.
dc.identifier.citationCheng, R.R., Nordesjӧ, O., Hayes, R.L., et al.. "Connecting the Sequence-Space of Bacterial Signaling Proteins to Phenotypes Using Coevolutionary Landscapes." <i>Molecular Biology and Evolution,</i> 33, no. 12 (2016) Oxford University Press: 3054-3064. https://doi.org/10.1093/molbev/msw188.
dc.identifier.doihttps://doi.org/10.1093/molbev/msw188
dc.identifier.urihttps://hdl.handle.net/1911/94197
dc.language.isoeng
dc.publisherOxford University Press
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subject.keywordstatistical inference
dc.subject.keywordmutational phenotypes
dc.subject.keywordinteraction specificity
dc.subject.keywordepistasis
dc.subject.keywordfitness landscape
dc.subject.keywordbacterial signaling
dc.titleConnecting the Sequence-Space of Bacterial Signaling Proteins to Phenotypes Using Coevolutionary Landscapes
dc.typeJournal article
dc.type.dcmiText
dc.type.publicationpublisher version
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