Designing bacterial signaling interactions with coevolutionary landscapes

Simple item page
dc.citation.articleNumbere0201734
dc.citation.issueNumber8
dc.citation.journalTitlePLoS ONE
dc.citation.volumeNumber13
dc.contributor.authorCheng, Ryan R.
dc.contributor.authorHaglund, Ellinor
dc.contributor.authorTiee, Nicholas S.
dc.contributor.authorMorcos, Faruck
dc.contributor.authorLevine, Herbert
dc.contributor.authorAdams, Joseph A.
dc.contributor.authorJennings, Patricia A.
dc.contributor.authorOnuchic, José N.
dc.date.accessioned2018-11-09T15:00:01Z
dc.date.available2018-11-09T15:00:01Z
dc.date.issued2018
dc.description.abstractSelecting amino acids to design novel protein-protein interactions that facilitate catalysis is a daunting challenge. We propose that a computational coevolutionary landscape based on sequence analysis alone offers a major advantage over expensive, time-consuming brute-force approaches currently employed. Our coevolutionary landscape allows prediction of single amino acid substitutions that produce functional interactions between non-cognate, interspecies signaling partners. In addition, it can also predict mutations that maintain segregation of signaling pathways across species. Specifically, predictions of phosphotransfer activity between the Escherichia coli histidine kinase EnvZ to the non-cognate receiver Spo0F from Bacillus subtilis were compiled. Twelve mutations designed to enhance, suppress, or have a neutral effect on kinase phosphotransfer activity to a non-cognate partner were selected. We experimentally tested the ability of the kinase to relay phosphate to the respective designed Spo0F receiver proteins against the theoretical predictions. Our key finding is that the coevolutionary landscape theory, with limited structural data, can significantly reduce the search-space for successful prediction of single amino acid substitutions that modulate phosphotransfer between the two-component His-Asp relay partners in a predicted fashion. This combined approach offers significant improvements over large-scale mutations studies currently used for protein engineering and design.
dc.identifier.citationCheng, Ryan R., Haglund, Ellinor, Tiee, Nicholas S., et al.. "Designing bacterial signaling interactions with coevolutionary landscapes." <i>PLoS ONE,</i> 13, no. 8 (2018) Public Library of Science: https://doi.org/10.1371/journal.pone.0201734.
dc.identifier.digitaljournal.pone.0201734
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0201734
dc.identifier.urihttps://hdl.handle.net/1911/103306
dc.language.isoeng
dc.publisherPublic Library of Science
dc.rightsThis is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleDesigning bacterial signaling interactions with coevolutionary landscapes
dc.typeJournal article
dc.type.dcmiText
dc.type.publicationpublisher version
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
journal.pone.0201734.pdf
Size:
2.03 MB
Format:
Adobe Portable Document Format
Download
Collections
Faculty Publications