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Predictive shifts in free energy couple mutations to their phenotypic consequences
Mutation is a critical mechanism by which evolution explores the functional landscape of proteins. Despite our ability to experimentally inflict mutations at will, it remains difficult to link sequence-level perturbations to systems-level responses. Here, we present a framework centered on measuring...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6744869/ https://www.ncbi.nlm.nih.gov/pubmed/31451655 http://dx.doi.org/10.1073/pnas.1907869116 |
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author | Chure, Griffin Razo-Mejia, Manuel Belliveau, Nathan M. Einav, Tal Kaczmarek, Zofii A. Barnes, Stephanie L. Lewis, Mitchell Phillips, Rob |
author_facet | Chure, Griffin Razo-Mejia, Manuel Belliveau, Nathan M. Einav, Tal Kaczmarek, Zofii A. Barnes, Stephanie L. Lewis, Mitchell Phillips, Rob |
author_sort | Chure, Griffin |
collection | PubMed |
description | Mutation is a critical mechanism by which evolution explores the functional landscape of proteins. Despite our ability to experimentally inflict mutations at will, it remains difficult to link sequence-level perturbations to systems-level responses. Here, we present a framework centered on measuring changes in the free energy of the system to link individual mutations in an allosteric transcriptional repressor to the parameters which govern its response. We find that the energetic effects of the mutations can be categorized into several classes which have characteristic curves as a function of the inducer concentration. We experimentally test these diagnostic predictions using the well-characterized LacI repressor of Escherichia coli, probing several mutations in the DNA binding and inducer binding domains. We find that the change in gene expression due to a point mutation can be captured by modifying only the model parameters that describe the respective domain of the wild-type protein. These parameters appear to be insulated, with mutations in the DNA binding domain altering only the DNA affinity and those in the inducer binding domain altering only the allosteric parameters. Changing these subsets of parameters tunes the free energy of the system in a way that is concordant with theoretical expectations. Finally, we show that the induction profiles and resulting free energies associated with pairwise double mutants can be predicted with quantitative accuracy given knowledge of the single mutants, providing an avenue for identifying and quantifying epistatic interactions. |
format | Online Article Text |
id | pubmed-6744869 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-67448692019-09-27 Predictive shifts in free energy couple mutations to their phenotypic consequences Chure, Griffin Razo-Mejia, Manuel Belliveau, Nathan M. Einav, Tal Kaczmarek, Zofii A. Barnes, Stephanie L. Lewis, Mitchell Phillips, Rob Proc Natl Acad Sci U S A PNAS Plus Mutation is a critical mechanism by which evolution explores the functional landscape of proteins. Despite our ability to experimentally inflict mutations at will, it remains difficult to link sequence-level perturbations to systems-level responses. Here, we present a framework centered on measuring changes in the free energy of the system to link individual mutations in an allosteric transcriptional repressor to the parameters which govern its response. We find that the energetic effects of the mutations can be categorized into several classes which have characteristic curves as a function of the inducer concentration. We experimentally test these diagnostic predictions using the well-characterized LacI repressor of Escherichia coli, probing several mutations in the DNA binding and inducer binding domains. We find that the change in gene expression due to a point mutation can be captured by modifying only the model parameters that describe the respective domain of the wild-type protein. These parameters appear to be insulated, with mutations in the DNA binding domain altering only the DNA affinity and those in the inducer binding domain altering only the allosteric parameters. Changing these subsets of parameters tunes the free energy of the system in a way that is concordant with theoretical expectations. Finally, we show that the induction profiles and resulting free energies associated with pairwise double mutants can be predicted with quantitative accuracy given knowledge of the single mutants, providing an avenue for identifying and quantifying epistatic interactions. National Academy of Sciences 2019-09-10 2019-08-26 /pmc/articles/PMC6744869/ /pubmed/31451655 http://dx.doi.org/10.1073/pnas.1907869116 Text en Copyright © 2019 the Author(s). Published by PNAS. http://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY) (http://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | PNAS Plus Chure, Griffin Razo-Mejia, Manuel Belliveau, Nathan M. Einav, Tal Kaczmarek, Zofii A. Barnes, Stephanie L. Lewis, Mitchell Phillips, Rob Predictive shifts in free energy couple mutations to their phenotypic consequences |
title | Predictive shifts in free energy couple mutations to their phenotypic consequences |
title_full | Predictive shifts in free energy couple mutations to their phenotypic consequences |
title_fullStr | Predictive shifts in free energy couple mutations to their phenotypic consequences |
title_full_unstemmed | Predictive shifts in free energy couple mutations to their phenotypic consequences |
title_short | Predictive shifts in free energy couple mutations to their phenotypic consequences |
title_sort | predictive shifts in free energy couple mutations to their phenotypic consequences |
topic | PNAS Plus |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6744869/ https://www.ncbi.nlm.nih.gov/pubmed/31451655 http://dx.doi.org/10.1073/pnas.1907869116 |
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