Cargando…

Fitness landscape of a dynamic RNA structure

RNA structures are dynamic. As a consequence, mutational effects can be hard to rationalize with reference to a single static native structure. We reasoned that deep mutational scanning experiments, which couple molecular function to fitness, should capture mutational effects across multiple conform...

Descripción completa

Detalles Bibliográficos
Autores principales: Soo, Valerie W. C., Swadling, Jacob B., Faure, Andre J., Warnecke, Tobias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7877785/
https://www.ncbi.nlm.nih.gov/pubmed/33524037
http://dx.doi.org/10.1371/journal.pgen.1009353
_version_ 1783650239340609536
author Soo, Valerie W. C.
Swadling, Jacob B.
Faure, Andre J.
Warnecke, Tobias
author_facet Soo, Valerie W. C.
Swadling, Jacob B.
Faure, Andre J.
Warnecke, Tobias
author_sort Soo, Valerie W. C.
collection PubMed
description RNA structures are dynamic. As a consequence, mutational effects can be hard to rationalize with reference to a single static native structure. We reasoned that deep mutational scanning experiments, which couple molecular function to fitness, should capture mutational effects across multiple conformational states simultaneously. Here, we provide a proof-of-principle that this is indeed the case, using the self-splicing group I intron from Tetrahymena thermophila as a model system. We comprehensively mutagenized two 4-bp segments of the intron. These segments first come together to form the P1 extension (P1ex) helix at the 5’ splice site. Following cleavage at the 5’ splice site, the two halves of the helix dissociate to allow formation of an alternative helix (P10) at the 3’ splice site. Using an in vivo reporter system that couples splicing activity to fitness in E. coli, we demonstrate that fitness is driven jointly by constraints on P1ex and P10 formation. We further show that patterns of epistasis can be used to infer the presence of intramolecular pleiotropy. Using a machine learning approach that allows quantification of mutational effects in a genotype-specific manner, we demonstrate that the fitness landscape can be deconvoluted to implicate P1ex or P10 as the effective genetic background in which molecular fitness is compromised or enhanced. Our results highlight deep mutational scanning as a tool to study alternative conformational states, with the capacity to provide critical insights into the structure, evolution and evolvability of RNAs as dynamic ensembles. Our findings also suggest that, in the future, deep mutational scanning approaches might help reverse-engineer multiple alternative or successive conformations from a single fitness landscape.
format Online
Article
Text
id pubmed-7877785
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-78777852021-02-19 Fitness landscape of a dynamic RNA structure Soo, Valerie W. C. Swadling, Jacob B. Faure, Andre J. Warnecke, Tobias PLoS Genet Research Article RNA structures are dynamic. As a consequence, mutational effects can be hard to rationalize with reference to a single static native structure. We reasoned that deep mutational scanning experiments, which couple molecular function to fitness, should capture mutational effects across multiple conformational states simultaneously. Here, we provide a proof-of-principle that this is indeed the case, using the self-splicing group I intron from Tetrahymena thermophila as a model system. We comprehensively mutagenized two 4-bp segments of the intron. These segments first come together to form the P1 extension (P1ex) helix at the 5’ splice site. Following cleavage at the 5’ splice site, the two halves of the helix dissociate to allow formation of an alternative helix (P10) at the 3’ splice site. Using an in vivo reporter system that couples splicing activity to fitness in E. coli, we demonstrate that fitness is driven jointly by constraints on P1ex and P10 formation. We further show that patterns of epistasis can be used to infer the presence of intramolecular pleiotropy. Using a machine learning approach that allows quantification of mutational effects in a genotype-specific manner, we demonstrate that the fitness landscape can be deconvoluted to implicate P1ex or P10 as the effective genetic background in which molecular fitness is compromised or enhanced. Our results highlight deep mutational scanning as a tool to study alternative conformational states, with the capacity to provide critical insights into the structure, evolution and evolvability of RNAs as dynamic ensembles. Our findings also suggest that, in the future, deep mutational scanning approaches might help reverse-engineer multiple alternative or successive conformations from a single fitness landscape. Public Library of Science 2021-02-01 /pmc/articles/PMC7877785/ /pubmed/33524037 http://dx.doi.org/10.1371/journal.pgen.1009353 Text en © 2021 Soo et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Soo, Valerie W. C.
Swadling, Jacob B.
Faure, Andre J.
Warnecke, Tobias
Fitness landscape of a dynamic RNA structure
title Fitness landscape of a dynamic RNA structure
title_full Fitness landscape of a dynamic RNA structure
title_fullStr Fitness landscape of a dynamic RNA structure
title_full_unstemmed Fitness landscape of a dynamic RNA structure
title_short Fitness landscape of a dynamic RNA structure
title_sort fitness landscape of a dynamic rna structure
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7877785/
https://www.ncbi.nlm.nih.gov/pubmed/33524037
http://dx.doi.org/10.1371/journal.pgen.1009353
work_keys_str_mv AT soovaleriewc fitnesslandscapeofadynamicrnastructure
AT swadlingjacobb fitnesslandscapeofadynamicrnastructure
AT faureandrej fitnesslandscapeofadynamicrnastructure
AT warnecketobias fitnesslandscapeofadynamicrnastructure