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Love the one you’re with: replicate viral adaptations converge on the same phenotypic change

Parallelism is important because it reveals how inherently stochastic adaptation is. Even as we come to better understand evolutionary forces, stochasticity limits how well we can predict evolutionary outcomes. Here we sought to quantify parallelism and some of its underlying causes by adapting a ba...

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Autores principales: Miller, Craig R., Nagel, Anna C., Scott, LuAnn, Settles, Matt, Joyce, Paul, Wichman, Holly A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4958007/
https://www.ncbi.nlm.nih.gov/pubmed/27547540
http://dx.doi.org/10.7717/peerj.2227
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author Miller, Craig R.
Nagel, Anna C.
Scott, LuAnn
Settles, Matt
Joyce, Paul
Wichman, Holly A.
author_facet Miller, Craig R.
Nagel, Anna C.
Scott, LuAnn
Settles, Matt
Joyce, Paul
Wichman, Holly A.
author_sort Miller, Craig R.
collection PubMed
description Parallelism is important because it reveals how inherently stochastic adaptation is. Even as we come to better understand evolutionary forces, stochasticity limits how well we can predict evolutionary outcomes. Here we sought to quantify parallelism and some of its underlying causes by adapting a bacteriophage (ID11) with nine different first-step mutations, each with eight-fold replication, for 100 passages. This was followed by whole-genome sequencing five isolates from each endpoint. A large amount of variation arose—281 mutational events occurred representing 112 unique mutations. At least 41% of the mutations and 77% of the events were adaptive. Within wells, populations generally experienced complex interference dynamics. The genome locations and counts of mutations were highly uneven: mutations were concentrated in two regulatory elements and three genes and, while 103 of the 112 (92%) of the mutations were observed in ≤4 wells, a few mutations arose many times. 91% of the wells and 81% of the isolates had a mutation in the D-promoter. Parallelism was moderate compared to previous experiments with this system. On average, wells shared 27% of their mutations at the DNA level and 38% when the definition of parallel change is expanded to include the same regulatory feature or residue. About half of the parallelism came from D-promoter mutations. Background had a small but significant effect on parallelism. Similarly, an analyses of epistasis between mutations and their ancestral background was significant, but the result was mostly driven by four individual mutations. A second analysis of epistasis focused on de novo mutations revealed that no isolate ever had more than one D-promoter mutation and that 56 of the 65 isolates lacking a D-promoter mutation had a mutation in genes D and/or E. We assayed time to lysis in four of these mutually exclusive mutations (the two most frequent D-promoter and two in gene D) across four genetic backgrounds. In all cases lysis was delayed. We postulate that because host cells were generally rare (i.e., high multiplicity of infection conditions developed), selection favored phage that delayed lysis to better exploit their current host (i.e., ‘love the one you’re with’). Thus, the vast majority of wells (at least 64 of 68, or 94%) arrived at the same phenotypic solution, but through a variety of genetic changes. We conclude that answering questions about the range of possible adaptive trajectories, parallelism, and the predictability of evolution requires attention to the many biological levels where the process of adaptation plays out.
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spelling pubmed-49580072016-08-19 Love the one you’re with: replicate viral adaptations converge on the same phenotypic change Miller, Craig R. Nagel, Anna C. Scott, LuAnn Settles, Matt Joyce, Paul Wichman, Holly A. PeerJ Evolutionary Studies Parallelism is important because it reveals how inherently stochastic adaptation is. Even as we come to better understand evolutionary forces, stochasticity limits how well we can predict evolutionary outcomes. Here we sought to quantify parallelism and some of its underlying causes by adapting a bacteriophage (ID11) with nine different first-step mutations, each with eight-fold replication, for 100 passages. This was followed by whole-genome sequencing five isolates from each endpoint. A large amount of variation arose—281 mutational events occurred representing 112 unique mutations. At least 41% of the mutations and 77% of the events were adaptive. Within wells, populations generally experienced complex interference dynamics. The genome locations and counts of mutations were highly uneven: mutations were concentrated in two regulatory elements and three genes and, while 103 of the 112 (92%) of the mutations were observed in ≤4 wells, a few mutations arose many times. 91% of the wells and 81% of the isolates had a mutation in the D-promoter. Parallelism was moderate compared to previous experiments with this system. On average, wells shared 27% of their mutations at the DNA level and 38% when the definition of parallel change is expanded to include the same regulatory feature or residue. About half of the parallelism came from D-promoter mutations. Background had a small but significant effect on parallelism. Similarly, an analyses of epistasis between mutations and their ancestral background was significant, but the result was mostly driven by four individual mutations. A second analysis of epistasis focused on de novo mutations revealed that no isolate ever had more than one D-promoter mutation and that 56 of the 65 isolates lacking a D-promoter mutation had a mutation in genes D and/or E. We assayed time to lysis in four of these mutually exclusive mutations (the two most frequent D-promoter and two in gene D) across four genetic backgrounds. In all cases lysis was delayed. We postulate that because host cells were generally rare (i.e., high multiplicity of infection conditions developed), selection favored phage that delayed lysis to better exploit their current host (i.e., ‘love the one you’re with’). Thus, the vast majority of wells (at least 64 of 68, or 94%) arrived at the same phenotypic solution, but through a variety of genetic changes. We conclude that answering questions about the range of possible adaptive trajectories, parallelism, and the predictability of evolution requires attention to the many biological levels where the process of adaptation plays out. PeerJ Inc. 2016-07-19 /pmc/articles/PMC4958007/ /pubmed/27547540 http://dx.doi.org/10.7717/peerj.2227 Text en ©2016 Miller 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, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Evolutionary Studies
Miller, Craig R.
Nagel, Anna C.
Scott, LuAnn
Settles, Matt
Joyce, Paul
Wichman, Holly A.
Love the one you’re with: replicate viral adaptations converge on the same phenotypic change
title Love the one you’re with: replicate viral adaptations converge on the same phenotypic change
title_full Love the one you’re with: replicate viral adaptations converge on the same phenotypic change
title_fullStr Love the one you’re with: replicate viral adaptations converge on the same phenotypic change
title_full_unstemmed Love the one you’re with: replicate viral adaptations converge on the same phenotypic change
title_short Love the one you’re with: replicate viral adaptations converge on the same phenotypic change
title_sort love the one you’re with: replicate viral adaptations converge on the same phenotypic change
topic Evolutionary Studies
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4958007/
https://www.ncbi.nlm.nih.gov/pubmed/27547540
http://dx.doi.org/10.7717/peerj.2227
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