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Predicting Evolution of the Transcription Regulatory Network in a Bacteriophage
Prediction of evolutionary trajectories has been an elusive goal, requiring a deep knowledge of underlying mechanisms that relate genotype to phenotype plus understanding how phenotype impacts organismal fitness. We tested our ability to predict molecular regulatory evolution in a bacteriophage (T7)...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6171733/ https://www.ncbi.nlm.nih.gov/pubmed/30184065 http://dx.doi.org/10.1093/gbe/evy191 |
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author | Garry, Daniel J Meyer, Adam J Ellefson, Jared W Bull, James J Ellington, Andrew D |
author_facet | Garry, Daniel J Meyer, Adam J Ellefson, Jared W Bull, James J Ellington, Andrew D |
author_sort | Garry, Daniel J |
collection | PubMed |
description | Prediction of evolutionary trajectories has been an elusive goal, requiring a deep knowledge of underlying mechanisms that relate genotype to phenotype plus understanding how phenotype impacts organismal fitness. We tested our ability to predict molecular regulatory evolution in a bacteriophage (T7) whose RNA polymerase (RNAP) was altered to recognize a heterologous promoter differing by three nucleotides from the wild-type promoter. A mutant of wild-type T7 lacking its RNAP gene was passaged on a bacterial strain providing the novel RNAP in trans. Higher fitness rapidly evolved. Predicting the evolutionary trajectory of this adaptation used measured in vitro transcription rates of the novel RNAP on the six promoter sequences capturing all possible one-step pathways between the wild-type and the heterologous promoter sequences. The predictions captured some of the regulatory evolution but failed both in explaining 1) a set of T7 promoters that consistently failed to evolve and 2) some promoter evolution that fell outside the expected one-step pathways. Had a more comprehensive set of transcription assays been undertaken initially, all promoter evolution would have fallen within predicted bounds, but the lack of evolution in some promoters is unresolved. Overall, this study points toward the increasing feasibility of predicting evolution in well-characterized, simple systems. |
format | Online Article Text |
id | pubmed-6171733 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-61717332018-10-09 Predicting Evolution of the Transcription Regulatory Network in a Bacteriophage Garry, Daniel J Meyer, Adam J Ellefson, Jared W Bull, James J Ellington, Andrew D Genome Biol Evol Research Article Prediction of evolutionary trajectories has been an elusive goal, requiring a deep knowledge of underlying mechanisms that relate genotype to phenotype plus understanding how phenotype impacts organismal fitness. We tested our ability to predict molecular regulatory evolution in a bacteriophage (T7) whose RNA polymerase (RNAP) was altered to recognize a heterologous promoter differing by three nucleotides from the wild-type promoter. A mutant of wild-type T7 lacking its RNAP gene was passaged on a bacterial strain providing the novel RNAP in trans. Higher fitness rapidly evolved. Predicting the evolutionary trajectory of this adaptation used measured in vitro transcription rates of the novel RNAP on the six promoter sequences capturing all possible one-step pathways between the wild-type and the heterologous promoter sequences. The predictions captured some of the regulatory evolution but failed both in explaining 1) a set of T7 promoters that consistently failed to evolve and 2) some promoter evolution that fell outside the expected one-step pathways. Had a more comprehensive set of transcription assays been undertaken initially, all promoter evolution would have fallen within predicted bounds, but the lack of evolution in some promoters is unresolved. Overall, this study points toward the increasing feasibility of predicting evolution in well-characterized, simple systems. Oxford University Press 2018-09-01 /pmc/articles/PMC6171733/ /pubmed/30184065 http://dx.doi.org/10.1093/gbe/evy191 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Garry, Daniel J Meyer, Adam J Ellefson, Jared W Bull, James J Ellington, Andrew D Predicting Evolution of the Transcription Regulatory Network in a Bacteriophage |
title | Predicting Evolution of the Transcription Regulatory Network in a Bacteriophage |
title_full | Predicting Evolution of the Transcription Regulatory Network in a Bacteriophage |
title_fullStr | Predicting Evolution of the Transcription Regulatory Network in a Bacteriophage |
title_full_unstemmed | Predicting Evolution of the Transcription Regulatory Network in a Bacteriophage |
title_short | Predicting Evolution of the Transcription Regulatory Network in a Bacteriophage |
title_sort | predicting evolution of the transcription regulatory network in a bacteriophage |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6171733/ https://www.ncbi.nlm.nih.gov/pubmed/30184065 http://dx.doi.org/10.1093/gbe/evy191 |
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