Predicting evolution of the transcription regulatory network in a bacteriophage

Daniel J. Garry, Adam J. Meyer, Jared W. Ellefson, James J. Bull, Andrew D. Ellington

Research output: Contribution to journalArticlepeer-review

Abstract

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 evolutionwould have fallenwithin 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.

Original languageEnglish (US)
Pages (from-to)2587-2595
Number of pages9
JournalGenome biology and evolution
Volume10
Issue number10
DOIs
StatePublished - Oct 2018
Externally publishedYes

Bibliographical note

Funding Information:
This workwas supported by grants from theWelch Foundation (F-1654), the Air Force Office of Scientific Research (FA9550- 14-1-0089), the Defense Advanced Research Projects Agency (HR0011-15-C-0095), and the National Science Foundation (MCB-0943383 and FA9550-10-1-0169).

Funding Information:
This work was supported by grants from the Welch Foundation (F-1654), the Air Force Office of Scientific Research (FA9550-14-1-0089), the Defense Advanced Research Projects Agency (HR0011-15-C-0095), and the National Science Foundation (MCB-0943383 and FA9550-10-1-0169).

Publisher Copyright:
© 2018 Oxford University Press. All rights reserved.

Keywords

  • Evolutionary path
  • Prediction.
  • Promoter
  • Sequence space
  • T7

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