Literature DB >> 18212807

Predicting evolution from genomics: experimental evolution of bacteriophage T7.

J J Bull1, I J Molineux.   

Abstract

A wealth of molecular biology has been exploited in designing and interpreting experimental evolution studies with bacteriophage T7. The modest size of its genome (40 kb dsDNA) and the ease of making genetic constructs, combined with the many genetic resources for its host (Escherichia coli), have enabled comprehensive and detailed studies of experimental adaptations. In several studies, the genome was specifically altered (gene knockouts, gene replacements, reordering of genetic elements) such that a priori knowledge of genetics and biochemistry of the phage could be used to predict the pathways of compensatory evolution when the modified phage is adapted to recover fitness. In other work, the phage has been adapted to specific environmental conditions chosen to select phenotypic outcomes with a quantitative basis, and the molecular bases of that evolution have been explored. Predicting the outcomes of these adaptations has been challenging. In hindsight, one-third to one-half of the compensatory nucleotide changes observed during the adaptation can be rationalized based on T7 biology. This rationalization usually only applies at the genetic level-a gene product may be known to be involved in the affected pathway, but it usually remains unknown how the observed change affects activity. The progress is encouraging, but the prediction of experimental evolution pathways remains far from complete, and is still sometimes confounded by observation when an adaptation yields a completely unexpected outcome.

Entities:  

Mesh:

Year:  2008        PMID: 18212807     DOI: 10.1038/sj.hdy.6801087

Source DB:  PubMed          Journal:  Heredity (Edinb)        ISSN: 0018-067X            Impact factor:   3.832


  29 in total

1.  Slow fitness recovery in a codon-modified viral genome.

Authors:  J J Bull; I J Molineux; C O Wilke
Journal:  Mol Biol Evol       Date:  2012-04-24       Impact factor: 16.240

2.  Real time forecasting of near-future evolution.

Authors:  Philip J Gerrish; Paul D Sniegowski
Journal:  J R Soc Interface       Date:  2012-04-18       Impact factor: 4.118

Review 3.  New insights into bacterial adaptation through in vivo and in silico experimental evolution.

Authors:  Thomas Hindré; Carole Knibbe; Guillaume Beslon; Dominique Schneider
Journal:  Nat Rev Microbiol       Date:  2012-03-27       Impact factor: 60.633

Review 4.  Optimality models in the age of experimental evolution and genomics.

Authors:  J J Bull; I-N Wang
Journal:  J Evol Biol       Date:  2010-07-14       Impact factor: 2.411

Review 5.  Experimental macroevolution.

Authors:  Graham Bell
Journal:  Proc Biol Sci       Date:  2016-01-13       Impact factor: 5.349

6.  Multiple genetic pathways to similar fitness limits during viral adaptation to a new host.

Authors:  Andre H Nguyen; Ian J Molineux; Rachael Springman; James J Bull
Journal:  Evolution       Date:  2011-09-20       Impact factor: 3.694

7.  Lethal mutagenesis failure may augment viral adaptation.

Authors:  Matthew L Paff; Steven P Stolte; James J Bull
Journal:  Mol Biol Evol       Date:  2013-10-03       Impact factor: 16.240

8.  Rescue of bacteriophage T7 DNA polymerase of low processivity by suppressor mutations affecting gene 3 endonuclease.

Authors:  Seung-Joo Lee; Kajal Chowdhury; Stanley Tabor; Charles C Richardson
Journal:  J Virol       Date:  2009-06-17       Impact factor: 5.103

Review 9.  Transcription regulation mechanisms of bacteriophages: recent advances and future prospects.

Authors:  Haiquan Yang; Yingfang Ma; Yitian Wang; Haixia Yang; Wei Shen; Xianzhong Chen
Journal:  Bioengineered       Date:  2014 Sep-Oct       Impact factor: 3.269

10.  A tale of tails: Sialidase is key to success in a model of phage therapy against K1-capsulated Escherichia coli.

Authors:  J J Bull; E R Vimr; I J Molineux
Journal:  Virology       Date:  2009-12-16       Impact factor: 3.616

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.