Literature DB >> 18254683

Optimal foraging by bacteriophages through host avoidance.

Richard H Heineman1, Rachael Springman, James J Bull.   

Abstract

Optimal foraging theory explains diet restriction as an adaptation to best utilize an array of foods differing in quality, the poorest items not worth the lost opportunity of finding better ones. Although optimal foraging has traditionally been applied to animal behavior, the model is easily applied to viral host range, which is genetically determined. The usual perspective for bacteriophages (bacterial viruses) is that expanding host range is always advantageous if fitness on former hosts is not compromised. However, foraging theory identifies conditions favoring avoidance of poor hosts even if larger host ranges have no intrinsic costs. Bacteriophage T7 rapidly evolved to discriminate among different Escherichia coli strains when one host strain was engineered to kill infecting phages but the other remained productive. After modifying bacteria to yield more subtle fitness effects on T7, we tested qualitative predictions of optimal foraging theory by competing broad and narrow host range phages against each other. Consistent with the foraging model, diet restriction was favored when good hosts were common or there was a large difference in host quality. Contrary to the model, the direction of selection was affected by the density of poor hosts because being able to discriminate was costly.

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Year:  2008        PMID: 18254683     DOI: 10.1086/528962

Source DB:  PubMed          Journal:  Am Nat        ISSN: 0003-0147            Impact factor:   3.926


  28 in total

1.  Structure of the receptor-binding carboxy-terminal domain of bacteriophage T7 tail fibers.

Authors:  Carmela Garcia-Doval; Mark J van Raaij
Journal:  Proc Natl Acad Sci U S A       Date:  2012-05-29       Impact factor: 11.205

2.  Resource availability affects the structure of a natural bacteria-bacteriophage community.

Authors:  Timothée Poisot; Gildas Lepennetier; Esteban Martinez; Johan Ramsayer; Michael E Hochberg
Journal:  Biol Lett       Date:  2010-10-20       Impact factor: 3.703

Review 3.  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

4.  Isolation of Polyvalent Bacteriophages by Sequential Multiple-Host Approaches.

Authors:  Pingfeng Yu; Jacques Mathieu; Mengyan Li; Zhaoyi Dai; Pedro J J Alvarez
Journal:  Appl Environ Microbiol       Date:  2015-11-20       Impact factor: 4.792

5.  Viral resistance evolution fully escapes a rationally designed lethal inhibitor.

Authors:  Thomas E Keller; Ian J Molineux; James J Bull
Journal:  Mol Biol Evol       Date:  2009-06-03       Impact factor: 16.240

6.  Plant root growth and the marginal value theorem.

Authors:  Gordon G McNickle; James F Cahill
Journal:  Proc Natl Acad Sci U S A       Date:  2009-03-05       Impact factor: 11.205

7.  Fitness benefits of low infectivity in a spatially structured population of bacteriophages.

Authors:  Pavitra Roychoudhury; Neelima Shrestha; Valorie R Wiss; Stephen M Krone
Journal:  Proc Biol Sci       Date:  2013-11-13       Impact factor: 5.349

8.  Experimental evolution of a microbial predator's ability to find prey.

Authors:  Kristina L Hillesland; Gregory J Velicer; Richard E Lenski
Journal:  Proc Biol Sci       Date:  2009-02-07       Impact factor: 5.349

Review 9.  Using artificial systems to explore the ecology and evolution of symbioses.

Authors:  Babak Momeni; Chi-Chun Chen; Kristina L Hillesland; Adam Waite; Wenying Shou
Journal:  Cell Mol Life Sci       Date:  2011-03-23       Impact factor: 9.261

10.  Tradeoffs in bacteriophage life histories.

Authors:  Eric C Keen
Journal:  Bacteriophage       Date:  2014-02-27
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