Evidence map›Paper›PMID 22429718›Full record

ArticleBMC evolutionary biology2012

A common, non-optimal phenotypic endpoint in experimental adaptations of bacteriophage lysis time.

Lynne Chantranupong, Richard H Heineman

Abstract read
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Article in BMC evolutionary biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Host-Directed Antiviral Therapy.Clinical microbiology reviews · 2020
    Review
  8. Article
  9. Mechanisms of viral mutation.Cellular and molecular life sciences : CMLS · 2016
    Review
  10. Article
  11. Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Lynne ChantranupongDepartment of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Richard H Heineman

Funding

MINNESOTA PAIN RESEARCH TRAINING PROGRAMT32DE007288 · NIDCR · UNIVERSITY OF MINNESOTA TWIN CITIES · PI HERZBERG, MARK C · 1996 to 2011
$8.8M
Experimental viral evolution at high mutation rateR01GM057756 · NIGMS · UNIVERSITY OF TEXAS AUSTIN · PI BULL, JAMES J · 1998 to 2013
$2.9M
Howard Hughes Medical Institute 52005907NIDCR NIH HHS T32DE007288NIGMS NIH HHS R01 GM057756PHS HHS 57756
6 · The paper itself

Abstract

backgroundOptimality models of evolution, which ignore genetic details and focus on natural selection, are widely used but sometimes criticized as oversimplifications. Their utility for quantitatively predicting phenotypic evolution can be tested experimentally. One such model predicts optimal bacteriophage lysis interval, how long a virus should produce progeny before lysing its host bacterium to release them. The genetic basis of this life history trait is well studied in many easily propagated phages, making it possible to test the model across a variety of environments and taxa.

resultsWe adapted two related small single-stranded DNA phages, ΦX174 and ST-1, to various conditions. The model predicted the evolution of the lysis interval in response to host density and other environmental factors. In all cases the initial phages lysed later than predicted. The ΦX174 lysis interval did not evolve detectably when the phage was adapted to normal hosts, indicating complete failure of optimality predictions. ΦX174 grown on slyD-defective hosts which initially entirely prevented lysis readily recovered to a lysis interval similar to that attained on normal hosts. Finally, the lysis interval still evolved to the same endpoint when the environment was altered to delay optimal lysis interval. ST-1 lysis interval evolved to be ~2 min shorter, qualitatively in accord with predictions. However, there were no changes in the single known lysis gene. Part of ST-1's total lysis time evolution consisted of an earlier start to progeny production, an unpredicted phenotypic response outside the boundaries of the optimality model.

conclusionsThe consistent failure of the optimality model suggests that constraint and genetic details affect quantitative and even qualitative success of optimality predictions. Several features of ST-1 adaptation show that lysis time is best understood as an output of multiple traits, rather than in isolation.

Indexed as

Adaptation, PhysiologicalModels, BiologicalPhenotypeBacteriophagesBiological EvolutionEscherichia coliTime Factors

Identifiers

PMID22429718
PMCPMC3324380

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.