Literature DB >> 7982567

Fluctuation tests: how reliable are the estimates of mutation rates?

F M Stewart1.   

Abstract

Fifty one years ago, Luria and Delbrück published in Genetics a paper that was to become a classic. In it they proved, beyond all reasonable doubt, that bacteria were mutating to phage resistance long before they could have encountered any bacteriophage. Luria and Delbrück also showed how the same experimental data could be used to estimate bacterial mutation rates. Since that time and in many different contexts the methods that they introduced have been used to estimate mutation rates. However, little seems to be known about the errors to be expected in such estimates. In what follows I examine how much uncertainty in the estimates is to be expected merely on the basis of the stochastic variability inherent in the sampling process. On the basis of this examination I question a few traditional ideas and conclude with some practical suggestions. The results were obtained by stimulation. It is my hope that they may inspire others to provide a rigorous theoretical basis for such calculations.

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Year:  1994        PMID: 7982567      PMCID: PMC1206060     

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


  4 in total

Review 1.  Haldane's solution of the Luria-Delbrück distribution.

Authors:  S Sarkar
Journal:  Genetics       Date:  1991-02       Impact factor: 4.562

2.  On fluctuation analysis: a new, simple and efficient method for computing the expected number of mutants.

Authors:  S Sarkar; W T Ma; G H Sandri
Journal:  Genetica       Date:  1992       Impact factor: 1.082

3.  Mutations of Bacteria from Virus Sensitivity to Virus Resistance.

Authors:  S E Luria; M Delbrück
Journal:  Genetics       Date:  1943-11       Impact factor: 4.562

4.  Fluctuation analysis: the probability distribution of the number of mutants under different conditions.

Authors:  F M Stewart; D M Gordon; B R Levin
Journal:  Genetics       Date:  1990-01       Impact factor: 4.562

  4 in total
  32 in total

Review 1.  Determining mutation rates in bacterial populations.

Authors:  W A Rosche; P L Foster
Journal:  Methods       Date:  2000-01       Impact factor: 3.608

2.  Spontaneously arising mutL mutators in evolving Escherichia coli populations are the result of changes in repeat length.

Authors:  Aaron C Shaver; Paul D Sniegowski
Journal:  J Bacteriol       Date:  2003-10       Impact factor: 3.490

3.  A Bayesian two-level model for fluctuation assay.

Authors:  Qi Zheng
Journal:  Genetica       Date:  2012-03-07       Impact factor: 1.082

4.  Methods for determining spontaneous mutation rates.

Authors:  Patricia L Foster
Journal:  Methods Enzymol       Date:  2006       Impact factor: 1.600

5.  Identifying mutator phenotypes among fluoroquinolone-resistant strains of Streptococcus pneumoniae using fluctuation analysis.

Authors:  Carolyn V Gould; Paul D Sniegowski; Mikhail Shchepetov; Joshua P Metlay; Jeffrey N Weiser
Journal:  Antimicrob Agents Chemother       Date:  2007-07-30       Impact factor: 5.191

6.  Fluctuation analysis CalculatOR: a web tool for the determination of mutation rate using Luria-Delbruck fluctuation analysis.

Authors:  Brandon M Hall; Chang-Xing Ma; Ping Liang; Keshav K Singh
Journal:  Bioinformatics       Date:  2009-04-15       Impact factor: 6.937

7.  A simple formula for obtaining markedly improved mutation rate estimates.

Authors:  Philip Gerrish
Journal:  Genetics       Date:  2008-10-01       Impact factor: 4.562

8.  Proliferation model dependence in fluctuation analysis: the neutral case.

Authors:  Wolfgang P Angerer
Journal:  J Math Biol       Date:  2009-08-26       Impact factor: 2.259

9.  The spontaneous appearance rate of the yeast prion [PSI+] and its implications for the evolution of the evolvability properties of the [PSI+] system.

Authors:  Alex K Lancaster; J Patrick Bardill; Heather L True; Joanna Masel
Journal:  Genetics       Date:  2009-11-16       Impact factor: 4.562

10.  Estimating the per-base-pair mutation rate in the yeast Saccharomyces cerevisiae.

Authors:  Gregory I Lang; Andrew W Murray
Journal:  Genetics       Date:  2008-01       Impact factor: 4.562

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