Literature DB >> 10610800

Determining mutation rates in bacterial populations.

W A Rosche1, P L Foster.   

Abstract

When properly determined, spontaneous mutation rates are a more accurate and biologically meaningful reflection of underlying mutagenic mechanisms than are mutant frequencies. Because bacteria grow exponentially and mutations arise stochastically, methods to estimate mutation rates depend on theoretical models that describe the distribution of mutant numbers among parallel cultures, as in the original Luria-Delbr]uck fluctuation analysis. An accurate determination of mutation rate depends on understanding the strengths and limitations of these methods, and how to design fluctuation assays to optimize a given method. In this paper we describe a number of methods to estimate mutation rates, give brief accounts of their derivations, and discuss how they behave under various experimental conditions. Copyright 2000 Academic Press.

Mesh:

Year:  2000        PMID: 10610800      PMCID: PMC2932672          DOI: 10.1006/meth.1999.0901

Source DB:  PubMed          Journal:  Methods        ISSN: 1046-2023            Impact factor:   3.608


  19 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.  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

3.  Destabilization of simple repetitive DNA sequences by transcription in yeast.

Authors:  M Wierdl; C N Greene; A Datta; S Jinks-Robertson; T D Petes
Journal:  Genetics       Date:  1996-06       Impact factor: 4.562

4.  A modified Luria-Delbrück fluctuation assay for estimating and comparing mutation rates.

Authors:  G J Crane; S M Thomas; M E Jones
Journal:  Mutat Res       Date:  1996-07-22       Impact factor: 2.433

5.  Bayesian procedures for the estimation of mutation rates from fluctuation experiments.

Authors:  G Asteris; S Sarkar
Journal:  Genetics       Date:  1996-01       Impact factor: 4.562

6.  A genetic strategy to demonstrate the occurrence of spontaneous mutations in nondividing cells within colonies of Escherichia coli.

Authors:  M Reddy; J Gowrishankar
Journal:  Genetics       Date:  1997-11       Impact factor: 4.562

7.  The origin of mutants.

Authors:  J Cairns; J Overbaugh; S Miller
Journal:  Nature       Date:  1988-09-08       Impact factor: 49.962

8.  The distribution of the numbers of mutants in bacterial populations.

Authors:  D E LEA; C A COULSON
Journal:  J Genet       Date:  1949-12       Impact factor: 1.166

Review 9.  Adaptive mutation: the uses of adversity.

Authors:  P L Foster
Journal:  Annu Rev Microbiol       Date:  1993       Impact factor: 15.500

10.  Luria-Delbrück fluctuation experiments: design and analysis.

Authors:  M E Jones; S M Thomas; A Rogers
Journal:  Genetics       Date:  1994-03       Impact factor: 4.562

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  195 in total

1.  Role of the dinB gene product in spontaneous mutation in Escherichia coli with an impaired replicative polymerase.

Authors:  B S Strauss; R Roberts; L Francis; P Pouryazdanparast
Journal:  J Bacteriol       Date:  2000-12       Impact factor: 3.490

2.  Structure and temporal dynamics of populations within wheat streak mosaic virus isolates.

Authors:  J S Hall; R French; T J Morris; D C Stenger
Journal:  J Virol       Date:  2001-11       Impact factor: 5.103

3.  A quantitative assay for telomere protection in Saccharomyces cerevisiae.

Authors:  Michelle L DuBois; Zara W Haimberger; Martin W McIntosh; Daniel E Gottschling
Journal:  Genetics       Date:  2002-07       Impact factor: 4.562

4.  Adaptive mutation: general mutagenesis is not a programmed response to stress but results from rare coamplification of dinB with lac.

Authors:  E Susan Slechta; Kim L Bunny; Elisabeth Kugelberg; Eric Kofoid; Dan I Andersson; John R Roth
Journal:  Proc Natl Acad Sci U S A       Date:  2003-10-14       Impact factor: 11.205

5.  Adaptive mutation: how growth under selection stimulates Lac(+) reversion by increasing target copy number.

Authors:  John R Roth; Dan I Andersson
Journal:  J Bacteriol       Date:  2004-08       Impact factor: 3.490

6.  Stochastic processes influence stationary-phase decisions in Bacillus subtilis.

Authors:  Heather Maughan; Wayne L Nicholson
Journal:  J Bacteriol       Date:  2004-04       Impact factor: 3.490

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

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

8.  Roles of YqjH and YqjW, homologs of the Escherichia coli UmuC/DinB or Y superfamily of DNA polymerases, in stationary-phase mutagenesis and UV-induced mutagenesis of Bacillus subtilis.

Authors:  Huang-Mo Sung; Gabriel Yeamans; Christian A Ross; Ronald E Yasbin
Journal:  J Bacteriol       Date:  2003-04       Impact factor: 3.490

9.  Experimental adaptation of Salmonella typhimurium to mice.

Authors:  Annika I Nilsson; Elisabeth Kugelberg; Otto G Berg; Dan I Andersson
Journal:  Genetics       Date:  2004-11       Impact factor: 4.562

Review 10.  Detecting Rare Mutations and DNA Damage with Sequencing-Based Methods.

Authors:  Daniel B Sloan; Amanda K Broz; Joel Sharbrough; Zhiqiang Wu
Journal:  Trends Biotechnol       Date:  2018-03-14       Impact factor: 19.536

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