Literature DB >> 7692255

Accounting for plating efficiency when estimating spontaneous mutation rates.

M E Jones1.   

Abstract

When the spontaneous mutation rate mu in mammalian cell cultures is estimated using Luria-Delbrück fluctuation analysis, many factors contribute to the unreliability of the estimate. Some of these have been documented by Featherstone et al. (1987) and by Kendal and Frost (1988). In particular, the plating efficiencies for mammalian cells are often much less than 100%, and this can be taken into account. A derivation of a generalized P0 estimator, mg, based on the classical P0 estimator of Luria and Delbrück (1943) is offered. In an experiment involving C cultures, of which z exhibit no mutant colonies, and in which the plating efficiency is p, (0 < p < 1), the estimated mean number of mutations per culture is given by [formula: see text] The classical P0 estimator is shown to be the limiting case of mg as plating efficiency tends to 100%.

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Year:  1993        PMID: 7692255     DOI: 10.1016/0165-1161(93)90146-q

Source DB:  PubMed          Journal:  Mutat Res        ISSN: 0027-5107            Impact factor:   2.433


  5 in total

1.  Methods for determining spontaneous mutation rates.

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

Review 2.  A practical guide to measuring mutation rates in antibiotic resistance.

Authors:  Cassie F Pope; Denise M O'Sullivan; Timothy D McHugh; Stephen H Gillespie
Journal:  Antimicrob Agents Chemother       Date:  2008-02-04       Impact factor: 5.191

3.  Frequency, spectrum, and nonzero fitness costs of resistance to myxopyronin in Staphylococcus aureus.

Authors:  Aashish Srivastava; David Degen; Yon W Ebright; Richard H Ebright
Journal:  Antimicrob Agents Chemother       Date:  2012-09-24       Impact factor: 5.191

4.  Competition for nutritional resources masks the true frequency of bacterial mutants.

Authors:  Henrique Iglesias Neves; Gabriella Trombini Machado; Taíssa Cristina Dos Santos Ramos; Hyun Mo Yang; Ezra Yagil; Beny Spira
Journal:  BMC Biol       Date:  2020-12-14       Impact factor: 7.431

5.  bz-rates: A Web Tool to Estimate Mutation Rates from Fluctuation Analysis.

Authors:  Alexandre Gillet-Markowska; Guillaume Louvel; Gilles Fischer
Journal:  G3 (Bethesda)       Date:  2015-09-02       Impact factor: 3.154

  5 in total

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