Literature DB >> 27113784

A second look at the final number of cells in a fluctuation experiment.

Qi Zheng1.   

Abstract

In a fluctuation experiment, the number of cells existing in a culture immediately before plating (commonly known as Nt) varies across the parallel cultures. However, most existing mathematical models for fluctuation assay data do not recognize the variation in Nt. Despite repeated attempts in the past to integrate this source of variability in the estimation of microbial mutation rates, several questions of practical importance remain unanswered. The present investigation finds that the variation needs accounting for only when the coefficient of variation for Nt is large, and experimental data suggest that the coefficient of variation is often moderate or small. Moreover, an increase in the inoculum size can reduce the coefficient of variation. Through extensive simulation, several existing methods that accommodate the variation in Nt are compared. It was found that a newly devised likelihood method based on the existing gamma mixture model outperforms other existing methods. The investigation focuses on the estimation of mutation rates using the Lea-Coulson model, under which mutation is selectively neutral; however, the paper also explores the major findings' implications for the comparison of mutation rates using the likelihood ratio test, and for the estimation of mutation rates using the Mandelbrot-Koch model that allows for non-neutral mutations.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Keywords:  Gamma mixture model; Likelihood ratio test; Mutation rate; Rifampin resistance

Mesh:

Year:  2016        PMID: 27113784     DOI: 10.1016/j.jtbi.2016.04.027

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  3 in total

1.  Quantitative Analysis of the Rates for Repeat-Mediated Genome Instability in a Yeast Experimental System.

Authors:  Elina A Radchenko; Ryan J McGinty; Anna Y Aksenova; Alexander J Neil; Sergei M Mirkin
Journal:  Methods Mol Biol       Date:  2018

2.  rSalvador: An R Package for the Fluctuation Experiment.

Authors:  Qi Zheng
Journal:  G3 (Bethesda)       Date:  2017-12-04       Impact factor: 3.154

3.  Spontaneous mutation rate is a plastic trait associated with population density across domains of life.

Authors:  Rok Krašovec; Huw Richards; Danna R Gifford; Charlie Hatcher; Katy J Faulkner; Roman V Belavkin; Alastair Channon; Elizabeth Aston; Andrew J McBain; Christopher G Knight
Journal:  PLoS Biol       Date:  2017-08-24       Impact factor: 8.029

  3 in total

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