» Articles » PMID: 18832356

A Simple Formula for Obtaining Markedly Improved Mutation Rate Estimates

Overview
Journal Genetics
Specialty Genetics
Date 2008 Oct 4
PMID 18832356
Citations 15
Authors
Affiliations
Soon will be listed here.
Abstract

In previous work by M. E. Jones and colleagues, it was shown that mutation rate estimates can be improved and corresponding confidence intervals tightened by following a very easy modification of the standard fluctuation assay: cultures are grown to a larger-than-usual final density, and mutants are screened for in only a fraction of the culture. Surprisingly, this very promising development has received limited attention, perhaps because there has been no efficient way to generate the predicted mutant distribution to obtain non-moment-based estimates of the mutation rate. Here, the improved fluctuation assay discovered by Jones and colleagues is made amenable to quantile-based, likelihood, and other Bayesian methods by a simple recursion formula that efficiently generates the entire mutant distribution after growth and dilution. This formula makes possible a further protocol improvement: grow cultures as large as is experimentally possible and severely dilute before plating to obtain easily countable numbers of mutants. A preliminary look at likelihood surfaces suggests that this easy protocol adjustment gives markedly improved mutation rate estimates and confidence intervals.

Citing Articles

Topical niclosamide (ATx201) reduces Staphylococcus aureus colonization and increases Shannon diversity of the skin microbiome in atopic dermatitis patients in a randomized, double-blind, placebo-controlled Phase 2 trial.

Weiss A, Delavenne E, Matias C, Lagler H, Simon D, Li P Clin Transl Med. 2022; 12(5):e790.

PMID: 35522900 PMC: 9076020. DOI: 10.1002/ctm2.790.


Polygenic Adaptation and Clonal Interference Enable Sustained Diversity in Experimental Pseudomonas aeruginosa Populations.

Harris K, Flynn K, Cooper V Mol Biol Evol. 2021; 38(12):5359-5375.

PMID: 34410431 PMC: 8662654. DOI: 10.1093/molbev/msab248.


Type III-A CRISPR immunity promotes mutagenesis of staphylococci.

Mo C, Mathai J, Rostol J, Varble A, Banh D, Marraffini L Nature. 2021; 592(7855):611-615.

PMID: 33828299 PMC: 8820005. DOI: 10.1038/s41586-021-03440-3.


The fitness cost of mismatch repair mutators in Saccharomyces cerevisiae: partitioning the mutational load.

Galeota-Sprung B, Guindon B, Sniegowski P Heredity (Edinb). 2019; 124(1):50-61.

PMID: 31515531 PMC: 6906417. DOI: 10.1038/s41437-019-0267-2.


High mutation rates limit evolutionary adaptation in Escherichia coli.

Sprouffske K, Aguilar-Rodriguez J, Sniegowski P, Wagner A PLoS Genet. 2018; 14(4):e1007324.

PMID: 29702649 PMC: 5942850. DOI: 10.1371/journal.pgen.1007324.


References
1.
Stewart F, Gordon D, Levin B . Fluctuation analysis: the probability distribution of the number of mutants under different conditions. Genetics. 1990; 124(1):175-85. PMC: 1203904. DOI: 10.1093/genetics/124.1.175. View

2.
Jones M, Thomas S, Clarke K . The application of a linear algebra to the analysis of mutation rates. J Theor Biol. 1999; 199(1):11-23. DOI: 10.1006/jtbi.1999.0933. View

3.
Jones M . An algorithm accounting for plating efficiency in estimating spontaneous mutation rates. Comput Biol Med. 1993; 23(6):455-61. DOI: 10.1016/0010-4825(93)90093-g. View

4.
Jones M, Thomas S, Rogers A . Luria-Delbrück fluctuation experiments: design and analysis. Genetics. 1994; 136(3):1209-16. PMC: 1205875. DOI: 10.1093/genetics/136.3.1209. View

5.
Kendal W, Frost P . Pitfalls and practice of Luria-Delbrück fluctuation analysis: a review. Cancer Res. 1988; 48(5):1060-5. View