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

Sarkar, Sahotra; T., W.; Sandri, G.

doi:10.1007/bf00120324

Cited by 176 publications

(169 citation statements)

References 11 publications

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“…Ninety-five percent confidence intervals were also calculated (Rosche and Foster 2000). Calculation of mutation rate was performed using the Ma-Sandri-Sarkar (MSS) method (Sarkar et al 1992) as described in Rosche and Foster (2000). We wrote a VB.net program (Table S1, K. Seier) that performs the recursive calculations necessary to determine the M value by the MSS.…”

Section: Methodsmentioning

confidence: 99%

Insights Into Mutagenesis Using Escherichia coli Chromosomal lacZ Strains That Enable Detection of a Wide Spectrum of Mutational Events

et al. 2011

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Strand misalignments at DNA repeats during replication are implicated in mutational hotspots. To study these events, we have generated strains carrying mutations in the Escherichia coli chromosomal lacZ gene that revert via deletion of a short duplicated sequence or by template switching within imperfect inverted repeat (quasipalindrome, QP) sequences. Using these strains, we demonstrate that mutation of the distal repeat of a quasipalindrome, with respect to replication fork movement, is about 10-fold higher than the proximal repeat, consistent with more common template switching on the leading strand. The leading strand bias was lost in the absence of exonucleases I and VII, suggesting that it results from more efficient suppression of template switching by 39 exonucleases targeted to the lagging strand. The loss of 39 exonucleases has no effect on strand misalignment at direct repeats to produce deletion. To compare these events to other mutations, we have reengineered reporters (designed by Cupples and Miller 1989) that detect specific base substitutions or frameshifts in lacZ with the reverting lacZ locus on the chromosome rather than an F9 element. This set allows rapid screening of potential mutagens, environmental conditions, or genetic loci for effects on a broad set of mutational events. We found that hydroxyurea (HU), which depletes dNTP pools, slightly elevated templated mutations at inverted repeats but had no effect on deletions, simple frameshifts, or base substitutions. Mutations in nucleotide diphosphate kinase, ndk, significantly elevated simple mutations but had little effect on the templated class. Zebularine, a cytosine analog, elevated all classes.

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Section: Methodsmentioning

confidence: 99%

Insights Into Mutagenesis Using Escherichia coli Chromosomal lacZ Strains That Enable Detection of a Wide Spectrum of Mutational Events

et al. 2011

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“…The mutation rate is defined as the probability of a cell undergoing a mutation in its lifetime and expressed per microsatellite per cell per generation. We used two different approaches for estimating the mutation rate: (i) a method of the mean developed by Luria and Delbruck (7) and (ii) a maximumlikelihood method (8,9). The method of the mean is momentbased, whereby the mutation rate is estimated as a function of the sample mean of the number of mutants.…”

Section: Statistical Analysis and Estimation Of Mutation Ratementioning

confidence: 99%

“…The probability distribution of the number of mutants is nonstandard. The maximum-likelihood approach utilizes a recursive algorithm to compute this probability distribution and construct it as a function of the unknown mutation rate (9). The mutation rate was estimated from this function.…”

Section: Statistical Analysis and Estimation Of Mutation Ratementioning

confidence: 99%

Identification of frame-shift intermediate mutant cells

Gasché

␣Chang

Goel

et al. 2003

Proc. Natl. Acad. Sci. U.S.A.

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Frame-shift mutations at microsatellites occur as a time-dependent function of polymerase errors followed by failure of postreplicational mismatch repair. A cell-culture system was developed that allows identification of intermediate mutant cells that carry the mutation on a single DNA strand after the initial DNA polymerase errors. A plasmid was constructed that contained 13 repeats of a poly(dC-dA)⅐poly(dGdT) oligonucleotide immediately after the translation initiation codon of the enhanced GFP (EGFP) gene, shifting the EGFP gene out of its proper reading frame. The plasmid was introduced into human mismatch repair-deficient (HCT116, hMLH1-mutated) and mismatch repair-proficient (HCT116؉chr3, hMLH1 wild type) colorectal cancer cells. After frame-shift mutations occurred that restored the EGFP reading frame, EGFP-expressing cells were detected, and two distinct fluorescent populations, M1 (dim cells) and M2 (bright cells), were identified. M1 cell numbers were stable, whereas M2 cells accumulated over time. In HCT116, single M2 cells gave rise to fluorescent colonies that carried a 2-bp deletion at the (CA)13 microsatellite. Twenty-eight percent of single M1 cells, however, gave rise to colonies with a mixed fluorescence pattern that carried both (CA)13 and (CA)12 microsatellites. It is likely that M1 cells represent intermediate mutants that carry (CA)13⅐(GT)12 heteroduplexes. Although the mutation rate in HCT116 cell clones (6.2 ؋ 10 ؊4 ) was 30 times higher than in HCT116؉chr3 (1.9 ؋ 10 ؊5 ), the proportion of M1 cells in culture did not significantly differ between HCT116 (5.87 ؋ 10 ؊3 ) and HCT116؉chr3 (4.13 ؋ 10 ؊3 ), indicating that the generation of intermediate mutants is not affected by mismatch-repair proficiency. mismatch repair ͉ frame-shift mutation ͉ microsatellite instability ͉ mutation rate

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“…The Ma-Sandri-Sarkar Maximum Likelihood (MSS-ML) method (Sarkar et al 1992), implemented in a custom-made program (Couce and Blázquez 2011), was used to yield an estimate of m = 1.19 3 10 27 and a 95% confidence interval of (1.85 3 10 27 -0.65 3 10 27 ). To characterize the genetic diversity within the glpT locus, two independent colonies per population were picked at random by proximity to arbitrary points.…”

Section: Experimental Systemmentioning

confidence: 99%

Determinants of Genetic Diversity of Spontaneous Drug Resistance in Bacteria

2016

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Any pathogen population sufficiently large is expected to harbor spontaneous drug-resistant mutants, often responsible for disease relapse after antibiotic therapy. It is seldom appreciated, however, that while larger populations harbor more mutants, the abundance distribution of these mutants is expected to be markedly uneven. This is because a larger population size allows early mutants to expand for longer, exacerbating their predominance in the final mutant subpopulation. Here, we investigate the extent to which this reduction in evenness can constrain the genetic diversity of spontaneous drug resistance in bacteria. Combining theory and experiments, we show that even small variations in growth rate between resistant mutants and the wild type result in orders-ofmagnitude differences in genetic diversity. Indeed, only a slight fitness advantage for the mutant is enough to keep diversity low and independent of population size. These results have important clinical implications. Genetic diversity at antibiotic resistance loci can determine a population's capacity to cope with future challenges (i.e., second-line therapy). We thus revealed an unanticipated way in which the fitness effects of antibiotic resistance can affect the evolvability of pathogens surviving a drug-induced bottleneck. This insight will assist in the fight against multidrug-resistant microbes, as well as contribute to theories aimed at predicting cancer evolution.

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

Cited by 176 publications

References 11 publications

Insights Into Mutagenesis Using Escherichia coli Chromosomal lacZ Strains That Enable Detection of a Wide Spectrum of Mutational Events

Insights Into Mutagenesis Using Escherichia coli Chromosomal lacZ Strains That Enable Detection of a Wide Spectrum of Mutational Events

Identification of frame-shift intermediate mutant cells

Determinants of Genetic Diversity of Spontaneous Drug Resistance in Bacteria

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