bz-rates: A Web Tool to Estimate Mutation Rates from Fluctuation Analysis
Open accessAbstract
Fluctuation analysis is the standard experimental method for measuring mutation rates in micro-organisms. The appearance of mutants is classically described by a Luria-Delbrück distribution composed of two parameters: the number of mutations per culture (m) and the differential growth rate between mutant and wild-type cells (b). A precise estimation of these two parameters is a prerequisite to the calculation of the mutation rate. Here, we developed bz-rates, a Web tool to calculate mutation rates that provides three useful advances over existing Web tools. First, it allows taking into account b, the differential growth rate between mutant and wild-type cells, in the estimation of m with the generating function. Second, bz-rates allows the user to take into account a deviation from the Luria-Delbrück distribution called z, the plating efficiency, in the estimation of m. Finally, the Web site provides a graphical visualization of the goodness-of-fit between the experimental data and the model. bz-rates is accessible at http://www.lcqb.upmc.fr/bzrates.
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Gillet-Markowska et al. (2015) emphasize that there is no universal cellular division time model as it depends on experimental conditions like the strain or the media.
“In response to Ycart’s suggestion, Gillet-Markowska et al. (2015) emphasize that “there is no universal cellular division time model as it depends on experimental conditions like the strain or the media.””
From rSalvador: An R Package for the Fluctuation Experiment (2017) · cites this paper as Gillet-Markowska et al. 2015
At least three versions of the GF method are available: Hamon and Ycart (2012), bz-rates (Gillet-Markowska et al. 2015), and flan (Mazoyer et al. 2017).
“At least three versions of the GF method are available: that given by Hamon and Ycart (2012) via the R code attendant to their paper, that given by the web tool bz-rates (Gillet-Markowska et al. 2015), and that given by the R package flan (Mazoyer et al. 2017).”
From rSalvador: An R Package for the Fluctuation Experiment (2017) · cites this paper as Gillet-Markowska et al. 2015
A simulation study of the GF method led Gillet-Markowska et al. (2015) to emphasize the importance of avoiding exceedingly large mutant counts.
“For example, a simulation study of the GF method led Gillet-Markowska et al. (2015) to emphasize the importance of avoiding exceedingly large mutant counts.”
From rSalvador: An R Package for the Fluctuation Experiment (2017) · cites this paper as Gillet-Markowska et al. 2015
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“In the case of differential growth rate, several estimators that jointly calculate m and b have long been made available (Koch 1982; Jones 1994; Jaeger and Sarkar 1995; Zheng 2002, 2005; Hamon and Ycart 2012).”
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Evolution of high-level resistance during low-level antibiotic exposure
Wistrand-Yuen, E., Knopp, M., Hjort, K., Koskiniemi, S., Berg, O. G., & Andersson, D. I. (2018) · Nature Communications · doi:10.1038/s41467-018-04059-1 · Cited by 466 · see citing works
rSalvador: An R Package for the Fluctuation Experiment
Zheng, Q. (2017) · G3 Genes|Genomes|Genetics · doi:10.1534/g3.117.300120 · Cited by 98 · see citing works
“In response to Ycart ’ s suggestion, Gillet-Markowska et al. (2015) emphasize that “ there is no universal cellular division time model as it depends on experimental conditions like the strain or the media.”
BackgroundMethodInfluentialflan: an R package for inference on mutation models.
Mazoyer, A., Drouilhet, R., Despréaux, S., & Ycart, B. (2017) · The R Journal · doi:10.32614/rj-2017-029 · Cited by 33 · see citing works
Boyce, K. J., Cao, C., Xue, C., & Idnurm, A. (2020) · DNA Repair · doi:10.1016/j.dnarep.2019.102751 · Cited by 14 · see citing works
Łazowski, K. (2023) · Mutation Research - Fundamental and Molecular Mechanisms of Mutagenesis · doi:10.1016/j.mrfmmm.2023.111816 · Cited by 10 · see citing works
- Authors
- Gillet-Markowska, A., Louvel, G., & Fischer, G.
- Affiliations
- Sorbonne Universités, UPMC Univ. Paris 06, Institut de Biologie Paris-Seine UMR7238, Biologie Computationnelle et Quantitative, F-75005, Paris, France
- Biologie Computationnelle, Quantitative et Synthétique (FR)
- Corresponding author
- Fischer, Gilles
- Venue
- G3 Genes|Genomes|Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 2015-11-01
- Volume
- 5
- Issue
- 11
- Pages
- 2323-2327
- ISSN
- 2160-1836 (ISSN-L)
- PMC
- PMC4632052
- OpenAlex
- W2253095891
- Cited by
- 58
- References
- 4
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 6 · 2023: 7 · 2022: 1 · 2021: 10 · 2020: 7 · 2019: 8 · 2018: 5 · 2017: 5 · 2016: 1
- FWCI
- 2.27
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- G3 Genes Genomes Genetics (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- HAL (submittedVersion, cc-by)
- Funders
- Ligue Contre le Cancer
- Sorbonne Université
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Bacterial Genetics and Biotechnology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- mutation rate estimation, fluctuation analysis, differential growth rates, plating efficiency, generating functions, web-based tool
- MeSH terms
- Software, Genome, Bacterial, Mutation Rate
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