Luria-Delbrück fluctuation experiments: design and analysis.

Jones, Michael E.; Thomas, Susan M.; Rogers, Alix

doi:10.1093/genetics/136.3.1209

Cited by 82 publications

(17 citation statements)

References 16 publications

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“…Statistical methods have been developed for correction of selection bias. One of them is the Ma-Sandri-Sarkar maximum likelihood estimator, available at the Fluctuation Analysis Calculator (FALCOR) [ 39 , 40 , 41 ]. When no correction for selection bias is applied, the discrepancy between a mutation frequency determined experimentally and the underlying mutation rate will depend on the fitness effect of the mutation.…”

Section: Mutation Rates and Frequenciesmentioning

confidence: 99%

Mutation Rates, Mutation Frequencies, and Proofreading-Repair Activities in RNA Virus Genetics

Domingo

García-Crespo

Lobo-Vega

et al. 2021

Viruses

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The error rate displayed during template copying to produce viral RNA progeny is a biologically relevant parameter of the replication complexes of viruses. It has consequences for virus–host interactions, and it represents the first step in the diversification of viruses in nature. Measurements during infections and with purified viral polymerases indicate that mutation rates for RNA viruses are in the range of 10−3 to 10−6 copying errors per nucleotide incorporated into the nascent RNA product. Although viruses are thought to exploit high error rates for adaptation to changing environments, some of them possess misincorporation correcting activities. One of them is a proofreading-repair 3′ to 5′ exonuclease present in coronaviruses that may decrease the error rate during replication. Here we review experimental evidence and models of information maintenance that explain why elevated mutation rates have been preserved during the evolution of RNA (and some DNA) viruses. The models also offer an interpretation of why error correction mechanisms have evolved to maintain the stability of genetic information carried out by large viral RNA genomes such as the coronaviruses

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Section: Mutation Rates and Frequenciesmentioning

confidence: 99%

Mutation Rates, Mutation Frequencies, and Proofreading-Repair Activities in RNA Virus Genetics

Domingo

García-Crespo

Lobo-Vega

et al. 2021

Viruses

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“…The rank-biserial correlation r, calculated as 1 À 2�U N 1 �N 2 , is r = −0.44 for the WT constructs and r = −0.88 for the ΔmutS constructs. We also estimate the number of mutations-which is different from the number of mutants [33]-that escape the protection in the overlap using Jones median estimator [72].…”

Section: Mutagenesis Protocolmentioning

confidence: 99%

Engineering gene overlaps to sustain genetic constructs in vivo

et al. 2021

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Evolution is often an obstacle to the engineering of stable biological systems due to the selection of mutations inactivating costly gene circuits. Gene overlaps induce important constraints on sequences and their evolution. We show that these constraints can be harnessed to increase the stability of costly genes by purging loss-of-function mutations. We combine computational and synthetic biology approaches to rationally design an overlapping reading frame expressing an essential gene within an existing gene to protect. Our algorithm succeeded in creating overlapping reading frames in 80% of E. coli genes. Experimentally, scoring mutations in both genes of such overlapping construct, we found that a significant fraction of mutations impacting the gene to protect have a deleterious effect on the essential gene. Such an overlap thus protects a costly gene from removal by natural selection by associating the benefit of this removal with a larger or even lethal cost. In our synthetic constructs, the overlap converts many of the possible mutants into evolutionary dead-ends, reducing the evolutionary potential of the system and thus increasing its stability over time.

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“…This was determined by counting the number of colonies formed on Mueller-Hinton agar supplemented or not with rifampicin (100 µg/mL). After incubation at 37 °C for 48 h, CFU as well as rifampicin resistant mutants were counted and the mutation rate was calculated by the Jones median estimator method (123).…”

Section: Estimation Of Spontaneous Mutation Ratesmentioning

confidence: 99%

Novel prokaryotic sensing and regulatory system employing previously unknown nucleic acids-based receptors

Tetz¹,

Tetz²

2021

Preprint

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The present study describes a previously unknown universal signaling and regulatory system, which we named TETZ-receptor system. This system is responsible for sensing, remembering, and regulating cell responses to various chemical, physical or biological stimuli. It controls cell survival, variability, reproduction, adaptation, genome changes, and gene transfer. Importantly, the TETZ-receptor system is responsible for the formation and maintenance of cell memory, as well the ability to forget preceding events. The system is composed of DNA- and RNA-based receptors located outside the membrane named TezRs, as well as reverse transcriptases and integrases. The sensory and regulatory functions of TezRs enable the TETZ-receptor system to control all major aspects of bacterial behavior, such as growth, biofilm formation and dispersal, utilization of nutrients including xenobiotics, virulence, chemo- and magnetoreception, response to external factors (e.g., temperature, UV, light and gas content), mutation events, phage-host interaction and recombination activity. Additionally, it supervises the function of other receptor-mediated signaling pathways.

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Luria-Delbrück fluctuation experiments: design and analysis.

Cited by 82 publications

References 16 publications

Mutation Rates, Mutation Frequencies, and Proofreading-Repair Activities in RNA Virus Genetics

Mutation Rates, Mutation Frequencies, and Proofreading-Repair Activities in RNA Virus Genetics

Engineering gene overlaps to sustain genetic constructs in vivo

Novel prokaryotic sensing and regulatory system employing previously unknown nucleic acids-based receptors

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