ReviewMicrobiology (Reading, England)2023
Mutation bias and adaptation in bacteria.
Review in Microbiology (Reading, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
24 citing papers in PubMed.
- Simulating the host niche: balancing complexity and control in the experimental evolution of antibiotic resistance and pathoadaptation.Microbiology (Reading, England) · 2026Review
- The adaptive landscapes of three globaleLife · 2026Article
- Evolutionary causes and consequences of gene duplication.Nature reviews. Genetics · 2026Review
- Exploring clonality ofMicrobiology spectrum · 2026Article
- High stability of the genome ofMicrobiology spectrum · 2026Article
- Artificial Intelligence as a Catalyst for Antimicrobial Discovery: From Predictive Models to De Novo Design.Microorganisms · 2026Review
- Antimicrobial Resistant Factors inInternational journal of genomics · 2026Article
- Bacterial mutation dynamics emerging insights into virulence evolution and drug resistance. A review study.Frontiers in medicine · 2026Review
- Development and preliminary evaluation of a ΔtssB-EP as a live attenuated vaccine against Edwardsiella piscicida.Frontiers in immunology · 2026Article
- Genomic Characterization and Antimicrobial Resistance Profile ofAntibiotics (Basel, Switzerland) · 2025Article
- Comprehensive Mutational Landscape of Yeast Mutator Strains Reveals the Genetic Basis of Mutational Signatures in Cancer.Molecular biology and evolution · 2025Article
- Prevalence, toxin virulence genes and investigating the effect of mutations in the tetracycline gene (tetK) on the response of methicillin-resistant Staphylococcus aureus to antibiotics: a study in sickle cell disease patients in Riyadh, Saudi Arabia.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2025Article
- Antimutator and Mutational Spectrum Effects Can Combine to Reduce Evolutionary Potential in Escherichia coli ΔnudJ.Molecular biology and evolution · 2025Article
- GnT Motifs Can Increase T:A→G:C Mutation Rates Over 1000-fold in Bacteria.Molecular biology and evolution · 2025Article
- A single mutation may contribute to accelerated evolution of SARS-CoV-2 toward Omicron.Nature communications · 2025Article
- Mutation bias alters the distribution of fitness effects of mutations.PLoS biology · 2025Article
- Genome-wide mapping of spontaneous DNA replication error-hotspots using mismatch repair proteins in rapidly proliferating Escherichia coli.Nucleic acids research · 2025Article
- An extreme mutational hotspot in nlpD depends on transcriptional induction of rpoS.PLoS genetics · 2025Article
- The highly rugged yet navigable regulatory landscape of the bacterial transcription factor TetR.Nature communications · 2024Article
- Survival Strategies ofAntibiotics (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Genetic mutation, which provides the raw material for evolutionary adaptation, is largely a stochastic force. However, there is ample evidence showing that mutations can also exhibit strong biases, with some mutation types and certain genomic positions mutating more often than others. It is becoming increasingly clear that mutational bias can play a role in determining adaptive outcomes in bacteria in both the laboratory and the clinic. As such, understanding the causes and consequences of mutation bias can help microbiologists to anticipate and predict adaptive outcomes. In this review, we provide an overview of the mechanisms and features of the bacterial genome that cause mutational biases to occur. We then describe the environmental triggers that drive these mechanisms to be more potent and outline the adaptive scenarios where mutation bias can synergize with natural selection to define evolutionary outcomes. We conclude by describing how understanding mutagenic genomic features can help microbiologists predict areas sensitive to mutational bias, and finish by outlining future work that will help us achieve more accurate evolutionary forecasts.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.