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Volume 169, Issue 11

Mutation bias and adaptation in bacteria Open Access

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.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): adaptation , bacterial evolution , evolutionary forecasting , mutation bias , mutation hotspot and stress response
Funding
This study was supported by the:
  • BBSRC (Award BB/T012994/1)
    • Principle Award Recipient: TiffanyB Taylor
  • Royal Society (Award DH150169)
    • Principle Award Recipient: TiffanyB Taylor
© 2023 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
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2023-11-09
2024-04-27
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References

  1. Rodríguez-Beltrán J, DelaFuente J, León-Sampedro R, MacLean RC, San Millán Á. Beyond horizontal gene transfer: the role of plasmids in bacterial evolution. Nat Rev Microbiol 2021; 19:347–359 [View Article] [PubMed]
     [Google Scholar]
  2. Malik JA, Ahmed S, Mir A, Shinde M, Bender O et al. The SARS-CoV-2 mutations versus vaccine effectiveness: new opportunities to new challenges. J Infect Public Health 2022; 15:228–240 [View Article] [PubMed]
     [Google Scholar]
  3. Davies J, Davies D. Origins and evolution of antibiotic resistance. Microbiol Mol Biol Rev 2010; 74:417–433 [View Article] [PubMed]
     [Google Scholar]
  4. Payne JL, Menardo F, Trauner A, Borrell S, Gygli SM et al. Transition bias influences the evolution of antibiotic resistance in Mycobacterium tuberculosis. PLoS Biol 2019; 17:e3000265 [View Article] [PubMed]
     [Google Scholar]
  5. Long H, Sung W, Miller SF, Ackerman MS, Doak TG et al. Mutation rate, spectrum, topology, and context-dependency in the DNA mismatch repair-deficient Pseudomonas fluorescens ATCC948. Genome Biol Evol 2014; 7:262–271 [View Article] [PubMed]
     [Google Scholar]
  6. Stoltzfus A. Mutation, Randomness, and Evolution Oxford University Press; 2021 [View Article]
     [Google Scholar]
  7. Hershberg R, Petrov DA. Evidence that mutation is universally biased towards AT in bacteria. PLoS Genet 2010; 6:e1001115 [View Article] [PubMed]
     [Google Scholar]
  8. Rice AM, Morales AC, Ho AT, Mordstein C, Mühlhausen S et al. Evidence for strong mutation bias toward, and selection against, U content in SARS-CoV-2: implications for vaccine design. Mol Biol Evol 2021; 38:67–83 [View Article] [PubMed]
     [Google Scholar]
  9. Horton JS, Ali SUP, Taylor TB. Transient mutation bias increases the predictability of evolution on an empirical genotype–phenotype landscape. Phil Trans R Soc B 2023; 378:20220043 [View Article]
     [Google Scholar]
  10. Cano AV, Rozhoňová H, Stoltzfus A, McCandlish DM, Payne JL. Mutation bias shapes the spectrum of adaptive substitutions. Proc Natl Acad Sci U S A 2022; 119:1–11 [View Article] [PubMed]
     [Google Scholar]
  11. Sane M, Diwan GD, Bhat BA, Wahl LM, Agashe D. Shifts in mutation spectra enhance access to beneficial mutations. Proc Natl Acad Sci U S A 2023; 120:e2207355120 [View Article] [PubMed]
     [Google Scholar]
  12. Dettman JR, Sztepanacz JL, Kassen R. The properties of spontaneous mutations in the opportunistic pathogen Pseudomonas aeruginosa. BMC Genomics 2016; 17:1–14 [View Article]
     [Google Scholar]
  13. Katju V, Bergthorsson U. Old trade, new tricks: insights into the spontaneous mutation process from the partnering of classical mutation accumulation experiments with high-throughput genomic approaches. Genome Biol Evol 2019; 11:136–165 [View Article] [PubMed]
     [Google Scholar]
  14. Stoltzfus A, Norris RW. On the causes of evolutionary transition:transversion bias. Mol Biol Evol 2016; 33:595–602 [View Article] [PubMed]
     [Google Scholar]
  15. Lyons DM, Lauring AS. Evidence for the selective basis of transition-to-transversion substitution bias in two RNA viruses. Mol Biol Evol 2017; 34:3205–3215 [View Article] [PubMed]
     [Google Scholar]
  16. Hefetz I, Israeli O, Bilinsky G, Plaschkes I, Hazkani-Covo E et al. A reversible mutation in a genomic hotspot saves bacterial swarms from extinction. iScience 2023; 26:106043 [View Article] [PubMed]
     [Google Scholar]
  17. Cherry JL, Katz L. T residues preceded by runs of G are hotspots of T→G mutation in bacteria. Genome Biol Evol 2023; 15:evad087 [View Article] [PubMed]
     [Google Scholar]
  18. Kapel N, Caballero JD, MacLean RC. Localized pmrB hypermutation drives the evolution of colistin heteroresistance. Cell Rep 2022; 39:110929 [View Article] [PubMed]
     [Google Scholar]
  19. Shepherd MJ, Horton JS, Taylor TB, Hendrickson H. A near-deterministic mutational hotspot in Pseudomonas fluorescens is constructed by multiple interacting genomic features. Mol Biol Evol 2022; 39:msac132 [View Article] [PubMed]
     [Google Scholar]
  20. Warnecke T, Supek F, Lehner B. Nucleoid-associated proteins affect mutation dynamics in E. coli in a growth phase-specific manner. PLoS Comput Biol 2012; 8:e1002846 [View Article] [PubMed]
     [Google Scholar]
  21. Maki H. Origins of spontaneous mutations: specificity and directionality of base-substitution, frameshift, and sequence-substitution mutageneses. Annu Rev Genet 2002; 36:279–303 [View Article] [PubMed]
     [Google Scholar]
  22. Selveshwari S, Lele K, Dey S. Genomic signatures of UV resistance evolution in Escherichia coli depend on the growth phase during exposure. J Evol Biol 2021; 34:953–967 [View Article] [PubMed]
     [Google Scholar]
  23. Bikard D, Loot C, Baharoglu Z, Mazel D. Folded DNA in action: hairpin formation and biological functions in prokaryotes. Microbiol Mol Biol Rev 2010; 74:570–588 [View Article] [PubMed]
     [Google Scholar]
  24. Hudson RE, Bergthorsson U, Roth JR, Ochman H. Effect of chromosome location on bacterial mutation rates. Mol Biol Evol 2002; 19:85–92 [View Article] [PubMed]
     [Google Scholar]
  25. Dillon MM, Sung W, Lynch M. Periodic variation of mutation rates in bacterial genomes. mBio 2018; 9: [View Article]
     [Google Scholar]
  26. Zhang X, Zhang X, Zhang X, Liao Y, Song L et al. Spatial vulnerabilities of the Escherichia coli genome. Genetics 2018; 210:547–558 [View Article]
     [Google Scholar]
  27. Maslowska KH, Makiela-Dzbenska K, Mo J-Y, Fijalkowska IJ, Schaaper RM. High-accuracy lagging-strand DNA replication mediated by DNA polymerase dissociation. Proc Natl Acad Sci U S A 2018; 115:4212–4217 [View Article] [PubMed]
     [Google Scholar]
  28. Bhagwat AS, Hao W, Townes JP, Lee H, Tang H et al. Strand-biased cytosine deamination at the replication fork causes cytosine to thymine mutations in Escherichia coli. Proc Natl Acad Sci U S A 2016; 113:2176–2181 [View Article] [PubMed]
     [Google Scholar]
  29. Foster PL, Niccum BA, Popodi E, Townes JP, Lee H et al. Determinants of base-pair substitution patterns revealed by whole-genome sequencing of DNA mismatch repair defective Escherichia coli. Genetics 2018; 209:1029–1042 [View Article] [PubMed]
     [Google Scholar]
  30. Dutra BE, Lovett ST. Cis and trans-acting effects on a mutational hotspot involving a replication template switch. J Mol Biol 2006; 356:300–311 [View Article] [PubMed]
     [Google Scholar]
  31. Lai PJ, Lim CT, Le HP, Katayama T, Leach DRF et al. Long inverted repeat transiently stalls DNA replication by forming hairpin structures on both leading and lagging strands. Genes Cells 2016; 21:136–145 [View Article] [PubMed]
     [Google Scholar]
  32. Trinh TQ, Sinden RR. Preferential DNA secondary structure mutagenesis in the lagging strand of replication in E. coli. Nature 1991; 352:544–547 [View Article]
     [Google Scholar]
  33. Schroeder JW, Hirst WG, Szewczyk GA, Simmons LA. The effect of local sequence context on mutational bias of genes encoded on the leading and lagging strands. Curr Biol 2016; 26:692–697 [View Article] [PubMed]
     [Google Scholar]
  34. Beletskii A, Bhagwat AS. Transcription-induced mutations: increase in C to T mutations in the nontranscribed strand during transcription in Escherichia coli. Proc Natl Acad Sci U S A 1996; 93:13919–13924 [View Article] [PubMed]
     [Google Scholar]
  35. Davis BD. Transcriptional bias: a non-Lamarckian mechanism for substrate-induced mutations. Proc Natl Acad Sci U S A 1989; 86:5005–5009 [View Article] [PubMed]
     [Google Scholar]
  36. Francino MP, Ochman H. Deamination as the basis of strand-asymmetric evolution in transcribed Escherichia coli sequences. Mol Biol Evol 2001; 18:1147–1150 [View Article] [PubMed]
     [Google Scholar]
  37. Mellon I, Hanawalt PC. Induction of the Escherichia coli lactose operon selectively increases repair of its transcribed DNA strand. Nature 1989; 342:95–98 [View Article]
     [Google Scholar]
  38. Kraithong T, Hartley S, Jeruzalmi D, Pakotiprapha D. A peek inside the machines of bacterial nucleotide excision repair. Int J Mol Sci 2021; 22:952 [View Article] [PubMed]
     [Google Scholar]
  39. Schroeder JW, Sankar TS, Wang JD, Simmons LA. The roles of replication-transcription conflict in mutagenesis and evolution of genome organization. PLoS Genet 2020; 16:e1008987 [View Article] [PubMed]
     [Google Scholar]
  40. Brüning J-G, Marians KJ. Bypass of complex co-directional replication-transcription collisions by replisome skipping. Nucleic Acids Res 2021; 49:9870–9885 [View Article] [PubMed]
     [Google Scholar]
  41. Paul S, Million-Weaver S, Chattopadhyay S, Sokurenko E, Merrikh H. Accelerated gene evolution through replication-transcription conflicts. Nature 2013; 495:512–515 [View Article] [PubMed]
     [Google Scholar]
  42. Foster PL, Niccum BA, Lee H. DNA replication-transcription conflicts do not significantly contribute to spontaneous mutations due to replication errors in Escherichia coli. mBio 2021; 12:e0250321 [View Article] [PubMed]
     [Google Scholar]
  43. Schroeder JW, Hirst WG, Szewczyk GA, Simmons LA. The effect of local sequence context on mutational bias of genes encoded on the leading and lagging strands. Curr Biol 2016; 26:692–697 [View Article] [PubMed]
     [Google Scholar]
  44. Merrikh CN, Weiss E, Merrikh H. The accelerated evolution of lagging strand genes is independent of sequence context. Genome Biol Evol 2016; 8:3696–3702 [View Article] [PubMed]
     [Google Scholar]
  45. Sankar TS, Wastuwidyaningtyas BD, Dong Y, Lewis SA, Wang JD. The nature of mutations induced by replication–transcription collisions. Nature 2016; 535:178–181 [View Article] [PubMed]
     [Google Scholar]
  46. Eisen JA, Hanawalt PC. A phylogenomic study of DNA repair genes, proteins, and processes. Mutat Res 1999; 435:171–213 [View Article] [PubMed]
     [Google Scholar]
  47. Boyce KJ. Mutators enhance adaptive micro-evolution in pathogenic microbes. Microorganisms 2022; 10:442 [View Article] [PubMed]
     [Google Scholar]
  48. LeClerc JE, Li B, Payne WL, Cebula TA. High mutation frequencies among Escherichia coli and Salmonella pathogens. Science 1996; 274:1208–1211 [View Article] [PubMed]
     [Google Scholar]
  49. Denamur E, Bonacorsi S, Giraud A, Duriez P, Hilali F et al. High frequency of mutator strains among human uropathogenic Escherichia coli isolates. J Bacteriol 2002; 184:605–609 [View Article] [PubMed]
     [Google Scholar]
  50. Oliver A, Cantón R, Campo P, Baquero F, Blázquez J. High frequency of hypermutable Pseudomonas aeruginosa in cystic fibrosis lung infection. Science 2000; 288:1251–1254 [View Article] [PubMed]
     [Google Scholar]
  51. Denamur E, Matic I. Evolution of mutation rates in bacteria. Mol Microbiol 2006; 60:820–827 [View Article] [PubMed]
     [Google Scholar]
  52. Couce A, Rodríguez-Rojas A, Blázquez J. Bypass of genetic constraints during mutator evolution to antibiotic resistance. Proc R Soc B 2015; 282:20142698 [View Article]
     [Google Scholar]
  53. Foster PL, Lee H, Popodi E, Townes JP, Tang H. Determinants of spontaneous mutation in the bacterium Escherichia coli as revealed by whole-genome sequencing. Proc Natl Acad Sci U S A 2015; 112:E5990–9 [View Article] [PubMed]
     [Google Scholar]
  54. Sung W, Ackerman MS, Gout J-F, Miller SF, Williams E et al. Asymmetric context-dependent mutation patterns revealed through mutation-accumulation experiments. Mol Biol Evol 2015; 32:1672–1683 [View Article] [PubMed]
     [Google Scholar]
  55. Ferenci T. Irregularities in genetic variation and mutation rates with environmental stresses. Environ Microbiol 2019; 21:3979–3988 [View Article] [PubMed]
     [Google Scholar]
  56. Abundiz-Yañez K, Leyva-Sánchez HC, Robleto EA, Pedraza-Reyes M. Stress-associated and growth-dependent mutagenesis are divergently regulated by c-di-AMP levels in Bacillus subtilis. Int J Mol Sci 2022; 24:455 [View Article] [PubMed]
     [Google Scholar]
  57. MacLean RC, Torres-Barceló C, Moxon R. Evaluating evolutionary models of stress-induced mutagenesis in bacteria. Nat Rev Genet 2013; 14:221–227 [View Article] [PubMed]
     [Google Scholar]
  58. Foster PL, Hanson AJ, Lee H, Popodi EM, Tang H. On the mutational topology of the bacterial genome. G3 Genes|Genomes|Genetics 2013; 3:399–407 [View Article]
     [Google Scholar]
  59. Kivisaar M. Mutation and recombination rates vary across bacterial chromosome. Microorganisms 2020; 8:25 [View Article]
     [Google Scholar]
  60. Niccum BA, Lee H, MohammedIsmail W, Tang H, Foster PL. The symmetrical wave pattern of base-pair substitution rates across the Escherichia coli chromosome has multiple causes. mBio 2019; 10:e01226-19 [View Article] [PubMed]
     [Google Scholar]
  61. Pereira FC, Berry D. Microbial nutrient niches in the gut. Environ Microbiol 2017; 19:1366–1378 [View Article] [PubMed]
     [Google Scholar]
  62. La Rosa R, Johansen HK, Molin S. Adapting to the airways: metabolic requirements of Pseudomonas aeruginosa during the infection of cystic fibrosis patients. Metabolites 2019; 9:234 [View Article] [PubMed]
     [Google Scholar]
  63. Gresham D, Dunham MJ. The enduring utility of continuous culturing in experimental evolution. Genomics 2014; 104:399–405 [View Article]
     [Google Scholar]
  64. Loewen PC, Hengge-Aronis R. The role of the sigma factor sigma S (KatF) in bacterial global regulation. Annu Rev Microbiol 1994; 48:53–80 [View Article] [PubMed]
     [Google Scholar]
  65. Maharjan R, Ferenci T. Stress-induced mutation rates show a sigmoidal and saturable increase due to the RpoS sigma factor in Escherichia coli. Genetics 2014; 198:1231–1235 [View Article] [PubMed]
     [Google Scholar]
  66. Battesti A, Majdalani N, Gottesman S. The RpoS-mediated general stress response in Escherichia coli. Annu Rev Microbiol 2011; 65:189–213 [View Article] [PubMed]
     [Google Scholar]
  67. Maharjan R, Ferenci T. Mutational signatures indicative of environmental stress in bacteria. Mol Biol Evol 2015; 32:380–391 [View Article] [PubMed]
     [Google Scholar]
  68. Krašovec R, Richards H, Gifford DR, Belavkin RV, Channon A et al. Opposing effects of final population density and stress on Escherichia coli mutation rate. ISME J 2018; 12:2981–2987 [View Article] [PubMed]
     [Google Scholar]
  69. Liu H, Zhang J. The rate and molecular spectrum of mutation are selectively maintained in yeast. Nat Commun 2021; 12:4044 [View Article]
     [Google Scholar]
  70. Krašovec R, Richards H, Gifford DR, Hatcher C, Faulkner KJ et al. Spontaneous mutation rate is a plastic trait associated with population density across domains of life. PLoS Biol 2017; 15:e2002731 [View Article] [PubMed]
     [Google Scholar]
  71. Friedlander A, Nir S, Reches M, Shemesh M. Preventing biofilm formation by dairy-associated bacteria using peptide-coated surfaces. Front Microbiol 2019; 10:1405 [View Article] [PubMed]
     [Google Scholar]
  72. Paul B. Rainey & Michael Travisano Adaptive radiation in a heterogeneous environment. Nat Lett 1998; 394:69–72 [View Article] [PubMed]
     [Google Scholar]
  73. Podlesek Z, Žgur Bertok D. The DNA damage inducible SOS response is a key player in the generation of bacterial persister cells and population wide tolerance. Front Microbiol 2020; 11:1785 [View Article] [PubMed]
     [Google Scholar]
  74. Kivisaar M. Mechanisms of stationary-phase mutagenesis in bacteria: mutational processes in pseudomonads. FEMS Microbiol Lett 2010; 312:1–14 [View Article] [PubMed]
     [Google Scholar]
  75. Joseph AM, Badrinarayanan A. Visualizing mutagenic repair: novel insights into bacterial translesion synthesis. FEMS Microbiol Rev 2020; 44:572–582 [View Article] [PubMed]
     [Google Scholar]
  76. Revitt-Mills SA, Robinson A. Antibiotic-induced mutagenesis: under the microscope. Front Microbiol 2020; 11:585175 [View Article] [PubMed]
     [Google Scholar]
  77. Long H, Miller SF, Strauss C, Zhao C, Cheng L et al. Antibiotic treatment enhances the genome-wide mutation rate of target cells. Proc Natl Acad Sci U S A 2016; 113:E2498–505 [View Article] [PubMed]
     [Google Scholar]
  78. Messer PW, Petrov DA. Population genomics of rapid adaptation by soft selective sweeps. Trends Ecol Evol 2013; 28:659–669 [View Article] [PubMed]
     [Google Scholar]
  79. Wilson BA, Petrov DA, Messer PW. Soft selective sweeps in complex demographic scenarios. Genetics 2014; 198:669–684 [View Article] [PubMed]
     [Google Scholar]
  80. Avalos A, Pan H, Li C, Acevedo-Gonzalez JP, Rendon G et al. A soft selective sweep during rapid evolution of gentle behaviour in an Africanized honeybee. Nat Commun 2017; 8:1550 [View Article] [PubMed]
     [Google Scholar]
  81. Garud NR, Messer PW, Buzbas EO, Petrov DA. Recent selective sweeps in North American Drosophila melanogaster show signatures of soft sweeps. PLoS Genet 2015; 11:e1005004 [View Article] [PubMed]
     [Google Scholar]
  82. Avrani S, Bolotin E, Katz S, Hershberg R. Rapid genetic adaptation during the first four months of survival under resource exhaustion. Mol Biol Evol 2017; 34:1758–1769 [View Article] [PubMed]
     [Google Scholar]
  83. Miller CR, Joyce P, Wichman HA. Mutational effects and population dynamics during viral adaptation challenge current models. Genetics 2011; 187:185–202 [View Article] [PubMed]
     [Google Scholar]
  84. Hermisson J, Pennings PS. Soft sweeps: molecular population genetics of adaptation from standing genetic variation. Genetics 2005; 169:2335–2352 [View Article] [PubMed]
     [Google Scholar]
  85. McCandlish DM, Stoltzfus A. Modeling evolution using the probability of fixation: history and implications. Q Rev Biol 2014; 89:225–252 [View Article] [PubMed]
     [Google Scholar]
  86. Horton JS, Flanagan LM, Jackson RW, Priest NK, Taylor TB. A mutational hotspot that determines highly repeatable evolution can be built and broken by silent genetic changes. Nat Commun 2021; 12:6092 [View Article] [PubMed]
     [Google Scholar]
  87. Sackman AM, McGee LW, Morrison AJ, Pierce J, Anisman J et al. Mutation-driven parallel evolution during viral adaptation. Mol Biol Evol 2017; 34:3243–3253 [View Article] [PubMed]
     [Google Scholar]
  88. Jensen JD. On the unfounded enthusiasm for soft selective sweeps. Nat Commun 2014; 5:5281 [View Article] [PubMed]
     [Google Scholar]
  89. Rousselle M, Simion P, Tilak M-K, Figuet E, Nabholz B et al. Is adaptation limited by mutation? A timescale-dependent effect of genetic diversity on the adaptive substitution rate in animals. PLoS Genet 2020; 16:e1008668 [View Article]
     [Google Scholar]
  90. Chiner-oms Á, Berney M, Boinett C, González-candelas F, Young DB et al. Genome-wide mutational biases fuel tuberculosis complex. Nat Commun 2019; 10: [View Article]
     [Google Scholar]
  91. Goldhill DH, Langat P, Xie H, Galiano M, Miah S et al. Determining the mutation bias of favipiravir in influenza virus. J Virol 2019; 93:e01217–18 [View Article]
     [Google Scholar]
  92. Bergstrom CT, McElhany P, Real LA. Transmission bottlenecks as determinants of virulence in rapidly evolving pathogens. Proc Natl Acad Sci U S A 1999; 96:5095–5100 [View Article] [PubMed]
     [Google Scholar]
  93. Hannan TJ, Totsika M, Mansfield KJ, Moore KH, Schembri MA et al. Host-pathogen checkpoints and population bottlenecks in persistent and intracellular uropathogenic Escherichia coli bladder infection. FEMS Microbiol Rev 2012; 36:616–648 [View Article] [PubMed]
     [Google Scholar]
  94. Bachta KER, Allen JP, Cheung BH, Chiu C-H, Hauser AR. Systemic infection facilitates transmission of Pseudomonas aeruginosa in mice. Nat Commun 2020; 11:543 [View Article] [PubMed]
     [Google Scholar]
  95. Golubchik T, Batty EM, Miller RR, Farr H, Young BC et al. Within-host evolution of Staphylococcus aureus during asymptomatic carriage. PLoS One 2013; 8:e61319 [View Article] [PubMed]
     [Google Scholar]
  96. Didelot X, Walker AS, Peto TE, Crook DW, Wilson DJ. Within-host evolution of bacterial pathogens. Nat Rev Microbiol 2016; 14:150–162 [View Article] [PubMed]
     [Google Scholar]
  97. Couce A, Tenaillon O. Mutation bias and GC content shape antimutator invasions. Nat Commun 2019; 10:3114 [View Article] [PubMed]
     [Google Scholar]
  98. Harris KB, Flynn KM, Cooper VS. Polygenic adaptation and clonal interference enable sustained diversity in experimental Pseudomonas aeruginosa populations. Mol Biol Evol 2021; 38:5359–5375 [View Article] [PubMed]
     [Google Scholar]
  99. Couce A, Rodríguez-Rojas A, Blázquez J. Determinants of genetic diversity of spontaneous drug resistance in bacteria. Genetics 2016; 203:1369–1380 [View Article] [PubMed]
     [Google Scholar]
  100. Schenk MF, Zwart MP, Hwang S, Ruelens P, Severing E et al. Population size mediates the contribution of high-rate and large-benefit mutations to parallel evolution. Nat Ecol Evol 2022; 6:439–447 [View Article] [PubMed]
     [Google Scholar]
  101. Bacigalupe R, Tormo-Mas MÁ, Penadés JR, Fitzgerald JR. A multihost bacterial pathogen overcomes continuous population bottlenecks to adapt to new host species. Sci Adv 2019; 5: [View Article]
     [Google Scholar]
  102. Garoff L, Pietsch F, Huseby DL, Lilja T, Brandis G et al. Population bottlenecks strongly influence the evolutionary trajectory to fluoroquinolone resistance in Escherichia coli. Mol Biol Evol 2020; 37:1637–1646 [View Article] [PubMed]
     [Google Scholar]
  103. Elena SF, Lenski RE. Evolution experiments with microorganisms: the dynamics and genetic bases of adaptation. Nat Rev Genet 2003; 4:457–469 [View Article] [PubMed]
     [Google Scholar]
  104. MacLean RC, Perron GG, Gardner A. Diminishing returns from beneficial mutations and pervasive epistasis shape the fitness landscape for rifampicin resistance in Pseudomonas aeruginosa. Genetics 2010; 186:1345–1354 [View Article] [PubMed]
     [Google Scholar]
  105. Lenski RE. Experimental evolution and the dynamics of adaptation and genome evolution in microbial populations. ISME J 2017; 11:2181–2194 [View Article] [PubMed]
     [Google Scholar]
  106. Vogwill T, Kojadinovic M, Furió V, MacLean RC. Testing the role of genetic background in parallel evolution using the comparative experimental evolution of antibiotic resistance. Mol Biol Evol 2014; 31:3314–3323 [View Article] [PubMed]
     [Google Scholar]
  107. Pentz JT, Lind PA. Forecasting of phenotypic and genetic outcomes of experimental evolution in Pseudomonas protegens. PLoS Genet 2021; 17:e1009722 [View Article] [PubMed]
     [Google Scholar]
  108. Cherry JL. Methylation-induced hypermutation in natural populations of bacteria. J Bacteriol 2018; 200:e00371-18 [View Article] [PubMed]
     [Google Scholar]
  109. Löytynoja A, Goldman N. Short template switch events explain mutation clusters in the human genome. Genome Res 2017; 27:1039–1049 [View Article] [PubMed]
     [Google Scholar]
  110. Lavi B, Levy Karin E, Pupko T, Hazkani-Covo E. The prevalence and evolutionary conservation of inverted repeats in proteobacteria. Genome Biol Evol 2018; 10:918–927 [View Article] [PubMed]
     [Google Scholar]
  111. Yoshiyama K, Maki H. Spontaneous hotspot mutations resistant to mismatch correction in Escherichia coli: transcription-dependent mutagenesis involving template-switching mechanisms. J Mol Biol 2003; 327:7–18 [View Article] [PubMed]
     [Google Scholar]
  112. Voineagu I, Narayanan V, Lobachev KS, Mirkin SM. Replication stalling at unstable inverted repeats: interplay between DNA hairpins and fork stabilizing proteins. Proc Natl Acad Sci U S A 2008; 105:9936–9941 [View Article] [PubMed]
     [Google Scholar]
  113. Moxon R, Bayliss C, Hood D. Bacterial contingency loci: the role of simple sequence DNA repeats in bacterial adaptation. Annu Rev Genet 2006; 40:307–333 [View Article] [PubMed]
     [Google Scholar]
  114. Darling AE, Miklós I, Ragan MA. Dynamics of genome rearrangement in bacterial populations. PLoS Genet 2008; 4:e1000128 [View Article] [PubMed]
     [Google Scholar]
  115. Tillier ERM, Collins RA. Genome rearrangement by replication-directed translocation. Nat Genet 2000; 26:195–197 [View Article]
     [Google Scholar]
  116. Mira A, Ochman H, Moran NA. Deletional bias and the evolution of bacterial genomes. Trends Genet 2001; 17:589–596 [View Article] [PubMed]
     [Google Scholar]
  117. Raeside C, Gaffé J, Deatherage DE, Tenaillon O, Briska AM et al. Large chromosomal rearrangements during a long-term evolution experiment with Escherichia coli. mBio 2014; 5:1–13 [View Article]
     [Google Scholar]
  118. Schaaper RM, Dunn RL. Spectra of spontaneous mutations in Escherichia coli strains defective in mismatch correction: the nature of in vivo DNA replication errors. Proc Natl Acad Sci USA 1987; 84:6220–6224 [View Article]
     [Google Scholar]
  119. Wong A, Rodrigue N, Kassen R, Guttman DS. Genomics of adaptation during experimental evolution of the opportunistic pathogen Pseudomonas aeruginosa. PLoS Genet 2012; 8:e1002928 [View Article]
     [Google Scholar]
  120. Blokzijl F, Janssen R, van Boxtel R, Cuppen E. MutationalPatterns: comprehensive genome-wide analysis of mutational processes. Genome Med 2018; 10:33 [View Article] [PubMed]
     [Google Scholar]
  121. Jack BR, Leonard SP, Mishler DM, Renda BA, Leon D et al. Predicting the genetic stability of engineered DNA sequences with the EFM calculator. ACS Synth Biol 2015; 4:939–943 [View Article] [PubMed]
     [Google Scholar]
  122. Monroe JG, Srikant T, Carbonell-Bejerano P, Becker C, Lensink M et al. Mutation bias reflects natural selection in Arabidopsis thaliana. Nature 2022; 602:101–105 [View Article]
     [Google Scholar]
  123. Lind PA, Andersson DI. Whole-genome mutational biases in bacteria. Proc Natl Acad Sci USA 2008; 105:17878–17883 [View Article]
     [Google Scholar]
  124. Georgakopoulos-Soares I, Koh G, Momen SE, Jiricny J, Hemberg M et al. Transcription-coupled repair and mismatch repair contribute towards preserving genome integrity at mononucleotide repeat tracts. Nat Commun 2020; 11:1–9 [View Article]
     [Google Scholar]
  125. Hoede C, Denamur E, Tenaillon O. Selection acts on DNA secondary structures to decrease transcriptional mutagenesis. PLOS Genet 2006; 2:e176 [View Article] [PubMed]
     [Google Scholar]
  126. Bailey SF, Blanquart F, Bataillon T, Kassen R. What drives parallel evolution?: How population size and mutational variation contribute to repeated evolution. Bioessays 2017; 39:1–9 [View Article] [PubMed]
     [Google Scholar]
  127. Weinreich DM, Delaney NF, Depristo MA, Hartl DL. Darwinian evolution can follow only very few mutational paths to fitter proteins. Science 2006; 312:111–114 [View Article] [PubMed]
     [Google Scholar]
  128. Drake JW. A constant rate of spontaneous mutation in DNA-based microbes. Proc Natl Acad Sci USA 1991; 88:7160–7164 [View Article]
     [Google Scholar]
  129. Kishony R, Leibler S. Environmental stresses can alleviate the average deleterious effect of mutations. J Biol 2003; 2:14 [View Article] [PubMed]
     [Google Scholar]
  130. Castañeda-García A, Prieto AI, Rodríguez-Beltrán J, Alonso N, Cantillon D et al. A non-canonical mismatch repair pathway in prokaryotes. Nat Commun 2017; 8:14246 [View Article] [PubMed]
     [Google Scholar]
  131. Castañeda-García A, Martín-Blecua I, Cebrián-Sastre E, Chiner-Oms A, Torres-Puente M et al. Specificity and mutagenesis bias of the mycobacterial alternative mismatch repair analyzed by mutation accumulation studies. Sci Adv 2020; 6:eaay4453 [View Article] [PubMed]
     [Google Scholar]
  132. Liu H, Zhang J, Zhai W. Is the mutation rate lower in genomic regions of stronger selective constraints?. Mol Biol Evol 2022; 39:msac169 [View Article] [PubMed]
     [Google Scholar]
  133. Wang L, Ho AT, Hurst LD, Yang S. Re-evaluating evidence for adaptive mutation rate variation. Nature 2023; 619:E52–E56 [View Article] [PubMed]
     [Google Scholar]
  134. Monroe JG, Murray KD, Xian W, Srikant T, Carbonell-Bejerano P et al. Reply to: re-evaluating evidence for adaptive mutation rate variation. Nature 2023; 619:E57–E60 [View Article] [PubMed]
     [Google Scholar]
  135. Lynch M. Evolution of the mutation rate. Trends Genet 2010; 26:345–352 [View Article] [PubMed]
     [Google Scholar]
  136. Sung W, Ackerman MS, Miller SF, Doak TG, Lynch M. Drift-barrier hypothesis and mutation-rate evolution. Proc Natl Acad Sci U S A 2012; 109:18488–18492 [View Article] [PubMed]
     [Google Scholar]
  137. Tenaillon O, Taddei F, Radmian M, Matic I. Second-order selection in bacterial evolution: selection acting on mutation and recombination rates in the course of adaptation. Res Microbiol 2001; 152:11–16 [View Article] [PubMed]
     [Google Scholar]
  138. Swings T, Van den Bergh B, Wuyts S, Oeyen E, Voordeckers K et al. Adaptive tuning of mutation rates allows fast response to lethal stress in Escherichia coli. Elife 2017; 6:e22939 [View Article] [PubMed]
     [Google Scholar]
  139. Moxon ER, Rainey PB, Nowak MA, Lenski RE. Adaptive evolution of highly mutable loci in pathogenic bacteria. Curr Biol 1994; 4:24–33 [View Article] [PubMed]
     [Google Scholar]
  140. De Ste Croix M, Holmes J, Wanford JJ, Moxon ER, Oggioni MR et al. Selective and non-selective bottlenecks as drivers of the evolution of hypermutable bacterial loci. Mol Microbiol 2020; 113:672–681 [View Article] [PubMed]
     [Google Scholar]
  141. Gor V, Ohniwa RL, Morikawa K. No change, no life? What we know about phase variation in Staphylococcus aureus. Microorganisms 2021; 9:244 [View Article]
     [Google Scholar]
  142. Phillips ZN, Tram G, Seib KL, Atack JM. Phase-variable bacterial loci: how bacteria gamble to maximise fitness in changing environments. Biochem Soc Trans 2019; 47:1131–1141 [View Article]
     [Google Scholar]
  143. Tan A, Atack JM, Jennings MP, Seib KL. The capricious nature of bacterial pathogens: phasevarions and vaccine development. Front Immunol 2016; 7:586 [View Article]
     [Google Scholar]
  144. Bayliss CD, Field D, Moxon ER. The simple sequence contingency loci of Haemophilus influenzae and Neisseria meningitidis. J Clin Invest 2001; 107:657–666 [View Article]
     [Google Scholar]
  145. Jerome JP, Bell JA, Plovanich-Jones AE, Barrick JE, Brown CT et al. Standing genetic variation in contingency loci drives the rapid adaptation of Campylobacter jejuni to a novel host. PLoS One 2011; 6:e16399 [View Article]
     [Google Scholar]
  146. Zhou K, Aertsen A, Michiels CW. The role of variable DNA tandem repeats in bacterial adaptation. FEMS Microbiol Rev 2014; 38:119–141 [View Article] [PubMed]
     [Google Scholar]
  147. Carasso S, Zaatry R, Hajjo H, Kadosh-Kariti D, Ben-Assa N et al. Inflammation and bacteriophages affect DNA inversion states and functionality of the gut microbiota. bioRxiv [View Article]
     [Google Scholar]
  148. Kudla G, Murray AW, Tollervey D, Plotkin JB. Coding-sequence determinants of gene expression in Escherichia coli. Science 2009; 324:255–258 [View Article] [PubMed]
     [Google Scholar]
  149. Kristofich J, Morgenthaler AB, Kinney WR, Ebmeier CC, Snyder DJ et al. Synonymous mutations make dramatic contributions to fitness when growth is limited by a weak-link enzyme. PLoS Genet 2018; 14:e1007615 [View Article]
     [Google Scholar]
  150. Lebeuf-Taylor E, McCloskey N, Bailey SF, Hinz A, Kassen R. The distribution of fitness effects among synonymous mutations in a gene under directional selection. eLife 2019; 8: [View Article]
     [Google Scholar]
  151. Frumkin I, Lajoie MJ, Gregg CJ, Hornung G, Church GM et al. Codon usage of highly expressed genes affects proteome-wide translation efficiency. Proc Natl Acad Sci USA 2018; 115:E4940–E4949 [View Article]
     [Google Scholar]
  152. Rahman S, Kosakovsky Pond SL, Webb A, Hey J. Weak selection on synonymous codons substantially inflates dN/dS estimates in bacteria. Proc Natl Acad Sci U S A 2021; 118:e2023575118 [View Article] [PubMed]
     [Google Scholar]
  153. Lind PA, Libby E, Herzog J, Rainey PB. Predicting mutational routes to new adaptive phenotypes. eLife 2019; 8: [View Article]
     [Google Scholar]
  154. Phaneuf PV, Gosting D, Palsson BO, Feist AM. ALEdb 1.0: a database of mutations from adaptive laboratory evolution experimentation. Nucleic Acids Res 2019; 47:D1164–D1171 [View Article]
     [Google Scholar]
  155. Rocha EPC, Touchon M, Feil EJ. Similar compositional biases are caused by very different mutational effects. Genome Res 2006; 16:1537–1547 [View Article] [PubMed]
     [Google Scholar]
  156. Sun TA, Lind PA. Distribution of mutation rates challenges evolutionary predictability. Microbiology 2023; 169:001323 [View Article]
     [Google Scholar]
  157. Ganai RA, Johansson E. DNA replication-a matter of fidelity. Mol Cell 2016; 62:745–755 [View Article] [PubMed]
     [Google Scholar]
  158. Li W, Lynch M. Universally high transcript error rates in bacteria. eLife 2020; 9:1–15 [View Article]
     [Google Scholar]
  159. Merrikh H, Zhang Y, Grossman AD, Wang JD. Replication–transcription conflicts in bacteria. Nat Rev Microbiol 2012; 10:449–458 [View Article]
     [Google Scholar]
  160. Long H, Miller SF, Williams E, Lynch M, Ruiz-Trillo I. Specificity of the DNA Mismatch Repair System (MMR) and mutagenesis bias in bacteria. Mol Biol Evol 2018; 35:2414–2421 [View Article]
     [Google Scholar]
  161. Pomerantz RT, O’Donnell M. Direct restart of a replication fork stalled by a head-on RNA polymerase. Science 2010; 327:590–592 [View Article] [PubMed]
     [Google Scholar]
  162. Million-Weaver S, Samadpour AN, Moreno-Habel DA, Nugent P, Brittnacher MJ et al. An underlying mechanism for the increased mutagenesis of lagging-strand genes in Bacillus subtilis. Proc Natl Acad Sci U S A 2015; 112:E1096–105 [View Article] [PubMed]
     [Google Scholar]
  163. Lang KS, Hall AN, Merrikh CN, Ragheb M, Tabakh H et al. Replication-transcription conflicts generate R-loops that orchestrate bacterial stress survival and pathogenesis. Cell 2017; 170:787–799 [View Article] [PubMed]
     [Google Scholar]
  164. Brazda V, Fojta M, Bowater RP. Structures and stability of simple DNA repeats from bacteria. Biochem J 2020; 477:325–339 [View Article] [PubMed]
     [Google Scholar]
  165. Watanabe S, Ohbayashi R, Kanesaki Y, Saito N, Chibazakura T et al. Intensive DNA replication and metabolism during the lag phase in cyanobacteria. PLoS One 2015; 10:e0136800 [View Article]
     [Google Scholar]
  166. Maddamsetti R, Grant NA. Divergent evolution of mutation rates and biases in the long-term evolution experiment with Escherichia coli. Genome Biol Evol 2020; 12:1591–1603 [View Article] [PubMed]
     [Google Scholar]
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Mutation bias and adaptation in bacteria
Microbiology 169, 001404 (2023); https://doi.org/10.1099/mic.0.001404
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