Mutational Spectrum Drives the Rise of Mutator Bacteria
Understanding how mutator strains emerge in bacterial populations is relevant both to evolutionary theory and to reduce the threat they pose in clinical settings. The rise of mutator alleles is understood as a result of their hitchhiking with linked beneficial mutations, although the factors that govern this process remain unclear. A prominent but underappreciated fact is that each mutator allele increases only a specific spectrum of mutational changes. This spectrum has been speculated to alter the distribution of fitness effects of beneficial mutations, potentially affecting hitchhiking. To study this possibility, we analyzed the fitness distribution of beneficial mutations generated from different mutator and wild-type Escherichia coli strains. Using antibiotic resistance as a model system, we show that mutational spectra can alter these distributions substantially, ultimately determining the competitive ability of each strain across environments. Computer simulation showed that the effect of mutational spectrum on hitchhiking dynamics follows a non-linear function, implying that even slight spectrum-dependent fitness differences are sufficient to alter mutator success frequency by several orders of magnitude. These results indicate an unanticipated central role for the mutational spectrum in the evolution of bacterial mutation rates. At a practical level, this study indicates that knowledge of the molecular details of resistance determinants is crucial for minimizing mutator evolution during antibiotic therapy.
Vyšlo v časopise:
Mutational Spectrum Drives the Rise of Mutator Bacteria. PLoS Genet 9(1): e32767. doi:10.1371/journal.pgen.1003167
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pgen.1003167
Souhrn
Understanding how mutator strains emerge in bacterial populations is relevant both to evolutionary theory and to reduce the threat they pose in clinical settings. The rise of mutator alleles is understood as a result of their hitchhiking with linked beneficial mutations, although the factors that govern this process remain unclear. A prominent but underappreciated fact is that each mutator allele increases only a specific spectrum of mutational changes. This spectrum has been speculated to alter the distribution of fitness effects of beneficial mutations, potentially affecting hitchhiking. To study this possibility, we analyzed the fitness distribution of beneficial mutations generated from different mutator and wild-type Escherichia coli strains. Using antibiotic resistance as a model system, we show that mutational spectra can alter these distributions substantially, ultimately determining the competitive ability of each strain across environments. Computer simulation showed that the effect of mutational spectrum on hitchhiking dynamics follows a non-linear function, implying that even slight spectrum-dependent fitness differences are sufficient to alter mutator success frequency by several orders of magnitude. These results indicate an unanticipated central role for the mutational spectrum in the evolution of bacterial mutation rates. At a practical level, this study indicates that knowledge of the molecular details of resistance determinants is crucial for minimizing mutator evolution during antibiotic therapy.
Zdroje
1. BoeL, DanielsenM, KnudsenS, PetersenJB, MaymannJ, et al. (2000) The frequency of mutators in populations of Escherichia coli. Mutat Res 448: 47–55.
2. FunchainP, YeungA, StewartJL, LinR, SlupskaMM, et al. (2000) The consequences of growth of a mutator strain of Escherichia coli as measured by loss of function among multiple gene targets and loss of fitness. Genetics 154: 959–970.
3. LeClercJE, LiB, PayneWL, CebulaTA (1996) High mutation frequencies among Escherichia coli and Salmonella pathogens. Science 274: 1208–1211.
4. SniegowskiPD, GerrishPJ, LenskiRE (1997) Evolution of high mutation rates in experimental populations of E. coli. Nature 387: 703–705.
5. MaoEF, LaneL, LeeJ, MillerJH (1997) Proliferation of mutators in a cell population. J Bacteriol 179: 417–422.
6. OliverA, CantónR, CampoP, BaqueroF, BlázquezJ (2000) High frequency of hypermutable Pseudomonas aeruginosa in cystic fibrosis lung infection. Science 288: 1251–1253.
7. RichardsonAR, YuZ, PopovicT, StojiljkovicI (2002) Mutator clones of Neisseria meningitidis in epidemic serogroup A disease. Proc Natl Acad Sci USA 99: 6103–6107.
8. PalC, MaciaMD, OliverA, SchacharI, BucklingA (2007) Coevolution with viruses drives the evolution of bacterial mutation rates. Nature 450: 1079–1081.
9. LeighEG (1970) Natural selection and mutability. Am Nat 104: 301–305.
10. TaddeiF, RadmanM, Maynard-SmithJ, ToupanceB, GouyonPH, et al. (1997) Role of mutator alleles in adaptive evolution. Nature 387: 700–702.
11. TenaillonO, ToupanceB, Le NagardH, TaddeiF, GodelleB (1999) Mutators, population size, adaptive landscape and the adaptation of asexual populations of bacteria. Genetics 152: 485–493.
12. Notley-McRobbL, SeetoS, FerenciT (2002) Enrichment and elimination of mutY mutators in Escherichia coli populations. Genetics 162: 1055–1062.
13. ShaverAC, DombrowskiPG, SweeneyJY, TreisT, ZappalaRM, et al. (2002) Fitness evolution and the rise of mutator alleles in experimental Escherichia coli populations. Genetics 162: 557–566.
14. TenaillonO, Le NagardH, GodelleB, TaddeiF (2000) Mutators and sex in bacteria: Conflict between adaptive strategies. Proc Natl Acad Sci USA 97: 10465–10470.
15. BlázquezJ (2003) Hypermutation as a factor contributing to the acquisition of antimicrobial resistance. Clin Infect Dis 37: 1201–1209.
16. LabatF, PradillonO, GarryL, PeuchmaurM, FantinB, et al. (2005) Mutator phenotype confers advantage in Escherichia coli chronic urinary tract infection pathogenesis. FEMS Immunol. Med Microbiol 44: 317–321.
17. OliverA, MenaA (2010) Bacterial hypermutation in cystic fibrosis, not only for antibiotic resistance. Clin Microbiol Infect 16: 798–808.
18. TravisJMJ, TravisER (2002) Mutator dynamics in fluctuating environments. Proc Biol Sci 269: 591–597.
19. TanakaMM, BergstromCT, LevinBR (2003) The evolution of mutator genes in bacterial populations: the roles of environmental change and timing. Genetics 164: 843–854.
20. WylieCS, GhimCM, KesslerD, LevineH (2009) The fixation probability of rare mutators in finite asexual populations. Genetics 181: 1595–1612.
21. AndreJ, GodelleB (2006) The evolution of mutation rate in finite asexual populations. Genetics 172: 611–626.
22. MaharjanR, SeetoS, Notley-McRobbL, FerenciT (2006) Clonal adaptive radiation in a constant environment. Science 313: 514–517.
23. TenaillonO, Rodríguez-VerdugoA, GautRL, McDonaldP, BennettAF, et al. (2012) The molecular diversity of adaptive convergence. Science 335: 457–461.
24. DenamurE, MaticI (2006) Evolution of mutation rates in bacteria. Mol Microbiol 60: 820–827.
25. MillerJH (1996) Spontaneous mutators in bacteria: insights into pathways of mutagenesis and repair. Annu Rev Microbiol 50: 625–643.
26. MacLeanRC, HallAR, PerronGG, BucklingA (2010) The population genetics of antibiotic resistance: integrating molecular mechanisms and treatment contexts. Nat Rev Genet 11: 405–414.
27. GaribyanL, HuangT, KimM, WolffE, NguyenA, et al. (2003) Use of the rpoB gene to determine the specificity of base substitution mutations on the Escherichia coli chromosome. DNA Repair 2: 593–608.
28. TimmsAR, SteingrimsdottirH, LehmannAR, BridgesBA (1992) Mutant sequences in the rpsL gene of Escherichia coli B/r: mechanistic implications for spontaneous and ultraviolet light mutagenesis. Mol Gen Genet 232: 89–96.
29. BjedovI, DasguptaCN, SladeD, Le BlastierS, SelvaM, et al. (2007) Involvement of Escherichia coli DNA polymerase IV in tolerance of cytotoxic alkylating DNA lesions in vivo. Genetics 176: 1431–1440.
30. HallAR, IlesJC, MacLeanRC (2002) The fitness cost of rifampicin resistance in Pseudomonas aeruginosa depends on demand for RNA polymerase. Genetics 187: 817–822.
31. ReynoldsMG (2000) Compensatory evolution in rifampin-resistant Escherichia coli. Genetics 156: 1471–1481.
32. Kurland C, Hughes D, Ehrenberg M (1996) Limitations of translational accuracy. In: Neidhardt F.C III, et al., editors. Escherichia coli and Salmonella: Cellular and molecular biology. ASM Press; Washington, DC: 1996. pp. 979–1004.
33. Kimura M (1994) Population genetics, molecular evolution, and the neutral theory: selected papers (University of Chicago Press)
34. BohannanBJ, LenskiRE (2000) Linking genetic change to community evolution: insights from studies of bacteria and bacteriophage. Ecol Lett 3: 362–377.
35. AnderssonDI, HughesD (2010) Antibiotic resistance and its cost: is it possible to reverse resistance? Nat Rev Micro 8: 260–271.
36. PrindleMJ, FoxEJ, LoebLA (2010) The mutator phenotype in cancer: molecular mechanisms and targeting strategies. Curr. Drug Targets 11: 1296–1303.
37. LenskiRE, RoseMR, SimpsonSC, TadlerSC (1991) Long-term experimental evolution in Escherichia coli I. Adaptation and divergence during 2,000 generations. Am Nat 138: 1315–1341.
38. R Development Core Team (2011) R: A language and environment for statistical computing, reference index version 2.13.0. (R Foundation for Statistical Computing, Vienna).
39. de VisserJA, ZeylCW, GerrishPJ, BlanchardJL, LenskiRE (1999) Diminishing returns from mutation supply rate in asexual populations. Science 283: 404–406.
40. AhrensJH, DieterU (1982) Computer generation of Poisson deviates from modified normal distributions. ACM Trans Math Softw 8: 163–179.
41. RozenDE, de VisserJAGM, GerrishPJ (2002) Fitness effects of fixed beneficial mutations in microbial populations. Curr Biol 12: 1040–1045.
42. TrindadeS, PerfeitoL, GordoI (2010) Rate and effects of spontaneous mutations that affect fitness in mutator Escherichia coli. Philos Trans R Soc Lond B Biol Sci 365: 1177–1186.
Štítky
Genetika Reprodukčná medicínaČlánok vyšiel v časopise
PLOS Genetics
2013 Číslo 1
- Je „freeze-all“ pro všechny? Odborníci na fertilitu diskutovali na virtuálním summitu
- Gynekologové a odborníci na reprodukční medicínu se sejdou na prvním virtuálním summitu
Najčítanejšie v tomto čísle
- Function and Regulation of , a Gene Implicated in Autism and Human Evolution
- The [] Prion Exists as a Dynamic Cloud of Variants
- Comprehensive Methylome Characterization of and at Single-Base Resolution
- Susceptibility Loci Associated with Specific and Shared Subtypes of Lymphoid Malignancies