Quantifying the Adaptive Potential of an Antibiotic Resistance Enzyme

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For a quantitative understanding of the process of adaptation, we need to understand its “raw material,” that is, the frequency and fitness effects of beneficial mutations. At present, most empirical evidence suggests an exponential distribution of fitness effects of beneficial mutations, as predicted for Gumbel-domain distributions by extreme value theory. Here, we study the distribution of mutation effects on cefotaxime (Ctx) resistance and fitness of 48 unique beneficial mutations in the bacterial enzyme TEM-1 β-lactamase, which were obtained by screening the products of random mutagenesis for increased Ctx resistance. Our contributions are threefold. First, based on the frequency of unique mutations among more than 300 sequenced isolates and correcting for mutation bias, we conservatively estimate that the total number of first-step mutations that increase Ctx resistance in this enzyme is 87 [95% CI 75–189], or 3.4% of all 2,583 possible base-pair substitutions. Of the 48 mutations, 10 are synonymous and the majority of the 38 non-synonymous mutations occur in the pocket surrounding the catalytic site. Second, we estimate the effects of the mutations on Ctx resistance by determining survival at various Ctx concentrations, and we derive their fitness effects by modeling reproduction and survival as a branching process. Third, we find that the distribution of both measures follows a Fréchet-type distribution characterized by a broad tail of a few exceptionally fit mutants. Such distributions have fundamental evolutionary implications, including an increased predictability of evolution, and may provide a partial explanation for recent observations of striking parallel evolution of antibiotic resistance.

Vyšlo v časopise: Quantifying the Adaptive Potential of an Antibiotic Resistance Enzyme. PLoS Genet 8(6): e32767. doi:10.1371/journal.pgen.1002783
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1002783

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1. ToprakEVeresAMichelJ-BChaitRHartlDL 2012 Evolutionary paths to antibiotic resistance under dynamically sustained drug selection. Nat Genet 44 101 105

2. SalverdaMLMDellusEGorterFADebetsAJMVan der OostJ 2011 Initial mutations direct alternative pathways of protein evolution. PLoS Genet 7 e1001321 doi:10.1371/journal.pgen.1001321

3. SniegowskiPDGerrishPJ 2010 Beneficial mutations and the dynamics of adaptation in asexual populations. Phil Trans R Soc B 365 1255 1263

4. WeinreichDMDelaneyNFDePristoMAHartlDL 2006 Darwinian evolution can follow only very few mutational paths to fitter proteins. Science 312 111 114

5. OrrHA 1998 Testing natural selection versus genetic drift in phenotypic evolution using quantitative trait locus data. Genetics 149 2099 2104

6. OrrHA 2003 The distribution of fitness effects among beneficial mutations. Genetics 163 1519 1526

7. OrrHA 2010 The population genetics of beneficial mutations. Phil Trans R Soc B 365 1195 1201

8. GillespieJH 1984 Molecular evolution over the mutational landscape. Evolution 38 1116 1129

9. KassenRBataillonT 2006 Distribution of fitness effects among beneficial mutations prior to selection in experimental populations of bacteria. Nat Genet 38 484 488

10. MacLeanRCBucklingA 2009 The distribution of fitness effects of beneficial mutations in Pseudomonas aeruginosa. PLoS Genet 5 e1000406 doi:10.1371/journal.pgen.1000406

11. RokytaDRJoycePCaudleSBWichmanHA 2005 An empirical test of the mutational landscape model of adaptation using a single-stranded DNA virus. Nat Genet 37 441 444

12. SanjuánRMoyaAElenaSF 2004 The distribution of fitness effects caused by single-nucleotide substitutions in an RNA virus. Proc Natl Acad Sci U S A 101 8396 8401

13. McDonaldMJCooperTFBeaumontHJERaineyPB 2010 The distribution of fitness effects of new beneficial mutations in Pseudomonas fluorescence. Biol Lett 7 98 100

14. JoycePRokytaDRBeiselCJOrrHA 2008 A General Extreme Value Theory Model for the Adaptation of DNA Sequences Under Strong Selection and Weak Mutation. Genetics 180 1627 1643

15. BataillonTZhangTKassenR 2011 Cost of Adaptation and Fitness Effects of Beneficial Mutations in Pseudomonas fluorescens. Genetics 189 939 949

16. RokytaDRBeiselCJJoycePFerrisMTBurchCL 2008 Beneficial Fitness Effects Are Not Exponential for Two Viruses. J Mol Evol 67 368 376

17. JainKSeetharamanS 2011 Multiple Adaptive Substitutions During Evolution in Novel Environments. Genetics 189 1029 1043

18. NeidhartJKrugJ 2011 Adaptive Walks and Extreme Value Theory. Phys Rev Lett 107 178102

19. JainK 2011 Number of adaptive steps to a local fitness peak. EPL 96 58006

20. OrrHA 2005 The probability of parallel evolution. Evolution 59 216 220

21. OrrHA 2003 A minimum on the mean number of steps taken in adaptive walks. J Theor Biol 220 241 247

22. FogleCANagleJLDesaiMM 2008 Clonal Interference, Multiple Mutations and Adaptation in Large Asexual Populations. Genetics 180 2163 2173

23. ParkS-CSimonDKrugJ 2010 The speed of evolution in large asexual populations. J Stat Phys 138 381 410

24. PerfeitoLFernandesLMotaCGordoI 2007 Adaptive mutations in bacteria: high rate and small effects. Science 317 813 815

25. SalverdaMLMde VisserJAGMBarlowM 2010 Natural evolution of TEM-1 beta-lactamase: experimental reconstruction and clinical relevance. FEMS Microbiol Rev 34 1015 1036

26. BarlowMHallBG 2002 Predicting evolutionary potential: In vitro evolution accurately reproduces natural evolution of the TEM beta-lactamase. Genetics 160 823 832

27. StemmerWPC 1994 Rapid evolution of a protein in vitro by DNA shuffling. Nature 370 389 391

28. DavisonACSmithRL 1990 Models for exeedances over high thresholds. J R Stat Soc B (Methodological) 52 393 442

29. StevensKESebertME 2011 Frequent Beneficial Mutations during Single-Colony Serial Transfer of Streptococcus pneumoniae. PLoS Genet 7 e1002232 doi:10.1371/journal.pgen.1002232

30. LalicJCuevasJMElenaSF 2011 Effect of Host Species on the Distribution of Mutational Fitness Effects for an RNA Virus. PLoS Genet 7 e1002378 doi:10.1371/journal.pgen.1002378

31. RomeroPAArnoldFH 2009 Exploring protein fitness landscapes by directed evolution. Nat Rev Mol Cell Biol 10 866 876

32. HallARGriffithsVFMacLeanRCColegraveN 2010 Mutational neighbourhood and mutation supply rate constrain adaptation in Pseudomonas aeruginosa. Proc R Soc B 277 643 650

33. DePristoMAWeinreichDMHartlDL 2005 Missense meanderings in sequence space: a biophysical view of protein evolution. Nat Rev Genet 6 678 687

34. HuangWPetrosinoJHirschMShenkinPSPalzkillT 1996 Amino acid sequence determinants of beta-lactamase structure and activity. J Mol Biol 258 688 703

35. SoskineMTawfikDS 2010 Mutational effects and the evolution of new protein functions. Nat Rev Genet 11 572 582

36. KryazhimskiySRiceDPDesaiMM 2012 Population Subdivision and Adaptation in Asexual Populations of Saccharomyces cerevisiae. Evolution in press

37. WangXMinasovGShoichetBK 2002 Evolution of an antibiotic resistance enzyme constrained by stability and activity trade-offs. J Mol Biol 320 85 95

38. GoldsmithMTawfikDS 2009 Potential role of phenotypic mutations in the evolution of protein expression and stability. Proc Natl Acad Sci U S A 106 6197 6202

39. DeanaAEhrlichRReissC 1996 Synonymous codon selection controls in vivo turnover and mount of mRNA in Escherichia coli bla and ompA genes. J Bacteriol 178 2718 2720

40. ZaluckiYMGittinsKLJenningsMP 2008 Secretory sequence signal non-optimal codons are required for expression and export of beta-lactamase. Biochem Biophys Res Comm 366 135 141

41. DuanJBWainwrightMSComeronJMSaitouNSandersAR 2003 Synonymous mutations in the human dopamine receptor D2 (DRD2) affect mRNA stability and synthesis of the receptor. Hum Mol Genet 12 205 216

42. LindPABergOGAnderssonDI 2010 Mutational Robustness of Ribosomal Protein Genes. Science 330 825 827

43. VakulenkoSBTaibi-TronchePTothMMassovaILernerSA 1999 Effects on substrate profile by mutational substitutions at positions 164 and 179 of the class A TEMpUC19 beta-lactamase from Escherichia coli. J Biol Chem 274 23052 23060

44. OrenciaMCYoonJSNessJEStemmerWPCStevensRC 2001 Predicting the emergence of antibiotic resistance by directed evolution and structural analysis. Nat Struct Biol 8 238 242

45. NegriM-CLipsitchMBlázquezJLevinBRBaqueroF 2000 Concentration-dependent selection of small phenotypic differences in TEM beta-lactamase-mediated antibiotic resistance. Antimicrob Agents Chemother 44 2485 2491

46. PaulanderWPennhagAAnderssonDIMaisnier-PatinS 2007 Caenorhabditis elegans as a model to determine fitness of antibiotic-resistant Salmonella enterica serovar typhimuriu. Antimicrob Agents Chemother 51 766 769

47. AnderssonDIHughesD 2010 Antibiotic resistance and its cost: is it possible to reverse resistance? Nat Rev Microb 8 260 271

48. MedeirosAA 1997 Evolution and dissemniation of beta-lactamases accelerated by generations of beta-lactam antibiotics. Clin Infect Dis 24 S19 S45

49. DerridaB 1994 Non-self averaging effects in sums of random variables, spin glasses, random maps and random walks. FannesMMaesCVerbeureA On three levels: Micro-, meso- and macro-approaches in physics New York Plenum Press 125 137

50. GiffordDRSchoustraSEKassenR 2011 The length of adaptive walks is insensitive to starting fitness in Aspergillus nidulans. Evolution 65 3070 3078

51. SchoustraSEBataillonTGiffordDRKassenR 2009 The Properties of Adaptive Walks in Evolving Populations of Fungus. PLOS Biol 7 e1000250 doi:10.1371/journal.pbio.1000250

52. SunF 1995 The polymerase chain reaction and branching processes. J Comp Biol 2 63 86

53. PatrickWMFirthAEBlackburnJM 2003 User-friendly algorithms for estimating completeness and diversity in randomized protein-encoding libraries. Protein Eng 16 451 457

54. AmblerRPCoulsonAFWFrereJMGhuysenJMJorisB 1991 A standard numbering scheme for the class A beta-lactamase. Biochem J 276 269 270

55. DeLanoWL 2002 The PyMOL Molecular Graphics System Palo Alto, CA DeLano Scientific

56. JaffeAChabbertYASemoninO 1982 Role of porin proteins OmpF and OmpC in the permeation of beta-lactams. Antimicrob Agents Chemother 22 942 948

57. FinkelsteinMTuckerHGVeehJA 1998 Confidence intervals for the number of unseen types. Stat Prob Lett 37 423 430

58. BeiselCJRokytaDRWichmanHAJoyceP 2007 Testing the extreme value domain of attraction for distributions of beneficial fitness effects. Genetics 176 2441 2449

59. PickandsJ 1975 Statistical inference using extreme order statistics. Ann Stat 3 119 131

60. ChoulakianVStephensMA 2001 Goodness-of-fit tests for the generalized pareto distribution. Technometrics 43 478 484

61. LangMOuardaTBMJBobéeB 1999 Towards operational guidelines for over-threshold modeling. J Hydrol 225 103 117

62. HaldaneJBS 1927 The mathematical theory of natural and artificial selection. Proc Cambridge Phil Soc 23 838 844