Payoffs, Not Tradeoffs, in the Adaptation of a Virus to Ostensibly Conflicting Selective Pressures

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One of the most fundamental tradeoffs in evolutionary biology is between survival and reproduction. Many parasites experience distinct selective pressures during different stages of their life cycles; mutations arising during one stage may be beneficial, but come at a cost during another. For example, many viruses experience favorable growth conditions within a host punctuated with harsh conditions outside the host during transmission. We conducted an evolution experiment with a ssDNA microvirid bacteriophage selecting for growth within the host and capsid stability outside the host in the presence of extreme environmental conditions (low pH or high temperature), and we hypothesized detection of a tradeoff between reproduction and survival. We found that individual mutations gained under rapidly fluctuating selective pressures similar to those experienced by pathogens increased both growth rate and capsid stability; tradeoffs were completely absent. We compared the effects of beneficial mutations gained in response to selection for growth rate alone and found the expected tradeoffs on capsid stability. Tradeoffs therefore arise when selection is not working to avoid them. Otherwise, payoffs prevail.

Vyšlo v časopise: Payoffs, Not Tradeoffs, in the Adaptation of a Virus to Ostensibly Conflicting Selective Pressures. PLoS Genet 10(10): e32767. doi:10.1371/journal.pgen.1004611
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1004611

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Zdroje

1. OttoSP (2004) Two steps forward, one step back: the pleiotropic effects of favoured alleles. Proceedings of the Royal Society of London B Biological Sciences 271 : 705–714.

2. OstmanB, HintzeA, AdamiC (2012) Impact of epistasis and pleiotropy on evolutionary adaptation. Proceedings of the Royal Society of London B Biological Sciences 279 : 247–256.

3. MatherK, HarrisonB (1949) The manifold effect of selection. Heredity 23 : 131–162.

4. CooperVS, LenskiRE (2000) The population genetics of ecological specialization in evolving Escherichia coli populations. Nature 407 : 736–739.

5. MagwireM, YamamotoA, CarboneM, RoshinaN, SymonenkoA, et al. (2010) Quantitative and molecular genetic analyses of mutations increasing drosophila life span. PLoS Genetics 6: e1001037.

6. WengerJ, PiotrowskiJ, NagarajanS, ChiottiK, SherlockG, et al. (2011) Hunger artists: yeast adapted to carbon limitation show trade-offs under carbon sufficiency. PLoS Genetics 7: e1002202.

7. BullJJ, BadgettMR, WichmanHA (2000) Big-benefit mutations in a bacteriophage inhibited with heat. Molecular Biology and Evolution 17 : 942–950.

8. LeeKH, MillerCR, NagelAC, WichmanHA, JoyceP, et al. (2011) First-step mutations for adaptation at elevated temperature increase capsid stability in a virus. PLoS One 6: e25640.

9. CooperVS, LenskiRE (2001) Evolution of thermal dependence of growth rate of Escherichia coli populations during 20,000 generations in a constant environment populations. Evolution 55 : 889–896.

10. WilliamsGC (1957) Pleiotropy, natural selection, and the evolution of senescence. Evolution 11 : 398–411.

11. HughesK, AlipazJ, DrnevichJ, ReynoldsR (2002) A test of evolutionary theories of aging. Proceedings of the National Academy of Sciences of the USA 99 : 14286–14291.

12. PromislowDEL (2004) Protein networks, pleiotropy and the evolution of senescence. Proceedings of the Royal Society of London B Biological Sciences 271 : 1225–1234.

13. OrrHA (2000) Adaptation and the cost of complexity. Evolution 54 : 13–20.

14. KassenR (2002) The experimental evolution of specialists, generalists, and the maintenance of diversity. Journal of Evolutionary Biology 15 : 173–190.

15. MacLeanRC, BellG, RaineyPB (2004) The evolution of a pleiotropic fitness tradeoff in Pseudomonas fluorescens. Proceedings of the National Academy of Sciences of the USA 101 : 8072–8077.

16. RemoldSK (2012) Understanding specialism when the jack of all trades can be the master of all. Proceedings of the National Academy of Sciences of the USA 98 : 11388–11393.

17. TurnerP, MoralesN, AltoB, RemoldS (2010) Role of evolved host breadth in the initial emergence of an RNA virus. Evolution 64 : 3273–3286.

18. ElenaSF, Agudelo-RomeroP, LalicJ (2009) The evolution of viruses in multi-host fitness landscapes. The Open Virology Journal 3 : 1–6.

19. CaracoT, WangIN (2008) Free-living pathogens: life-history constraints and strain competition. Journal of Theoretical Biology 250 : 569–579.

20. HandelA, BennettMR (2008) Surviving the bottleneck: transmission mutants and the evolution of microbial populations. Genetics 180 : 2193–2200.

21. BonhoefferS, LenskiRE, EbertD (1996) The curse of the pharaoh: the evolution of virulence in pathogens with long living propagules. Proceedings of the Royal Society of London B Biological Sciences 263 : 715–721.

22. GandonS (1998) The curse of the pharaoh hypothesis. Proceedings of the Royal Society of London B Biological Sciences 265 : 1545–1552.

23. De PaepeM, TaddeiF (2006) Viruses' life history: towards a mechanistic basis of a trade-off between survival and reproduction among phages. PLoS Biology 4: e193.

24. EwensWJ (1967) The probability of survival of a new mutant in a fluctuating environment. Heredity 43 : 438–443.

25. WahlLM, GerrishPJ (2001) The probability that beneficial mutations are lost in populations with periodic bottlenecks. Evolution 55 : 2606–2610.

26. HeffernanJM, WahlLM (2002) The effects of genetic drift in experimental evolution. Theoretical Population Biology 62 : 349–356.

27. WahlLM, GerrishPJ, Saika-VoivodI (2002) Evaluating the impact of population bottlenecks in experimental evolution. Genetics 162 : 961–971.

28. DePristoMA, WeinreichDM, HartlDL (2005) Missense meanderings in sequence space: a biophysical view of protein evolution. Nature Reviews Genetics 6 : 678–687.

29. ZlotnickA (1994) To build a virus capsid: an equilibrium model of the self assembly of polyhedral protein complexes. Journal of Molelcular Biology 241 : 59–67.

30. ZlotnickA (2003) Are weak protein-protein interactions the general rule in capsid assembly? Virology 315 : 269–274.

31. ZlotnickA (2005) Theoretical aspects of virus capsid assembly. Journal of Molecular Recognition 18 : 479–490.

32. CeresP, ZlotnickA (2002) Weak protein-protein interactions are sufficient to drive assembly of hepatitis B virus capsids. Biochemistry 41 : 11525–11531.

33. CrillWD, WichmanHA, BullJJ (2000) Evolutionary reversals during viral adaptation to alternating hosts. Genetics 154 : 27–37.

34. InagakiM, KawauraT, WakashimaH, KatoM, NishikawaS, et al. (2003) Different contributions of the outer and inner R-core residues of lipopolysaccharide to the recognition by spike H and G proteins of bacteriophage φX174. FEMS Microbiol Lett 226 : 221–227.

35. SunL, YoungL, ZhangX, BoudkoS, FokineA, et al. (2014) Icosahedral bacteriophage φX174 forms a tail for DNA transport during infection. Nature 505 : 432–443.

36. DessauM, GoldhillD, McBrideR, TurnerP, ModisY (2012) Selective pressure causes an rna virus to trade reproductive fitness for increased structural and thermal stability of a viral enzyme. PLoS Genetics 8: e1003102.

37. GoldmanRP, TravisanoM (2011) Experimental evolution of ultraviolet radiation resistance in Escherichia coli. Evolution 65 : 3486–3498.

38. LeibyN, MarxC (2014) Metabolic erosion primarily through mutation accumulation, and not tradeoffs, drives limited evolution of substrate specificity in Escherichia coli. PLoS Biology 12 : 1–10.

39. RokytaDR, AbdoZ, WichmanHA (2009) The genetics of adaptation for eight microvirid bacteriophages. Journal of Molecular Evolution 69 : 229–239.

40. RokytaDR, JoyceP, CaudleSB, WichmanHA (2005) An empirical test of the mutational landscape model of adaptation using a single-stranded DNA virus. Nature Genetics 37 : 441–444.

41. TravisanoM, VasiF, LenskiRE (1995) Long-term experimental evolution in Escherichia coli. III. variation among replicate populations in correlated responses to novel environments. Evolution 49 : 189–200.

42. OstrowskiE, RozenD, LenskiR (2005) Pleiotropic effects of beneficial mutations in Escherichia coli. Evolution 59 : 2343–2352.

43. Fisher RA (1930) The genetical theory of natural selection. Oxford (UK): Oxford University Press.

44. SniegowskiP, GerrishP, LenskiR (1997) Evolution of high mutation rates in experimental populations of Escherichia coli. Nature 387 : 703–705.

45. RoscheW, FosterP, CairnsJ (1999) The role of transient hypermutators in adaptive mutation in Escherichia coli. Proceedings of the National Academy of Sciences of the USA 96 : 6862–6867.

46. WielgossS, BarrickJE, TenaillonO, WiserMJ, DittmarWJ, et al. (2013) Mutation rate dynamics in a bacterial population reflect tension between adaptation and genetic load. Proceedings of the National Academy of Sciences of the USA 110 : 222–227.

47. CuevasJM, DuffyS, SanjuánR (2009) Point mutation rate of bacteriophage?x174. Genetics 183 : 747–749.

48. ZhengL, YangW (2012) Practically efficient and robust free energy calculations: double-integration orthogonal space tempering. Journal of Chemical Theory and Computation 8 : 810–823.

49. McKennaR, BowmanBR, IlagLL, RossmannMG, FaneBA (1996) Atomic structure of the degraded procapsid particle of the bacteriophage G4: induced structural changes in the presence of calcium ions and functional implications. Journal of Molelcular Biology 256 : 736–750.

50. ZhengL, ChenM, YangW (2008) Random walk in orthogonal space to achieve efficient free-energy simulation of complex systems. Proceedings of the National Academy of Sciences of the USA 105 : 20227–20232.

51. ZhengL, ChenM, YangW (2009) Simultaneous escaping of explicit and hidden free energy barriers: application of the orthogonal space random walk strategy in generalized ensemble based conformational sampling. Journal of Chemical Physics 130 : 234105.

52. BerezovskyIN, ShakhnovichEI (2005) Physics and evolution of thermophilic adaptation. Proceedings of the National Academy of Sciences of the USA 102 : 12742–12747.

53. AharoniA, GaidukovL, KhersonskyO, GouldSM, RoodveldtC, et al. (2004) The 'evolvability' of promiscuous protein functions. Nature Genetics 37 : 73–76.

54. BloomJD, LabthavikulST, OteyCR, ArnoldFH (2006) Protein stability promotes evolvability. Proceedings of the National Academy of Sciences of the USA 103 : 5869–5874.

55. TokurikiN, TawfikD (2009) Stability effects of mutations and protein evolvability. Current Opinion in Structural Biology 19 : 1–9.

56. BesenmatterW, KastP, HilvertD (2007) Relative tolerance of mesostable and thermostable protein homologs to extensive mutation. Proteins 66 : 500–506.

57. Domingo-CalapP, Pereira-GómezM, SanjuáR (2010) Selection for thermostability can lead to the emergence of mutational robustness in an RNA virus. Journal of Evolutionary Biology 23 : 2453–2460.

58. TembeB, McCammonJ (1984) Ligand receptor interactions. Journal of Computational Chemistry 8 : 281–283.

59. JorgensenW, RavimohanC (1985) Monte-carlo simulation of differences in free-energies of hydration. Journal of the American Chemical Society 83 : 3050–3054.

60. StraatsmanT, McCammonJ (1992) Computational alchemy. Annual Review of Physical Chemistry 43 : 407–435.

61. JorgensenW, ThomasL (2008) Perspective on free-energy perturbation calculations for chemical equilibria. Journal of Chemical Theory and Computation 4 : 869–876.

62. AD MacKerellJ, BashfordD, BellottM, JrRD, EvanseckJ, et al. (1998) All-atom empirical potential for molecular modeling and dynamics studies of proteins. Journal of Physical Chemistry B 102 : 3586–3616.

63. JorgensenW, ChandrasekharJ, MaduraJ, ImpeyR, KleinM (1983) Comparison of simple potential functions for simulating liquid water. Journal of Chemical Physics 79 : 926–935.

64. DardenT, YorkD, PedersenL (1993) Particle mesh Ewald: an Nlog(N) method for Ewald sums in large systems. Journal of Chemical Physics 98 : 10089–10092.

65. ZachariasM, StraatsmaT, McCammonJ (1994) Separation-shifted scaling: A new scaling method for lennard-jones interactions in thermodynamic integration. Journal of Chemical Physics 100 : 9025–9031.