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Annual Review of Virology

Volume 9, 2022

A Trait-Based Approach to Predicting Viral Host-Range Evolvability

Abstract

Predicting the evolution of virus host range has proven to be extremely difficult, in part because of the sheer diversity of viruses, each with unique biology and ecological interactions. We have not solved this problem, but to make the problem more tractable, we narrowed our focus to three traits intrinsic to all viruses that may play a role in host-range evolvability: mutation rate, recombination rate, and phenotypic heterogeneity. Although each trait should increase evolvability, they cannot do so unbounded because fitness trade-offs limit the ability of all three traits to maximize evolvability. By examining these constraints, we can begin to identify groups of viruses with suites of traits that make them especially concerning, as well as ecological and environmental conditions that might push evolution toward accelerating host-range expansion.

Keyword(s): bacteriophage, evolvability, host-range evolution, mutation, recombination, robustness, viruses
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/content/journals/10.1146/annurev-virology-091919-092003
2022-09-29
2024-04-27
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Literature Cited

  1. 1.
    Gordon DE, Jang GM, Bouhaddou M, Xu J, Obernier K et al. 2020. A SARS-CoV-2 protein interaction map reveals targets for drug repurposing. Nature 583:459–68
     [Crossref] [Google Scholar]
  2. 2.
    V'Kovski P, Kratzel A, Steiner S, Stalder H, Thiel V. 2021. Coronavirus biology and replication: implications for SARS-CoV-2. Nat. Rev. Microbiol. 19:155–70
     [Crossref] [Google Scholar]
  3. 3.
    de Jonge PA, Nobrega FL, Brouns SJJ, Dutilh BE. 2019. Molecular and evolutionary determinants of bacteriophage host range. Trends Microbiol 27:51–63
     [Crossref] [Google Scholar]
  4. 4.
    Rothenburg S, Brennan G. 2020. Species-specific host-virus interactions: implications for viral host range and virulence. Trends Microbiol 28:46–56
     [Crossref] [Google Scholar]
  5. 5.
    Peck KM, Burch CL, Heise MT, Baric RS. 2015. Coronavirus host range expansion and Middle East respiratory syndrome coronavirus emergence: biochemical mechanisms and evolutionary perspectives. Annu. Rev. Virol. 2:95–117
     [Crossref] [Google Scholar]
  6. 6.
    Hall JP, Harrison E, Brockhurst MA 2013. Viral host-adaptation: insights from evolution experiments with phages. Curr. Opin. Virol. 3:572–77
     [Crossref] [Google Scholar]
  7. 7.
    Strobel HM, Horwitz EK, Meyer JR. 2022. Viral protein instability enhances host-range evolvability. PLOS Genet 18:2e1010030
     [Crossref] [Google Scholar]
  8. 8.
    Meyer JR, Dobias DT, Weitz JS, Barrick JE, Quick RT, Lenski RE. 2012. Repeatability and contingency in the evolution of a key innovation in phage lambda. Science 335:428–32
     [Crossref] [Google Scholar]
  9. 9.
    Maddamsetti R, Johnson DT, Spielman SJ, Petrie KL, Marks DS, Meyer JR. 2018. Gain-of-function experiments with bacteriophage lambda uncover residues under diversifying selection in nature. Evolution 72:2234–43
     [Crossref] [Google Scholar]
  10. 10.
    Tétart F, Repoila F, Monod C, Krisch HM. 1996. Bacteriophage T4 host range is expanded by duplications of a small domain of the tail fiber adhesin. J. Mol. Biol. 258:726–31
     [Crossref] [Google Scholar]
  11. 11.
    Boon M, Holtappels D, Lood C, van Noort V, Lavigne R 2020. Host range expansion of Pseudomonas virus LUZ7 is driven by a conserved tail fiber mutation. PHAGE 1:87–90
     [Crossref] [Google Scholar]
  12. 12.
    Yehl K, Lemire S, Yang AC, Ando H, Mimee M et al. 2019. Engineering phage host-range and suppressing bacterial resistance through phage tail fiber mutagenesis. Cell 179:459–69
     [Crossref] [Google Scholar]
  13. 13.
    Crill WD, Wichman HA, Bull JJ. 2000. Evolutionary reversals during viral adaptation to alternating hosts. Genetics 154:27–37
     [Crossref] [Google Scholar]
  14. 14.
    Duffy S, Burch CL, Turner PE. 2007. Evolution of host specificity drives reproductive isolation among RNA viruses. Evolution 61:2614–22
     [Crossref] [Google Scholar]
  15. 15.
    Duffy S, Turner PE, Burch CL. 2006. Pleiotropic costs of niche expansion in the RNA bacteriophage Φ6. Genetics 172:751–57
     [Crossref] [Google Scholar]
  16. 16.
    Koel BF, Burke DF, Bestebroer TM, van der Vliet S, Zondag GC et al. 2013. Substitutions near the receptor binding site determine major antigenic change during influenza virus evolution. Science 342:976–79
     [Crossref] [Google Scholar]
  17. 17.
    Linster M, van Boheemen S, de Graaf M, Schrauwen EJA, Lexmond P et al. 2014. Identification, characterization, and natural selection of mutations driving airborne transmission of A/H5N1 virus. Cell 157:329–39
     [Crossref] [Google Scholar]
  18. 18.
    Shi Y, Wu Y, Zhang W, Qi J, Gao GF. 2014. Enabling the ‘host jump’: structural determinants of receptor-binding specificity in influenza A viruses. Nat. Rev. Microbiol. 12:822–31
     [Crossref] [Google Scholar]
  19. 19.
    Song H, Qi J, Xiao H, Bi Y, Zhang W et al. 2017. Avian-to-human receptor-binding adaptation by influenza A virus hemagglutinin H4. Cell Rep 20:1201–14
     [Crossref] [Google Scholar]
  20. 20.
    Lu G, Hu Y, Wang Q, Qi J, Gao F et al. 2013. Molecular basis of binding between novel human coronavirus MERS-CoV and its receptor CD26. Nature 500:227–31
     [Crossref] [Google Scholar]
  21. 21.
    Bradel-Tretheway BG, Mattiacio JL, Krasnoselsky A, Stevenson C, Purdy D et al. 2011. Comprehensive proteomic analysis of influenza virus polymerase complex reveals a novel association with mitochondrial proteins and RNA polymerase accessory factors. J. Virol. 85:8569–81
     [Crossref] [Google Scholar]
  22. 22.
    Haller SL, Peng C, McFadden G, Rothenburg S. 2014. Poxviruses and the evolution of host range and virulence. Infect. Genet. Evol. 21:15–40
     [Crossref] [Google Scholar]
  23. 23.
    Maynard ND, Birch EW, Sanghvi JC, Chen L, Gutschow MV, Covert MW. 2010. A forward-genetic screen and dynamic analysis of lambda phage host-dependencies reveals an extensive interaction network and a new anti-viral strategy. PLOS Genet 6:e1001017
     [Crossref] [Google Scholar]
  24. 24.
    Gupta A, Soto AN, Medina SJ, Petrie KL, Meyer JR. 2020. Bacteriophage lambda overcomes a perturbation in its host–viral genetic network through mutualism and evolution of life history traits. Evolution 74:764–74
     [Crossref] [Google Scholar]
  25. 25.
    Sanjuán R. 2012. From molecular genetics to phylodynamics: evolutionary relevance of mutation rates across viruses. PLOS Pathog 8:e1002685
     [Crossref] [Google Scholar]
  26. 26.
    Elena SF, Sanjuán R. 2005. Adaptive value of high mutation rates of RNA viruses: separating causes from consequences. J. Virol. 79:11555–58
     [Crossref] [Google Scholar]
  27. 27.
    Fisher AM. 2021. The evolutionary impact of population size, mutation rate and virulence on pathogen niche width. J. Evol. Biol. 34:1256–65
     [Crossref] [Google Scholar]
  28. 28.
    Sanjuán R. 2010. Mutational fitness effects in RNA and single-stranded DNA viruses: common patterns revealed by site-directed mutagenesis studies. Philos. Trans. R. Soc. B 365:1975–82
     [Crossref] [Google Scholar]
  29. 29.
    Domingo-Calap P, Cuevas JM, Sanjuán R. 2009. The fitness effects of random mutations in single-stranded DNA and RNA bacteriophages. PLOS Genet 5:e1000742
     [Crossref] [Google Scholar]
  30. 30.
    Visher E, Whitefield SE, McCrone JT, Fitzsimmons W, Lauring AS. 2016. The mutational robustness of influenza A virus. PLOS Pathog 12:e1005856
     [Crossref] [Google Scholar]
  31. 31.
    Zhao L, Seth-Pasricha M, Stemate D, Crespo-Bellido A, Gagnon J et al. 2019. Existing host range mutations constrain further emergence of RNA viruses. J. Virol. 93:e01385–18
     [Google Scholar]
  32. 32.
    Anderson JP, Daifuku R, Loeb LA. 2004. Viral error catastrophe by mutagenic nucleosides. Annu. Rev. Microbiol. 58:183–205
     [Crossref] [Google Scholar]
  33. 33.
    Bull JJ, Sanjuán R, Wilke CO. 2007. Theory of lethal mutagenesis for viruses. J. Virol. 81:2930–39
     [Crossref] [Google Scholar]
  34. 34.
    Domingo E. 2006. Quasispecies: Concept and Implications for Virology Berlin: Springer
  35. 35.
    Malone B, Campbell EA. 2021. Molnupiravir: coding for catastrophe. Nat. Struct. Mol. Biol. 28:706–8
     [Crossref] [Google Scholar]
  36. 36.
    Jiang D, Wang Q, Bai Z, Qi H, Ma J et al. 2020. Could environment affect the mutation of H1N1 influenza virus?. Int. J. Environ. Res. Public Health 17:3092
     [Crossref] [Google Scholar]
  37. 37.
    Burmeister AR, Lenski RE, Meyer JR. 2016. Host coevolution alters the adaptive landscape of a virus. Proc. R. Soc. B 283:20161528
     [Crossref] [Google Scholar]
  38. 38.
    Gupta A, Zaman L, Strobel HM, Gallie J, Burmeister AR et al. 2021. Host-parasite coevolution promotes innovation through deformations in fitness landscapes. bioRxiv 449783. https://doi.org/10.1101/2021.06.25.449783
    [Crossref]
  39. 39.
    Pérez-Losada M, Arenas M, Galán JC, Palero F, González-Candelas F. 2015. Recombination in viruses: mechanisms, methods of study, and evolutionary consequences. Infect. Genet. Evol. 30:296–307
     [Crossref] [Google Scholar]
  40. 40.
    Young CS, Cachianes G, Munz P, Silverstein S. 1984. Replication and recombination in adenovirus-infected cells are temporally and functionally related. J. Virol. 51:571–77
     [Crossref] [Google Scholar]
  41. 41.
    Weller SK, Sawitzke JA. 2014. Recombination promoted by DNA viruses: phage λ to herpes simplex virus. Annu. Rev. Microbiol. 68:237–58
     [Crossref] [Google Scholar]
  42. 42.
    Wilkinson DE, Weller SK. 2004. Recruitment of cellular recombination and repair proteins to sites of herpes simplex virus type 1 DNA replication is dependent on the composition of viral proteins within prereplicative sites and correlates with the induction of the DNA damage response. J. Virol. 78:4783–96
     [Crossref] [Google Scholar]
  43. 43.
    Bobay LM, Touchon M, Rocha EP. 2013. Manipulating or superseding host recombination functions: a dilemma that shapes phage evolvability. PLOS Genet 9:e1003825
     [Crossref] [Google Scholar]
  44. 44.
    Murphy KC. 2016. λ recombination and recombineering. EcoSal Plus 7: https://doi.org/10.1128/ecosalplus.ESP-0011-2015
    [Crossref] [Google Scholar]
  45. 45.
    Liu J, Morrical SW. 2010. Assembly and dynamics of the bacteriophage T4 homologous recombination machinery. Virol. J. 7:357
     [Crossref] [Google Scholar]
  46. 46.
    Worobey M, Holmes EC. 1999. Evolutionary aspects of recombination in RNA viruses. J. Gen. Virol. 80:2535–43
     [Crossref] [Google Scholar]
  47. 47.
    Simon-Loriere E, Holmes EC. 2011. Why do RNA viruses recombine?. Nat. Rev. Microbiol. 9:617–26
     [Crossref] [Google Scholar]
  48. 48.
    Lai MM. 1992. RNA recombination in animal and plant viruses. Microbiol. Rev. 56:61–79
     [Crossref] [Google Scholar]
  49. 49.
    Morris P, Marinelli LJ, Jacobs-Sera D, Hendrix RW, Hatfull GF. 2008. Genomic characterization of mycobacteriophage Giles: evidence for phage acquisition of host DNA by illegitimate recombination. J. Bacteriol. 190:2172–82
     [Crossref] [Google Scholar]
  50. 50.
    De Paepe M, Hutinet G, Son O, Amarir-Bouhram J, Schbath S, Petit MA. 2014. Temperate phages acquire DNA from defective prophages by relaxed homologous recombination: the role of Rad52-like recombinases. PLOS Genet 10:e1004181
     [Crossref] [Google Scholar]
  51. 51.
    Dudenhöffer C, Rohaly G, Will K, Deppert W, Wiesmüller L. 1998. Specific mismatch recognition in heteroduplex intermediates by p53 suggests a role in fidelity control of homologous recombination. Mol. Cell. Biol. 18:5332–42
     [Crossref] [Google Scholar]
  52. 52.
    Simon-Loriere E, Martin DP, Weeks KM, Negroni M. 2010. RNA structures facilitate recombination-mediated gene swapping in HIV-1. J. Virol. 84:12675–82
     [Crossref] [Google Scholar]
  53. 53.
    Galetto R, Giacomoni V, Véron M, Negroni M. 2006. Dissection of a circumscribed recombination hot spot in HIV-1 after a single infectious cycle. J. Biol. Chem. 281:2711–20
     [Crossref] [Google Scholar]
  54. 54.
    Tenaillon O, Taddei F, Radmian M, Matic I. 2001. Second-order selection in bacterial evolution: selection acting on mutation and recombination rates in the course of adaptation. Res. Microbiol. 152:11–16
     [Crossref] [Google Scholar]
  55. 55.
    Patiño-Galindo J, Filip I, Rabadan R 2021. Global patterns of recombination across human viruses. Mol. Biol. Evol. 38:2520–31
     [Crossref] [Google Scholar]
  56. 56.
    Banner LR, Lai MM. 1991. Random nature of coronavirus RNA recombination in the absence of selection pressure. Virology 185:441–45
     [Crossref] [Google Scholar]
  57. 57.
    Fang SG, Shen S, Tay FP, Liu DX. 2005. Selection of and recombination between minor variants lead to the adaptation of an avian coronavirus to primate cells. Biochem. Biophys. Res. Commun. 336:417–23
     [Crossref] [Google Scholar]
  58. 58.
    Jackwood MW, Boynton TO, Hilt DA, McKinley ET, Kissinger JC et al. 2010. Emergence of a group 3 coronavirus through recombination. Virology 398:98–108
     [Crossref] [Google Scholar]
  59. 59.
    Decaro N, Lorusso A. 2020. Novel human coronavirus (SARS-CoV-2): a lesson from animal coronaviruses. Vet. Microbiol. 244:108693
     [Crossref] [Google Scholar]
  60. 60.
    Graham RL, Baric RS. 2010. Recombination, reservoirs, and the modular spike: mechanisms of coronavirus cross-species transmission. J. Virol. 84:3134–46
     [Crossref] [Google Scholar]
  61. 61.
    Hu B, Zeng LP, Yang XL, Ge XY, Zhang W et al. 2017. Discovery of a rich gene pool of bat SARS-related coronaviruses provides new insights into the origin of SARS coronavirus. PLOS Pathog 13:e1006698
     [Crossref] [Google Scholar]
  62. 62.
    Dudas G, Rambaut A. 2016. MERS-CoV recombination: implications about the reservoir and potential for adaptation. Virus Evol 2:vev023
     [Crossref] [Google Scholar]
  63. 63.
    Wang Y, Liu D, Shi W, Lu R, Wang W et al. 2015. Origin and possible genetic recombination of the Middle East respiratory syndrome coronavirus from the first imported case in China: phylogenetics and coalescence analysis. mBio 6:5e01280–15
     [Crossref] [Google Scholar]
  64. 64.
    Li X, Giorgi EE, Marichannegowda MH, Foley B, Xiao C et al. 2020. Emergence of SARS-CoV-2 through recombination and strong purifying selection. Sci. Adv. 6:27eabb9153
     [Crossref] [Google Scholar]
  65. 65.
    Boni MF, Lemey P, Jiang X, Lam TT, Perry BW et al. 2020. Evolutionary origins of the SARS-CoV-2 sarbecovirus lineage responsible for the COVID-19 pandemic. Nat. Microbiol. 5:1408–17
     [Crossref] [Google Scholar]
  66. 66.
    Hahn CS, Lustig S, Strauss EG, Strauss JH. 1988. Western equine encephalitis virus is a recombinant virus. PNAS 85:5997–6001
     [Crossref] [Google Scholar]
  67. 67.
    Kondo A, Maeda S. 1991. Host range expansion by recombination of the baculoviruses Bombyx mori nuclear polyhedrosis virus and Autographa californica nuclear polyhedrosis virus. J. Virol. 65:3625–32
     [Crossref] [Google Scholar]
  68. 68.
    Wu X, Cao C, Xu Y, Lu X. 2004. Construction of a host range-expanded hybrid baculovirus of BmNPV and AcNPV, and knockout of cysteinase gene for more efficient expression. Sci. China C Life Sci. 47:406–15
     [Crossref] [Google Scholar]
  69. 69.
    Padidam M, Sawyer S, Fauquet CM. 1999. Possible emergence of new geminiviruses by frequent recombination. Virology 265:218–25
     [Crossref] [Google Scholar]
  70. 70.
    Lefeuvre P, Moriones E. 2015. Recombination as a motor of host switches and virus emergence: geminiviruses as case studies. Curr. Opin. Virol. 10:14–19
     [Crossref] [Google Scholar]
  71. 71.
    Aguado LC, Jordan TX, Hsieh E, Blanco-Melo D, Heard J et al. 2018. Homologous recombination is an intrinsic defense against antiviral RNA interference. PNAS 115:E9211–19
     [Crossref] [Google Scholar]
  72. 72.
    Tétart F, Desplats C, Krisch HM. 1998. Genome plasticity in the distal tail fiber locus of the T-even bacteriophage: recombination between conserved motifs swaps adhesin specificity. J. Mol. Biol. 282:543–56
     [Crossref] [Google Scholar]
  73. 73.
    Mahichi F, Synnott AJ, Yamamichi K, Osada T, Tanji Y. 2009. Site-specific recombination of T2 phage using IP008 long tail fiber genes provides a targeted method for expanding host range while retaining lytic activity. FEMS Microbiol. Lett. 295:211–17
     [Crossref] [Google Scholar]
  74. 74.
    Burrowes BH, Molineux IJ, Fralick JA 2019. Directed in vitro evolution of therapeutic bacteriophages: the Appelmans protocol. Viruses 11:241
     [Crossref] [Google Scholar]
  75. 75.
    Borin JM, Avrani S, Barrick JE, Petrie KL, Meyer JR. 2021. Coevolutionary phage training leads to greater bacterial suppression and delays the evolution of phage resistance. PNAS 118:e2104592118
     [Crossref] [Google Scholar]
  76. 76.
    Zhang H, Fouts DE, DePew J, Stevens RH. 2013. Genetic modifications to temperate Enterococcus faecalis phage Ef11 that abolish the establishment of lysogeny and sensitivity to repressor, and increase host range and productivity of lytic infection. Microbiology 159:1023–35
     [Crossref] [Google Scholar]
  77. 77.
    Drummond DA, Silberg JJ, Meyer MM, Wilke CO, Arnold FH. 2005. On the conservative nature of intragenic recombination. PNAS 102:5380–85
     [Crossref] [Google Scholar]
  78. 78.
    Lefeuvre P, Lett JM, Reynaud B, Martin DP. 2007. Avoidance of protein fold disruption in natural virus recombinants. PLOS Pathog 3:e181
     [Crossref] [Google Scholar]
  79. 79.
    Poirier EZ, Mounce BC, Rozen-Gagnon K, Hooikaas PJ, Stapleford KA et al. 2015. Low-fidelity polymerases of alphaviruses recombine at higher rates to overproduce defective interfering particles. J. Virol. 90:2446–54
     [Crossref] [Google Scholar]
  80. 80.
    Giachetti C, Holland JJ. 1989. Vesicular stomatitis virus and its defective interfering particles exhibit in vitro transcriptional and replicative competition for purified L-NS polymerase molecules. Virology 170:264–67
     [Crossref] [Google Scholar]
  81. 81.
    Frensing T, Heldt FS, Pflugmacher A, Behrendt I, Jordan I et al. 2013. Continuous influenza virus production in cell culture shows a periodic accumulation of defective interfering particles. PLOS ONE 8:e72288
     [Crossref] [Google Scholar]
  82. 82.
    Sackman AM, Reed D, Rokyta DR. 2015. Intergenic incompatibilities reduce fitness in hybrids of extremely closely related bacteriophages. PeerJ 3:e1320
     [Crossref] [Google Scholar]
  83. 83.
    Meyer JR, Dobias DT, Medina SJ, Servilio L, Gupta A, Lenski RE. 2016. Ecological speciation of bacteriophage lambda in allopatry and sympatry. Science 354:1301–4
     [Crossref] [Google Scholar]
  84. 84.
    Golden M, Muhire BM, Semegni Y, Martin DP. 2014. Patterns of recombination in HIV-1M are influenced by selection disfavouring the survival of recombinants with disrupted genomic RNA and protein structures. PLOS ONE 9:e100400
     [Crossref] [Google Scholar]
  85. 85.
    Lefeuvre P, Lett JM, Varsani A, Martin DP. 2009. Widely conserved recombination patterns among single-stranded DNA viruses. J. Virol. 83:2697–707
     [Crossref] [Google Scholar]
  86. 86.
    Martin DP, Lefeuvre P, Varsani A, Hoareau M, Semegni JY et al. 2011. Complex recombination patterns arising during geminivirus coinfections preserve and demarcate biologically important intra-genome interaction networks. PLOS Pathog 7:e1002203
     [Crossref] [Google Scholar]
  87. 87.
    Martin DP, van der Walt E, Posada D, Rybicki EP. 2005. The evolutionary value of recombination is constrained by genome modularity. PLOS Genet. 1:e51
     [Crossref] [Google Scholar]
  88. 88.
    Hendrix RW, Lawrence JG, Hatfull GF, Casjens S. 2000. The origins and ongoing evolution of viruses. Trends Microbiol 8:504–8
     [Crossref] [Google Scholar]
  89. 89.
    Casjens SR, Hendrix RW. 2015. Bacteriophage lambda: early pioneer and still relevant. Virology 479–480:310–30
     [Crossref] [Google Scholar]
  90. 90.
    Comeau AM, Bertrand C, Letarov A, Tétart F, Krisch HM. 2007. Modular architecture of the T4 phage superfamily: a conserved core genome and a plastic periphery. Virology 362:384–96
     [Crossref] [Google Scholar]
  91. 91.
    Botstein D. 1980. A theory of modular evolution for bacteriophages. Ann. N. Y. Acad. Sci. 354:484–90
     [Crossref] [Google Scholar]
  92. 92.
    Bocharov G, Ford NJ, Edwards J, Breinig T, Wain-Hobson S, Meyerhans A. 2005. A genetic-algorithm approach to simulating human immunodeficiency virus evolution reveals the strong impact of multiply infected cells and recombination. J. Gen. Virol. 86:3109–18
     [Crossref] [Google Scholar]
  93. 93.
    Hall AR, Scanlan PD, Leggett HC, Buckling A. 2012. Multiplicity of infection does not accelerate infectivity evolution of viral parasites in laboratory microcosms. J. Evol. Biol. 25:409–15
     [Crossref] [Google Scholar]
  94. 94.
    Priyadarsini SL, Suresh M, Huisingh D. 2020. What can we learn from previous pandemics to reduce the frequency of emerging infectious diseases like COVID-19?. Glob. Transit. 2:202–20
     [Crossref] [Google Scholar]
  95. 95.
    Wagner A. 2005. Robustness, evolvability, and neutrality. FEBS Lett 579:1772–78
     [Crossref] [Google Scholar]
  96. 96.
    Eyre-Walker A, Keightley PD 2007. The distribution of fitness effects of new mutations. Nat. Rev. Genet. 8:610–18
     [Crossref] [Google Scholar]
  97. 97.
    Hayden EJ, Ferrada E, Wagner A. 2011. Cryptic genetic variation promotes rapid evolutionary adaptation in an RNA enzyme. Nature 474:92–95
     [Crossref] [Google Scholar]
  98. 98.
    Zheng J, Payne JL, Wagner A. 2019. Cryptic genetic variation accelerates evolution by opening access to diverse adaptive peaks. Science 365:347–53
     [Crossref] [Google Scholar]
  99. 99.
    Holland SL, Reader T, Dyer PS, Avery SV. 2014. Phenotypic heterogeneity is a selected trait in natural yeast populations subject to environmental stress. Environ. Microbiol. 16:1729–40
     [Crossref] [Google Scholar]
  100. 100.
    Bódi Z, Farkas Z, Nevozhay D, Kalapis D, Lázár V et al. 2017. Phenotypic heterogeneity promotes adaptive evolution. PLOS Biol 15:e2000644
     [Crossref] [Google Scholar]
  101. 101.
    Bloom JD, Labthavikul ST, Otey CR, Arnold FH. 2006. Protein stability promotes evolvability. PNAS 103:5869–74
     [Crossref] [Google Scholar]
  102. 102.
    Bloom JD, Arnold FH. 2009. In the light of directed evolution: pathways of adaptive protein evolution. PNAS 106:9995–10000
     [Crossref] [Google Scholar]
  103. 103.
    Zheng J, Guo N, Wagner A. 2020. Selection enhances protein evolvability by increasing mutational robustness and foldability. Science 370:6521eabb5962
     [Crossref] [Google Scholar]
  104. 104.
    Payne JL, Wagner A. 2019. The causes of evolvability and their evolution. Nat. Rev. Genet. 20:24–38
     [Crossref] [Google Scholar]
  105. 105.
    Besenmatter W, Kast P, Hilvert D. 2007. Relative tolerance of mesostable and thermostable protein homologs to extensive mutation. Proteins 66:500–6
     [Crossref] [Google Scholar]
  106. 106.
    McBride RC, Ogbunugafor CB, Turner PE. 2008. Robustness promotes evolvability of thermotolerance in an RNA virus. BMC Evol. Biol. 8:231
     [Crossref] [Google Scholar]
  107. 107.
    Domingo-Calap P, Pereira-Gómez M, Sanjuán R. 2010. Selection for thermostability can lead to the emergence of mutational robustness in an RNA virus. J. Evol. Biol. 23:2453–60
     [Crossref] [Google Scholar]
  108. 108.
    Presloid JB, Mohammad TF, Lauring AS, Novella IS. 2016. Antigenic diversification is correlated with increased thermostability in a mammalian virus. Virology 496:203–14
     [Crossref] [Google Scholar]
  109. 109.
    Cuevas JM, Moya A, Sanjuán R. 2009. A genetic background with low mutational robustness is associated with increased adaptability to a novel host in an RNA virus. J. Evol. Biol. 22:2041–48
     [Crossref] [Google Scholar]
  110. 110.
    Tokuriki N, Tawfik DS. 2009. Protein dynamism and evolvability. Science 324:203–7
     [Crossref] [Google Scholar]
  111. 111.
    Sikosek T, Chan HS. 2014. Biophysics of protein evolution and evolutionary protein biophysics. J. R. Soc. Interface 11:20140419
     [Crossref] [Google Scholar]
  112. 112.
    Song WJ, Yu J, Tezcan FA. 2017. Importance of scaffold flexibility/rigidity in the design and directed evolution of artificial metallo-β-lactamases. J. Am. Chem. Soc. 139:16772–79
     [Crossref] [Google Scholar]
  113. 113.
    Raman AS, White KI, Ranganathan R. 2016. Origins of allostery and evolvability in proteins: a case study. Cell 166:468–80
     [Crossref] [Google Scholar]
  114. 114.
    Zimmermann J, Oakman EL, Thorpe IF, Shi X, Abbyad P et al. 2006. Antibody evolution constrains conformational heterogeneity by tailoring protein dynamics. PNAS 103:13722–27
     [Crossref] [Google Scholar]
  115. 115.
    Yadid I, Kirshenbaum N, Sharon M, Dym O, Tawfik DS. 2010. Metamorphic proteins mediate evolutionary transitions of structure. PNAS 107:7287–92
     [Crossref] [Google Scholar]
  116. 116.
    Petrie KL, Palmer ND, Johnson DT, Medina SJ, Yan SJ et al. 2018. Destabilizing mutations encode nongenetic variation that drives evolutionary innovation. Science 359:1542–45
     [Crossref] [Google Scholar]
  117. 117.
    Elena SF, Sanjuán R. 2008. The effect of genetic robustness on evolvability in digital organisms. BMC Evol. Biol. 8:284
     [Crossref] [Google Scholar]
  118. 118.
    Wagner A. 2008. Robustness and evolvability: a paradox resolved. Proc. Biol. Sci. 275:91–100
     [Google Scholar]
  119. 119.
    Gitlin L, Hagai T, LaBarbera A, Solovey M, Andino R. 2014. Rapid evolution of virus sequences in intrinsically disordered protein regions. PLOS Pathog. 10:e1004529
     [Crossref] [Google Scholar]
  120. 120.
    Stern A, Bianco S, Yeh MT, Wright C, Butcher K et al. 2014. Costs and benefits of mutational robustness in RNA viruses. Cell Rep 8:1026–36
     [Crossref] [Google Scholar]
  121. 121.
    Aviner R, Frydman J. 2020. Proteostasis in viral infection: unfolding the complex virus–chaperone interplay. Cold Spring Harb. Perspect. Biol. 12:a034090
     [Crossref] [Google Scholar]
  122. 122.
    Sang X, Wang A, Ding J, Kong H, Gao X et al. 2015. Adaptation of H9N2 AIV in guinea pigs enables efficient transmission by direct contact and inefficient transmission by respiratory droplets. Sci. Rep. 5:15928
     [Crossref] [Google Scholar]
  123. 123.
    Yang TJ, Yu PY, Chang YC, Hsu SD. 2021. D614G mutation in the SARS-CoV-2 spike protein enhances viral fitness by desensitizing it to temperature-dependent denaturation. J. Biol. Chem. 297:101238
     [Crossref] [Google Scholar]
  124. 124.
    Yang G, Ojha CR, Russell CJ. 2021. Relationship between hemagglutinin stability and influenza virus persistence after exposure to low pH or supraphysiological heating. PLOS Pathog 17:e1009910
     [Crossref] [Google Scholar]
  125. 125.
    Vihinen M. 1987. Relationship of protein flexibility to thermostability. Protein Eng 1:477–80
     [Crossref] [Google Scholar]
  126. 126.
    Rathi PC, Jaeger KE, Gohlke H. 2015. Structural rigidity and protein thermostability in variants of lipase A from Bacillus subtilis. PLOS ONE 10:e0130289
     [Crossref] [Google Scholar]
  127. 127.
    Wang X, Minasov G, Shoichet BK. 2002. Evolution of an antibiotic resistance enzyme constrained by stability and activity trade-offs. J. Mol. Biol. 320:85–95
     [Crossref] [Google Scholar]
  128. 128.
    Studer RA, Christin PA, Williams MA, Orengo CA. 2014. Stability-activity tradeoffs constrain the adaptive evolution of RubisCO. PNAS 111:2223–28
     [Crossref] [Google Scholar]
  129. 129.
    Tokuriki N, Stricher F, Serrano L, Tawfik DS. 2008. How protein stability and new functions trade off. PLOS Comput. Biol. 4:e1000002
     [Crossref] [Google Scholar]
  130. 130.
    Marina CF, Fernández-Salas I, Ibarra JE, Arredondo-Jiménez JI, Valle J, Williams T. 2005. Transmission dynamics of an iridescent virus in an experimental mosquito population: the role of host density. Ecol. Entomol. 30:376–82
     [Crossref] [Google Scholar]
  131. 131.
    Holtzman T, Globus R, Molshanski-Mor S, Ben-Shem A, Yosef I, Qimron U. 2020. A continuous evolution system for contracting the host range of bacteriophage T7. Sci. Rep. 10:307
     [Crossref] [Google Scholar]
  132. 132.
    Sant DG, Woods LC, Barr JJ, McDonald MJ. 2021. Host diversity slows bacteriophage adaptation by selecting generalists over specialists. Nat. Ecol. Evol. 5:350–59
     [Crossref] [Google Scholar]
  133. 133.
    Barik S. 2020. Evolution of protein structure and stability in global warming. Int. J. Mol. Sci. 21:9662
     [Crossref] [Google Scholar]
  134. 134.
    Phillips AM, Ponomarenko AI, Chen K, Ashenberg O, Miao J et al. 2018. Destabilized adaptive influenza variants critical for innate immune system escape are potentiated by host chaperones. PLOS Biol 16:e3000008
     [Crossref] [Google Scholar]
  135. 135.
    Murrieta RA, Garcia-Luna SM, Murrieta DJ, Halladay G, Young MC et al. 2021. Impact of extrinsic incubation temperature on natural selection during Zika virus infection of Aedes aegypti and Aedes albopictus. PLOS Pathog. 17:e1009433
     [Crossref] [Google Scholar]
/content/journals/10.1146/annurev-virology-091919-092003
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A Trait-Based Approach to Predicting Viral Host-Range Evolvability
Annual Review of Virology 9, 139 (2022); https://doi.org/10.1146/annurev-virology-091919-092003
/content/journals/10.1146/annurev-virology-091919-092003
/content/journals/10.1146/annurev-virology-091919-092003
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