Review Article | Published:

Population genomics of bacterial host adaptation

Nature Reviews Geneticsvolume 19pages549565 (2018) | Download Citation

Abstract

Some bacteria can transfer to new host species, and this poses a risk to human health. Indeed, an estimated 60% of all human pathogens have originated from other animal species. Similarly, human-to-animal transitions are recognized as a major threat to sustainable livestock production, and emerging pathogens impose an increasing burden on crop yield and global food security. Recent advances in high-throughput sequencing technologies have enabled comparative genomic analyses of bacterial populations from multiple hosts. Such studies are providing new insights into the evolutionary processes that underpin the establishment of bacteria in new host niches. A better understanding of the genetic and mechanistic basis for bacterial host adaptation may reveal novel targets for controlling infection or inform the design of approaches to limit the emergence of new pathogens.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Additional information

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. 1.

    Holt, R. D. Bringing the Hutchinsonian niche into the 21st century: ecological and evolutionary perspectives. Proc. Natl Acad. Sci. USA 106 (Suppl. 2), 19659–19665 (2009).

  2. 2.

    Davenport, E. R. et al. The human microbiome in evolution. BMC Biol. 15, 127 (2017).

  3. 3.

    Hibbing, M. E., Fuqua, C., Parsek, M. R. & Peterson, S. B. Bacterial competition: surviving and thriving in the microbial jungle. Nat. Rev. Microbiol. 8, 15–25 (2010).

  4. 4.

    Price, M. N. & Arkin, A. P. Weakly deleterious mutations and low rates of recombination limit the impact of natural selection on bacterial genomes. mBio 6, e01302–e01315 (2015).

  5. 5.

    Vonaesch, P., Anderson, M. & Sansonetti, P. J. Pathogens, microbiome and the host: emergence of the ecological Koch’s postulates. FEMS Microbiol. Rev. 42, 273–292 (2018).

  6. 6.

    McAdam, P. R., Richardson, E. J. & Fitzgerald, J. R. High-throughput sequencing for the study of bacterial pathogen biology. Curr. Opin. Microbiol. 19, 106–113 (2014).

  7. 7.

    Toft, C. & Andersson, S. G. E. Evolutionary microbial genomics: insights into bacterial host adaptation. Nat. Rev. Genet. 11, 465–475 (2010).

  8. 8.

    Guinane, C. M. et al. Evolutionary genomics of Staphylococcus aureus reveals insights into the origin and molecular basis of ruminant host adaptation. Genome Biol. Evol. 2, 454–466 (2010).

  9. 9.

    Sheppard, S. K. et al. Niche segregation and genetic structure of Campylobacter jejuni populations from wild and agricultural host species. Mol. Ecol. 20, 3484–3490 (2011).

  10. 10.

    Weinert, L. A. et al. Molecular dating of human-to-bovid host jumps by Staphylococcus aureus reveals an association with the spread of domestication. Biol. Lett. 8, 829–832 (2012).

  11. 11.

    Schierup, M. H. & Wiuf, C. in Bacterial Population Genetics in Infectious Disease (eds Robinson, D., Falush D. & Feil, E. J.) (John Wiley & Sons, 2010).

  12. 12.

    Kingman, J. F. C. The coalescent. Stochast. Processes Their Appl. 13, 235–248 (1982).

  13. 13.

    Hudson, R. R. Properties of a neutral allele model with intragenic recombination. Theor. Popul. Biol. 23, 183–201 (1983).

  14. 14.

    Kern, A. D. & Hahn, M. W. The neutral theory in light of natural selection. Mol. Biol. Evol. 35, 1366–1371 (2018).

  15. 15.

    Hayward, M. R., Petrovska, L., Jansen, V. A. A. & Woodward, M. J. Population structure and associated phenotypes of Salmonella enterica serovars Derby and Mbandaka overlap with host range. BMC Microbiol. 16, 15 (2016).

  16. 16.

    Sheppard, S. K. et al. Host association of Campylobacter genotypes transcends geographic variation. Appl. Environ. Microbiol. 76, 5269–5277 (2010).

  17. 17.

    Birky, C. W. & Walsh, J. B. Effects of linkage on rates of molecular evolution. Proc. Natl Acad. Sci. USA 85, 6414–6418 (1988).

  18. 18.

    Smith, J. M. & Haigh, J. The hitch-hiking effect of a favourable gene. Genet. Res. 23, 23–35 (1974).

  19. 19.

    Atwood, K. C., Schneider, L. K. & Ryan, F. J. Periodic selection in Escherichia coli. Proc. Natl Acad. Sci. USA 37, 146–155 (1951).

  20. 20.

    Cohan, F. M. & Koeppel, A. F. The origins of ecological diversity in prokaryotes. Curr. Biol. 18, R1024–R1034 (2008). This paper provides a detailed description of the ecotype model in bacterial evolution.

  21. 21.

    Cui, Y. et al. Epidemic clones, oceanic gene pools, and eco-ld in the free living marine pathogen Vibrio parahaemolyticus. Mol. Biol. Evol. 32, 1396–1410 (2015).

  22. 22.

    Batut, B., Knibbe, C., Marais, G. & Daubin, V. Reductive genome evolution at both ends of the bacterial population size spectrum. Nat. Rev. Microbiol. 12, 841–850 (2014).

  23. 23.

    Wright, S. Evolution in mendelian populations. Genetics 16, 97–159 (1931).

  24. 24.

    Wright, S. The distribution of gene frequencies in populations of polyploids. Proc. Natl Acad. Sci. USA 24, 372–377 (1938).

  25. 25.

    Achtman, M. & Wagner, M. Microbial diversity and the genetic nature of microbial species. Nat. Rev. Microbiol. 6, 431–440 (2008).

  26. 26.

    Méric, G., Kemsley, E. K., Falush, D., Saggers, E. J. & Lucchini, S. Phylogenetic distribution of traits associated with plant colonization in Escherichia coli. Environ. Microbiol. 15, 487–501 (2012).

  27. 27.

    Lowder, B. V. et al. Recent human-to-poultry host jump, adaptation, and pandemic spread of Staphylococcus aureus. Proc. Natl Acad. Sci. 106, 19545–19550 (2009). This paper describes a host-jump event for Staphylococcus aureus and reports the identification of MGEs associated with adaptation to poultry.

  28. 28.

    Murray, S. et al. Recombination-mediated host adaptation by avian Staphylococcus aureus. Genome Biol. Evol. 9, 830–842 (2017).

  29. 29.

    Shapiro, B. J. et al. Population genomics of early events in the ecological differentiation of bacteria. Science 336, 48–51 (2012). This study provides evidence for ecological differentiation driven by gene-specific (rather than genome-wide) sweeps followed by emergence of barriers to gene flow.

  30. 30.

    Price, L. B. et al. Staphylococcus aureus CC398: host adaptation and emergence of methicillin resistance in livestock. mBio 3, e00305–e00311 (2012).

  31. 31.

    Ward, M. J. et al. Time-scaled evolutionary analysis of the transmission and antibiotic resistance dynamics of Staphylococcus aureus clonal complex 398. Appl. Environ. Microbiol. 80, 7275–7282 (2014).

  32. 32.

    Wendlandt, S., Fessler, A. T., Kadlec, K., van Duijkeren, E. & Schwarz, S. Identification of the novel spectinomycin resistance gene spd in a different plasmid background among methicillin-resistant Staphylococcus aureus CC398 and methicillin-susceptible S. aureus ST433. J. Antimicrob. Chemother. 69, 2000–2003 (2014).

  33. 33.

    Wendlandt, S., Kadlec, K., Feßler, A. T., van Duijkeren, E. & Schwarz, S. Two different erm(C)-carrying plasmids in the same methicillin-resistant Staphylococcus aureus CC398 isolate from a broiler farm. Veterinary Microbiol. 171, 382–387 (2014).

  34. 34.

    Wimalarathna, H. M. L. et al. Widespread acquisition of antimicrobial resistance among Campylobacter isolates from UK retail poultry and evidence for clonal expansion of resistant lineages. BMC Microbiol. 13, 160 (2013).

  35. 35.

    Charlesworth, D. Balancing selection and its effects on sequences in nearby genome regions. PLOS Genet. 2, e64 (2006).

  36. 36.

    Niehus, R., Mitri, S., Fletcher, A. G. & Foster, K. R. Migration and horizontal gene transfer divide microbial genomes into multiple niches. Nat. Commun. 6, 8924 (2015).

  37. 37.

    Sheppard, S. K., McCarthy, N. D., Falush, D. & Maiden, M. C. Convergence of Campylobacter species: implications for bacterial evolution. Science 320, 237–239 (2008).

  38. 38.

    Sheppard, S. K. et al. Progressive genome-wide introgression in agricultural Campylobacter coli. Mol. Ecol. 22, 1051–1064 (2013). This study demonstrates extensive recombination between different bacterial species in the same agricultural niche, which may be relevant to adaptation.

  39. 39.

    de Bentzmann, S. & Plesiat, P. The Pseudomonas aeruginosa opportunistic pathogen and human infections. Environ. Microbiol. 13, 1655–1665 (2011).

  40. 40.

    Judelson, H. S. & Blanco, F. A. The spores of Phytophthora: weapons of the plant destroyer. Nat. Rev. Microbiol. 3, 47–58 (2005).

  41. 41.

    Takeuchi, N., Cordero, O. X., Koonin, E. V. & Kaneko, K. Gene-specific selective sweeps in bacteria and archaea caused by negative frequency-dependent selection. BMC Biol. 13, 20 (2015).

  42. 42.

    Sheppard, S. K. et al. Genome-wide association study identifies vitamin B5 biosynthesis as a host specificity factor in Campylobacter. Proc. Natl Acad. Sci. USA 110, 11923–11927 (2013). This paper presents a GWAS approach for bacteria that takes into account the clonal population structure and that is applicable to both core and accessory genome variation.

  43. 43.

    Guttman, D. S. & Dykhuizen, D. E. Clonal divergence in Escherichia coli as a result of recombination, not mutation. Science 266, 1380–1383 (1994).

  44. 44.

    Croucher, N. J. et al. Horizontal DNA transfer mechanisms of bacteria as weapons of intragenomic conflict. PLOS Biol. 14, e1002394 (2016).

  45. 45.

    McInerney, J. O., McNally, A. & O’Connell, M. J. Why prokaryotes have pangenomes. Nature Microbiol. 2, 17040 (2017).

  46. 46.

    Morley, L. et al. Gene loss and lineage-specific restriction-modification systems associated with niche differentiation in the Campylobacter jejuni sequence type 403 clonal complex. Appl. Environ. Microbiol. 81, 3641–3647 (2015).

  47. 47.

    Thorpe, H. A., Bayliss, S. C., Hurst, L. D. & Feil, E. J. Comparative analyses of selection operating on non-translated intergenic regions of diverse bacterial species. Genetics 206, 363–376 (2017).

  48. 48.

    Westermann, A. J. et al. Dual RNA-seq unveils noncoding RNA functions in host-pathogen interactions. Nature 529, 496–501 (2016).

  49. 49.

    Kimura, M. On evolutionary adjustment of spontaneous mutation rates. Genet. Res. 9, 23–34 (1967).

  50. 50.

    Lynch, M. et al. Genetic drift, selection and the evolution of the mutation rate. Nat. Rev. Genet. 17, 704–714 (2016).

  51. 51.

    Bobay, L. M. & Ochman, H. The evolution of bacterial genome architecture. Front. Genet. 8, 72 (2017).

  52. 52.

    Duchêne, S. et al. Genome-scale rates of evolutionary change in bacteria. Microb. Genom. 2, e000094 (2016).

  53. 53.

    Didelot, X. et al. Genomic evolution and transmission of Helicobacter pylori in two South African families. Proc. Natl Acad. Sci. 110, 13880–13885 (2013).

  54. 54.

    Lieberman, T. D. et al. Genetic variation of a bacterial pathogen within individuals with cystic fibrosis provides a record of selective pressures. Nat. Genet. 46, 82–87 (2013).

  55. 55.

    Marvig, R. L., Johansen, H. K., Molin, S. & Jelsbak, L. Genome analysis of a transmissible lineage of pseudomonas aeruginosa reveals pathoadaptive mutations and distinct evolutionary paths of hypermutators. PLOS Genet. 9, e1003741 (2013).

  56. 56.

    Prunier, A. L. et al. High rate of macrolide resistance in Staphylococcus aureus strains from patients with cystic fibrosis reveals high proportions of hypermutable strains. J. Infect. Dis. 187, 1709–1716 (2003).

  57. 57.

    Wang, S., Wu, C., Shen, J., Wu, Y. & Wang, Y. Hypermutable Staphylococcus aureus strains present at high frequency in subclinical bovine mastitis isolates are associated with the development of antibiotic resistance. Veterinary Microbiol. 165, 410–415 (2013).

  58. 58.

    Lees, J. A. et al. Large scale genomic analysis shows no evidence for pathogen adaptation between the blood and cerebrospinal fluid niches during bacterial meningitis. Microb. Genom. 3, e000103 (2017).

  59. 59.

    van Ham, R. C. et al. Reductive genome evolution in Buchnera aphidicola. Proc. Natl Acad. Sci. USA 100, 581–586 (2003).

  60. 60.

    McCutcheon, J. P. & Moran, N. A. Extreme genome reduction in symbiotic bacteria. Nat. Rev. Microbiol. 10, 13–26 (2011).

  61. 61.

    Ochman, H., Lawrence, J. G. & Groisman, E. A. Lateral gene transfer and the nature of bacterial innovation. Nature 405, 299–304 (2000). This paper describes one of the first studies to demonstrate how horizontal gene transfer influences bacterial evolution and adaptation.

  62. 62.

    Felsenstein, J. Evolutionary advantage of recombination. Genetics 78, 737–756 (1974).

  63. 63.

    Vos, M. & Didelot, X. A comparison of homologous recombination rates in bacteria and archaea. Isme J. 3, 199–208 (2009).

  64. 64.

    Dixit, P. D., Pang, T. Y. & Maslov, S. Recombination-driven genome evolution and stability of bacterial species. Genetics 207, 281–295 (2017).

  65. 65.

    Yahara, K. et al. The landscape of realized homologous recombination in pathogenic bacteria. Mol. Biol. Evol. 33, 456–471 (2015).

  66. 66.

    Yahara, K. et al. Genome-wide association of functional traits linked with Campylobacter jejuni survival from farm to fork. Environ. Microbiol. 19, 361–380 (2017).

  67. 67.

    Miralles, R., Gerrish, P. J., Moya, A. & Elena, S. F. Clonal interference and the evolution of RNA viruses. Science 285, 1745–1747 (1999).

  68. 68.

    Tree, Jai, J., Granneman, S., McAteer, Sean, P., Tollervey, D. & Gally, David, L. Identification of bacteriophage-encoded anti-sRNAs in pathogenic Escherichia coli. Mol. Cell 55, 199–213 (2014).

  69. 69.

    Song, H. et al. The early stage of bacterial genome-reductive evolution in the host. PLOS Pathog. 6, e1000922 (2010).

  70. 70.

    Siguier, P., Gourbeyre, E. & Chandler, M. Bacterial insertion sequences: their genomic impact and diversity. FEMS Microbiol. Rev. 38, 865–891 (2014).

  71. 71.

    Porcelli, I., Reuter, M., Pearson, B. M., Wilhelm, T. & van Vliet, A. H. M. Parallel evolution of genome structure and transcriptional landscape in the Epsilonproteobacteria. BMC Genomics 14, 616 (2013).

  72. 72.

    Hacker, J. & Kaper, J. B. Pathogenicity islands and the evolution of microbes. Annu. Rev. Microbiol. 54, 641–679 (2000).

  73. 73.

    Goldman, N. & Yang, Z. A codon-based model of nucleotide substitution for protein-coding DNA sequences. Mol. Biol. Evol. 11, 725–736 (1994).

  74. 74.

    Wheeler, N. E., Barquist, L., Kingsley, R. A. & Gardner, P. P. A profile-based method for identifying functional divergence of orthologous genes in bacterial genomes. Bioinformatics 32, 3566–3574 (2016).

  75. 75.

    Didelot, X., Walker, A. S., Peto, T. E., Crook, D. W. & Wilson, D. J. Within-host evolution of bacterial pathogens. Nat. Rev. Microbiol. 14, 150–162 (2016).

  76. 76.

    Rocha, E. P. C. et al. Comparisons of dN/dS are time dependent for closely related bacterial genomes. J. Theor. Biol. 239, 226–235 (2006). This paper describes how dN/dS ratio can be computed to assay the strength and direction of selection in bacteria.

  77. 77.

    Lieberman, T. D. et al. Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes. Nat. Genet. 43, 1275–1280 (2011).

  78. 78.

    Marvig, R. L., Sommer, L. M., Molin, S. & Johansen, H. K. Convergent evolution and adaptation of Pseudomonas aeruginosa within patients with cystic fibrosis. Nat. Genet. 47, 57–64 (2014).

  79. 79.

    Price, E. P. et al. Within-host evolution of burkholderia pseudomallei over a twelve-year chronic carriage infection. mBio 4, e00388-13 (2013).

  80. 80.

    Kennemann, L. et al. Helicobacter pylori genome evolution during human infection. Proc. Natl Acad. Sci. 108, 5033–5038 (2011).

  81. 81.

    Palmer, A. C. & Kishony, R. Understanding, predicting and manipulating the genotypic evolution of antibiotic resistance. Nat. Rev. Genet. 14, 243–248 (2013).

  82. 82.

    Levin, B. R. Frequency-dependent selection in bacterial populations. Philos. T. Roy. Soc. B 319, 459–472 (1988).

  83. 83.

    Tellier, A. & Brown, J. K. M. Stability of genetic polymorphism in host-parasite interactions. P R. Soc. B 274, 809–817 (2007).

  84. 84.

    Bentley, S. D. & Parkhill, J. Comparative genomic structure of prokaryotes. Annu. Rev. Genet. 38, 771–792 (2004).

  85. 85.

    Kryazhimskiy, S. & Plotkin, J. B. The population genetics of dN/dS. PLOS Genet. 4, e1000304 (2008).

  86. 86.

    McVean, G. A. T. & Charlesworth, B. The effects of Hill-Robertson interference between weakly selected mutations on patterns of molecular evolution and variation. Genetics 155, 929–944 (2000).

  87. 87.

    van Wamel, W. J. B., Rooijakkers, S. H. M., Ruyken, M., van Kessel, K. P. M. & van Strijp, J. A. G. The innate immune modulators staphylococcal complement inhibitor and chemotaxis inhibitory protein of Staphylococcus aureus are located on β-hemolysin-converting bacteriophages. J. Bacteriol. 188, 1310–1315 (2006).

  88. 88.

    Koop, G. et al. Identification of LukPQ, a novel, equid-adapted leukocidin of Staphylococcus aureus. Sci. Rep. 7, 40660 (2017).

  89. 89.

    Koymans, K. J., Vrieling, M., Gorham, R. D. & van Strijp, J. A. G. in Current Topics in Microbiology and Immunology (Springer Berlin Heidelberg, 2015).

  90. 90.

    Vrieling, M. et al. Bovine Staphylococcus aureus secretes the leukocidin LukMF′ to kill migrating neutrophils through CCR1. mBio 6, e00335-15 (2015).

  91. 91.

    Viana, D. et al. Adaptation of Staphylococcus aureus to ruminant and equine hosts involves SaPI-carried variants of von Willebrand factor-binding protein. Mol. Microbiol. 77, 1583–1594 (2010).

  92. 92.

    Deringer, J. R., Ely, R. J., Monday, S. R., Stauffacher, C. V. & Bohach, G. A. Vβ-dependent stimulation of bovine and human T cells by host-specific staphylococcal enterotoxins. Infect. Immun. 65, 4048–4054 (1997).

  93. 93.

    Edwards, V. M. et al. Characterization of the canine type C enterotoxin produced by Staphylococcus intermedius pyoderma isolates. Infect. Immun. 65, 2346–2352 (1997).

  94. 94.

    Wilson, G. J. et al. A novel core genome-encoded superantigen contributes to lethality of community-associated MRSA necrotizing pneumonia. PLOS Pathog. 7, e1002271 (2011).

  95. 95.

    Godfrey, S. A. et al. The stealth episome: suppression of gene expression on the excised genomic island PPHGI-1 from Pseudomonas syringae pv. phaseolicola. PLOS Pathog. 7, e1002010 (2011).

  96. 96.

    Lovell, H. C. et al. Bacterial evolution by genomic island transfer occurs via DNA transformation in planta. Curr. Biol. 19, 1586–1590 (2009).

  97. 97.

    Pitman, A. R. et al. Exposure to host resistance mechanisms drives evolution of bacterial virulence in plants. Curr. Biol. 15, 2230–2235 (2005).

  98. 98.

    Yue, M. et al. Allelic variation contributes to bacterial host specificity. Nat. Commun. 6, 8754 (2015).

  99. 99.

    De Masi, L. et al. Cooperation of adhesin alleles in Salmonella-host tropism. mSphere 2, e00066-17 (2017).

  100. 100.

    Kingsley, R. A. et al. Genome and transcriptome adaptation accompanying emergence of the definitive type 2 host-restricted Salmonella enterica Serovar Typhimurium Pathovar. mBio 4, e00565-13 (2013).

  101. 101.

    Viana, D. et al. A single natural nucleotide mutation alters bacterial pathogen host tropism. Nat. Genet. 47, 361–366 (2015). This study demonstrates that a single mutation can have a profound influence on host adaptation.

  102. 102.

    Bayliss, C. D. et al. Phase variable genes of Campylobacter jejuni exhibit high mutation rates and specific mutational patterns but mutability is not the major determinant of population structure during host colonization. Nucleic Acids Res. 40, 5876–5889 (2012).

  103. 103.

    Nuijten, P. J., van den Berg, A. J., Formentini, I., van der Zeijst, B. A. & Jacobs, A. A. DNA rearrangements in the flagellin locus of an flaA mutant of Campylobacter jejuni during colonization of chicken ceca. Infect. Immun. 68, 7137–7140 (2000).

  104. 104.

    Jerome, J. P. et al. Standing genetic variation in contingency loci drives the rapid adaptation of Campylobacter jejuni to a novel host. PLOS One 6, e16399 (2011).

  105. 105.

    Langridge, G. C. et al. Patterns of genome evolution that have accompanied host adaptation in Salmonella. Proc. Natl Acad. Sci. 112, 863–868 (2014).

  106. 106.

    Colles, F. M., Dingle, K. E., Cody, A. J. & Maiden, M. C. J. Comparison of Campylobacter populations in wild geese with those in starlings and free-range poultry on the same farm. Appl. Environ. Microbiol. 74, 3583–3590 (2008).

  107. 107.

    Colles, F. M., McCarthy, N. D., Bliss, C. M., Layton, R. & Maiden, M. C. J. The long-term dynamics of Campylobacter colonizing a free-range broiler breeder flock: an observational study. Environ. Microbiol. 17, 938–946 (2014).

  108. 108.

    Hohwy, J., Reinholdt, J. & Kilian, M. Population dynamics of Streptococcus mitis in its natural habitat. Infect. Immun. 69, 6055–6063 (2001).

  109. 109.

    Nowrouzian, Forough, L., Wold, Agnes, E. & Adlerberth, I. Escherichia coli strains belonging to phylogenetic group B2 have superior capacity to persist in the intestinal microflora of infants. J. Infecti. Diseases 191, 1078–1083 (2005).

  110. 110.

    Chen, P. E. & Shapiro, B. J. The advent of genome-wide association studies for bacteria. Curr. Opin. Microbiol. 25, 17–24 (2015).

  111. 111.

    Arnold, B. J. et al. Weak epistasis may drive adaptation in recombining bacteria. Genetics 208, 1247–1260 (2018). This paper describes a quantitative analysis of the role of epistasis in bacterial adaptation.

  112. 112.

    Skwark, M. J. Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis. PLOS Genetics 13, e1006508 (2017).

  113. 113.

    Corander, J. et al. Frequency-dependent selection in vaccine-associated pneumococcal population dynamics. Nat. Ecol. Evol. 1, 1950–1960 (2017).

  114. 114.

    Fraser, C., Hanage, W. P. & Spratt, B. G. Neutral microepidemic evolution of bacterial pathogens. Proc. Natl Acad. Sci. 102, 1968–1973 (2005). This paper provides a neutral explanation for bacterial population structure and challenges the assumption that strains differ markedly in relative fitness.

  115. 115.

    Cohan, F. M. Towards a conceptual and operational union of bacterial systematics, ecology, and evolution. Phil. Trans. R. Soc. B 361, 1985–1996 (2006).

  116. 116.

    Lees, J. A. et al. Sequence element enrichment analysis to determine the genetic basis of bacterial phenotypes. Nat. Commun. 7, 12797 (2016).

  117. 117.

    Collins, C. & Didelot, X. A phylogenetic method to perform genome-wide association studies in microbes that accounts for population structure and recombination. PLOS Comput. Biol. 14, e1005958 (2018).

  118. 118.

    Thépault, A. et al. Genome-wide identification of host-segregating epidemiological markers for source attribution in Campylobacter jejuni. Appl. Environ. Microbiol. 83, e03085–03016 (2017).

  119. 119.

    McCarthy, N. D. et al. Host-associated genetic import in Campylobacter jejuni. Emerg. Infecti. Diseases 13, 267–272 (2007).

  120. 120.

    Wilson, D. J. et al. Rapid evolution and the importance of recombination to the gastroenteric pathogen Campylobacter jejuni. Mol. Biol. Evol. 26, 385–397 (2008).

  121. 121.

    Maiden, M. C. J. Putting leprosy on the map. Nat. Genet. 41, 1264–1266 (2009).

  122. 122.

    Fraser, C., Hanage, W. P. & Spratt, B. G. Recombination and the nature of bacterial speciation. Science 315, 476–480 (2007). This paper highlights the importance of recombination rates in the processes of adaptation and speciation.

  123. 123.

    Eggleston, A. K., Mitchell, A. H. & West, S. C. In vitro reconstitution of the late steps of genetic recombination in E. coli. Cell 89, 607–617 (1997).

  124. 124.

    Zhu, P. et al. Fit genotypes and escape variants of subgroup III Neisseria meningitidis during three pandemics of epidemic meningitis. Proc. Natl Acad. Sci. USA 98, 5234–5239 (2001).

  125. 125.

    Didelot, X., Achtman, M., Parkhill, J., Thomson, N. R. & Falush, D. A bimodal pattern of relatedness between the Salmonella Paratyphi A and Typhi genomes: convergence or divergence by homologous recombination? Genome Res. 17, 61–68 (2007).

  126. 126.

    Sheppard, S. K. et al. Cryptic ecology among host generalist Campylobacter jejuni in domestic animals. Mol. Ecol. 23, 2442–2451 (2014).

  127. 127.

    Spoor, L. E. et al. Recombination-mediated remodelling of host–pathogen interactions during Staphylococcus aureus niche adaptation. Microb. Genom. 1, 000036 (2015).

  128. 128.

    Almeida, R. P. P. & Nunney, L. How do plant diseases caused by Xylella fastidiosa emerge? Plant Dis. 99, 1457–1467 (2015).

  129. 129.

    Coletta, H. D., Francisco, C. S., Lopes, J. R. S., Muller, C. & Almeida, R. P. P. Homologous recombination and Xylella fastidiosa host-pathogen associations in South America. Phytopathology 107, 305–312 (2017).

  130. 130.

    Nunney, L., Yuan, X. L., Bromley, R. E. & Stouthamer, R. Detecting genetic introgression: high levels of intersubspecific recombination found in Xylella fastidiosa in Brazil. Appl. Environ. Microbiol. 78, 4702–4714 (2012).

  131. 131.

    Corander, J. & Marttinen, P. Bayesian identification of admixture events using multilocus molecular markers. Mol. Ecol. 15, 2833–2843 (2006).

  132. 132.

    Pritchard, J. K., Stephens, M. & Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 155, 945–959 (2000).

  133. 133.

    Lawson, D. J., Hellenthal, G., Myers, S. & Falush, D. Inference of population structure using dense haplotype data. PLOS Genet. 8, e1002453 (2012).

  134. 134.

    Marttinen, P. et al. Detection of recombination events in bacterial genomes from large population samples. Nucleic Acids Res. 40, e6 (2011).

  135. 135.

    Yahara, K., Didelot, X., Ansari, M. A., Sheppard, S. K. & Falush, D. Efficient inference of recombination hot regions in bacterial genomes. Mol. Biol. Evol. 31, 1593–1605 (2014).

  136. 136.

    Harrison, E. M. et al. A shared population of epidemic methicillin-resistant Staphylococcus aureus 15 circulates in humans and companion animals. mBio 5, e00985-13 (2014).

  137. 137.

    Weinert, L. A. et al. Genomic signatures of human and animal disease in the zoonotic pathogen Streptococcus suis. Nat. Commun. 6, 6740 (2015).

  138. 138.

    Vanneste, J. L. The scientific, economic, and social impacts of the New Zealand outbreak of bacterial canker of kiwifruit (Pseudomonas syringae pv. actinidiae). Annu. Rev. Phytopathol. 55, 377–399 (2017).

  139. 139.

    McCann, H. C. et al. Origin and evolution of the kiwifruit canker pandemic. Genome Biol. Evol. 9, 932–944 (2017).

  140. 140.

    Sheppard, S. K. & Maiden, M. C. The evolution of Campylobacter jejuni and Campylobacter coli. Cold Spring Harb. Perspect. Biol. 7, a018119 (2015).

  141. 141.

    Fitzgerald, J. R. Livestock-associated Staphylococcus aureus: origin, evolution and public health threat. Trends Microbiol. 20, 192–198 (2012).

  142. 142.

    Pascoe, B. et al. Local genes for local bacteria: evidence of allopatry in the genomes of transatlantic Campylobacter populations. Mol. Ecol. 26, 4497–4508 (2017).

  143. 143.

    La Reau, A. J., Meier-Kolthoff, J. P. & Suen, G. Sequence-based analysis of the genus Ruminococcus resolves its phylogeny and reveals strong host association. Microb. Genom. 2, e000099 (2016).

  144. 144.

    Richards, V. P., Choi, S., Bitar, P. D., Gurjar, A. A. & Stanhope, M. J. Transcriptomic and genomic evidence for Streptococcus agalactiae adaptation to the bovine environment. BMC Genomics 14, 920 (2013).

  145. 145.

    Slifierz, M. J., Friendship, R. M. & Weese, J. S. Methicillin-resistant Staphylococcus aureus in commercial swine herds is associated with disinfectant and zinc usage. Appl. Environ. Microbiol. 81, 2690–2695 (2015).

  146. 146.

    Cavaco, L. M. et al. Cloning and occurrence of czrC, a gene conferring cadmium and zinc resistance in methicillin-resistant Staphylococcus aureus CC398 isolates. Antimicrob. Agents Chemother. 54, 3605–3608 (2010).

  147. 147.

    Liu, J. et al. Staphylococcal chromosomal cassettes mec (SCCmec): a mobile genetic element in methicillin-resistant Staphylococcus aureus. Microb. Pathog. 101, 56–67 (2016).

  148. 148.

    Schwarz, S. & Johnson, A. P. Transferable resistance to colistin: a new but old threat. J. Antimicrob. Chemother. 71, 2066–2070 (2016).

  149. 149.

    Shepheard, M. A. et al. Historical zoonoses and other changes in host tropism of Staphylococcus aureus, identified by phylogenetic analysis of a population dataset. PLOS ONE 8, e62369 (2013).

  150. 150.

    Spoor, L. E. et al. Livestock origin for a human pandemic clone of community-associated methicillin-resistant Staphylococcus aureus. mBio 4, e00356-13 (2013).

  151. 151.

    Sheppard, S. K. et al. Evolution of an agriculture-associated disease causing Campylobacter coli clade: evidence from national surveillance data in Scotland. PLOS One 5, e15708 (2010).

  152. 152.

    Baumler, A. & Fang, F. C. Host specificity of bacterial pathogens. Cold Spring Harb. Perspect. Med. 3, a010041 (2013).

  153. 153.

    Dearlove, B. L. et al. Rapid host switching in generalist Campylobacter strains erodes the signal for tracing human infections. ISME J. 10, 721–729 (2015).

  154. 154.

    Griekspoor, P. et al. Marked host specificity and lack of phylogeographic population structure of Campylobacter jejuni in wild birds. Mol. Ecol. 22, 1463–1472 (2013).

  155. 155.

    Waldenström, J. et al. Campylobacter jejuni colonization in wild birds: results from an infection experiment. PLOS One 5, e9082 (2010).

  156. 156.

    Sriswasdi, S., Yang, C. C. & Iwasaki, W. Generalist species drive microbial dispersion and evolution. Nat. Commun. 8, 1162 (2017).

  157. 157.

    Elena, S. F., Agudelo-Romero, P. & Lalic, J. The evolution of viruses in multi-host fitness landscapes. Open Virol. J. 3, 1–6 (2009).

  158. 158.

    Geoghegan, J. L., Senior, A. M. & Holmes, E. C. Pathogen population bottlenecks and adaptive landscapes: overcoming the barriers to disease emergence. Proc. Biol. Sci. 283, 20160727 (2016).

  159. 159.

    Fisher, R. A. The genetical theory of natural selection. Vol. 1 (Clarendon Press, 1930).

  160. 160.

    Muller, H. J. Some genetic aspects of sex. Am. Naturalist 66, 118–138 (1932).

  161. 161.

    Johnson, T. J. et al. Associations between multidrug resistance, plasmid content, and virulence potential among extraintestinal pathogenic and commensal Escherichia coli from humans and poultry. Foodborne Pathog. Dis. 9, 37–46 (2012).

  162. 162.

    Woodcock, D. J. et al. Genomic plasticity and rapid host switching can promote the evolution of generalism: a case study in the zoonotic pathogen Campylobacter. Sci. Rep. 7, 9650 (2017). This paper explains how observed gradients of host specialism and generalism can evolve in a multi-host system through the transfer of ecologically important loci among coexisting strains.

  163. 163.

    Wiedenbeck, J. & Cohan, F. M. Origins of bacterial diversity through horizontal genetic transfer and adaptation to new ecological niches. FEMS Microbiol. Rev. 35, 957–976 (2011).

  164. 164.

    Doolittle, W. F. & Papke, R. T. Genomics and the bacterial species problem. Genome Biol. 7, 116 (2006). This paper argues that there is no intrinsic reason why the processes driving diversification and adaptation in bacteria must produce coherent groups of individuals.

  165. 165.

    Watkins, E. R., Maiden, M. C. & Gupta, S. Metabolic competition as a driver of bacterial population structure. Future Microbiol. 11, 1339–1357 (2016).

  166. 166.

    Marttinen, P. & Hanage, W. P. Speciation trajectories in recombining bacterial species. PLOS Comput. Biol. 13, e1005640 (2017).

  167. 167.

    Monteil, C. L. et al. Population-genomic insights into emergence, crop adaptation and dissemination of Pseudomonas syringae pathogens. Microb. Genom. 2, e000089 (2016).

  168. 168.

    Pascoe, B. et al. Enhanced biofilm formation and multi-host transmission evolve from divergent genetic backgrounds in Campylobacter jejuni. Environ. Microbiol. 17, 4779–4789 (2015).

  169. 169.

    Loman, N. J., Quick, J. & Simpson, J. T. A complete bacterial genome assembled de novo using only nanopore sequencing data. Nat. Methods 12, 733–735 (2015).

  170. 170.

    Gawad, C., Koh, W. & Quake, S. R. Single-cell genome sequencing: current state of the science. Nat. Rev. Genet. 17, 175–188 (2016).

  171. 171.

    Quince, C., Walker, A. W., Simpson, J. T., Loman, N. J. & Segata, N. Shotgun metagenomics, from sampling to analysis. Nat. Biotechnol. 35, 833–844 (2017).

  172. 172.

    Lupolova, N., Dallman, T. J., Matthews, L., Bono, J. L. & Gally, D. L. Support vector machine applied to predict the zoonotic potential of E. coli O157 cattle isolates. Proc. Natl Acad. Sci. USA 113, 11312–11317 (2016).

  173. 173.

    Arango-Argoty, G. et al. DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data. Microbiome 6, 23 (2018).

  174. 174.

    Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447, 661–678 (2007).

  175. 175.

    Earle, S. G. et al. Identifying lineage effects when controlling for population structure improves power in bacterial association studies. Nature Microbiol. 1, 16041 (2016).

  176. 176.

    Power, R. A., Parkhill, J. & de Oliveira, T. Microbial genome-wide association studies: lessons from human GWAS. Nat. Rev. Genet. 18, 41–50 (2016).

  177. 177.

    Read, T. D. & Massey, R. C. Characterizing the genetic basis of bacterial phenotypes using genome-wide association studies: a new direction for bacteriology. Genome Med. 6, 109 (2014).

  178. 178.

    Alam, M. T. et al. Dissecting vancomycin-intermediate resistance in Staphylococcus aureus using genome-wide association. Genome Biol. Evol. 6, 1174–1185 (2014).

  179. 179.

    Chewapreecha, C. et al. Comprehensive identification of single nucleotide polymorphisms associated with β-lactam resistance within pneumococcal mosaic genes. PLOS Genet. 10, e1004547 (2014).

  180. 180.

    Laabei, M. et al. Predicting the virulence of MRSA from its genome sequence. Genome Res. 24, 839–849 (2014).

  181. 181.

    Marttinen, P., Croucher, N. J., Gutmann, M. U., Corander, J. & Hanage, W. P. Recombination produces coherent bacterial species clusters in both core and accessory genomes. Microb. Genom. 1, e000038 (2015).

  182. 182.

    Francisco, A. P., Bugalho, M., Ramirez, M. & Carriço, J. A. Global optimal eBURST analysis of multilocus typing data using a graphic matroid approach. BMC Bioinformatics 10, 152 (2009).

Download references

Acknowledgements

The authors thank current and former members of their laboratories for their contributions to current understanding of this topic. S.K.S. was supported by Medical Research Council (MRC) grants MR/L015080/1 and G0801929, Biotechnology and Biological Sciences Research Council (BBSRC) grant BB/I02464X/1 and the Wellcome Trust. J.R.F. was supported by a project grant (BB/K00638X/1) and institute strategic grant funding BBS/E/D/20002173 from the BBSRC, a Wellcome Trust collaborative award 201531/Z/16/Z and MRC grant MRNO2995X/1. D.S.G. was funded by a Discovery Grant through the Canadian Natural Sciences and Engineering Research Council (NSERC).

Reviewer information

Nature Reviews Genetics thanks D. Dean, M. Polz and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Affiliations

  1. Milner Centre for Evolution, Department of Biology & Biotechnology, University of Bath, Claverton Down, Bath, UK

    • Samuel K. Sheppard
  2. Department of Cell & Systems Biology, University of Toronto, Toronto, Ontario, Canada

    • David S. Guttman
  3. Centre for the Analysis of Genome Evolution & Function, University of Toronto, Toronto, Ontario, Canada

    • David S. Guttman
  4. The Roslin Institute, University of Edinburgh, Easter Bush Campus, Edinburgh, UK

    • J. Ross Fitzgerald

Authors

  1. Search for Samuel K. Sheppard in:

  2. Search for David S. Guttman in:

  3. Search for J. Ross Fitzgerald in:

Contributions

S.K.S. and J.R.F. researched data for the article, made substantial contributions to discussions of the content and wrote the article. D.S.G. contributed content and reviewed and edited the manuscript before submission.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to J. Ross Fitzgerald.

Glossary

Effective population size

(Ne). The size of an idealized population that would be reduced in diversity at a rate equal to that of the observed population.

Host adaptation

The ability of bacteria to undergo modification in order to colonize a new host.

Genetic structure

Variation in the genetic makeup of individuals within a population.

Genetic drift

A change in the frequency of an existing gene variant (allele) in a population over time owing to random events (such as mutation).

Ecotypes

Genotypes adapted to a particular niche, which is defined by the extent of spread of an advantageous mutation.

Coalescent theory

A retrospective stochastic genetic model of how genetic diversity arises from a common ancestor.

Phylogroups

A term used in microbiology to describe a deep branching tree structure when monophyletic clades or clonal complexes are difficult to discern.

Linkage disequilibrium

(LD). The nonrandom association of alleles at different loci. LD can be used as a measure of bacterial clonality, which is a lack of recombination that would otherwise disrupt the linkage.

Genetic hitchhiking

The process by which an allele changes frequency in a population because it is linked to a gene under positive selection.

Selective sweep

The fixation of a beneficial allele in a population owing to positive selection, which results in the loss of less fit, alternative alleles.

Core genome

The complement of shared genes among strains of a given bacterial sample or species.

Accessory genome

The complement of strain-dependent (not-shared) genes among strains of a given bacterial sample or species.

Reductive evolution

The downsizing of the genome through gene loss or conversion of genes to pseudogenes.

Genetic bottlenecks

Purges of genetic diversity within a population owing to selective or stochastic events.

Illegitimate recombination

The process by which two non-homologous DNA sequences are joined to each other.

Hill–Robertson effect

The evolutionary advantage provided by recombination when it reduces competition between two beneficial mutations by bringing them into the same genetic background; also known as Hill–Robertson interference.

Clonal interference

Competition between selected clones that carry different competing beneficial mutations.

Pathogenicity islands

Mobile genetic elements containing genes that can confer a pathogenic trait.

Synteny

The physical colocalization and order of loci on the same chromosome in a given strain or species.

Diversifying selection

Selection that occurs when extreme values for a trait are favoured over intermediate values during host adaptation, leading to maintenance of polymorphism (multiple alleles).

Convergent evolution

The independent evolution of similar traits; also known as parallel evolution.

Genome-wide association studies

(GWAS). Studies that use a statistical approach to identify genetic variation within populations that is associated with phenotypic traits.

Epistasis

The interaction between genes whereby the expression of one gene influences the function of another.

Zoonotic

Relating to the transmission of pathogens from animal species to humans.

Gene flow

Transfer of genes from one population to another.

Probabilistic models

Mathematical models used in population genetics to incorporate variables (here, alleles or single nucleotide polymorphisms) and probability distributions (based upon frequency) to identify the number of populations in the sample.

Genetic admixture

The exchange of DNA through recombination between two or more previously isolated populations.

Phylogeographic signatures

Genomic elements that show a segregation pattern that is consistent with geographic distributions of individuals.

Ecological generalism

The capacity to colonize multiple hosts and/or niches.

Metagenomics

The simultaneous analysis of multiple genomes recovered directly from entire bacterial communities, such as environmental or host samples.

About this article

Publication history

Published

DOI

https://doi.org/10.1038/s41576-018-0032-z

Further reading