1887

Abstract

has emerged as an important nosocomial pathogen, which is increasingly difficult to treat due to the genetic acquisition of vancomycin resistance. Ireland has a recalcitrant vancomycin-resistant bloodstream infection rate compared to other developed countries.

Vancomycin resistance rates persist amongst isolates from Irish hospitals. The evolutionary genomics governing these trends have not been fully elucidated.

A set of 28 vancomycin-resistant isolates was sequenced to construct a dataset alongside 61 other publicly available Irish genomes. This dataset was extensively analysed using methodologies (comparative genomics, pangenomics, phylogenetics, genotypics and comparative functional analyses) to uncover distinct evolutionary, coevolutionary and clinically relevant population trends.

These results suggest that a stable (in terms of genome size, GC% and number of genes), yet genetically diverse population (in terms of gene content) of persists in Ireland with acquired resistance arising via plasmid acquisition () or, to a lesser extent, chromosomal recombination (). Population analysis revealed five clusters with one cluster partitioned into four clades which transcend isolation dates. Pangenomic and recombination analyses revealed an open (whole genome and chromosomal specific) pangenome illustrating a rampant evolutionary pattern. Comparative resistomics and virulomics uncovered distinct chromosomal and mobilomal propensity for multidrug resistance, widespread chromosomal point-mutation-mediated resistance and chromosomally harboured arsenals of virulence factors. Interestingly, a potential difference in biofilm formation strategies was highlighted by coevolutionary analysis, suggesting differential biofilm genotypes between and isolates.

These results highlight the evolutionary history of Irish isolates and may provide insight into underlying infection dynamics in a clinical setting. Due to the apparent ease of vancomycin resistance acquisition over time, susceptible should be concurrently reduced in Irish hospitals to mitigate potential resistant infections.

  • This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
Loading

Article metrics loading...

/content/journal/jmm/10.1099/jmm.0.001590
2022-10-27
2024-05-02
Loading full text...

Full text loading...

/deliver/fulltext/jmm/71/10/jmm001590.html?itemId=/content/journal/jmm/10.1099/jmm.0.001590&mimeType=html&fmt=ahah

References

  1. Zhou X, Willems RJL, Friedrich AW, Rossen JWA, Bathoorn E. Enterococcus faecium: from microbiological insights to practical recommendations for infection control and diagnostics. Antimicrob Resist Infect Control 2020; 9:130 [View Article]
    [Google Scholar]
  2. Howden BP, Holt KE, Lam MMC, Seemann T, Ballard S et al. Genomic insights to control the emergence of vancomycin-resistant Enterococci. mBio 2013; 4:e00412-13 [View Article]
    [Google Scholar]
  3. Giannakopoulos X, Sakkas H, Ragos V, Tsiambas E, Bozidis P et al. Impact of Enterococcal urinary tract infections in immunocompromised - neoplastic patients. J BUON 2019; 24:1768–1775
    [Google Scholar]
  4. Chilambi GS, Nordstrom HR, Evans DR, Ferrolino JA, Hayden RT et al. Evolution of vancomycin-resistant Enterococcus faecium during colonization and infection in immunocompromised pediatric patients. Proc Natl Acad Sci U S A 2020; 117:11703–11714 [View Article]
    [Google Scholar]
  5. Alghamdi F, Shakir M. The influence of Enterococcus faecalis as a dental root canal pathogen on endodontic treatment: a systematic review. Cureus 2020; 12:e7257 [View Article]
    [Google Scholar]
  6. Higuita NIA, Huycke MM. Enterococcal Disease, epidemiology, and implications for treatment. Enterococci from commensals to lead causes drug resist infect. Internet 2014 Feb 4 https://www.ncbi.nlm.nih.gov/books/NBK190429 accessed 17 August 2021
    [Google Scholar]
  7. Tortosa JA, Hernández-Palazón J. Enterococcus faecalis meningitis after spinal anesthesia. Anesthesiology 2000; 92:909 [View Article]
    [Google Scholar]
  8. Scapellato PG, Ormazabal C, Scapellato JL, Bottaro EG, Rodríguez Brieschke MT. Meningitis due to vancomycin-resistant Enterococcus faecium successfully treated with combined intravenous and intraventricular chloramphenicol. J Clin Microbiol 2005; 43:3578–3579 [View Article]
    [Google Scholar]
  9. Van Tyne D, Gilmore MS. Friend turned foe: evolution of Enterococcal virulence and antibiotic resistance. Annu Rev Microbiol 2014; 68:337–356 [View Article]
    [Google Scholar]
  10. Tsoulas C, Nathwani D. Review of meta-analyses of vancomycin compared with new treatments for gram-positive skin and soft-tissue infections: are we any clearer?. Int J Antimicrob Agents 2015; 46:1–7 [View Article]
    [Google Scholar]
  11. Liu C, Bayer A, Cosgrove SE, Daum RS, Fridkin SK et al. Clinical practice guidelines by the infectious diseases society of america for the treatment of methicillin-resistant Staphylococcus aureus infections in adults and children. Clin Infect Dis 2011; 52:e18–55 [View Article]
    [Google Scholar]
  12. Munita JM, Arias CA, Murray BE. Enterococcal endocarditis: can we win the war?. Curr Infect Dis Rep 2012; 14:339–349 [View Article]
    [Google Scholar]
  13. Top J, Sinnige JC, Brouwer EC, Werner G, Corander J et al. Identification of a novel genomic island associated with vanD-type vancomycin resistance in six dutch vancomycin-resistant Enterococcus faecium isolates. Antimicrob Agents Chemother 2018; 62:e01793-17 [View Article]
    [Google Scholar]
  14. Hayakawa K, Marchaim D, Palla M, Gudur UM, Pulluru H et al. Epidemiology of vancomycin-resistant Enterococcus faecalis: a case-case-control study. Antimicrob Agents Chemother 2013; 57:49–55 [View Article]
    [Google Scholar]
  15. Machado H, Seif Y, Sakoulas G, Olson CA, Hefner Y et al. Environmental conditions dictate differential evolution of vancomycin resistance in Staphylococcus aureus. Commun Biol 2021; 4:793 [View Article]
    [Google Scholar]
  16. Patel R. Clinical impact of vancomycin-resistant Enterococci. J Antimicrob Chemother 2003; 51 Suppl 3:iii13–21 [View Article]
    [Google Scholar]
  17. Correa-Martinez CL, Tönnies H, Froböse NJ, Mellmann A, Kampmeier S. Transmission of vancomycin-resistant Enterococci in the hospital setting: uncovering the patient-environment interplay. Microorganisms 2020; 8:E203 [View Article]
    [Google Scholar]
  18. Courvalin P. Vancomycin resistance in gram-positive cocci. Clin Infect Dis 2006; 42 Suppl 1:S25–34 [View Article]
    [Google Scholar]
  19. Arias CA, Contreras GA, Murray BE. Management of multidrug-resistant Enterococcal infections. Clin Microbiol Infect 2010; 16:555–562 [View Article]
    [Google Scholar]
  20. O’Driscoll T, Crank CW. Vancomycin-resistant Enterococcal infections: epidemiology, clinical manifestations, and optimal management. Infect Drug Resist 2015; 8:217–230 [View Article]
    [Google Scholar]
  21. Leavis HL, Bonten MJM, Willems RJL. Identification of high-risk Enterococcal clonal complexes: global dispersion and antibiotic resistance. Curr Opin Microbiol 2006; 9:454–460 [View Article]
    [Google Scholar]
  22. Getachew Y, Hassan L, Zakaria Z, Abdul Aziz S. Genetic variability of vancomycin-resistant Enterococcus faecium and Enterococcus faecalis isolates from humans, chickens, and pigs in Malaysia. Appl Environ Microbiol 2013; 79:4528–4533 [View Article]
    [Google Scholar]
  23. Leclercq R, Derlot E, Duval J, Courvalin P. Plasmid-mediated resistance to vancomycin and teicoplanin in Enterococcus faecium. N Engl J Med 1988; 319:157–161 [View Article]
    [Google Scholar]
  24. Yim J, Smith JR, Rybak MJ. Role of combination antimicrobial therapy for vancomycin-resistant Enterococcus faecium infections: review of the urrent Evidence. Pharmacotherapy 2017; 37:579–592 [View Article]
    [Google Scholar]
  25. Zhong Z, Zhang W, Song Y, Liu W, Xu H et al. Comparative genomic analysis of the genus Enterococcus. Microbiol Res 2017; 196:95–105 [View Article]
    [Google Scholar]
  26. Zhong Z, Kwok L-Y, Hou Q, Sun Y, Li W et al. Comparative genomic analysis revealed great plasticity and environmental adaptation of the genomes of Enterococcus faecium. BMC Genomics 2019; 20:602 [View Article]
    [Google Scholar]
  27. Sadowy E, Gawryszewska I, Kuch A, Żabicka D, Hryniewicz W. The changing epidemiology of VanB Enterococcus faecium in Poland. Eur J Clin Microbiol Infect Dis 2018; 37:927–936 [View Article]
    [Google Scholar]
  28. Paoletti C, Foglia G, Princivalli MS, Magi G, Guaglianone E et al. Co-transfer of vanA and aggregation substance genes from Enterococcus faecalis isolates in intra- and interspecies matings. J Antimicrob Chemother 2007; 59:1005–1009 [View Article]
    [Google Scholar]
  29. Handwerger S, Pucci MJ, Volk KJ, Liu J, Lee MS. The cytoplasmic peptidoglycan precursor of vancomycin-resistant Enterococcus faecalis terminates in lactate. J Bacteriol 1992; 174:5982–5984 [View Article]
    [Google Scholar]
  30. Dutka-Malen S, Molinas C, Arthur M, Courvalin P. The VANA glycopeptide resistance protein is related to D-alanyl-D-alanine ligase cell wall biosynthesis enzymes. Mol Gen Genet 1990; 224:364–372 [View Article]
    [Google Scholar]
  31. Roper DI, Huyton T, Vagin A, Dodson G. The molecular basis of vancomycin resistance in clinically relevant Enterococci: crystal structure of D-alanyl-D-lactate ligase (VanA). Proc Natl Acad Sci U S A 2000; 97:8921–8925 [View Article]
    [Google Scholar]
  32. Clark NC, Cooksey RC, Hill BC, Swenson JM, Tenover FC. Characterization of glycopeptide-resistant enterococci from U.S. hospitals. Antimicrob Agents Chemother 1993; 37:2311–2317 [View Article]
    [Google Scholar]
  33. Arthur M, Courvalin P. Genetics and mechanisms of glycopeptide resistance in Enterococci. Antimicrob Agents Chemother 1993; 37:1563–1571 [View Article]
    [Google Scholar]
  34. Park IJ, Lee WG, Shin JH, Lee KW, Woo GJ. VanB phenotype-vanA genotype Enterococcus faecium with heterogeneous expression of teicoplanin resistance. J Clin Microbiol 2008; 46:3091–3093 [View Article]
    [Google Scholar]
  35. Turner RJ, Huang L-N, Viti C, Mengoni A. Metal-resistance in bacteria: why care?. Genes 2020; 11:E1470 [View Article]
    [Google Scholar]
  36. Chen J, Li J, Zhang H, Shi W, Liu Y. Bacterial heavy-metal and antibiotic resistance genes in a copper tailing dam area in northern China. Front Microbiol 2019; 10:1916 [View Article]
    [Google Scholar]
  37. Li L-G, Xia Y, Zhang T. Co-occurrence of antibiotic and metal resistance genes revealed in complete genome collection. ISME J 2017; 11:651–662 [View Article]
    [Google Scholar]
  38. Liu H, Li M, Dao TD, Liu Y, Zhou W et al. Design of PdAu alloy plasmonic nanoparticles for improved catalytic performance in CO2 reduction with visible light irradiation. Nano Energy 2016; 26:398–404 [View Article]
    [Google Scholar]
  39. Maillard J-Y. Antimicrobial biocides in the healthcare environment: efficacy, usage, policies, and perceived problems. Ther Clin Risk Manag 2021; 307:
    [Google Scholar]
  40. Wilkinson LJ, White RJ, Chipman JK. Silver and nanoparticles of silver in wound dressings: a review of efficacy and safety. J Wound Care 2011; 20:543–549 [View Article]
    [Google Scholar]
  41. Grass G, Rensing C, Solioz M. Metallic copper as an antimicrobial surface. Appl Environ Microbiol 2011; 77:1541–1547 [View Article]
    [Google Scholar]
  42. Lebreton F, van Schaik W, Sanguinetti M, Posteraro B, Torelli R et al. AsrR is an oxidative stress sensing regulator modulating Enterococcus faecium opportunistic traits, antimicrobial resistance, and pathogenicity. PLoS Pathog 2012; 8:e1002834 [View Article]
    [Google Scholar]
  43. Hasman H, Aarestrup FM. tcrB, a gene conferring transferable copper resistance in Enterococcus faecium: occurrence, transferability, and linkage to macrolide and glycopeptide resistance. Antimicrob Agents Chemother 2002; 46:1410–1416 [View Article]
    [Google Scholar]
  44. Pidot S, Gao W, Buultjens A, Monk I, Guerillot R et al. Increasing tolerance of hospital Enterococcus faecium to hand-wash alcohols. increasing toler hosp Enterococcus faecium to handwash alcohols. Sci Transl Med 2016053728 [View Article]
    [Google Scholar]
  45. Comerlato CB, Resende MCC de, Caierão J, d’Azevedo PA. Presence of virulence factors in Enterococcus faecalis and Enterococcus faecium susceptible and resistant to vancomycin. Mem Inst Oswaldo Cruz 2013; 108:590–595 [View Article]
    [Google Scholar]
  46. Haghi F, Lohrasbi V, Zeighami H. High incidence of virulence determinants, aminoglycoside and vancomycin resistance in Enterococci isolated from hospitalized patients in Northwest Iran. BMC Infect Dis 2019; 19:744 [View Article]
    [Google Scholar]
  47. Biswas PP, Dey S, Adhikari L, Sen A. Virulence markers of vancomycin resistant Enterococci isolated from infected and colonized patients. J Glob Infect Dis 2014; 6:157–163 [View Article]
    [Google Scholar]
  48. Kim EB, Marco ML. Nonclinical and clinical Enterococcus faecium strains, but not Enterococcus faecalis strains, have distinct structural and functional genomic features. Appl Environ Microbiol 2014; 80:154–165 [View Article]
    [Google Scholar]
  49. van Hal SJ, Willems RJL, Gouliouris T, Ballard SA, Coque TM et al. The global dissemination of hospital clones of Enterococcus faecium. Genome Med 2021; 13:52 [View Article]
    [Google Scholar]
  50. Banfield JF, Young M. Microbiology. variety--the splice of life--in microbial communities. Science 2009; 326:1198–1199 [View Article]
    [Google Scholar]
  51. Koskella B, Brockhurst MA. Bacteria-phage coevolution as a driver of ecological and evolutionary processes in microbial communities. FEMS Microbiol Rev 2014; 38:916–931 [View Article]
    [Google Scholar]
  52. Broniewski JM, Meaden S, Paterson S, Buckling A, Westra ER. The effect of phage genetic diversity on bacterial resistance evolution. ISME J 2020; 14:828–836 [View Article]
    [Google Scholar]
  53. Bonilla N, Santiago T, Marcos P, Urdaneta M, Domingo JS et al. Enterophages, a group of phages infecting Enterococcus faecalis, and their potential as alternate indicators of human faecal contamination. Water Sci Technol 2010; 61:293–300 [View Article]
    [Google Scholar]
  54. Lee D, Im J, Na H, Ryu S, Yun C-H et al. The novel Enterococcus Phage vB_EfaS_HEf13 has broad lytic activity against clinical isolates of Enterococcus faecalis. Front Microbiol 2019; 10:2877 [View Article]
    [Google Scholar]
  55. Wandro S, Oliver A, Gallagher T, Weihe C, England W et al. Predictable molecular adaptation of coevolving Enterococcus faecium and lytic phage EfV12-phi1. Front Microbiol 2018; 9:3192 [View Article]
    [Google Scholar]
  56. Whelan FJ, Rusilowicz M, McInerney JO. Coinfinder: detecting significant associations and dissociations in pangenomes. Microb Genom 2020; 6: [View Article]
    [Google Scholar]
  57. Raven KE, Reuter S, Gouliouris T, Reynolds R, Russell JE et al. Genome-based characterization of hospital-adapted Enterococcus faecalis lineages. Nat Microbiol 2016; 1:15033 [View Article]
    [Google Scholar]
  58. Leinonen R, Sugawara H, Shumway M. The sequence read archive. Nucleic Acids Res 2011; 39:D19–21 [View Article]
    [Google Scholar]
  59. Krueger F. Babraham bioinformatics - Trim Galore. Internet 2012 2021Jan16 https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/
    [Google Scholar]
  60. Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet j 2011; 17:10 [View Article]
    [Google Scholar]
  61. Andrews S, Krueger F, Seconds-Pichon A, Biggins F, FastQC WS. A quality control tool for high throughput sequence data Babraham Bioinformatics. 1(1):undefined-undefined 2015 https://www.mendeley.com/catalogue/8057171e-e700-36a0-b936-1c307058462d/?utm_source=desktop&utm_medium=1.19.8&utm_campaign=open_catalog&userDocumentId=%7B124edc8f-5459-3c1b-a449-8ab9bc3e95f8%7D accessed 18 August 2021
    [Google Scholar]
  62. Wick RR, Judd LM, Gorrie CL, Holt KE. Completing bacterial genome assemblies with multiplex MinION sequencing. Microb Genom 2017; 3:e000132 [View Article]
    [Google Scholar]
  63. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 2012; 19:455–477 [View Article]
    [Google Scholar]
  64. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods 2012; 9:357–359 [View Article]
    [Google Scholar]
  65. Walker BJ, Abeel T, Shea T, Priest M, Abouelliel A et al. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS One 2014; 9:e112963 [View Article]
    [Google Scholar]
  66. Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J et al. BLAST+: architecture and applications. BMC Bioinformatics 2009; 10:421 [View Article]
    [Google Scholar]
  67. Altschul SSF, Gish W, Miller W, Myers EEW, Lipman DJD. Basic local alignment search tool. J Mol Biol 1990; 215:403–410 [View Article]
    [Google Scholar]
  68. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J et al. The sequence alignment/Map format and SAMtools. Bioinform 2009; 25:2078–2079 [View Article]
    [Google Scholar]
  69. Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res 2015; 25:1043–1055 [View Article]
    [Google Scholar]
  70. Seemann T. GitHub - tseemann/mlst: Scan contig files against PubMLST typing schemes. Internet 2014 2021 https://github.com/tseemann/mlst
    [Google Scholar]
  71. Jolley KA, Maiden MCJ. BIGSdb: calable analysis of bacterial genome variation at the population level. BMC Bioinform 2010; 11:595 [View Article]
    [Google Scholar]
  72. Jolley KA, Bray JE, Maiden MCJ. Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications. Wellcome Open Res 2018; 3:124 [View Article]
    [Google Scholar]
  73. Schwengers O, Barth P, Falgenhauer L, Hain T, Chakraborty T et al. Platon: identification and characterization of bacterial plasmid contigs in short-read draft assemblies exploiting protein sequence-based replicon distribution scores. Microb Genom 2020; 6: [View Article]
    [Google Scholar]
  74. Angelopoulou A, Warda AK, O’Connor PM, Stockdale SR, Shkoporov AN et al. Diverse bacteriocins produced by strains from the human milk microbiota. Front Microbiol 2020; 11:788 [View Article]
    [Google Scholar]
  75. Ondov BD, Treangen TJ, Melsted P, Mallonee AB, Bergman NH et al. Mash: fast genome and metagenome distance estimation using minhash. Genome Biol 2016; 17:132 [View Article]
    [Google Scholar]
  76. Galata V, Fehlmann T, Backes C, Keller A. PLSDB: a resource of complete bacterial plasmids. Nucleic Acids Res 2019; 47:D195–D202 [View Article]
    [Google Scholar]
  77. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinf 2014; 30:2068–2069 [View Article]
    [Google Scholar]
  78. Hyatt D, Chen G-L, Locascio PF, Land ML, Larimer FW et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinform 2010; 11:111 [View Article]
    [Google Scholar]
  79. Laslett D, Canback B. ARAGORN, a program to detect tRNA genes and tmRNA genes in nucleotide sequences. Nucleic Acids Res 2004; 32:11–16 [View Article]
    [Google Scholar]
  80. Skennerton C. minced: Mining CRISPRs in Environmental Datasets. Internet 2013 https://github.com/ctSkennerton/minced accessed 18 August 2021
    [Google Scholar]
  81. Petersen TN, Brunak S, von Heijne G, Nielsen H. SignalP 4.0: discriminating signal peptides from transmembrane regions. Nat Methods 2011; 8:785–786 [View Article]
    [Google Scholar]
  82. Finn RD, Clements J, Eddy SR. HMMER web server: interactive sequence similarity searching. Nucleic Acids Res 2011; 39:W29–37 [View Article]
    [Google Scholar]
  83. Stajich JE, Block D, Boulez K, Brenner SE, Chervitz SA et al. The bioperl toolkit: perl modules for the life sciences. Genome Res 2002; 12:1611–1618 [View Article]
    [Google Scholar]
  84. Seemann T. barrnap: Bacterial ribosomal RNA predictor. Internet 2013 https://github.com/tseemann/barrnap accessed 18 August 2021
    [Google Scholar]
  85. Jones P, Binns D, Chang H-Y, Fraser M, Li W et al. InterProScan 5: genome-scale protein function classification. Bioinformatics 2014; 30:1236–1240 [View Article]
    [Google Scholar]
  86. Bateman A, Coin L, Durbin R, Finn RD, Hollich V et al. The Pfam protein families database. Nucleic Acids Res 2004; 32:D138–41 [View Article]
    [Google Scholar]
  87. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H et al. Gene ontology: tool for the unification of biology. Nat Genet 2000; 25:25–29 [View Article]
    [Google Scholar]
  88. Carroll LM, Larralde M, Fleck JS, Ponnudurai R, Milanese A. Accurate de novo identification of biosynthetic gene clusters with GECCO. Bioinform 2000 [View Article]
    [Google Scholar]
  89. Blin K, Shaw S, Steinke K, Villebro R, Ziemert N et al. antiSMASH 5.0: updates to the secondary metabolite genome mining pipeline. Nucleic Acids Res 2019; 47:W81–W87 [View Article]
    [Google Scholar]
  90. Johansson MHK, Bortolaia V, Tansirichaiya S, Aarestrup FM, Roberts AP et al. Detection of mobile genetic elements associated with antibiotic resistance in Salmonella enterica using a newly developed web tool: mobile element finder. J Antimicrob Chemother 2021; 76:101–109 [View Article]
    [Google Scholar]
  91. Seemann T. ABRicate: mass screening of contigs for antimicrobial resistance or virulence genes. Internet 2014 https://github.com/tseemann/abricate/commits/master?after=955d402a23371a61bfca48f1b9e0d30ac724e6ef+209&branch=master accessed 18 August 2021
    [Google Scholar]
  92. Alcock BP, Raphenya AR, Lau TTY, Tsang KK, Bouchard M et al. CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database. Nucleic Acids Res 2020; 48:D517–D525 [View Article]
    [Google Scholar]
  93. Zankari E, Allesøe R, Joensen KG, Cavaco LM, Lund O et al. PointFinder: a novel web tool for WGS-based detection of antimicrobial resistance associated with chromosomal point mutations in bacterial pathogens. J Antimicrob Chemother 2017; 72:2764–2768 [View Article]
    [Google Scholar]
  94. Chen L, Yang J, Yu J, Yao Z, Sun L et al. VFDB: a reference database for bacterial virulence factors. Nucleic Acids Res 2005; 33:D325–8 [View Article]
    [Google Scholar]
  95. Pal C, Bengtsson-Palme J, Rensing C, Kristiansson E, Larsson DGJ. BacMet: antibacterial biocide and metal resistance genes database. Nucleic Acids Res 2014; 42:D737–43 [View Article]
    [Google Scholar]
  96. Rice P, Longden I, Bleasby A. EMBOSS: the european molecular biology open software suite. Trends Genet 2000; 16:276–277 [View Article]
    [Google Scholar]
  97. WELCH BL. The generalisation of student’s problems when several different population variances are involved. Biometrika 1947; 34:28–35 [View Article]
    [Google Scholar]
  98. Student The probable error of a mean. Biometrika 1908; 6:1 [View Article]
    [Google Scholar]
  99. Bonferroni C. Teoria statistica delle classi e calcolo delle probabilita. Pubbl del R Ist uper di sci econ e commericiali di Firenze. Internet 1936 https://ci.nii.ac.jp/naid/20001561442 accessed 20 April 2021
    [Google Scholar]
  100. Dunn OJ. Multiple comparisons among means. J Am Stat Assoc 1961; 56:52–64 [View Article]
    [Google Scholar]
  101. Benjamin DJ, Berger JO, Johannesson M, Nosek BA, Wagenmakers E-J et al. Redefine statistical significance. Nat Hum Behav 2018; 2:6–10 [View Article]
    [Google Scholar]
  102. Kolmogorov AN. Sulla determinazione empirica di una lgge di distribuzione – ScienceOpen Inst Ital Attuari, Giorn. Internet 1933 2021 May 5 https://www.scienceopen.com/document?vid=c3c08573-63b2-4153-a72e-97bd1b3663a0
    [Google Scholar]
  103. Lilliefors HW. On the Kolmogorov-smirnov test for normality with mean and variance unknown. J Am Stat Assoc 1967; 62:399–402 [View Article]
    [Google Scholar]
  104. Levene H. Robust tests for equality of variances. In Olkin I. eds Contributions to Probability and Statistics Stanford University Press, Palo Alto; 1960 pp 278–292
    [Google Scholar]
  105. Bastian M, Heymann S, Jacomy M. Gephi: an open source software for exploring and manipulating networks. in: international AAAI conference on weblogs and social media; 2009
  106. Fruchterman TMJ, Reingold EM. Graph drawing by force-directed placement. Softw: Pract Exper 1991; 21:1129–1164 [View Article]
    [Google Scholar]
  107. Page AJ, Cummins CA, Hunt M, Wong VK, Reuter S et al. Roary: rapid large-scale prokaryote pan genome analysis. Bioinformatics 2015; 31:3691–3693 [View Article]
    [Google Scholar]
  108. Löytynoja A. Phylogeny-aware alignment with PRANK [Internet] 2014. Methods Mol Biol 2020
    [Google Scholar]
  109. Fisher RA. On the “Probable Error” of a coefficient of correlation deduced from a small sample. Metron 1921; 1:3–32
    [Google Scholar]
  110. Klopfenstein DV, Zhang L, Pedersen BS, Ramírez F, Warwick Vesztrocy A et al. GOATOOLS: a python library for gene ontology analyses. Sci Rep 2018; 8:10872 [View Article]
    [Google Scholar]
  111. Capella-Gutiérrez S, Silla-Martínez JM, Gabaldón T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 2009; 25:1972–1973 [View Article]
    [Google Scholar]
  112. Kück P, Meusemann K. FASconCAT: Convenient handling of data matrices. Mol Phylogenet Evol 2010; 56:1115–1118 [View Article]
    [Google Scholar]
  113. Nguyen L-T, Schmidt HA, von Haeseler A, Minh BQ. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol 2015; 32:268–274 [View Article]
    [Google Scholar]
  114. Darriba D, Posada D, Kozlov AM, Stamatakis A, Morel B et al. ModelTest-NG: a new and scalable tool for the selection of DNA and protein evolutionary models. Mol Biol Evol 2020; 37:291–294 [View Article]
    [Google Scholar]
  115. Tavare S. Some probabilistic and statistical problems in the analysis of DNA sequences Lect Math life. Internet 1986 2021 Aug 18 https://books.google.com/books?hl=en&lr=&id=8aI1phhOKhgC&oi=fnd&pg=PA57&ots=roMG4RHdKi&sig=csERmeVhWARlEZ2mHiyf3_zHGSA
    [Google Scholar]
  116. Lechner M, Findeiss S, Steiner L, Marz M, Stadler PF et al. Proteinortho: detection of (co-)orthologs in large-scale analysis. BMC Bioinform 2011; 12:124 [View Article]
    [Google Scholar]
  117. Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 2004; 32:1792–1797 [View Article]
    [Google Scholar]
  118. Le SQ, Gascuel O. An improved general amino acid replacement matrix. Mol Biol Evol 2008; 25:1307–1320 [View Article]
    [Google Scholar]
  119. Letunic I, Bork P. Interactive tree Of life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res 2021; 49:W293–W296 [View Article]
    [Google Scholar]
  120. Cheng L, Connor TR, Sirén J, Aanensen DM, Corander J. Hierarchical and spatially explicit clustering of DNA sequences with BAPS software. Mol Biol Evol 2013; 30:1224–1228 [View Article]
    [Google Scholar]
  121. Tonkin-Hill G, Lees JA, Bentley SD, Frost SDW, Corander J. RhierBAPS: an R implementation of the population clustering algorithm hierBAPS. Wellcome Open Res 2018; 3:93 [View Article]
    [Google Scholar]
  122. Silva M, Machado MP, Silva DN, Rossi M, Moran-Gilad J et al. chewBBACA: a complete suite for gene-by-gene schema creation and strain identification. Microb Genom 2018; 4: [View Article]
    [Google Scholar]
  123. Zhou Z, Alikhan N-F, Sergeant MJ, Luhmann N, Vaz C et al. GrapeTree: visualization of core genomic relationships among 100,000 bacterial pathogens. Genome Res 2018; 28:1395–1404 [View Article]
    [Google Scholar]
  124. Abudahab K, Prada JM, Yang Z, Bentley SD, Croucher NJ et al. PANINI: pangenome neighbour identification for bacterial populations. Microb Genom 2019; 5: [View Article]
    [Google Scholar]
  125. Argimón S, Abudahab K, Goater RJE, Fedosejev A, Bhai J et al. Microreact: visualizing and sharing data for genomic epidemiology and phylogeography. Microb Genom 2016; 2:e000093 [View Article]
    [Google Scholar]
  126. Croucher NJ, Page AJ, Connor TR, Delaney AJ, Keane JA et al. Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins. Nucleic Acids Res 2015; 43:e15 [View Article]
    [Google Scholar]
  127. Hadfield J, Croucher NJ, Goater RJ, Abudahab K, Aanensen DM et al. Phandango: an interactive viewer for bacterial population genomics. Bioinformatics 2018; 34:292–293 [View Article]
    [Google Scholar]
  128. Starikova EV, Tikhonova PO, Prianichnikov NA, Rands CM, Zdobnov EM et al. Phigaro: high-throughput prophage sequence annotation. Bioinformatics 2020; 36:3882–3884 [View Article]
    [Google Scholar]
  129. Cury J, Jové T, Touchon M, Néron B, Rocha EP. Identification and analysis of integrons and cassette arrays in bacterial genomes. Nucleic Acids Res 2016; 44:4539–4550 [View Article]
    [Google Scholar]
  130. Singh KV, Malathum K, Murray BE. Disruption of an Enterococcus faecium species-specific gene, a homologue of acquired macrolide resistance genes of Staphylococci, is associated with an increase in macrolide susceptibility. Antimicrob Agents Chemother 2001; 45:263–266 [View Article]
    [Google Scholar]
  131. Costa Y, Galimand M, Leclercq R, Duval J, Courvalin P. Characterization of the chromosomal aac(6’)-Ii gene specific for Enterococcus faecium. Antimicrob Agents Chemother 1993; 37:1896–1903 [View Article]
    [Google Scholar]
  132. Draker K, Northrop DB, Wright GD. Kinetic mechanism of the GCN5-related chromosomal aminoglycoside acetyltransferase AAC(6’)-Ii from Enterococcus faecium: evidence of dimer subunit cooperativity. Biochemistry 2003; 42:6565–6574 [View Article]
    [Google Scholar]
  133. Wybenga-Groot LE, Draker K, Wright GD, Berghuis AM. Crystal structure of an aminoglycoside 6’-N-acetyltransferase: defining the GCN5-related N-acetyltransferase superfamily fold. Structure 1999; 7:497–507 [View Article]
    [Google Scholar]
  134. Guzmán Prieto AM, Wijngaarden J, Braat JC, Rogers MRC, Majoor E et al. The two-component system ChtRS contributes to chlorhexidine tolerance in Enterococcus faecium. Antimicrob Agents Chemother 2017; 61:e02122-16 [View Article]
    [Google Scholar]
  135. Fujishima K, Kawada-Matsuo M, Oogai Y, Tokuda M, Torii M et al. dpr and sod in Streptococcus mutans are involved in coexistence with S. sanguinis, and PerR is associated with resistance to H2O2. Appl Environ Microbiol 2013; 79:1436–1443 [View Article]
    [Google Scholar]
  136. Yamamoto Y, Poole LB, Hantgan RR, Kamio Y. An iron-binding protein, Dpr, from Streptococcus mutans prevents iron-dependent hydroxyl radical formation in vitro. J Bacteriol 2002; 184:2931–2939 [View Article]
    [Google Scholar]
  137. Hasman H, Kempf I, Chidaine B, Cariolet R, Ersbøll AK et al. Copper resistance in Enterococcus faecium, mediated by the tcrB gene, is selected by supplementation of pig feed with copper sulfate. Appl Environ Microbiol 2006; 72:5784–5789 [View Article]
    [Google Scholar]
  138. Fard RMN, Heuzenroeder MW, Barton MD. Antimicrobial and heavy metal resistance in commensal Enterococci isolated from pigs. Vet Microbiol 2011; 148:276–282 [View Article]
    [Google Scholar]
  139. Horsburgh MJ, Clements MO, Crossley H, Ingham E, Foster SJ. PerR controls oxidative stress resistance and iron storage proteins and is required for virulence in Staphylococcus aureus. Infect Immun 2001; 69:3744–3754 [View Article]
    [Google Scholar]
  140. Møller AK, Barkay T, Hansen MA, Norman A, Hansen LH et al. Mercuric reductase genes (merA) and mercury resistance plasmids in high arctic snow, freshwater and sea-ice brine. FEMS Microbiol Ecol 2014; 87:52–63 [View Article]
    [Google Scholar]
  141. Zaheer R, Cook SR, Barbieri R, Goji N, Cameron A et al. Surveillance of Enterococcus spp. reveals distinct species and antimicrobial resistance diversity across a one-health continuum. Sci Reports 2021
    [Google Scholar]
  142. Creti R, Koch S, Fabretti F, Baldassarri L, Huebner J. Enterococcal colonization of the gastro-intestinal tract: role of biofilm and environmental oligosaccharides. BMC Microbiol 2006; 6:60 [View Article]
    [Google Scholar]
  143. Nallapareddy SR, Singh KV, Sillanpää J, Garsin DA, Höök M et al. Endocarditis and biofilm-associated pili of Enterococcus faecalis. J Clin Invest 2006; 116:2799–2807 [View Article]
    [Google Scholar]
  144. Dahl A, Rasmussen RV, Bundgaard H, Hassager C, Bruun LE et al. Enterococcus faecalis infective endocarditis. Circulation 2021 [View Article]
    [Google Scholar]
  145. Matos RC, Lapaque N, Rigottier-Gois L, Debarbieux L, Meylheuc T et al. Enterococcus faecalis prophage dynamics and contributions to pathogenic traits. PLoS Genet 2013; 9:e1003539 [View Article]
    [Google Scholar]
  146. Mayer C, Vocadlo DJ, Mah M, Rupitz K, Stoll D et al. Characterization of a beta-N-acetylhexosaminidase and a beta-N-acetylglucosaminidase/beta-glucosidase from Cellulomonas fimi. FEBS J 2006; 273:2929–2941 [View Article]
    [Google Scholar]
  147. Rivolta C, Soldo B, Lazarevic V, Joris B, Mauël C et al. A 35.7 kb DNA fragment from the Bacillus subtilis chromosome containing a putative 12.3 kb operon involved in hexuronate catabolism and a perfectly symmetrical hypothetical catabolite-responsive element. Microb 1998; 144 (Pt 4):877–884 [View Article]
    [Google Scholar]
  148. Phillips MK, Hederstedt L, Hasnain S, Rutberg L, Guest JR. Nucleotide sequence encoding the flavoprotein and iron-sulfur protein subunits of the Bacillus subtilis PY79 succinate dehydrogenase complex. J Bacteriol 1987; 169:864–873 [View Article]
    [Google Scholar]
  149. Wipat A, Carter N, Brignell SC, Guy BJ, Piper K et al. The dnaB-pheA (256 degrees-240 degrees) region of the Bacillus subtilis chromosome containing genes responsible for stress responses, the utilization of plant cell walls and primary metabolism. Microbio 1996; 142 (Pt 11):3067–3078 [View Article]
    [Google Scholar]
  150. Mekjian KR, Bryan EM, Beall BW, Moran CP. Regulation of hexuronate utilization in Bacillus subtilis. J Bacteriol 1999; 181:426–433 [View Article]
    [Google Scholar]
  151. Setlow B, Cabrera-Hernandez A, Cabrera-Martinez RM, Setlow P. Identification of aryl-phospho-beta-D-glucosidases in Bacillus subtilis. Arch Microbiol 2004; 181:60–67 [View Article]
    [Google Scholar]
  152. Sadaie Y, Nakadate H, Fukui R, Yee LM, Asai K. Glucomannan utilization operon of Bacillus subtilis. FEMS Microbiol Lett 2008; 279:103–109 [View Article]
    [Google Scholar]
  153. Wong MD, Lin Y-F, Rosen BP. The soft metal Ion binding sites in the Staphylococcus aureus pI258 CadC Cd(II)/Pb(II)/Zn(II)-responsive repressor are formed between subunits of the homodimer. J Biol Chem 2002; 277:40930–40936 [View Article]
    [Google Scholar]
  154. Msadek T, Kunst F, Rapoport G. MecB of Bacillus subtilis, a member of the ClpC ATPase family, is a pleiotropic regulator controlling competence gene expression and growth at high temperature. Proc Natl Acad Sci U S A 1994; 91:5788–5792 [View Article]
    [Google Scholar]
  155. Krüger E, Völker U, Hecker M. Stress induction of clpC in Bacillus subtilis and its involvement in stress tolerance. J Bacteriol 1994; 176:3360–3367 [View Article]
    [Google Scholar]
  156. Leskelä S, Wahlström E, Kontinen VP, Sarvas M. Lipid modification of prelipoproteins is dispensable for growth but essential for efficient protein secretion in Bacillus subtilis: characterization of the lgt gene. Mol Microbiol 1999; 31:1075–1085 [View Article]
    [Google Scholar]
  157. Harvie DR, Andreini C, Cavallaro G, Meng W, Connolly BA et al. Predicting metals sensed by ArsR-SmtB repressors: allosteric interference by a non-effector metal. Mol Microbiol 2006; 59:1341–1356 [View Article]
    [Google Scholar]
  158. Nicolaou SA, Fast AG, Nakamaru-Ogiso E, Papoutsakis ET. Overexpression of fetA (ybbL) and fetB (ybbM), encoding an iron exporter, enhances resistance to oxidative stress in Escherichia coli. Appl Environ Microbiol 2013; 79:7210–7219 [View Article]
    [Google Scholar]
  159. Zheng R, Blanchard JS. Kinetic and mechanistic analysis of the E. coli panE-encoded ketopantoate reductase. Biochemistry 2000; 39:3708–3717 [View Article]
    [Google Scholar]
  160. Fraser KR, Harvie D, Coote PJ, O’Byrne CP. Identification and characterization of an ATP binding cassette L-carnitine transporter in listeria monocytogenes. Appl Environ Microbiol 2000; 66:4696–4704 [View Article]
    [Google Scholar]
  161. Huynh TN, Choi PH, Sureka K, Ledvina HE, Campillo J et al. Cyclic di-AMP targets the cystathionine beta-synthase domain of the osmolyte transporter OpuC. Mol Microbiol 2016; 102:233–243 [View Article]
    [Google Scholar]
  162. Pruteanu M, Baker TA. Controlled degradation by ClpXP protease tunes the levels of the excision repair protein UvrA to the extent of DNA damage. Mol Microbiol 2009; 71:912–924 [View Article]
    [Google Scholar]
  163. Myles GM, Sancar A. Isolation and characterization of functional domains of UvrA. Biochemistry 1991; 30:3834–3840 [View Article]
    [Google Scholar]
  164. Cooper RA. The utilisation of D-galactonate and D-2-oxo-3-deoxygalactonate by Escherichia coli K-12. biochemical and genetical studies. Arch Microbiol 1978; 118:199–206 [View Article]
    [Google Scholar]
  165. LowKam C, Liotard B, Sygusch J. Structure of a class I tagatose-1,6-bisphosphate aldolase: investigation into an apparent loss of stereospecificity. J Biol Chem 2010; 285:21143–21152 [View Article]
    [Google Scholar]
  166. Erni B, Zanolari B, Kocher HP. The mannose permease of Escherichia coli consists of three different proteins. amino acid sequence and function in sugar transport, sugar phosphorylation, and penetration of phage lambda DNA. J Biol Chem 1987; 262:5238–5247 [View Article]
    [Google Scholar]
  167. Stolz B, Huber M, Marković-Housley Z, Erni B. The mannose transporter of Escherichia coli. Structure and function of the IIABMan subunit. J Biol Chem 1993; 268:27094–27099 [View Article]
    [Google Scholar]
  168. Newton GL, Koledin T, Gorovitz B, Rawat M, Fahey RC et al. The glycosyltransferase gene encoding the enzyme catalyzing the first step of mycothiol biosynthesis (mshA). J Bacteriol 2003; 185:3476–3479 [View Article]
    [Google Scholar]
  169. Schöck F, Dahl MK. Analysis of DNA flanking the treA gene of Bacillus subtilis reveals genes encoding a putative specific enzyme IITre and a potential regulator of the trehalose operon. Gene 1996; 175:59–63 [View Article]
    [Google Scholar]
  170. Kearns DB, Chu F, Branda SS, Kolter R, Losick R. A master regulator for biofilm formation by Bacillus subtilis. Mol Microbiol 2005; 55:739–749 [View Article]
    [Google Scholar]
  171. S-Nogueira I, Nogueira TV, Soares S, de Lencastre H. The Bacillus subtilis L-arabinose (ara) operon: nucleotide sequence, genetic organization and expression. Microbiology 1997; 143 (Pt 3):957–969 [View Article]
    [Google Scholar]
  172. Sirko A, Hryniewicz M, Hulanicka D, Böck A. Sulfate and thiosulfate transport in Escherichia coli K-12: nucleotide sequence and expression of the cysTWAM gene cluster. J Bacteriol 1990; 172:3351–3357 [View Article]
    [Google Scholar]
  173. Chowdhury N, Norris J, McAlister E, Lau SYK, Thomas GH et al. The VC1777-VC1779 proteins are members of a sialic acid-specific subfamily of TRAP transporters (SiaPQM) and constitute the sole route of sialic acid uptake in the human pathogen Vibrio cholerae. Microbiol 2012; 158:2158–2167 [View Article]
    [Google Scholar]
  174. Mathiopoulos C, Mueller JP, Slack FJ, Murphy CG, Patankar S et al. A Bacillus subtilis dipeptide transport system expressed early during sporulation. Mol Microbiol 1991; 5:1903–1913 [View Article]
    [Google Scholar]
  175. Perego M, Higgins CF, Pearce SR, Gallagher MP, Hoch JA. The oligopeptide transport system of Bacillus subtilis plays a role in the initiation of sporulation. Mol Microbiol 1991; 5:173–185 [View Article]
    [Google Scholar]
  176. Koide A, Hoch JA. Identification of a second oligopeptide transport system in Bacillus subtilis and determination of its role in sporulation. Mol Microbiol 1994; 13:417–426 [View Article] [PubMed]
    [Google Scholar]
  177. Parra-Lopez C, Baer MT, Groisman EA. Molecular genetic analysis of a locus required for resistance to antimicrobial peptides in Salmonella typhimurium. EMBO J 1993; 12:4053–4062 [View Article]
    [Google Scholar]
  178. Breazeale SD, Ribeiro AA, Raetz CRH. Origin of lipid a species modified with 4-AMINO-4-DEOXY-L-ARABINOSE in polymyxin-resistant mutants of Escherichia coli. AN AMINOTRANSFERASE (ArnB) THAT GENERATES UDP-4-deoxyl-L-ARABINOSE. J Biol Chem 2003; 278:24731–24739 [View Article]
    [Google Scholar]
  179. Yan A, Guan Z, Raetz CRH. An undecaprenyl phosphate-aminoarabinose flippase required for polymyxin resistance in Escherichia coli. J Biol Chem 2007; 282:36077–36089 [View Article]
    [Google Scholar]
  180. Liu Y-Y, Wang Y, Walsh TR, Yi L-X, Zhang R et al. Emergence of plasmid-mediated colistin resistance mechanism MCR-1 in animals and human beings in China: a microbiological and molecular biological study. Lancet Infect Dis 2016; 16:161–168 [View Article]
    [Google Scholar]
  181. Alonso A, Sanchez P, Martínez JL. Stenotrophomonas maltophilia D457R contains a cluster of genes from gram-positive bacteria involved in antibiotic and heavy metal resistance. Antimicrob Agents Chemother 2000; 44:1778–1782 [View Article]
    [Google Scholar]
  182. Humphrey S, Fillol-Salom A, Quiles-Puchalt N, Ibarra-Chávez R, Haag AF et al. Bacterial chromosomal mobility via lateral transduction exceeds that of classical mobile genetic elements. Nat Commun 2021; 12:6509 [View Article]
    [Google Scholar]
  183. Chiang YN, Penadés JR, Chen J. Genetic transduction by phages and chromosomal islands: The new and noncanonical. PLoS Pathog 2019; 15:e1007878 [View Article]
    [Google Scholar]
  184. Royal College of Physicians I, Health Service Executive I Guidelines for the prevention and control of MDRO excluding MRSA in the healthcare setting. J R Coll Physicians Edinb 2012
    [Google Scholar]
  185. Wein T, Wang Y, Barz M, Stücker FT, Hammerschmidt K et al. Essential gene acquisition destabilizes plasmid inheritance. PLoS Genet 2021; 17:e1009656 [View Article]
    [Google Scholar]
  186. Alice AF, López CS, Crosa JH. Plasmid- and chromosome-encoded redundant and specific functions are involved in biosynthesis of the siderophore anguibactin in Vibrio anguillarum 775: a case of chance and necessity?. J Bacteriol 2005; 187:2209–2214 [View Article]
    [Google Scholar]
  187. Zheng J, Guan Z, Cao S, Peng D, Ruan L et al. Plasmids are vectors for redundant chromosomal genes in the Bacillus cereus group. BMC Genomics 2015; 16:6 [View Article]
    [Google Scholar]
  188. Carroll AC, Wong A. Plasmid persistence: costs, benefits, and the plasmid paradox. Can J Microbiol 2018; 64:293–304 [View Article]
    [Google Scholar]
  189. Baker-Austin C, Wright MS, Stepanauskas R, McArthur JV. Co-selection of antibiotic and metal resistance. Trends Microbiol 2006; 14:176–182 [View Article]
    [Google Scholar]
  190. Bae T, Baba T, Hiramatsu K, Schneewind O. Prophages of Staphylococcus aureus Newman and their contribution to virulence. Mol Microbiol 2006 Nov; 62:1035–1047 [View Article]
    [Google Scholar]
  191. Bae T, Baba T, Hiramatsu K, Schneewind O. Prophages of Staphylococcus aureus newman and their contribution to virulence. Mol Microbiol 2006; 62:1035–1047 [View Article] [PubMed]
    [Google Scholar]
  192. Xia G, Wolz C. Phages of Staphylococcus aureus and their impact on host evolution. Infect Genet Evol 2014; 21:593–601 [View Article]
    [Google Scholar]
  193. Pasek S, Risler J-L, Brézellec P. Gene fusion/fission is a major contributor to evolution of multi-domain bacterial proteins. Bioinformatics 2006; 22:1418–1423 [View Article]
    [Google Scholar]
  194. Des Marais DL, Rausher MD. Escape from adaptive conflict after duplication in an anthocyanin pathway gene. Nature 2008; 454:762–765 [View Article]
    [Google Scholar]
  195. Rastogi S, Liberles DA. Subfunctionalization of duplicated genes as a transition state to neofunctionalization. BMC Evol Biol 2005; 5:28 [View Article]
    [Google Scholar]
  196. Leonard G, Richards TA. Genome-scale comparative analysis of gene fusions, gene fissions, and the fungal tree of life. Proc Natl Acad Sci U S A 2012; 109:21402–21407 [View Article]
    [Google Scholar]
  197. Conant GC, Birchler JA, Pires JC. Dosage, duplication, and diploidization: clarifying the interplay of multiple models for duplicate gene evolution over time. Curr Opin Plant Biol 2014; 19:91–98 [View Article]
    [Google Scholar]
  198. Wang W, Yu H, Long M. Duplication-degeneration as a mechanism of gene fission and the origin of new genes in Drosophila species. Nat Genet 2004; 36:523–527 [View Article]
    [Google Scholar]
  199. Snel B, Bork P, Huynen M. Genome evolution. gene fusion versus gene fission. Trends Genet 2000; 16:9–11 [View Article]
    [Google Scholar]
  200. de Been M, van Schaik W, Cheng L, Corander J, Willems RJ. Recent recombination events in the core genome are associated with adaptive evolution in Enterococcus faecium. Genome Biol Evol 2013; 5:1524–1535 [View Article]
    [Google Scholar]
  201. Leavis HL, Willems RJL, van Wamel WJB, Schuren FH, Caspers MPM et al. Insertion sequence-driven diversification creates a globally dispersed emerging multiresistant subspecies of E. faecium. PLoS Pathog 2007; 3:0075–0096 [View Article]
    [Google Scholar]
  202. Arenas M, Araujo NM, Branco C, Castelhano N, Castro-Nallar E et al. Mutation and recombination in pathogen evolution: relevance, methods and controversies. Infect Genet Evol 2018; 63:295–306 [View Article]
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/jmm/10.1099/jmm.0.001590
Loading
/content/journal/jmm/10.1099/jmm.0.001590
Loading

Data & Media loading...

Supplements

Supplementary material 1

PDF
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error