Skip to content
1887

Microbial Genomics logo Microbial Genomics

Volume 10, Issue 7

Five centuries of genome evolution and multi-host adaptation of in Brazil Open Access

Abstract

Consumption of raw, undercooked or contaminated animal food products is a frequent cause of infection. Brazil is the world’s third largest producer and a major exporter of chicken meat, yet population-level genomic investigations of in the country remain scarce. Analysis of 221 . genomes from Brazil shows that the overall core and accessory genomic features of are influenced by the identity of the human or animal source. Of the 60 sequence types detected, ST353 is the most prevalent and consists of samples from chicken and human sources. Notably, we identified the presence of diverse genes from the OXA-61 and OXA-184 families that confer beta-lactam resistance as well as the operon related to multidrug efflux pump, which contributes to resistance against tetracyclines, macrolides and quinolones. Based on limited data, we estimated the most recent common ancestor of ST353 to the late 1500s, coinciding with the time the Portuguese first arrived in Brazil and introduced domesticated chickens into the country. We identified at least two instances of ancestral chicken-to-human infections in ST353. The evolution of in Brazil was driven by the confluence of clinically relevant genetic elements, multi-host adaptation and clonal population growth that coincided with major socio-economic changes in poultry farming.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): antimicrobial resistance , Campylobacter jejuni , genome evolution , population structure , sequence type 353 and virulence
Funding
This study was supported by the:
  • National Institutes of Health (Award R35GM142924)
    • Principle Award Recipient: CherylP Andam
© 2024 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.
Loading

Article metrics loading...

/content/journal/mgen/10.1099/mgen.0.001274
2024-07-19
2025-06-12
Loading full text...

Full text loading...

/deliver/fulltext/mgen/10/7/mgen001274.html?itemId=/content/journal/mgen/10.1099/mgen.0.001274&mimeType=html&fmt=ahah

References

  1. Kaakoush NO, Castaño-Rodríguez N, Mitchell HM, Man SM. Global epidemiology of campylobacter infection. Clin Microbiol Rev 2015; 28:687–720 [View Article] [PubMed]
     [Google Scholar]
  2. Liu F, Lee SA, Xue J, Riordan SM, Zhang L. Global epidemiology of campylobacteriosis and the impact of COVID-19. Front Cell Infect Microbiol 2022; 12:979055 [View Article] [PubMed]
     [Google Scholar]
  3. Burnham PM, Hendrixson DR. Campylobacter jejuni: collective components promoting a successful enteric lifestyle. Nat Rev Microbiol 2018; 16:551–565 [View Article] [PubMed]
     [Google Scholar]
  4. Zbrun MV, Rossler E, Romero-Scharpen A, Soto LP, Berisvil A et al. Worldwide meta-analysis of the prevalence of Campylobacter in animal food products. Res Vet Sci 2020; 132:69–77 [View Article] [PubMed]
     [Google Scholar]
  5. Mughini-Gras L, Pijnacker R, Coipan C, Mulder AC, Fernandes Veludo A et al. Sources and transmission routes of campylobacteriosis: a combined analysis of genome and exposure data. J Infect 2021; 82:216–226 [View Article] [PubMed]
     [Google Scholar]
  6. Blaser MJ, Engberg J. Clinical aspects of Campylobacter jejuni and Campylobacter coli infections. In Campylobacter John Wiley & Sons, Ltd; pp 97–121 [View Article]
     [Google Scholar]
  7. Schiaffino F, Platts-Mills J, Kosek MN. A One Health approach to prevention, treatment, and control of campylobacteriosis. Curr Opin Infect Dis 2019; 32:453–460 [View Article] [PubMed]
     [Google Scholar]
  8. Shen Z, Wang Y, Zhang Q, Shen J. Antimicrobial resistance in campylobacter spp. Microbiol Spectr 2018 [View Article]
     [Google Scholar]
  9. Shahrizaila N, Lehmann HC, Kuwabara S. Guillain-Barré syndrome. Lancet 2021; 397:1214–1228 [View Article] [PubMed]
     [Google Scholar]
  10. Scallan Walter EJ, Crim SM, Bruce BB, Griffin PM. Incidence of Campylobacter-associated Guillain-Barré syndrome estimated from health insurance data. Foodborne Pathog Dis 2020; 17:23–28 [View Article] [PubMed]
     [Google Scholar]
  11. Joseph LA, Griswold T, Vidyaprakash E, Im SB, Williams GM et al. Evaluation of core genome and whole genome multilocus sequence typing schemes for Campylobacter jejuni and Campylobacter coli outbreak detection in the USA. Microb Genom 2023; 9:mgen001012 [View Article] [PubMed]
     [Google Scholar]
  12. Arning N, Sheppard SK, Bayliss S, Clifton DA, Wilson DJ. Machine learning to predict the source of campylobacteriosis using whole genome data. PLoS Genet 2021; 17:e1009436 [View Article] [PubMed]
     [Google Scholar]
  13. Mehla K, Ramana J. Novel drug targets for food-borne pathogen Campylobacter jejuni: an integrated subtractive genomics and comparative metabolic pathway study. OMICS 2015; 19:393–406 [View Article] [PubMed]
     [Google Scholar]
  14. van Vliet AHM, Thakur S, Prada JM, Mehat JW, La Ragione RM. Genomic screening of antimicrobial resistance markers in UK and US Campylobacter isolates highlights stability of resistance over an 18-year period. Antimicrob Agents Chemother 2022; 66:e0168721 [View Article] [PubMed]
     [Google Scholar]
  15. Epping L, Walther B, Piro RM, Knüver M-T, Huber C et al. Genome-wide insights into population structure and host specificity of Campylobacter jejuni. Sci Rep 2021; 11:10358 [View Article] [PubMed]
     [Google Scholar]
  16. Costa S. ed The Saga of the Brazilian Poultry Industry - How Brazil has Become the World’s Largest Exporter of Chicken Meat Rio de Janeiro and São Paulo, Brazil: UBABEF; 2011
     [Google Scholar]
  17. Klein H, Vidal F. La emergencia de Brasil como principal exportador mundial de carne de pollo (the emergence of Brazil as the leading world exporter of chicken meat). Historia Agraria de América Latina 2022; 3:75–99 [View Article]
     [Google Scholar]
  18. Brazil - Ministry of Health Banco de dados de surtos de DTHA (2000 a 2022) (Foodborne disease outbreak database - 2000 to 2022); 2023 https://www.gov.br/saude/pt-br/assuntos/saude-de-a-a-z/d/dtha/publicacoes
  19. Munayco CV, Gavilan RG, Ramirez G, Loayza M, Miraval ML et al. Large Outbreak of Guillain-Barré Syndrome, Peru, 2019. Emerg Infect Dis 2020; 26:2778–2780 [View Article]
     [Google Scholar]
  20. Quino W, Caro-Castro J, Mestanza O, Hurtado V, Zamudio ML et al. Emergence and molecular epidemiology of Campylobacter jejuni ST-2993 associated with a large outbreak of Guillain-Barré syndrome in Peru. Microbiol Spectr 2022; 10:e0118722 [View Article] [PubMed]
     [Google Scholar]
  21. World Health Organization (WHO) Guillain-Barré syndrome – Peru. n.d https://www.who.int/emergencies/disease-outbreak-news/item/2023-DON477 accessed 20 June 2024
  22. Pascoe B, Schiaffino F, Murray S, Méric G, Bayliss SC et al. Genomic epidemiology of Campylobacter jejuni associated with asymptomatic pediatric infection in the Peruvian Amazon. PLoS Negl Trop Dis 2020; 14:e0008533 [View Article] [PubMed]
     [Google Scholar]
  23. Collado L, Muñoz N, Porte L, Ochoa S, Varela C et al. Genetic diversity and clonal characteristics of ciprofloxacin-resistant Campylobacter jejuni isolated from Chilean patients with gastroenteritis. Infect Genet Evol 2018; 58:290–293 [View Article] [PubMed]
     [Google Scholar]
  24. Toledo Z, Simaluiza RJ, Astudillo X, Fernández H. Occurrence and antimicrobial susceptibility of thermophilic Campylobacter species isolated from healthy children attending municipal care centers in Southern Ecuador. Rev Inst Med Trop Sao Paulo 2017; 59:e77 [View Article] [PubMed]
     [Google Scholar]
  25. Melo RT, Grazziotin AL, Júnior ECV, Prado RR, Mendonça EP et al. Evolution of Campylobacter jejuni of poultry origin in Brazil. Food Microbiol 2019; 82:489–496 [View Article] [PubMed]
     [Google Scholar]
  26. Rodrigues CS, Armendaris PM, de Sá CVGC, Haddad JPA, de Melo CB. Prevalence of Campylobacter spp. in chicken carcasses in slaughterhouses from South of Brazil. Curr Microbiol 2021; 78:2242–2250 [View Article] [PubMed]
     [Google Scholar]
  27. 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] [PubMed]
     [Google Scholar]
  28. Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: quality assessment tool for genome assemblies. Bioinformatics 2013; 29:1072–1075 [View Article] [PubMed]
     [Google Scholar]
  29. 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] [PubMed]
     [Google Scholar]
  30. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 2014; 30:2068–2069 [View Article] [PubMed]
     [Google Scholar]
  31. Jain C, Rodriguez-R LM, Phillippy AM, Konstantinidis KT, Aluru S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Commun 2018; 9:5114 [View Article] [PubMed]
     [Google Scholar]
  32. Tettelin H, Masignani V, Cieslewicz MJ, Donati C, Medini D et al. Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: implications for the microbial “pan-genome.”. Proc Natl Acad Sci U S A 2005; 102:13950–13955 [View Article] [PubMed]
     [Google Scholar]
  33. Tonkin-Hill G, MacAlasdair N, Ruis C, Weimann A, Horesh G et al. Producing polished prokaryotic pangenomes with the Panaroo pipeline. Genome Biol 2020; 21:180 [View Article] [PubMed]
     [Google Scholar]
  34. Löytynoja A. Phylogeny-aware alignment with PRANK. Methods Mol Biol 2014; 1079:155–170 [View Article] [PubMed]
     [Google Scholar]
  35. Page AJ, Taylor B, Delaney AJ, Soares J, Seemann T et al. SNP-sites: rapid efficient extraction of SNPs from multi-FASTA alignments. Microb Genom 2016; 2:e000056 [View Article]
     [Google Scholar]
  36. Stamatakis A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 2014; 30:1312–1313 [View Article] [PubMed]
     [Google Scholar]
  37. Tavaré S. Some probabilistic and statistical problems in the analysis of DNA sequences. In American Mathematical Society: Lectures on Mathematics in the Life Sciences American Mathematical Society; 1986 pp 57–86
     [Google Scholar]
  38. 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] [PubMed]
     [Google Scholar]
  39. Tonkin-Hill G, Lees JA, Bentley SD, Frost SDW, Corander J. Fast hierarchical Bayesian analysis of population structure. Nucleic Acids Res 2019; 47:5539–5549 [View Article] [PubMed]
     [Google Scholar]
  40. Dingle KE, Colles FM, Wareing DR, Ure R, Fox AJ et al. Multilocus sequence typing system for Campylobacter jejuni. J Clin Microbiol 2001; 39:14–23 [View Article] [PubMed]
     [Google Scholar]
  41. 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] [PubMed]
     [Google Scholar]
  42. Feldgarden M, Brover V, Gonzalez-Escalona N, Frye JG, Haendiges J et al. AMRFinderPlus and the reference gene catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence. Sci Rep 2021; 11:12728 [View Article] [PubMed]
     [Google Scholar]
  43. Alcock BP, Huynh W, Chalil R, Smith KW, Raphenya AR et al. CARD 2023: expanded curation, support for machine learning,and resistome prediction at the comprehensive antibiotic resistance database. Nucleic Acids Res 2023; 51:D690–D699 [View Article] [PubMed]
     [Google Scholar]
  44. Liu B, Zheng D, Zhou S, Chen L, Yang J. VFDB 2022: a general classification scheme for bacterial virulence factors. Nucleic Acids Res 2022; 50:D912–D917 [View Article] [PubMed]
     [Google Scholar]
  45. 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] [PubMed]
     [Google Scholar]
  46. Didelot X, Croucher NJ, Bentley SD, Harris SR, Wilson DJ. Bayesian inference of ancestral dates on bacterial phylogenetic trees. Nucleic Acids Res 2018; 46:e134 [View Article]
     [Google Scholar]
  47. Didelot X, Siveroni I, Volz EM. Additive uncorrelated relaxed clock models for the dating of genomic epidemiology phylogenies. Mol Biol Evol 2021; 38:307–317 [View Article] [PubMed]
     [Google Scholar]
  48. Spiegelhalter DJ, Best NG, Carlin BP, Van Der Linde A. Bayesian measures of model complexity and fit. J R Stat Soc Series B Stat Methodol 2002; 64:583–639 [View Article]
     [Google Scholar]
  49. Grolemund G, Wickham H. Dates and times made easy with Lubridate. J Stat Softw 2011; 40:1–25 [View Article]
     [Google Scholar]
  50. Plummer M, Best N, Cowles K, Vines K. CODA: convergence diagnosis and output analysis for MCMC. R News 2006; 6:7–11
     [Google Scholar]
  51. Gelman A, Rubin DB. Inference from iterative simulation using multiple sequences. Statist Sci 1992; 7:457–472 [View Article]
     [Google Scholar]
  52. Brooks SP, Gelman A. General methods for monitoring convergence of iterative simulations. J Comput Graph Stat 1998; 7:434–455 [View Article]
     [Google Scholar]
  53. Helekal D, Ledda A, Volz E, Wyllie D, Didelot X. Bayesian inference of clonal expansions in a dated phylogeny. Syst Biol 2022; 71:1073–1087 [View Article] [PubMed]
     [Google Scholar]
  54. Volz EM, Didelot X. Modeling the growth and decline of pathogen effective population size provides insight into epidemic dynamics and drivers of antimicrobial resistance. Syst Biol 2018; 67:719–728 [View Article] [PubMed]
     [Google Scholar]
  55. Nei M, Tajima F. Genetic drift and estimation of effective population size. Genetics 1981; 98:625–640 [View Article] [PubMed]
     [Google Scholar]
  56. Patil I. Visualizations with statistical details: the “ggstatsplot” approach. JOSS 2021; 6:3167 [View Article]
     [Google Scholar]
  57. RStudio Team RStudio: integrated development for R. n.d http://www.rstudio.com
  58. Kemper L, Hensel A. Campylobacter jejuni: targeting host cells, adhesion, invasion, and survival. Appl Microbiol Biotechnol 2023; 107:2725–2754 [View Article] [PubMed]
     [Google Scholar]
  59. Carrillo CD, Taboada E, Nash JHE, Lanthier P, Kelly J et al. Genome-wide expression analyses of Campylobacter jejuni NCTC11168 reveals coordinate regulation of motility and virulence by flhA. J Biol Chem 2004; 279:20327–20338 [View Article] [PubMed]
     [Google Scholar]
  60. Konkel ME, Klena JD, Rivera-Amill V, Monteville MR, Biswas D et al. Secretion of virulence proteins from Campylobacter jejuni is dependent on a functional flagellar export apparatus. J Bacteriol 2004; 186:3296–3303 [View Article] [PubMed]
     [Google Scholar]
  61. Linton D, Gilbert M, Hitchen PG, Dell A, Morris HR et al. Phase variation of a beta-1,3 galactosyltransferase involved in generation of the ganglioside GM1-like lipo-oligosaccharide of Campylobacter jejuni. Mol Microbiol 2000; 37:501–514 [View Article] [PubMed]
     [Google Scholar]
  62. Culebro A, Machado MP, Carriço JA, Rossi M. Origin, evolution, and distribution of the molecular machinery for biosynthesis of sialylated lipooligosaccharide structures in Campylobacter coli. Sci Rep 2018; 8:3028 [View Article] [PubMed]
     [Google Scholar]
  63. Nielsen LN, Sheppard SK, McCarthy ND, Maiden MCJ, Ingmer H et al. MLST clustering of Campylobacter jejuni isolates from patients with gastroenteritis, reactive arthritis and Guillain-Barré syndrome. J Appl Microbiol 2010; 108:591–599 [View Article] [PubMed]
     [Google Scholar]
  64. Lin J, Michel LO, Zhang Q. CmeABC functions as a multidrug efflux system in Campylobacter jejuni. Antimicrob Agents Chemother 2002; 46:2124–2131 [View Article] [PubMed]
     [Google Scholar]
  65. Griggs DJ, Peake L, Johnson MM, Ghori S, Mott A et al. Beta-lactamase-mediated beta-lactam resistance in Campylobacter species: prevalence of Cj0299 (bla OXA-61) and evidence for a novel beta-Lactamase in C. jejuni. Antimicrob Agents Chemother 2009; 53:3357–3364 [View Article] [PubMed]
     [Google Scholar]
  66. Connell SR. Mechanism of Tet(O)-mediated tetracycline resistance. EMBO J 2003; 22:945–953 [View Article]
     [Google Scholar]
  67. Hormeño L, Campos MJ, Vadillo S, Quesada A. Occurrence of tet(O/M/O) mosaic gene in tetracycline-resistant campylobacter. Microorganisms 2020; 8:1710 [View Article]
     [Google Scholar]
  68. Shaw KJ, Rather PN, Hare RS, Miller GH. Molecular genetics of aminoglycoside resistance genes and familial relationships of the aminoglycoside-modifying enzymes. Microbiol Rev 1993; 57:138–163 [View Article] [PubMed]
     [Google Scholar]
  69. Jacob J, Evers S, Bischoff K, Carlier C, Courvalin P. Characterization of the sat4 gene encoding a streptothricin acetyltransferase in Campylobacter coli BE/G4. FEMS Microbiol Lett 1994; 120:13–17 [View Article] [PubMed]
     [Google Scholar]
  70. Wang L, Jeon B, Sahin O, Zhang Q. Identification of an arsenic resistance and arsenic-sensing system in Campylobacter jejuni. Appl Environ Microbiol 2009; 75:5064–5073 [View Article] [PubMed]
     [Google Scholar]
  71. Hakanen A, Jalava J, Kotilainen P, Jousimies-Somer H, Siitonen A et al. gyrA polymorphism in Campylobacter jejuni: detection of gyrA mutations in 162 C. jejuni isolates by single-strand conformation polymorphism and DNA sequencing. Antimicrob Agents Chemother 2002; 46:2644–2647 [View Article] [PubMed]
     [Google Scholar]
  72. Gibreel A, Kos VN, Keelan M, Trieber CA, Levesque S et al. Macrolide resistance in Campylobacter jejuni and Campylobacter coli: molecular mechanism and stability of the resistance phenotype. Antimicrob Agents Chemother 2005; 49:2753–2759 [View Article] [PubMed]
     [Google Scholar]
  73. Cagliero C, Mouline C, Cloeckaert A, Payot S. Synergy between efflux pump CmeABC and modifications in ribosomal proteins L4 and L22 in conferring macrolide resistance in Campylobacter jejuni and Campylobacter coli. Antimicrob Agents Chemother 2006; 50:3893–3896 [View Article] [PubMed]
     [Google Scholar]
  74. Abreau JC. Chapters of Brazil’s Colonial History, 1500-1800 New York, NY, USA: Oxford University Press; 1997
     [Google Scholar]
  75. Costa MA da, Rios FJ. The gold mining industry in Brazil: a historical overview. Ore Geol Rev 2022; 148:105005 [View Article]
     [Google Scholar]
  76. Calland JK, Pascoe B, Bayliss SC, Mourkas E, Berthenet E et al. Quantifying bacterial evolution in the wild: a birthday problem for Campylobacter lineages. PLoS Genet 2021; 17:e1009829 [View Article] [PubMed]
     [Google Scholar]
  77. de Fátima Rauber Würfel S, Jorge S, de Oliveira NR, Kremer FS, Sanchez CD et al. Campylobacter jejuni isolated from poultry meat in Brazil: in silico analysis and genomic features of two strains with different phenotypes of antimicrobial susceptibility. Mol Biol Rep 2020; 47:671–681 [View Article] [PubMed]
     [Google Scholar]
  78. Frazão MR, Cao G, Medeiros MIC, Duque S da S, Allard MW et al. Antimicrobial resistance profiles and phylogenetic analysis of Campylobacter jejuni strains isolated in Brazil by whole genome sequencing. Microb Drug Resist 2021; 27:660–669 [View Article] [PubMed]
     [Google Scholar]
  79. Gomes CN, Barker DOR, Duque S da S, Che EV, Jayamanna V et al. Campylobacter coli isolated in Brazil typed by core genome multilocus sequence typing shows high genomic diversity in a global context. Infect Genet Evol 2021; 95:105018 [View Article] [PubMed]
     [Google Scholar]
  80. Morita D, Arai H, Isobe J, Maenishi E, Kumagai T et al. Whole-genome and plasmid comparative analysis of Campylobacter jejuni from human patients in Toyama, Japan, from 2015 to 2019. Microbiol Spectr 2023; 11:e0265922 [View Article] [PubMed]
     [Google Scholar]
  81. Sheppard SK, Colles F, Richardson J, Cody AJ, Elson R et al. Host association of Campylobacter genotypes transcends geographic variation. Appl Environ Microbiol 2010; 76:5269–5277 [View Article] [PubMed]
     [Google Scholar]
  82. Sheppard SK, Cheng L, Méric G, de Haan CPA, Llarena A-K et al. Cryptic ecology among host generalist Campylobacter jejuni in domestic animals. Mol Ecol 2014; 23:2442–2451 [View Article] [PubMed]
     [Google Scholar]
  83. Dearlove BL, Cody AJ, Pascoe B, Méric G, Wilson DJ et al. Rapid host switching in generalist Campylobacter strains erodes the signal for tracing human infections. ISME J 2016; 10:721–729 [View Article] [PubMed]
     [Google Scholar]
  84. Wieczorek K, Wołkowicz T, Osek J. MLST-based genetic relatedness of Campylobacter jejuni isolated from chickens and humans in Poland. PLoS One 2020; 15:e0226238 [View Article] [PubMed]
     [Google Scholar]
  85. Mäesaar M, Meremäe K, Ivanova M, Roasto M. Antimicrobial resistance and multilocus sequence types of Campylobacter jejuni isolated from Baltic broiler chicken meat and Estonian human patients. Poult Sci 2018; 97:3645–3651 [View Article] [PubMed]
     [Google Scholar]
  86. Rokney A, Valinsky L, Moran-Gilad J, Vranckx K, Agmon V et al. Genomic epidemiology of Campylobacter jejuni transmission in Israel. Front Microbiol 2018; 9:2432 [View Article] [PubMed]
     [Google Scholar]
  87. Ngulukun S, Oboegbulem S, Klein G. Multilocus sequence typing of Campylobacter jejuni and Campylobacter coli isolates from poultry, cattle and humans in Nigeria. J Appl Microbiol 2016; 121:561–568 [View Article] [PubMed]
     [Google Scholar]
  88. Zhang G, Zhang X, Hu Y, Jiao X-A, Huang J. Multilocus sequence types of Campylobacter jejuni isolates from different sources in eastern China. Curr Microbiol 2015; 71:341–346 [View Article] [PubMed]
     [Google Scholar]
  89. Hull DM, Harrell E, van Vliet AHM, Correa M, Thakur S. Antimicrobial resistance and interspecies gene transfer in Campylobacter coli and Campylobacter jejuni isolated from food animals, poultry processing, and retail meat in North Carolina, 2018-2019. PLoS One 2021; 16:e0246571 [View Article] [PubMed]
     [Google Scholar]
  90. Stevens MJA, Stephan R, Horlbog JA, Cernela N, Nüesch-Inderbinen M. Whole genome sequence-based characterization of Campylobacter isolated from broiler carcasses over a three-year period in a big poultry slaughterhouse reveals high genetic diversity and a recurring genomic lineage of Campylobacter jejuni. Infect Genet Evol 2024; 119:105578 [View Article] [PubMed]
     [Google Scholar]
  91. Prendergast DM, Lynch H, Whyte P, Golden O, Murphy D et al. Genomic diversity, virulence and source of Campylobacter jejuni contamination in Irish poultry slaughterhouses by whole genome sequencing. J Appl Microbiol 2022; 133:3150–3160 [View Article] [PubMed]
     [Google Scholar]
  92. Davis MF, Kamel F, Hoppin JA, Alavanja MCR, Freeman LB et al. Neurologic symptoms associated with raising poultry and swine among participants in the Agricultural Health Study. J Occup Environ Med 2011; 53:190–195 [View Article] [PubMed]
     [Google Scholar]
  93. Vegosen L, Breysse PN, Agnew J, Gray GC, Nachamkin I et al. Occupational exposure to swine, poultry, and cattle and antibody biomarkers of Campylobacter jejuni exposure and autoimmune peripheral neuropathy. PLoS One 2015; 10:e0143587 [View Article] [PubMed]
     [Google Scholar]
  94. Kim S-H, Choi S-I, Song K-H, Seo K-W. Two cases of acute polyradiculoneuritis in dogs consuming a raw poultry diet. J Vet Med Sci 2021; 83:465–468 [View Article] [PubMed]
     [Google Scholar]
  95. Li CY, Xue P, Tian WQ, Liu RC, Yang C. Experimental Campylobacter jejuni infection in the chicken: an animal model of axonal Guillain-Barré syndrome. J Neurol Neurosurg Psychiatry 1996; 61:279–284 [View Article] [PubMed]
     [Google Scholar]
  96. Nyati KK, Prasad KN, Kharwar NK, Soni P, Husain N et al. Immunopathology and Th1/Th2 immune response of Campylobacter jejuni-induced paralysis resembling Guillain-Barré syndrome in chicken. Med Microbiol Immunol 2012; 201:177–187 [View Article] [PubMed]
     [Google Scholar]
  97. Furtado C. Formação Econômica Do Brasil São Paulo: Brasil: Companhia Editora Nacional; 2005
     [Google Scholar]
  98. Prescott JF. History of antimicrobial usage in agriculture: an overview. In Antimicrobial Resistance in Bacteria of Animal Origin John Wiley & Sons, Ltd; pp 19–27 [View Article]
     [Google Scholar]
  99. Rabello RF, Bonelli RR, Penna BA, Albuquerque JP, Souza RM et al. Antimicrobial resistance in farm animals in Brazil: an update overview. Animals 2020; 10:552 [View Article] [PubMed]
     [Google Scholar]
  100. Mourkas E, Taylor AJ, Méric G, Bayliss SC, Pascoe B et al. Agricultural intensification and the evolution of host specialism in the enteric pathogen Campylobacter jejuni. Proc Natl Acad Sci U S A 2020; 117:11018–11028 [View Article] [PubMed]
     [Google Scholar]
  101. Murray GGR, Hossain ASMM, Miller EL, Bruchmann S, Balmer AJ et al. The emergence and diversification of a zoonotic pathogen from within the microbiota of intensively farmed pigs. Proc Natl Acad Sci U S A 2023; 120:e2307773120 [View Article] [PubMed]
     [Google Scholar]
  102. Yebra G, Harling-Lee JD, Lycett S, Aarestrup FM, Larsen G et al. Multiclonal human origin and global expansion of an endemic bacterial pathogen of livestock. Proc Natl Acad Sci U S A 2022; 119:e2211217119 [View Article] [PubMed]
     [Google Scholar]
  103. Bronowski C, James CE, Winstanley C. Role of environmental survival in transmission of Campylobacter jejuni. FEMS Microbiol Lett 2014; 356:8–19 [View Article] [PubMed]
     [Google Scholar]
  104. Zinsstag J, Schelling E, Waltner-Toews D, Tanner M. From “one medicine” to “one health” and systemic approaches to health and well-being. Prev Vet Med 2011; 101:148–156 [View Article] [PubMed]
     [Google Scholar]
/content/journal/mgen/10.1099/mgen.0.001274
Loading
Five centuries of genome evolution and multi-host adaptation of Campylobacter jejuni in Brazil
M Gen 10, 001274 (2024); https://doi.org/10.1099/mgen.0.001274
/content/journal/mgen/10.1099/mgen.0.001274
/content/journal/mgen/10.1099/mgen.0.001274
Loading

Data & Media loading...

Supplements

Supplementary material 1

PDF

Supplementary material 2

EXCEL

Most cited Most Cited RSS feed

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