1887

Abstract

serovar Infantis is the fifth most common serovar isolated in England and Wales. Epidemiological, genotyping and antimicrobial-resistance data for . Infantis isolates were used to analyse English and Welsh demographics over a 5 year period. Travel cases associated with . Infantis were mainly from Asia, followed by cases from Europe and North America. Since 2000, increasing numbers of . Infantis had multidrug resistance determinants harboured on a large plasmid termed ‘plasmid of emerging . Infantis’ (pESI). Between 2013 and 2018, 42 . Infantis isolates were isolated from humans and food that harboured resistance determinants to multiple antimicrobial classes present on a pESI-like plasmid, including extended-spectrum β-lactamases (ESBLs; ). Nanopore sequencing of an ESBL-producing human . Infantis isolate indicated the presence of two regions on an IncFIB pESI-like plasmid harbouring multiple resistance genes. Phylogenetic analysis of the English and Welsh . Infantis population indicated that the majority of multidrug-resistant isolates harbouring the pESI-like plasmid belonged to a single clade maintained within the population. The ESBL isolates first isolated in 2013 comprise a lineage within this clade, which was mainly associated with South America. Our data, therefore, show the emergence of a stable resistant clone that has been in circulation for some time in the human population in England and Wales, highlighting the necessity of monitoring resistance in this serovar.

  • 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/mgen/10.1099/mgen.0.000658
2021-10-14
2021-10-24
Loading full text...

Full text loading...

/deliver/fulltext/mgen/7/10/mgen000658.html?itemId=/content/journal/mgen/10.1099/mgen.0.000658&mimeType=html&fmt=ahah

References

  1. Majowicz SE, Musto J, Scallan E, Angulo FJ, Kirk M et al. The global burden of nontyphoidal Salmonella gastroenteritis. Clin Infect Dis 2010; 50:882–889 [View Article] [PubMed]
    [Google Scholar]
  2. European Food Safety Authority (EFSA)European Centre for Disease Prevention and Control (ECDC) The European Union summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in 2015/2016. EFSA Journal 2016; 14:4634
    [Google Scholar]
  3. Chattaway MA, Dallman TJ, Larkin L, Nair S, McCormick J et al. The transformation of reference microbiology methods and surveillance for Salmonella with the use of whole genome sequencing in England and Wales. Front Public Health 2019; 7:317 [View Article] [PubMed]
    [Google Scholar]
  4. Franco A, Leekitcharoenphon P, Feltrin F, Alba P, Cordaro G et al. Emergence of a clonal lineage of multi-drug resistant ESBL producing Salmonella Infantis transmitted from broilers and broiler meat to humans in Italy between 2011 and 2014. PLoS One 2015; 10:e0144802
    [Google Scholar]
  5. Tate H, Folster JP, Hsu C-H, Chen J, Hoffmann M et al. Comparative analysis of extended-spectrum-β-lactamase CTX-M-65-producing Salmonella enterica Infantis isolates from humans, food animals, and retail chickens in the United States. Antimicrob Agents Chemother 2017; 61:e00488-17
    [Google Scholar]
  6. European Food Safety Authority (EFSA)European Centre for Disease Prevention and Control (ECDC) The European Union summary report on antimicrobial resistance in zoonotic and indicator bacteria from humans, animals and food in 2017/2018. EFSA Journal 2020; 18:6007
    [Google Scholar]
  7. Nόgrády N, Király M, Davies R, Nagy B. Multidrug resistant clones of Salmonella Infantis of broiled origin in Europe. Int J Food Microbiol 2012; 157:108–112 [View Article] [PubMed]
    [Google Scholar]
  8. Alba P, Leekitcharoenphon P, Carfora V, Amoruso R, Cordaro G et al. Molecular epidemiology of Salmonella Infantis in Europe: insights into the success of the bacterial host and its parasitic pESI-like megaplasmid. Microb Genom 2020; 6:e000365 [View Article]
    [Google Scholar]
  9. Aviv G, Tsyba K, Steck N, Salmon-Divon M, Cornelius A et al. A unique megaplasmid contributes to stress tolerance and pathogencity of an emergent Salmonella enterica serovar Infantis strain. Environ Microbiol 2014; 16:977–994 [View Article] [PubMed]
    [Google Scholar]
  10. Granda A, Riveros M, Martínez-Puchol S, Ocampo K, Laureano-Adame L et al. Presence of extended-spectrum β-lactamase, CTX-M-65 in Salmonella enterica serovar Infantis isolated from children with diarrhea in Lima, Peru. J Pediatr Infect Dis 2019; 14:194–200 [View Article]
    [Google Scholar]
  11. Cartelle Gestal M, Zurita J, Paz Y Mino A, Ortega-Paredes D, Alcocer I. Characterization of a small outbreak of Salmonella enterica serovar Infantis that harbour CTX-M-65 in Ecuador. Braz J Infect Dis 2016; 20:406–407 [View Article]
    [Google Scholar]
  12. Ashton PM, Nair S, Peters T, Bale J, Powell D et al. Identification of Salmonella for public health surveillance using whole genome sequencing. PeerJ 2016; 4:e1752 [View Article]
    [Google Scholar]
  13. McDermott F, Tyson H, Kabera C, Chen Y, Li C et al. Whole-genome sequencing for detecting antimicrobial resistance in non-typhoidal Salmonella. Antimicrob Agents Chemother 2016; 60:5515–5520 [View Article]
    [Google Scholar]
  14. Nair S, Ashton P, Doumith M, Connell S, Painset A et al. WGS for surveillance of antimicrobial resistance: a pilot study to detect the prevalence and mechanism of resistance to azithromycin in a UK population of non-typhoidal Salmonella. J Antimicrob Chemother 2016; 71:3400–3408 [View Article]
    [Google Scholar]
  15. Mejia L, Medina JL, Bayas R, Salazar CS, Villavicencio F et al. Genomic epidemiology of Salmonella Infantis in Ecuador: from poultry farms to human infections. Front Vet Sci 2020; 7:547891 [View Article]
    [Google Scholar]
  16. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 2014; 30:2114–2120 [View Article]
    [Google Scholar]
  17. Rasheed F, Saeed M, Alikahn NF, Baker D, Khurshid M et al. Emergence of resistance to fluoroquinolones and third-generation cephalosporins in Salmonella Typhi in Lahore, Pakistan. Microorganisms 2020; 8:1336
    [Google Scholar]
  18. Connor TR, Loman NJ, Thompson S, Smith A, Southgate J et al. CLIMB (the Cloud Infrastructure for Microbial Bioinformatics): an online resource for the medical microbiology community. Microb Genom 2016; 2:e000086 [View Article]
    [Google Scholar]
  19. Tewolde R, Dallman T, Schaefer U, Sheppard CL, Ashton P et al. MOST: a modified MLST typing tool based on short read sequencing. PeerJ 2016; 4:e2308 [View Article] [PubMed]
    [Google Scholar]
  20. Achtman M, Wain J, Weill F-X, Nair S, Zhou Z et al. Multilocus sequence typing as a replacement for serotyping in Salmonella enterica. PLoS Pathog 2012; 8:e1002776 [View Article]
    [Google Scholar]
  21. Carattoli A, Zankari E, Garcıa-Fernandez A, Voldby Larsen M, Lund O et al. In silico detection and typing of plasmids using PlasmidFinder and plasmid multilocus sequence typing. Antimicrob Agents Chemother 2014; 58:3895–3903 [View Article] [PubMed]
    [Google Scholar]
  22. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods 2012; 9:357–359 [View Article]
    [Google Scholar]
  23. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 2009; 25:2078–2079 [View Article] [PubMed]
    [Google Scholar]
  24. Day MR, Doumith M, Do Nascimento V, Nair S, Ashton PM et al. Comparison of phenotypic and WGS-derived antimicrobial resistance profiles of Salmonella enterica serovars Typhi and Paratyphi. J Antimicrob Chemother 2018; 73:365–372 [View Article] [PubMed]
    [Google Scholar]
  25. Day M, Doumith M, Jenkins C, Dallman TJ, Hopkins KL et al. Antimicrobial resistance in Shiga toxin-producing Escherichia coli serogroups O157 and O26 isolated from human cases of diarrhoeal disease in England, 2015. J Antimicrob Chemother 2017; 72:145–152 [View Article] [PubMed]
    [Google Scholar]
  26. Sadouki Z, Day MR, Doumith M, Chattaway MA, Dallman TJ et al. Comparison of phenotypic and WGS-derived antimicrobial resistance profiles of Shigella sonnei isolated from cases of diarrhoeal disease in England and Wales, 2015. J Antimicrob Chemother 2017; 72:2496–2502 [View Article] [PubMed]
    [Google Scholar]
  27. Hunt M, Mather AE, Sánchez-Busó L, Page AJ, Parkhill J et al. ARIBA: rapid antimicrobial resistance genotyping directly from sequencing reads. Microb Genom 2017; 3:e000131 [View Article]
    [Google Scholar]
  28. Koren S, Walenz BP, Berlin K, Miller JR, Bergman NH et al. CANU: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res 2017; 27:722–736 [View Article]
    [Google Scholar]
  29. Li H, Durbin R. Fast and accurate long-read alignment with Burrows–Wheeler transform. Bioinformatics 2010; 26:589–595 [View Article] [PubMed]
    [Google Scholar]
  30. Vaser R, Sović I, Nagarajan N, Šikić M. Fast and accurate de novo genome assembly from long uncorrected reads. Genome Res 2017; 27:737–746 [View Article] [PubMed]
    [Google Scholar]
  31. 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] [PubMed]
    [Google Scholar]
  32. Wick RR. Porechop; 2017 https://github.com/rrwick/Porechop
  33. Wick RR. Filtlong; 2017 https://github.com/rrwick/Filtlong
  34. Kolmogorov M, Yuan J, Lin Y, Pevzner PA. Assembly of long, error-prone reads using repeat graphs. Nat Biotechnol 2019; 37:540–546 [View Article] [PubMed]
    [Google Scholar]
  35. Yara DA, Greig DR, Gally DL, Dallman TJ, Jenkins C. Comparison of Shiga toxin-encoding bacteriophages in highly pathogenic strains of Shiga toxin-producing Escherichia coli O157:H7 in the UK. Microb Genom 2020; 6:e000334 [View Article]
    [Google Scholar]
  36. Loman NJ, Quick J, Simpson JT. A complete bacterial genome assembled de novo using only nanopore sequencing data. Nat Methods 2015; 12:733–735 [View Article] [PubMed]
    [Google Scholar]
  37. Wicks RR, Schultz MB, Zobel J, Holt KE. Bandage: interactive visualisation of de novo genome assemblies. Bioinformatics 2015; 31:3350–3352 [View Article] [PubMed]
    [Google Scholar]
  38. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 2014; 30:2068–2069 [View Article] [PubMed]
    [Google Scholar]
  39. Rutherford K, Parkhill J, Crook J, Horsnell T, Rice P et al. Artemis: sequence visualization and annotation. Bioinformatics 2000; 16:944–945 [View Article]
    [Google Scholar]
  40. Sullivan MJ, Petty NK, Beatson SA. Easyfig: a genome comparison visualizer. Bioinformatics 2011; 27:1009–1010 [View Article]
    [Google Scholar]
  41. Alikhan N-F, Petty NK, Ben Zakour NL, Beatson SA. BLAST Ring Image Generator (BRIG): simple prokaryote genome comparisons. BMC Genomics 2011; 12:402 [View Article] [PubMed]
    [Google Scholar]
  42. Revell LJ. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol Evol 2012; 3:217–223 [View Article]
    [Google Scholar]
  43. Dowle M, Srinivasan A. Data.table; 2018 https://github.com/Rdatatable/data.table/wiki
  44. Paradis E, Schliep K. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 2019; 35:526–528 [View Article]
    [Google Scholar]
  45. R Core Team R: a Language and Environment for Statistical Computing Vienna: R Foundation for Statistical Computing; 2018
    [Google Scholar]
  46. Dallman T, Ashton P, Schafer U, Jironkin A, Painset A et al. SnapperDB: a database solution for routine sequencing analysis of bacterial isolates. Bioinformatics 2018; 34:3028–3029 [View Article]
    [Google Scholar]
  47. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K et al. The Genome Analysis Toolkit: a MapReduce frame-work for analyzing next-generation DNA sequencing data. Genome Res 2010; 20:1297–1303 [View Article]
    [Google Scholar]
  48. 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]
  49. Arndt D, Grant JR, Marcu A, Sajed T, Pon A et al. PHASTER: a better, faster version of the PHAST phage search tool. Nucleic Acids Res 2016; 44:W16–W21
    [Google Scholar]
  50. Stamatakis A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 2014; 30:1312–1313 [View Article]
    [Google Scholar]
  51. Letunic I, Bork P. Interactive Tree Of Life (iTOL) v4: recent updates and new developments. Nucleic Acids Res 2019; 47:W256–W259 [View Article]
    [Google Scholar]
  52. Rambaut A, Drummond AJ. Figtree; 2018 https://github.com/rambaut/figtree
  53. 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] [PubMed]
    [Google Scholar]
  54. Kumar S, Stecher G, Tamura K. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol 2016; 33:1870–1874 [View Article]
    [Google Scholar]
  55. European Food Safety Authority (EFSA) The community summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in the European Union in 2008. EFSA J 2010; 8:1496
    [Google Scholar]
  56. Gal-Mor O, Valinsky L, Weinberger M, Guy S, Jaffe J et al. Multidrug-resistant Salmonella enterica serovar Infantis, Israel. Emerg Infect Dis 2010; 16:1754–1757 [View Article] [PubMed]
    [Google Scholar]
  57. Mendonça EP, Melo RT, Oliveira MRM, Monteiro GP, Peres PABM et al. Characteristics of virulence, resistance and genetic diversity of strains of Salmonella Infantis isolated from broiler chicken in Brazil. Pesq Vet Bras 2020; 40:29–38 [View Article]
    [Google Scholar]
  58. Mejia L, Vela G, Zapata S. High occurrence of multiresistant Salmonella Infantis in retail meat in Ecuador. Foodborne Pathog Dis 2021; 18:41–48 [View Article]
    [Google Scholar]
  59. Brown AC, Chen JC, Watkins LKF, Campbell D, Folster JP et al. CTX-M-65 extended-spectrum β-lactamase–producing Salmonella enterica serotype Infantis, United States. Emerg Infect Dis 2018; 24:2284–2291 [View Article]
    [Google Scholar]
  60. Burke L, Hopkins KL, Meunier D, de Pinna E, Fitzgerald-Hughes D et al. Resistance to third-generation cephalosporins in human non-typhoidal Salmonella enterica isolates from England and Wales, 2010-12. J Antimicrob Chemother 2014; 69:977–981 [View Article]
    [Google Scholar]
  61. Patel SS, Balfour JA, Bryson HM. Fosfomycin tromethamine: a review of its antibacterial activity, pharmacokinetic properties and therapeutic efficacy as a single-dose oral treatment for acute uncomplicated lower urinary tract infections. Drugs 1997; 53:637–656 [View Article] [PubMed]
    [Google Scholar]
  62. Argudín MA, Hoefer A, Butaye P. Heavy metal resistance in bacteria from animals. Res Vet Sci 2019; 122:132–147 [View Article] [PubMed]
    [Google Scholar]
  63. Hobman J, Crosman L. Bacterial antimicrobial metal ion resistance. J Med Microbiol 2014; 64:471–497 [View Article] [PubMed]
    [Google Scholar]
  64. Gilmour MW, Thomson NR, Sanders M, Parkhill J, Taylor DE. The complete nucleotide sequence of the resistance plasmid R478: defining the backbone components of incompatibility group H conjugative plasmids through comparative genomics. Plasmid 2004; 52:182–202 [View Article]
    [Google Scholar]
  65. Van Melderen L. Toxin-antitoxin systems: why so many, what for. Curr Opin Microbiol 2010; 13:781–785 [View Article] [PubMed]
    [Google Scholar]
  66. Riccobono E, Di Pilato V, Di Maggio T, Revollo C, Bartoloni A et al. Characterization of IncI1 sequence type 71 epidemic plasmid lineage responsible for the recent dissemination of CTX-M-65 extended-spectrum β-lactamase in the Bolivian Chaco region. Antimicrob Agents Chemother 2015; 59:5340–5347 [View Article] [PubMed]
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/mgen/10.1099/mgen.0.000658
Loading
/content/journal/mgen/10.1099/mgen.0.000658
Loading

Data & Media loading...

Supplements

Loading data from figshare Loading data from figshare

Most cited this month 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