1887

Access Microbiology open research platform logo

Volume 1, Issue 2

Application of whole genome sequencing to query a potential outbreak of Elizabethkingia anophelis in Ontario, Canada Open Access

Abstract

Bioinformatic analysis of whole genome sequence (WGS) data is emerging as a tool to provide powerful insights for clinical microbiology. We used WGS data to investigate the genetic diversity of clinical isolates of the bacterial pathogen Elizabethkingia anophelis to query the existence of a single-strain outbreak in Ontario, Canada. The Public Health Ontario Laboratory (PHOL) provides reference identification of clinical isolates of bacteria for Ontario and prior to 2016 had not identified E. anophelis . In the wake of the Wisconsin outbreak of 2015–2016 for which a source was never elucidated, the identification of E. anophelis from clinical specimens from five Ontario patients gave reason to question the presence of an outbreak. Genomic comparisons based on core genome multi-locus sequence typing conclusively refuted the existence of an outbreak, since the 5 Ontario isolates were genetically dissimilar, representing at least 3 distinct sub-lineages scattered among a set of 39 previously characterized isolates. Further interrogation of the genomic data revealed multiple antimicrobial resistance genes. Retrospective reidentification via rpoB sequence analysis of 22 clinical isolates of Elizabethkingia spp. collected by PHOL from 2010 to 2018 demonstrated that E. anophelis was isolated from clinical specimens as early as 2010. The uptick in E. anophelis in Ontario was not due to an outbreak or increased incidence of the pathogen, but rather enhanced laboratory identification techniques and improved sequence databases. This study demonstrates the usefulness of WGS analysis as a public health tool to quickly rule out the existence of clonally related case clusters of bacterial pathogens indicative of single-strain outbreaks.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): antimicrobial resistance , core genome MLST , Elizabethkingia anophelis , outbreak and whole genome sequence
© 2019 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Loading

Article metrics loading...

/content/journal/acmi/10.1099/acmi.0.000017
2019-04-24
2024-04-25
Loading full text...

Full text loading...

/deliver/fulltext/acmi/1/2/acmi000017.html?itemId=/content/journal/acmi/10.1099/acmi.0.000017&mimeType=html&fmt=ahah

References

  1. Bruun B, Bernardet J. Elizabethkingia. In Whitman WB. editor Bergey's Manual of Systematics of Archaea and Bacteria, [book on the Internet]. Athens, GA: Bergey's Manual Trust; 2015
     [Google Scholar]
  2. King EO. Studies on a group of previously unclassified bacteria associated with meningitis in infants. Am J Clin Pathol 1959; 31:241–247 [View Article]
     [Google Scholar]
  3. Nicholson AC, Gulvik CA, Whitney AM, Humrighouse BW, Graziano J et al. Revisiting the taxonomy of the genus Elizabethkingia using whole-genome sequencing, optical mapping, and MALDI-TOF, along with proposal of three novel Elizabethkingia species: Elizabethkingia bruuniana sp. nov., Elizabethkingia ursingii sp. nov., and Elizabethkingia occulta sp. nov. Antonie Van Leeuwenhoek 2018; 111:55–72 [View Article]
     [Google Scholar]
  4. Breurec S, Criscuolo A, Diancourt L, Rendueles O, Vandenbogaert M et al. Genomic epidemiology and global diversity of the emerging bacterial pathogen Elizabethkingia anophelis. Sci Rep 2016; 6:30379 [View Article]
     [Google Scholar]
  5. Jean SS, Lee WS, Chen FL, Ou TY, Hsueh PR. Elizabethkingia meningoseptica: an important emerging pathogen causing healthcare-associated infections. J Hosp Infect 2014; 86:244–249 [View Article]
     [Google Scholar]
  6. Perrin A, Larsonneur E, Nicholson AC, Edwards DJ, Gundlach KM et al. Evolutionary dynamics and genomic features of the Elizabethkingia anophelis 2015 to 2016 Wisconsin outbreak strain. Nat Commun 2017; 8:15483 [View Article]
     [Google Scholar]
  7. Balm MN, Salmon S, Jureen R, Teo C, Mahdi R et al. Bad design, bad practices, bad bugs: frustrations in controlling an outbreak of Elizabethkingia meningoseptica in intensive care units. J Hosp Infect 2013; 85:134–140 [View Article]
     [Google Scholar]
  8. Moore LS, Owens DS, Jepson A, Turton JF, Ashworth S et al. Waterborne Elizabethkingia meningoseptica in Adult Critical Care. Emerg Infect Dis 2016; 22:9–17 [View Article]
     [Google Scholar]
  9. Teo J, Tan SY, Liu Y, Tay M, Ding Y et al. Comparative genomic analysis of malaria mosquito vector-associated novel pathogen Elizabethkingia anophelis. Genome Biol Evol 2014; 6:1158–1165 [View Article]
     [Google Scholar]
  10. Lau SK, Chow WN, Foo CH, Curreem SO, Lo GC et al. Elizabethkingia anophelis bacteremia is associated with clinically significant infections and high mortality. Sci Rep 2016; 6:26045 [View Article]
     [Google Scholar]
  11. Han MS, Kim H, Lee Y, Kim M, Ku NS et al. Relative Prevalence and Antimicrobial Susceptibility of Clinical Isolates of Elizabethkingia Species Based on 16S rRNA Gene Sequencing. J Clin Microbiol 2017; 55:274–280 [View Article]
     [Google Scholar]
  12. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol 1990; 215:403–410 [View Article]
     [Google Scholar]
  13. Benson DA, Cavanaugh M, Clark K, Karsch-Mizrachi I, Ostell J et al. GenBank. Nucleic Acids Res 2018; 46:D41–D47 [View Article]
     [Google Scholar]
  14. CLSI Interpretive Criteria for Identification of Bacteria and fungi by DNA target sequencing, 2nd ed. CLSI document MM18-A Wayne, PA: Clinical and Laboratory Standards Institute; 2018
     [Google Scholar]
  15. 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]
  16. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 2014; 30:2068–2069 [View Article]
     [Google Scholar]
  17. HMMER HMMER: biosequence analysis using profile hidden Markov models v3.1b2. , [Internet]. New York: Howard Hughes Medical Institute; 2015
  18. Gibson MK, Forsberg KJ, Dantas G. Improved annotation of antibiotic resistance determinants reveals microbial resistomes cluster by ecology. ISME J 2015; 9:207–216 [View Article]
     [Google Scholar]
  19. Wattam AR, Abraham D, Dalay O, Disz TL, Driscoll T et al. PATRIC, the bacterial bioinformatics database and analysis resource. Nucleic Acids Res 2014; 42:D581–D591 [View Article]
     [Google Scholar]
  20. Aziz RK, Bartels D, Best AA, DeJongh M, Disz T et al. The RAST server: rapid annotations using subsystems technology. BMC Genomics 2008; 9:75 [View Article]
     [Google Scholar]
  21. Jia B, Raphenya AR, Alcock B, Waglechner N, Guo P et al. Card 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database. Nucleic Acids Res 2017; 45:D566–D573 [View Article]
     [Google Scholar]
  22. McArthur AG, Waglechner N, Nizam F, Yan A, Azad MA et al. The comprehensive antibiotic resistance database. Antimicrob Agents Chemother 2013; 57:3348–3357 [View Article]
     [Google Scholar]
  23. Weyant RS, Wayne C, Weaver RE, Hollis DG, Jordan JG et al. Identification of Unusual Pathogenic gram-negative aerobic and facultatively anaerobic bacteria Baltimore, MD: Williams & Wilkins; 1996; Flavobacterium meningosepticum and similar strains pp 348–349
     [Google Scholar]
  24. CLSI Methods for dilution antimicrobial susceptibility tests for bacteria that grow aerobically, 10th ed. CLSI document M07-A10 Wayne, PA: Clinical Laboratory Standards Institute; 2015
     [Google Scholar]
  25. CLSI Performance standards for antimicrobial susceptibility testing, 25th ed. CLSI document M100-S25 Wayne, PA: Clinical Laboratory Standards Institute; 2015
     [Google Scholar]
  26. Jean SS, Hsieh TC, Ning YZ, Hsueh PR. Role of vancomycin in the treatment of bacteraemia and meningitis caused by Elizabethkingia meningoseptica. Int J Antimicrob Agents 2017; 50:507–511 [View Article]
     [Google Scholar]
  27. Figueroa Castro CE, Johnson C, Williams M, VanDerSlik A, Graham MB et al. Elizabethkingia anophelis: clinical experience of an academic health system in Southeastern Wisconsin. Open Forum Infect Dis 2017; 4:ofx251 [View Article]
     [Google Scholar]
  28. Lin JN, Lai CH, Yang CH, Huang YH, Lin HH. Genomic features, phylogenetic relationships, and comparative genomics of Elizabethkingia anophelis strain EM361-97 isolated in Taiwan. Sci Rep 2017; 7:14317 [View Article]
     [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/acmi/10.1099/acmi.0.000017
Loading
Application of whole genome sequencing to query a potential outbreak of Elizabethkingia anophelis in Ontario, Canada
Access Microbiology 1, e000017 (2019); https://doi.org/10.1099/acmi.0.000017
/content/journal/acmi/10.1099/acmi.0.000017
/content/journal/acmi/10.1099/acmi.0.000017
Loading

Data & Media loading...

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