1887

Microbial Genomics logo

Volume 6, Issue 3

Using genomics to understand inter- and intra- outbreak diversity of isolates associated with fowl cholera in meat chickens Open Access

Abstract

Fowl cholera, caused by continues to be a challenge in meat-chicken-breeder operations and has emerged as a problem for free-range meat chickens. Here, using whole-genome sequencing (WGS) and phylogenomic analysis, we investigate isolate relatedness during outbreaks of fowl cholera on a free-range meat chicken farm over a 5-year period. Our genomic analysis revealed that while all outbreak isolates were sequence type (ST) 20, they could be separated into two distinct clades (clade 1 and clade 2) consistent with difference in their lipopolysaccharide (LPS) type. The isolates from the earlier outbreaks (clade 1) were carrying LPS type L3 while those from the more recent outbreaks (clade 2) were LPS type L1. Additionally, WGS data indicated high inter- and intra-chicken genetic diversity during a single outbreak. Furthermore, we demonstrate that while a killed autogenous vaccine carrying LPS type L3 had been successful in protecting against challenge from L3 isolates it might have driven the emergence of the closely related clade 2, against which the vaccine was ineffective. The genomic results also revealed a 14 bp deletion in the galactosyltransferase gene in LPS type L3 isolates, which would result in producing a semi-truncated LPS in those isolates. In conclusion, our study clearly demonstrates the advantages of genomic analysis over the conventional PCR-based approaches in providing clear insights in terms of linkage of isolate within and between outbreaks. More importantly, it provides more detailed information than the multiplex PCR on the possible structure of outer LPS, which is very important in the case of strain selection for killed autogenous vaccines.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): fowl cholera , lipopolysaccharides , Pasteurella multocida , phylogeny and whole-genome sequencing
Funding
This study was supported by the:
  • Australian Eggs, http://dx.doi.org/10.13039/501100009313 (Award PRJ-010276)
  • Agrifutures Australia, http://dx.doi.org/10.13039/501100009207 (Award PRJ-010276)
© 2020 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution NonCommercial License.
Loading

Article metrics loading...

/content/journal/mgen/10.1099/mgen.0.000346
2020-03-02
2024-04-16
Loading full text...

Full text loading...

/deliver/fulltext/mgen/6/3/mgen000346.html?itemId=/content/journal/mgen/10.1099/mgen.0.000346&mimeType=html&fmt=ahah

References

  1. Blackall PJ, Norskov-Lauritsen N. Pasteurellaceae - the view from the diagnostic laboratory. In Kuhnerts P, Christensen H. (editors) Pasteurellaceae: Biology, Genomics and Molecular Aspects Norwich, UK: Horizon Scientific Press; 2008 pp 227–260
     [Google Scholar]
  2. Hunt ML, Adler B, Townsend KM. The molecular biology of Pasteurella multocida . Vet Microbiol 2000; 72:3–25 [View Article]
     [Google Scholar]
  3. Crawford RL, Blyde D, Blackall PJ, Forde BM, Beatson SA et al. Novel insights into pasteurellosis in captive pinnipeds. Vet Microbiol 2019; 231:232–237 [View Article]
     [Google Scholar]
  4. Omaleki L, Beatson SA, Thomrongsuwannakij T, Blackall PJ, Buller N et al. Phase variation in latB gene associated with a fatal Pasteurella multocida outbreak in captive squirrel gliders. . 2019
     [Google Scholar]
  5. Singh R, Blackall PJ, Remington B, Turni C. Studies on the presence and persistence of Pasteurella multocida serovars and genotypes in fowl cholera outbreaks. Avian Pathol 2013; 42:581–585 [View Article]
     [Google Scholar]
  6. Singh R, Remington B, Blackall P, Turni C. Epidemiology of fowl cholera in free range broilers. Avian Dis 2014; 58:124–128 [View Article]
     [Google Scholar]
  7. Christensen JP, Dietz HH, Bisgaard M. Phenotypic and genotypic characters of isolates of Pasteurella multocida obtained from back-yard poultry and from two outbreaks of avian cholera in avifauna in Denmark. Avian Pathol 1998; 27:373–381 [View Article]
     [Google Scholar]
  8. Brogden KA, Rhoades KR, Heddleston KL. A new serotype of Pasteurella multocida associated with fowl cholera. Avian Dis 1978; 22:185–-90 [View Article]
     [Google Scholar]
  9. Heddleston KL, Gallagher JE, Rebers PA. Fowl cholera: gel diffusion precipitin test for serotyping Pasteruella multocida from avian species. Avian Dis 1972; 16:925–936 [View Article]
     [Google Scholar]
  10. Harper M, John M, Turni C, Edmunds M, St Michael F et al. Development of a rapid multiplex PCR assay to genotype Pasteurella multocida strains by use of the lipopolysaccharide outer core biosynthesis locus. J Clin Microbiol 2015; 53:477–485 [View Article]
     [Google Scholar]
  11. Turni C, Singh R, Blackall PJ. Genotypic diversity of Pasteurella multocida isolates from pigs and poultry in Australia. Aust Vet J 2018; 96:390–394 [View Article]
     [Google Scholar]
  12. Harper M, John M, Edmunds M, Wright A, Ford M et al. Protective efficacy afforded by live Pasteurella multocida vaccines in chickens is independent of lipopolysaccharide outer core structure. Vaccine 2016; 34:1696–1703 [View Article]
     [Google Scholar]
  13. Harper M, Boyce JD. The properties of Pasteurella multocida lipopolysaccharide. Toxins 2017; 9:E254 [View Article]
     [Google Scholar]
  14. Bartley PB, Ben Zakour NL, Stanton-Cook M, Muguli R, Prado L et al. Hospital-wide eradication of a nosocomial Legionella pneumophila serogroup 1 outbreak. Clin Infect Dis 2016; 62:273–279 [View Article]
     [Google Scholar]
  15. Quainoo S, Coolen JPM, van Hijum SAFT, Huynen MA, Melchers WJG et al. Whole-Genome sequencing of bacterial pathogens: the future of nosocomial outbreak analysis. Clin Microbiol Rev 2017; 30:1015–1063 [View Article]
     [Google Scholar]
  16. Pijnacker R, Dallman TJ, Tijsma ASL, Hawkins G, Larkin L et al. An international outbreak of Salmonella enterica serotype Enteritidis linked to eggs from Poland: a microbiological and epidemiological study. Lancet Infect Dis 2019; 19:778–786 [View Article]
     [Google Scholar]
  17. Stanczak-Mrozek KI, Manne A, Knight GM, Gould K, Witney AA et al. Within-Host diversity of MRSA antimicrobial resistances. J Antimicrob Chemother 2015; 70:2191–2198 [View Article]
     [Google Scholar]
  18. Harper M, St Michael F, John M, Vinogradov E, Steen JA et al. Pasteurella multocida Heddleston serovar 3 and 4 strains share a common lipopolysaccharide biosynthesis locus but display both inter- and intrastrain lipopolysaccharide heterogeneity. J Bacteriol 2013; 195:4854–4864 [View Article]
     [Google Scholar]
  19. Gunawardana GA, Townsend KM, Frost AJ. Molecular characterisation of avian Pasteurella multocida isolates from Australia and Vietnam by REP-PCR and PFGE. Vet Microbiol 2000; 72:97–109 [View Article]
     [Google Scholar]
  20. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 2014; 30:2114–2120 [View Article]
     [Google Scholar]
  21. Andrews S. FastQC: a quality control tool for high throughput sequence data 2010. [Available from: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/].
  22. 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]
  23. Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: quality assessment tool for genome assemblies. Bioinformatics 2013; 29:1072–1075 [View Article]
     [Google Scholar]
  24. Jolley KA, Chan M-S, Maiden MCJ. mlstdbNet - distributed multi-locus sequence typing (MLST) databases. BMC Bioinformatics 2004; 5:86 [View Article]
     [Google Scholar]
  25. Subaaharan S, Blackall LL, Blackall PJ. Development of a multi-locus sequence typing scheme for avian isolates of Pasteurella multocida . Vet Microbiol 2010; 141:354–361 [View Article]
     [Google Scholar]
  26. Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA et al. Clustal W and Clustal X version 2.0. Bioinformatics 2007; 23:2947–2948 [View Article]
     [Google Scholar]
  27. Harper M, Wright A, St Michael F, Li J, Deveson Lucas D et al. Characterization of two novel lipopolysaccharide phosphoethanolamine transferases in Pasteurella multocida and their role in resistance to Cathelicidin-2. Infect Immun 2017; 85: [View Article]
     [Google Scholar]
  28. Carver T, Harris SR, Berriman M, Parkhill J, McQuillan JA. Artemis: an integrated platform for visualization and analysis of high-throughput sequence-based experimental data. Bioinformatics 2012; 28:464–469 [View Article]
     [Google Scholar]
  29. Treangen TJ, Ondov BD, Koren S, Phillippy AM. The harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes. Genome Biol 2014; 15:524 [View Article]
     [Google Scholar]
  30. 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]
  31. 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]
  32. Nascimento M, Sousa A, Ramirez M, Francisco AP, Carriço JA et al. PHYLOViZ 2.0: providing scalable data integration and visualization for multiple phylogenetic inference methods. Bioinformatics 2017; 33:128–129 [View Article]
     [Google Scholar]
  33. Wang Y, Zhu J, Lu C, Wu B, Liu D et al. Evidence of circulation of an epidemic strain of Pasteurella multocida in Jiangsu, China by multi-locus sequence typing (MLST). Infect Genet Evol 2013; 20:34–38 [View Article]
     [Google Scholar]
  34. Sherrard LJ, Tai AS, Wee BA, Ramsay KA, Kidd TJ et al. Within-host whole genome analysis of an antibiotic resistant Pseudomonas aeruginosa strain sub-type in cystic fibrosis. PLoS One 2017; 12:e0172179 [View Article]
     [Google Scholar]
  35. Luo C, Knight R, Siljander H, Knip M, Xavier RJ et al. Constrains identifies microbial strains in metagenomic datasets. Nat Biotechnol 2015; 33:1045–1052 [View Article]
     [Google Scholar]
  36. Oh J, Byrd AL, Deming C, Conlan S, Kong HH, Barnabas B et al. Biogeography and individuality shape function in the human skin metagenome. Nature 2014; 514:59–64 [View Article]
     [Google Scholar]
  37. Harper M, St Michael F, John M, Vinogradov E, Adler B et al. Pasteurella multocida Heddleston serovars 1 and 14 express different lipopolysaccharide structures but share the same lipopolysaccharide biosynthesis outer core locus. Vet Microbiol 2011; 150:289–296 [View Article]
     [Google Scholar]
  38. Walker MJ, Beatson SA, Outbreaks O. Epidemiology outsmarting outbreaks. Science 2012; 338:1161–1162 [View Article]
     [Google Scholar]
  39. Brown E, Dessai U, McGarry S, Gerner-Smidt P. Use of whole-genome sequencing for food safety and public health in the United States. Foodborne Pathog Dis 2019; 16:441–450 [View Article]
     [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/mgen/10.1099/mgen.0.000346
Loading
Using genomics to understand inter- and intra- outbreak diversity of Pasteurella multocida isolates associated with fowl cholera in meat chickens
M Gen 6, e000346 (2020); https://doi.org/10.1099/mgen.0.000346
/content/journal/mgen/10.1099/mgen.0.000346
/content/journal/mgen/10.1099/mgen.0.000346
Loading

Data & Media loading...

Supplements

Supplementary material 1

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