1887

Abstract

Fowl cholera caused by has re-emerged in Australian poultry production since the increasing adoption of free-range production systems. Currently, autogenous killed whole-cell vaccines prepared from the isolates previously obtained from each farm are the main preventative measures used. In this study, we use whole-genome sequencing and phylogenomic analysis to investigate outbreak dynamics, as well as monitoring and comparing the variations in the lipopolysaccharide (LPS) outer core biosynthesis loci of the outbreak and vaccine strains. In total, 73 isolates from two different free-range layer farms were included. Our genomic analysis revealed that all investigated isolates within the two farms (layer A and layer B) carried LPS type L3, albeit with a high degree of genetic diversity between them. Additionally, the isolates belonged to five different sequence types (STs), with isolates belonging to ST9 and ST20 being the most prevalent. The isolates carried ST-specific mutations within their LPS type L3 outer core biosynthesis loci, including frameshift mutations in the outer core heptosyltransferase gene () (ST7 and ST274) or galactosyltransferase gene () (ST20). The ST9 isolates could be separated into three groups based on their LPS outer core biosynthesis loci sequences, with evidence for potential phase variation mechanisms identified. The potential phase variation mechanisms included a tandem repeat insertion in and a single base deletion in a homopolymer region of . Importantly, our results demonstrated that two of the three ST9 groups shared identical rep-PCR (repetitive extragenic palindromic PCR) patterns, while carrying differences in their LPS outer core biosynthesis loci region. In addition, we found that ST9 isolates either with or without the tandem repeat insertion were both associated with a single outbreak, which would indicate the importance of screening more than one isolate within an outbreak. Our results strongly suggest the need for a metagenomics culture-independent approach, as well as a genetic typing scheme for LPS, to ensure an appropriate vaccine strain with a matching predicted LPS structure is used.

Funding
This study was supported by the:
  • Agrifutures Australia
    • Principle Award Recipient: PatrickJ. Blackall
  • Australian Egg Corporation Limited (Award PRJ-010276)
    • Principle Award Recipient: PatrickJ. Blackall
  • This is an open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 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.0.000772
2022-03-10
2024-04-25
Loading full text...

Full text loading...

/deliver/fulltext/mgen/8/3/mgen000772.html?itemId=/content/journal/mgen/10.1099/mgen.0.000772&mimeType=html&fmt=ahah

References

  1. Blackall PJ, Hofacre CL. Fowl cholera. In Swayne DE, Boulianne M, Logue CM, McDougald LR, Nair VL. eds Diseases of Poultry Hoboken, NJ: Wiley; 2020 pp 831–845
    [Google Scholar]
  2. Wilson BA, Ho M. Pasteurella multocida: from zoonosis to cellular microbiology. Clin Microbiol Rev 2013; 26:631–655 [View Article] [PubMed]
    [Google Scholar]
  3. 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] [PubMed]
    [Google Scholar]
  4. Omaleki L, Blackall PJ, Cuddihy T, Beatson SA, Forde BM et al. Using genomics to understand inter- and intra- outbreak diversity of Pasteurella multocida isolates associated with fowl cholera in meat chickens. Microb Genom 2020; 6:000346 [View Article] [PubMed]
    [Google Scholar]
  5. Brogden KA, Rhoades KR, Heddleston KL. A new serotype of Pasteurella multocida associated with fowl cholera. Avian Dis 1978; 22:185–190 [View Article] [PubMed]
    [Google Scholar]
  6. Heddleston KL, Gallagher JE, Rebers PA. Fowl cholera: gel diffusion precipitin test for serotyping Pasteurella multocida from avian species. Avian Dis 1972; 16:925–936 [View Article] [PubMed]
    [Google Scholar]
  7. 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] [PubMed]
    [Google Scholar]
  8. 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] [PubMed]
    [Google Scholar]
  9. 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] [PubMed]
    [Google Scholar]
  10. Harper M, Boyce JD, Cox AD, St Michael F, Wilkie IW et al. Pasteurella multocida expresses two lipopolysaccharide glycoforms simultaneously, but only a single form is required for virulence: identification of two acceptor-specific heptosyl I transferases. Infect Immun 2007; 75:3885–3893 [View Article] [PubMed]
    [Google Scholar]
  11. Nahar N, Turni C, Tram G, Blackall PJ, Atack JM. Actinobacillus pleuropneumoniae: the molecular determinants of virulence and pathogenesis. Adv Microb Physiol 2021; 78:179–216 [View Article] [PubMed]
    [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] [PubMed]
    [Google Scholar]
  13. Walker MJ, Beatson SA. Outsmarting outbreaks. Science 2012; 338:1161–1162 [View Article] [PubMed]
    [Google Scholar]
  14. Zhang P, Fegan N, Fraser I, Duffy P, Bowles RE et al. Molecular epidemiology of two fowl cholera outbreaks on a free-range chicken layer farm. J Vet Diagn Invest 2004; 16:458–460 [View Article] [PubMed]
    [Google Scholar]
  15. 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] [PubMed]
    [Google Scholar]
  16. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 2014; 30:2114–2120 [View Article] [PubMed]
    [Google Scholar]
  17. 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]
  18. Jolley KA, Maiden MCJ. BIGSdb: scalable analysis of bacterial genome variation at the population level. BMC Bioinformatics 2010; 11:595 [View Article] [PubMed]
    [Google Scholar]
  19. 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] [PubMed]
    [Google Scholar]
  20. Omaleki L, Beatson SA, Thomrongsuwannakij T, Blackall PJ, Buller NB et al. Phase variation in latB associated with a fatal Pasteurella multocida outbreak in captive squirrel gliders. Vet Microbiol 2020; 243:108612 [View Article] [PubMed]
    [Google Scholar]
  21. 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] [PubMed]
    [Google Scholar]
  22. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods 2012; 9:357–359 [View Article] [PubMed]
    [Google Scholar]
  23. Langmead B, Wilks C, Antonescu V, Charles R. Scaling read aligners to hundreds of threads on general-purpose processors. Bioinformatics 2019; 35:421–432 [View Article] [PubMed]
    [Google Scholar]
  24. Carver T, Harris SR, Otto TD, Berriman M, Parkhill J et al. BamView: visualizing and interpretation of next-generation sequencing read alignments. Brief Bioinform 2013; 14:203–212 [View Article] [PubMed]
    [Google Scholar]
  25. 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] [PubMed]
    [Google Scholar]
  26. 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]
  27. 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] [PubMed]
    [Google Scholar]
  28. 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]
  29. 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]
  30. Harper M, Boyce JD. The myriad properties of Pasteurella multocida lipopolysaccharide. Toxins 2017; 9:E254 [View Article] [PubMed]
    [Google Scholar]
  31. Fox KL, Atack JM, Srikhanta YN, Eckert A, Novotny LA et al. Selection for phase variation of LOS biosynthetic genes frequently occurs in progression of non-typeable Haemophilus influenzae infection from the nasopharynx to the middle ear of human patients. PLoS One 2014; 9:e90505 [View Article] [PubMed]
    [Google Scholar]
  32. Phillips ZN, Brizuela C, Jennison AV, Staples M, Grimwood K et al. Analysis of invasive nontypeable Haemophilus influenzae isolates reveals selection for the expression state of particular phase-variable lipooligosaccharide biosynthetic genes. Infect Immun 2019; 87:e00093-19 [View Article] [PubMed]
    [Google Scholar]
  33. 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] [PubMed]
    [Google Scholar]
  34. Lango-Scholey L, Aidley J, Woodacre A, Jones MA, Bayliss CD. High throughput method for analysis of repeat number for 28 phase variable loci of Campylobacter jejuni strain NCTC11168. PLoS One 2016; 11:e0159634 [View Article] [PubMed]
    [Google Scholar]
  35. Atack JM, Weinert LA, Tucker AW, Husna AU, Wileman TM et al. Streptococcus suis contains multiple phase-variable methyltransferases that show a discrete lineage distribution. Nucleic Acids Res 2018; 46:11466–11476 [View Article] [PubMed]
    [Google Scholar]
  36. Bush SJ, Foster D, Eyre DW, Clark EL, De Maio N et al. Genomic diversity affects the accuracy of bacterial single-nucleotide polymorphism-calling pipelines. Gigascience 2020; 9:giaa007 [View Article] [PubMed]
    [Google Scholar]
  37. Payne M, Octavia S, Luu LDW, Sotomayor-Castillo C, Wang Q et al. Enhancing genomics-based outbreak detection of endemic Salmonella enterica serovar Typhimurium using dynamic thresholds. Microb Genom 2021; 7:000310 [View Article] [PubMed]
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/mgen/10.1099/mgen.0.000772
Loading
/content/journal/mgen/10.1099/mgen.0.000772
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