1887

Abstract

Where classical epidemiology has proven to be inadequate for surveillance and control of foodborne pathogens, molecular epidemiology, using genomic typing methods, can add value. However, the analysis of whole genome sequencing (WGS) data varies widely and is not yet fully harmonised. We used genomic data on 494 isolates from ready-to-eat food products and food processing environments deposited in the strain collection of the German National Reference Laboratory to compare various procedures for WGS data analysis and to evaluate compatibility of results. Two different core genome multilocus sequence typing (cgMLST) schemes, different reference genomes in single nucleotide polymorphism (SNP) analysis and commercial as well as open-source software were compared. Correlation of allele distances from the different cgMLST approaches was high, ranging from 0.97 to 1, and unified thresholds yielded higher clustering concordance than scheme-specific thresholds. The number of detected SNP differences could be increased up to a factor of 3.9 using a specific reference genome compared with a general one. Additionally, specific reference genomes improved comparability of SNP analysis results obtained using different software tools. The use of a closed or a draft specific reference genome did not make a difference. The harmonisation of WGS data analysis will finally guarantee seamless data exchange, but, in the meantime, knowledge on threshold values that lead to comparable clustering of isolates by different methods may improve communication between laboratories. We therefore established a translation code between commonly applied cgMLST and SNP methods based on optimised clustering concordances. This code can work as a first filter to identify WGS-based typing matches resulting from different methods, which opens up a new perspective for data exchange and thereby accelerates time-critical analyses, such as in outbreak investigations.

Funding
This study was supported by the:
  • Bundesministerium für Gesundheit (Award GE 2016 03 26)
    • Principle Award Recipient: NotApplicable
  • 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.0.000491
2020-12-04
2024-12-06
Loading full text...

Full text loading...

/deliver/fulltext/mgen/7/1/mgen000491.html?itemId=/content/journal/mgen/10.1099/mgen.0.000491&mimeType=html&fmt=ahah

References

  1. Allerberger F, Wagner M. Listeriosis: a resurgent foodborne infection. Clin Microbiol Infect 2010; 16:16–23 [View Article][PubMed]
    [Google Scholar]
  2. ECDC The European Union summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in 2017. Efsa J 2018; 16:e05500 [View Article][PubMed]
    [Google Scholar]
  3. Swaminathan B, Gerner-Smidt P. The epidemiology of human listeriosis. Microbes Infect 2007; 9:1236–1243 [View Article][PubMed]
    [Google Scholar]
  4. Angelo KM, Conrad AR, Saupe A, Dragoo H, West N et al. Multistate outbreak of Listeria monocytogenes infections linked to whole apples used in commercially produced, prepackaged caramel apples: United States, 2014-2015. Epidemiol Infect 2017; 145:848–856 [View Article][PubMed]
    [Google Scholar]
  5. Chen Y, Luo Y, Curry P, Timme R, Melka D et al. Assessing the genome level diversity of Listeria monocytogenes from contaminated ice cream and environmental samples linked to a listeriosis outbreak in the United States. PLoS One 2017; 12:e0171389 [View Article][PubMed]
    [Google Scholar]
  6. EFSA Multi‐country outbreak of Listeria monocytogenes serogroup IV B, multi‐locus sequence type 6, infections linked to frozen corn and possibly to other frozen vegetables–first update. EFSA Supporting Publications 2018; 15:1448E
    [Google Scholar]
  7. Goulet V, King LA, Vaillant V, de Valk H. What is the incubation period for listeriosis?. BMC Infect Dis 2013; 13:11 [View Article][PubMed]
    [Google Scholar]
  8. Kleta S, Hammerl JA, Dieckmann R, Malorny B, Borowiak M et al. Molecular tracing to find source of protracted invasive listeriosis outbreak, southern Germany, 2012–2016. Emerg Infect Dis 2017; 23:1680–1683 [View Article]
    [Google Scholar]
  9. Gelbíčová T, Zobaníková M, Tomáštíková Z, Van Walle I, Ruppitsch W et al. An outbreak of listeriosis linked to turkey meat products in the Czech Republic, 2012-2016. Epidemiol Infect 2018; 146:1407–1412 [View Article][PubMed]
    [Google Scholar]
  10. Schjørring S, Gillesberg Lassen S, Jensen T, Moura A, Kjeldgaard JS et al. Cross-border outbreak of listeriosis caused by cold-smoked salmon, revealed by integrated surveillance and whole genome sequencing (WGS), Denmark and France, 2015 to 2017. Eurosurveillance 2017; 22:17–762 [View Article]
    [Google Scholar]
  11. Pietzka A, Allerberger F, Murer A, Lennkh A, Stöger A et al. Whole genome sequencing based surveillance of L. monocytogenes for early detection and investigations of Listeriosis outbreaks. Front Public Health 2019; 7:139 [View Article][PubMed]
    [Google Scholar]
  12. Ruppitsch W, Pietzka A, Prior K, Bletz S, Fernandez HL et al. Defining and evaluating a core genome multilocus sequence typing scheme for whole-genome sequence-based typing of Listeria monocytogenes . J Clin Microbiol 2015; 53:2869–2876 [View Article][PubMed]
    [Google Scholar]
  13. Moura A, Criscuolo A, Pouseele H, Maury MM, Leclercq A et al. Whole genome-based population biology and epidemiological surveillance of Listeria monocytogenes . Nat Microbiol 2016; 2:16185 [View Article][PubMed]
    [Google Scholar]
  14. Silva M, Machado MP, Silva DN, Rossi M, Moran-Gilad J et al. chewBBACA: a complete suite for gene-by-gene schema creation and strain identification. Microb Genom 2018; 4: [View Article][PubMed]
    [Google Scholar]
  15. Seemann T. Snippy - Rapid haploid variant calling and core genome alignment. https://github.com/tseemann/snippy ; 2015
  16. Møller Nielsen E, Björkman JT, Kiil K, Grant K, Dallman T et al. Closing gaps for performing a risk assessment on Listeria monocytogenes in ready‐to‐eat (RTE) foods: activity 3, the comparison of isolates from different compartments along the food chain, and from humans using whole genome sequencing (WGS) analysis. EFSA Supporting Publications 2017; 14:
    [Google Scholar]
  17. Kwong JC, Mercoulia K, Tomita T, Easton M, Li HY et al. Prospective whole-genome sequencing enhances national surveillance of Listeria monocytogenes . J Clin Microbiol 2016; 54:333–342 [View Article][PubMed]
    [Google Scholar]
  18. Allard MW, Strain E, Melka D, Bunning K, Musser SM et al. Practical value of food pathogen traceability through building a whole-genome sequencing network and database. J Clin Microbiol 2016; 54:1975–1983 [View Article][PubMed]
    [Google Scholar]
  19. Wielinga PR, Hendriksen RS, Aarestrup FM, Lund O, Smits SL et al. Global Microbial Identifier Springer: Applied Genomics of Foodborne Pathogens; 2017 pp 13–31
    [Google Scholar]
  20. Nadon C, Van Walle I, Gerner-Smidt P, Campos J, Chinen I et al. Pulsenet international: vision for the implementation of whole genome sequencing (WGS) for global food-borne disease surveillance. Euro Surveill 2017; 22:30544 [View Article][PubMed]
    [Google Scholar]
  21. Babraham Bioinformatics FastQC: a quality control tool for high throughput sequence data. https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ ; 2019
  22. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for illumina sequence data. Bioinformatics 2014; 30:2114–2120 [View Article][PubMed]
    [Google Scholar]
  23. Deneke C, Tausch S. AQUAMIS (Assembly-based quality assessment for microbial isolate sequencing). https://gitlab.com/bfr_bioinformatics/AQUAMIS ; 2019
  24. Seemann T. mlst - Scan contig files against traditional PubMLST typing schemes. https://github.com/tseemann/mlst ; 2019
  25. Van Walle I, Björkman JT, Cormican M, Dallman T, Mossong J et al. Retrospective validation of whole genome sequencing-enhanced surveillance of listeriosis in Europe, 2010 to 2015. Euro Surveill 2018; 23: [View Article][PubMed]
    [Google Scholar]
  26. Hyatt D, Chen G-L, Locascio PF, Land ML, Larimer FW et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 2010; 11:119 [View Article][PubMed]
    [Google Scholar]
  27. Deneke C. chewieSnake - snakemake pipeline based on chewbbaca. https://gitlab.com/bfr_bioinformatics/chewieSnake ; 2019
  28. Zhou Z, Alikhan N-F, Sergeant MJ, Luhmann N, Vaz C et al. GrapeTree: visualization of core genomic relationships among 100,000 bacterial pathogens. Genome Res 2018; 28:1395–1404 [View Article][PubMed]
    [Google Scholar]
  29. 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: [View Article][PubMed]
    [Google Scholar]
  30. Deneke C Variant calling pipeline with snippy. https://gitlab.com/bfr_bioinformatics/snippy-snake ; 2019
  31. Seemann T 2018; snp-dists - Pairwise SNP distance matrix from a FASTA sequence alignment. https://github.com/tseemann/snp-dists
  32. Carriço JA, Silva-Costa C, Melo-Cristino J, Pinto FR, de Lencastre H et al. Illustration of a common framework for relating multiple typing methods by application to macrolide-resistant Streptococcus pyogenes . J Clin Microbiol 2006; 44:2524–2532 [View Article][PubMed]
    [Google Scholar]
  33. Pightling AW, Pettengill JB, Luo Y, Baugher JD, Rand H et al. Interpreting whole-genome sequence analyses of foodborne bacteria for regulatory applications and outbreak investigations. Front Microbiol 2018; 9:1482 [View Article][PubMed]
    [Google Scholar]
  34. Jackson BR, Tarr C, Strain E, Jackson KA, Conrad A et al. Implementation of nationwide real-time whole-genome sequencing to enhance listeriosis outbreak detection and investigation. Clin Infect Dis 2016; 63:380–386 [View Article][PubMed]
    [Google Scholar]
  35. Schürch AC, van Schaik W. Challenges and opportunities for whole-genome sequencing-based surveillance of antibiotic resistance. Ann N Y Acad Sci 2017; 1388:108–120 [View Article][PubMed]
    [Google Scholar]
  36. Jagadeesan B, Baert L, Wiedmann M, Orsi RH. Comparative analysis of tools and approaches for source tracking Listeria monocytogenes in a food facility using whole-genome sequence data. Front Microbiol 2019; 10:947 [View Article][PubMed]
    [Google Scholar]
  37. Gardner SN, Slezak T, Hall BG. kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome. Bioinformatics 2015; 31:2877–2878 [View Article][PubMed]
    [Google Scholar]
  38. Rossen JWA, Friedrich AW, Moran-Gilad J. ESCMID Study Group for Genomic and Molecular Diagnostics (ESGMD) Practical issues in implementing whole-genome-sequencing in routine diagnostic microbiology. Clin Microbiol Infect 2018; 24:355–360 [View Article][PubMed]
    [Google Scholar]
/content/journal/mgen/10.1099/mgen.0.000491
Loading
/content/journal/mgen/10.1099/mgen.0.000491
Loading

Data & Media loading...

Supplements

Supplementary material 1

EXCEL

Supplementary material 2

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