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Integrating WGS data into Quantitative Microbial Risk Assessment: - - PowerPoint PPT Presentation

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Integrating WGS data into Quantitative Microbial Risk Assessment: Refinement of the L. monocytogenes in cold smoked salmon model Lena Fritsch Email: lena.fritsch@anses.fr ? ? ? 26/04/2018 26/04/2018 26/04/2018 26/04/2018 ? ? ?

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Integrating WGS data into Quantitative Microbial Risk Assessment:

Lena Fritsch

Email: lena.fritsch@anses.fr

Refinement of the

  • L. monocytogenes in cold smoked salmon model
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? ? ?

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? ? ?

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Whole Genome Sequencing

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Whole Genome Sequencing

  • GWAS
  • Transcriptomics
  • ….

(Cocolin et al. 2017)

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Genome wide association studies (GWAS)

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Genome wide association studies (GWAS)

Trait 1

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Genome wide association studies (GWAS)

Trait 1 DNA sequencing

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Genome wide association studies (GWAS)

Trait 1 DNA sequencing Find associations between genetic variations and

  • bservable traits

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Genome wide association studies (GWAS)

Trait 1 DNA sequencing Find associations between genetic variations and

  • bservable traits

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Biomarker « X »

  • Genes
  • SNPs
  • ….
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How to use genomic-data ?

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Prevalence

10.4% (EFSA, 2015)

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How to use genomic-data ?

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Prevalence Genomic data

Searching for Biomarker « X » 10.4% (EFSA, 2015)

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How to use genomic-data ?

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Prevalence Genomic data

Searching for Biomarker « X » 10.4% (EFSA, 2015)

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How to use genomic-data ?

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Prevalence Genomic data

Searching for Biomarker « X » Implementation in QMRA 10.4% (EFSA, 2013)

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  • Cold smoked salmon model (Pouillot et al. 2007/2009) L. monocytogenes

Objective

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  • Cold smoked salmon model (Pouillot et al. 2007/2009) L. monocytogenes

Objective

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EFSA baseline+ Møller-Nielsen et al. 2017

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  • Cold smoked salmon model (Pouillot et al. 2007/2009) L. monocytogenes

Objective

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EFSA baseline+ Møller-Nielsen et al. 2017

GWAS Hingston et al. 2017

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  • Cold smoked salmon model (Pouillot et al. 2007/2009) L. monocytogenes

Objective

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EFSA baseline+ Møller-Nielsen et al. 2017

GWAS Hingston et al. 2017 Virulence

Maury et al. 2016

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Dose-Response (FDA, 2003)

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Dose-Response (FDA, 2003)

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Dose-Response (FDA, 2003)

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But which CC correspond to which group?

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CC1

(Maury et al. 2016)

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But which CC correspond to which group?

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CC1

(Maury et al. 2016)

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But which CC correspond to which group?

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CC1

(Maury et al. 2016)

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But which CC correspond to which group?

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CC1

(Maury et al. 2016)

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Prevalence

10.4% (EFSA, 2013)

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Prevalence Genomic data

Which CCs are present 10.4% (EFSA, 2013)

(Møller-Nielsen et al. 2017)

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Prevalence Genomic data

Which CCs are present 10.4% (EFSA, 2013)

Prevalence [%] Hypervirulent 9.2% Medium virulence 39.1% Hypovirulent 51.7%

(Møller-Nielsen et al. 2017)

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Prevalence Genomic data

Which CCs are present 10.4% (EFSA, 2013)

Prevalence [%] Hypervirulent 9.2% Medium virulence 39.1% Hypovirulent 51.7%

(Møller-Nielsen et al. 2017)

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Tmin (Hingston et al. 2017)

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  • Biomarker as Genes, SNPs, …
  • Biomarker full length inlA adaptation to cold temperature
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Tmin (Hingston et al. 2017)

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  • Biomarker as Genes, SNPs, …
  • Biomarker full length inlA adaptation to cold temperature

Tmin HG Tmin LG

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Cases of listeriosis

Exposure

Hypovirluent

Medium

Hypervirulent

Results

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39.1% 51.7% 9.2% 95.5 % 0.02 % 4.4 %

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Cases of listeriosis

Exposure

Hypovirluent

Medium

Hypervirulent

Results

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39.1% 51.7% 9.2% 95.5 % 0.02 % 4.4 % Predicted concentrations in contaminated CSS  2 times less important per 30g for « LG » strains

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Conclusion and perspectives

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  • One of the first approaches (Pielaat et al. 2015)
  • Strong hypothesis: r-value

CCs Clinical Frequency

  • Issue to take into account food specific prevalence
  • Near future

 Biomarker  Accessible data

  • Adapting or refinement of intervention strategies
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Many thanks to:

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  • Prof. Dr. J.-C. Augustin
  • Dr. Laurent Guillier
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References

  • Cocolin, L., Mataragas, M., Bourdichon, F., Doulgeraki, A., Pilet, M.-F., Jagadeesan, B., Rantsiou, K., Phister, T., 2017. Next generation

microbiological risk assessment meta-omics: The next need for integration. International journal of food microbiology.

  • Cocolin, L., Membré, J.-M., Zwietering, M., 2017. Integration of omics into MRA. International journal of food microbiology.
  • Pouillot, R., Goulet, V., Delignette‐Muller, M.L., Mahé, A., Cornu, M., 2009. Quantitative Risk Assessment of Listeria monocytogenes in

French Cold‐Smoked Salmon: II. Risk Characterization. Risk analysis 29(6), 806-819.

  • EFSA, 2013. Analysis of the baseline survey on the prevalence of Listeria monocytogenes in certain ready‐to‐eat foods in the EU, 2010–

2011 Part A: Listeria monocytogenes prevalence estimates. EFSA Journal 11(6).

  • EFSA BIOHAZ Panel, Ricci, A., Allende, A., Bolton, D., Chemaly, M., Davies, R., Fernández Escámez, P., Girones, R., Herman, L.,

Koutsoumanis, K., Nørrung, B., Robertson, L., Ru, G., Sanaa, M., Simmons, M., Skandamis, P., Snary, E., Speybroeck, N., Ter Kuile, B., Threlfall, J., Wahlstrom, H., Takkinen, J., Wagner, M., Arcella, D., Da Silva Felicio, M., Georgiadis, M., Messens, W., Lindqvist, R., 2018. Scientific Opinion on the Listeria monocytogenes contamination of ready-to-eat foods and the risk for human health in the EU. EFSA Journal 16(1), 173 pp. .

  • FDA/FSIS, 2003. Quantitative assessment of relative risk to public health from foodborne Listeria monocytogenes among selected categories
  • f ready-to-eat foods. Food and Drug Administration, U.S. Department of Agriculture, Centers for Disease Control and Prevention.
  • Hingston, P., Chen, J., Dhillon, B.K., Laing, C., Bertelli, C., Gannon, V., Tasara, T., Allen, K., Brinkman, F.S., Hansen, L.T., 2017. Genotypes

Associated with Listeria monocytogenes Isolates Displaying Impaired or Enhanced Tolerances to Cold, Salt, Acid, or Desiccation Stress. Frontiers in Microbiology 8.

  • Maury, M.M., Tsai, Y.-H., Charlier, C., Touchon, M., Chenal-Francisque, V., Leclercq, A., Criscuolo, A., Gaultier, C., Roussel, S., Brisabois,

A., 2016. Uncovering Listeria monocytogenes hypervirulence by harnessing its biodiversity. Nature genetics 48(3), 308-313.

  • Møller-Nielsen, E., Björkman, J.T., Kiil, K., Grant, K., Dallman, et al. 2017. 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 14(2).

  • Pielaat, A., Boer, M.P., Wijnands, L.M., van Hoek, A.H., Bouw, E., Barker, G.C., Teunis, P.F., Aarts, H.J., Franz, E., 2015. First step in using

molecular data for microbial food safety risk assessment; hazard identification of Escherichia coli O157: H7 by coupling genomic data with in vitro adherence to human epithelial cells. International journal of food microbiology 213, 130-138.

  • Pouillot, R., Hoelzer, K., Chen, Y., Dennis, S.B., 2015. Listeria monocytogenes dose response revisited—incorporating adjustments for

variability in strain virulence and host susceptibility. Risk Analysis 35(1), 90-108.

  • Pouillot, R., Klontz, K.C., Chen, Y., Burall, L.S., Macarisin, D., Doyle, M., Bally, K.M., Strain, E., Datta, A.R., Hammack, T.S., 2016. Infectious

dose of Listeria monocytogenes in outbreak linked to ice cream, United States, 2015. Emerging infectious diseases 22(12), 2113.

  • Pouillot, R., Miconnet, N., Afchain, A.L., Delignette‐Muller, M.L., Beaufort, A., Rosso, L., Denis, J.B., Cornu, M., 2007. Quantitative risk

assessment of Listeria monocytogenes in French cold‐smoked salmon: I. Quantitative exposure assessment. Risk analysis 27(3), 683-700.

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