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TRANSCRIPT
Does WGS play a role forFood Safety?
Beatriz Guerra Román
XII IMMEM, Dubrovnik
26.09.2019
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EFSA Molecular studies for Food Safety
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Novel molecularbiology methods
Effects chemicalcomponents on living organisms
Geneticpolymorphisms
Novel computationalapproaches to predictdrug metabolism and toxicity
Enzymecharacterization
OMICs
Detection of emerging«high risk» clones
WGS
Metagenomics
AMR surveillance
(EUSR)
Outbreakinvestigation(ROAs)
Characterization/predictionresistance/virulence
Transcriptomics
GMOs
Guidelines applicationsregulated products
Cloud
Novel food
Food/ Feedaditives
Pesticides Technical notes
Metabolomics
Big data
Biomarkers
Proteomics
Source attribution
Health claims
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What is WGS for?
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WGS sequencing
…ATTGCATCACTAGATTAGATTATGAAGATATTGATTACACCTCGA….
ACTGAACCTGTACGCCAGAAACAGCAAGCCCATGCTTTTCCGGCGCACAGATTCAAAGTGACGGACCGTT
GTACGTTCGCTGTCGCTGAGATCGTTCCAGCTCCAGCGCTTTCTGATGCTGCGCCGCCCGTTCCTGCTCA
CGATGTGCCTCTATCACGTTCAGCCTTGTGACAACCGGCGCAGCTGCTCGCTCAAACTCTGCACCTGCCT
GCTCAAGCCCGTGACGCGCTCGCTCAGCGCCGCGTTCTCCCGTTGCATAAGACCAGACATCGTCCGCCAT
TCCGCGAAGGCGTTCTCCCACTCGTCCAGCCTTTTCGAGTAGTCCTGCTGTAGCTGCTCTAATGCGCTCA
GCAACTGTTTTTCCAGCTCCGTCATGTGCTATTTCCCCGCCAGTATCATCCAGCTCGAATCCTCTCCGAA
CCGTCCCGCTTCCGGGTTCACCCTCACGCAGCGGCGTCTCTGCTCTCCGCAGGTCGAGAGCTGCACGCCG
CTGTTCCTCTCGGACAGCATGGCCTGCGTGCTCTTCTGCTCCCGGATGATCGTGTAATTGTCGAGTATCT
GCTGCCCCTGCCACCATAGAATGCTTGCGCCCGATGCTGTCAGCAGTGTAGACACCAGGACGATGGTCAG
CCACGTCTGGCTGACCATACGCACCATGCCTTTCGTGCGCTGGCTCATGGCTGAGGACAGCTTCCGGTCG
Resistance traits
Pathogenicity, virulence
Strain characterization
Plasmid characterization
Phylogeny Genetic relatedness
Species identification
Persistence traits publicST121
publicST6
publicST9
publicST8
publicST1
publicST155
publicST2
publicST101
publicST4
publicST87
publicST7
publicST37
publicST3
publicST14
publicST204
publicST31
publicST399
publicST59
publicST5
publicST21
publicST394
publicST20
publicST325
publicST18
“TAG the AGATA’s CAT tail*”
*Iolanda’s Mangone idea! (ISZ, Teramo, out bioinformatician for 1,5 years)
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Foodborne pathogens and zoonotic bacteria
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EC survey: WGS for food/waterborne pathogens
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Q1. DO YOU CARRY OUT WGS ACTIVITIES? 28% YES (N=154 respondents)
Status December 2016Current data collected by the EURLs end2017 show a similar picture (EC EURLsWGS WG personal communication)
YesNo
*
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General questions section:
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Q1...DO YOU CARRY OUT WGS… BY RESPONDENT (N=72 respondents)*
*72 respondentscorresponding to a total of 183 replies frompathogen specificlaboratoriesacting as NRLs. Analyses of data by “respondents” or by “Network laboratories” provided a similar picture for thewholequestionnaire.
<50%
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Examples of WGS for Food Safety
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WGS for Outbreak investigations
and other activities
Context: examples of work done somewhere else
Our reality: work done in/for EFSA© ESCMID eL
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Do you remember? E. coli O104 Germany
May 2011
3816 cases
845 HUS cases
54 deaths
Taken from Frank et al. NEJM 2011; 365:1771-1780
Photos kindly provided by Istvan Szabo, National reference Laboratory for Salmonella,
Federal Institute for Risk Assessment, Berlin, Germany
B. Guerra
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O104:H4 E. coli WGS within days…
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BGI, Uni Hamburg-Eppendorf
TY2482 (1/2. June)
Health Protection
Agency
H112180280 (10 June)
Lifetech, Uni Münster
LB226692 (1/2. June)
Published on July 27, 2011, N Engl J Med 2011;365:718-24.
Received June 29, 2011; Accepted July 6, 2011; Published July 20, 2011
www.hpa-bioinformatics.org.uk/lgp/genomes
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Social media Real time WGS Analysis O104:H4
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Blogs and Wikis!!!!
BacPathGenomicsGenomics and evolution of bacterial pathogens
CrowdSourcingBlogging the German outbreak E.coli 0104:H4
Pathogens: Genes and GenomesA heady mix of bacterial pathogenomics, next-generation sequencing, type-III secretion, bioinformatics and evolution!
EHEC Infection @EHECInfection· http://www.ehecinfection.com
GMO Pundit a.k.a. David TribeHelping readers navigate the confusing myths of modern biology
Figures kindly provided by Kat HoltLondon School of Hygiene & Tropical MedicineMonash University, Melbourne
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O104, more info...
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DE isolates, little diversity, 2 SNPs in 4 isolates. FR isolates, 19 SNPs in 7 isolates. DE isolates formed a clade within the more diverse FR strains. Diversity present in the original set, and later reduced in the distribution to Germany?, or original homogeneous populationsubjected to different mutation rates upon their geographicalsegregation?
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Detection methods: real time PCR (based on WGS data)
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O104, more info...
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Listeriosis outbreak
• Mid-June 2017
• Several clinicians/microbiologists report unusually high numbers of listeriosis cases
• Signaled the start of the outbreak
• 1 January 2017 to 17 July 2018
• 1060 cases
Figures kindly provided by Anthony Smith
Centre for Enteric Diseases (CED),
National Institute for Communicable Diseases (NICD)
South Africa
>1000 cases, the largest L. monocytogenes outbreak
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Outbreak of Listeria monocytogenes in South Africa, 2017-2018
91% of human isolates are
MLST sequence type 6 (ST6)
abcZ bglA cat dapE dat ldh lhkA
3 9 9 3 3 1 5
- WGS data
- minimum spanning tree
- drawn using cgMLST data (1748 genes)
- 695 isolates
Food
Human
Production facility
Figures kindly provided by Anthony Smith
Centre for Enteric Diseases (CED),
National Institute for Communicable Diseases (NICD)
South Africa
L. monocytogenes ST6 Outbreak South Africa
- ST6 cluster
- 91% of human isolates
- <10 SNP differences among isolates
- highly related
• Environmental ST6 isolates
recovered from the food
production facility
• ST6 isolates recovered from
the company food samples
Outbreak of Listeria monocytogenes in South Africa, 2017-2018
- human isolates (n=706)
- WGS data
- maximum likelihood tree (linear tree)
- drawn using SNP profiles
• grey shading links isolates showing ≤7 allele differences
• indicative of highly related isolates
• indicative of epidemiological relatedness
Food, n=22
Human, n=328
Production facility, n=24
- WGS data
- minimum spanning tree
- drawn using cgMLST data
- ST6 isolates only (n=374)
Straincharacterization
Trace back
Genetic relateness
+ Epi and tracing back data
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Multicountry Rapid Outbreak Assessment (ROAs)
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EFSA WGS Capacity building
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Online tools and existing platforms: e.g. ENTEROBASE, BIGSdb, CGE, INNUENDO, COMPARE, PATRIC, etc.
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“Technical support to collect and analyse whole genome sequencing (WGS) data in the joint ECDC-EFSA molecular typing database”
at least L. monocytogenes, Salmonella, E.coli
Published May 2019
https://efsa.onlinelibrary.wiley.com/doi/epdf/10.2903/sp.efsa.2019.EN-1337
Other EFSA activities for foodborne pathogens
BIOHAZ PANEL“Self-tasking mandate for scientific opinion on the application and use of
next generation sequencing (including whole genome sequencing) for risk assessment of foodborne microorganisms”
Deadline October 2019
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WGS for AMR:
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VIM-1 occurrence in the food chain
E. coli ST88 clone
E. coli ST131
2011/2012 2015/2016 2017
Salmonella Infantis
Salmonella rough
Salmonella Infantis
Salmonella Goldcoast
E. coli ST88 clone
Enterobacter cloacae
Salmonella group C
E. coli ST7593
Salmonella?
E. coli ST48
Positive farms (1)Positive farms (5) Positive farms (3)
pRH-R3 like IncHI2 plasmid
Slide kindly provided by Jennie Fischer,
German Federal Institute for Risk Assessment
Roschanski et al. 2019. mSphere 4:e00089-19© ESCMID
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Carbapenemase-produding bacteria in the food chain
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Larsen et al. (2016) – www.danmap.org
Several human cases in the poultry associated clade reporteddirect contact with raw poultry meat
Figure kindly provided by Anders Rhod Larsen
Statens Serum Institute
Denmark
Livestock-associated MRSA
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Livestock-associated MRSA at EFSA
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Harmonized monitoring EU Legislation
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Decision 2013/652/EU
2014 - 2020
Directive 2003/99/ECArt. 7(3) and 9(1) + Annexes II (B) IV
Zoonotic Bacteria
Salmonella spp.
C. jejuni / C. coli
ESBL-/AmpC-/CP-producing Salmonella
Indicator Bacteria
E. coli
E. faecalis / E. faecium
ESBL-/AmpC-/CP-producing E. coli
Bacterial species
Sampling
AST
MatrixSource
New Decision
2021 - …© ESCMID
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EUSR-AMR Reference Testing (EURL-AR + MSs)
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Selection of isolates:
Emerging resistances
Detection of clones
Discrepancies
Confirmation of results
Ask MSs for the isolates
Perform:
WGS, MIC re-testing
Seq. publicly available ENA
WGS analyses to support phenotypical AMR data: around 400 isolates selected sequnced by yearSequences released to ENA (with permission of the MSs)
MSs
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From WGS testing, detection of…
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Emerging AMR-Clones/Plasmids?
S. Infantis ESBL in ItalyS. Kentucky Cipro-R
Development of detection methods
Multi-plex PCR
Emerging AMR-Mechanisms?COL: mcr-1, mcr1.6, mcr-3, mcr-4, mcr-5ESBLs, PMQRsAZT: mefC-mphG tándemE. coli OXA-162
Figures kindly provided by and Antonio Battisti (ISZLT, Italy)
Figures kindly provided by Valeria Bortolaia (EURL-AR, DTU, Denmark)
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Request for scientific and technical assistance on harmonised monitoring of antimicrobial resistance (AMR) in bacteria transmitted through food
Published June 2019
https://efsa.onlinelibrary.wiley.com/doi/epdf/10.2903/j.efsa.2019.5709
……..
To address the use of molecular typing methods
o To complement and/or replace the phenotypic methods
o To ensure the comparability between the results of technics
o To integrate molecular data with past/future phenotypicaldata
…This includes the use of WGS
EC Mandate Revision Techn. SpecificationsAMR MON
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AMR tools? Benchmarking needed
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Taken from ENGAGE final mtg. 01.2018.Published Final Report
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EFSA Capacity building AMR benchmarking
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beta-lactamase genes detection …..
Sometimes, the same tool does not detect all the genes (different input sequences different results)Some tool give you all similar genes….
Sample name File used Trimmed Assembler Pipeline beta-lactams
ERR2019187_EnaSPA ENA_reads no SPADES A blaCTX-M-15,blaTEM-1C
ERR2019187_EnaVelv ENA_reads no Velvet A
blaCTX-M-15,blaTEM-10 (1),blaTEM-10 (2),blaTEM-101 (1),blaTEM-101 (2),blaTEM-102
(1),blaTEM-102 (2),blaTEM-104 (1),blaTEM-104 (2),blaTEM-105 (1),blaTEM-105 (2),blaTEM-
106 (1),blaTEM-106 (2),blaTEM-107 (1),blaTEM-107 (2),blaTEM-108 (1),blaTEM-108 (2),blaTEM-
109 (1),blaTEM-109 (2),blaTEM-11 (1),blaTEM-11 (2),blaTEM-110 (1),blaTEM-110 (2),blaTEM-
111 (1),blaTEM-111 (2),blaTEM-112 (1),blaTEM-112 (2),blaTEM-113 (1),blaTEM-113 (2),blaTEM-
ERR2019187_SRAVelv SRA_reads no Velvet A
blaCTX-M-15,blaTEM-10 (1),blaTEM-10 (2),blaTEM-101 (1),blaTEM-101 (2),blaTEM-102
(1),blaTEM-102 (2),blaTEM-104 (1),blaTEM-104 (2),blaTEM-105 (1),blaTEM-105 (2),blaTEM-
106 (1),blaTEM-106 (2),blaTEM-107 (1),blaTEM-107 (2),blaTEM-108 (1),blaTEM-108 (2),blaTEM-
109 (1),blaTEM-109 (2),blaTEM-11 (1),blaTEM-11 (2),blaTEM-110 (1),blaTEM-110 (2),blaTEM-
111 (1),blaTEM-111 (2),blaTEM-112 (1),blaTEM-112 (2),blaTEM-113 (1),blaTEM-113 (2),blaTEM-
ERR2019187_T_EnaVelvENA_reads yes Velvet A blaCTX-M-15,blaTEM-1C
ERR2019187 ENA_assembly yes SPADES B blaCTX-M-15,TEM-171,TEM-2
ERR2019187 SRA_assembly yes SPADES B blaCTX-M-15,TEM-171,TEM-2
ERR2019187 ENA_reads no no? C blaCTX-M-15,
ERR2019187T ENA_reads yes no? C blaCTX-M-15,blaTEM-1B-like
ERR2019187 ENA_assembly yes SPADES C blaCTX-M-15,blaTEM-1B-like
ERR2019187 ENA_reads no SPADES D
blaCTX-M-15_23,CTX-M-33,OXA-368,TEM-3,TEM-33,TEM-4,blaTEM-102_1,blaTEM-104_1,
blaTEM-112_1,blaTEM-141_1
ERR2019187T ENA_reads yes SPADES D
blaCTX-M-15_23,CTX-M-33,OXA-368,TEM-3,TEM-33,TEM-4,blaTEM-102_1,blaTEM-104_1,
blaTEM-112_1,blaTEM-141_1
ERR2019187 Reftest WGS blaCTX-M-15,blaTEM-1B (100, 741 / 861)
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Aminoglycoside genes detection …..
Nomenclature chaos depending on the databases….
EFSA Capacity building AMR benchmarking
Sample name File used Trimmed Assembler Pipeline aminoglycosidesERR2019166_Ena ENA_reads no SPADES A aac(3)-IIa,aadA1,aadA2,aph(3')-Ia,strA,strB
ERR2019166_Ena ENA_reads no Velvet A
aac(3)-IIa,aadA1 (1),aadA1 (2),aadA1 (3),aadA21 (1),aadA21 (2),aadA22 (1),aadA22 (2),aadA23
(1),aadA23 (2),aadA24 (1),aadA24 (2),aadA3 (1),aadA3 (2),aadA8 (1),aadA8 (2),aadA8b
(1),aadA8b (2),aph(3')-Ia,strA,strB
ERR2019166_SRA SRA_reads no Velvet A aac(3)-IIa,aadA1,aadA2,aph(3')-Ia,strA,strB
ERR2019166_T_Ena ENA_reads yes Velvet A
aac(3)-IIa,aadA1 (1),aadA1 (2),aadA1 (3),aadA15 (1),aadA15 (2),aadA21 (1),aadA21 (2),aadA22
(1),aadA22 (2),aadA23 (1),aadA23 (2),aadA24 (1),aadA24 (2),aadA3 (1),aadA3 (2),aadA8
(1),aadA8 (2),aadA8b (1),aadA8b (2),aph(3')-Ia,strA,strB
ERR2019166 ENA_assembly yes SPADES B AAC(3)-IIc,AAC(6')-Ib7,APH(3'')-Ib (strA),APH(3')-Ia,APH(6)-Id (strB),aadA,aadA3,acrD,kdpE
ERR2019166 SRA_assembly yes SPADES B AAC(3)-IIc,AAC(6')-Ib7,APH(3'')-Ib (strA),APH(3')-Ia,APH(6)-Id (strB),aadA,aadA3,acrD,kdpE
ERR2019166 ENA_reads no C aac(3)-IIa,aadA1-like,aadA2,aph(3')-Ic-like,strA,strB
ERR2019166T ENA_reads yes C aac(3)-IIa,aadA1-like,aadA2,aph(3')-Ia-like,APH(6)-Id (strB),strA
ERR2019166 ENA_assembly yes SPADES C aac(3)-IIa,aadA1-like,aadA2,aph(3')-Ia-like,APH(6)-Id (strB),strA
ERR2019166 ENA_reads no SPADES D
AAC(3)-IIa,AAC(6)-Ib,AAC(6)-Ib7,APH(3)-Ia,APH(3)-Ib,APH(6)-Id (strB),aac(3)-
IIa_1,aadA,aadA15,aadA1_2,aadA1_3,aadA1_4,aadA1_5,aadA2,aadA22,aadA23,aadA24,aadA2
_2,aadA8,aadA9,acrD,ant(3)-Ia_1,aph(3)-Ia_1,aph(3)-Ib_1,APH(6)-Id_1,kdpE,strA_1
ERR2019166T ENA_reads yes SPADES D
AAC(3)-IIa,AAC(6)-Ib,AAC(6)-Ib7,APH(3)-Ia,APH(3)-Ib,APH(6)-Id (strB),aac(3)-
IIa_1,aadA,aadA15,aadA1_2,aadA1_3,aadA1_4,aadA1_5,aadA2,aadA22,aadA23,aadA24,aadA2
_2,aadA8,aadA9,acrD,ant(3)-Ia_1,aph(3)-Ia_1,aph(3)-Ib_1,APH(6)-Id_1,kdpE,strA_1
ERR2019166 Reftest WGS aph(3')-Ic (99.14)/ aac(3)-Iia
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Tech. specifications AMR MON recommendations
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Proposed approach to integration of WGS … Incremental approach over 2021-2026
Voluntary use of WGS:
for Specific Monitoring of ESBL/AmpC/CP-producing E. coli (mandatory!)
For Confirmatory Testing using WGS
Harmonised protocol and quality criteria are needed! Several bioninformatic tools/pipelines/sequencing platforms
Various reference AMR gene databases
… can hamper comparative accuracy of WGS results.
-> EURL-AR to provide Harmonised Protocols/Quality Criteria and Training on DNA extraction, library preparation, sequencing in 2019-2020
For the moment...Report genes
Further developments in the future (re-assess regularly 2021-2026)
… To switch: EU-wide WGS data collection, leading to harmonized AMR mon.
Provided a high concordance WGS- genotyping fand AST … technology mature nd fully implemented … and MSs ready.
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Regulated products
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Regulated products
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B. Guerra
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Conclussions
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WGS is useful for Food Safety…
• YES! A lot of information can be extracted from TAG, AGATA, CAT..
• We need to ask us always three questions • what do we want to know?• how can we achieve it? • which is the context?
• Different aims, similar/different bioinformatic tools needed.
• For surveillance/monitoring, harmonization is extremely important to allow comparability. The use of curated and updated data bases is a must.
• Detailed information on analysis done, tools, versions, parameters, etc. needed.
• Challenge: rapid and constant evolution of the techniques, tools, etc., can make reproducibility of the results difficult…
…reproducibility needs to be ensured© ESCMID
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Beatriz GuerraLead Expert Molecular Epidemiology. Senior Scientific OfficerUnit on Biological Hazards and Contaminants (BIOCONTAM)Department of Risk Assessment and Scientific Assistance (RASA)
e-mail: [email protected]
Thanks for your attention and thanks to…!
Ernesto Liébana, Valentina Rizzi, Pierre-Alexander Beloeil, Mirko Rossi, Elonora Sarmo, Montserrat Anguita, Jaime Aguilera, Nikoletta Papadopoulous (EFSA)
Iolanda Mangone (ISZ Teramo, EFSA Tasking Grant Bioinformatician)
Raquel Garcia Fierro and Daniel Thomas López (ex-EFSA trainees)
Jennie Fischer and Istvan Szabo (BfR), Lothar Beutin (formerly BfR, Berlin)
Anthony Smith (NICD, South Africa)
Kathryn Holt (London School of Hygiene & Tropical Medicine, Monash Univ., Melbourne)
Ander R Larsen (SSI, Copenhagen)
Valeria Bortolaia (DTU, Copenhagen)
Antonio Battisti (ISZLT, Rome)
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