D4.18 Cogwheel Workshop 5 WP4 Joint integrative projects · Deliverable D4.18: 5th cogwheel...

D4.18 Cogwheel Workshop 5

WP4 Joint integrative projects

Responsible Partner: SVA

Contributing partners: NVI

GENERAL INFORMATION European Joint Programme full title

Promoting One Health in Europe through joint actions on foodborne zoonoses, antimicrobial resistance and emerging microbiological hazards

European Joint Programme acronym

One Health EJP

Funding This project has received funding from the European Union’s Horizon 2020

research and innovation programme under Grant Agreement No 773830.

Grant Agreement Grant agreement n° 773830

Start Date 01/01/2018

Duration 60 Months

DOCUMENT MANAGEMENT Deliverable D4.18: 5th cogwheel workshop report with JPIAMR

WP and task WP4; Task 4.3 – Subtask 4.3.1

Author Karin Artursson (SVA)

Other contributors Marie Nykvist (SVA), Solveig Sølverød Mo (NVI) and Kristin Sæbø Pettersen (NVI)

Due month of the

report

Actual submission

R: Document, report DEC: Websites, patent filings, videos, etc.; OTHER

Save date: 29-Jun-20

Dissemination level

PU: Public (default) CO: confidential, only for members of the consortium (including the Commission Services)

Dissemination

Author’s suggestion to inform the following possible interested parties.

OHEJP WP 1 ☐ OHEJP WP 2 ☒ OHEJP WP 3 ☒

OHEJP WP 4 ☒ OHEJP WP 5 ☒ OHEJP WP 6 ☐

OHEJP WP 7 ☐ Project Management Team ☐

Communication Team ☐ Scientific Steering Board ☐

National Stakeholders/Program Owners Committee ☐

EFSA ☐ ECDC ☐

Other international stakeholder(s):

………………………………………………………………………

Social Media: .........................................................................................................

Other recipient(s): ...............................................................................................

Report from Cogwheel Workshop 5 One Health EJP / JPIAMR

Introduction In Work Package 4 (WP4) of the One Health European Joint Programme (OHEJP), EU initiatives that require strategic interaction with OHEJP are identified in collaboration with WP2 and WP5, to avoid redundancy and to further leverage the alignment at EU level. One of the instruments, so called cogwheel workshops (CWs), are being organised by WP4 to allow key actors and relevant partners within the OHEJP, typically Project leaders or WP leaders within Joint Research Projects (JRP:s) or Joint Integrative Projects (JIP:s), to identify synergies, joint priorities and opportunities for collaboration within the OHEJP or with other EU initiatives. Before contacting the relevant EU initiative/project, it is important to identify and collect (common) JRP and JIP needs and to define if the initiative complies with these needs. Furthermore, it is important to see if the initiative can complement or assist the OHEJP, for instance with database/repositories, protocols, advice, practical collaboration (sequencing, bioinformatics) and so on.

Eight CWs will be organised during the OHEJP. The reports from the CWs will be part of the input to the Strategic Research Agenda (SRA) of WP2, as well as the Strategic Research and Innovation Agenda (SRIA) of WP7.

The target for the fifth CW was five projects funded through the 9th call from the Joint Programming Initiative on Antimicrobial Resistance (JPIAMR) on Diagnostics and Surveillance;

• MAGITICS: MAchine learning for diGItal diagnosTICS of antimicrobial resistance;https://www.jpiamr.eu/wp-content/uploads/2019/11/MAGITICS.pdf

• K-STaR: A K-mer Based Approach for Institutional AMR Surveillance, TransmissionMonitoring, and Rapid Diagnostics; https://www.jpiamr.eu/wp-content/uploads/2019/11/K-STaR.pdf

• OASIS: One Health AMR Surveillance through Innovative Sampling;https://www.jpiamr.eu/wp-content/uploads/2019/11/OASIS.pdf

• TRIuMPH: Improving the TRIcycle protocol: upscaling to national Monitoring, detection ofCPE and WGS pipelines for One Health Surveillance; https://www.jpiamr.eu/wp-content/uploads/2019/11/TRIuMPH.pdf

• IDx: An exploration of regulatory, corporate, relational, and technical barriers to uptake ofdiagnostics in the fight against AMR; https://www.jpiamr.eu/wp-content/uploads/2019/11/IDx.pdf

The CW will ensure that OHEJP development is complementary and that potential synergies are identified.

Practicalities • Information about the upcoming cogwheel workshop was sent to all OHEJP Project leaders and

deputies and members of the Scientific Steering Board (SSB) on 19 March 2020. Information aboutJPIAMR was included.

• Five OHEJP projects (two from the integrative category; Care and OH-Harmony Cap, and three fromthe foodborne zoonose category; TOXOSOURCE, MedVetKlebs and NOVA) responded and 10 outof 12 JPIAM projects in total were identified as relevant. Five of the JPIAMR projects were invited,ensuring all OHEJP projects having at least one project of interest. All five invited JPIAMR projectsattended the workshop.

• Invitation to the CW was sent on 3 April 2020 with deadline for registration on 21 April 2020.

• Seven OHEJP and the five invited JPIAMR projects signed up with presentations at the CW. TwelveOHEJP projects were represented in total.

• The CW was held as an online meeting with 38 participants using Adobe Connect on 28 April 2020.The agenda is included in the annex.

• The meeting was recorded until lunch, and a document with link to the recorded meeting, thegiven presentations and contact information for follow-up questions was distributed one weekafter the CW.

Attendance list

Project Representatives (institution)

FARMED Manal AbuOun (APHA) Kevin Vanneste (Sciensano) Carlus Deneke (BfR)

FULL- FORCE Pieter Jan Ceyssens (Sciensano) Henrik Hasman (SSI) Benoit Doublet (INRAE) Alma Brolund (Public Health Agency of Sweden)

LISTADAPT Yann Sevellec (ANSES)

MATRIX Esther Maria Sundermann (BfR)

OH-HARMONY-CAP Nadia Boisen ( also OHEJP administration, SSI)

ORION Estíbalís Lópes de Abuchuco (BfR)

TOXOSOURCES Pikka Jokelainen (also OHEJP administration, SSI)

ADONIS Ana Amaro (INIAV) Clara Samper (VISAVET-UCM) Angela Pista (INSA)

CARE Mia Torpdahl (SSI) Mery Pina (IP)

DiSCoVeR Vicente Lopez Chavarrias (VISAVET-UCM)

RaDar Kyrre Kausrud (NVI) Madelaine Norström (NVI)

OHEJP Administration

Solveig Sølverød Mo (NVI) Kristin Pettersen (NVI) Marie Nykvist (SVA) Karin Artursson (SVA) María Ugarte Ruiz (VISAVET-UCM) Cécile Boland (Sciensano) Racha El Mounaged (Sciensano)

Other Teresa Nogueira (INIAV)

Output All OHEJP projects interested in participating in the CW had the opportunity to do so. The relevant key elements in JPIAMR, as identified by each OHEJP project, are listed below. The proposed action points from each project are listed in a separate summary table below. Meeting summary, per project Key elements in JPIAMR relevant for each EJP project:

EJP Project FARMED and APHA

• The K-STaR project seems quite appropriate for FARMED, and sharing of practical bioinformatics ideas are of interest. Also the applicability of their currently available software could be tested. Their focus seemed to be on long read sequencing of isolates / targeted metagenomics of specific species. Therefore an unbiased metagenomic approach on a complex matrix might require a different analysis approach. The machine learning in MAGITICS could be useful for FARMED also.

• Publication https://www.nature.com/articles/s41564-019-0656-6 and Software https://github.com/c2-d2/rase were also mentioned.

EJP Project FULL-FORCE

• Although there is no immediate overlap between the presented projects and FULL_FORCE, the k-mer

approach pursued by K-STaR project sounds very attractive as a follow-up action after the MedVet

groups have established their capacity for long-read sequencing.

EJP Project LISTADAPT

• No overlap with the LISTADAPT project was reported

EJP Project MATRIX

• Surveillance in One Health was identified as relevant in general

• Relevant key elements in JPIAMR were knowledge, collaboration, ensuring non-overlapping activities and AMR priorities. These key elements were also relevant for ADONIS, DiSCoVeR and OH-HARMONY-CAP.

EJP Project OH-HARMONY-CAP

• We expect that there will be no or very little overlap between OH-Harmony-Cap and the JPIAMR projects. Notably, OH-Harmony-Cap is only focusing on zoonotic pathogens and AMR for Salmonella and Campylobacter in EU. Seeing that our aim is to harmonize protocols and propose a harmonised testing strategy for Europe, the output and deliverables will be designed in such a way that they can be used in laboratories, which might be beneficial for some JPIAMR projects.

• Relevant key elements as described for MATRIX

EJP Project ORION

• No overlap with the ORION project was identified.

EJP Project TOXOSOURCES

• Networking between projects

EJP Project ADONIS, MATRIX, MOMIR-PPC and DISCoVeR (VISAVET-UCM)

• Tools, omics knowledge and One Health approach (TRIuMPH) were identified as relevant key elements.

• Some of the JPIAMR projects using ‘omics’ as the main tool to study antimicrobial resistance, such as K-STaR, are very relevant to the developing work within bioinformatics in the VISAVET project.

• JPIAMR provides complementary background knowledge to DISCoVeR, which overall aims to provide the basis for future approaches for source attribution of zoonotic foodborne pathogens and AMR. Further and deeper research in these areas will bring good ideas, and hopefully, useful solutions to the challenges posed by AMR.

EJP Project CARE

• From the presentations made by the JPIAMR projects, both MAGITICS and K-STaR might be relevant for CARE. WP2 and WP3 in CARE will be working with creation of a EURO panel of One Health reference material and the access and sustainability of well defined microbial reference material.

• Direct action points and collaboration is not foreseen as the projects are running simultaneously and with different target organisms; CARE focuses in a one health zoonotic perspective and MAGITICS and K-STaR is oriented around developing databases and tools for prediction of resistance emergence.

EJP Project RaDAR

• The projects presented had little to no overlap with RADAR, possibly methodology used in MAGITICS could be of relevance for WP1 in RADAR. However, no participants from WP1 RADAR were present at the meeting so it’s hard to tell.

• Interesting workshop and even if synergy points to current projects we are involved in not was detected, it will certainly be beneficial to have the information of the projects provided for future studies.

EJP Project OHEJP WP3

EJP Project OHEJP WP5

• JPIAMR as OHEJP stakeholder – mutual added value is obvious

Summary table Action points

Project Action points Who, when

FARMED • Contact K-STaR group to discuss possible collaboration

• Test software

• WP2 leaders (Saria Otani, Kevin Vanneste, Carlus Deneke), in the next 12 months

FULL-FORCE • None identified at this point •

LISTADAPT • None identified at this point •

MATRIX • Contact for collaboration, also relevant for ADONIS and DiSCoVeR

• Leader and Deputy Leader of each project, when relevant.

OH-HARMONY-CAP • None identified at this point •

ORION • None identified at this point •

TOXOSOURCES • Continue following the other projects for points of shared interest/synergy

• Pikka Jokelainen, Continuing

ADONIS and DISCoVeR/VISAVET-UCM

• Following up on omics knowledge. • All partners. When was not identified.

CARE • None identified at this point •

RaDAR • None as we only participated to get some general information of the projects

OHEJP WP3 • Continue following the projects for points of shared interest/synergy

• Follow up how participation will be reported by the JRPs

OHEJP WP5 • Continue following the projects for points of shared interest/synergy

• Mention/discuss this workshop at SCM

Other comments

• Even though no collaboration opportunities were immediately identified for some of the projects, insight in the JPIAMR project was confirmed interesting and relevant in general for the OHEJP projects. Also, the presentations given by the OHEJP projects is a good opportunity for updates and looking for potential synergies within the OHEJP.

• JPIAMR will arrange a workshop in November on surveillance, and OHEJP was invited to initiate further collaboration.

• Some of the JPIAMR projects were in early stages, and some outside the EU, which may have challenged the identification of relevance.

• For detailed information, the presentations were not deep enough, and sharing of a document with contact information to the presenters was requested. This way, participants could contact the relevant projects directly and get more information if relevant.

• Feedback was given on the importance of also identifying projects that do not overlap, and that collaboration is not the only aim. Learning from each other is also important.

• Aspects of the JPIAMR projects covering economy was highly appreciated.

• Considering all new approaches to omics it is suggested and appreciated working together – enhancing the possibility to do “big things”.

• Participants confirmed that the format of the meeting was satisfying.

• The EU project SafeConsume was suggested by TOXOSOURCES as relevant for the CW#6

Concluding remarks Representatives from the OHEJP were content with the cogwheel workshop. In general, no major overlaps between JPIAMR and the OHEJP projects represented were identified. The participants were happy with the online format of the meeting.

Presentations given at the meeting See Annex. The recording of the cogwheel workshop can be accessed through the following link; https://svasweden.adobeconnect.com/p99orsayzc7o/

ANNEX Cogwheel Workshop 5

One Health EJP / JPIAMR

Item Page Agenda 2 JPIAMR introduction – Laura Plant 4 iDX – Olof Lindahl 22 MAGITICS – Juho Rousu 60 K-STaR – Derek MacFadden 69 OASIS – Frank van Leth 91 TRIuMPH – Heike Schmitt 117 FARMED – Manal AbuOun 136 FULL-FORCE – Pieter-Jan Ceyssens 142 LISTADAPT – Yann Sevellec 149 MATRIX – Esther M. Sundermann 163 OH-HARMONY-CAP – Nadia Boisen 168 ORION – Estibaliz Lopez de Abechuco

TOXOSOURCES – Pikka Jokelainen 184

This meeting is part of the European Joint Programme One Health EJP. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 773830.

Cogwheel Workshop OHEJP and JPIAMR hosted by SVA and NVI, 28.04.2020

Date 28 April 2020

Venue Virtual meeting, https://svasweden.adobeconnect.com/ohejp-cogwheel-workshops/

Meeting Cogwheel Workshop OHEJP and JPIAMR

Meeting agenda

09:00-14:30 Cogwheel Workshop (28.04.2020)

09:00-09:10 Welcome and presentation of participants

9.10-11.50 Presentation of JPIAMR projects and discussion (30 min per project)

o Short introduction - Laura Plant (9.10-9.20)

o IDx – Olof Lindahl (9.20-9.50)

o MAGITICS – Jaques Corbeil (9.50-10.20)

o K-STaR – Derek MacFadden (10.20-10.50)

o OASIS – Frank van Leth (10.50-11.20)

o TRIuMPH – Heike Schmitt (11.20-11.50)

11.50 – 12.45 Presentation of OHEJP projects and discussion (5 min per project)

o FARMED – Fast Antimicrobial Resistance and Mobile-Element Detection using metagenomics for animal and human on-site tests (Manal AbuOun)

o FULL-FORCE – Full-length sequencing for an enhanced EFFORT to map and understand drivers and reservoirs of antimicrobial resistance (Pieter-Jan Ceyssens)

Agenda

One Health EJP

Grant Agreement number 773830

This meeting is part of the European Joint Programme One Health EJP. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 773830.

Cogwheel Workshop OHEJP and InfAct hosted by SVA and NVI, 22.01.2020

o LISTADAPT – Adaptive traits of Listeria monocytogenes to its diverse ecological niches (Yann Sevellec)

o MATRIX – Connecting dimensions in One Health surveillance (Esther-Maria Sundermann)

o OH-HARMONY-CAP – One Health Harmonisation of Protocols for the Detection of Foodborne Pathogens and AMR Determinants (Nadia Boisen)

o ORION - One Health Surveillance Initiative on Harmonization of data collection and interpretation (Estibaliz Lopez de Abechuco Garrido)

o TOXOSOURCES – Toxoplasma gondii sources quantified (Pikka Jokelainen)

12.45-13.30 Break

13:30-14:30 Separate meeting with only OHEJP projects, summary of discussions and follow up

www.jpiamr.eu twitter.com/JPIAMR facebook.com/JPIAMRwww.jpiamr.eu twitter.com/JPIAMR facebook.com/JPIAMR

JPIAMR: Global coordination of AMR research funding and activitiesLaura PlantJPIAMR Secretariat

One Health EJP Cogwheel Workshop 28th April 2020

www.jpiamr.eu twitter.com/JPIAMR facebook.com/JPIAMR

Uniting 28 countries to address AMR with a One Health perspective

JPIAMR: A global organisation

The EuropeanCommission (DG Research) is a full non-voting member

JPIAMR in action: achievements

Joint AMR Strategic Research and Innovation Agenda

Roadmap of Actions: calls, scientific workshops & JPIAMR-VRI activities

Identification of research priorities/gaps: R&D investment dashboard

Mapping: 1.8 B€ in AMR investments

JPIAMR Research Funding 80 M€ (61 research projects and 31 Networks)

JPIAMR-Virtual Research Institute

Global partnerships and collaborations

SRIA: Strategic Research and Innovation Agenda• Therapeutics: Discovery of new antibiotics and therapeutic

alternatives, and the improvement of current antibiotics and treatment regimens.

• Diagnostics: Development and improvement of diagnostics to improve use of antibiotics and alternatives to antibiotics.

• Surveillance: Optimisation of surveillance systems to understand the drivers and burden of AMR in a One Health perspective.

• Transmission: Understanding and preventing the transmission of AMR.

• Environment: The role of the environment in the selection and spread of AMR.

• Interventions: Investigation and improvement of infection prevention and control measures in One Health settings.

Roadmap of Actions 2019-2024

JPIAMR Open Calls

JPIAMR workshops

Transmission Workshop, September 2020

“JPIAMR Early Researchers Capacity Building Workshop”, October 2020

Final workshop for JPIAMR Networks, 4-5 November 2020

AMR Research Funding and Research Project Dashboard

58% of the total investmentis in Therapeutics

22 countries+ European Commission & Wellcome Trust

1 939Total projects

1 794 M€Total investment

87%Projects in antibiotic

resistanceDiagnostics Therapeutics Environment Transmission Surveillance Interventions

1033 M€

236 M€203 M€

134 M€ 120 M€68 M€

Basic, pre-clinical and phase 1 clinical trials

• Goal: to foster and support multi-national translational research collaborations that can accomplish more than individual countries working independently.

• 3-6 researchers per project receivingfunding from their own country committment.

• To date 61 projects awarded

JPIAMR Research Projects

Therapeutics34 %

Diagnostics10 %

Surveillance13 %

Transmission28 %

Environment9 %

Interventions6 %

JPIAMR has funded 20 Therapeutics research projects• 100 partners in 17 countries

• 25M€ invested

WHO priority pathogens

Medium (Priority 3)

Critical (Priority 1)

High (Priority 2)

Others

0 1 2 3 4 5 6 7 8 9 10 11 12

S . M A L T O P H I L I A ( G - )

V . C H O L E R A E ( G - )

B . S U B T I L I S ( G + )

H . I N F L U E N Z A E ( G - )

S . P N E U M O N I A E ( G + )

C . J E J U N I ( G - )

H . P Y L O R I ( G - )

E . F A E C I U M ( G + )

S . A U R E U S ( G + )

M . T U B E R C U L O S I S

E N T E R O B A C T E R S P P ( G - )

A . B A U M A N N I I ( G - )

K . P N E U M O N I A E ( G - )

E . C O L I ( G - )

P . A E R U G I N O S A ( G - )

no. of projects investigating pathogens

Distribution of JPIAMR funded projects on the basis of pathogens studied

JPIAMR supported research projects addressing pathogens categorised under WHO Priority

Pathogens List

Overview of funded projects in JPIAMR 1st call on Therapeutics

Treat infections caused by Pseudomonas aeruginosa

Counteract β-lactam resistance Against TB

Under clinical

development

ReceivedCARB-X support

Patent pendingCollaboration

with TB Alliance

Health care Community

Animal & Nutrition

Agriculture Pets

Environment

Water, Soil & Air

JPIAMR Transmission and Intervention funding

ONE HEALTH

Data/Advice for public healthpolicy makers and managers

Interventions & Intervention proposals

Antimicrobial Stewardship

Drug targets/drug combinations/ alternative treatments

Vaccine design

Diagnostic tests

Health care Community

Animal & Nutrition

Agriculture Pets

Environment

Water, Soil & Air

BEAT-AMR

COLL.DAM.

EmerGE-NeT

Pneumospread

Res.SP_AMR

JumpAR

AB-assist.

ImpresU Pilgrim

MACO TRA

PET-Risk

TransComp-ESC-R

ExcludeMRSA

Resilience

ReduceAMU

TransPred

HECTORSpARK

ST_131 Transm. STARCSMOD

ASBOpen

Steward

PREPARE

AwareWWTP

DAR WIN

Gene-gas

INART ARMIS

JPIAMR Transmission and Intervention funding

Call 3: Transmission Dynamics

Call 5: Prevention, Control & Intervention Strategies29 projects with a focus

on transmission and prevention of AMR

Enhance resource alignment and maximise existing and future efforts to combat AMR

• One Coordinator receiving funding from their own country committment to facilitate Networking activities.

• To date 31 Networks funded

JPIAMR: Networks

Therapeutics20 %

Diagnostics11 %

Surveillance36 %

Transmission5 %

Environment8 %

Interventions20 %

JPIAMR Networks: Global distribution partners

The JPIAMR-Virtual Research Institute Digital Platform

Connection to data Connection to people Call to action• Aggregate data• Facilitate data and information mining• Connect users to resources• Hub-like functionalities

• Facilitate people-people interactions• Connect individuals to communities• Relationships and Networking building• Visibility

• Facilitate mobilization around issues• Achieve shared goals• Outcomes

Tools DataServices Information

Search

EngineOnline discussion

forumsCapacity

Building

JPIAMR and global coordination - building partnerships

UNGA, IACG & Call for Action

G7/G20 ResolutionsEU Council Conclusions

ORGANISATIONS FUNDERS RESEARCH

INITIATIVES

The iDX Project- and some background

Olof Lindahl, Ph.D.Dept of Business Studies & Uppsala Antibiotic Center

Uppsala UniversitySweden

Overview• Who am I?

• My cross-disciplinary work in AMR– Previous research projects– Ongoing research projects– The iDX Project

• With the purpose of giving you an idea of what I/we do

• And hopefully inspire future collaboration

Antibiotic Resistance & Global Industry Decline

Innovation gap and discovery void

4L. Silver

A dying industry

Source: Graphic adapted by John Rex from Sharma & Towse, 2011

Typical view of costs and revenues in Pharmaceuticals & Diagnostics

Source: Graphic adapted by John Rex from Sharma & Towse, 2011

Reality in Antibiotics…

Previous & OngoingResearch Projects

The Beginning

DRIVE-AB (2014-2018)

Developing new economic models to stimulate

innovation, responsible use and sustainable

access of novel antibiotics to meet public health

needs.

The DRIVE-AB Consortium

The British Society for Antimicrobial

Chemotherapy

Center for Anti-Infective Agents Austria

Chatham House UK

London School of Economics and Political Science UK

Norwegian Institute of Public Health Norway

Tel-Aviv Sourasky Medical Center Israel

Radboud University Nijmegen Medical Centre Netherlands

University of Antwerp Belgium

University of Geneva Switzerland

University of Heidelberg Germany

University of Lorraine France

University of Rijeka Croatia

University of Strathclyde UK

University of Tübingen Germany

Uppsala University Sweden

Wageningen University Netherlands

Astellas Pharma Europe Ltd

AstraZeneca

Cubist Pharmaceuticals

F. Hoffmann-La Roche Ltd

GlaxoSmithKline R&D

Pfizer Ltd

Sanofi-Aventis R&D

An Interdisciplinary Consortium• Medicine• Global Health• Microbiology• Pharmaceutics

• Business Studies• Innovation Management• Economics• Law

How to drive investments in antibiotic R&D?

The Solution

TARGETED GRANTS

PIPELINE COORDINATORS

SUPPLY CM

Basic Science Phase I Phase II Phase III MarketPreclinical Generic market

Methods:• Model identification (n=35)• Internal evaluation• Stakeholder feedback

Companies won’t invest

In this project we tried to make antibiotics profitable

In essence: we tried to change the behavior of organizations

A “Swedish DRIVE-AB”

(2018)Evaluating incentive models for the development

of new antibiotics

E. Baraldi, F. Ciabuschi, O. Lindahl, S. Callegari

2018-2020(2021)

Value Creation and the roles of Business Actors in Pipeline Coordinators

F. Ciabuschi, E. Baraldi, O. Lindahl, S. Callegari

2018-2020(2021)Exploring the feasibility of an antibiotic susceptibility bonus for drugs to treat

Gram-negative infection

Developing New Incentives

A. Hollis, C. Morel, O. Lindahl

ASB Project Team

Calgary:

Geneva:

Uppsala:

Chantal MorelStephan Harbarthet al.

Aidan Holliset al.

Olof Lindahlet al.

An Antibiotic Susceptibility Bonus?

• AIM: Develop and evaluate a new policy incentive to support R&D in

ABx while ensuring long-term drug efficacy through sustainable use.

• Results: Strengths, weaknesses and implementability of an

“Antibiotic Susceptibility Bonus”

TimeAnnual sales revenues

R&D Cost

Market authorisation

Patent expiry

PIIIPIIPI

TimeAnnual sales revenues

R&D Cost

Market authorisation

Patent expiry

PIIIPIIPI

Main Questions• How measure susceptibility?

• How big a bonus?

• How ensure access to the antibiotic?

• How ensure that only useful products receive the bonus?

• Who finances it and who benefits from it?

• Is an Antibiotic Susceptibility Bonus feasible? – Or just a alluring economic construct?

2020-2023(2024)iDX: An exploration of regulatory, corporate, relational, and technical barriers to uptake of

diagnostics in the fight against AMR

Implementing Diagnostics

O. Lindahl, M. Mendelsohn, E. Dubé, V. Özenci, C. Morel,

iDX Consortium Partners

• Florence Séjourné

• Marc Mendelson

• Olof Lindahl• Chantal morel

• Volkan Özenci

• Eve Dubé

Innovation and Implementation Diagnostics for Bacterial Infection

• Combining two main strands of my previous research

• Implementation in the context of AMR – Diagnostics

• Challenging in both hospitals and clinics internationally– Problems in specific settings– But also for businesses developing them– And by extension for the Government

• Incorrect prescription of antibiotics– Effects on patients– Effects on last-resort drugs

• Caused by unavailable or ineffective diagnostic tools

Caused by unavailable or ineffective diagnostic tools?• Not necessarily…

• There is a void between what is developed and what is used in hospitals and clinics

• New diagnostic tools have been/are invented

• But their spread is alarmingly slow

• This is noted and is therefore affecting innovation

Challenging in both hospitals and clinics internationally– But challenges can be expected to be both common

and different (context-specific)

• “What are the barriers to implementation of new diagnostics for bacterial infection in different healthcare settings?”

• From both developer, regulator, and user standpoints

• Applying business and org. behavior perspectives.

Aims of the project• To identify obstacles relating to:

– The actions of firms inventing new diagnostics• E.g., the “technology-push” problem, implementation

– Differences in regulation and reimbursement• Cheaper to market follow-on products, unpredictability

of prices, hospital incentives– Culture and organizational factors in hospitals/clinics

• Importance of org. culture, attitudes, and values

– The specific context of LMICs• Laboratory infrastructure, above 3 in LMICs

Work Packages

WP1: Tech transfer and technology support– Firms, technologies, implementation

WP2: Regulation & Reimbursement– Formal rules and guidelines

WP3: Clinical Context

– Behavior in hospitals and clinics

WP4: Uptake in Rural South Africa

– Availability and use of technologies

iDX: A MAPPING EXERCISE – (UN)SUCCESSFUL CASES OF DX

Developing Firms

Regulation & Reimbursements

Hospitals & Clinics

In Europe and North America

In South Africa

Purpose• To support the decision-making of

– businesses, – policy-makers, – hospital management and clinicians

• to remove obstacles, and• better implement new diagnostics for bacterial infection.

Expected Findings• The business of diagnostics

– Reimbursement– Uncertainty– Markets

• Generic challenges– But also context-specific

• Implementation– Change management– Knowledge– Attitudes

Questions!

Thank you for listening!

MAGITICS - MAchine learning for diGItal diagnosTICS of antimicrobial resistance (2020-2022)

Jacques Corbeil, coordinatorCogwheel workshop One Health EJP & JPIAMRApril 28, 2020

Goal of MAGITICS

• To develop and apply new machine learning approaches for modelling AMR for faster diagnosis, better surveillance and prediction of resistance emergence

• To achieve a machine learning implementation that can• orient the selection of treatments by assessing the level of

resistance• provide rational for the generation of novel antibiotics, • and assist in the surveillance of human and livestock AMR around

the globe.

MAGITICS

The consortium bringstogether multi-disciplinaryexpertise• Machine Learning• NGS & Genomics• Metabolomics & mass

spectrometry• AMR mechanisms and

diagnostics• Experimental validation

MAGITICS

Jacques Corbeil

Medical genomics & metabolomics

AMRMachine Learning

Experimental validation

Jie FengAMR mechanisms

Evolution and epidemiology of

resistanceExperimental

validation

Veronique Dubois

AMRClinical diagnostics

Experimental validation

Macha Nikolski

BioinformaticsNGS

Machine learning

Juho RousuMachine Learning &

Metabolomics

Specific AimsAim 1: Generation of data sets to implement robust machine learning approaches• Next-generation sequencing of Pseudomonas aeruginosa

(Pa) and Streptococcus pneumoniae (Spn) with preciselydetermined Minimum inhibitory concentration (MIC). MIC isimportant for clinicians but often not present in current databasessuch as PATRIC

• Metabolomics of Pa and Spn and β-lactam resistance. Metabolomic responses to drug may reveal new mechanisms of resistance and thus aid more accurate diagnostics

Planned schedule: Q1/20-Q2/21

24.4.20204

Specific Aims

Aim 2: Creation and validation of AMR models using NGS and metabolite data sets• Predictive modelling of AMR using NGS and metabolomic

data. We will use multiple machine learning and data mining toolsto predict MIC and uncover the important variables for the prediction as well as elucidate the responding biologicalprocesses.

• Knowledge transfer and output with BacteriApps. The modelsand databases developed in the MAGITICS will be integrated to BacteriApps (https://bacteriapps.genome.ulaval.ca)

24.4.20205

Specific Aims

Aim 3. Experimental validation of the models to drive amelioration of the predictive models• The predictions of the important variables for AMR

(genes,SNVs, metabolites) will be experimentally validated• The goal is to reconstruct the resistance phenotype of the

clinical isolates. • This will serve as a basis for optimisation of the ML

algorithms.

24.4.20206

Proposed workflow

24.4.20207

Outputs and potential impact• Our global aim is to gain a deep understanding of AMR at a

level that will allow us to make predictions and mostimportantly, design and propose interventions.

• Our proposal is to use NGS and metabolomics data for predicting MIC instead of using standard techniques that willbe a paradigm shift if successfull.

• Our objective is to provide a data repository and analyticaltools where researchers can access our raw data and resultsin a way that conforms to the FAIR (Findable, Accessible, Interoperable, Reusable) principles.

24.4.20208

Thank you for your attention!

24.4.20209

A K-mer Based Approach for Institutional AMR Surveillance,

Transmission Monitoring, and Rapid Diagnostics

Derek MacFadden (Ottawa Hospital Research Institute, Canada)For the K-STaR Group

Allison McGeer, Mt. Sinai Hospital, Toronto;Hajo Grundmann, University of Freiburg, Germany;

Martin Antonio, MRC The Gambia.

Cogwheel Workshop – One Health EJP - April 28th, 2020

No conflicts of interest to declare.

Outline

•Background•AIMS•Methods•Potential Impact•Timeline•Questions

Background

Reardon, Nature. 2015 Olesen et al, elife. 2018

Antibiotic Resistance and Outcomes

Kumar et al. Crit Care Med 2006.

• Antibiotic resistance means delayed times to effective therapy.

• Some associations between antibiotic resistance and virulence.

• Antibiotic resistance is generally associated with:• Increased morbidity• Increased mortality• Increased hospital length of stay• Increased costs

Serra Burriell. PLOS One. 2020.

Background

A Big Issue, A One Health Issue

https://amr-review.org/

Background

Rapid Diagnostics

• Getting more rapid diagnostic information offers promise of:• Earlier effective treatment -> mortality/morbidity benefit.• Reduced (broad-spectrum) antibiotic use.

• Variety of different approaches: Culture, molecular, PCR, etc. • Often limited scope/limited pathogens/limited susceptibility.

• New sequencing-based approaches offer a one-stop shop.• BUT traditional NGS is too slow.• What about real-time long read sequencing?

Background

Rapid Diagnostics - MINION

8Brinda et al. Nature Microbiology. Accepted. 2020.

Real Time Long Read Sequencing with Rapid ID and Resistance Prediction

Background

Brinda et al. Nature Microbiology. 2020.

• Stable organism/genotype within 1-5 minutes

• Can predict antibiotic sensitivity• Works well for S.

pneumo• What about Gram - ?

• Can look at relatedness (infection control/outbreak management)

Background

Stewardship – Rapid Diagnostics

• We have a platform for rapid prediction (minutes), from primary specimens and isolates.• Can identify species, lineage/genotype, predict susceptibility,

and evaluate relatedness.• Potentially valuable tool for in/outpatient settings BUT: • The optimal use of this approach needs to be determined.• This approach needs to be validated across organisms, settings,

and regions.• This is what we have sought to do with this project.

Background

AIMSAIM1: To assemble local and international databases of whole genomes of Gram-negative organisms of global concern with associated phenotypic metadata.

AIM2: To generate local and international k-merdatabases of Gram-negative organisms of global concern that can be used for predicting antibiotic resistance phenotype as well as surveillance.

AIMSAIM3: To validate the performance of k-mer databases for predicting antibiotic resistance phenotype and genetic relatedness for infection control surveillance purposes compared to gold standard phenotype and phylogenetic relationships.

AIM4: To validate the usefulness of k-mer based approaches in the rapid identification of nosocomial transmission on high acuity units for next to real-time detection of transmission events and interventions.

Methods – Study DesignProspective Cohort Study• Samples from Colonized/Infected

Patients• High Acuity Wards/Units• Four Hospitals• Three Continents• Over 3 years

LocationsNorth America• Ottawa, Ontario• Toronto, OntarioEurope• Freiburg, GermanyAfrica• The Gambia

Methods – Sampling/Sequencing StrategyYear 1 (Database Generation): • Isolate Short Read Sequencing (Illumina) Year 2 (Validation): • Isolate Short Read Sequencing (Illumina)• Isolate Long Read Sequencing (Nano)• Specimen Metagenomic Short Read Sequencing (Illumina)• Specimen Metagenomic Long Read Sequencing (Nano)

Methods – Sampling/Sequencing StrategyGram-negative Sequencing Priority:

1. Escherichia coli2. Klebsiella pneumoniae3. Pseudomonas aeruginosa4. Enterobacter spp.5. Serratia spp.6. Acinetobacter spp.

Decreasing sample size

Methods – OutcomesSurveillance: •Maximum likelihood phylogenetic tree/distances• Pairwise genetic distances•MASH distances•MLST• cgMLST• k-mer best match/match metrics

Methods – OutcomesDiagnostics/Resistance: • Phenotypic antibiotic susceptibility• Antibiotic resistance genome loci•MLST• cgMLST• k-mer nearest neighbor• k-mer lineage prediction

Methods – AnalysisSurveillance: • Isolate and Metagenomic Short Read Sequencing (Illumina)• Construct Genetic Trees and Lineage Classifications• ML Phylogenetic tree/distances – Gold standard • MASH tree/distance• MLST• cgMLST

• Compare k-mer based placement of isolates within these genetic phylogenies/trees/lineage classifications.• Compare k-mer match metrics with quantitative measure genetic

distance.

Methods – AnalysisDiagnostics/Resistance: • Isolate and Metagenomic Short Read Sequencing (Illumina)

a) Compare AMR genotype (e.g. CARD) with phenotypeb) Compare k-mer lineage-based prediction with phenotypec) Compare k-mer nearest-neighbor prediction with phenotype

• Test characteristics of a-c. • Calculate posterior probabilities of susceptibility given prediction

results for a-c above.

Timeline

REB App ✓

Jan 2020 Jun 2020 Jan 2021 Jun 2021 Jan 2022 Jun 2022

Isolate Collection Specimen Collection

Reference DB Generation

Sequencing

Database Upload

Start Analysis

Dissemination

PENDING COVID

Knowledge Translation and Impact

• The results of this study should inform:• The use of our approach for predicting antibiotic resistance and

its viability as a tool for supporting antibiotic decision-making.• The use of this approach as a surveillance tool, and how it could

support hospital/community control efforts.• If both (or either) show further promise after this validation work,

this will form the basis for large prospective clinical trial(s). • Potential for significant impact and inversion of typical

microbiology workflow/clinical information stream.

QUESTIONS?

FRANK VAN LETH

ASSOCIATE PROFESSOR GLOBAL HEALTH

AMSTERDAM INSTITUTE FOR GLOBAL HEALTH AND DEVELOPMENT

28 April 2020 oasisresist.org 1

OASIS: project description

JPIAMR – OHEJP cogwheel workshop

oasisresist.org 2

• Aim and objectives project

• Rationale

• Concept of Lot Quality Assurance Sampling (LQAS)

• Project activities

• Envisioned outputs

Content

oasisresist.org 3

• Aim

– To provide evidence base for rapid AMR surveillance strategy

• Enabling transition to population-based surveillance

• In a One-Health context

• Widely applicable

• Objectives

– To test optimal implementation of dynamic LQAS-approach

– To validate LQAS-based AMR surveillance in veterinary domain

– To assess policy requirements for LQAS-based surveillance

– To build capacity for LQAS-based AMR surveillance

Aim and objectives

oasisresist.org 4

RATIONALE

oasisresist.org 5

Potential bias in laboratory-based surveillance data

Sugianli et al. PLoS One, 2020

oasisresist.org 6

Population-based surveillance: needs large sample size

oasisresist.org 7

Population-based surveillance: limited local relevance

Thor Alvis on Unsplash

oasisresist.org 8

LOT QUALITY ASSURANCE SAMPLING

oasisresist.org 9

• Derived from setting of manufacturing

– Quality assurance strategy

• Question posed:

– Is threshold for “adequate quality” met?

• Assessment on small number of samples

– From well-defined batches of goods

Lot Quality Assurance Sampling (LQAS)

oasisresist.org 10

Basic 2-way static LQAS approach

oasisresist.org 11

• Done in a classification framework

– Is the AMR prevalence above or below x%?

• Lot can be any well-defined grouping

– District

– Health facility

– Sub-population

• Classification ”high” AMR prevalence requires action

Lot Quality Assurance Sampling (LQAS)

oasisresist.org 12

• Threshold setting (what is high?)

– Setting

– Possibility to implement action

• Misclassification

– True “low” classified as “high” prevalence (and vice versa)

• How much is allowed?

• Equal weight?

Statistical parameters

oasisresist.org 13

Typical sample sizes

LQASdefinition

SampleSize

Decisionrule

MisclassL as H

MisclassH as L

MisclassTot

2 - 10 76 4 6.6 4.7 11.3

5 - 20 44 5 6.7 4.4 11.1

10 - 20 112 16 9.2 4.7 13.9

10 - 25 55 9 9.5 4.5 13.9

15 - 25 139 27 9.3 5.0 14.3

15 - 30 70 15 9.4 4.1 13.5

oasisresist.org 14

OASIS ACTIVITIES

oasisresist.org 15

• Population-based AMR-surveillance

– Participants suspected of UTI

– Primary care setting Togo / Burkina Faso

• Dynamic approach feasible?

– Rapid turn-around laboratory testing

– Rapid communication of results

• Extension of earlier work in Indonesia

– Static approach

1. Dynamic LQAS-based AMR surveillance human domain

oasisresist.org 16

Static versus dynamic LQAS-approach

oasisresist.org 17

• Conventional AMR survey as reference standard

– Broiler chickens

– Fattening pigs

• Lots defined by truck from single farm at slaughterhouse

– Batch sampling manure

– No mixing livestock

– No mixing farms

2. Validation static LQAS-approach veterinary domain

oasisresist.org 18

Lots in human and veterinary domain

oasisresist.org 19

Validation: combine lots in conventional estimate

5Estimated prevalence

Measured prevalence

oasisresist.org 20

• Qualitative research

– Stakeholder involvement

• Define parameters

– Knowledge utilization strategies

• LQAS-based AMR surveillance as policy of ASPs

3. Identify optimal implementation strategy

oasisresist.org 21

ENVISIONED OUTPUTS

oasisresist.org 22

• Validation of LQAS-based AMR surveillance

– Dynamic approach in human domain

– Static approach as proof-of-concept in veterinary domain

• Capacity for LQAS-based AMR surveillance

– Trained staff

– Laboratory infrastructure

• LQAS-based AMR surveillance as policy

– Stakeholder involvement

– Knowledge utilization

Outputs

oasisresist.org 23

CONSORTIUM

oasisresist.org 24

Partners

oasisresist.org 25

Where to find us

oasisresist.org @oasisresist oasisresist@gmail.com

oasisresist.org 26

Funders

Building on the WHO tricycle project: JPI TRIuMPH

Heike Schmitt

This talk JPI TRIuMPH: ● building on the WHO Tricycle protocol ● Just started (not yet in all countries) ● Therefore: ● Background: WHO Tricycle project

● JPI TRIuMPH

Context – WHO AGISAR group

● WHO Advisory Group on Integrated Surveillance of Antimicrobial Resistance (AGISAR) – Support WHO on resistance from the food chain – Integrated surveillance – Capacity building (on surveillance) – Define critically important antimicrobials – Support WHO in FAO/OIE/WHO tripartite activities and Codex

WHO Tricycle project on One Health surveillance ● Started out of the AGISAR group

Idea: ● Develop a simplified, integrated surveillance system for bacterial

resistance to antibiotics, to be implemented on a global basis ● Simplified: Based on ESBL-producing E. coli as indicator ● Integrated: One health approach including humans, food chain and

the environment

Why ESBL E. coli?

● Simplification: one species / antibiotic resistance

● Large variations between regions and in time

Woerther, 2013

One Health surveillance

• Bloodstream infections

• Healthy adults: pregnant women

• Chicken

• Human wastewater • Animal (slaughter)

wastewater • Surface water (river

up- and downstream of the city)

Capacity building ● Training workshops:

– Netherlands 2017, 2018 / Indonesia 2017 / Jordan 2019

● Country visits

Results pilot testing Outcomes • Protocol implemented in all countries • Costs are moderate (30 000 $ reagents / year) • Led to inter-sectoral interaction, triggers One Health thinking

Requirements • WHO has critical coordination role

Opportunities • Tricycle to be linked to GLASS • Implementation in more countries

Outcomes pilot – building on.. Ideas of pilot countries: • Additional endpoints, depending on countries’ interests • Interpretation of WGS data • Making use of existing sampling networks

JPI TRIuMPh

• Building on the TRIcycle protocol: upscaling to national

Monitoring, detection of CPE and WGS pipelines for One Health Surveillance

• Joint initiative of pilot countries and labs involved in method establishment

• H Schmitt, National Institute for Public Health and the Environment (RIVM) (coordinator / methods – environment / link to wastewater surveillance)

• L Armand-Lefevre, University Paris-Diderot (methods – human) (and Fondation M’erieux)

• J Wagenaar, Utrecht University (methods – animals / WGS pipelines) • R Hashim, Institute for Medical Research, Malaysia • M Salman, National Institute of Health, Pakistan • L Samison, University of Antananarivo, Madagascar

• J Matheu Alvarez, WHO Headquarters • More institutions within Malaysia and Pakistan

Consortium

Project structure

CPE Protocol development Tasks: ● Method development for all compartments Principles: ● Unified across compartments (if possible) ● Globally applicable

CPE Protocol development Method ● Direct culture from swab (human, animal) vs enrichment ● Quantification by membrane filtration (environment) Culture medium – first choices: ● MacConkey (human / animal surveillance) ● TBX / EEC (water) CPE selection ● Stability matters ● Different antibiotics, also as disks

Protocol development – difficulties ● Global availability, price restrictions ● MacConkey instead of chromogenic selective media ● But: strong differences between suppliers

WGS pipelines Tasks ● Gathering suitable tools ● Developing training material, conducting

trainings ● Joint data analysis Principles ● Open source or freely available ● Stably maintained ● Web accessible resources ● So far, focus on E. coli ● E.g. cgMLST typing, resistance genes,

virulence genes, plasmid sequence recognition

National roll-out Tasks ● Repeat Tricycle protocol ● Add CPE protocol ● In 2 regions within the participating

countries ● study trends and regional

differences Principles ● Train-the-trainer approach ● Local languages where needed

Wastewater-based surveillance Tasks ● Include samples retrieved within other

monitoring networks in Tricycle / TRIuMPH

● Specifically, polio environmental surveillance samples

● Test ESBL and CPE in these samples ● Validate WBS study regional differences Principles ● Focus on larger communities

Future.. ● CPE protocol development ● WGS pipeline development

● Train-the-trainers for regional extension

● One year sampling campaign

● Joint data evaluation

Questions?

This presentation is part of the European Joint Programme One Health EJP. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 773830.

ast Antimicrobial Resistance and Mobile-Element Detection using metagenomics for animal

and human on-site tests ( ARMED)

Project Lead: Manal AbuOun (APHA)

Deputy lead: Mike Brouwer (WVBR)

ARMED Consortium

Expertise within the consortium of

9 Institutes, 7 countries

• Public and Animal Health

• Antimicrobial resistance

• Plasmid Biology

• Whole genome sequencing

• Long read sequencing

• Metagenome sequencing

• Bioinformatics Analysis

Development of diagnostic tool for

early, real-time and on-site detection

of antibiotic resistant bacteria in

humans, animals, foodstuff or the

environment

WP 3 - Implementation of on-site protocols for long-read metagenomic DNA sequencing

• Develop harmonised protocols for ‘on-site’ extraction of DNA from sample matrices, to enable long-read sequencing• Test ONT automated DNA extraction device, VolTRAX system

• Develop a harmonised protocol for ‘on-site’ DNA sequencing library preparation.

• Deploy protocols developed in WP1, WP2, WP3 for their use on-site, within clinical and veterinary settings.

ARMED ObjectivesF

WP2 - Bioinformatics tools to analyse the sequencing data and define the characteristics within the sample.

• Establish best practice ‘off-site’ bioinformatics analyses.

• Develop efficient real-time mapping strategies to identify the origin of the genetic context • AMR genes, Microbial profiling and typing

WP1 - Assess feasibility of long-read metagenomic sequencing

• Compare metagenomic sequencing using long and short-read technologies from human, animal, food and environmental sample matrices.• Does long read sequencing (MinION) provide sufficient depth of sequencing to detect AMR and pathogen?

• Does combining Hi-C sequencing with long-read sequencing data to gain insights into AMR and bacterial species linkage, within the metagenome?

armed work plan

• Development of diagnostic tool for early and real-time detection of antibiotic

resistant bacteria in humans, animals, foodstuff or environment

• Evaluation of on-site testing

Feasibility of long-read

metagenome sequencing

(WP1 – T1, T2, T3)

Hi-C metagenomic

sequencing

(WP1-T4)

Literature review on DNA

extraction methods

(WP3 – T1)

Tool for establishing microbial

community composition

(WP2 – T1, T3)

Tool for establishing presence

of AMR genes

(WP2 – T2, T3)

Protocol for on-site DNA

extraction

(WP3 – T3)

Protocol for on-site Voltrax

DNA extraction

(WP3 – T2)

On-site DNA extraction and long-

read sequencing from

metagenomic samples

(WP3 – T4)

Protocol for on-site long-read,

sequencing and analysis

(WP3 – T2, T3)

Annual communication to stakeholders

OH EJP coordinators

(WP4 – T4)

Training workshop

(WP4 – T3)

• Bioinformatic analysis• Develop tools that can be used ‘on-site’

• Establishing ‘off-site’ bioinformatic standards for the analysis of short and long-read metagenomics sequencing data

ARMED: Expected One Health impactF

• Molecular methods• DNA extraction techniques and/or targeted enrichment of

metagenomic samples on-site

• Integration of these techniques into standard practice.

• Rapidly testing the metagenome from different settings

• On-site metagenomic sequencing will revolutionise the battle against pathogens and AMR

• Provide the clinician or veterinarian with real-time AMR profile to aid treatment options

This presentation is part of the European Joint Programme One Health EJP. This programme has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 773830.

Manal.AbuOun@apha.gov.uk

Full-length sequencing for an enhanced EFFORT to map and

understand drivers and reservoirs of antimicrobial

resistance(FULL_FORCE)

Pieter-Jan Ceyssens

JRP – AMR 2.2

pieterjan.ceyssens@sciensano.beBerlin, November 13, 2019

• Responsible Partner: SCIENSANO

• Contributing partners: ANSES, INSA, BfR, DTU, APHA, INIA, INRA, ISS, PIWET, PHAS, SSI, RIVM, SVA, WbvR, NVI (+ UU, IZSLT, UG)

Consortium

• More and more countries rely on WGS for surveillance of AMR

• Large sequence collection were generated in COMPARE, EFFORT, ENGAGE, and other projects

• Mobile Genetic Elements (MGEs) often encode resistance to critical antibiotics, and can spread within or across species and genera

• MGEs remain challenging to reconstitute due to their chimeric, modular and repetitive nature.

Background

Solution : Long-read sequencing & Hybrid assemblies

WHAT NATURE THINKS IT LOOKS LIKE

HOW REALITY LOOKS LIKEHOW THE ACTUAL DATA LOOKS LIKE

WHAT THE COMPANY SAYS IT LOOKS LIKE

Full Force : Objectives

Expected One Health impact

• Capacity building for SMRT sequencing across EU

• To dissect clonal from horizontal transmission of AMR genes by broadly introduce single

molecule real-time (SMRT) sequencing in EU veterinary and public health institutes

• To apply this knowledge on six study cases, incl. samples isolated in the context of

national surveillance programmes, EFFORT and ARDIG projects.

• Hopefully : levelling the field for a future strategy for EU AMR surveillance, including

effective integration of MGE tracking in veterinary and public health

pieter-jan.ceyssens@sciensano.be

LISTADAPT- An update(Adaptative traits of Listeria monocytogenes to its diversse

ecological niches)

(Institute logo)

Listeria Monocytogenes

Ubiquitous saprophyte & facultative intracellular pathogen

Widely distributed in the environment Soil, water, vegetation

Manufacturing environment persistent strains that have found a

harborage site within the facility where it may reside for years

Capable of growing at T < 4°c

Still a problem for public health

High mortality rate (12,7%) (EFSA 2019)

EFSA’s opinion of the increase incidence of listeriosis at EU-level (EFSA

Performant epidemiological investigation (Moura et al., 2016)

Knowledge population structure in food (Henri et al. 2016, Maury et al., 2016) , in human (Maury et al., 2016)

Knowledge on virulence: role of CC (strain-specific virulence difference) (Maury et al.,

Far less is known on adaptation in environment, farm, industry (despite numerous

investigation on persistence in industry)

Partial knowledge about the genetic factor linked to adaptation to the different

ecological niches of Listeria

State of the art

4 Objectives

1. Decipher genetic traits linked to adaptation in various

ecological niches

2. Generate a database of 3000 genomes (mainly farms

environment, wild animal, food and human)

3. Develop and implement cutting-egde methodologies

(new phenotypic analysis, GWAS)

4. Make available common resources for European

research

LISTADAPT: Adaptive traits of Listeria monocytogenes to its

diverse ecological niches

LISTADAPT

Which genes are involved in the adaptation of

Listeria monocytogenes to

its diverse ecological niches

WP1-Constitution of

the straincollection

WP2-WGS Consitution of the genome

collection

WP3-Phenotypic

WP4-Genetic traits

underlyingadaptation

WP5-Training, Dissemination

Valorisation

Sequences

Strains from farm- and- wide animals

)Bear (IT)

LISTADAPT consortium partners

6 European countriesAT, CZ, IT, FR, NO, SE

Search for externalpartners

8 European countriesCZ, IT, FR, CH, ES, FI, PL, SI

Strain collections published :

DE, ES, FI, FR SI

Strain collections not published :

BE, DE, CZ, EE, FI, LT, NL, PT, SK

Strains

• Wild and farm Animals (725 strains)• Wild and fariming environement (222 strains)• Food (776 strains)

MLST clonal complex

Animal and

environmental

strains

Food strain

Difference ENV-

-11,8C

Genetic diversity results

Distribution study of the CCs between food and animal and environment compartments

Marked distribution of CCs between both compartments

Higher diversity observed in the environment and animal compartment

Some CCs like CC6, CC26, CC77 and CC224 were observed in equivalent proportion (p-value > 0.1)

191 strains

Isolated from

1987 to 2018

C2 - 96 strains

RTE food

Fish food products (25)

CCs: 121, 9, 155, 2, 8, 6

Country: FR, SW, CZ

Year: 2002-2015

RTE meat products (23)

CCs: 121, 9, 1, 2, 8, 6

Country: FR

Year: 2005-2014

Dairy products (25)

CCs: 1, 2, 21, 217, 37, 4, 6, 7

Country: FR, SI

Year: 2005-2017

Other foods (including composite dished and

vegetables) (23)

CCs: 1, 121, 2, 37, 6

Country: FR, UK

Year: 2005-2017

C1 - 95 strains

Environmental/

animal

Cattle (healthy/ill) (14)

Farm Animals

CCs: 11, 412, 77, 54, 59, 1, 9, 315, 2, 14, 451, 8, 20, 29, 26, 220, 224, 5, 412, 36

Country: FR, CZ, LV, NL, SI, SP, SW, UK, FI

Year: 1987-2018

Sheep/goat (healthy/ill) (11)

Swine (2)

Game and wild animals (32)

Wild Animals

CCs: 1, 121, 7, 11, 21, 59, 4, 26, 412, 220, 31, 315, 14, 29, 36, 451, 4, 37, 9, 18, 184

Country: CZ, DE, FI, IT, NO, SE, SI

Year: 1998-2018

Farm and natural envs(water, meadow, soil)

CCs: 1, 11, 121, 14, 18, 20, 21, 220, 26, 37, 4, 451, 5, 54, 59, 6, 7, 77, 8

Country: CZ, DE, FR, IT, PL, SW, UK, FR, AT

Year: 2004-2017

From the top 6 CCs found in each category

From the most prevalent CCs in env

(WP4 task 1)

Strains selection from the LISTADAPT collection

Phenotypic characterization

1. Antibiotic and biocide resistance profiles

2. Adaptation to biocides

3. Strain adhesion and biofilm formation

4. The effects of biocides on strains in biofilm

5. Survival and persistence of strains in differentecological niches

-In food products and gastro-intestinalenvironment

-In soil microcosm

Strain1

Strain2

GWAS tools Assembly and annotation of the

genome (Artwork)

ROARY (V. 3.12.0)

Correlate genome annotation with

sequence

Gene presence absence matrix

Determination of the core and pan

genome

Differentiation of variants of a same

Scoary (V. 1.6.16)

From the pan genome, calculate

the association of a gene to a

phenotype.

Pyseer (V. 1.3.4)

Association based on variable

length k-mer

No specific genetic factor can be associated to soil survivability in the whole collection

No specific factor in the lineage 1 and 2

Soil survivability in Listeria have multiple genetic factor that are associated with the different CC.

Strain of the phenotype 1 contain additional genes absent in phenotype 3, mostly phage related genes.

GWAS results on soil survivability

Phenotype 3: more than 5%

Phenotype 1: less than 2%

Phenotype 2: 2% < survival rate < 5%

Presence of a large phage insertion (17 genes) in the strain from phenotype 1.

this phage contain 7 proteins matching the phage LP-030-3.

This phage is absent from the strain of phenotype 3

This phage in integrated in the genome inside the comK locus. It has been

show to have significant impoact on stress resistance (rabinovitch, 2012)

The transcritionnal regulator BlgG is inactivated by an insertion of 8 “T” and

splinted into 2 separate genes (MtlR_4 and cmtB_2)

Vegetables: the phenotype 3 present several large cluster of genes

corresponding to transposon (plasmid and transposon TN3)

Gwas on soil survival

Investigate phage diversity at the comK locus

Functional analysis of associated CDSs

Detailed screening of plasmids and transposons

Test phenotype prediction based on phylogeny

Gwas on the biofilm formation data and intestinal tract survivability.

Perspectives

Special thanks to

Anses Salmonella & ListeriaBenjamin FelixYann Sevellec

LISTADPT consortium partnersAGES (AT)VRI (CZ)INRA (FR)NVI (NO)ANSES (FR)IZSAM (IT)SVA (SE)DTU (DK)

External partnersVetSuisse (CH)Munich University (DE)Freie Universität of Berlin IHMT (DE)VetLab (EE)NEIKER (ES)University of Helsinki (FI)French Institute for Pig Industry (FR)Veterinary faculty of Zaghreb (HR)BIOR (LT)VWA (NL)Szczecin University (PL)INIAV (PT)Veterinary faculty of Ljubjana (SI)Public Health England (UK)

Ploufragan laboratoryAnses genomic plateform

Yannick BlanchardPierrick Lucas

Fabrice TouzainAurélie Leroux

MATRIX: CONNECTING DIMENSIONS in ONE-

HEALTH SURVEILLANCE

Esther M. Sundermann, BfR

(WP 5 leader)

• A Joint Integrative Project (JIP) under the EJP One Health

• Aims to:

Establish a practical roadmap for adopting One Health Surveillance

(OHS) by building onto existing surveillance structures or

implementing new structures, tailored to different levels of financial

and infrastructural conditions

• Does not aim to:

Describe OHS, harmonize OHS, propose ‘one-size-fits-all’ scenario,

collect or analyse data, work across borders…

MATRIX

• A roadmap to future develop or implement national OHS activities

• The roadmap considers different levels of infrastructural and

economic capacities

• The roadmap is based on a self-assesment of OHS capacities

(EUEpiCap tool)

Roadmap

Input & output

MATRIX

ECDC & EFSA

- Databases

- Projects

- Knowledge

- Guidelines

- Inventories

- Glossary

- Knowledge Hub

COHESIVE

- Data collection& analysisplatform

- Guidelines

National OHS (full structures/ components)

Overview of

surveillance frameworks

and identification of best

practicesEUEpiCap tool:

characterise OHS capacities

Roadmap to further develop or

implement OHS (at different

levels of infrastructure and

economy)

Pathogen-specific tracks: Campylobacter, Salmonella, Listeria, Emerging Threats (e.g. AMR)

THANK YOU FOR YOUR ATTENTION!

One Health Harmonisation of Protocols for the Detection of Foodborne

Pathogens and AMR Determinants

OH-Harmony-CapHarmonised protocols and common best practice

Nadia Boisen

nbo@ssi.dk28 April 2020

Cogwheel Workshop

• Project leader: Nadia Boisen (SSI)

• Deputy leader: Flemming Scheutz (SSI)

• 15 partners across 11 countries

• Project group: ANSES, INSA, ISS, RIVM, SSI, and Teagasc

Consortium

Overview

• Collect laboratory information on current capabilities,

capacities and interoperability

• Quantitative description of current and best practices and

the development of harmonised protocols

• Identify and possibly close the gaps and suggest future

studies of how best to detect and characterise food borne

pathogens across the OH sectors.

OHLabCap laboratory

interoperability

guidance

harmonised

protocols

Increase the

EU capacityWP2 WP3 WP4 WP5

Objectives

Develop a Benchmarking Instrument OHLabCap

• Overview and general description of the microbiology

system in the OH-field

• Survey OH laboratory capability, capacity and

interoperability

• National Reference Laboratories and Primary diagnostic

laboratories

• Detection and typing of priority foodborne bacterial

pathogens, parasites, and AMR for Salmonella and

Campylobacter

Objectives

One Health laboratory interoperability

guidance for model organisms

Propose new studies and methods

a) The best-practice in sampling and testing

b) Characterisation of methods

c) Data management of harmonised reporting

Objectives

Design harmonised protocols for model

organisms

• Collect and assess the laboratory protocols

• Design harmonised protocols upon review of the

collected protocols and literature

Objectives

Increase the EU capacity to deal with foodborne

zoonoses, antimicrobial resistance and emerging threats

across OH interface

• Workshop for communicating and discussing the

outcome of the OHLabCap survey

• A joint meeting between CARE, OH-Harmony-Cap, and

MATRIX

• Practical workshops and e-learning activities dedicated

to the harmonised protocols

This presentation is part of the European Joint Programme One Health EJP. This project has received funding from the European Union’s Horizon 2020 research and

innovation programme under Grant Agreement No 773830.

ORION Knowledge Hub

webinar

Estíbaliz López de Abechuco,

Matthias Filter

28.04.2020

The JIP Project “ORION”

One health surRveillance Initiative on

harmOnization of data collection and

interpretatioN (ORION)

3 years (2018 – 2020)

13 partners from 7 countries

ORION’s Mission Statement

The ORION project aims at establishing and

strengthening inter-institutional collaboration

and transdisciplinary knowledge transfer in the

area of surveillance data integration and

interpretation, along the One Health (OH)

objective of improving health and well-being.

ORION’s Work Plan

Animal health surveillance

Public health surveillance

Food safety surveillance

REPORTING

The OHS Codex Framework

The OHS Codex „Umbrella“

Codex document: https://oh-surveillance-codex.readthedocs.io/en/latest/index.html

The OHS Codex – a living resource

Codex document: https://oh-surveillance-codex.readthedocs.io/en/latest/index.html

This presentation is part of the European Joint Programme One Health EJP. This programme has received funding from the European Union’s Horizon 2020 research and

innovation programme under Grant Agreement No 773830.

ejp-orion@bfr.bund.de

Estibaliz.Lopez-de-Abechuco-Garrido@bfr.bund.de

#TOXOSOURCES Toxoplasma gondii sources quantified

Pikka Jokelainen

DVM, PhD

Project leader

PIJO@ssi.dk

Twitter: @PikkaJokelainen

Statens Serum Institut,

Denmark

Parasitesand antimicrobial resistance

Toxoplasma gondii

High disease burden worldwide and in Europe (WHO-FERG; Havelaar et al, 2015)

North: Denmark (DTU, SSI) Sweden (SVA, SLV), Norway (NVI, FHI)

East: Poland (PIWet), Czech Republic (VRI, NIPH)

South: Italy (ISS), Spain (VISAVET-UCM), Portugal (INSA, INIAV)

West: The Netherlands (RIVM, WBVR), France (ANSES),

Germany (BfR, RKI, FLI), UK (UoS)

External: Latvia (BIOR), Ireland (CVRL), Norway (NMBU),

France (BRCT and NRCT), Greece (AUTh),

Romania (UASVMCN), China (HZAU, JLU)

TOXOSOURCES - Toxoplasma gondii sources quantified

Joint Research Project within H2020 OneHealth EJP

Project Leader: Pikka Jokelainen, SSI, Denmark; PIJO@ssi.dk

Co-Leader: Joke van der Giessen, RIVM, the Netherlands

#TOXOSOURCES: What are the relative contributions of the different sources of T. gondii infections?

Different approaches, including modelling and new methods

PIJO@ssi.dk

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