Multiserology via Microarray Meemken, D. 1 ; Pingen, S. 2 ; Greiner, M. 2 ; Blaha, T. 2 1 Freie Universitaet Berlin, Germany 2 University of Veterinary Medicine, Hannover, Germany
At a glance Why multi-serology? Concept of multi-serology Microarray Future Perspectives 2
Why multi-serology? Aims of the European food safety strategy Improvement of: + + food safety animal health animal welfare Demand for monitoring programmes to identify zoonotic pathogens in pig herds (Regulation (EC) No 854/2004) Food chain information: including samples taken in the framework of the monitoring and control of zoonoses and residues. (Regulation (EC) No 853/2004) 3
Why multi-serology? Scientific Opinion EFSA (2011): Most relevant biological hazards in the context of meat inspection Salmonella Trichinella Yersinia Toxoplasma https://commons.wikimedia.org/wiki/file:salmonella_bacteria_(5613656967).jpg https://commons.wikimedia.org/wiki/file:yersinia_pestis_bacteria.jpg?uselang=de https://commons.wikimedia.org/wiki/file:trichinella_larvaeg.jpg?uselang=de 4
Concept of multi-serology 5
Concept of the multi-serology Collection of blood samples in the herds -> stress, pain, risk of infection -> bleeding is veterinarian work only -> additional manpower needed v. Altrock Collection of blood or muscle samples at the slaughter line -> no risks for animal health, lower costs, no stress or pain for the animals -> well-established working process because of the Salmonella monitoring -> no additional manpower needed 6
Concept of multi-serology Sampling (blood during bleeding) Sampling (diaphragm pillar) Serum Meat juice Testing via microarray Multi-serological livestock profile Zoonotic agents Pig disease pathogens Epizootic agents 7
Choosen agents for simultaneous serological testing Zoontic agents Salmonella spp. Yersinia enterocolitica Toxoplasma gondii Trichinella spp. Pig disease agents Influenza A-Virus Mycoplasma hypneumoniae Actinobacillus pleuropneumoniae PRRSV Hepatitis E-Virus 8
Microarray: test procedure One drop of - meat juice or - serum Detection of antibodies against: - zoonotic pathogens & - pig disease pathogens Computer-based test evaluation Test duration for simultaneous detection of 9 targets: 1h 45 minutes 9
Test procedure meat juice blood serum centrifugation 5min 4000U/min dilution: 1:2 dilution: 1:20 Ready to use in the microarray 10
Initial challenges: - Unspecific bindings Unspecific bindings caused by using the wrong conjugate Positive controls Negativ controls 11
Initial challenges: - Clouds Clouds caused by using wrong washing solution 12
Successful detection: - Salmonella antibodies Meat juice sample of S. Typhimurium infection trial (Dr. Szabo, BfR) Positive control S. Typhimurium 13
Successful detection: - Trichinella antibodies & - HEV antibodies Meat juice sample from the German Reference Laboratory for Trichinella (Dr. Nöckler, BfR) Positive control Trichinella HEV 14
Comparable results meat juice (dilution: 1:2) blood serum (dilution 1:20) Microarray works with serum & meat juice! 15
Microarray Computer-based test evaluation (Iconoclust ) 16
Pathogen specific cut-off determination with ROC curve tool to calculated the optimal cut-off value comparison of single-elisa results vs. microarray results sensitivity and specificity, test accuracy ROC-Kurve / SIV_02 / AUC=0,457 1 0,9 Echt-positive Rate (Sensitivität) 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0,1 0 0 0,2 0,4 0,6 0,8 1 Falsch-positiv-Rate (1 - Spezifizität) ROC- curve Salmonella ROC- curve for Influenza 17
1 ROC-analysis: - zoonotic pathogens 0,8 0,6 0,4 0,2 sensitivity Sensitivity speciticity Specificity 0 18
ROC-analysis: - pig disease pathogens 1 0,8 0,6 0,4 0,2 sensitivity Sensitivität speciticity Spezifität 0 19
Usability of multi-serology As continuous monitoring system for zoonoses & production diseases Generating serological herd profiles (e.g. 60 samples/herd/year) Benchmarking herds for their infectious status Detecting changes of infectious status of herds over time Identifying regional infection patterns As information tool for the stakeholders in the food chain: - State veterinarians responsible for food safety and meat inspection - State veterinarians responsible for animals health and animal welfare - Slaughterhouse operators - Farmers and their consulting veterinarians -> multi-serology: tool for risk-based decisions alomg the food chain 20
Usability of serological herd profiles at herd level 100 100 Seroprevalence 75 50 25 Salmonella Yersinia Toxoplasma Trichinella Seroprevalence 75 50 25 Salmonella Yersinia Toxoplasma Trichinella 0 0 3rd qu 2012 4th qu. 2012 1st qu. 2013 2nd qu. 2013 3rd qu. 2013 3rd qu. 4th qu. 1st qu. 2012 2012 2013 2nd qu. 2013 3rd qu. 2013 Herd A high risk for Toxoplasma and Yersinia -> preferred for cooked pork products Herd B low risk for Salm., Yers. and Toxoplasma -> preferred for raw pork products 21
Usability of serological herd profiles along the food chain Salm. Yersinia Trichin. Toxopl. PRRSV M. hyo H1N1 H3N2 73% 0% 0% 20% 1% 63% 10% 92% Targeted herd investigation - source of Salmonella infection - optimizing C&D Visual meat inspection/ logistic slaughter - reducing cross contamination Use of meat - no raw meat products Tageted herd investigation - occurrence of cats in the barn Use of meat - no raw meat products Targeted diagnostic measures - necropsy, slaughter check, histology, PCR Reassessment of vaccination scheme - time of vaccination Herd investigation: reasons for low seroprevalence - implementation of these good measures in other herds 22
Conclusion Meat juice and blood serum are equally suitable specimens Only a small amount of antigen is needed Test duration is comparable to ELISA tests Possibility to test up to 100 different pathogens via microarray Good test acuracy for antigens validated for ELISA-Tests Approach agrees the demand of the EU Food Safety Strategy 23
Future Perspectives Project Multiserology via Microarray Extending of the test procedure for: - other zoonoses and production diseases Automation on 96-microtitre plates: - increased analyze rate - standardised sample handling - easy and fast sample processing - cost-efficiency 24
Thank you! 25
Come to Berlin in 2019. Tear down interdisciplinary walls One Health 26