Metagenomics in food safety: What's the added value? Case studies from the livestock sector in Tanzania and Uganda
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Presentation by Silvia Alonso, Kristina Roesel, Stephen Opiyo, Francesca Stomeo and Delia Grace at the FAO Regional Meeting on Agricultural Biotechnologies in Sustainable Food Systems and Nutrition in sub-Saharan Africa, Addis Ababa, Ethiopia, 22–24 November 2017.
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Metagenomics in food safety: What's the added value? Case studies from the livestock sector in Tanzania and Uganda
- 1. Metagenomics in food safety: What’s the added value? Case studies from the livestock sector in Tanzania and Uganda Silvia Alonso, Kristina Roesel, Stephen Opiyo, Francesca Stomeo, Delia Grace FAO Regional Meeting on Agricultural Biotechnologies in Sustainable Food Systems and Nutrition in Sub-Saharan Africa Addis Ababa, Ethiopia, 22-24 November 2017
- 2. Main campuses: Nairobi, Kenya and Addis Ababa, Ethiopia Offices in 14 other countries ILRI offices
- 3. ILRI resources 2017 • Staff: 670+ • Budget: about US$80 million • Senior scientists from 39 countries • One third of ILRI staff are women • Main campuses in Kenya and Ethiopia, and offices in 14 other countries around the world
- 4. CIMMYT Mexico City Mexico IFPRI Wash. DC USA CIP Lima Peru CIAT Cali Colombia Bioversity International Rome Italy AfricaRice Cotonou Benin IITA Ibadan Nigeria ILRI Nairobi Kenya Addis Ababa, Ethiopia World Agroforestry Nairobi Kenya ICARDA Beirut Lebanon ICRISAT Patancheru India IWMI Colombo Sri Lanka IRRI Los Banos Phillippines WorldFish Penang Malaysia CIFOR Bogor Indonesia CGIAR Research Centres
- 5. Safe Food, Fair Food project 2010-2015 (2 phases) • Assessing health risks associated with animal source foods in low income countries • Identification and evaluation of risk management interventions”
- 6. Risk assessment and biotechnologies 1 Hazard identification Hazard characterization Exposure assessment Risk characterization Risk communication What harm does it cause? How does harm depend on dose? Can it be present in food? Can it cause harm? How and to what extent does it get from source to victim? What is the harm? What is its likelihood? Participatory methods fit well Risk assessment framework: Codex Alimentarius Commission
- 7. METAGENOMICS “The study of communities of known and unknown microbial organisms (bacteria, viruses, parasites) directly in their natural environments, through the study of their entire genetic information, bypassing the need for isolation and lab cultivation of individual species”. Aims of metagenomics in SFFF project: • to develop a catalogue of microbe species/groups present in different food value chains • In terms of sensitivity, can genomic approaches complement or even substitute conventional microbiology in food safety hazard identification? • How applicable and economically feasible are these new approaches in resource-poor settings of low-income settings.
- 8. Food safety in milk Milk from pastoralist and smallholder farms in Tanzania • Household milk • Individual cow’s milk
- 9. Food safety assessment - MILK Conventional microbiology Hygiene indicators Total bacterial count Enterobacteriaceae count Pathogens Listeria spp. Salmonella spp. CP Staphylococcus spp. Mastitis pathogens Staphylococcus spp. Escherichia coli Food safety hygiene standards 50% samples Listeria 0% samples Salmonella All samples carriers 35% S. aureus 13% E.coli 51% S. epidermidis
- 10. Food safety assessment - MILK 16S Metagenomics* * Caporaso et al (2012). Performed using the Illumina MiSeq Platform 0 2 4 6 8 10 12 14 16 18 20 Relative abundance of bacteria (Genus) in household milk from Morogoro, Tanzania Household milk Alonso et al, upcoming
- 11. Food safety assessment - MILK 16S Metagenomics* * Caporaso et al (2012). Performed using the Illumina MiSeq Platform 0 2 4 6 8 10 12 14 16 18 20 Relative abundance of bacteria (Genus) in household milk from Morogoro, Tanzania Household milk0 5 10 15 20 25 30 35 40 Lactococcus Weissella Sphingomonas Acinetobacter Enterobacter Unclassified Others Staphylococcus Macrococcus Streptococcus Pseudomonas Leuconostoc Erwinia Plesiomonas Vagococcus Serratia Enhydrobacter Microvirus Tolumonas Kurthia Viridibacillus Clostridium Trabulsiella Methylosinus Citrobacter Bacillus Kocuria Corynebacterium Curtobacterium Streptomyces Pseudomonas Enterococcus Calothrix Bradyrhizobium Cupriavidus Klebsiella CandidatusBlochmannia Thermogemmatispora Escherichia Alkaliphilus Aerococcus Turicibacter Yersinia Lactobacillus Rhodoferax Relative abundance of Bacteria (Genus) in milk from Morogoro, Tanzania Household milk Cow's milk Alonso et al, upcoming
- 12. Food safety - PORK – Highest per capita consumption in EAC (3.4 kg) – Explosion in pig numbers over the past 30 years (0.19 to 3.2 million pigs) – Mostly in hands of smallholders – “piggy bank” – 70% consumed in urban areas – “pork joint” phenomenon
- 13. Food safety assessment – Pork • 88 pork samples (fresh and processed) from 31 butcheries (Kamuli & Mukono districts) • Total aerobic counts • Metagenomics - 16 samples excluded (poor DNA quality) • Illumina MiSeq libraries preparation and sequencing • Denovo assembly and blast queries
- 14. Food safety assessment – Pork Total bacterial count: All fresh pork and ca. 50% of the processed pork: above national food safety standards Metagenomics: Ca. 300 bacteria genus including pig pathogens (i.e. Brachyspira spp., Haemophilus spp., Mycoplasma spp.) potential foodborne zoonoses (i.e. Bacillus cereus, Campylobacter coli, Clostridium botulinum, Escherichia coli, Yersinia enterocolitica, Staphylococcus aureus etc.) occupational zoonoses (Erysipelothrix spp., Streptococcus suis) and anthropozoonoses (Mycobacterium tuberculosis) Blast queries showed no hits for parasitic and viral diseases (Descriptive and spatial analysis still ongoing) Roesel et al, upcoming
- 15. Main messages • Comprehensive overview of microbial flora in food • As screening process on food safety (finds more, but may miss some…) • Could aid pathogen discovery • Lots of info - enormous “untapped” potential • Substitute for conventional microbiology? • Does not speak about “viable” cells • May not detect microbes in small amounts (Salmonella, Listeria) • Rather a “complement”
- 16. Main messages • Practical aspects: – Not necessarily faster, but could be if equipment and expertise are in place – Overall costs (long run) may be similar or even smaller – Requires “highly-specialized” expertise for processing and data analysis
- 17. This presentation is licensed for use under the Creative Commons Attribution 4.0 International Licence. better lives through livestock ilri.org
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