WP7 aims at designing and validating microbial communities – or microbiome-tailored actions to reduce antimicrobial resistance (AMR) and enhance safety and recycling potential of plants, poultry, pigs, aquaculture and marine fish productions.
WP7 will answer the following specific questions:
- How does AMR spread and evolve across all actors of the CIRCLES food chains?
- What characterizes the microbiomes of workers and environments such as wastewaters, sediments, soil and air linked to the CIRCLES food chains?
- To what extent we can reduce and control AMR across food chains by microbiome-tailored integrated circular actions?
- What is the effect of the CIRCLES microbiome-tailored circular actions on the microbial communities of food chain workers, their cohabitants and household surfaces?
- Can the CIRCLES microbiome-tailored actions modulate environmental microbial communities in wastewaters and sediments to enhance safety and recycling potential across all food chains?
WP7 is a horizontal. It will combine microbiome and metagenomics approaches to monitor AMR and pathogens occurrence, transmission, and evolution across each reservoir of CIRCLES food chains, including feed, animals, plants, soil, air, wastewater, food, and workers.
Food chain environmental metagenomes such as wastewaters, sediments and soil will also be explored with the specific aim to improve recycling and safety measured as diminished release of environmental pollutants (e.g. heavy metals and greenhouse gases) and increase of azote and phosphor recycling among other key indicators.
In addition, metagenomes from food chain workers, cohabitants and household surfaces will be explored with particular attention to metagenome markers of safety and health such as diminished AMR occurrence and increased disease resistance, among others.
WP7 will generate microbiome and metagenomics data by combining next-generation sequencing (NGS) and culturomics approaches and using state-of-the-art bioinformatics tools. WP7 data analysis will draw on the WP leaders’ and partners’ experience in developing and maintaining bioinformatics pipelines (www.genomicepidemiology.org) widely used globally.
- Expected impacts
By improving knowledge on AMR and microbiomes dynamics in plant, meat and fish food systems, WP7 will lead to the discovery of association of specific food system microbiomes with the food chain productivity, quality, safety and sustainability.
This will boost productivity, which is critical to meet the food demands of a growing world population, while supporting increased welfare for production animals and food chain workers and mitigating the negative impact of current food systems on climate.
D7.1: Report on resistome dynamics and evolution across actors of CIRCLES food chains, observation phase (M39)
D7.2: Report on environmental metagenomes across CIRCLES food chains, observation phase (M39)
D7.3: Report on workers metagenome in CIRCLES food chains, observation phase (M39)
D7.4: Report on workers metagenome in CIRCLES food chains, intervention phase (M58)
D7.5: Report on impact of circular microbiomes-tailored interventions on resistome dynamics and evolution actors of CIRCLES food chains (M58)
D7.6: Guidelines for circular microbiomes-tailored interventions for AMR reduction (M58)
D7.7: Report on impact of circular microbiomes-tailored interventions in term of food chains environmental metagenomes amelioration (M58)
D7.8: Report on guidelines for circular microbiomes-tailored interventions to modulate environmental metagenomes for improved recycling & safety (M58)
Discovering the microbiomes that foster food system sustainability in the animal, human and environmental systems to meet the aims of the One Health vision. – Frank Møller Aarestrup, WP leader
- Contact details
Frank Møller Aarestrup (email@example.com), Technical University of Denmark, Denmark
Valeria Bortolaia (firstname.lastname@example.org), Technical University of Denmark, Denmark
Partners: University of Bologna (IT), Norwegian Veterinary Institute (NO), Eurovix (IT), University of Dundee (UK), MS Biotech (IT), University of Thessaloniki (GR), Luxembourg Centre for Systems Biomedicine (LU), Wellmicro (IT)