In the farms, we are sampling and sequencing animal faeces, feed and water, the air inside and outside the houses, soil outside the houses, faeces of the farmers and production wastes. At the slaughterhouse, we are sampling and sequencing meat products obtained from the animals investigated at the farm, food contact surfaces and environmental samples. The variables we are registering during samplings are the animal production parameters, temperature and relative humidity inside and outside the farm, feed conversion rate, animal body weight gain, animal mortality, use of whatever additive and antimicrobial for the animals or the litter, application of biosecurity measures, slaughtering time of the tested animals, cleaning procedures at the slaughterhouse, meat quality and microbiological parameters.
When all the results obtained by sequencing the animal microbiomes, the farm microbiomes, the farmer microbiomes, the food microbiomes and the microbiomes circulating in their surrounding environments will be available they will be analyzed to see which microorganisms and functional genes they contain. However, these results will be not considered as self-standing but always in connection with the variables registered when the poultry and swine samples have been collected by using quantitative models. The framework for quantitative models to correlated production and environmental variables to circulating microbiomes exists but to a large extent these models lack structured data on both animal and food microorganisms as those we are collecting in CIRCLES.
As results of our work of modeling sequences and categorized variables as well as groups of microbiomes and categorized variables we are sure to see trends, clusters, matchings coming out from our dataset to clarify on one hand which variables really affect keystone species or microbial communities supporting both animal health and food safety and, on the other hand, which variables can predict dysbiosis or some negative scenarios, such as infections in the animals requiring treatments or growth of foodborne pathogens in the meat.
We’ll make predictions based on data collected in real animals and meat products, sampled in commercial situations. This is not the end of the story because all our predictions will start to be validated back in the real poultry and swine meat companies in a couple of years. Hopefully, these predictions will be exploited at commercial level as new Smart Microbiome Food Products (SMFPs) with innovative Microbiome Transparent Labels (MTLs) for the poultry and swine food chains.
For centuries scientists tried to improve animal productivity, food quality and safety testing. CIRCLES will support improvements in productivity, quality, safety and sustainability of poultry and swine food chains by exploiting their beneficial microbes and positive interactions. Follow us to see how it ends!
Image credit: Dewdrop147 and Mutinka via Pixabay