The world's population continues to grow - but the Earth's surface does not. This urges us to ensure that the associated need for increased food production is performed in a sustainable fashion, because optimising food production is not only of commercial interest for companies, but also of critical importance for humanity and biodiversity. In this regard, understanding the interplay between animals and microorganisms associated with them has been recognised as an essential step by the European Commission for improving and optimising animal health, welfare, and production worldwide.
To understand the truly relevant biomolecular interactions that impact production processes, researchers are implementing novel strategies based on the analysis of animal genomes, the metagenomes of the associated microorganisms, and the different omic layers interconnecting them — the so-called holo’omic framework.
However, these approaches do not yet capture spatial properties of feeds, microorganisms, and host epithelial tissue, which are known to differ across intestinal sections, time points, and individuals. Neither conventional multi-omics nor histology provide information on how gene expression and biomolecule production of such cells is triggered by proximity of specific bacterial cells and metabolites, and vice versa. Current methods provide us information analogous to what would be learned from studying the functioning of the Amazon rainforest through mixing all living organisms in the jungle in a big pot and quantifying their relative abundances without acknowledging, for instance, which bird nests or which mycorrhizal fungi are associated with which tree.
Now, we are finally capable of breaking these barriers and boosting animal-microbiota research with a groundbreaking technological advancement. In recent years, there has been a rapid development of techniques that, separately, have enabled the generation of multiple omics data, including both microbial and host components, processing very small amounts of biological material, generating 3D reconstructions of biological elements, and analysing complex microbial communities. Hence, the technology required for 3D multi-omics are finally in place and we will use it to develop, implement, and assess a new methodological framework that will revolutionise animal-microbiota research in animal science and beyond. Ultimately, we foresee that our new framework will open new research avenues to improve the generation of animal breeds with enhanced microbiota-related genetic features, probiotics, microbiota - and host-tailored feeds, animal health treatments, and management practices that will enable increasing production efficiency while decreasing environmental impact and improving animal welfare.
