Overall Aim of this GitHub: Synthesise the technical knowledge generated in HoloFood to ease the implementation of hologenomic approaches in animal production.

HoloFood is a hologenomic approach that will improve the efficiency of food production systems by understanding the biomolecular and physiological processes affected by incorporating feed additives and
novel sustainable feeds in farmed animals.

The HoloFood consortium will showcase the potential of an innovative solution that holds enormous potential for optimising modern food production. Specifically, HoloFood is a framework that integrates a suite of recent analytical and technological developments, that is applicable to any major animal food production system, spanning the full production line.

Thus it is as relevant for the farmers producing livestock, as it is to the associate industries such as those producing the feed and feed additives upon which the animal’s growth, quality, health and wellbeing depends.

For a short introduction, please see youtube video below

With the planet’s population rapidly increasing, one of the key global challenges of this century is to secure that the growing food production is performed in a sustainable fashion and with a low-carbon signature. Hence, optimising food production is thus not only of commercial interest for companies, but also of critical importance for humanity.

In the last decades, and in particular since the 2006 ban of using antibiotics to promote animal growth in the European Union, different strategies are being developed to modulate gut microbiomes aiming to improve food production, such as functional feed components or feed additives.Feed additives have been proven effective at modulating microbiomes in many animal systems, although their efficiency often exhibits large variation. The likely reason underlying such inconsistency, is the very limited knowledge we have about the specific means of action of the additives.

Understanding the effect of these additives is poorly understood, because the microorganisms of interest might interact with hundreds of other microbial taxa as well as the host organism. Consequently, the procedures to improve the feed additive products are not as efficient as they could be, and it is unlikely that any truly optimal product can be found without drastically modifying the approach taken.

The holo-omic approach considers the holobiont (host animal and its associated microbiota) as a single unit of action, across multiple molecular levels. ​To achieve this, HoloFood takes advantage of large variety of new technological developments that allow us to understand the interactions between the animal and their respective gut microbiome on numerous molecular levels. In addition to this genetic data, HoloFood also incorporates a lot more information to the dataset, such as physiological and health information.

Methodologies are divided into laboratory procedures, bioinformatic procedures, and statistical procedures. Each procedures has a repository, which holds both individual README.md files with explanation, protocols (if any), and overall pipelines.