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Unified computational solutions to disentangle biological interactions in multi-omics data

Project description

DEENESFRITPL

New framework to decipher biomolecular interaction

Attempts to improve animal and plant microbiome functions are largely unsuccessful since interactions between the host’s biological process and their microbiome remain only superficially understood. What is certain is that microbiome functions can be optimised for sustainable food production. The question is how. In this context, the EU-funded FindingPheno project will develop a holistic statistical framework to decipher biomolecular interactions between host and microbiome. Specifically, it will combine biological knowledge and state-of-the-art statistical methods: structural causal modelling, variable selection, dimensionality reduction and feature detection. The next step will be to apply the framework to case studies from actual food production systems. The aim is to demonstrate the utility of the framework and provide avenues for quick and easy application of this new approach.

Objective

Animal and plant microbiome functions can be modulated, and thereby optimized, for sustainable food production. However, the outcome, i.e. the microbial response, can vary greatly depending on (e.g.)Animal and plant microbiome functions can be modulated, and thereby optimized, for sustainable food production. However, the outcome, i.e. the microbial response, can vary greatly depending on (e.g.) the genetic background and developmental stage of the host, and the farming environment. The interactions between the biological process of the host and their microbiome are still only superficially understood, even though microbial interventions have been used for years. This incomplete understanding means that new attempts to improve microbiome functions are both inefficient and costly, and unlikely to hit upon the optimal solutions. An approach that recognizes the intimate biological interactions between host genome and microbiome functions holds the potential to greatly reduce cost and improve the outcome.
To that end, FindingPheno will develop a holistic statistical framework to decipher biomolecular interactions between host and microbiome by combining biological knowledge and state-of-the-art statistical methods: structural causal modelling, variable selection, dimensionality reduction and feature detection. We will then apply the framework to case studies from actual food production systems, using a unique multi-omics data set from three biological systems – chicken, salmon and maize – derived from ongoing research projects. In addition, we demonstrate the utility of the framework to obtain biological insights from publicly available data sets from tomato and bees.
We expect to show how to improve the effectiveness of microbiome interventions in sustainable food production, and simultaneously, we will offer avenues for quick and easy application of this new approach to other relevant biotechnology-based industries, e.g. enzyme production and fermentation.

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Call for proposal

H2020-NMBP-TR-IND-2018-2020

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Sub call

H2020-NMBP-TR-IND-2020-twostage

Funding Scheme

RIA - Research and Innovation action

Coordinator

KOBENHAVNS UNIVERSITET
Net EU contribution
€ 1 854 905,00
Address
NORREGADE 10
1165 Kobenhavn
Denmark

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Region
Danmark Hovedstaden Byen København
Activity type
Higher or Secondary Education Establishments
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Total cost
€ 1 854 905,00

Participants (7)

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Last update: 15 March 2024

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Permalink: https://cordis.europa.eu/project/id/952914

European Union, 2024