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A computational framework to interpret the chemical language of the microbiome

Project description

Investigating the role of metabolic gene clusters in the microbiome

The microbiome has a major impact on the health of the host and is associated with growth promotion, stress resilience and disease resistance. Recent studies have shown that microbiome-associated phenotypes are determined by specific molecules, which enable microbes to interact with each other and with the host. The biosynthesis of these molecules is encoded in metabolic gene clusters (MGCs), which are strain-specific and subject to horizontal transfer. The EU-funded DECIPHER project will capitalise on the recently developed automated identification of MGCs, their grouping into families and subsequent annotation using reference data. The project's goal is to develop new computational algorithms to link MGCs to their metabolic products and predict their molecular and ecological functions in the microbiome.

Objective

"Humans, animals and plants are covered in microbes. Such microbiomes have a major impact on the health of their hosts and have been linked to traits like growth promotion, stress resilience, and diseases. However, the mechanisms underlying microbiome-host interactions remain poorly understood. Recent studies have shown that microbiome-associated phenotypes are often mediated by specific molecules, a chemical language that enables microbes to interact with each other and with the host. The biosynthesis of these molecules is encoded in metabolic gene clusters (MGCs) that are subject to frequent horizontal transfer and are therefore highly strain-specific.
Current computational methods for analysing microbiomes largely focus on comparative taxonomic analyses and generic metabolism, and overlook this complex ""chemical dialog"". Indeed, no adequate methods are available to systematically study the roles of MGCs in microbiomes. At the same time, metabolomics data from microbiomes are full of dark matter: unknown molecules that cannot be traced to their producers. Here, I propose to develop the first comprehensive computational framework to study the chemical language of the microbiome.
In the past years, I have developed technologies that lay the foundation for this ERC project, including automated identification of MGCs, grouping them into families and annotating them using reference data. With DECIPHER, I will move my research to the next level, by developing new algorithms to link MGCs to their metabolic products and to predict their molecular and ecological functions in microbiomes. I will then apply this new framework in a systematic study of microbiome- associated phenotypes in plants and humans. Together, the innovations proposed here will fill a key gap in the analysis of microbiome function and pave the way toward precision-engineering of microbiomes with specific metabolic capabilities for designer soils and microbiome-based therapies."

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ERC-STG - Starting Grant

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Call for proposal

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(opens in new window) ERC-2020-STG

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Host institution

WAGENINGEN UNIVERSITY
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 499 965,00
Address
DROEVENDAALSESTEEG 4
6708 PB Wageningen
Netherlands

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Region
Oost-Nederland Gelderland Veluwe
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 499 965,00

Beneficiaries (1)

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