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BestTreat – Building a Gut Microbiome Engineering Toolbox for In-Situ Therapeutic Treatments for Non-alcoholic Fatty Liver Disease

Project description

Microbiome-based treatment for liver disease

Non-alcoholic fatty liver disease (NAFLD) is characterised by the accumulation of fat in the liver and affects mainly overweight or obese individuals. NAFLD can develop into cirrhosis and is a major cause of liver cancer. The EU-funded BestTreat project is interested to delineate the role of the microbiome in NAFLD. Imbalance of the gut microbiome has been associated with various diseases including NAFLD, but little is known regarding the underlying mechanism. The project research will help develop novel diagnostic and live biotherapeutic approaches involving the gut microbiome for prevention or treatment of NAFLD.

Objective

BestTreat fosters education of ESRs in a project to uncover microbiome signatures for risk prediction and monitoring of NAFLD and to contribute to the development of therapeutic treatments based on metabolically beneficial microbial consortia. It trains 15 ESRs at world-leading academic institutions and companies, thus forming strong interdisciplinary links between industry, life and medical sciences, and end-users. BestTreat aims to train a new generation of highly qualified ESRs with entrepreneurial competencies in modern Life Sciences through state-of-the-art research projects. The projects focus on the identification and functional characterization of microbial consortia that contribute to metabolic control, and the application of this knowledge to develop novel leads for drug discovery and therapies for NAFLD. The new field on microbiome based therapeutics requires highly skilled scientists with interdisciplinary knowledge on medicine, systems biology and computer science, as well as hands-on experience with several types of tissue samples and model organisms that can optimally translate their research findings into sustainable improvements in clinical practice. BestTreat overcomes current barriers by establishing a strong, multidisciplinary and inter-sectoral training network, developing technologies tailored to solve key questions in human metabolism, microbiology and bioinformatics. The BestTreat programme will exploit recent developments in high-throughput and genome-wide screening technologies, combine these with modern molecular cell biology and systems biology approaches and ultimately translate the data into new leads for the discovery of live biotherapeutics. This specific cross-disciplinary training program will educate young scientists to the next level needed to advance this research field for the upcoming decennium. The training programme will be complemented with a complete set of transferable skills.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

MSCA-ITN - Marie Skłodowska-Curie Innovative Training Networks (ITN)

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-MSCA-ITN-2018

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Coordinator

LEIBNIZ-INSTITUT FUR NATURSTOFF-FORSCHUNG UND INFEKTIONSBIOLOGIE EV HANS-KNOLL-INSTITUT
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.

€ 758 365,20
Address
BEUTENBERG STRASSE 11A
07745 Jena
Germany

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Region
Thüringen Thüringen Jena, Kreisfreie Stadt
Activity type
Research Organisations
Links
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.

€ 758 365,20

Participants (7)

Partners (6)

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