Enhancer-AI - AI-driven modelling and design of cell type specific enhancers for gene therapy
From 01-10-2023 to 30-09-2027
Description
Gene therapy offers the promise of an efficient, single-dose therapeutic solution for many incurable diseases. In reality, despite large efforts of the scientific community and a strong industrial interest, bringing gene therapy to the market has proven challenging. The major hurdles faced by gene therapy come in the form of its safety and efficacy with off- target effects caused by low specificity or inappropriate transgene expression levels. The use of well-designed synthetic regulatory regions, called enhancers, could provide a solution to reach cell type-specificity and high levels of transgene expression. This SBO project proposes to develop new computational and experimental tools, and combine them in a pipeline to identify enhancers in complex tissues. This pipeline will exploit recent advances in single-cell multi-omics, gene regulatory network (GRN) inference, and deep learning. We will use this pipeline to design enhancers that are specifically active in three chosen brain cell types that are of high relevance for gene therapy. Practically, we will: 1) use mouse and human brain samples to generate a single-cell multi- omic atlas; 2) select unique regulatory regions to each cell type and train enhancer models; and 3) design and validate synthetic enhancers in vivo, using massively parallel reporter assays. As a clinically relevant case study, we will focus on microglia enhancers in the context of Alzheimer’s disease. In parallel, we will use the AI-based GRN and enhancer models to interpret and prioritize regulatory variation in whole genome sequences, in order to improve diagnosis and prediction of risk and progression for neurodegenerative disease. Our project will yield licensable enhancers, software tools, and diagnostic AI models with direct industrial applicability, and will demonstrate our ability to interpret and generate enhancers specific to any cell type, which can find application in a wide range of diseases, even beyond the scope of our project.
Team
- Stein Aerts, Coordinator (External)
- Yves Moreau, Promoter
Financing
Funding: FWO - Research Foundation - Flanders
Program/Grant Type: FWO SBO - FWO Projects Strategic Basic Research
Events
2/09/2024:
PhD defense - Martijn Oldenhof
Machine Learning for Advanced Chemical Analysis and Structure Recognition in Drug Discovery
3/09/2024:
Meet the Jury Igor Tetko on Advanced Machine Learning in Drug Discovery
12/09/2024:
Multimodal analysis of cell-free DNA for sensitive cancer detection in low-coverage and low-sample settings
Seminar by Antoine Passemiers
News
STADIUS Alumni Herman Verrelst – new CEO of Biocartis
08 June 2017
Herman Verrelst, the founder of KU Leuven spin-off Cartagenia, who has been working in Silicon Valley, US for the last few years will be returning to Belgium to follow the steps of Rudi Pauwels as CEO of the Belgian diagnostic company, Biocartis.
Supporting healthcare policymaking via machine learning – batteries included!
29 May 2017
STADIUS takes the lead in the data analytics efforts in an ambitious European Project MIDAS.
Marc Claesen gives an interview about his PhD for the magazine of the Faculty of Engineering Sciences "Geniaal"
10 February 2017
Did you know that in Belgium approximately one third of type 2 diabetes patients are unaware of their condition?
Joos Vandewalle is nieuwe voorzitter KVAB
09 October 2016
Op 5 oktober 2016 heeft de Algemene Vergadering van de Academie KVAB Joos Vandewalle verkozen tot voorzitter van de KVAB.