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Building a causal regulatory network of mesenchymal cells using targeted programming experiments

Project description

Modelling cell differentiation

Cells undertake complex processes in response to multiple biochemical stimuli, which requires a careful coordination of gene expression. Transcription factors, associated proteins and target genes have a key role in gene expression regulation, and collectively they form a gene regulatory network. The EU-funded DesignerCells project proposes to develop a computational approach to model how combinations of transcription factors affect a cell's differentiation status. Researchers will combine modelling with experimentation on mesenchymal stem cells to understand the emergence of the different cell lineages. The generated workflow has the potential to be applied to various types of cells.

Objective

Gene regulation is one of the main drivers of a cell's fate and function, but current methods that infer genome-wide regulatory networks have problems with inferring causal and/or combinatorial interactions. Pooled single-cell screening technologies, such as those developed in the host lab, now provide a powerful alternative to regulatory network inference. However, as this technology matures, data analysis is now more and more becoming the rate-limiting step in inferring causal and combinatorial regulatory networks.
In this project, I will develop a combined computational and experimental workflow to infer regulatory networks. At the computational side, I will develop an algorithm that models how combinations of transcription factors affect a cell's state. The model will go beyond a ball-stick model, and investigate combinatorial logic, dosage effects, cell proliferation and cellular heterogeneity. The algorithm will also propose new combinations that may move a cell towards a fate of interest. Through multiple rounds of modelling and experimentation, I will iteratively improve our understanding of the causality and combinatorics of a regulatory network.
I will validate the workflow on mesenchymal stem cells (MSCs), a cell type for which some (combinations of) transcription factors that drive its differentiation are already known, but for which a combinatorial view across lineages is still missing. I will first start with easier well-studied systems, such as adipocyte differentiation, and later in the project move on to less-studied systems such as adipocyte progenitors.
By integrating experimental and computational techniques, the proposed project will provide a causal regulatory network across MSC lineages, and yield a framework to generate such a network in other systems. Moreover, the project will allow me to expand my computational skill set with emerging experimental techniques and management skills which will be invaluable for advancing my scientific career.

Fields of science (EuroSciVoc)

Programme(s)

Topic(s)

Funding Scheme

MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)

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Call for proposal

(opens in new window) H2020-MSCA-IF-2020

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Coordinator

ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE
Net EU contribution
€ 203 149,44
Address
BATIMENT CE 3316 STATION 1
1015 Lausanne
Switzerland
Region
Schweiz/Suisse/Svizzera Région lémanique Vaud
Activity type
Higher or Secondary Education Establishments
Links
Total cost
€ 203 149,44