A single cell-based computational platform for cellular conversion to generate functionally mature cells – application to regenerative therapies


CALL: 2019

DOMAIN: BM - Translational Biomedical Research


LAST NAME: del Sol Mesa



HOST INSTITUTION: University of Luxembourg

KEYWORDS: Regenerative Medicine, Cell transplantation therapies, Single-cell RNA-seq, Cell conversion, Cell functional maturation, Information theory, Computational systems biology, Limbus

START: 2020-02-01


WEBSITE: http://www.uni.lu

Submitted Abstract

Cellular phenotypes can be characterized by stable gene expression profiles maintained by a set of transcription factors (TFs) that together determine cell identity. Cell conversions between different cellular phenotypes can be induced by perturbing TFs that shift cell identity from the initial cell type to the target one. However, in vitro cell conversion often results in immature, non-functional target cells, failing to generate cells with desired functionalities. Importantly, this has been a major obstacle to successful stem cell transplantation therapies. Existing computational methods for predicting cell conversion factors do not address this issue of functional maturation. Here we propose, based on previous evidence, that each functional cell identity is determined by hierarchical identity TFs consisting of broad cell identity TFs and more specific subtype-identity TFs, and that sequential, rather than simultaneous, overexpression of these TFs will enhance functional maturation of converted cells. Motivated by these hypotheses, we develop a single-cell RNA-seq based computational platform that unbiasedly determines a hierarchy among all cell subtypes in single-cell RNA-seq data, and identifies minimum hierarchical identity TFs for each functional cell subtype. Furthermore, the platform suggests the order, in which the hierarchical identity TFs should be sequentially overexpressed to produce functionally mature target cells. Finally, in collaboration with Prof. Michele De Luca’s group at Center for Regenerative Medicine, Modena, we generate single-cell RNA-seq data of cultured human limbus, and apply the computational platform to it. Importantly, the predicted cell conversion TFs will be experimentally tested to obtain in vitro limbal stem cells, which will be later used for clinical transplantation to treat patients who have lost their vision. Thus, the propose CORE project will present a novel computational platform that could shift the paradigm of cell conversion experiments and its application to cell transplantation therapies in collaboration with a renowned group in regenerative medicine.

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