A network-based approach to modelling cell-niche interactions and its application to studying salamander limb regeneration

SCHEME: CORE

CALL: 2015

DOMAIN: BM - Regenerative Medicine in Age-related Diseases

FIRST NAME: Antonio

LAST NAME: Del Sol Mesa

INDUSTRY PARTNERSHIP / PPP: No

INDUSTRY / PPP PARTNER:

HOST INSTITUTION: University of Luxembourg

KEYWORDS: niche, signalling pathway, gene regulatory network, regeneration, salamander

START: 2016-09-01

END: 2019-08-31

WEBSITE: https://www.uni.lu

Submitted Abstract

Cell fate decision is a complex process involving several layers of regulation. Not only the intrinsic genetic programme of the cell, but also external influences such as those exerted by its niche (microenvironment), can induce a transition from one cellular state to another. The niche effect is interpreted through intracellular signal transduction pathways, which in turn brings about changes in the gene regulatory network (GRN) of the cell. Key niche components include direct interactions with neighbouring cells, secreted factors by other cells, immunological control, and environmental conditions such as hypoxia. The effects of niche interactions include differentiation tendency of various stem cells, epithelial-to-mesenchymal transitions, cell migration and regeneration. Salamander is the only tetrapod, where the adult limb functionally regenerates all constituent tissues. Understanding the mechanism of salamander limb regeneration has direct relevance to mammals including humans, as it has been shown that regeneration of mouse tissue utilized the extracellular matrix (ECM) environments that were similar to those characterized in salamander limb regeneration. Thus, investigating the molecular factors that induce salamander limb regeneration is crucial from both aspects of cell niche interactions and addressing regeneration in mammals. Although there exist several tools that can infer active/inactive signalling pathways, they do not integrate signalling pathways with a GRN, and are therefore unable to predict key signalling pathways responsible for cellular state transitions. Here we propose a novel computational method that integrates signalling pathways and GRNs, and devise a systematic computational strategy for predicting key signalling pathways and their target genes by means of differential network analysis. We will apply this method to the salamander limb regeneration system and address which combinations of signalling pathways are responsible for the regeneration. The completion of this project will help community understandings and enable regeneration to become clinically more useful.

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