Integrating gene regulatory network and signalling pathways to model niche interactions – application to salamander limb regeneration


CALL: 2015

DOMAIN: BM - Life Sciences, Biology and Medicine


LAST NAME: Zaffaroni



HOST INSTITUTION: University of Luxembourg

KEYWORDS: limb regeneration, niche effect, gene regulatory network, signalling pathways, integration, cell differentiation

START: 2015-09-01

END: 2019-08-31


Submitted Abstract

Cellular decision-making 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 influence of niche is transmitted 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, addressing the question of what are the molecular factors that determine the progression of 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 (i.e., SPIA), they do not provide a systematic strategy for predicting key genes/signalling pathways for cellular state transitions and progression by integrating the effects of signalling on the underlying GRN. Here we propose a novel computational method that integrates signalling pathways and GRNs. Based on this network model, we devise a systematic strategy for predicting key genes/signalling pathways by means of differential network analysis. We will apply this method to the salamander limb regeneration system and address which combinations of genes/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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