Network based meta-analysis prediction of microenvironmental relays involved in stemness of human embryonic stem cells

Mournetas, Virginie, Nunes, Quentin ORCID: 0000-0002-7513-8595, Murray, Patricia, Sanderson, Christopher ORCID: 0000-0002-7301-3537 and Fernig, David ORCID: 0000-0003-4875-4293 (2014) Network based meta-analysis prediction of microenvironmental relays involved in stemness of human embryonic stem cells. PeerJ, 2 (1). e618-.

Text Fernig 2014 peerj-618.pdf - Unspecified Download (5MB)

Abstract

Background. Human embryonic stem cells (hESCs) are pluripotent cells derived from the inner cell mass of in vitro fertilised blastocysts, which can either be maintained in an undifferentiated state or committed into lineages under determined culture conditions. These cells offer great potential for regenerative medicine, but at present, little is known about the mechanisms that regulate hESC stemness; in particular, the role of cell–cell and cell-extracellular matrix interactions remain relatively unexplored. Methods and Results. In this study we have performed an in silico analysis of cellmicroenvironment interactions to identify novel proteins that may be responsible for the maintenance of hESC stemness. A hESC transcriptome of 8,934 mRNAs was assembled using a meta-analysis approach combining the analysis of microarrays and the use of databases for annotation. The STRING database was utilised to construct a protein–protein interaction network focused on extracellular and transcription factor components contained within the assembled transcriptome. This interactome was structurally studied and filtered to identify a short list of 92 candidate proteins, which may regulate hESC stemness. Conclusion.We hypothesise that this list of proteins, either connecting extracellular components with transcriptional networks, or with hub or bottleneck properties, may contain proteins likely to be involved in determining stemness.

Item Type:	Article
Additional Information:	Copyright 2014 Mournetas et al. Distributed under Creative Commons CC-BY 4.0
Uncontrolled Keywords:	Transcriptome, Interactome, Protein-protein interaction network, Human embryonic stem cells, In silico analysis
Depositing User:	Symplectic Admin
Date Deposited:	18 Jun 2015 14:49
Last Modified:	15 Dec 2022 23:46
DOI:	10.7717/peerj.618
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/2013826