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

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...

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Main Authors: Virginie Mournetas, Quentin M. Nunes, Patricia A. Murray, Christopher M. Sanderson, David G. Fernig
Format: Article
Language:English
Published: PeerJ Inc. 2014-10-01
Series:PeerJ
Subjects:
Online Access:https://peerj.com/articles/618.pdf
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spelling doaj-9103320b57b54cd5af1fc3a7cb3f2cfb2020-11-24T22:55:15ZengPeerJ Inc.PeerJ2167-83592014-10-012e61810.7717/peerj.618618Network based meta-analysis prediction of microenvironmental relays involved in stemness of human embryonic stem cellsVirginie Mournetas0Quentin M. Nunes1Patricia A. Murray2Christopher M. Sanderson3David G. Fernig4Department of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, Liverpool, United KingdomDepartment of Biochemistry, Institute of Integrative Biology, University of Liverpool, Liverpool, United KingdomDepartment of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, Liverpool, United KingdomDepartment of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, Liverpool, United KingdomDepartment of Biochemistry, Institute of Integrative Biology, University of Liverpool, Liverpool, United KingdomBackground. 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 cell-microenvironment 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.https://peerj.com/articles/618.pdfTranscriptomeInteractomeProtein–protein interaction networkHuman embryonic stem cellsIn silico analysis
collection DOAJ
language English
format Article
sources DOAJ
author Virginie Mournetas
Quentin M. Nunes
Patricia A. Murray
Christopher M. Sanderson
David G. Fernig
spellingShingle Virginie Mournetas
Quentin M. Nunes
Patricia A. Murray
Christopher M. Sanderson
David G. Fernig
Network based meta-analysis prediction of microenvironmental relays involved in stemness of human embryonic stem cells
PeerJ
Transcriptome
Interactome
Protein–protein interaction network
Human embryonic stem cells
In silico analysis
author_facet Virginie Mournetas
Quentin M. Nunes
Patricia A. Murray
Christopher M. Sanderson
David G. Fernig
author_sort Virginie Mournetas
title Network based meta-analysis prediction of microenvironmental relays involved in stemness of human embryonic stem cells
title_short Network based meta-analysis prediction of microenvironmental relays involved in stemness of human embryonic stem cells
title_full Network based meta-analysis prediction of microenvironmental relays involved in stemness of human embryonic stem cells
title_fullStr Network based meta-analysis prediction of microenvironmental relays involved in stemness of human embryonic stem cells
title_full_unstemmed Network based meta-analysis prediction of microenvironmental relays involved in stemness of human embryonic stem cells
title_sort network based meta-analysis prediction of microenvironmental relays involved in stemness of human embryonic stem cells
publisher PeerJ Inc.
series PeerJ
issn 2167-8359
publishDate 2014-10-01
description 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 cell-microenvironment 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.
topic Transcriptome
Interactome
Protein–protein interaction network
Human embryonic stem cells
In silico analysis
url https://peerj.com/articles/618.pdf
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