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Mournetas V, Nunes QM, Murray PA, Sanderson CM, Fernig DG.2014. Network based meta-analysis prediction of microenvironmental relays involved in stemness of human embryonic stem cells. PeerJ PrePrints2:e415v2https://doi.org/10.7287/peerj.preprints.415v2
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.
This is an update of a previous version based on reviewers' comments.
The hESC putative interactomes
The hESC EC+TF putative interactomes A) ALL and B) C+S (C: common part; S: specific part). (Cytoscape file)
List of mRNAs forming hESC and hESC-derived transcriptomes
Each mRNA is identified by the EntrezGene ID, the Official Gene Symbol and the full gene name. 'Transcriptome' column: transcriptome(s) or sub-transcriptome containing the mRNAs (hESC: human embryonic stem cells; Endo: endothelial cell; F: fibroblast; Mix: mixture of hESC-derived cells). Colour code (see Legend sheet) indicates different transcriptome and sub-transcriptomes. GO term column: GO terms found during the GO extraction (CA: cell adhesion; CC: cell cycle; CCo: cell communication; CS: cytoskeleton organisation; J: cell junction; EC: extracellular part; HS: heparan sulfate binding proteins; TF: transcription factor related part). (Excel file)
ALL R is the randomised network from the ALL interactome while C+S R is the randomised network from the C+S interactome (C: common part; S: specific part; R: random). Power law of the degree distribution: <!--[if !msEquation]--> <!--[endif]--> with R2, the polynomial regression coefficient (degree 2).
GO Biological Processes term and KEGG pathway enrichments analysis of A) EC+TF interactomes, B) full lists of candidates and C-I) sub-sets of candidates (EC: extracellular part; TF: transcription factor related part).
Each protein is identified by its corresponding EntrezGene ID, gene acronym and full gene name. 'Transcriptome' column: transcriptome(s) or sub-transcriptome containing the corresponding mRNA (Endo: endothelial cell; F: fibroblast; Mix: mixture of hESC-derived cells). A colour code is applied to aid recognition of each transcriptome and sub-transcriptome (see the Legend sheet). GO term column: GO terms found during the GO term analysis (CA: cell adhesion; CC: cell cycle; CCo: cell communication; CS: cytoskeleton; J: cell junction; EC: extracellular part; HS: heparan sulfate binding proteins; TF: transcription factor related part). "Hubs" column: indicates the number of edges associated with each hub protein. 'S/C' and 'EC/TF' columns: indicates if a protein is in the specific/common interface or extracellular/transcription factor interface respectively. A) the longest ALL_EC+TF list of candidates, B) the random list, C) the ALL_EC list, D) the C+S_EC+TF list and E) the shortest C+S_EC list of candidate proteins, in which C = common part and S = specific part. (Excel file)
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