Identification of molecular pathways and protein-protein interactions in adipose tissue-derived mesenchymal stromal cells (ASCs) under physiological oxygen concentration in a diabetic rat model

Iran J Basic Med Sci. 2022 Feb;25(2):155-163. doi: 10.22038/IJBMS.2022.59004.13107.

Abstract

Objectives: Adipose tissue-derived mesenchymal stromal cells (ASCs) are useful in cell-based therapy. However, it is well known that diabetes mellitus (DM) alters ASCs' functionality. The majority of in vitro studies related to ASCs are developed under non-physiological oxygen conditions. Therefore, they may not reflect the full effects of DM on ASCs, in vivo. The main aim of the current study is to identify molecular pathways and underlying biological mechanisms affected by diabetes on ASCs in physiological oxygen conditions.

Materials and methods: ASCs derived from healthy (ASCs-C) and diabetic (ASCs-D) rats were expanded under standard culture conditions (21% O2) or cultured in physiological oxygen conditions (3% O2) and characterized. Differential gene expressions (DEGs) of ASCs-D with respect to ASCs-C were identified and analyzed with bioinformatic tools. Protein-protein interaction (PPI) networks, from up- and down-regulated DEGs, were also constructed.

Results: The bioinformatic analysis revealed 1354 up-regulated and 859 down-regulated DEGs in ASCs-D, with 21 and 78 terms over and under-represented, respectively. Terms linked with glycosylation and ribosomes were over-represented and terms related to the activity of RNA-polymerase II and transcription regulation were under-represented. PPI network disclosed RPL11-RPS5 and KDR-VEGFA as the main interactions from up- and down-regulated DEGs, respectively.

Conclusion: These results provide valuable information about gene pathways and underlying molecular mechanisms by which diabetes disturbs ASCs biology in physiological oxygen conditions. Furthermore, they reveal, molecular targets to improve the use of ASCs in autologous transplantation.

Keywords: Cell-based therapy; Diabetes; Enrichment analysis; Microarray; Physioxia.