Related Experiment Video
Updated: Jun 12, 2026

Isolating, Sequencing and Analyzing Extracellular MicroRNAs from Human Mesenchymal Stem Cells
Published on: March 8, 2019
Mesenchymal Stromal Cells Improve Islet β-Cell Functional Survival: Analysis of Extracellular Vesicle-Trafficked
Tzu-Wen Hong1, Rosie Sullivan1, Ryea Arora1
1Department of Diabetes, School of Cardiovascular and Metabolic Medicine & Sciences, King's College London, London SE1 1UL, UK.
Abstract:
Type 1 diabetes is caused by autoimmune destruction of insulin-secreting β-cells within islets of Langerhans. Transplantation of donor islets can improve glycaemic control, but current clinical islet transplantation protocols are compromised by extensive loss of β-cell functional mass soon after implantation. Co-incubation in vitro or co-transplantation in vivo of mesenchymal stromal cells (MSCs) with isolated islets improves their functional survival, although the underlying mechanisms remain obscure. Here, we show that MSC-derived extracellular vesicles (MSC-EVs) are alone sufficient to recapitulate many of the beneficial effects of MSCs on islet functional survival, offering the possibility of simple cell-free treatments to improve the outcomes of islet transplantation. We used LC- analysis and small RNA sequencing to analyse the protein and microRNA (miRNA) molecular cargos of MSC-EVs. Proteomic analysis identified >100 proteins from the Uniprot Mouse Database, including β-cell G protein-coupled receptor (GPCR) agonists which we have previously shown to enhance β-cell functional survival. MSC-EVs contained ~300 distinct miRNAs and we identified five highly enriched miRNAs that were significantly upregulated in MSC-EV-treated islets, notably miR-21a-5p. MSC-EV treatment also altered the expression of a distinct set of islet mRNAs known to be involved in islet metabolism and function. These observations may enable the further simplification of the islet pretreatment strategy by focusing on defined GMP-grade biologically active molecules rather than whole heterogeneous EV populations.