Engineered extracellular vesicles from human skin cells induce pro-β-cell conversions in pancreatic ductal cells.
Lilibeth Ortega-PinedaElizabeth GuilfoyleMaria Angelica Rincon-BenavidesAmrita Lakshmi AnaparthiLuke R LemmermanTatiana Z Cuellar-GaviriaWilliam LawrenceJill L BussBinbin DengBritani N BlackstoneAna Salazar-PuertaDavid W McCombHeather PowellDaniel Gallego-PerezNatalia Higuita-CastroPublished in: Advanced nanobiomed research (2023)
Direct nuclear reprogramming has the potential to enable the development of β cell replacement therapies for diabetes that do not require the use of progenitor/stem cell populations. However, despite their promise, current approaches to β cell-directed reprogramming rely heavily on the use of viral vectors. Here we explored the use of extracellular vesicles (EVs) derived from human dermal fibroblasts (HDFs) as novel non-viral carriers of endocrine cell-patterning transcription factors, to transfect and transdifferentiate pancreatic ductal epithelial cells (PDCs) into hormone-expressing cells. Electrotransfection of HDFs with expression plasmids for Pdx1 , Ngn3 , and MafA ( PNM ) led to the release of EVs loaded with PNM at the gene, mRNA, and protein level. Exposing PDC cultures to PNM -loaded EVs led to successful transfection and increased PNM expression in PDCs, which ultimately resulted in endocrine cell-directed conversions based on the expression of insulin/c-peptide, glucagon, and glucose transporter 2 (Glut2). These findings were further corroborated in vivo in a mouse model following intraductal injection of PNM - vs sham-loaded EVs. Collectively these findings suggest that dermal fibroblast-derived EVs could potentially serve as a powerful platform technology for the development and deployment of non-viral reprogramming-based cell therapies for insulin-dependent diabetes.
Keyphrases
- type diabetes
- single cell
- stem cells
- cell therapy
- induced apoptosis
- poor prognosis
- drug delivery
- cardiovascular disease
- sars cov
- cell cycle arrest
- endothelial cells
- blood pressure
- machine learning
- gene expression
- glycemic control
- oxidative stress
- escherichia coli
- signaling pathway
- cell proliferation
- binding protein
- metabolic syndrome
- wound healing
- genome wide
- long non coding rna
- cell death
- anti inflammatory
- bone marrow
- insulin resistance
- ultrasound guided
- amino acid
- artificial intelligence
- cell fate