Effect of the Enrichment in c-Kit Stem Cell Potential of Foetal Human Amniotic Fluid Cells: Characterization from Single Cell Analysis to the Secretome Content

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Abstract

Human amniotic fluid cells (hAFSCs) are a fascinating foetal cell-type that have important stem cell characteristics; however, they are a heterogeneous population that ranges from totally differentiated or progenitor cells to highly multipotent stem cells. There is no single approach to isolating the stem cell component, but the selection of a subpopulation of hAFSCs expressing c-Kit is widely employed, while a deep characterization of the two populations is still lacking. Here we performed single-cell and bulk RNAseq analysis to compare the gene expression profiles of adherent amniotic fluid cells and their subpopulation c-Kit+. Information deriving from this high throughput technology on the transcriptome was then confirmed for specific targets with protein expression experiments and functional analysis. In particular, transcriptome profiling identified changes in cellular distribution among the different clusters that correlated with significant differential expression in pathways related to stemness, proliferation, and cell cycle checkpoints. These differences were validated by RT-PCR, immunofluorescence, WB, and cell cycle assays. Interestingly, the two populations produced secretomes with different immune-modulating and pro-regenerative potentials. Indeed, the presence of TGFβ, HGF, IDO was higher in EVs deriving from c-Kit+ cells, unlike IL-6. These results suggest the existence of deep intra-population differences that can influence the stemness profile of hAFSCs. This study represents a proof-of-concept of the importance of selecting c-Kit positive fractions with higher potential in regenerative medicine applications.

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Casciaro, F., Beretti, F., Gatti, M., Persico, G., Bertucci, E., Giorgio, M., & Maraldi, T. (2023). Effect of the Enrichment in c-Kit Stem Cell Potential of Foetal Human Amniotic Fluid Cells: Characterization from Single Cell Analysis to the Secretome Content. Biomedicines, 11(2). https://doi.org/10.3390/biomedicines11020430

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