Exploring the Functional Heterogeneity of Directly Reprogrammed Neural Stem Cell-Derived Neurons via Single-Cell RNA Sequencing

Cells. 2023 Dec 11;12(24):2818. doi: 10.3390/cells12242818.

Abstract

The therapeutic potential of directly reprogrammed neural stem cells (iNSCs) for neurodegenerative diseases relies on reducing the innate tumorigenicity of pluripotent stem cells. However, the heterogeneity within iNSCs is a major hurdle in quality control prior to clinical applications. Herein, we generated iNSCs from human fibroblasts, by transfecting transcription factors using Sendai virus particles, and characterized the expression of iNSC markers. Using immunostaining and quantitative real time -polymerase chain reaction (RT -qPCR), no differences were observed between colonies of iNSCs and iNSC-derived neurons. Unexpectedly, patch-clamp analysis of iNSC-derived neurons revealed distinctive action potential firing even within the same batch product. We performed single-cell RNA sequencing in fibroblasts, iNSCs, and iNSC-derived neurons to dissect their functional heterogeneity and identify cell fate regulators during direct reprogramming followed by neuronal differentiation. Pseudotime trajectory analysis revealed distinct cell types depending on their gene expression profiles. Differential gene expression analysis showed distinct NEUROG1, PEG3, and STMN2 expression patterns in iNSCs and iNSC-derived neurons. Taken together, we recommend performing a predictable functional assessment with appropriate surrogate markers to ensure the quality control of iNSCs and their differentiated neurons, particularly before cell banking for regenerative cell therapy.

Keywords: direct reprogramming; functional heterogeneity; iNSC-derived neuron; neural stem cells; quality control; single-cell RNA sequencing; surrogate biomarker.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cell Differentiation / genetics
  • Humans
  • Neural Stem Cells* / metabolism
  • Neurons
  • Pluripotent Stem Cells*
  • Sequence Analysis, RNA