Single-cell transcriptome analyses reveal signals to activate dormant neural stem cells

Cell. 2015 May 21;161(5):1175-1186. doi: 10.1016/j.cell.2015.04.001.

Abstract

The scarcity of tissue-specific stem cells and the complexity of their surrounding environment have made molecular characterization of these cells particularly challenging. Through single-cell transcriptome and weighted gene co-expression network analysis (WGCNA), we uncovered molecular properties of CD133(+)/GFAP(-) ependymal (E) cells in the adult mouse forebrain neurogenic zone. Surprisingly, prominent hub genes of the gene network unique to ependymal CD133(+)/GFAP(-) quiescent cells were enriched for immune-responsive genes, as well as genes encoding receptors for angiogenic factors. Administration of vascular endothelial growth factor (VEGF) activated CD133(+) ependymal neural stem cells (NSCs), lining not only the lateral but also the fourth ventricles and, together with basic fibroblast growth factor (bFGF), elicited subsequent neural lineage differentiation and migration. This study revealed the existence of dormant ependymal NSCs throughout the ventricular surface of the CNS, as well as signals abundant after injury for their activation.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • AC133 Antigen
  • Animals
  • Antigens, CD / metabolism
  • Cell Differentiation
  • Cell Movement
  • Ependyma / cytology*
  • Ependyma / metabolism
  • Fibroblast Growth Factors / metabolism
  • Gene Expression Profiling
  • Gene Regulatory Networks
  • Glycoproteins / metabolism
  • Mice
  • Neural Stem Cells / cytology
  • Neural Stem Cells / metabolism*
  • Peptides / metabolism
  • Sequence Analysis, RNA
  • Single-Cell Analysis
  • Vascular Endothelial Growth Factor A / metabolism

Substances

  • AC133 Antigen
  • Antigens, CD
  • Glycoproteins
  • PROM1 protein, human
  • Peptides
  • Prom1 protein, mouse
  • Vascular Endothelial Growth Factor A
  • Fibroblast Growth Factors

Associated data

  • GEO/GSE61288