An RNA/DNA-Based Flow Cytometry Approach for Isolating Slow-Cycling Stem Cells

Methods Mol Biol. 2023:2680:157-168. doi: 10.1007/978-1-0716-3275-8_9.

Abstract

Flow cytometry methods for sorting specific populations of cells based on fluorescence or physical properties have been a widely used technique for decades. Flow cytometry has been particularly vital to the study of planarians, which remain refractory to transgenic transformation, as it has provided a work-around solution for studying stem cell biology and lineage relationships in the context of regeneration. Many flow cytometry applications have been published in planarians, beginning with broad Hoechst-based strategies for isolating cycling stem cells and progressing to more function-based approaches involving vital dyes and surface antibodies. In this protocol, we look to build on the classic DNA-labeling Hoechst staining strategy by adding pyronin Y staining to label RNA. While Hoechst labeling alone allows for the isolation of stem cells in the S/G2/M phases of the cell cycle, heterogeneity within the population of stem cells with 2 C DNA content is not resolved. By considering RNA levels, this protocol can further divide this population of stem cells into two groups: G1 stem cells with relatively high RNA content and a slow-cycling population with low RNA content, which we call RNAlow stem cells. In addition, we provide instruction for combining this RNA/DNA flow cytometry protocol with EdU labeling experiments and describe an optional step for incorporating immunostaining prior to cell sorting (in this case with the pluripotency marker TSPAN-1). This protocol adds a new staining strategy and examples of combinatorial flow cytometry approaches to the repertoire of flow cytometry techniques for studying planarian stem cells.

Keywords: CellMask; EdU; Flow cytometry; Hoechst; Planarians; Pyronin Y; Stem cells.

MeSH terms

  • Cell Cycle
  • Cell Separation
  • DNA / genetics
  • DNA / metabolism
  • Flow Cytometry / methods
  • RNA* / genetics
  • RNA* / metabolism
  • Stem Cells*

Substances

  • RNA
  • DNA