eLife (Mar 2022)

A light-gated transcriptional recorder for detecting cell-cell contacts

  • Kelvin F Cho,
  • Shawn M Gillespie,
  • Nicholas A Kalogriopoulos,
  • Michael A Quezada,
  • Martin Jacko,
  • Michelle Monje,
  • Alice Y Ting

DOI
https://doi.org/10.7554/eLife.70881
Journal volume & issue
Vol. 11

Abstract

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Technologies for detecting cell-cell contacts are powerful tools for studying a wide range of biological processes, from neuronal signaling to cancer-immune interactions within the tumor microenvironment. Here, we report TRACC (Transcriptional Readout Activated by Cell-cell Contacts), a GPCR-based transcriptional recorder of cellular contacts, which converts contact events into stable transgene expression. TRACC is derived from our previous protein-protein interaction recorders, SPARK (Kim et al., 2017) and SPARK2 (Kim et al., 2019), reported in this journal. TRACC incorporates light gating via the light-oxygen-voltage-sensing (LOV) domain, which provides user-defined temporal control of tool activation and reduces background. We show that TRACC detects cell-cell contacts with high specificity and sensitivity in mammalian cell culture and that it can be used to interrogate interactions between neurons and glioma, a form of brain cancer.

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