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:10.7554/eLife.70881

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

Elife. 2022 Mar 21:11:e70881. doi: 10.7554/eLife.70881.

Authors

Kelvin F Cho^{1

2}, Shawn M Gillespie^{1

3}, Nicholas A Kalogriopoulos², Michael A Quezada³, Martin Jacko⁴, Michelle Monje^{3

5

6

7

8}, Alice Y Ting^{2

9

10

11}

Affiliations

¹ Cancer Biology Program, Stanford University, Stanford, United States.
² Department of Genetics, Stanford University, Stanford, United States.
³ Department of Neurology and Neurological Sciences, Stanford University, Stanford, United States.
⁴ BridgeBio, Palo Alto, United States.
⁵ Department of Pathology, Stanford University, Stanford, United States.
⁶ Department of Pediatrics, Stanford University, Stanford, United States.
⁷ Department of Neurosurgery, Stanford University, Stanford, United States.
⁸ Howard Hughes Medical Institute, Stanford University, Stanford, United States.
⁹ Department of Biology, Stanford University, Stanford, United States.
¹⁰ Department of Chemistry, Stanford University, Stanford, United States.
¹¹ Chan Zuckerberg Biohub, San Francisco, United States.

Abstract

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.

Keywords: cell biology; cell contacts; none; synthetic biology; transcriptional reporter.

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

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