Visual barcodes for clonal-multiplexing of live microscopy-based assays

Tom Kaufman, Erez Nitzan, Nir Firestein, Miriam Bracha Ginzberg, Seshu Iyengar, Nish Patel, Rotem Ben-Hamo, Ziv Porat, Jaryd Hunter, Andreas Hilfinger, Varda Rotter, Ran Kafri, Ravid Straussman

Research output: Contribution to journalArticlepeer-review

Abstract

While multiplexing samples using DNA barcoding revolutionized the pace of biomedical discovery, multiplexing of live imaging-based applications has been limited by the number of fluorescent proteins that can be deconvoluted using common microscopy equipment. To address this limitation, we develop visual barcodes that discriminate the clonal identity of single cells by different fluorescent proteins that are targeted to specific subcellular locations. We demonstrate that deconvolution of these barcodes is highly accurate and robust to many cellular perturbations. We then use visual barcodes to generate ‘Signalome’ cell-lines by mixing 12 clones of different live reporters into a single population, allowing simultaneous monitoring of the activity in 12 branches of signaling, at clonal resolution, over time. Using the ‘Signalome’ we identify two distinct clusters of signaling pathways that balance growth and proliferation, emphasizing the importance of growth homeostasis as a central organizing principle in cancer signaling. The ability to multiplex samples in live imaging applications, both in vitro and in vivo may allow better high-content characterization of complex biological systems. Multiplex analyses of samples allow understanding complex processes in cancer initiation, progression and therapy response. Here, the authors present a fluorescence imaging-based visual barcode for livecell clonal-multiplexing which allows identifying signalling pathways clusters in response to different chemotherapy compounds.
Original languageEnglish
Article number2725
JournalNature Communications
Volume13
Issue number1
DOIs
StatePublished - Dec 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • General Chemistry
  • General Biochemistry,Genetics and Molecular Biology
  • General Physics and Astronomy

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