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Digital microfluidic isolation of single cells for -Omics

Author

Listed:
  • Julian Lamanna

    (University of Toronto
    University of Toronto)

  • Erica Y. Scott

    (University of Toronto
    University of Toronto)

  • Harrison S. Edwards

    (University of Toronto
    University of Toronto)

  • M. Dean Chamberlain

    (University of Toronto
    University of Toronto)

  • Michael D. M. Dryden

    (University of Toronto)

  • Jiaxi Peng

    (University of Toronto)

  • Barbara Mair

    (University of Toronto)

  • Adam Lee

    (University of Toronto)

  • Calvin Chan

    (University of Toronto)

  • Alexandros A. Sklavounos

    (University of Toronto
    University of Toronto)

  • Austin Heffernan

    (University of Toronto)

  • Farhana Abbas

    (University of Toronto
    University of Toronto)

  • Charis Lam

    (University of Toronto)

  • Maxwell E. Olson

    (University of Toronto)

  • Jason Moffat

    (University of Toronto
    University of Toronto
    University of Toronto)

  • Aaron R. Wheeler

    (University of Toronto
    University of Toronto
    University of Toronto)

Abstract

We introduce Digital microfluidic Isolation of Single Cells for -Omics (DISCO), a platform that allows users to select particular cells of interest from a limited initial sample size and connects single-cell sequencing data to their immunofluorescence-based phenotypes. Specifically, DISCO combines digital microfluidics, laser cell lysis, and artificial intelligence-driven image processing to collect the contents of single cells from heterogeneous populations, followed by analysis of single-cell genomes and transcriptomes by next-generation sequencing, and proteomes by nanoflow liquid chromatography and tandem mass spectrometry. The results described herein confirm the utility of DISCO for sequencing at levels that are equivalent to or enhanced relative to the state of the art, capable of identifying features at the level of single nucleotide variations. The unique levels of selectivity, context, and accountability of DISCO suggest potential utility for deep analysis of any rare cell population with contextual dependencies.

Suggested Citation

  • Julian Lamanna & Erica Y. Scott & Harrison S. Edwards & M. Dean Chamberlain & Michael D. M. Dryden & Jiaxi Peng & Barbara Mair & Adam Lee & Calvin Chan & Alexandros A. Sklavounos & Austin Heffernan & , 2020. "Digital microfluidic isolation of single cells for -Omics," Nature Communications, Nature, vol. 11(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-19394-5
    DOI: 10.1038/s41467-020-19394-5
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