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Monitoring single-cell gene regulation under dynamically controllable conditions with integrated microfluidics and software

Author

Listed:
  • Matthias Kaiser

    (University of Basel and Swiss Institute of Bioinformatics)

  • Florian Jug

    (Max Planck Institute of Molecular Cell Biology and Genetics)

  • Thomas Julou

    (University of Basel and Swiss Institute of Bioinformatics)

  • Siddharth Deshpande

    (University of Basel
    TU Delft)

  • Thomas Pfohl

    (University of Basel)

  • Olin K. Silander

    (University of Basel and Swiss Institute of Bioinformatics
    Massey University Auckland)

  • Gene Myers

    (Max Planck Institute of Molecular Cell Biology and Genetics)

  • Erik van Nimwegen

    (University of Basel and Swiss Institute of Bioinformatics)

Abstract

Much is still not understood about how gene regulatory interactions control cell fate decisions in single cells, in part due to the difficulty of directly observing gene regulatory processes in vivo. We introduce here a novel integrated setup consisting of a microfluidic chip and accompanying analysis software that enable long-term quantitative tracking of growth and gene expression in single cells. The dual-input Mother Machine (DIMM) chip enables controlled and continuous variation of external conditions, allowing direct observation of gene regulatory responses to changing conditions in single cells. The Mother Machine Analyzer (MoMA) software achieves unprecedented accuracy in segmenting and tracking cells, and streamlines high-throughput curation with a novel leveraged editing procedure. We demonstrate the power of the method by uncovering several novel features of an iconic gene regulatory program: the induction of Escherichia coli’s lac operon in response to a switch from glucose to lactose.

Suggested Citation

  • Matthias Kaiser & Florian Jug & Thomas Julou & Siddharth Deshpande & Thomas Pfohl & Olin K. Silander & Gene Myers & Erik van Nimwegen, 2018. "Monitoring single-cell gene regulation under dynamically controllable conditions with integrated microfluidics and software," Nature Communications, Nature, vol. 9(1), pages 1-16, December.
  • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-017-02505-0
    DOI: 10.1038/s41467-017-02505-0
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    Cited by:

    1. Ankit Gupta & Mustafa Khammash, 2022. "Frequency spectra and the color of cellular noise," Nature Communications, Nature, vol. 13(1), pages 1-18, December.

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