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Enabling reactive microscopy with MicroMator

Author

Listed:
  • Zachary R. Fox

    (Inria Paris
    Institut Pasteur
    Center for Nonlinear Studies, Los Alamos National Laboratory)

  • Steven Fletcher

    (Inria Paris
    Institut Pasteur)

  • Achille Fraisse

    (Inria Paris
    Institut Pasteur)

  • Chetan Aditya

    (Inria Paris
    Institut Pasteur)

  • Sebastián Sosa-Carrillo

    (Inria Paris
    Institut Pasteur)

  • Julienne Petit

    (Structural Microbiology Unit, Institut Pasteur, CNRS UMR 3528, Université de Paris)

  • Sébastien Gilles

    (Inria Saclay—Ile-de-France, 1 rue H. d’Estienne d’Orves)

  • François Bertaux

    (Inria Paris
    Institut Pasteur)

  • Jakob Ruess

    (Inria Paris
    Institut Pasteur)

  • Gregory Batt

    (Inria Paris
    Institut Pasteur)

Abstract

Microscopy image analysis has recently made enormous progress both in terms of accuracy and speed thanks to machine learning methods and improved computational resources. This greatly facilitates the online adaptation of microscopy experimental plans using real-time information of the observed systems and their environments. Applications in which reactiveness is needed are multifarious. Here we report MicroMator, an open and flexible software for defining and driving reactive microscopy experiments. It provides a Python software environment and an extensible set of modules that greatly facilitate the definition of events with triggers and effects interacting with the experiment. We provide a pedagogic example performing dynamic adaptation of fluorescence illumination on bacteria, and demonstrate MicroMator’s potential via two challenging case studies in yeast to single-cell control and single-cell recombination, both requiring real-time tracking and light targeting at the single-cell level.

Suggested Citation

  • Zachary R. Fox & Steven Fletcher & Achille Fraisse & Chetan Aditya & Sebastián Sosa-Carrillo & Julienne Petit & Sébastien Gilles & François Bertaux & Jakob Ruess & Gregory Batt, 2022. "Enabling reactive microscopy with MicroMator," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-29888-z
    DOI: 10.1038/s41467-022-29888-z
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    References listed on IDEAS

    as
    1. Melinda Liu Perkins & Dirk Benzinger & Murat Arcak & Mustafa Khammash, 2020. "Cell-in-the-loop pattern formation with optogenetically emulated cell-to-cell signaling," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    2. Remy Chait & Jakob Ruess & Tobias Bergmiller & Gašper Tkačik & Călin C. Guet, 2017. "Shaping bacterial population behavior through computer-interfaced control of individual cells," Nature Communications, Nature, vol. 8(1), pages 1-11, December.
    3. Chetan Aditya & François Bertaux & Gregory Batt & Jakob Ruess, 2021. "A light tunable differentiation system for the creation and control of consortia in yeast," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    4. Dirk Benzinger & Mustafa Khammash, 2018. "Pulsatile inputs achieve tunable attenuation of gene expression variability and graded multi-gene regulation," Nature Communications, Nature, vol. 9(1), pages 1-10, December.
    5. Adrià Sogues & Mariano Martinez & Quentin Gaday & Mathilde Ben Assaya & Martin Graña & Alexis Voegele & Michael VanNieuwenhze & Patrick England & Ahmed Haouz & Alexandre Chenal & Sylvain Trépout & Ros, 2020. "Essential dynamic interdependence of FtsZ and SepF for Z-ring and septum formation in Corynebacterium glutamicum," Nature Communications, Nature, vol. 11(1), pages 1-14, December.
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    Cited by:

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    2. Michael B. Sheets & Nathan Tague & Mary J. Dunlop, 2023. "An optogenetic toolkit for light-inducible antibiotic resistance," Nature Communications, Nature, vol. 14(1), pages 1-13, December.

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