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© Institut Pasteur
Cells infected for 24 hrs with C. Trachomatis. The cell nuclei are labelled in blue, the bacteria appear yellow, within the inclusion lumen. A bacterial protein secreted out the inclusion into the host cytoplasm id labelled in red.
Scientific Fields
Diseases
Organisms
Applications
Technique

Published in Nature communications - 22 Apr 2022

Fox ZR, Fletcher S, Fraisse A, Aditya C, Sosa-Carrillo S, Petit J, Gilles S, Bertaux F, Ruess J, Batt G,

Link to Pubmed [PMID] – 35459274

Link to DOI – 10.1038/s41467-022-29888-z

Nat Commun 2022 Apr; 13(1): 2199

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.

https://pubmed.ncbi.nlm.nih.gov/35459274