Protocol for machine-learning-based 3D image analysis of nuclear envelope tubules in cultured cells.

Journal: STAR protocols
Published Date: Jul 31, 2024

Abstract

The nuclear envelope can form complex structures in physiological and pathological contexts. Current approaches to quantify nuclear envelope structures can be time-consuming or inaccurate. Here, we present a protocol to measure nuclear envelope tubules induced by DNA double-strand breaks using a mid-throughput approach. We describe steps for the induction of these nuclear envelope structures and 3D image analysis using machine-learning-based image segmentation. This protocol can be applied to analyze various nuclear envelope structures in contexts beyond DNA repair. For complete details on the use and execution of this protocol, please refer to Shokrollahi et al..

Authors

  • Anisha Hundal
    Department of Laboratory Medicine and Pathobiology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada; Princess Margaret Cancer Research Centre, University Health Network, Toronto, ON, Canada.
  • Defne Urman
    Department of Laboratory Medicine and Pathobiology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
  • Mia Stanic
    Department of Laboratory Medicine and Pathobiology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
  • Razqallah Hakem
    Department of Laboratory Medicine and Pathobiology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada; Princess Margaret Cancer Research Centre, University Health Network, Toronto, ON, Canada; Department of Medical Biophysics, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada. Electronic address: razq.hakem@uhn.ca.
  • Karim Mekhail
    Department of Laboratory Medicine and Pathobiology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada; Temerty Centre for AI Research and Education in Medicine, University of Toronto, Toronto, ON, Canada; College of New Scholars, Artists and Scientists, The Royal Society of Canada, Ottawa, ON, Canada. Electronic address: karim.mekhail@utoronto.ca.

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