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

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.¹.