Automated analysis of organelle morphology and motility in live-cell imaging, highlighting its utility for cell biology research.
Understanding the dynamics and interactions of intracellular organelles is critical for understanding the mechanisms of cellular homeostasis and disease. Here, we present AutoMorphoTrack, an open-source Python package for automated detection (optional thresholding), morphology classification, motility tracking, and colocalization analysis of mitochondria and lysosomes in live-cell imaging data. The package provides a pipeline capable of processing multichannel time-lapse image stacks, generating organelle-specific segmentations, organelle-specific count, tracking organelle motility, quantifying morphology parameters, and performing frame-by-frame colocalization analysis. We demonstrate the utility of AutoMorphoTrack using a representative dataset, illustrating each analysis step and the associated outputs. This package offers a flexible and scalable tool for organelle dynamics studies, facilitating reproducible and quantitative analysis for the broader cell biology community.
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Bayati et al. (2025) studied this question.
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