4.8 Article

Automated segmentation and tracking of mitochondria in live-cell time-lapse images

Journal

NATURE METHODS
Volume 18, Issue 9, Pages 1091-+

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41592-021-01234-z

Keywords

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Funding

  1. National Institutes of Health [P41-GM103540]
  2. National Science Foundation [DMS1763272, 1847005, NSF GRFP DGE1839285]
  3. Simons Foundation [594598 QN]
  4. National Cancer Institute [1R01CA234496, K22 CA190511]
  5. American Cancer Society [132551-RSG-18-19401-DDC]
  6. V Foundation [V2019-019]
  7. Canadian Institutes of Health Research Postdoctoral Fellowship
  8. National Institutes of Health
  9. Directorate For Engineering [1847005] Funding Source: National Science Foundation
  10. Div Of Chem, Bioeng, Env, & Transp Sys [1847005] Funding Source: National Science Foundation

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Mitometer is an algorithm for fast, unbiased, and automated segmentation and tracking of mitochondria in live-cell time-lapse images, which can identify mitochondrial motion and morphology, including fusion and fission events. Using Mitometer, it was found that mitochondria in triple-negative breast cancer cells are faster, more directional, and more elongated than those in receptor-positive counterparts. Furthermore, mitochondrial motility and morphology in breast cancer, but not in normal breast epithelia, correlate with metabolic activity.
Mitochondria display complex morphology and movements, which complicates their segmentation and tracking in time-lapse images. Here, we introduce Mitometer, an algorithm for fast, unbiased, and automated segmentation and tracking of mitochondria in live-cell two-dimensional and three-dimensional time-lapse images. Mitometer requires only the pixel size and the time between frames to identify mitochondrial motion and morphology, including fusion and fission events. The segmentation algorithm isolates individual mitochondria via a shape- and size-preserving background removal process. The tracking algorithm links mitochondria via differences in morphological features and displacement, followed by a gap-closing scheme. Using Mitometer, we show that mitochondria of triple-negative breast cancer cells are faster, more directional, and more elongated than those in their receptor-positive counterparts. Furthermore, we show that mitochondrial motility and morphology in breast cancer, but not in normal breast epithelia, correlate with metabolic activity. Mitometer is an unbiased and user-friendly tool that will help resolve fundamental questions regarding mitochondrial form and function. Mitometer enables efficient, rapid, and accurate automated segmentation and tracking of mitochondria from time-lapse images. Mitometer performs well on diverse input images and can be used to monitor dynamic fission and fusion events.

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