Methods for Tracking Individual Centrioles in Living Cells
DOI:
https://doi.org/10.65649/zpk07v64Keywords:
Centriole, Live-Cell Imaging, Super-Resolution Microscopy, Fluorescent Protein, CRISPR/Cas9, Trajectory AnalysisAbstract
The ability to track individual centrioles in living cells represents a pivotal methodology for advancing our understanding of centrosome biology, cell division, and ciliogenesis. This article provides a comprehensive review of the current methodological landscape for centriole tracking, bridging historical approaches with cutting-edge innovations. We begin by outlining the fundamental challenges—including the organelle's sub-diffraction size, dynamic life cycle, and close pairing—that have historically limited observation. The review then details a hierarchical progression of techniques, from foundational static methods like immunofluorescence and electron microscopy to the direct live-cell imaging enabled by fluorescent protein fusions and advanced microscopy platforms such as spinning-disk confocal and Total Internal Reflection Fluorescence (TIRF) microscopy. A significant focus is placed on super-resolution methods, particularly Stimulated Emission Depletion (STED) microscopy, which allows for the resolution of individual centrioles within a pair in real time. We further explore critical genetic manipulation and labeling strategies, including CRISPR/Cas9-mediated endogenous tagging and photoactivatable proteins for pulse-chase experiments. Practical, detailed protocols for long-term tracking, super-resolution imaging, and lineage analysis are presented, followed by an in-depth discussion of the computational pipeline for data analysis, encompassing object detection, trajectory linking, and quantitative kinetic measurements. Finally, we address common artifacts and mitigation strategies, and conclude by highlighting emerging technologies like correlative light-electron microscopy (CLEM) and lattice light-sheet microscopy (LLSM) that promise to further revolutionize the field by linking dynamic behavior with ultrastructure and enabling studies within complex 3D tissues.
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Copyright (c) 2026 Jaba Tkemaladze (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.
