Authors
Aritra Mondal, Comert Kural
Published in
Frontiers in molecular biosciences. Volume 13. Pages 1844575. Epub Jun 24, 2026.
Abstract
Measuring protein kinetics in living cells remains challenging due to the complexity of intracellular environments and the limitations of live-cell imaging. Clathrin-mediated endocytosis (CME) provides a model system in which protein assembly dynamics encode functional outcomes, yet conventional approaches rely on reconstructing full trajectories of individual events, making them sensitive to tracking errors and difficult to extend to dense or in vivo systems. Here, we review growth rate-based analysis of clathrin assembly as an alternative framework for quantifying endocytic kinetics. By extracting local rates of fluorescence intensity change from short temporal segments, this approach bypasses trajectory reconstruction and instead yields growth rate distributions that robustly capture ensemble dynamics. The standard deviation of these distributions serves as a quantitative metric of kinetic variability and distinguishes distinct dynamical regimes. We highlight how growth-rate analysis reveals key regulatory mechanisms, including membrane tension-dependent modulation of CME and spatiotemporal heterogeneity across cells and tissues, and discuss recent advances leveraging deep learning to infer dynamic behavior from single images. Together, these developments establish a scalable and minimally invasive strategy for measuring protein kinetics in living systems under physiologically relevant conditions.
PMID:
42422881
Bibliographic data and abstract were imported from PubMed on 09 Jul 2026.
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