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Data from: Cholesterol and ORP1L dependent clustering of dynein on endolysosmes in cells 2 revealed by super resolution microscopy

Cite this dataset

Lakadamyali, Melike; Thakur, Shreyasi (2021). Data from: Cholesterol and ORP1L dependent clustering of dynein on endolysosmes in cells 2 revealed by super resolution microscopy [Dataset]. Dryad.


The sub-cellular positioning of endolysosomes is crucial for regulating their function. Particularly, the positioning of endolysosomes between the cell periphery versus the peri-nuclear region impacts autophagy, mTOR (mechanistic target of rapamycin) signaling and other processes. The mechanisms that regulate the positioning of endolysosomes at these two locations are still being uncovered. Here, using quantitative super-resolution microscopy in intact cells, we show that the retrograde motor dynein forms nano-clusters on endolysosomal membranes containing 1-2 dyneins, with an average of ~3 nanoclusters per endolysosome. These data suggest that a very small number of dynein motors (1-6) drive endolysosome motility inside cells. Surprisingly, dynein nano-clusters are slightly larger on peripheral endolysosomes having higher cholesterol levels compared to peri-nuclear ones. By perturbing endolysosomal membrane cholesterol levels, we show that dynein copy number within nano-clusters is influenced by the amount of endolysosomal cholesterol while the total number of nano-clusters per endolysosome is independent of cholesterol. Finally, we show that the dynein adapter protein ORP1L (Oxysterol Binding Protein Homologue) regulates the number of dynein motors within nano-clusters in response to cholesterol levels. We propose a new model by which endolysosomal transport and positioning is influenced by the cholesterol sensing adapter protein ORP1L, which influences dynein’s copy number within nano-clusters.

Usage notes

The source data is organized by figure number and corresponds to the data used to make the bar plots in Figures 1, 2 and 4. Each source data is an excel file containing columns of numbers. Each column corresponds to a condition tested in the manuscript and the title of each column describes the condition tested such as "no treatment", "low cholesterol" and "high cholesterol". An additional title is provided when the measurement was done on peripheral or peri-nuclear endolysosomes separately ("peripheral" and "peri-nuclear"). When this secondary title is omitted, the measurement was done on all endolysosomes. Finally, each column has a third title corresponding to the measured entity such as "number of localizations", "filipin intensity". For the histogram in Figure 3, matlab files in the form of .mat is included. The Read Me text file describes the content and data structure. These files can be used with the Matlab code diposited on Github (melikelab/elife) to generate the histograms and perform the statistical analysis.