AI Article Synopsis
- Single-molecule localization microscopy is being used to explore the nanoscale organization of proteins in living cells by focusing on their spatial arrangements.
- Current methods mostly focus on where protein clusters are located without considering how long they last or how often they appear in certain spots.
- Researchers developed a new approach using the R-tree spatial indexing algorithm to analyze protein dynamics over time, leading to a better understanding of the behavior of proteins involved in neuroexocytosis and providing a free Python tool called NASTIC for researchers.
Article Abstract
Single-molecule localization microscopy techniques are emerging as vital tools to unravel the nanoscale world of living cells by understanding the spatiotemporal organization of protein clusters at the nanometer scale. Current analyses define spatial nanoclusters based on detections but neglect important temporal information such as cluster lifetime and recurrence in "hotspots" on the plasma membrane. Spatial indexing is widely used in video games to detect interactions between moving geometric objects. Here, we use the R-tree spatial indexing algorithm to determine the overlap of the bounding boxes of individual molecular trajectories to establish membership in nanoclusters. Extending the spatial indexing into the time dimension allows the resolution of spatial nanoclusters into multiple spatiotemporal clusters. Using spatiotemporal indexing, we found that syntaxin1a and Munc18-1 molecules transiently cluster in hotspots, offering insights into the dynamics of neuroexocytosis. Nanoscale spatiotemporal indexing clustering (NASTIC) has been implemented as a free and open-source Python graphic user interface.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10250379 | PMC |
| http://dx.doi.org/10.1038/s41467-023-38866-y | DOI Listing |
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