Super-resolved trajectory-derived nanoclustering analysis using spatiotemporal indexing
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 neg...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-06-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-023-38866-y |
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| _version_ | 1849234505338978304 |
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| author | Tristan P. Wallis Anmin Jiang Kyle Young Huiyi Hou Kye Kudo Alex J. McCann Nela Durisic Merja Joensuu Dietmar Oelz Hien Nguyen Rachel S. Gormal Frédéric A. Meunier |
| author_facet | Tristan P. Wallis Anmin Jiang Kyle Young Huiyi Hou Kye Kudo Alex J. McCann Nela Durisic Merja Joensuu Dietmar Oelz Hien Nguyen Rachel S. Gormal Frédéric A. Meunier |
| author_sort | Tristan P. Wallis |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-f36f1f2833e14480b10a8a1fee2c2af3 |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2023-06-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-f36f1f2833e14480b10a8a1fee2c2af32025-08-20T04:03:07ZengNature PortfolioNature Communications2041-17232023-06-0114111610.1038/s41467-023-38866-ySuper-resolved trajectory-derived nanoclustering analysis using spatiotemporal indexingTristan P. Wallis0Anmin Jiang1Kyle Young2Huiyi Hou3Kye Kudo4Alex J. McCann5Nela Durisic6Merja Joensuu7Dietmar Oelz8Hien Nguyen9Rachel S. Gormal10Frédéric A. Meunier11Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of QueenslandClem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of QueenslandSchool of Mathematics and Physics, The University of QueenslandClem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of QueenslandClem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of QueenslandClem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of QueenslandQueensland Brain Institute, The University of QueenslandClem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of QueenslandSchool of Mathematics and Physics, The University of QueenslandSchool of Mathematics and Physics, The University of QueenslandClem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of QueenslandClem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of QueenslandAbstract 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.https://doi.org/10.1038/s41467-023-38866-y |
| spellingShingle | Tristan P. Wallis Anmin Jiang Kyle Young Huiyi Hou Kye Kudo Alex J. McCann Nela Durisic Merja Joensuu Dietmar Oelz Hien Nguyen Rachel S. Gormal Frédéric A. Meunier Super-resolved trajectory-derived nanoclustering analysis using spatiotemporal indexing Nature Communications |
| title | Super-resolved trajectory-derived nanoclustering analysis using spatiotemporal indexing |
| title_full | Super-resolved trajectory-derived nanoclustering analysis using spatiotemporal indexing |
| title_fullStr | Super-resolved trajectory-derived nanoclustering analysis using spatiotemporal indexing |
| title_full_unstemmed | Super-resolved trajectory-derived nanoclustering analysis using spatiotemporal indexing |
| title_short | Super-resolved trajectory-derived nanoclustering analysis using spatiotemporal indexing |
| title_sort | super resolved trajectory derived nanoclustering analysis using spatiotemporal indexing |
| url | https://doi.org/10.1038/s41467-023-38866-y |
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