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Super-resolved trajectory-derived nanoclustering analysis using spatiotemporal indexing

Author

Listed:
  • Tristan P. Wallis

    (The University of Queensland)

  • Anmin Jiang

    (The University of Queensland)

  • Kyle Young

    (The University of Queensland)

  • Huiyi Hou

    (The University of Queensland)

  • Kye Kudo

    (The University of Queensland)

  • Alex J. McCann

    (The University of Queensland)

  • Nela Durisic

    (The University of Queensland)

  • Merja Joensuu

    (The University of Queensland
    The University of Queensland)

  • Dietmar Oelz

    (The University of Queensland)

  • Hien Nguyen

    (The University of Queensland)

  • Rachel S. Gormal

    (The University of Queensland)

  • Frédéric A. Meunier

    (The University of Queensland
    The University of Queensland)

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.

Suggested Citation

  • 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, 2023. "Super-resolved trajectory-derived nanoclustering analysis using spatiotemporal indexing," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-38866-y
    DOI: 10.1038/s41467-023-38866-y
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    References listed on IDEAS

    as
    1. Adekunle T. Bademosi & Elsa Lauwers & Pranesh Padmanabhan & Lorenzo Odierna & Ye Jin Chai & Andreas Papadopulos & Geoffrey J. Goodhill & Patrik Verstreken & Bruno van Swinderen & Frédéric A Meunier, 2017. "Erratum: In vivo single-molecule imaging of syntaxin1A reveals polyphosphoinositide- and activity-dependent trapping in presynaptic nanoclusters," Nature Communications, Nature, vol. 8(1), pages 1-1, April.
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    Cited by:

    1. Wei-Siang Liau & Qiongyi Zhao & Adekunle Bademosi & Rachel S. Gormal & Hao Gong & Paul R. Marshall & Ambika Periyakaruppiah & Sachithrani U. Madugalle & Esmi L. Zajaczkowski & Laura J. Leighton & Haob, 2023. "Fear extinction is regulated by the activity of long noncoding RNAs at the synapse," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    2. Anmin Jiang & Kye Kudo & Rachel S. Gormal & Sevannah Ellis & Sikao Guo & Tristan P. Wallis & Shanley F. Longfield & Phillip J. Robinson & Margaret E. Johnson & Merja Joensuu & Frédéric A. Meunier, 2024. "Dynamin1 long- and short-tail isoforms exploit distinct recruitment and spatial patterns to form endocytic nanoclusters," Nature Communications, Nature, vol. 15(1), pages 1-21, December.
    3. Shanley F. Longfield & Rachel S. Gormal & Matis Feller & Pierre Parutto & Jürgen Reingruber & Tristan P. Wallis & Merja Joensuu & George J. Augustine & Ramón Martínez-Mármol & David Holcman & Frédéric, 2024. "Synapsin 2a tetramerisation selectively controls the presynaptic nanoscale organisation of reserve synaptic vesicles," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    4. Steen W. B. Bender & Marcus W. Dreisler & Min Zhang & Jacob Kæstel-Hansen & Nikos S. Hatzakis, 2024. "SEMORE: SEgmentation and MORphological fingErprinting by machine learning automates super-resolution data analysis," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    5. Shanley F. Longfield & Mahdie Mollazade & Tristan P. Wallis & Rachel S. Gormal & Merja Joensuu & Jesse R. Wark & Ashley J. Waardenberg & Christopher Small & Mark E. Graham & Frédéric A. Meunier & Ramó, 2023. "Tau forms synaptic nano-biomolecular condensates controlling the dynamic clustering of recycling synaptic vesicles," Nature Communications, Nature, vol. 14(1), pages 1-20, December.

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