NASTIC: Nanoscale Spatiotemporal Indexing Clustering
A Toolkit for Visualisation and Quantification of Nanoscale Protein Clustering Dynamics
Overview
NASTIC is a novel computational platform designed to quantify nanoscale protein clustering dynamics in live cells.1,2 Developed at UQ, it processes live cell super resolution microscopy data to detect and track the transient protein assemblies whose dysfunction is implicated in neurodegenerative and other diseases. Unlike traditional static imaging, NASTIC provides real-time spatio-temporal analysis, offering unprecedented insight into early pathological changes. This capability positions NASTIC as a powerful tool for preclinical drug screening and biomarker discovery. Its user-friendly interface and compatibility with standard imaging workflows enhance scalability and adoption potential.
Key Features of NASTIC
- Spatiotemporal clustering of single-molecule trajectory data.
- R-tree spatial indexing for efficient detection of trajectory overlap.
- Identification and quantification of dynamic nanoclusters.
- Measurement of cluster properties including lifetime, size, and recurrence.
- Broad compatibility with single-particle tracking datasets.
- Optional segment-based (SegNASTIC) and DBSCAN based (BOOSH) analysis to improve clustering accuracy in complex environments.
- Extraction of quantitative metrics describing nanoscale protein organisation.
Applications
NASTIC enables the analysis of dynamic nanoscale protein organisation in live cells by interrogating single-molecule tracking datasets. It is used to characterise transient clustering behaviour, including the formation, persistence, and recurrence of molecular assemblies, and supports investigation of protein dynamics in both expressed and endogenous systems. The platform is applicable to a range of experimental contexts, including complex cellular environments such as neurons, where understanding spatiotemporal organisation is critical.
Access
For use of NASTIC only for academic research or teaching, please request the Academic Research and Teaching Licence.
Once orders have been approved, a link will be provided to download NASTIC.
Acknowledgements
The software was developed with supported from an Australian Research Council (ARC) Discovery Project grant (DP190100674), an ARC Linkage Infrastructure Equipment and Facilities grant (LE130100078) and a National Health and Medical Research Council (NHMRC) Senior Research Fellowship (GNT1155794) as well as an ARC Discovery Early Career Research Award (DE190100565), an NHMRC Project Grant (GNT 1147600), an ARC Discovery Project (DP180102956) and National Institute On Aging of the National Institutes of Health Award Number R21AG080435.
The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies.
Attributions
Design and coding: Tristan Wallis
Additional coding: Alex McCann, Kyle Young
Debugging: Sophie Huiyi Hou, Kye Kudo
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expand_more library_books References (2)
- Wallis, T.P., Jiang, A., Young, K. et al. (2023), Super-resolved trajectory-derived nanoclustering analysis using spatiotemporal indexing, Nature Communications, 14, 3353
- Gormal R.S., Wallis T.P., McCann A.J., et al (2025), Nanoscale spatiotemporal cluster analysis of expressed and endogenous proteins, Nature Protocols, 20, 3655
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expand_more cloud_download Supporting documents (1)Product brochureNASTIC: Nanoscale Spatiotemporal Indexing Clustering.pdfAdditional files may be available once you've completed the transaction for this product. If you've already done so, please log into your account and visit My account / Downloads section to view them.