Correction of multiple-blinking artefacts in photoactivated localisation microscopy

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Poster Session 2
Louis Jensen (1), Tjun Yee Hoh (5), David Williamson (3), Juliette Griffie (2), Daniel Sage (2), Patrick Rubin-Delanchy (5), Dylan Owen (4)
1. Aarhus University
3. King's College London
4. University of Birmingham
5. University of Bristol

PALM, SMLM, Cluster analysis

Abstract text

Photoactivated localisation microscopy (PALM) produces an array of localisation coordinates by means of photoactivatable fluorescent proteins. However, observations are subject to fluorophore multiple-blinking and each protein is included in the dataset an unknown number of times at different positions, due to localisation error. This causes artificial clustering to be observed in the data. We present a workflow using calibration-free estimation of blinking dynamics and model-based clustering, to produce a corrected set of localisation coordinates now representing the true underlying fluorophore locations with enhanced localisation precision. These can be reliably tested for spatial randomness or analysed by other clustering approaches, and previously inestimable descriptors such as the absolute number of fluorophores per cluster are now quantifiable, which we validate with simulated data. Using experimental data, we confirm that the adaptor protein, LAT, is clustered at the T cell immunological synapse, with its nanoscale clustering properties depending on location and intracellular phosphorylatable tyrosine residues.