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2017 ; 7
(1
): 4077
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gab.com Text
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3D Bayesian cluster analysis of super-resolution data reveals LAT recruitment to
the T cell synapse
#MMPMID28642595
Griffié J
; Shlomovich L
; Williamson DJ
; Shannon M
; Aaron J
; Khuon S
; L Burn G
; Boelen L
; Peters R
; Cope AP
; Cohen EAK
; Rubin-Delanchy P
; Owen DM
Sci Rep
2017[Jun]; 7
(1
): 4077
PMID28642595
show ga
Single-molecule localisation microscopy (SMLM) allows the localisation of
fluorophores with a precision of 10-30?nm, revealing the cell's nanoscale
architecture at the molecular level. Recently, SMLM has been extended to 3D,
providing a unique insight into cellular machinery. Although cluster analysis
techniques have been developed for 2D SMLM data sets, few have been applied to
3D. This lack of quantification tools can be explained by the relative novelty of
imaging techniques such as interferometric photo-activated localisation
microscopy (iPALM). Also, existing methods that could be extended to 3D SMLM are
usually subject to user defined analysis parameters, which remains a major
drawback. Here, we present a new open source cluster analysis method for 3D SMLM
data, free of user definable parameters, relying on a model-based Bayesian
approach which takes full account of the individual localisation precisions in
all three dimensions. The accuracy and reliability of the method is validated
using simulated data sets. This tool is then deployed on novel experimental data
as a proof of concept, illustrating the recruitment of LAT to the T-cell
immunological synapse in data acquired by iPALM providing ~10?nm isotropic
resolution.
|Adaptor Proteins, Signal Transducing/*metabolism
[MESH]