3D Bayesian cluster analysis of super-resolution data reveals LAT recruitment to the T cell synapse

Research output: Contribution to journalArticlepeer-review

Standard

3D Bayesian cluster analysis of super-resolution data reveals LAT recruitment to the T cell synapse. / Griffié, Juliette; Shlomovich, Leigh; Williamson, David J.; Shannon, Michael; Aaron, Jesse; Khuon, Satya; Burn, Garth L.; Boelen, Lies; Peters, Ruby; Cope, Andrew P.; Cohen, Edward A.K.; Rubin-Delanchy, Patrick; Owen, Dylan M.

In: Scientific Reports, Vol. 7, No. 1, 4077, 01.12.2017.

Research output: Contribution to journalArticlepeer-review

Harvard

Griffié, J, Shlomovich, L, Williamson, DJ, Shannon, M, Aaron, J, Khuon, S, Burn, GL, Boelen, L, Peters, R, Cope, AP, Cohen, EAK, Rubin-Delanchy, P & Owen, DM 2017, '3D Bayesian cluster analysis of super-resolution data reveals LAT recruitment to the T cell synapse', Scientific Reports, vol. 7, no. 1, 4077. https://doi.org/10.1038/s41598-017-04450-w

APA

Griffié, J., Shlomovich, L., Williamson, D. J., Shannon, M., Aaron, J., Khuon, S., Burn, G. L., Boelen, L., Peters, R., Cope, A. P., Cohen, E. A. K., Rubin-Delanchy, P., & Owen, D. M. (2017). 3D Bayesian cluster analysis of super-resolution data reveals LAT recruitment to the T cell synapse. Scientific Reports, 7(1), [4077]. https://doi.org/10.1038/s41598-017-04450-w

Vancouver

Author

Griffié, Juliette ; Shlomovich, Leigh ; Williamson, David J. ; Shannon, Michael ; Aaron, Jesse ; Khuon, Satya ; Burn, Garth L. ; Boelen, Lies ; Peters, Ruby ; Cope, Andrew P. ; Cohen, Edward A.K. ; Rubin-Delanchy, Patrick ; Owen, Dylan M. / 3D Bayesian cluster analysis of super-resolution data reveals LAT recruitment to the T cell synapse. In: Scientific Reports. 2017 ; Vol. 7, No. 1.

Bibtex

@article{773182144f074425add85620ec2dc0a2,
title = "3D Bayesian cluster analysis of super-resolution data reveals LAT recruitment to the T cell synapse",
abstract = "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.",
author = "Juliette Griffi{\'e} and Leigh Shlomovich and Williamson, {David J.} and Michael Shannon and Jesse Aaron and Satya Khuon and Burn, {Garth L.} and Lies Boelen and Ruby Peters and Cope, {Andrew P.} and Cohen, {Edward A.K.} and Patrick Rubin-Delanchy and Owen, {Dylan M.}",
year = "2017",
month = dec,
day = "1",
doi = "10.1038/s41598-017-04450-w",
language = "English",
volume = "7",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",
number = "1",

}

RIS

TY - JOUR

T1 - 3D Bayesian cluster analysis of super-resolution data reveals LAT recruitment to the T cell synapse

AU - Griffié, Juliette

AU - Shlomovich, Leigh

AU - Williamson, David J.

AU - Shannon, Michael

AU - Aaron, Jesse

AU - Khuon, Satya

AU - Burn, Garth L.

AU - Boelen, Lies

AU - Peters, Ruby

AU - Cope, Andrew P.

AU - Cohen, Edward A.K.

AU - Rubin-Delanchy, Patrick

AU - Owen, Dylan M.

PY - 2017/12/1

Y1 - 2017/12/1

N2 - 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.

AB - 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.

U2 - 10.1038/s41598-017-04450-w

DO - 10.1038/s41598-017-04450-w

M3 - Article

VL - 7

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

IS - 1

M1 - 4077

ER -