Pre-existing clusters of the adaptor Lat do not participate in early T cell signaling events

Williamson, David J.; Owen, Dylan M.; Rossy, Jérémie; Magenau, Astrid; Wehrmann, Matthias; Gooding, J. Justin; Gaus, Katharina

doi:10.1038/ni.2049

Cited by 305 publications

(348 citation statements)

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“…Each localisation is then disturbed by Gaussian noise with variance drawn from a Gamma distribution with mean 30 nm and standard deviation 13 nm (emulating the localisation error of the microscope). These parameters were chosen to approximately reflect typical clustering behaviour of proteins at the immunological synapse 14,15,20,21 . The three remaining scenarios have the same parameters as the Standard Conditions except where stated otherwise.…”

Section: Performance and Sensitivity Analysismentioning

confidence: 99%

“…To investigate and quantify clustering behaviour, widely used are Ripley's K-function [14][15][16] and pair-correlation (PC) analysis 17,18 . Both rely on drawing a series of concentric shapes -circles in the case of the K-function and tori in the case of PC -around each localisation and counting the number of neighbours enclosed.…”

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confidence: 99%

“…This provides a principled mechanism for choosing between clustering proposals generated by different algorithms and settings. In this article, clustering proposals are generated using a strategy based on the K-function 14 , with variable spatial scale and threshold. We therefore generate several thousand candidate clustering proposals per ROI, from which the optimum is selected according to the Bayesian model.…”

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confidence: 99%

“…Here, it is accepted that proteins, including the CD3ζ subunit, arrange into microclusters upon synapse formation. While many other biological processes involve the clustering of proteins at the cell surface, this application is especially informative because both the K-function strategy and PC have been applied previously 14,15,20,21 . For experimental data, it is important that artefacts caused by multiple blinking of individual fluorophores and overlapped PSFs, inherent to the methodology of SMLM, are removed (or accounted for).…”

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Bayesian cluster identification in single-molecule localization microscopy data

et al. 2015

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Correspondence should be addressed to patrick. rubin-delanchy@bristol.ac.uk and dylan.owen@kcl.ac.uk Single-molecule identification-based super-resolution microscopy techniques such as photo-activated localisation microscopy (PALM) and stochastic optical reconstruction microscopy (STORM) produce pointillist data sets of molecular coordinates. While many algorithms exist for the identification and localisation of molecules from the raw image data, methods for analysing the resulting point patterns for properties such as clustering have remained relatively under-studied. Here, we present the first model-based Bayesian approach to evaluate molecular cluster assignment proposals which, in this article, are generated by analysis based on Ripley's Kfunction. The method is also the first to take full account of the individual localisation precisions calculated for each emitter. The technique is validated using simulated and experimental data from which we characterise the clustering behaviour of CD3ζ, an important subunit of the CD3-T cell receptor complex required for T cell function, in resting and activated primary human T cells.Conventional fluorescence microscopes produce images of the distribution of fluorophores in the sample convolved with the microscope Point Spread Function (PSF). Due to diffraction, this PSF typically has a width of hundreds of nanometres meaning the resulting image has a resolution, as assessed by the Rayleigh criterion, of ~200 nm. Several strategies now exist to circumvent this resolution limit 1 . Some of these, such as Stimulated Emission Depletion (STED) microscopy, rely on narrowing the excitation spot of a confocal microscope by means of a toroidal depletion beam and the process of stimulated emission 2,3 . Despite the increased resolution, these produce conventional fluorescence images, i.e., arrays of pixels with values representing the fluorescence intensity at those locations. Quantification can be performed in the same way as for conventional microscopes.Another strategy is based on Single-Molecule Localisation Microscopy (SMLM) [4][5][6][7] . This relies on the temporal separation of the excitation of fluorophores in the sample whose PSFs would otherwise overlap at the detector.The position of each fluorophore can then be estimated from the centres of the PSFs. Many algorithms are available to extract the x-y coordinates of the molecules [8][9][10] . Each emitter can be localised to a precision between 10 and 30 nm. Common strategies for the temporal separation of molecules involve intra-molecular rearrangements to switch from dark to fluorescent states or the exploitation of non-emitting molecular radicals 11,12 . These strategies are typically pursued using photoactivatable or photoconvertible fluorescent proteins or small molecule probes coupled with a reducing buffer and immunostaining protocols 13 . We refer to all such strategies as SMLM.Unlike non-pointillist microscopy methods, SMLM imaging does not produce a conventional image. Instead, the raw data is a list of the...

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Section: Performance and Sensitivity Analysismentioning

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Bayesian cluster identification in single-molecule localization microscopy data

et al. 2015

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“…This way the authors showed that TCR signalling depends on Lat molecules that are associated with intracellular vesicles, rather than pre-existing clusters of Lat molecules at the plasma membrane. These observations helped determine that it is vesicular Lat and not plasmamembrane-bound Lat which makes the bulk contribution to signalling [197].…”

Section: Signalling Dynamic Assembly Of Proteinsmentioning

confidence: 97%

Fluorescence nanoscopy. Methods and applications

Requejo-Isidro

2013

J Chem Biol

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Fluorescence nanoscopy refers to the experimental techniques and analytical methods used for fluorescence imaging at a resolution higher than conventional, diffractionlimited, microscopy. This review explains the concepts behind fluorescence nanoscopy and focuses on the latest and promising developments in acquisition techniques, labelling strategies to obtain highly detailed super-resolved images and in the quantitative methods to extract meaningful information from them.

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Immunological Synapse

Agüera-González¹,

Bouchet²,

Alcover³

2015

Encyclopedia of Life Sciences

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International audienceImmunological synapses are dynamically organised cell–cell interfaces formed between cells of the immune system. Different types of immunological synapses lead to distinct functional outcomes. Thus, T and B lymphocytes form immunological synapses with each other and with dendritic cells or macrophages, conveying mutual activation cues. Moreover, natural killer cells or cytotoxic T lymphocytes form synapses with tumour or infected cells delivering cytotoxic granules that destroy those anomalous cells. Immunological synapses are the result of an orchestrated cell polarisation process that involves cytoskeleton rearrangements, intracellular vesicle traffic and the clustering of receptors, adhesion molecules and signalling effectors, which together ensure the immunological synapse stability, its structure and function. Immunological synapses play key roles in immune responses, like T- and B-cell activation, and polarised secretion of cytokines or cytotoxic granules

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Pre-existing clusters of the adaptor Lat do not participate in early T cell signaling events

Cited by 305 publications

References 50 publications

Bayesian cluster identification in single-molecule localization microscopy data

Bayesian cluster identification in single-molecule localization microscopy data

Fluorescence nanoscopy. Methods and applications

Immunological Synapse

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