Dissecting the actin cortex density and membrane-cortex distance in living cells by super-resolution microscopy

Clausen, Mathias P.; Colin‐York, Huw; Schneider, Falk; Eggeling, Christian; Fritzsche, Marco

doi:10.1088/1361-6463/aa52a1

Cited by 65 publications

(55 citation statements)

References 38 publications

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“…In recent decades, fluorescence-based imaging technology has made a great leap forward from basic wide-field microscopes to complex super-resolution imaging systems [1][2][3][4]. To-date, modern fluorescence microscopy offers diverse opportunities to specifically label and study the dynamics of single or multiple molecules, protein clusters and/or complete structures of interest at unprecedented detail [5][6][7]. Consequently, a myriad of imaging modes is available as turn-key commercial setups [5].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Potential of Airyscan Microscopy for Live Cell Imaging

et al. 2017

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Biological research increasingly demands the use of non-invasive and ultra-sensitive imaging techniques. The Airyscan technology was recently developed to bridge the gap between conventional confocal and super-resolution microscopy. This technique combines confocal imaging with a 0.2 Airy Unit pinhole, deconvolution and the pixel-reassignment principle in order to enhance both the spatial resolution and signal-to-noise-ratio without increasing the excitation power and acquisition time. Here, we present a detailed study evaluating the performance of Airyscan as compared to confocal microscopy by imaging a variety of reference samples and biological specimens with different acquisition and processing parameters. We found that the processed Airyscan images at default deconvolution settings have a spatial resolution similar to that of conventional confocal imaging with a pinhole setting of 0.2 Airy Units, but with a significantly improved signal-to-noise-ratio. Further gains in the spatial resolution could be achieved by the use of enhanced deconvolution filter settings, but at a steady loss in the signal-to-noise ratio, which at more extreme settings resulted in significant data loss and image distortion.

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Section: Introductionmentioning

confidence: 99%

Exploring the Potential of Airyscan Microscopy for Live Cell Imaging

et al. 2017

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“…Consistent with this line of thought, high mechanical stress and large indentations on the length‐scale of the cell height resulted in poor mechanoadaptation, which is in contrast to favored cell adhesion on hard surfaces in the gigapascal range . Similarly, indentations in the order of the cortex thickness, but small compared to the average length of formin‐mediated F‐actin, yielded no significant mechanoadaptation. From the mechanical point of view, formins are well known to contribute to mechanosensation .…”

Section: Summary Of Frap Fitting Parameters In Living Hela Cells Sinmentioning

confidence: 57%

Simultaneous Quantification of the Interplay Between Molecular Turnover and Cell Mechanics by AFM–FRAP

Skamrahl

Colin‐York

Barbieri

et al. 2019

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of their actin cytoskeleton. [5][6][7][8][9] Despite the significance for cell function, [10,11] our understanding of the interplay of cell mechanics and its underlying actin kinetics controlling the adaptive mechanical behavior of cells remains at best correlative from independent measurements.Fluorescence recovery after photobleaching (FRAP) is perhaps the most successful quantification methodology of molecule kinetics and dynamics, owing to its versatility to measure reaction and diffusion dynamics at the right spatiotemporal scales. [12][13][14] In a typical FRAP experiment, a small region of interest (ROI) is bleached by a short exposure to highpower laser light, and subsequently the recovery of fluorescently tagged molecules is monitored over time. [15][16][17][18] The shape of the FRAP recovery curve, the so-called mobile fraction, reflects all of the complexity of the reaction diffusion dynamics of the molecule of interest. Using a theoretical model or numerical simulations for the analysis of the molecular actions combined with knowledge of the recovery time(s) of the respective molecule, the reaction kinetics and diffusion dynamics can be calculated and interpreted. [19][20][21] Analysis of the experiments reveals whether a molecule undergoes reaction kinetics or diffusion dynamics or a combination of both processes. [13,22] The presence of a substantial immobile fraction may be the result of the loss of fluorescence due to imaging as experienced by the fluorescent molecules during image acquisition, or it may signify that recovery has been followed over a duration that is short in comparison with the molecule's actual recovery time. [13] To this end, FRAP has been employed to identify and quantify the different types of filamentous actin (F-actin), their turnover dynamics, and lengths in the actin cortex, lamellipodium, and stress fibers. [22][23][24][25][26] Atomic force microscopy (AFM) is the most broadly used quantification methodology of cell mechanics. AFM allows the precise quantification and application of mechanical forces on the apical cell surface with piconewton (pN) resolution. [27][28][29][30][31] For the application of mechanical force over a microscaled subregion of a cell, the cantilever tip is typically functionalized with a micron-sized fluorescent bead, and then exerted against the apical cell surface. Using AFM electronic feedback loops allows the recording of nanoscale force indentations of the cell surface as a function of the applied constant mechanical force. For example, this type of approach has been applied to investigate the biological behavior and function of living cells in response to external mechanical force. [32,33] Quantifying the adaptive mechanical behavior of living cells is essential for the understanding of their inner working and function. Yet, despite the establishment of quantitative methodologies correlating independent mea surements of cell mechanics and its underlying molecular kinetics, explicit evidence and knowledge of the sensitivity of the feedback me...

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“…This is evident in the case of prominent receptors such as MHC class I and II (12,13), IL-1 receptor α-subunit, transferrin receptor (14), FcεRI (15,16), CD1d (17), BCR -IgM, IgD, CD19 (18), NK cell receptors (19), and the leucocyte HA receptor CD44 (20)(21)(22)(23). The cortical actin cytoskeleton consists of filaments (F-actin) that form a complex network in close contact with the cytoplasmic surface of the plasma membrane (< 10 -20 nm) (24). This network is highly dynamic and the filaments are actively turned over by Arp2/3-mediated branching and formin-mediated extension, leading to changes in F-actin filament length, network mesh size and cortex-membrane distance.…”

Section: Introductionmentioning

confidence: 99%

The cortical actin network regulates avidity-dependent binding of hyaluronan by the lymphatic vessel endothelial receptor LYVE-1

Stanly

Fritzsche

Banerji

et al. 2020

Journal of Biological Chemistry

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Lymphatic vessel endothelial hyaluronan receptor 1 (LYVE-1) mediates the docking and entry of dendritic cells to lymphatic vessels through selective adhesion to its ligand hyaluronan in the leukocyte surface glycocalyx. To bind hyaluronan efficiently, LYVE-1 must undergo surface clustering, a process that is induced efficiently by the large cross-linked assemblages of glycosaminoglycan present within leukocyte pericellular matrices but is induced poorly by the shorter polymer alone. These properties suggested that LYVE-1 may have limited mobility in the endothelial plasma membrane, but no biophysical investigation of these parameters has been carried out to date. Here, using super-resolution fluorescence microscopy and spectroscopy combined with biochemical analyses of the receptor in primary lymphatic endothelial cells, we provide the first evidence that LYVE-1 dynamics are indeed restricted by the submembranous actin network. We show that actin disruption not only increases LYVE-1 lateral diffusion but also enhances hyaluronan-binding activity. However, unlike the related leukocyte HA receptor CD44, which uses ERM and ankyrin motifs within its cytoplasmic tail to bind actin, LYVE-1 displays little if any direct interaction with actin, as determined by co-immunoprecipitation. Instead, as shown by super-resolution stimulated emission depletion microscopy in combination with fluorescence correlation spectroscopy, LYVE-1 diffusion is restricted by transient entrapment within submembranous actin corrals. These results point to an actin-mediated constraint on LYVE-1 clustering in lymphatic endothelium that tunes the receptor for selective engagement with hyaluronan assemblages in the glycocalyx that are large enough to cross-bridge the corral-bound LYVE-1 molecules and thereby facilitate leukocyte adhesion and transmigration.

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Dissecting the actin cortex density and membrane-cortex distance in living cells by super-resolution microscopy

Cited by 65 publications

References 38 publications

Exploring the Potential of Airyscan Microscopy for Live Cell Imaging

Exploring the Potential of Airyscan Microscopy for Live Cell Imaging

Simultaneous Quantification of the Interplay Between Molecular Turnover and Cell Mechanics by AFM–FRAP

The cortical actin network regulates avidity-dependent binding of hyaluronan by the lymphatic vessel endothelial receptor LYVE-1

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