Single-particle tracking (SPT) is a powerful method for exploring single-molecule dynamics in living cells with nanoscale spatiotemporal resolution. Photostability and bright fluorescence make quantum dots (Qdots) a popular choice for SPT. However, their large size could potentially alter the mobility of the molecule of interest. To test this, we labelled B cell receptors on the surface of B-lymphocytes with monovalent Fab fragments of antibodies that were either linked to Qdots via streptavidin or directly conjugated to the small organic fluorophore Cy3. Imaging of receptor mobility by total internal reflection fluorescence microscopy (TIRFM), followed by quantitative single-molecule diffusion and confinement analysis, definitively showed that Qdots sterically hinder lateral mobility regardless of the substrate to which the cells were adhered. Qdot labelling also drastically altered the frequency with which receptors transitioned between apparent slow- and fast-moving states and reduced the size of apparent confinement zones. Although we show that Qdot-labelled probes can detect large differences in receptor mobility, they fail to resolve subtle differences in lateral diffusion that are readily detectable using Cy3-labelled Fabs. Our findings highlight the utility and limitations of using Qdots for TIRFM and wide-field-based SPT, and have significant implications for interpreting SPT data.
A novel 3D imaging system based on single-molecule localization microscopy is presented to allow high-accuracy drift-free (<0.7 nm lateral; 2.5 nm axial) imaging many microns deep into a cell. When imaging deep within the cell, distortions of the point-spread function result in an inaccurate and very compressed Z distribution. For the system to accurately represent the position of each blink, a series of depth-dependent calibrations are required. The system and its allied methodology are applied to image the ryanodine receptor in the cardiac myocyte. Using the depth-dependent calibration, the receptors deep within the cell are spread over a Z range that is many hundreds of nanometers greater than implied by conventional analysis. We implemented a time domain filter to detect overlapping blinks that were not filtered by a stringent goodness of fit criterion. This filter enabled us to resolve the structure of the individual (30 nm square) receptors giving a result similar to that obtained with electron tomography.
Single-molecule localization microscopy (SMLM) has become an essential tool for examining a wide variety of biological structures and processes. However, the relatively long acquisition time makes SMLM prone to drift-induced artifacts. Here we report an optical design with an electrically tunable lens (ETL) that actively stabilizes a SMLM in three dimensions and nearly eliminates the mechanical drift (RMS ~0.7 nm lateral and ~2.7 nm axial). The bifocal design that employed fiducial markers on the coverslip was able to stabilize the sample regardless of the imaging depth. The effectiveness of the ETL was demonstrated by imaging endosomal transferrin receptors near the apical surface of B-lymphocytes at a depth of 8 µm. The drift-free images obtained with the stabilization system showed that the transferrin receptors were present in distinct but heterogeneous clusters with a bimodal size distribution. In contrast, the images obtained without the stabilization system showed a broader unimodal size distribution. Thus, this stabilization system enables a more accurate analysis of cluster topology. Additionally, this ETL-based stabilization system is cost-effective and can be integrated into existing microscopy systems.
1Clustering of proteins is crucial for many cellular processes and can be imaged at nanoscale resolution using 2 single-molecule localization microscopy (SMLM). Existing cluster analysis methods for SMLM data suffer 3 from major limitations, such as unsuitability for heterogeneous datasets, failure to account for uncertainties 4 in localization data, excessive computation time, or inability to analyze three-dimensional data. To address 5 these shortcomings, we developed StormGraph, an algorithm using graph theory and community detection 6 to identify and quantify clusters in heterogeneous 2D and 3D SMLM datasets. StormGraph accounts for 7 localization uncertainties and, by determining thresholds adaptively, it allows many heterogeneous samples 8 to be analyzed using identical parameters. Consequently, StormGraph improves the potential accuracy, 9 objectivity, and throughput of cluster analysis. Furthermore, StormGraph generates a hierarchical clustering, 10 and it quantifies cluster colocalization for two-color SMLM data. We use simulated data to show that 11 StormGraph is superior to existing algorithms. Finally, we demonstrate its application to two-dimensional 12 B-cell antigen receptor clustering and three-dimensional intracellular LAMP-1 clustering. 13 Single-molecule localization microscopy (SMLM) techniques, such as direct stochastic optical reconstruc-15 tion microscopy (dSTORM) (1; 2) and photoactivated localization microscopy (PALM) (3), overcome the 16 diffraction limit of conventional microscopy by acquiring many sequential images, each containing very few 17 fluorescing labels. Individual labels can then be computationally super-resolved and precisely localized to 18 generate a list of localization coordinates, often with estimated positional uncertainties (4; 5; 6). This is 19 possible in both two and three dimensions (7; 8; 9; 10). 20 SMLM is commonly used to investigate nanoscale clustering of cell-membrane and intracellular proteins ), which usually exhibits both cell-to-cell and within-cell heterogene-22 ity. Notwithstanding, clustering is frequently analyzed using spatial summary statistics that fail to capture 23 the heterogeneity of clusters within a sample, such as Ripley's functions (21; 22). Instead, clusters can be 24 individually quantified by using a clustering algorithm to assign localizations to specific clusters. However, 25 using existing clustering algorithms, it is difficult to accurately and objectively analyze multiple heteroge-26 neous samples. Subjective bias can result from algorithm parameter selection, or from selection of a small 27 number of "representative samples" to analyze using slow or cumbersome algorithms. Failure to account for 28 localization uncertainties can also make conclusions unreliable. 29 The most widely used clustering algorithms in SMLM literature, including Density-Based Spatial Cluster-30 ing of Applications with Noise (DBSCAN) (23), identify clusters based on a user-specified minimum number 31 of points within a user-specified radius. However, these ...
Marginal zone (MZ) B cells exist in a partially-activated ‘primed’ state but the molecular basis for this priming is not fully understood. We found that MZ B cells exhibit greater antigen-independent ‘tonic’ BCR signaling than naïve follicular (FO) B cells. Because BCR signaling output is dependent on BCR spatial organization and BCR-BCR interactions, we hypothesized that the increased tonic BCR signaling in MZ B cells is due to altered lateral mobility and nanoscale organization of BCRs. Single-particle tracking showed that surface IgM-BCRs on MZ B cells have higher diffusion coefficients and decreased confinement compared to IgM-BCRs on FO B cells. In contrast, the mobility and confinement of IgD-BCRs was similar on MZ and FO B cells. To assess BCR nanoscale organization, we used dSTORM and a novel graph-based clustering algorithm. This revealed that IgM-BCRs were more dispersed and less clustered on MZ B cells than on FO B cells, whereas IgD-BCR spatial organization was similar on the two cell populations. Importantly, 3-color STED imaging revealed that phospho-CD79 nanoclusters overlapped to a much greater extent with IgM-BCRs than with IgD-BCRs on FO B cells, and that this IgM-pCD79 overlap was even greater in MZ B cells. MZ B cells also exhibited greater pCD79 signaling in response to membrane-bound antigens than FO B cells. Thus, MZ B cells have greater tonic and antigen-dependent BCR signaling, which correlates with altered IgM-BCR mobility and organization
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.