A hydrophilic gel matrix for single-molecule super-resolution microscopy

Raw Data to Results: A Hands-On Introduction and Overview of Computational Analysis for Single-Molecule Localization Microscopy

Single-molecule localization microscopy (SMLM) is an advanced microscopy method that uses the blinking of fluorescent molecules to determine the position of these molecules with a resolution below the diffraction limit (∼5-40 nm). While SMLM imaging itself is becoming more popular, the computational analysis surrounding the technique is still a specialized area and often remains a "black box" for experimental researchers. Here, we provide an introduction to the required computational analysis of SMLM imaging, post-processing and typical data analysis. Importantly, user-friendly, ready-to-use and well-documented code in Python and MATLAB with exemplary data is provided as an interactive experience for the reader, as well as a starting point for further analysis. Our code is supplemented by descriptions of the computational problems and their implementation. We discuss the state of the art in computational methods and software suites used in SMLM imaging and data analysis. Finally, we give an outlook into further computational challenges in the field.

The N terminus of myosin-binding protein C extends toward actin filaments in intact cardiac muscle

Myosin and actin filaments are highly organized within muscle sarcomeres. Myosin-binding protein C (MyBP-C) is a flexible, rod-like protein located within the C-zone of the sarcomere. The C-terminal domain of MyBP-C is tethered to the myosin filament backbone, and the N-terminal domains are postulated to interact with actin and/or the myosin head to modulate filament sliding. To define where the N-terminal domains of MyBP-C are localized in the sarcomere of active and relaxed mouse myocardium, the relative positions of the N terminus of MyBP-C and actin were imaged in fixed muscle samples using super-resolution fluorescence microscopy. The resolution of the imaging was enhanced by particle averaging. The images demonstrate that the position of the N terminus of MyBP-C is biased toward the actin filaments in both active and relaxed muscle preparations. Comparison of the experimental images with images generated in silico, accounting for known binding partner interactions, suggests that the N-terminal domains of MyBP-C may bind to actin and possibly the myosin head but only when the myosin head is in the proximity of an actin filament. These physiologically relevant images help define the molecular mechanism by which the N-terminal domains of MyBP-C may search for, and capture, molecular binding partners to tune cardiac contractility.

Statistical analysis of 3D localisation microscopy images for quantification of membrane protein distributions in a platelet clot model

We present the software platform 2CALM that allows for a comparative analysis of 3D localisation microscopy data representing protein distributions in two biological samples. The in-depth statistical analysis reveals differences between samples at the nanoscopic level using parameters such as cluster-density and -curvature. An automatic classification system combines multiplex and multi-level statistical approaches into one comprehensive parameter for similarity testing of the compared samples. We demonstrated the biological importance of 2CALM, comparing the protein distributions of CD41 and CD62p on activated platelets in a 3D artificial clot. Additionally, using 2CALM, we quantified the impact of the inflammatory cytokine interleukin-1β on platelet activation in clots. The platform is applicable to any other cell type and biological system and can provide new insights into biological and medical applications.

Postrecording Pixel-Reconstruction Approach for Correcting the Lateral Drifts in Surface Plasmon Resonance Microscope

Surface plasmon resonance microscope (SPRM) sample stage inevitably suffers from lateral drifts as a result of many environmental factors including thermal fluctuation, mechanical vibration, and relaxation. It places great obstacles to time-lapsed imaging and measurements that need high spatial resolution or long recording time. Existing solutions often require experimental efforts such as the addition of optical markers together with piezoelectric stage-based active feedback configurations. Herein, we propose an all-digital, postrecording image-processing method to remove the lateral drift in a series of time-lapsed SPRM images. The method first calculates the value of lateral drift at subpixel accuracy by combining image cross-correlation analysis and superlocalization strategy. It subsequently reconstructed the drift-free image sequences in a pixel-by-pixel and frame-by-frame manner, according to the linear decomposition and reconstruction principle. This method purely relies on image processing, and it does not require any experimental efforts or hardware. In addition to SPRM, we further demonstrated the applicability of the present method in other types of optical imaging techniques including bright-field transmission microscope and dark-field scattering microscope.

The Accuracy of Determining Cluster Size by Analyzing Ripley’s K Function in Single Molecule Localization Microscopy

Ripley’s K function was developed to analyze the spatial distribution characteristics in point pattern analysis, including geography, economics and biomedical research. In biomedical applications, it is popularly used to analyze the clusters of proteins on the cell plasma membrane in single molecule localization microscopy (SMLM), such as photo activated localization microscopy (PALM), stochastic optical reconstruction microscopy (STORM), universal point accumulation imaging in nanoscale topography (uPAINT), etc. Here, by varying the parameters of the simulated clusters on a modeled SMLM image, the effects of cluster size, cluster separation and protein ratio inside/outside the cluster on the accuracy of cluster analysis by analyzing Ripley’s K function were studied. Although the predicted radius of clusters by analyzing Ripley’s K function did not exactly correspond to the actual radius, we suggest the cluster radius could be estimated within a factor of 1.3. Employing peak analysis methods to analyze the experimental epidermal growth factor receptor (EGFR) clusters at fibroblast-like cell lines derived from monkey kidney tissue - COS7 cell surface observed by uPAINT method, the cluster properties were characterized with errors. Our results present quantification of clusters and can be used to enhance the understanding of clusters in SMLM.

Sequential Super-Resolution Imaging of Bacterial Regulatory Proteins: The Nucleoid and the Cell Membrane in Single, Fixed E. coli Cells

Despite their small size and the lack of compartmentalization, bacteria exhibit a striking degree of cellular organization, both in time and space. During the last decade, a group of new microscopy techniques emerged, termed super-resolution microscopy or nanoscopy, which facilitate visualizing the organization of proteins in bacteria at the nanoscale. Single-molecule localization microscopy (SMLM) is especially well suited to reveal a wide range of new information regarding protein organization, interaction, and dynamics in single bacterial cells. Recent developments in click chemistry facilitate the visualization of bacterial chromatin with a resolution of ~20 nm, providing valuable information about the ultrastructure of bacterial nucleoids, especially at short generation times. In this chapter, we describe a simple-to-realize protocol that allows determining precise structural information of bacterial nucleoids in fixed cells, using direct stochastic optical reconstruction microscopy (dSTORM). In combination with quantitative photoactivated localization microscopy (PALM), the spatial relationship of proteins with the bacterial chromosome can be studied. The position of a protein of interest with respect to the nucleoids and the cell cylinder can be visualized by super-resolving the membrane using point accumulation for imaging in nanoscale topography (PAINT). The combination of the different SMLM techniques in a sequential workflow maximizes the information that can be extracted from single cells, while maintaining optimal imaging conditions for each technique.

From single molecules to life: microscopy at the nanoscale

Super-resolution microscopy is the term commonly given to fluorescence microscopy techniques with resolutions that are not limited by the diffraction of light. Since their conception a little over a decade ago, these techniques have quickly become the method of choice for many biologists studying structures and processes of single cells at the nanoscale. In this review, we present the three main approaches used to tackle the diffraction barrier of ∼200 nm: stimulated-emission depletion (STED) microscopy, structured illumination microscopy (SIM), and single-molecule localization microscopy (SMLM). We first present a theoretical overview of the techniques and underlying physics, followed by a practical guide to all of the facets involved in designing a super-resolution experiment, including an approachable explanation of the photochemistry involved, labeling methods available, and sample preparation procedures. Finally, we highlight some of the most exciting recent applications of and developments in these techniques, and discuss the outlook for this field.

Graphical Abstract

Investigating the usage of point spread functions in point source and microsphere localization

Using a point spread function (PSF) to localize a point-like object, such as a fluorescent molecule or microsphere, represents a common task in single molecule microscopy image data analysis. The localization may differ in purpose depending on the application or experiment, but a unifying theme is the importance of being able to closely recover the true location of the point-like object with high accuracy. We present two simulation studies, both relating to the performance of object localization via the maximum likelihood fitting of a PSF to the object's image. In the first study, we investigate the integration of the PSF over an image pixel, which represents a critical part of the localization algorithm. Specifically, we explore how the fineness of the integration affects how well a point source can be localized, and find the use of too coarse a step size to produce location estimates that are far from the true location, especially when the images are acquired at relatively low magnifications. We also propose a method for selecting an appropriate step size. In the second study, we investigate the suitability of the common practice of using a PSF to localize a microsphere, despite the mismatch between the microsphere's image and the fitted PSF. Using criteria based on the standard errors of the mean and variance, we find the method suitable for microspheres up to 1 μm and 100 nm in diameter, when the localization is performed, respectively, with and without the simultaneous estimation of the width of the PSF.

One, two or three? Probing the stoichiometry of membrane proteins by single-molecule localization microscopy

Probing the oligomeric state of abundant molecules, such as membrane proteins in intact cells, is essential, but has not been straightforward. We address this challenge with a simple counting strategy that is capable of reporting the oligomeric state of dense, membrane-bound protein complexes. It is based on single-molecule localization microscopy to super-resolve protein structures in intact cells and basic quantitative evaluation. We validate our method with membrane-bound monomeric CD86 and dimeric cytotoxic T-lymphocyte-associated protein as model proteins and confirm their oligomeric states. We further detect oligomerization of CD80 and vesicular stomatitis virus glycoprotein and propose coexistence of monomers and dimers for CD80 and trimeric assembly of the viral protein at the cell membrane. This approach should prove valuable for researchers striving for reliable molecular counting in cells.

Fluorescent Microspheres as Point Sources: A Localization Study

The localization of fluorescent microspheres is often employed for drift correction and image registration in single molecule microscopy, and is commonly carried out by fitting a point spread function to the image of the given microsphere. The mismatch between the point spread function and the image of the microsphere, however, calls into question the suitability of this localization approach. To investigate this issue, we subject both simulated and experimental microsphere image data to a maximum likelihood estimator that localizes a microsphere by fitting an Airy pattern to its image, and assess the suitability of the approach by evaluating the ability of the estimator to recover the true location of the microsphere with the best possible accuracy as determined based on the Cramér-Rao lower bound. Assessing against criteria based on the standard errors of the mean and the variance for an ideal estimator of the microsphere’s location, we find that microspheres up to 100 nm in diameter can in general be localized using a fixed width Airy pattern, and that microspheres as large as 1 μm in diameter can in general be localized using a floated width Airy pattern.

Drift correction for single-molecule imaging by molecular constraint field, a distance minimum metric

Background

The recent developments of far-field optical microscopy (single molecule imaging techniques) have overcome the diffraction barrier of light and improve image resolution by a factor of ten compared with conventional light microscopy. These techniques utilize the stochastic switching of probe molecules to overcome the diffraction limit and determine the precise localizations of molecules, which often requires a long image acquisition time. However, long acquisition times increase the risk of sample drift. In the case of high resolution microscopy, sample drift would decrease the image resolution.

Results

In this paper, we propose a novel metric based on the distance between molecules to solve the drift correction. The proposed metric directly uses the position information of molecules to estimate the frame drift. We also designed an algorithm to implement the metric for the general application of drift correction. There are two advantages of our method: First, because our method does not require space binning of positions of molecules but directly operates on the positions, it is more natural for single molecule imaging techniques. Second, our method can estimate drift with a small number of positions in each temporal bin, which may extend its potential application.

Conclusions

The effectiveness of our method has been demonstrated by both simulated data and experiments on single molecular images.

Single molecule microscopy in 3D cell cultures and tissues

From the onset of the first microscopic visualization of single fluorescent molecules in living cells at the beginning of this century, to the present, almost routine application of single molecule microscopy, the method has well-proven its ability to contribute unmatched detailed insight into the heterogeneous and dynamic molecular world life is composed of. Except for investigations on bacteria and yeast, almost the entire story of success is based on studies on adherent mammalian 2D cell cultures. However, despite this continuous progress, the technique was not able to keep pace with the move of the cell biology community to adapt 3D cell culture models for basic research, regenerative medicine, or drug development and screening. In this review, we will summarize the progress, which only recently allowed for the application of single molecule microscopy to 3D cell systems and give an overview of the technical advances that led to it. While initially posing a challenge, we finally conclude that relevant 3D cell models will become an integral part of the on-going success of single molecule microscopy.

Eight years of single-molecule localization microscopy

Super-resolution imaging by single-molecule localization (localization microscopy) provides the ability to unravel the structural organization of cells and the composition of biomolecular assemblies at a spatial resolution that is well below the diffraction limit approaching virtually molecular resolution. Constant improvements in fluorescent probes, efficient and specific labeling techniques as well as refined data analysis and interpretation strategies further improved localization microscopy. Today, it allows us to interrogate how the distribution and stoichiometry of interacting proteins in subcellular compartments and molecular machines accomplishes complex interconnected cellular processes. Thus, it exhibits potential to address fundamental questions of cell and developmental biology. Here, we briefly introduce the history, basic principles, and different localization microscopy methods with special focus on direct stochastic optical reconstruction microscopy (dSTORM) and summarize key developments and examples of two- and three-dimensional localization microscopy of the last 8 years.