Coordinate-based colocalization analysis of single-molecule localization microscopy data

Colocalization of differently labeled biomolecules is a valuable tool in fluorescence microscopy and can provide information on biomolecular interactions. With the advent of super-resolution microscopy, colocalization analysis is getting closer to molecular resolution, bridging the gap to other technologies such as fluorescence resonance energy transfer. Among these novel microscopic techniques, single-molecule localization-based super-resolution methods offer the advantage of providing single-molecule coordinates that, rather than intensity information, can be used for colocalization analysis. This requires adapting the existing mathematical algorithms for localization microscopy data. Here, we introduce an algorithm for coordinate-based colocalization analysis which is suited for single-molecule super-resolution data. In addition, we present an experimental configuration for simultaneous dual-color imaging together with a robust approach to correct for optical aberrations with an accuracy of a few nanometers. We demonstrate the potential of our approach for cellular structures and for two proteins binding actin filaments.     

Optimization of cell morphology measurement via single-molecule tracking PALM

In neurons, the shape of dendritic spines relates to synapse function, which is rapidly altered during experience-dependent neural plasticity. The small size of spines makes detailed measurement of their morphology in living cells best suited to super-resolution imaging techniques. The distribution of molecular positions mapped via live-cell Photoactivated Localization Microscopy (PALM) is a powerful approach, but molecular motion complicates this analysis and can degrade overall resolution of the morphological reconstruction. Nevertheless, the motion is of additional interest because tracking single molecules provides diffusion coefficients, bound fraction, and other key functional parameters. We used Monte Carlo simulations to examine features of single-molecule tracking of practical utility for the simultaneous determination of cell morphology. We find that the accuracy of determining both distance and angle of motion depend heavily on the precision with which molecules are localized. Strikingly, diffusion within a bounded region resulted in an inward bias of localizations away from the edges, inaccurately reflecting the region structure. This inward bias additionally resulted in a counterintuitive reduction of measured diffusion coefficient for fast-moving molecules; this effect was accentuated by the long camera exposures typically used in single-molecule tracking. Thus, accurate determination of cell morphology from rapidly moving molecules requires the use of short integration times within each image to minimize artifacts caused by motion during image acquisition. Sequential imaging of neuronal processes using excitation pulses of either 2 ms or 10 ms within imaging frames confirmed this: processes appeared erroneously thinner when imaged using the longer excitation pulse. Using this pulsed excitation approach, we show that PALM can be used to image spine and spine neck morphology in living neurons. These results clarify a number of issues involved in interpretation of single-molecule data in living cells and provide a method to minimize artifacts in single-molecule experiments.     

Quantifying and Optimizing Single-Molecule Switching Nanoscopy at High Speeds

Single-molecule switching nanoscopy overcomes the diffraction limit of light by stochastically switching single fluorescent molecules on and off, and then localizing their positions individually. Recent advances in this technique have greatly accelerated the data acquisition speed and improved the temporal resolution of super-resolution imaging. However, it has not been quantified whether this speed increase comes at the cost of compromised image quality. The spatial and temporal resolution depends on many factors, among which laser intensity and camera speed are the two most critical parameters. Here we quantitatively compare the image quality achieved when imaging Alexa Fluor 647-immunolabeled microtubules over an extended range of laser intensities and camera speeds using three criteria – localization precision, density of localized molecules, and resolution of reconstructed images based on Fourier Ring Correlation. We found that, with optimized parameters, single-molecule switching nanoscopy at high speeds can achieve the same image quality as imaging at conventional speeds in a 5–25 times shorter time period. Furthermore, we measured the photoswitching kinetics of Alexa Fluor 647 from single-molecule experiments, and, based on this kinetic data, we developed algorithms to simulate single-molecule switching nanoscopy images. We used this software tool to demonstrate how laser intensity and camera speed affect the density of active fluorophores and influence the achievable resolution. Our study provides guidelines for choosing appropriate laser intensities for imaging Alexa Fluor 647 at different speeds and a quantification protocol for future evaluations of other probes and imaging parameters.     

Real-Time Analysis and Visualization for Single-Molecule Based Super-Resolution Microscopy

Accurate multidimensional localization of isolated fluorescent emitters is a time consuming process in single-molecule based super-resolution microscopy. We demonstrate a functional method for real-time reconstruction with automatic feedback control, without compromising the localization accuracy. Compatible with high frame rates of EM-CCD cameras, it relies on a wavelet segmentation algorithm, together with a mix of CPU/GPU implementation. A combination with Gaussian fitting allows direct access to 3D localization. Automatic feedback control ensures optimal molecule density throughout the acquisition process. With this method, we significantly improve the efficiency and feasibility of localization-based super-resolution microscopy.     

Recent Advances in Super-Resolution Fluorescence Imaging and Its Applications in Biology

Fluorescence microscopy has become an essential tool for biological research because it can be minimally invasive, acquire data rapidly, and target molecules of interest with specific labeling strategies. However, the diffraction-limited spatial resolution, which is classically limited to about 200 nm in the lateral direction and about 500 nm in the axial direction, hampers its application to identify delicate details of subcellular structure. Extensive efforts have been made to break diffraction limit for obtaining high-resolution imaging of a biological specimen. Various methods capable of obtaining super-resolution images with a resolution of tens of nanometers are currently available. These super-resolution techniques can be generally divided into three primary classes： （1） patterned illumination- based super-resolution imaging, which employs spatially and temporally modulated illumination light to reconstruct sub-diffraction structures; （2） single-molecule localization-based super-resolution imaging, which localizes the profile center of each individual fluo- rophore at subdiffraction precision; （3） bleaching/blinking-based super-resolution imaging. These super-resolution techniques have been utilized in different biological fields and provide novel insights into several new aspects of life science. Given unique technical merits and commercial availability of super-resolution fluorescence microscope, increasing applications of this powerful technique in life science can be expected.     

Faster STORM using compressed sensing

In super-resolution microscopy methods based on single-molecule switching, the rate of accumulating single-molecule activation events often limits the time resolution. Here we developed a sparse-signal recovery technique using compressed sensing to analyze images with highly overlapping fluorescent spots. This method allows an activated fluorophore density an order of magnitude higher than what conventional single-molecule fitting methods can handle. Using this method, we demonstrated imaging microtubule dynamics in living cells with a time resolution of 3 s.     

A Microfluidic Platform for Correlative Live-Cell and Super-Resolution Microscopy

Recently, super-resolution microscopy methods such as stochastic optical reconstruction microscopy (STORM) have enabled visualization of subcellular structures below the optical resolution limit. Due to the poor temporal resolution, however, these methods have mostly been used to image fixed cells or dynamic processes that evolve on slow time-scales. In particular, fast dynamic processes and their relationship to the underlying ultrastructure or nanoscale protein organization cannot be discerned. To overcome this limitation, we have recently developed a correlative and sequential imaging method that combines live-cell and super-resolution microscopy. This approach adds dynamic background to ultrastructural images providing a new dimension to the interpretation of super-resolution data. However, currently, it suffers from the need to carry out tedious steps of sample preparation manually. To alleviate this problem, we implemented a simple and versatile microfluidic platform that streamlines the sample preparation steps in between live-cell and super-resolution imaging. The platform is based on a microfluidic chip with parallel, miniaturized imaging chambers and an automated fluid-injection device, which delivers a precise amount of a specified reagent to the selected imaging chamber at a specific time within the experiment. We demonstrate that this system can be used for live-cell imaging, automated fixation, and immunostaining of adherent mammalian cells in situ followed by STORM imaging. We further demonstrate an application by correlating mitochondrial dynamics, morphology, and nanoscale mitochondrial protein distribution in live and super-resolution images.     

Virtual-'Light-Sheet' Single-Molecule Localisation Microscopy Enables Quantitative Optical Sectioning for Super-Resolution Imaging

Single-molecule super-resolution microscopy allows imaging of fluorescently-tagged proteins in live cells with a precision well below that of the diffraction limit. Here, we demonstrate 3D sectioning with single-molecule super-resolution microscopy by making use of the fitting information that is usually discarded to reject fluorophores that emit from above or below a virtual-''light-sheet'', a thin volume centred on the focal plane of the microscope. We describe an easy-to-use routine (implemented as an open-source ImageJ plug-in) to quickly analyse a calibration sample to define and use such a virtual light-sheet. In addition, the plug-in is easily usable on almost any existing 2D super-resolution instrumentation. This optical sectioning of super-resolution images is achieved by applying well-characterised width and amplitude thresholds to diffraction-limited spots that can be used to tune the thickness of the virtual light-sheet. This allows qualitative and quantitative imaging improvements: by rejecting out-of-focus fluorophores, the super-resolution image gains contrast and local features may be revealed; by retaining only fluorophores close to the focal plane, virtual-''light-sheet'' single-molecule localisation microscopy improves the probability that all emitting fluorophores will be detected, fitted and quantitatively evaluated.     

Calcium regulation of nucleocytoplasmic transport

Bidirectional trafficking of macromolecules between the cytoplasm and the nucleus is mediated by the nuclear pore complexes (NPCs) embedded in the nuclear envelope (NE) of eukaryotic cell. The NPC functions as the sole pathway to allow for the passive diffusion of small molecules and the facilitated translocation of larger molecules. Evidence shows that these two transport modes and the conformation of NPC can be regulated by calcium stored in the lumen of nuclear envelope and endoplasmic reticulum. However, the mechanism of calcium regulation remains poorly understood. In this review, we integrate data on the observations of calcium-regulated structure and function of the NPC over the past years. Furthermore, we highlight challenges in the measurements of dynamic conformational changes and transient transport kinetics in the NPC. Finally, an innovative imaging approach, single-molecule super-resolution fluorescence microscopy, is introduced and expected to provide more insights into the mechanism of calcium-regulated nucleocytoplasmic transport.     

Nanoscale Imaging of Caveolin-1 Membrane Domains In Vivo

Light microscopy enables noninvasive imaging of fluorescent species in biological specimens, but resolution is generally limited by diffraction to ~200–250 nm. Many biological processes occur on smaller length scales, highlighting the importance of techniques that can image below the diffraction limit and provide valuable single-molecule information. In recent years, imaging techniques have been developed which can achieve resolution below the diffraction limit. Utilizing one such technique, fluorescence photoactivation localization microscopy (FPALM), we demonstrated its ability to construct super-resolution images from single molecules in a living zebrafish embryo, expanding the realm of previous super-resolution imaging to a living vertebrate organism. We imaged caveolin-1 in vivo, in living zebrafish embryos. Our results demonstrate the successful image acquisition of super-resolution images in a living vertebrate organism, opening several opportunities to answer more dynamic biological questions in vivo at the previously inaccessible nanoscale.     

Graph ranking based butterfly segmentation in ecological images

An accurate cultural insect detection and recognition relies mainly on a proper automatic segmentation. This paper deals with butterfly segmentation in ecological images characterized by several artifacts like the complexity of environmental decors and cluttered backgrounds. The distractors contained in the rich ecological environment and the huge difference between butterfly species complicate severely the segmentation and make it a challenging task. As butterflies appears to be well contrasted from their surrounding, we suggest to explore the saliency property to delineate accurately the butterfly boundaries. In this vein, we perform a graph ranking process with high level guidance according to foreground and background cues to improve the quality of segmentation. The ranking accuracy is improved through a weighting scheme that combines accurately color, texture and spatial information. The contribution of each used feature is controlled according to its relevance in highlighting butterfly regions. After that, we initialize foreground seeds from most salient pixels and background seeds from less salient pixels as an input for a Graph-cut algorithm to extract the butterfly from the background. Comparative evaluation has shown that our segmentation scheme outperforms some existing segmentation methods that provide high segmentation scores.     

DNA and chromatin imaging with super-resolution fluorescence microscopy based on single-molecule localization

With the expansion of super-resolution fluorescence microscopy methods, it is now possible to access the organization of cells and materials at the nanoscale by optical means. This review discusses recent progress in super-resolution imaging of isolated and cell DNA using single-molecule localization methods. A high labeling density of photoswitchable fluorophores is crucial for these techniques, which can be provided by sequence independent DNA stains in which photoblinking reactions can be induced. In particular, unsymmetrical cyanine intercalating dyes in combination with special buffers can be used to image isolated DNA with a spatial resolution of 30-40 nm. For super-resolution imaging of chromatin, cell permeant cyanine dyes that bind the minor groove of DNA have the potential to become a useful alternative to the labeling of histones and other DNA-associated proteins. Other recent developments that are interesting in this context such as high density labeling methods or new DNA probes with photoswitching functionalities are also surveyed. Progress in labeling, optics, and single-molecule localization algorithms is being rapid, and it is likely to provide real insight into DNA structuring in cells and materials.     

Super-resolution Imaging Reveals the Internal Architecture of Nano-sized Syntaxin Clusters

Key synaptic proteins from the soluble SNARE (N-ethylmaleimide-sensitive factor attachment protein receptor) family, among many others, are organized at the plasma membrane of cells as clusters containing dozens to hundreds of protein copies. However, the exact membranal distribution of proteins into clusters or as single molecules, the organization of molecules inside the clusters, and the clustering mechanisms are unclear due to limitations of the imaging and analytical tools. Focusing on syntaxin 1 and SNAP-25, we implemented direct stochastic optical reconstruction microscopy together with quantitative clustering algorithms to demonstrate a novel approach to explore the distribution of clustered and nonclustered molecules at the membrane of PC12 cells with single-molecule precision. Direct stochastic optical reconstruction microscopy images reveal, for the first time, solitary syntaxin/SNAP-25 molecules and small clusters as well as larger clusters. The nonclustered syntaxin or SNAP-25 molecules are mostly concentrated in areas adjacent to their own clusters. In the clusters, the density of the molecules gradually decreases from the dense cluster core to the periphery. We further detected large clusters that contain several density gradients. This suggests that some of the clusters are formed by unification of several clusters that preserve their original organization or reorganize into a single unit. Although syntaxin and SNAP-25 share some common distributional features, their clusters differ markedly from each other. SNAP-25 clusters are significantly larger, more elliptical, and less dense. Finally, this study establishes methodological tools for the analysis of single-molecule-based super-resolution imaging data and paves the way for revealing new levels of membranal protein organization.     

蜻蜒运动检测神经元的光谱反应

蜻蜒腹神经束上存在着自运动检测神经元和目标运动检测神经元.我们采用了两种视觉刺激条件来测试自运动检测神经元的光谱反应.当采用控制强度和波长的闪光进行测试时、它们的光谱反应曲线与绿色光感受器的光谱灵敏度曲线极其相似,峰值位于500nm处.然而采用运动的条纹进行测试时,它们的峰值却位于560nm处.当用一种颜色的运动图案作为目标放置在另一种颜色背景的前方测试时,发现存在某个目标的照明强度值能使反应下降到自发放电的水平,这表明自运动检测器无法检测这二种颜色的差别,即它们是色盲的、它主要接受来自绿色光感受器的信号.目标运动检测神经元的光谱反应特性与自运动检测神经元的不同,目标运动检测神经元在以380nm至580nm的范围中有着平坦的光谱反应曲线,有时在紫外频段出现峰有(?)前景与背景颜色不同且固定背景光的颜色与强度而改变前景的光强时,神经元的反应不会下降到自发放电水平,当背景为绿色而目标为另一个颜色.特别是兰色时,神经元反应强烈,但当背景为兰色而目标为绿色时,它们的反应相对较弱.这些结果表明目标运动检测神经元是对颜色敏感的.     

A simple, versatile method for GFP-based super-resolution microscopy via nanobodies

We developed a method to use any GFP-tagged construct in single-molecule super-resolution microscopy. By targeting GFP with small, high-affinity antibodies coupled to organic dyes, we achieved nanometer spatial resolution and minimal linkage error when analyzing microtubules, living neurons and yeast cells. We show that in combination with libraries encoding GFP-tagged proteins, virtually any known protein can immediately be used in super-resolution microscopy and that simplified labeling schemes allow high-throughput super-resolution imaging.     

Super-resolution localization microscopy with photoactivatable fluorescent marker proteins

Fluorescent proteins (FPs) have become popular imaging tools because of their high specificity, minimal invasive labeling and allowing visualization of proteins and structures inside living organisms. FPs are genetically encoded and expressed in living cells, therefore, labeling involves minimal effort in comparison to approaches involving synthetic dyes. Photoactivatable FPs (paFPs) comprise a subclass of FPs that can change their absorption/emission properties such as brightness and color upon irradiation. This methodology has found a broad range of applications in the life sciences, especially in localization-based super-resolution microscopy of cells, tissues and even entire organisms. In this review, we discuss recent developments and applications of paFPs in super-resolution localization imaging.     

Super-Resolution Imaging Strategies for Cell Biologists Using a Spinning Disk Microscope

In this study we use a spinning disk confocal microscope (SD) to generate super-resolution images of multiple cellular features from any plane in the cell. We obtain super-resolution images by using stochastic intensity fluctuations of biological probes, combining Photoactivation Light-Microscopy (PALM)/Stochastic Optical Reconstruction Microscopy (STORM) methodologies. We compared different image analysis algorithms for processing super-resolution data to identify the most suitable for analysis of particular cell structures. SOFI was chosen for X and Y and was able to achieve a resolution of ca. 80 nm; however higher resolution was possible >30 nm, dependant on the super-resolution image analysis algorithm used. Our method uses low laser power and fluorescent probes which are available either commercially or through the scientific community, and therefore it is gentle enough for biological imaging. Through comparative studies with structured illumination microscopy (SIM) and widefield epifluorescence imaging we identified that our methodology was advantageous for imaging cellular structures which are not immediately at the cell-substrate interface, which include the nuclear architecture and mitochondria. We have shown that it was possible to obtain two coloured images, which highlights the potential this technique has for high-content screening, imaging of multiple epitopes and live cell imaging.     

Super-resolution Imaging of the Cytokinetic Z Ring in Live Bacteria Using Fast 3D-Structured Illumination Microscopy (f3D-SIM)

Imaging of biological samples using fluorescence microscopy has advanced substantially with new technologies to overcome the resolution barrier of the diffraction of light allowing super-resolution of live samples. There are currently three main types of super-resolution techniques – stimulated emission depletion (STED), single-molecule localization microscopy (including techniques such as PALM, STORM, and GDSIM), and structured illumination microscopy (SIM). While STED and single-molecule localization techniques show the largest increases in resolution, they have been slower to offer increased speeds of image acquisition. Three-dimensional SIM (3D-SIM) is a wide-field fluorescence microscopy technique that offers a number of advantages over both single-molecule localization and STED. Resolution is improved, with typical lateral and axial resolutions of 110 and 280 nm, respectively and depth of sampling of up to 30 µm from the coverslip, allowing for imaging of whole cells. Recent advancements (fast 3D-SIM) in the technology increasing the capture rate of raw images allows for fast capture of biological processes occurring in seconds, while significantly reducing photo-toxicity and photobleaching. Here we describe the use of one such method to image bacterial cells harboring the fluorescently-labelled cytokinetic FtsZ protein to show how cells are analyzed and the type of unique information that this technique can provide.     

Quantitative analysis of photoactivated localization microscopy (PALM) datasets using pair-correlation analysis

Pointillistic based super-resolution techniques, such as photoactivated localization microscopy (PALM), involve multiple cycles of sequential activation, imaging, and precise localization of single fluorescent molecules. A super-resolution image, having nanoscopic structural information, is then constructed by compiling all the image sequences. Because the final image resolution is determined by the localization precision of detected single molecules and their density, accurate image reconstruction requires imaging of biological structures labeled with fluorescent molecules at high density. In such image datasets, stochastic variations in photon emission and intervening dark states lead to uncertainties in identification of single molecules. This, in turn, prevents the proper utilization of the wealth of information on molecular distribution and quantity. A recent strategy for overcoming this problem is pair-correlation analysis applied to PALM. Using rigorous statistical algorithms to estimate the number of detected proteins, this approach allows the spatial organization of molecules to be quantitatively described.