Quantitative Data Analysis in Single-Molecule Localization Microscopy

Machine Learning for Single-Molecule Localization Microscopy: From Data Analysis to Quantification

Single-molecule localization microscopy (SMLM) is a versatile tool for realizing nanoscale imaging with visible light and providing unprecedented opportunities to observe bioprocesses. The integration of machine learning with SMLM enhances data analysis by improving efficiency and accuracy. This tutorial aims to provide a comprehensive overview of the data analysis process and theoretical aspects of SMLM, while also highlighting the typical applications of machine learning in this field. By leveraging advanced analytical techniques, SMLM is becoming a powerful quantitative analysis tool for biological research.

In-section Click-iT detection and super-resolution CLEM analysis of nucleolar ultrastructure and replication in plants

Correlative light and electron microscopy (CLEM) is an important tool for the localisation of target molecule(s) and their spatial correlation with the ultrastructural map of subcellular features at the nanometre scale. Adoption of these advanced imaging methods has been limited in plant biology, due to challenges with plant tissue permeability, fluorescence labelling efficiency, indexing of features of interest throughout the complex 3D volume and their re-localization on micrographs of ultrathin cross-sections. Here, we demonstrate an imaging approach based on tissue processing and embedding into methacrylate resin followed by imaging of sections by both, single-molecule localization microscopy and transmission electron microscopy using consecutive CLEM and same-section CLEM correlative workflow. Importantly, we demonstrate that the use of a particular type of embedding resin is not only compatible with single-molecule localization microscopy but shows improvements in the fluorophore blinking behavior relative to the whole-mount approaches. Here, we use a commercially available Click-iT ethynyl-deoxyuridine cell proliferation kit to visualize the DNA replication sites of wild-type Arabidopsis thaliana seedlings, as well as fasciata1 and nucleolin1 plants and apply our in-section CLEM imaging workflow for the analysis of S-phase progression and nucleolar organization in mutant plants with aberrant nucleolar phenotypes.

Are There Lipid Membrane-Domain Subtypes in Neurons with Different Roles in Calcium Signaling?

Lipid membrane nanodomains or lipid rafts are 10-200 nm diameter size cholesterol- and sphingolipid-enriched domains of the plasma membrane, gathering many proteins with different roles. Isolation and characterization of plasma membrane proteins by differential centrifugation and proteomic studies have revealed a remarkable diversity of proteins in these domains. The limited size of the lipid membrane nanodomain challenges the simple possibility that all of them can coexist within the same lipid membrane domain. As caveolin-1, flotillin isoforms and gangliosides are currently used as neuronal lipid membrane nanodomain markers, we first analyzed the structural features of these components forming nanodomains at the plasma membrane since they are relevant for building supramolecular complexes constituted by these molecular signatures. Among the proteins associated with neuronal lipid membrane nanodomains, there are a large number of proteins that play major roles in calcium signaling, such as ionotropic and metabotropic receptors for neurotransmitters, calcium channels, and calcium pumps. This review highlights a large variation between the calcium signaling proteins that have been reported to be associated with isolated caveolin-1 and flotillin-lipid membrane nanodomains. Since these calcium signaling proteins are scattered in different locations of the neuronal plasma membrane, i.e., in presynapses, postsynapses, axonal or dendritic trees, or in the neuronal soma, our analysis suggests that different lipid membrane-domain subtypes should exist in neurons. Furthermore, we conclude that classification of lipid membrane domains by their content in calcium signaling proteins sheds light on the roles of these domains for neuronal activities that are dependent upon the intracellular calcium concentration. Some examples described in this review include the synaptic and metabolic activity, secretion of neurotransmitters and neuromodulators, neuronal excitability (long-term potentiation and long-term depression), axonal and dendritic growth but also neuronal cell survival and death.

Trends in Single-Molecule Total Internal Reflection Fluorescence Imaging and Their Biological Applications with Lab-on-a-Chip Technology

Single-molecule imaging technologies, especially those based on fluorescence, have been developed to probe both the equilibrium and dynamic properties of biomolecules at the single-molecular and quantitative levels. In this review, we provide an overview of the state-of-the-art advancements in single-molecule fluorescence imaging techniques. We systematically explore the advanced implementations of in vitro single-molecule imaging techniques using total internal reflection fluorescence (TIRF) microscopy, which is widely accessible. This includes discussions on sample preparation, passivation techniques, data collection and analysis, and biological applications. Furthermore, we delve into the compatibility of microfluidic technology for single-molecule fluorescence imaging, highlighting its potential benefits and challenges. Finally, we summarize the current challenges and prospects of fluorescence-based single-molecule imaging techniques, paving the way for further advancements in this rapidly evolving field.

Heterogeneity of Signaling Complex Nanostructure in T Cells Activated Via the T Cell Antigen Receptor

Activation of the T cell antigen receptor (TCR) is a key step in initiating the adaptive immune response. Single-molecule localization techniques have been used to investigate the arrangement of proteins within the signaling complexes formed around activated TCRs, but a clear picture of nanoscale organization in stimulated T cells has not emerged. Here, we have improved the examination of T cell nanostructure by visualizing individual molecules of six different proteins in a single sample of activated Jurkat T cells using the multiplexed antibody-size limited direct stochastic optical reconstruction microscopy (madSTORM) technique. We formally define irregularly shaped regions of interest, compare areas where signaling complexes are concentrated with other areas, and improve the statistical analyses of the locations of molecules. We show that nanoscale organization of proteins is mainly confined to the areas with dense concentrations of TCR-based signaling complexes. However, randomly distributed molecules are also found in some areas containing concentrated signaling complexes. These results are consistent with the view that the proteins within signaling complexes are connected by numerous weak interactions, leading to flexible, dynamic, and mutable structures which produce large variations in the nanostructure found in activated T cells.

Single-molecule localization microscopy goes quantitative

In the last few years, single-molecule localization (SMLM) techniques have been used to address biological questions in different research fields. More recently, super-resolution has also been proposed as a quantitative tool for quantifying protein copy numbers at the nanoscale level. In this scenario, quantitative approaches, mainly based on stepwise photobleaching and quantitative SMLM assisted by calibration standards, offer an exquisite tool for investigating protein complexes. This primer focuses on the basic concepts behind quantitative super-resolution microscopy, also providing strategies to overcome the technical hurdles that could limit their application.

Pore-Forming Proteins: From Pore Assembly to Structure by Quantitative Single-Molecule Imaging

Pore-forming proteins (PFPs) play a central role in many biological processes related to infection, immunity, cancer, and neurodegeneration. A common feature of PFPs is their ability to form pores that disrupt the membrane permeability barrier and ion homeostasis and generally induce cell death. Some PFPs are part of the genetically encoded machinery of eukaryotic cells that are activated against infection by pathogens or in physiological programs to carry out regulated cell death. PFPs organize into supramolecular transmembrane complexes that perforate membranes through a multistep process involving membrane insertion, protein oligomerization, and finally pore formation. However, the exact mechanism of pore formation varies from PFP to PFP, resulting in different pore structures with different functionalities. Here, we review recent insights into the molecular mechanisms by which PFPs permeabilize membranes and recent methodological advances in their characterization in artificial and cellular membranes. In particular, we focus on single-molecule imaging techniques as powerful tools to unravel the molecular mechanistic details of pore assembly that are often obscured by ensemble measurements, and to determine pore structure and functionality. Uncovering the mechanistic elements of pore formation is critical for understanding the physiological role of PFPs and developing therapeutic approaches.

Clathrin coats partially preassemble and subsequently bend during endocytosis

Eukaryotic cells use clathrin-mediated endocytosis to take up a large range of extracellular cargo. During endocytosis, a clathrin coat forms on the plasma membrane, but it remains controversial when and how it is remodeled into a spherical vesicle. Here, we use 3D superresolution microscopy to determine the precise geometry of the clathrin coat at large numbers of endocytic sites. Through pseudo-temporal sorting, we determine the average trajectory of clathrin remodeling during endocytosis. We find that clathrin coats assemble first on flat membranes to 50% of the coat area before they become rapidly and continuously bent, and this mechanism is confirmed in three cell lines. We introduce the cooperative curvature model, which is based on positive feedback for curvature generation. It accurately describes the measured shapes and dynamics of the clathrin coat and could represent a general mechanism for clathrin coat remodeling on the plasma membrane.

Machine learning framework to segment sarcomeric structures in SMLM data

Object detection is an image analysis task with a wide range of applications, which is difficult to accomplish with traditional programming. Recent breakthroughs in machine learning have made significant progress in this area. However, these algorithms are generally compatible with traditional pixelated images and cannot be directly applied for pointillist datasets generated by single molecule localization microscopy (SMLM) methods. Here, we have improved the averaging method developed for the analysis of SMLM images of sarcomere structures based on a machine learning object detection algorithm. The ordered structure of sarcomeres allows us to determine the location of the proteins more accurately by superimposing SMLM images of identically assembled proteins. However, the area segmentation process required for averaging can be extremely time-consuming and tedious. In this work, we have automated this process. The developed algorithm not only finds the regions of interest, but also classifies the localizations and identifies the true positive ones. For training, we used simulations to generate large amounts of labelled data. After tuning the neural network's internal parameters, it could find the localizations associated with the structures we were looking for with high accuracy. We validated our results by comparing them with previous manual evaluations. It has also been proven that the simulations can generate data of sufficient quality for training. Our method is suitable for the identification of other types of structures in SMLM data.

STORM Super-Resolution Imaging of CB1 Receptors in Tissue Preparations

Single-molecule localization microscopy (SMLM) opened new possibilities to study the spatial arrangement of molecular distribution and disease-associated redistribution at a previously unprecedented resolution that was not achievable with optical microscopy approaches. Recent discoveries based on SMLM techniques uncovered specific nanoscale organizational principles of signaling proteins in several biological systems including the chemical synapses in the brain. Emerging data suggest that the spatial arrangement of the molecular players of the endocannabinoid system is also precisely regulated at the nanoscale level in synapses and in other neuronal and glial subcellular compartments. The precise nanoscale distribution pattern is likely to be important to subserve several specific signaling functions of this important messenger system in a cell-type- and subcellular domain-specific manner.STochastic Optical Reconstruction Microscopy (STORM) is an especially suitable SMLM modality for cell-type-specific nanoscale molecular imaging due to its compatibility with traditional diffraction-limited microscopy approaches and classical staining methods. Here, we describe a detailed protocol for STORM imaging in mouse brain tissue samples with a focus on the CB₁ cannabinoid receptor, one of the most abundant synaptic receptors in the brain. We also summarize important conceptual and methodical details that are essential for the valid interpretation of single-molecule localization microscopy data.

Quantitative Analysis of PcG-Associated Condensates by Stochastic Optical Reconstruction Microscopy (STORM)

The polycomb group (PcG) proteins play a central role in the maintenance of a repressive state of gene expression. Recent findings demonstrate that PcG components are organized into nuclear condensates, contributing to the reshaping of chromatin architecture in physiological and pathological conditions, thus affecting the nuclear mechanics. In this context, direct stochastic optical reconstruction microscopy (dSTORM) provides an effective tool to achieve a detailed characterization of PcG condensates by visualizing them at a nanometric level. Furthermore, by analyzing dSTORM datasets with cluster analysis algorithms, quantitative information can be yielded regarding protein numbers, grouping, and spatial organization. Here, we describe how to set up a dSTORM experiment and perform the data analysis to study PcG complexes' components in adhesion cells quantitatively.

Maximum-likelihood model fitting for quantitative analysis of SMLM data

Quantitative data analysis is important for any single-molecule localization microscopy (SMLM) workflow to extract biological insights from the coordinates of the single fluorophores. However, current approaches are restricted to simple geometries or require identical structures. Here, we present LocMoFit (Localization Model Fit), an open-source framework to fit an arbitrary model to localization coordinates. It extracts meaningful parameters from individual structures and can select the most suitable model. In addition to analyzing complex, heterogeneous and dynamic structures for in situ structural biology, we demonstrate how LocMoFit can assemble multi-protein distribution maps of six nuclear pore components, calculate single-particle averages without any assumption about geometry or symmetry, and perform a time-resolved reconstruction of the highly dynamic endocytic process from static snapshots. We provide extensive simulation and visualization routines to validate the robustness of LocMoFit and tutorials to enable any user to increase the information content they can extract from their SMLM data.

Algorithm for Modern Electron Microscopic Examination of the Golgi Complex

The Golgi complex (GC) is an essential organelle of the eukaryotic exocytic pathway. It has a very complexed structure and thus localization of its resident proteins is not trivial. Fast development of microscopic methods generates a huge difficulty for Golgi researchers to select the best protocol to use. Modern methods of light microscopy, such as super-resolution light microscopy (SRLM) and electron microscopy (EM), open new possibilities in analysis of various biological structures at organelle, cell, and organ levels. Nowadays, new generation of EM methods became available for the study of the GC; these include three-dimensional EM (3DEM), correlative light-EM (CLEM), immune EM, and new estimators within stereology that allow realization of maximal goal of any morphological study, namely, to achieve a three-dimensional model of the sample with optimal level of resolution and quantitative determination of its chemical composition. Methods of 3DEM have partially overlapping capabilities. This requires a careful comparison of these methods, identification of their strengths and weaknesses, and formulation of recommendations for their application to cell or tissue samples. Here, we present an overview of 3DEM methods for the study of the GC and some basics for how the images are formed and how the image quality can be improved.

Convex hull as diagnostic tool in single-molecule localization microscopy

MOTIVATION

Single-molecule localization microscopy resolves individual fluorophores or fluorescence-labeled biomolecules. Data are provided as a set of localizations that distribute normally around the true fluorophore position with a variance determined by the localization precision. Characterizing the spatial fluorophore distribution to differentiate between resolution-limited localization clusters, which resemble individual biomolecules, and extended structures, which represent aggregated molecular complexes, is a common challenge.

RESULTS

We demonstrate the use of the convex hull and related hull properties of localization clusters for diagnostic purposes, as a parameter for cluster selection or as a tool to determine localization precision.

AVAILABILITY AND IMPLEMENTATION

https://github.com/super-resolution/Ebert-et-al-2022-supplement.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Application of Lacunarity for Quantification of Single Molecule Localization Microscopy Images

The quantitative analysis of datasets achieved by single molecule localization microscopy is vital for studying the structure of subcellular organizations. Cluster analysis has emerged as a multi-faceted tool in the structural analysis of localization datasets. However, the results it produces greatly depend on the set parameters, and the process can be computationally intensive. Here we present a new approach for structural analysis using lacunarity. Unlike cluster analysis, lacunarity can be calculated quickly while providing definitive information about the structure of the localizations. Using simulated data, we demonstrate how lacunarity results can be interpreted. We use these interpretations to compare our lacunarity analysis with our previous cluster analysis-based results in the field of DNA repair, showing the new algorithm’s efficiency.

Qudi-HiM: an open-source acquisition software package for highly multiplexed sequential and combinatorial optical imaging

Multiplexed sequential and combinatorial imaging enables the simultaneous detection of multiple biological molecules, e.g. proteins, DNA, or RNA, enabling single-cell spatial multi-omics measurements at sub-cellular resolution. Recently, we designed a multiplexed imaging approach (Hi-M) to study the spatial organization of chromatin in single cells. In order to enable Hi-M sequential imaging on custom microscope setups, we developed Qudi-HiM, a modular software package written in Python 3. Qudi-HiM contains modules to automate the robust acquisition of thousands of three-dimensional multicolor microscopy images, the handling of microfluidics devices, and the remote monitoring of ongoing acquisitions and real-time analysis. In addition, Qudi-HiM can be used as a stand-alone tool for other imaging modalities.

Qudi-HiM: an open-source acquisition software package for highly multiplexed sequential and combinatorial optical imaging

Multiplexed sequential and combinatorial imaging enables the simultaneous detection of multiple biological molecules, e.g. proteins, DNA, or RNA, enabling single-cell spatial multi-omics measurements at sub-cellular resolution. Recently, we designed a multiplexed imaging approach (Hi-M) to study the spatial organization of chromatin in single cells. In order to enable Hi-M sequential imaging on custom microscope setups, we developed Qudi-HiM, a modular software package written in Python 3. Qudi-HiM contains modules to automate the robust acquisition of thousands of three-dimensional multicolor microscopy images, the handling of microfluidics devices, and the remote monitoring of ongoing acquisitions and real-time analysis. In addition, Qudi-HiM can be used as a stand-alone tool for other imaging modalities.

Imaging Minimal Bacteria at the Nanoscale: a Reliable and Versatile Process to Perform Single-Molecule Localization Microscopy in Mycoplasmas

Mycoplasmas are the smallest free-living organisms. These bacteria are important models for both fundamental and synthetic biology, owing to their highly reduced genomes. They are also relevant in the medical and veterinary fields, as they are pathogenic to both humans and most livestock species. Mycoplasma cells have minute sizes, often in the 300- to 800-nm range. As these dimensions are close to the diffraction limit of visible light, fluorescence imaging in mycoplasmas is often poorly informative. Recently developed superresolution imaging techniques can break this diffraction limit, improving the imaging resolution by an order of magnitude and offering a new nanoscale vision of the organization of these bacteria. These techniques have, however, not been applied to mycoplasmas before. Here, we describe an efficient and reliable protocol to perform single-molecule localization microscopy (SMLM) imaging in mycoplasmas. We provide a polyvalent transposon-based system to express the photoconvertible fluorescent protein mEos3.2, enabling photo-activated localization microscopy (PALM) in most Mycoplasma species. We also describe the application of direct stochastic optical reconstruction microscopy (dSTORM). We showcase the potential of these techniques by studying the subcellular localization of two proteins of interest. Our work highlights the benefits of state-of-the-art microscopy techniques for mycoplasmology and provides an incentive to further the development of SMLM strategies to study these organisms in the future.

IMPORTANCE Mycoplasmas are important models in biology, as well as highly problematic pathogens in the medical and veterinary fields. The very small sizes of these bacteria, well below a micron, limits the usefulness of traditional fluorescence imaging methods, as their resolution limit is similar to the dimensions of the cells. Here, to bypass this issue, we established a set of state-of-the-art superresolution microscopy techniques in a wide range of Mycoplasma species. We describe two strategies: PALM, based on the expression of a specific photoconvertible fluorescent protein, and dSTORM, based on fluorophore-coupled antibody labeling. With these methods, we successfully performed single-molecule imaging of proteins of interest at the surface of the cells and in the cytoplasm, at lateral resolutions well below 50 nm. Our work paves the way toward a better understanding of mycoplasma biology through imaging of subcellular structures at the nanometer scale.

A coordinate-based co-localization index to quantify and visualize spatial associations in single-molecule localization microscopy

Visualizing the subcellular distribution of proteins and determining whether specific proteins co-localize is one of the main strategies in determining the organization and potential interactions of protein complexes in biological samples. The development of super-resolution microscopy techniques such as single-molecule localization microscopy (SMLM) has tremendously increased the ability to resolve protein distribution at nanometer resolution. As super-resolution imaging techniques are becoming instrumental in revealing novel biological insights, new quantitative approaches that exploit the unique nature of SMLM datasets are required. Here, we present a new, local density-based algorithm to quantify co-localization in dual-color SMLM datasets. We show that this method is broadly applicable and only requires molecular coordinates and their localization precision as inputs. Using simulated point patterns, we show that this method robustly measures the co-localization in dual-color SMLM datasets, independent of localization density, but with high sensitivity towards local enrichments. We further validated our method using SMLM imaging of the microtubule network in epithelial cells and used it to study the spatial association between proteins at neuronal synapses. Together, we present a simple and easy-to-use, but powerful method to analyze the spatial association of molecules in dual-color SMLM datasets.

LOCAN: a python library for analyzing single-molecule localization microscopy data

SUMMARY

Single-molecule localization microscopy has become an important part of the super-resolution microscopy toolbox in biomedical research. Software platforms for applying analytical methods to the point-based data structures are needed that offer both routine application and flexible customization of analysis procedures. We present a python library called LOCAN that consists of well-defined data structures and analysis methods for analyzing localization data in a script or computable notebook.

AVAILABILITY AND IMPLEMENTATION

The package source code is released open-source under a BSD-3 license at https://github.com/super-resolution/Locan. It can be installed form the Python Package Index at https://pypi.org/project/locan. Documentation is available at https://locan.readthedocs.io.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Super-Resolution Microscopy for Structural Cell Biology

Super-resolution microscopy techniques, and specifically single-molecule localization microscopy (SMLM), are approaching nanometer resolution inside cells and thus have great potential to complement structural biology techniques such as electron microscopy for structural cell biology. In this review, we introduce the different flavors of super-resolution microscopy, with a special emphasis on SMLM and MINFLUX (minimal photon flux). We summarize recent technical developments that pushed these localization-based techniques to structural scales and review the experimental conditions that are key to obtaining data of the highest quality. Furthermore, we give an overview of different analysis methods and highlight studies that used SMLM to gain structural insights into biologically relevant molecular machines. Ultimately, we give our perspective on what is needed to push the resolution of these techniques even further and to apply them to investigating dynamic structural rearrangements in living cells. Expected final online publication date for the Annual Review of Biophysics, Volume 51 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Determinants of synapse diversity revealed by super-resolution quantal transmission and active zone imaging

Neural circuit function depends on the pattern of synaptic connections between neurons and the strength of those connections. Synaptic strength is determined by both postsynaptic sensitivity to neurotransmitter and the presynaptic probability of action potential evoked transmitter release (Pr). Whereas morphology and neurotransmitter receptor number indicate postsynaptic sensitivity, presynaptic indicators and the mechanism that sets Pr remain to be defined. To address this, we developed QuaSOR, a super-resolution method for determining Pr from quantal synaptic transmission imaging at hundreds of glutamatergic synapses at a time. We mapped the Pr onto super-resolution 3D molecular reconstructions of the presynaptic active zones (AZs) of the same synapses at the Drosophila larval neuromuscular junction (NMJ). We find that Pr varies greatly between synapses made by a single axon, quantify the contribution of key AZ proteins to Pr diversity and find that one of these, Complexin, suppresses spontaneous and evoked transmission differentially, thereby generating a spatial and quantitative mismatch between release modes. Transmission is thus regulated by the balance and nanoscale distribution of release-enhancing and suppressing presynaptic proteins to generate high signal-to-noise evoked transmission.

Single-Molecule Localization Microscopy of Subcellular Protein Distribution in Neurons

Over the past years several forms of superresolution fluorescence microscopy have been developed that offer the possibility to study cellular structures and protein distribution at a resolution well below the diffraction limit of conventional fluorescence microscopy (<200 nm). A particularly powerful superresolution technique is single-molecule localization microscopy (SMLM). SMLM enables the quantitative investigation of subcellular protein distribution at a spatial resolution up to tenfold higher than conventional imaging, even in live cells. Not surprisingly, SMLM has therefore been used in many applications in biology, including neuroscience. This chapter provides a step-by-step SMLM protocol to visualize the nanoscale organization of endogenous proteins in dissociated neurons but can be extended to image other adherent cultured cells. We outline a number of methods to visualize endogenous proteins in neurons for live-cell and fixed application, including immunolabeling, the use of intrabodies for live-cell SMLM, and endogenous tagging using CRISPR/Cas9.

SUBCELLULAR TRANSCRIPTOMICS & PROTEOMICS: A COMPARATIVE METHODS REVIEW

The internal environment of cells is molecularly crowded, which requires spatial organization via subcellular compartmentalization. These compartments harbor specific conditions for molecules to perform their biological functions, such as coordination of the cell cycle, cell survival, and growth. This compartmentalization is also not static, with molecules trafficking between these subcellular neighborhoods to carry out their functions. For example, some biomolecules are multifunctional, requiring an environment with differing conditions or interacting partners, and others traffic to export such molecules. Aberrant localization of proteins or RNA species has been linked to many pathological conditions, such as neurological, cancer, and pulmonary diseases. Differential expression studies in transcriptomics and proteomics are relatively common, but the majority have overlooked the importance of subcellular information. In addition, subcellular transcriptomics and proteomics data do not always colocate because of the biochemical processes that occur during and after translation, highlighting the complementary nature of these fields. In this review, we discuss and directly compare the current methods in spatial proteomics and transcriptomics, which include sequencing- and imaging-based strategies, to give the reader an overview of the current tools available. We also discuss current limitations of these strategies as well as future developments in the field of spatial -omics.

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Subcellular information of protein and RNA give insights into molecular function.

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This review discusses strategies available to measure subcellular information.

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Hybridization of methods shows promise for exploring the composition of organelles.

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Advances are aiding understanding of the organisation and dynamics of cells.

Single-Molecule Blinking Fluorescence Enhancement by Surface Plasmon-Coupled Emission-Based Substrates for Single-Molecule Localization Imaging

Surface plasmon-coupled emission (SPCE) substrates to enhance the blinking fluorescence of spontaneously blinking fluorophores in single-molecule localization microscopy (SMLM) were fabricated to reduce the excitation power density requirement and reveal the distribution of fluorophore-labeled proteins on a plasma membrane with nanoscale-level resolution. The systemic investigation of the contribution of local field enhancement, modified quantum yield, and emission coupling yield through glass coverslip substrates coated with metal layers of different thicknesses revealed that the silver-layer substrate with a thickness of 44 nm produces the highest SPCE fluorescence in spontaneously blinking fluorophores, and it has a highly directional SPCE fluorescence, which helps improve the detection efficiency. Moreover, the uniform and surface-enhanced field created on the substrate surface is beneficial for fluorescence background reduction in single fluorophore detection and localization, as well as for revealing the real position of fluorophores. Consequently, compared with a glass coverslip substrate, the presented SPCE substrate demonstrated a fluorescence enhancement of 480% and an increase in blinking events from a single spontaneously blinking fluorophore; moreover, the required excitation power density for SMLM imaging was significantly reduced to 23 W cm^-2 for visualizing the distribution of epidermal growth factor receptors (EGFRs) on the basal plasma membrane of A549 lung cancer cells with a localization precision of 19 ± 7 nm. Finally, the fluorophore-labeled EGFRs on the basal plasma membrane in the presence of PIKfyve-specific inhibitor treatment were explored using SPCE-SMLM imaging; the results revealed a distinct reduction in the density of localization events because of a decrease in EGFR abundance at the plasma membranes of the cells.

A Quantitative Perspective of Alpha-Synuclein Dynamics - Why Numbers Matter

The function of synapses depends on spatially and temporally controlled molecular interactions between synaptic components that can be described in terms of copy numbers, binding affinities, and diffusion properties. To understand the functional role of a given synaptic protein, it is therefore crucial to quantitatively characterise its biophysical behaviour in its native cellular environment. Single molecule localisation microscopy (SMLM) is ideally suited to obtain quantitative information about synaptic proteins on the nanometre scale. Molecule counting of recombinant proteins tagged with genetically encoded fluorophores offers a means to determine their absolute copy numbers at synapses due to the known stoichiometry of the labelling. As a consequence of its high spatial precision, SMLM also yields accurate quantitative measurements of molecule concentrations. In addition, live imaging of fluorescently tagged proteins at synapses can reveal diffusion dynamics and local binding properties of behaving proteins under normal conditions or during pathological processes. In this perspective, it is argued that the detailed structural information provided by super-resolution imaging can be harnessed to gain new quantitative information about the organisation and dynamics of synaptic components in cellula. To illustrate this point, I discuss the concentration-dependent aggregation of α-synuclein in the axon and the concomitant changes in the dynamic equilibrium of α-synuclein at synapses in quantitative terms.

Single-molecule imaging of replication fork conflicts at genomic DNA G4 structures in human cells

DNA G-quadruplexes (G4s) are stable, non-canonical DNA secondary structures formed within guanine(G)-rich sequences. While extensively studied in vitro, evidence of the occurrence of G4s in vivo has only recently emerged. The formation of G4 structures may pose an obstacle for diverse DNA transactions including replication, which is linked to mutagenesis and genomic instability. A fundamental question in the field has been whether and how the formation of G4s is coupled to the progression of replication forks. This process has remained undefined largely due to the lack of experimental approaches capable of monitoring the presence of G4s and their association with the replication machinery in cells. Here, we describe a detailed multicolor single-molecule localization microscopy (SMLM) protocol for detecting nanoscale spatial-association of DNA G4s with the cellular replisome complex. This method offers a unique platform for visualizing the mechanisms of G4 formation at the molecular level, as well as addressing key biological questions as to the functional roles of these structures in the maintenance of genome integrity.

Single Molecules Are Your Quanta: A Bottom-Up Approach toward Multidimensional Super-resolution Microscopy

The rise of single-molecule localization microscopy (SMLM) and related super-resolution methods over the past 15 years has revolutionized how we study biological and materials systems. In this Perspective, we reflect on the underlying philosophy of how diffraction-unlimited pictures containing rich spatial and functional information may gradually emerge through the local accumulation of single-molecule measurements. Starting with the basic concepts, we analyze the uniqueness of and opportunities in building up the final picture one molecule at a time. After brief introductions to the more established multicolor and three-dimensional measurements, we highlight emerging efforts to extend SMLM to new dimensions and functionalities as fluorescence polarization, emission spectra, and molecular motions, and discuss rising opportunities and future directions. With single molecules as our quanta, the bottom-up accumulation approach provides a powerful conduit for multidimensional microscopy at the nanoscale.

3D particle averaging and detection of macromolecular symmetry in localization microscopy

Single molecule localization microscopy offers in principle resolution down to the molecular level, but in practice this is limited primarily by incomplete fluorescent labeling of the structure. This missing information can be completed by merging information from many structurally identical particles. In this work, we present an approach for 3D single particle analysis in localization microscopy which hugely increases signal-to-noise ratio and resolution and enables determining the symmetry groups of macromolecular complexes. Our method does not require a structural template, and handles anisotropic localization uncertainties. We demonstrate 3D reconstructions of DNA-origami tetrahedrons, Nup96 and Nup107 subcomplexes of the nuclear pore complex acquired using multiple single molecule localization microscopy techniques, with their structural symmetry deducted from the data.

DNA Manipulation and Single-Molecule Imaging

DNA replication, repair, and recombination in the cell play a significant role in the regulation of the inheritance, maintenance, and transfer of genetic information. To elucidate the biomolecular mechanism in the cell, some molecular models of DNA replication, repair, and recombination have been proposed. These biological studies have been conducted using bulk assays, such as gel electrophoresis. Because in bulk assays, several millions of biomolecules are subjected to analysis, the results of the biological analysis only reveal the average behavior of a large number of biomolecules. Therefore, revealing the elementary biological processes of a protein acting on DNA (e.g., the binding of protein to DNA, DNA synthesis, the pause of DNA synthesis, and the release of protein from DNA) is difficult. Single-molecule imaging allows the analysis of the dynamic behaviors of individual biomolecules that are hidden during bulk experiments. Thus, the methods for single-molecule imaging have provided new insights into almost all of the aspects of the elementary processes of DNA replication, repair, and recombination. However, in an aqueous solution, DNA molecules are in a randomly coiled state. Thus, the manipulation of the physical form of the single DNA molecules is important. In this review, we provide an overview of the unique studies on DNA manipulation and single-molecule imaging to analyze the dynamic interaction between DNA and protein.

Microclusters as T Cell Signaling Hubs: Structure, Kinetics, and Regulation

When T cell receptors (TCRs) engage with stimulatory ligands, one of the first microscopically visible events is the formation of microclusters at the site of T cell activation. Since the discovery of these structures almost 20 years ago, they have been studied extensively in live cells using confocal and total internal reflection fluorescence (TIRF) microscopy. However, due to limits in image resolution and acquisition speed, the spatial relationships of signaling components within microclusters, the kinetics of their assembly and disassembly, and the role of vesicular trafficking in microcluster formation and maintenance were not finely characterized. In this review, we will summarize how new microscopy techniques have revealed novel insights into the assembly of these structures. The sub-diffraction organization of microclusters as well as the finely dissected kinetics of recruitment and disassociation of molecules from microclusters will be discussed. The role of cell surface molecules in microcluster formation and the kinetics of molecular recruitment via intracellular vesicular trafficking to microclusters is described. Finally, the role of post-translational modifications such as ubiquitination in the downregulation of cell surface signaling molecules is also discussed. These results will be related to the role of these structures and processes in T cell activation.

FOCAL3D: A 3-dimensional clustering package for single-molecule localization microscopy

Single-molecule localization microscopy (SMLM) is a powerful tool for studying intracellular structure and macromolecular organization at the nanoscale. The increasingly massive pointillistic data sets generated by SMLM require the development of new and highly efficient quantification tools. Here we present FOCAL3D, an accurate, flexible and exceedingly fast (scaling linearly with the number of localizations) density-based algorithm for quantifying spatial clustering in large 3D SMLM data sets. Unlike DBSCAN, which is perhaps the most commonly employed density-based clustering algorithm, an optimum set of parameters for FOCAL3D may be objectively determined. We initially validate the performance of FOCAL3D on simulated datasets at varying noise levels and for a range of cluster sizes. These simulated datasets are used to illustrate the parametric insensitivity of the algorithm, in contrast to DBSCAN, and clustering metrics such as the F1 and Silhouette score indicate that FOCAL3D is highly accurate, even in the presence of significant background noise and mixed populations of variable sized clusters, once optimized. We then apply FOCAL3D to 3D astigmatic dSTORM images of the nuclear pore complex (NPC) in human osteosaracoma cells, illustrating both the validity of the parameter optimization and the ability of the algorithm to accurately cluster complex, heterogeneous 3D clusters in a biological dataset. FOCAL3D is provided as an open source software package written in Python.

We have developed an accurate, highly-efficient and flexible algorithm for quantifying spatial clustering in large, 3-dimensional single-molecule localization microscopy (SMLM) datasets. Our method, FOCAL3D, is provided as an open-source software package written in Python. FOCAL3D scales linearly with the number of localizations and the algorithmic parameters may be systematically optimized so that the resulting analysis is insensitive to variation over a range of parameter choices. We initially validate the performance and parametric insensitivity of FOCAL3D on simulated datasets, then apply the algorithm to 3-dimensional, astigmatic dSTORM images of the nuclear pore complex in human osteosarcoma cells.