Model-independent counting of molecules in single-molecule localization microscopy

Toward quantitative super-resolution microscopy: molecular maps with statistical guarantees

Quantifying the number of molecules from fluorescence microscopy measurements is an important topic in cell biology and medical research. In this work, we present a consecutive algorithm for super-resolution (stimulated emission depletion (STED)) scanning microscopy that provides molecule counts in automatically generated image segments and offers statistical guarantees in form of asymptotic confidence intervals. To this end, we first apply a multiscale scanning procedure on STED microscopy measurements of the sample to obtain a system of significant regions, each of which contains at least one molecule with prescribed uniform probability. This system of regions will typically be highly redundant and consists of rectangular building blocks. To choose an informative but non-redundant subset of more naturally shaped regions, we hybridize our system with the result of a generic segmentation algorithm. The diameter of the segments can be of the order of the resolution of the microscope. Using multiple photon coincidence measurements of the same sample in confocal mode, we are then able to estimate the brightness and number of molecules and give uniform confidence intervals on the molecule counts for each previously constructed segment. In other words, we establish a so-called molecular map with uniform error control. The performance of the algorithm is investigated on simulated and real data.

Channelrhodopsin-2 Oligomerization in Cell Membrane Revealed by Photo-Activated Localization Microscopy

Microbial rhodopsins are retinal membrane proteins that found a broad application in optogenetics. The oligomeric state of rhodopsins is important for their functionality and stability. Of particular interest is the oligomeric state in the cellular native membrane environment. Fluorescence microscopy provides powerful tools to determine the oligomeric state of membrane proteins directly in cells. Among these methods is quantitative photoactivated localization microscopy (qPALM) allowing the investigation of molecular organization at the level of single protein clusters. Here, we apply qPALM to investigate the oligomeric state of the first and most used optogenetic tool Channelrhodopsin-2 (ChR2) in the plasma membrane of eukaryotic cells. ChR2 appeared predominantly as a dimer in the cell membrane and did not form higher oligomers. The disulfide bonds between Cys34 and Cys36 of adjacent ChR2 monomers were not required for dimer formation and mutations disrupting these bonds resulted in only partial monomerization of ChR2. The monomeric fraction increased when the total concentration of mutant ChR2 in the membrane was low. The dissociation constant was estimated for this partially monomerized mutant ChR2 as 2.2±0.9 proteins/μm2 . Our findings are important for understanding the mechanistic basis of ChR2 activity as well as for improving existing and developing future optogenetic tools.

Molecular basis of JAK2 activation in erythropoietin receptor and pathogenic JAK2 signaling

Janus kinase 2 (JAK2) mediates type I/II cytokine receptor signaling, but JAK2 is also activated by somatic mutations that cause hematological malignancies by mechanisms that are still incompletely understood. Quantitative superresolution microscopy (qSMLM) showed that erythropoietin receptor (EpoR) exists as monomers and dimerizes upon Epo stimulation or through the predominant JAK2 pseudokinase domain mutations (V617F, K539L, and R683S). Crystallographic analysis complemented by kinase activity analysis and atomic-level simulations revealed distinct pseudokinase dimer interfaces and activation mechanisms for the mutants: JAK V617F activity is driven by dimerization, K539L involves both increased receptor dimerization and kinase activity, and R683S prevents autoinhibition and increases catalytic activity and drives JAK2 equilibrium toward activation state through a wild-type dimer interface. Artificial intelligence-guided modeling and simulations revealed that the pseudokinase mutations cause differences in the pathogenic full-length JAK2 dimers, particularly in the FERM-SH2 domains. A detailed molecular understanding of mutation-driven JAK2 hyperactivation may enable novel therapeutic approaches to selectively target pathogenic JAK2 signaling.

Quasi-equilibrium state based quantification of biological macromolecules in single-molecule localization microscopy

The stoichiometry of molecular components within supramolecular biological complexes is often an important property to understand their biological functioning, particularly within their native environment. While there are well established methods to determine stoichiometryin vitro, it is presently challenging to precisely quantify this propertyin vivo,especially with single molecule resolution that is needed for the characterization stoichiometry heterogeneity. Previous work has shown that optical microscopy can provide some information to this end, but it can be challenging to obtain highly precise measurements at higher densities of fluorophores. Here we provide a simple approach using already established procedures in single-molecule localization microscopy (SMLM) to enable precise quantification of stoichiometry within individual complexes regardless of the density of fluorophores. We show that by focusing on the number of fluorophore detections accumulated during the quasi equilibrium-state of this process, this method yields a 50-fold improvement in precision over values obtained from images with higher densities of active fluorophores. Further, we show that our method yields more correct estimates of stoichiometry with nuclear pore complexes and is easily adaptable to quantify the DNA content with nanodomains of chromatin within individual chromosomes inside cells. Thus, we envision that this straightforward method may become a common approach by which SMLM can be routinely employed for the accurate quantification of subunit stoichiometry within individual complexes within cells.

Temporally resolved SMLM (with large PAR shift) enabled visualization of dynamic HA cluster formation and migration in a live cell

The blinking properties of a single molecule are critical for single-molecule localization microscopy (SMLM). Typically, SMLM techniques involve recording several frames of diffraction-limited bright spots of single-molecules with a detector exposure time close to the blinking period. This sets a limit on the temporal resolution of SMLM to a few tens of milliseconds. Realizing that a substantial fraction of single molecules emit photons for time scales much shorter than the average blinking period, we propose accelerating data collection to capture these fast emitters. Here, we put forward a short exposure-based SMLM (shortSMLM) method powered by sCMOS detector for understanding dynamical events (both at single molecule and ensemble level). The technique is demonstrated on an Influenza-A disease model, where NIH3T3 cells (both fixed and live cells) were transfected by Dendra2-HA plasmid DNA. Analysis shows a 2.76-fold improvement in the temporal resolution that comes with a sacrifice in spatial resolution, and a particle resolution shift PAR-shift (in terms of localization precision) of [Formula: see text] 11.82  nm compared to standard SMLM. We visualized dynamic HA cluster formation in transfected cells post 24 h of DNA transfection. It is noted that a reduction in spatial resolution does not substantially alter cluster characteristics (cluster density, [Formula: see text] molecules/cluster, cluster spread, etc.) and, indeed, preserves critical features. Moreover, the time-lapse imaging reveals the dynamic formation and migration of Hemagglutinin (HA) clusters in a live cell. This suggests that [Formula: see text] using a synchronized high QE sCMOS detector (operated at short exposure times) is excellent for studying temporal dynamics in cellular system.

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.

An anti-HER2 biparatopic antibody that induces unique HER2 clustering and complement-dependent cytotoxicity

Human epidermal growth factor receptor 2 (HER2) is a receptor tyrosine kinase that plays an oncogenic role in breast, gastric and other solid tumors. However, anti-HER2 therapies are only currently approved for the treatment of breast and gastric/gastric esophageal junction cancers and treatment resistance remains a problem. Here, we engineer an anti-HER2 IgG1 bispecific, biparatopic antibody (Ab), zanidatamab, with unique and enhanced functionalities compared to both trastuzumab and the combination of trastuzumab plus pertuzumab (tras + pert). Zanidatamab binds adjacent HER2 molecules in trans and initiates distinct HER2 reorganization, as shown by polarized cell surface HER2 caps and large HER2 clusters, not observed with trastuzumab or tras + pert. Moreover, zanidatamab, but not trastuzumab nor tras + pert, elicit potent complement-dependent cytotoxicity (CDC) against high HER2-expressing tumor cells in vitro. Zanidatamab also mediates HER2 internalization and downregulation, inhibition of both cell signaling and tumor growth, antibody-dependent cellular cytotoxicity (ADCC) and phagocytosis (ADCP), and also shows superior in vivo antitumor activity compared to tras + pert in a HER2-expressing xenograft model. Collectively, we show that zanidatamab has multiple and distinct mechanisms of action derived from the structural effects of biparatopic HER2 engagement.

Towards Unbiased Fluorophore Counting in Superresolution Fluorescence Microscopy

With the advent of fluorescence superresolution microscopy, nano-sized structures can be imaged with a previously unprecedented accuracy. Therefore, it is rapidly gaining importance as an analytical tool in the life sciences and beyond. However, the images obtained so far lack an absolute scale in terms of fluorophore numbers. Here, we use, for the first time, a detailed statistical model of the temporal imaging process which relies on a hidden Markov model operating on two timescales. This allows us to extract this information from the raw data without additional calibration measurements. We show this on the basis of added data from experiments on single Alexa 647 molecules as well as GSDIM/dSTORM measurements on DNA origami structures with a known number of labeling positions.

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.

Photoswitching fingerprint analysis bypasses the 10-nm resolution barrier

Advances in super-resolution microscopy have demonstrated single-molecule localization precisions of a few nanometers. However, translation of such high localization precisions into sub-10-nm spatial resolution in biological samples remains challenging. Here we show that resonance energy transfer between fluorophores separated by less than 10 nm results in accelerated fluorescence blinking and consequently lower localization probabilities impeding sub-10-nm fluorescence imaging. We demonstrate that time-resolved fluorescence detection in combination with photoswitching fingerprint analysis can be used to determine the number and distance even of spatially unresolvable fluorophores in the sub-10-nm range. In combination with genetic code expansion with unnatural amino acids and bioorthogonal click labeling with small fluorophores, photoswitching fingerprint analysis can be used advantageously to reveal information about the number of fluorophores present and their distances in the sub-10-nm range in cells.

Analysis of conditional colocalization relationships and hierarchies in three-color microscopy images

Colocalization analysis of multicolor microscopy images is a cornerstone approach in cell biology. It provides information on the localization of molecules within subcellular compartments and allows the interrogation of known molecular interactions in their cellular context. However, almost all colocalization analyses are designed for two-color images, limiting the type of information that they reveal. Here, we describe an approach, termed "conditional colocalization analysis," for analyzing the colocalization relationships between three molecular entities in three-color microscopy images. Going beyond the question of whether colocalization is present or not, it addresses the question of whether the colocalization between two entities is influenced, positively or negatively, by their colocalization with a third entity. We benchmark the approach and showcase its application to investigate receptor-downstream adaptor colocalization relationships in the context of functionally relevant plasma membrane locations. The software for conditional colocalization analysis is available at https://github.com/kjaqaman/conditionalColoc.

Systematic Assessment of the Accuracy of Subunit Counting in Biomolecular Complexes Using Automated Single-Molecule Brightness Analysis

Analysis of single-molecule brightness allows subunit counting of high-order oligomeric biomolecular complexes. Although the theory behind the method has been extensively assessed, systematic analysis of the experimental conditions required to accurately quantify the stoichiometry of biological complexes remains challenging. In this work, we develop a high-throughput, automated computational pipeline for single-molecule brightness analysis that requires minimal human input. We use this strategy to systematically quantify the accuracy of counting under a wide range of experimental conditions in simulated ground-truth data and then validate its use on experimentally obtained data. Our approach defines a set of conditions under which subunit counting by brightness analysis is designed to work optimally and helps in establishing the experimental limits in quantifying the number of subunits in a complex of interest. Finally, we combine these features into a powerful, yet simple, software that can be easily used for the analysis of the stoichiometry of such complexes.

Calibration-free counting of low molecular copy numbers in single DNA-PAINT localization clusters

Single-molecule localization microscopy (SMLM) has revolutionized light microscopy by enabling optical resolution down to a few nanometer. Yet, localization precision commonly does not suffice to visually resolve single subunits in molecular assemblies or multimeric complexes. Because each targeted molecule contributes localizations during image acquisition, molecular counting approaches to reveal the target copy numbers within localization clusters have been persistently proposed since the early days of SMLM, most of which rely on preliminary knowledge of the dye photophysics or on a calibration to a reference. Previously, we developed localization-based fluorescence correlation spectroscopy (lbFCS) as an absolute ensemble counting approach for the SMLM-variant DNA-PAINT (points accumulation for imaging in nanoscale topography), for the first time, to our knowledge, circumventing the necessity for reference calibrations. Here, we present an extended concept termed lbFCS+, which allows absolute counting of copy numbers for individual localization clusters in a single DNA-PAINT image. In lbFCS+, absolute counting of fluorescent loci contained in individual nanoscopic volumes is achieved via precise measurement of the local hybridization rates of the fluorescently labeled oligonucleotides ("imagers") employed in DNA-PAINT imaging. In proof-of-principle experiments on DNA origami nanostructures, we demonstrate the ability of lbFCS+ to truthfully determine molecular copy numbers and imager association and dissociation rates in well-separated localization clusters containing up to 10 docking strands. For N ≤ 4 target molecules, lbFCS+ is even able to resolve integers, providing the potential to study the composition of up to tetrameric molecular complexes. Furthermore, we show that lbFCS+ allows resolving heterogeneous binding dynamics, enabling the distinction of stochastically generated and a priori indistinguishable DNA assemblies. Beyond advancing quantitative DNA-PAINT imaging, we believe that lbFCS+ could find promising applications ranging from biosensing to DNA computing.

Efficient Cross-Correlation Filtering of One- and Two-Color Single Molecule Localization Microscopy Data

Single molecule localization microscopy has become a prominent technique to quantitatively study biological processes below the optical diffraction limit. By fitting the intensity profile of single sparsely activated fluorophores, which are often attached to a specific biomolecule within a cell, the locations of all imaged fluorophores are obtained with ∼20 nm resolution in the form of a coordinate table. While rendered super-resolution images reveal structural features of intracellular structures below the optical diffraction limit, the ability to further analyze the molecular coordinates presents opportunities to gain additional quantitative insights into the spatial distribution of a biomolecule of interest. For instance, pair-correlation or radial distribution functions are employed as a measure of clustering, and cross-correlation analysis reveals the colocalization of two biomolecules in two-color SMLM data. Here, we present an efficient filtering method for SMLM data sets based on pair- or cross-correlation to isolate localizations that are clustered or appear in proximity to a second set of localizations in two-color SMLM data. In this way, clustered or colocalized localizations can be separately rendered and analyzed to compare other molecular properties to the remaining localizations, such as their oligomeric state or mobility in live cell experiments. Current matrix-based cross-correlation analyses of large data sets quickly reach the limitations of computer memory due to the space complexity of constructing the distance matrices. Our approach leverages k-dimensional trees to efficiently perform range searches, which dramatically reduces memory needs and the time for the analysis. We demonstrate the versatile applications of this method with simulated data sets as well as examples of two-color SMLM data. The provided MATLAB code and its description can be integrated into existing localization analysis packages and provides a useful resource to analyze SMLM data with new detail.

Super-resolving Microscopy in Neuroscience

Fluorescence imaging techniques play a pivotal role in our understanding of the nervous system. The emergence of various super-resolution microscopy methods and specialized fluorescent probes enables direct insight into neuronal structure and protein arrangements in cellular subcompartments with so far unmatched resolution. Super-resolving visualization techniques in neurons unveil a novel understanding of cytoskeletal composition, distribution, motility, and signaling of membrane proteins, subsynaptic structure and function, and neuron-glia interaction. Well-defined molecular targets in autoimmune and neurodegenerative disease models provide excellent starting points for in-depth investigation of disease pathophysiology using novel and innovative imaging methodology. Application of super-resolution microscopy in human brain samples and for testing clinical biomarkers is still in its infancy but opens new opportunities for translational research in neurology and neuroscience. In this review, we describe how super-resolving microscopy has improved our understanding of neuronal and brain function and dysfunction in the last two decades.

Estimating the dynamic range of quantitative single-molecule localization microscopy

In recent years, there have been significant advances in quantifying molecule copy number and protein stoichiometry with single-molecule localization microscopy (SMLM). However, as the density of fluorophores per diffraction-limited spot increases, distinguishing between detection events from different fluorophores becomes progressively more difficult, affecting the accuracy of such measurements. Although essential to the design of quantitative experiments, the dynamic range of SMLM counting techniques has not yet been studied in detail. Here, we provide a working definition of the dynamic range for quantitative SMLM in terms of the relative number of missed localizations or blinks and explore the photophysical and experimental parameters that affect it. We begin with a simple two-state model of blinking fluorophores, then extend the model to incorporate photobleaching and temporal binning by the detection camera. From these models, we first show that our estimates of the dynamic range agree with realistic simulations of the photoswitching. We find that the dynamic range scales inversely with the duty cycle when counting both blinks and localizations. Finally, we validate our theoretical approach on direct stochastic optical reconstruction microscopy (dSTORM) data sets of photoswitching Alexa Fluor 647 dyes. Our results should help guide researchers in designing and implementing SMLM-based molecular counting experiments.

KAHRP dynamically relocalizes to remodeled actin junctions and associates with knob spirals in Plasmodium falciparum-infected erythrocytes

The knob-associated histidine-rich protein (KAHRP) plays a pivotal role in the pathophysiology of Plasmodium falciparum malaria by forming membrane protrusions in infected erythrocytes, which anchor parasite-encoded adhesins to the membrane skeleton. The resulting sequestration of parasitized erythrocytes in the microvasculature leads to severe disease. Despite KAHRP being an important virulence factor, its physical location within the membrane skeleton is still debated, as is its function in knob formation. Here, we show by super-resolution microscopy that KAHRP initially associates with various skeletal components, including ankyrin bridges, but eventually colocalizes with remnant actin junctions. We further present a 35 Å map of the spiral scaffold underlying knobs and show that a KAHRP-targeting nanoprobe binds close to the spiral scaffold. Single-molecule localization microscopy detected ~60 KAHRP molecules/knob. We propose a dynamic model of KAHRP organization and a function of KAHRP in attaching other factors to the spiral scaffold.

A pairwise distance distribution correction (DDC) algorithm to eliminate blinking-caused artifacts in SMLM

Single-molecule localization microscopy (SMLM) relies on the blinking behavior of a fluorophore, which is the stochastic switching between fluorescent and dark states. Blinking creates multiple localizations belonging to the same fluorophore, confounding quantitative analyses and interpretations. Here we present a method, termed distance distribution correction (DDC), to eliminate blinking-caused repeat localizations without any additional calibrations. The approach relies on obtaining the true pairwise distance distribution of different fluorophores naturally from the imaging sequence by using distances between localizations separated by a time much longer than the average fluorescence survival time. We show that, using the true pairwise distribution, we can define and maximize the likelihood, obtaining a set of localizations void of blinking artifacts. DDC results in drastic improvements in obtaining the closest estimate of the true spatial organization and number of fluorescent emitters in a wide range of applications, enabling accurate reconstruction and quantification of SMLM images.

A pairwise distance distribution correction (DDC) algorithm to eliminate blinking-caused artifacts in SMLM

Single-molecule localization microscopy (SMLM) relies on the blinking behavior of a fluorophore, which is the stochastic switching between fluorescent and dark states. Blinking creates multiple localizations belonging to the same fluorophore, confounding quantitative analyses and interpretations. Here we present a method, termed distance distribution correction (DDC), to eliminate blinking-caused repeat localizations without any additional calibrations. The approach relies on obtaining the true pairwise distance distribution of different fluorophores naturally from the imaging sequence by using distances between localizations separated by a time much longer than the average fluorescence survival time. We show that, using the true pairwise distribution, we can define and maximize the likelihood, obtaining a set of localizations void of blinking artifacts. DDC results in drastic improvements in obtaining the closest estimate of the true spatial organization and number of fluorescent emitters in a wide range of applications, enabling accurate reconstruction and quantification of SMLM images.

Fluorescent proteins of the EosFP clade: intriguing marker tools with multiple photoactivation modes for advanced microscopy

Optical fluorescence microscopy has taken center stage in the exploration of biological structure and dynamics, especially on live specimens, and super-resolution imaging methods continue to deliver exciting new insights into the molecular foundations of life. Progress in the field, however, crucially hinges on advances in fluorescent marker technology. Among these, fluorescent proteins (FPs) of the GFP family are advantageous because they are genetically encodable, so that live cells, tissues or organisms can produce these markers all by themselves. A subclass of them, photoactivatable FPs, allow for control of their fluorescence emission by light irradiation, enabling pulse-chase imaging and super-resolution microscopy. In this review, we discuss FP variants of the EosFP clade that have been optimized by amino acid sequence modification to serve as markers for various imaging techniques. In general, two different modes of photoactivation are found, reversible photoswitching between a fluorescent and a nonfluorescent state and irreversible green-to red photoconversion. First, we describe their basic structural and optical properties. We then summarize recent research aimed at elucidating the photochemical processes underlying photoactivation. Finally, we briefly introduce various advanced imaging methods facilitated by specific EosFP variants, and show some exciting sample applications.

Automated Analysis of Fluorescence Kinetics in Single-Molecule Localization Microscopy Data Reveals Protein Stoichiometry

Understanding the function of protein complexes requires information on their molecular organization, specifically, their oligomerization level. Optical super-resolution microscopy can localize single protein complexes in cells with high precision, however, the quantification of their oligomerization level, remains a challenge. Here, we present a Quantitative Algorithm for Fluorescent Kinetics Analysis (QAFKA), that serves as a fully automated workflow for quantitative analysis of single-molecule localization microscopy (SMLM) data by extracting fluorophore "blinking" events. QAFKA includes an automated localization algorithm, the extraction of emission features per localization cluster, and a deep neural network-based estimator that reports the ratios of cluster types within the population. We demonstrate molecular quantification of protein monomers and dimers on simulated and experimental SMLM data. We further demonstrate that QAFKA accurately reports quantitative information on the monomer/dimer equilibrium of membrane receptors in single immobilized cells, opening the door to single-cell single-protein analysis.

Quantitative Assessment of Labeling Probes for Super-Resolution Microscopy Using Designer DNA Nanostructures

Improving labeling probes for state-of-the-art super-resolution microscopy is becoming of major importance. However, there is currently a lack of tools to quantitatively evaluate probe performance regarding efficiency, precision, and achievable resolution in an unbiased yet modular fashion. Herein, we introduce designer DNA origami structures combined with DNA-PAINT to overcome this issue and evaluate labeling efficiency, precision, and quantification using antibodies and nanobodies as exemplary labeling probes. Whereas current assessment of binders is mostly qualitative, e. g. based on an expected staining pattern, we herein present a quantitative analysis platform of the antigen labeling efficiency and achievable resolution, allowing researchers to choose the best performing binder. The platform can furthermore be readily adapted for discovery and precise quantification of a large variety of additional labeling probes.

Sample Preparation and Imaging Conditions Affect mEos3.2 Photophysics in Fission Yeast Cells

Photoconvertible fluorescent proteins (PCFPs) are widely used in super-resolution microscopy and studies of cellular dynamics. However, our understanding of their photophysics is still limited, hampering their quantitative application. For example, we do not know the optimal sample preparation methods or imaging conditions to count protein molecules fused to PCFPs by single-molecule localization microscopy in live and fixed cells. We also do not know how the behavior of PCFPs in live cells compares with fixed cells. Therefore, we investigated how formaldehyde fixation influences the photophysical properties of the popular green-to-red PCFP mEos3.2 in fission yeast cells under a wide range of imaging conditions. We estimated photophysical parameters by fitting a three-state model of photoconversion and photobleaching to the time course of fluorescence signal per yeast cell expressing mEos3.2. We discovered that formaldehyde fixation makes the fluorescence signal, photoconversion rate, and photobleaching rate of mEos3.2 sensitive to the buffer conditions likely by permeabilizing the yeast cell membrane. Under some imaging conditions, the time-integrated mEos3.2 signal per yeast cell is similar in live cells and fixed cells imaged in buffer at pH 8.5 with 1 mM DTT, indicating that light chemical fixation does not destroy mEos3.2 molecules. We also discovered that 405-nm irradiation drove some red-state mEos3.2 molecules to enter an intermediate dark state, which can be converted back to the red fluorescent state by 561-nm illumination. Our findings provide a guide to quantitatively compare conditions for imaging mEos3.2-tagged molecules in yeast cells. Our imaging assay and mathematical model are easy to implement and provide a simple quantitative approach to measure the time-integrated signal and the photoconversion and photobleaching rates of fluorescent proteins in cells.

CRISPR/Cas12a-mediated labeling of MET receptor enables quantitative single-molecule imaging of endogenous protein organization and dynamics

Single-molecule localization microscopy (SMLM) reports on protein organization in cells with near-molecular resolution and in combination with stoichiometric labeling enables protein counting. Fluorescent proteins allow stoichiometric labeling of cellular proteins; however, most methods either lead to overexpression or are complex and time demanding. We introduce CRISPR/Cas12a for simple and efficient tagging of endogenous proteins with a photoactivatable protein for quantitative SMLM and single-particle tracking. We constructed a HEK293T cell line with the receptor tyrosine kinase MET tagged with mEos4b and demonstrate full functionality. We determine the oligomeric state of MET with quantitative SMLM and find a reorganization from monomeric to dimeric MET upon ligand stimulation. In addition, we measured the mobility of single MET receptors in vivo in resting and ligand-treated cells. The combination of CRISPR/Cas12a-assisted endogenous protein labeling and super-resolution microscopy represents a powerful tool for cell biological research with molecular resolution.

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CRISPR/Cas12a enables endogenous protein labeling for super-resolution microscopy

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HEK293T cells were generated with MET endogenously labeled with mEos4b

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Quantitative PALM microscopy reports efficient dimerization of MET receptor

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Single-particle tracking shows increased MET immobilization upon ligand treatment

Unscrambling fluorophore blinking for comprehensive cluster detection via photoactivated localization microscopy

Determining nanoscale protein distribution via Photoactivated Localization Microscopy (PALM) mandates precise knowledge of the applied fluorophore's blinking properties to counteract overcounting artifacts that distort the resulting biomolecular distributions. Here, we present a readily applicable methodology to determine, optimize and quantitatively account for the blinking behavior of any PALM-compatible fluorophore. Using a custom-designed platform, we reveal complex blinking of two photoswitchable fluorescence proteins (PS-CFP2 and mEOS3.2) and two photoactivatable organic fluorophores (PA Janelia Fluor 549 and Abberior CAGE 635) with blinking cycles on time scales of several seconds. Incorporating such detailed information in our simulation-based analysis package allows for robust evaluation of molecular clustering based on individually recorded single molecule localization maps.

Single-molecule analysis reveals agonist-specific dimer formation of µ-opioid receptors

G-protein-coupled receptors (GPCRs) are key signaling proteins that mostly function as monomers, but for several receptors constitutive dimer formation has been described and in some cases is essential for function. Using single-molecule microscopy combined with super-resolution techniques on intact cells, we describe here a dynamic monomer-dimer equilibrium of µ-opioid receptors (µORs), where dimer formation is driven by specific agonists. The agonist DAMGO, but not morphine, induces dimer formation in a process that correlates both temporally and in its agonist- and phosphorylation-dependence with β-arrestin2 binding to the receptors. This dimerization is independent from, but may precede, µOR internalization. These data suggest a new level of GPCR regulation that links dimer formation to specific agonists and their downstream signals.

Quantitative single-molecule imaging of TNFR1 reveals zafirlukast as antagonist of TNFR1 clustering and TNFα-induced NF-ĸB signaling

TNFR1 is a crucial regulator of NF-ĸB-mediated proinflammatory cell survival responses and programmed cell death (PCD). Deregulation of TNFα- and TNFR1-controlled NF-ĸB signaling underlies major diseases, like cancer, inflammation, and autoimmune diseases. Therefore, although being routinely used, antagonists of TNFα might also affect TNFR2-mediated processes, so that alternative approaches to directly antagonize TNFR1 are beneficial. Here, we apply quantitative single-molecule localization microscopy (SMLM) of TNFR1 in physiologic cellular settings to validate and characterize TNFR1 inhibitory substances, exemplified by the recently described TNFR1 antagonist zafirlukast. Treatment of TNFR1-mEos2 reconstituted TNFR1/2 knockout mouse embryonic fibroblasts (MEFs) with zafirlukast inhibited both ligand-independent preligand assembly domain (PLAD)-mediated TNFR1 dimerization as well as TNFα-induced TNFR1 oligomerization. In addition, zafirlukast-mediated inhibition of TNFR1 clustering was accompanied by deregulation of acute and prolonged NF-ĸB signaling in reconstituted TNFR1-mEos2 MEFs and human cervical carcinoma cells. These findings reveal the necessity of PLAD-mediated, ligand-independent TNFR1 dimerization for NF-ĸB activation, highlight the PLAD as central regulator of TNFα-induced TNFR1 oligomerization, and demonstrate that TNFR1-mEos2 MEFs can be used to investigate TNFR1-antagonizing compounds employing single-molecule quantification and functional NF-ĸB assays at physiologic conditions.

Verifying molecular clusters by 2-color localization microscopy and significance testing

While single-molecule localization microscopy (SMLM) offers the invaluable prospect to visualize cellular structures below the diffraction limit of light microscopy, its potential has not yet been fully capitalized due to its inherent susceptibility to blinking artifacts. Particularly, overcounting of single molecule localizations has impeded a reliable and sensitive detection of biomolecular nanoclusters. Here we introduce a 2-Color Localization microscopy And Significance Testing Approach (2-CLASTA), providing a parameter-free statistical framework for the qualitative analysis of two-dimensional SMLM data via significance testing methods. 2-CLASTA yields p-values for the null hypothesis of random biomolecular distributions, independent of the blinking behavior of the chosen fluorescent labels. The method is parameter-free and does not require any additional measurements nor grouping of localizations. We validated the method both by computer simulations as well as experimentally, using protein concatemers as a mimicry of biomolecular clustering. As the new approach is not affected by overcounting artifacts, it is able to detect biomolecular clustering of various shapes at high sensitivity down to a level of dimers.

Single-molecule imaging reveals the oligomeric state of functional TNFα-induced plasma membrane TNFR1 clusters in cells

Ligand-induced tumor necrosis factor receptor 1 (TNFR1) activation controls nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB) signaling, cell proliferation, programmed cell death, and survival and is crucially involved in inflammation, autoimmune disorders, and cancer progression. Despite the relevance of TNFR1 clustering for signaling, oligomerization of ligand-free and ligand-activated TNFR1 remains controversial. At present, models range from ligand-independent receptor predimerization to ligand-induced oligomerization. Here, we used quantitative, single-molecule superresolution microscopy to study TNFR1 assembly directly in native cellular settings and at physiological cell surface abundance. In the absence of its ligand TNFα, TNFR1 assembled into monomeric and dimeric receptor units. Upon binding of TNFα, TNFR1 clustered predominantly not only into trimers but also into higher-order oligomers. A functional mutation in the preligand assembly domain of TNFR1 resulted in only monomeric TNFR1, which exhibited impaired ligand binding. In contrast, a form of TNFR1 with a mutation in the ligand-binding CRD2 subdomain retained the monomer-to-dimer ratio of the unliganded wild-type TNFR1 but exhibited no ligand binding. These results underscore the importance of ligand-independent TNFR1 dimerization in NF-κB signaling.

Toward Absolute Molecular Numbers in DNA-PAINT

Single-molecule localization microscopy (SMLM) has revolutionized optical microscopy, extending resolution down to the level of individual molecules. However, the actual counting of molecules relies on preliminary knowledge of the blinking behavior of individual targets or on a calibration to a reference. In particular for biological applications, great care has to be taken because a plethora of factors influence the quality and applicability of calibration-dependent approaches to count targets in localization clusters particularly in SMLM data obtained from heterogeneous samples. Here, we present localization-based fluorescence correlation spectroscopy (lbFCS) as the first absolute molecular counting approach for DNA-points accumulation for imaging in nanoscale topography (PAINT) microscopy and, to our knowledge, for SMLM in general. We demonstrate that lbFCS overcomes the limitation of previous DNA-PAINT counting and allows the quantification of target molecules independent of the localization cluster density. In accordance with the promising results of our systematic proof-of-principle study on DNA origami structures as idealized targets, lbFCS could potentially also provide quantitative access to more challenging biological targets featuring heterogeneous cluster sizes in the future.

Optical super-resolution microscopy unravels the molecular composition of functional protein complexes

Optical super-resolution microscopy has revolutionized our understanding of cell biology. Next to visualizing cellular structures with near-molecular spatial resolution, an additional benefit is the molecular characterization of biomolecular complexes directly in an intact cell. Single-molecule localization microscopy, as one technology out of the toolbox of super-resolution methods, generates images by detecting the position of single fluorophore labels and is particularly suited for molecular quantification. We review imaging and analysis methods employing single-molecule localization microscopy and extract molecule numbers.

Molecular contribution function in RESOLFT nanoscopy

The ultimate objective of a microscope of the highest resolution is to map the molecules of interest in the sample. Traditionally, linear imaging systems are characterized by their spatial frequency transfer function, which is given, in real space, by the point spread function (PSF). By extending the concept of the PSF towards the molecular contribution function (MCF), that quantifies the average contribution of a single fluorophore to the image, a straightforward concept for counting fluorophores is obtained. Using reversible saturable optical fluorescence transitions (RESOLFT), fluorophores are effectively activated only in a small, subdiffraction-sized volume before they are read out. During readout the signal exhibits an increased variance due to the stochastic nature of prior activation, which scales quadratically with the brightness of the active fluorophores while the mean of the signal scales only linearly with it. Using a two-state Markov model for the activation, showing comparable behavior to the switching kinetics of the switchable fluorescent protein rsEGFP2, we can approximate quantitatively the MCF of RESOLFT nanoscopy allowing to count the number of fluorophores within a subdiffraction-sized region of the sample. The method is validated on measurements of tubulin structures in Drosophila melagonaster larvae. Modeling and estimation of the MCF is a promising approach to quantitative microscopy.

Super-resolution imaging and estimation of protein copy numbers at single synapses with DNA-point accumulation for imaging in nanoscale topography

In the brain, the strength of each individual synapse is defined by the complement of proteins present or the "local proteome." Activity-dependent changes in synaptic strength are the result of changes in this local proteome and posttranslational protein modifications. Although most synaptic proteins have been identified, we still know little about protein copy numbers in individual synapses and variations between synapses. We use DNA-point accumulation for imaging in nanoscale topography as a single-molecule super-resolution imaging technique to visualize and quantify protein copy numbers in single synapses. The imaging technique provides near-molecular spatial resolution, is unaffected by photobleaching, enables imaging of large field of views, and provides quantitative molecular information. We demonstrate these benefits by accessing copy numbers of surface AMPA-type receptors at single synapses of rat hippocampal neurons along dendritic segments.

Synthetic and genetic dimers as quantification ruler for single-molecule counting with PALM

How membrane proteins oligomerize determines their function. Superresolution microscopy can report on protein clustering and extract quantitative molecular information. Here, we evaluate the blinking kinetics of four photoactivatable fluorescent proteins for quantitative single-molecule microscopy. We identified mEos3.2 and mMaple3 to be suitable for molecular quantification through blinking histogram analysis. We designed synthetic and genetic dimers of mEos3.2 as well as fusion proteins of monomeric and dimeric membrane proteins as reference structures, and we demonstrate their versatile use for quantitative superresolution imaging in vitro and in situ. We further found that the blinking behavior of mEos3.2 and mMaple3 is modified by a reducing agent, offering the possibility to adjust blinking parameters according to experimental needs.

A stochastic view on surface inhomogeneity of nanoparticles

The interactions between and with nanostructures can only be fully understood when the functional group distribution on their surfaces can be quantified accurately. Here we apply a combination of direct stochastic optical reconstruction microscopy (dSTORM) imaging and probabilistic modelling to analyse molecular distributions on spherical nanoparticles. The properties of individual fluorophores are assessed and incorporated into a model for the dSTORM imaging process. Using this tailored model, overcounting artefacts are greatly reduced and the locations of dye labels can be accurately estimated, revealing their spatial distribution. We show that standard chemical protocols for dye attachment lead to inhomogeneous functionalization in the case of ubiquitous polystyrene nanoparticles. Moreover, we demonstrate that stochastic fluctuations result in large variability of the local group density between particles. These results cast doubt on the uniform surface coverage commonly assumed in the creation of amorphous functional nanoparticles and expose a striking difference between the average population and individual nanoparticle coverage.

Visualizing ubiquitination in mammalian cells

Covalent modification of proteins with ubiquitin is essential for the majority of biological processes in mammalian cells. Numerous proteins are conjugated with single or multiple ubiquitin molecules or chains in a dynamic fashion, often determining protein half-lives, localization or function. Experimental approaches to study ubiquitination have been dominated by genetic and biochemical analysis of enzyme structure-function relationships, reaction mechanisms and physiological relevance. Here, we provide an overview of recent developments in microscopy-based imaging of ubiquitination, available reagents and technologies. We discuss the progress in direct and indirect imaging of differentially linked ubiquitin chains in fixed and living cells using confocal fluorescence microscopy and super-resolution microscopy, illustrated by the role of ubiquitin in antibacterial autophagy and pro-inflammatory signalling. Finally, we speculate on future developments and forecast a transition from qualitative to quantitative super-resolution approaches to understand fundamental aspects of ubiquitination and the formation and distribution of functional E3 ligase protein complexes in their native environment.

What we talk about when we talk about nanoclusters

Superresolution microscopy results have sparked the idea that many membrane proteins are not randomly distributed across the plasma membrane but are instead arranged in nanoclusters. Frequently, these new results seemed to confirm older data based on biochemical and electron microscopy experiments. Recently, however, it was recognized that multiple countings of the very same fluorescently labeled protein molecule can be easily confused with true protein clusters. Various strategies have been developed, which are intended to solve the problem of discriminating true protein clusters from imaging artifacts. We believe that there is currently no perfect algorithm for this problem; instead, different approaches have different strengths and weaknesses. In this review, we discuss single molecule localization microscopy in view of its ability to detect nanoclusters of membrane proteins. To capture the different views on nanoclustering, we chose an unconventional style for this article: we placed its scientific content in the setting of a fictive conference, where five researchers from different fields discuss the problem of detecting and quantifying nanoclusters. Using this style, we feel that the different approaches common for different research areas can be well illustrated. Similarities to a short story by Raymond Carver are not unintentional.

A Platform To Enhance Quantitative Single Molecule Localization Microscopy

Quantitative single molecule localization microscopy (qSMLM) is a powerful approach to study in situ protein organization. However, uncertainty regarding the photophysical properties of fluorescent reporters can bias the interpretation of detected localizations and subsequent quantification. Furthermore, strategies to efficiently detect endogenous proteins are often constrained by label heterogeneity and reporter size. Here, a new surface assay for molecular isolation (SAMI) was developed for qSMLM and used to characterize photophysical properties of fluorescent proteins and dyes. SAMI-qSMLM afforded robust quantification. To efficiently detect endogenous proteins, we used fluorescent ligands that bind to a specific site on engineered antibody fragments. Both the density and nano-organization of membrane-bound epidermal growth factor receptors (EGFR, HER2, and HER3) were determined by a combination of SAMI, antibody engineering, and pair-correlation analysis. In breast cancer cell lines, we detected distinct differences in receptor density and nano-organization upon treatment with therapeutic agents. This new platform can improve molecular quantification and can be developed to study the local protein environment of intact cells.

Biological Insight from Super-Resolution Microscopy: What We Can Learn from Localization-Based Images

Super-resolution optical imaging based on the switching and localization of individual fluorescent molecules [photoactivated localization microscopy (PALM), stochastic optical reconstruction microscopy (STORM), etc.] has evolved remarkably over the last decade. Originally driven by pushing technological limits, it has become a tool of biological discovery. The initial demand for impressive pictures showing well-studied biological structures has been replaced by a need for quantitative, reliable data providing dependable evidence for specific unresolved biological hypotheses. In this review, we highlight applications that showcase this development, identify the features that led to their success, and discuss remaining challenges and difficulties. In this context, we consider the complex topic of defining resolution for this imaging modality and address some of the more common analytical methods used with this data.

Photoswitching of Green mEos2 by Intense 561 nm Light Perturbs Efficient Green-to-Red Photoconversion in Localization Microscopy

Green-to-red photoconvertible fluorescent proteins (PCFPs) such as mEos2 and its derivatives are widely used in PhotoActivated Localization Microscopy (PALM). However, the complex photophysics of these genetically encoded markers complicates the quantitative analysis of PALM data. Here, we show that intense 561 nm light (∼1 kW/cm²) typically used to localize single red molecules considerably affects the green-state photophysics of mEos2 by populating at least two reversible dark states. These dark states retard green-to-red photoconversion through a shelving effect, although one of them is rapidly depopulated by 405 nm light illumination. Multiple mEos2 switching and irreversible photobleaching is thus induced by yellow/green and violet photons before green-to-red photoconversion occurs, contributing to explain the apparent limited signaling efficiency of this PCFP. Our data reveals that the photophysics of PCFPs of anthozoan origin is substantially more complex than previously thought, and suggests that intense 561 nm laser light should be used with care, notably for quantitative or fast PALM approaches.

Fluorescence nanoscopy in cell biology

Fluorescence nanoscopy uniquely combines minimally invasive optical access to the internal nanoscale structure and dynamics of cells and tissues with molecular detection specificity. While the basic physical principles of 'super-resolution' imaging were discovered in the 1990s, with initial experimental demonstrations following in 2000, the broad application of super-resolution imaging to address cell-biological questions has only more recently emerged. Nanoscopy approaches have begun to facilitate discoveries in cell biology and to add new knowledge. One current direction for method improvement is the ambition to quantitatively account for each molecule under investigation and assess true molecular colocalization patterns via multi-colour analyses. In pursuing this goal, the labelling of individual molecules to enable their visualization has emerged as a central challenge. Extending nanoscale imaging into (sliced) tissue and whole-animal contexts is a further goal. In this Review we describe the successes to date and discuss current obstacles and possibilities for further development.

Molecular Counting with Localization Microscopy: A Bayesian Estimate Based on Fluorophore Statistics

Superresolved localization microscopy has the potential to serve as an accurate, single-cell technique for counting the abundance of intracellular molecules. However, the stochastic blinking of single fluorophores can introduce large uncertainties into the final count. Here we provide a theoretical foundation for applying superresolved localization microscopy to the problem of molecular counting based on the distribution of blinking events from a single fluorophore. We also show that by redundantly tagging single molecules with multiple, blinking fluorophores, the accuracy of the technique can be enhanced by harnessing the central limit theorem. The coefficient of variation then, for the number of molecules M estimated from a given number of blinks B, scales like ∼1/N_l, where N_l is the mean number of labels on a target. As an example, we apply our theory to the challenging problem of quantifying the cell-to-cell variability of plasmid copy number in bacteria.

A DNA origami platform for quantifying protein copy number in super-resolution

Single-molecule-based super-resolution microscopy offers a unique opportunity for quantifying protein copy-number with nanoscale resolution. However, while fluorescent proteins have been characterized for quantitative imaging using calibration standards, similar calibration tools for immunofluorescence with small organic fluorophores are lacking. Here, we show that DNA origami in combination with GFP antibodies is a versatile platform for calibrating fluorophore and antibody labeling efficiency to quantify protein copy-number in cellular contexts using super-resolution microscopy.