Counting single photoactivatable fluorescent molecules by photoactivated localization microscopy (PALM)

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.

Modulation of FGF pathway signaling and vascular differentiation using designed oligomeric assemblies

Many growth factors and cytokines signal by binding to the extracellular domains of their receptors and driving association and transphosphorylation of the receptor intracellular tyrosine kinase domains, initiating downstream signaling cascades. To enable systematic exploration of how receptor valency and geometry affect signaling outcomes, we designed cyclic homo-oligomers with up to 8 subunits using repeat protein building blocks that can be modularly extended. By incorporating a de novo-designed fibroblast growth factor receptor (FGFR)-binding module into these scaffolds, we generated a series of synthetic signaling ligands that exhibit potent valency- and geometry-dependent Ca2+ release and mitogen-activated protein kinase (MAPK) pathway activation. The high specificity of the designed agonists reveals distinct roles for two FGFR splice variants in driving arterial endothelium and perivascular cell fates during early vascular development. Our designed modular assemblies should be broadly useful for unraveling the complexities of signaling in key developmental transitions and for developing future therapeutic applications.

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.

Triggered cagedSTORM microscopy

In standard SMLM methods, the photoswitching of single fluorescent molecules and the data acquisition processes are independent, which leads to the detection of single molecule blinking events on several consecutive frames. This mismatch results in several data points with reduced localization precision, and it also increases the possibilities of overlapping. Here we discuss how the synchronization of the fluorophores' ON state to the camera exposure time increases the average intensity of the captured point spread functions and hence improves the localization precision. Simulations and theoretical results show that such synchronization leads to fewer localizations with 15% higher sum signal on average, while reducing the probability of overlaps by 10%.

Photoactivatable Xanthone (PaX) Dyes Enable Quantitative, Dual Color, and Live-Cell MINFLUX Nanoscopy

The single-molecule localization concept MINFLUX has triggered a reevaluation of the features of fluorophores for attaining nanometer-scale resolution. MINFLUX nanoscopy benefits from temporally controlled fluorescence ("on"/"off") photoswitching. Combined with an irreversible switching behavior, the localization process is expected to turn highly efficient and quantitative data analysis simple. The potential in the recently reported photoactivable xanthone (PaX) dyes is recognized to extend the list of molecular switches used for MINFLUX with 561 nm excitation beyond the fluorescent protein mMaple. The MINFLUX localization success rates of PaX560 , PaX+560, and mMaple are quantitatively compared by analyzing the effective labeling efficiency of endogenously tagged nuclear pore complexes. The PaX dyes prove to be superior to mMaple and on par with the best reversible molecular switches routinely used in single-molecule localization microscopy. Moreover, the rationally designed PaX595 is introduced for complementing PaX560 in dual color 561 nm MINFLUX imaging based on spectral classification and the deterministic, irreversible, and additive-independent nature of PaX photoactivation is showcased in fast live-cell MINFLUX imaging. The PaX dyes meet the demands of MINFLUX for a robust readout of each label position and fill the void of reliable fluorophores dedicated to 561 nm MINFLUX imaging.

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.

Single-molecule localization microscopy reveals STING clustering at the trans-Golgi network through palmitoylation-dependent accumulation of cholesterol

Stimulator of interferon genes (STING) is critical for the type I interferon response to pathogen- or self-derived DNA in the cytosol. STING may function as a scaffold to activate TANK-binding kinase 1 (TBK1), but direct cellular evidence remains lacking. Here we show, using single-molecule imaging of STING with enhanced time resolutions down to 5 ms, that STING becomes clustered at the trans-Golgi network (about 20 STING molecules per cluster). The clustering requires STING palmitoylation and the Golgi lipid order defined by cholesterol. Single-molecule imaging of TBK1 reveals that STING clustering enhances the association with TBK1. We thus provide quantitative proof-of-principle for the signaling STING scaffold, reveal the mechanistic role of STING palmitoylation in the STING activation, and resolve the long-standing question of the requirement of STING translocation for triggering the innate immune signaling.

Single-molecule tracking of PprI in D. radiodurans without interference of autoblinking

Autoblinking is a widespread phenomenon and exhibits high level of intensity in some bacteria. In Deinococcus radiodurans (D. radiodurans), strong autoblinking was found to be indistinguishable from PAmCherry and greatly prevented single-molecule tracking of proteins of interest. Here we employed the bright photoswitchable fluorescent protein mMaple3 to label PprI, one essential DNA repair factor, and characterized systematically the fluorescence intensity and bleaching kinetics of both autoblinking and PprI-mMaple3 molecules within cells grown under three different conditions. Under minimal media, we can largely separate autoblinking from mMaple3 molecules and perform reliably single-molecule tracking of PprI in D. radiodurans, by means of applying signal-to-noise ratio and constraining the minimal length for linking the trajectories. We observed three states of PprI molecules, which bear different subcellular localizations and distinct functionalities. Our strategy provides a useful means to study the dynamics and distributions of proteins of interest in bacterial cells with high level of autoblinking.

Absolute quantification of protein number and dynamics in single cells

Quantitative characterization of protein abundance and interactions in live cells is necessary to understand and predict cellular behavior. The accurate determination of copy number for individual proteins and heterologous complexes in individual cells is critical because small changes in protein dosage, often less than two-fold, can have strong phenotypic consequences. Here, we review the merits and pitfalls of different quantitative fluorescence imaging methods for single-cell determination of protein abundance, localization, interactions, and dynamics. In particular, we discuss how scanning number and brightness (sN&B) and its variation, Raster scanning image correlation spectroscopy (RICS), exploit stochastic noise in small measurement volumes to quantify protein abundance, stoichiometry, and dynamics with high accuracy.

ULK1 forms distinct oligomeric states and nanoscopic structures during autophagy initiation

Autophagy induction involves extensive molecular and membrane reorganization. Despite substantial progress, the mechanism underlying autophagy initiation remains poorly understood. Here, we used quantitative photoactivated localization microscopy with single-molecule sensitivity to analyze the nanoscopic distribution of endogenous ULK1, the kinase that triggers autophagy. Under amino acid starvation, ULK1 formed large clusters containing up to 161 molecules at the endoplasmic reticulum. Cross-correlation analysis revealed that ULK1 clusters engaging in autophagosome formation require 30 or more molecules. The ULK1 structures with more than the threshold number contained varying levels of Atg13, Atg14, Atg16, LC3B, GEC1, and WIPI2. We found that ULK1 activity is dispensable for the initial clustering of ULK1, but necessary for the subsequent expansion of the clusters, which involves interaction with Atg14, Atg16, and LC3B and relies on Vps34 activity. This quantitative analysis at the single-molecule level has provided unprecedented insights into the behavior of ULK1 during autophagy initiation.

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.

Dual-color Colocalization in Single-molecule Localization Microscopy to Determine the Oligomeric State of Proteins in the Plasma Membrane

Determining the oligomeric state of membrane proteins is critical for understanding their function. However, traditional ex situ methods like clear native gel electrophoresis can disrupt protein subunit interactions during sample preparation. In situ methods such as stepwise photobleaching have limitations due to high expression levels and limitations of optical resolution in microscopy. Super-resolution microscopy techniques such as single-molecule localization microscopy (SMLM) have the potential to overcome these limitations, but the stochastic nature of signals can lead to miscounting due to over-expression, background noise, and temporal separation of signals. Additionally, this technique has limited application due to the limited selection of fluorescent labels and the demanding control of laser power. To address these issues, we developed a dual color colocalization (DCC) strategy that offers higher tolerance to background noise and simplifies data acquisition and processing for high-throughput and reliable counting. The DCC strategy was used to determine the oligomeric states of membrane proteins of the SLC17 and SLC26 family with SMLM, providing a robust and efficient method for studying protein interactions.

Single Extracellular VEsicle Nanoscopy

Extracellular vesicles (EVs) and their cargo constitute novel biomarkers. EV subpopulations have been defined not only by abundant tetraspanins (e.g., CD9, CD63 and CD81) but also by specific markers derived from their source cells. However, it remains a challenge to robustly isolate and characterize EV subpopulations. Here, we combined affinity isolation with super-resolution imaging to comprehensively assess EV subpopulations from human plasma. Our Single Extracellular VEsicle Nanoscopy (SEVEN) assay successfully quantified the number of affinity-isolated EVs, their size, shape, molecular tetraspanin content, and heterogeneity. The number of detected tetraspanin-enriched EVs positively correlated with sample dilution in a 64-fold range (for SEC-enriched plasma) and a 50-fold range (for crude plasma). Importantly, SEVEN robustly detected EVs from as little as ∼0.1 μL of crude plasma. We further characterized the size, shape and molecular tetraspanin content (with corresponding heterogeneities) for CD9-, CD63- and CD81-enriched EV subpopulations. Finally, we assessed EVs from the plasma of four pancreatic ductal adenocarcinoma patients with resectable disease. Compared to healthy plasma, CD9-enriched EVs from patients were smaller while IGF1R-enriched EVs from patients were larger, rounder and contained more tetraspanin molecules, suggestive of a unique pancreatic cancer-enriched EV subpopulation. This study provides the method validation and demonstrates that SEVEN could be advanced into a platform for characterizing both disease-associated and organ-associated EV subpopulations.

Bioengineered Bacteriophage-Like Nanoparticles as RNAi Therapeutics to Enhance Radiotherapy against Glioblastomas

Since glioblastomas (GBMs) are radioresistant malignancies and most GBM recurrences occur in radiotherapy, increasing the effectiveness of radiotherapy by gene-silencing has recently attracted attention. However, the difficulty in precisely tuning the composition and RNA loading in nanoparticles leads to batch-to-batch variations of the RNA therapeutics, thus significantly restricting their clinical translation. Here, we bioengineer bacteriophage Qβ particles with a designed broccoli light-up three-way junction (b-3WJ) RNA scaffold (contains two siRNA/miRNA sequences and one light-up aptamer) packaging for the silencing of genes in radioresistant GBM cells. The in vitro results demonstrate that the cleavage of de novo designed b-3WJ RNA by Dicer enzyme can be easily monitored in real-time using fluorescence microscopy, and the TrQβ@b-3WJ_Let-7g^siEGFR successfully knocks down EGFR and IKKα simultaneously and thereby inactivates NF-κB signaling to inhibit DNA repair. Delivery of TrQβ@b-3WJ_Let-7g^siEGFR through convection-enhanced delivery (CED) infusion followed by 2Gy X-ray irradiation demonstrated that the median survival was prolonged to over 60 days compared with the 2Gy X-ray irradiated group (median survival: 31 days). Altogether, the results of this study could be critical for the design of RNAi-based genetic therapeutics, and CED infusion serves as a powerful delivery system for promoting radiotherapy against GBMs without evidence of systemic toxicity.

Peptide-PAINT Using a Transfected-Docker Enables Live- and Fixed-Cell Super-Resolution Imaging

Point accumulation for imaging in nanoscale topography (PAINT) is a single-molecule technique for super-resolution microscopy, which uses exchangeable single stranded DNA oligos or peptide-pairs to create blinking phenomenon and achieves ≈5-25 nanometer resolution. Here, it is shown that by transfecting the protein-of-interest with a docker-coil, rather than by adding the docker externally-as is the norm when using DNA tethers or antibodies as dockers-similar localization can be achieved, ≈10 nm. However, using a transfected docker has several experimental advances and simplifications. Most importantly, it allows Peptide-PAINT to be applied to transfected live cells for imaging surface proteins in mammalian cells and neurons under physiological conditions. The enhanced resolution of Peptide-PAINT is also shown for organelles in fixed cells to unravel structural details including ≈40-nm and ≈60-nm axial repeats in vimentin filaments in the cytoplasm, and fiber shapes of sub-100-nm histone-rich regions in the nucleus.

Modulation of FGF pathway signaling and vascular differentiation using designed oligomeric assemblies

Growth factors and cytokines signal by binding to the extracellular domains of their receptors and drive association and transphosphorylation of the receptor intracellular tyrosine kinase domains, initiating downstream signaling cascades. To enable systematic exploration of how receptor valency and geometry affects signaling outcomes, we designed cyclic homo-oligomers with up to 8 subunits using repeat protein building blocks that can be modularly extended. By incorporating a de novo designed fibroblast growth-factor receptor (FGFR) binding module into these scaffolds, we generated a series of synthetic signaling ligands that exhibit potent valency- and geometry-dependent Ca2+ release and MAPK pathway activation. The high specificity of the designed agonists reveal distinct roles for two FGFR splice variants in driving endothelial and mesenchymal cell fates during early vascular development. The ability to incorporate receptor binding domains and repeat extensions in a modular fashion makes our designed scaffolds broadly useful for probing and manipulating cellular signaling pathways.

Live-cell photo-activated localization microscopy correlates nanoscale ryanodine receptor configuration to calcium sparks in cardiomyocytes

Ca2+ sparks constitute the fundamental units of Ca2+ release in cardiomyocytes. Here we investigate how ryanodine receptors (RyRs) collectively generate these events by employing a transgenic mouse with a photo-activated label on RyR2. This allowed correlative imaging of RyR localization, by super-resolution Photo-Activated Localization Microscopy, and Ca2+ sparks, by high-speed imaging. Two populations of Ca2+ sparks were observed: stationary events and "travelling" events that spread between neighbouring RyR clusters. Travelling sparks exhibited up to 8 distinct releases, sourced from local or distal junctional sarcoplasmic reticulum. Quantitative analyses showed that sparks may be triggered by any number of RyRs within a cluster, and that acute β-adrenergic stimulation augments intra-cluster RyR recruitment to generate larger events. In contrast, RyR "dispersion" during heart failure facilitates the generation of travelling sparks. Thus, RyRs cooperatively generate Ca2+ sparks in a complex, malleable fashion, and channel organization regulates the propensity for local propagation of Ca2+ release.

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.

Single molecule imaging simulations with advanced fluorophore photophysics

Advanced fluorescence imaging techniques such as single-molecule localization microscopy (SMLM) fundamentally rely on the photophysical behavior of the employed fluorophores. This behavior is generally complex and impacts data quality in a subtle manner. A simulation software named Single-Molecule Imaging Simulator (SMIS) is introduced that simulates a widefield microscope and incorporates fluorophores with their spectral and photophysical properties. With SMIS, data collection schemes combining 3D, multicolor, single-particle-tracking or quantitative SMLM can be implemented. The influence of advanced fluorophore characteristics, imaging conditions, and environmental parameters can be evaluated, facilitating the design of real experiments and their proper interpretation.

Resolution limit in opto-digital systems revisited

The resolution limit achievable with an optical system is a fundamental piece of information when characterizing its performance, mainly in case of microscopy imaging. Usually this information is given in the form of a distance, often expressed in microns, or in the form of a cutoff spatial frequency, often expressed in line pairs per mm. In modern imaging systems, where the final image is collected by pixelated digital cameras, the resolution limit is determined by the performance of both, the optical systems and the digital sensor. Usually, one of these factors is considered to be prevalent over the other for estimating the spatial resolution, leading to the global performance of the imaging system ruled by either the classical Abbe resolution limit, based on physical diffraction, or by the Nyquist resolution limit, based on the digital sensor features. This estimation fails significantly to predict the global performance of opto-digital imaging systems, like 3D microscopes, where none of the factors is negligible. In that case, which indeed is the most common, neither the Abbe formula nor the Nyquist formula provide by themselves a reliable prediction for the resolution limit. This is a serious drawback since systems designers often use those formulae as design input parameters. Aiming to overcome this lack, a simple mathematical expression obtained by finely articulating the Abbe and Nyquist formulas, to easily predict the spatial resolution limit of opto-digital imaging systems, is proposed here. The derived expression is tested experimentally, and shows to be valid in a broad range of opto-digital combinations.

Characterizing Properties of Biomolecular Condensates Below the Diffraction Limit In Vivo

Fluorescence microscopy assays enable the investigation of endogenous biomolecular condensates directly in their cellular context. With appropriate experimental designs, these assays yield quantitative information on condensate material properties and inform on biophysical mechanisms of condensate formation. Single-molecule super-resolution and tracking experiments grant access to the smallest condensates and early condensation stages not resolved by conventional imaging approaches. Here, we discuss considerations for using single-molecule assays to extract quantitative information about biomolecular condensates directly in their cellular context.

Multifrequency-based sharpening of focal volume

Systems that emit electromagnetic or sonic waves for diagnostic or interventional applications often have constraints on the size of their aperture, and thus produce an elongated focus in the axial dimension. This extended depth of focus limits imaging resolution and spatial specificity of the delivered energy. Here, we have developed a method that substantially minimizes the depth of focus. The method superimposes beams of distinct frequencies in space and time to create constructive interference at target and amplify deconstructive interference everywhere else, thus sharpening the focus. The method does not require labeling of targets or other manipulations of the medium. Using simulations, we found that the method tightens the depth of focus even for systems with a narrow bandwidth. Moreover, we implemented the method in ultrasonic hardware and found that a 46.1% frequency fractional bandwidth provides an average 7.4-fold reduction in the focal volume of the resulting beams. This method can be readily applied to sharpen the focus of interventional systems and is expected to also improve the axial resolution of existing imaging systems.

A novel and robust method for counting components within bio-molecular complexes using fluorescence microscopy and statistical modelling

Cellular biology occurs through myriad interactions between diverse molecular components, many of which assemble in to specific complexes. Various techniques can provide a qualitative survey of which components are found in a given complex. However, quantitative analysis of the absolute number of molecules within a complex (known as stoichiometry) remains challenging. Here we provide a novel method that combines fluorescence microscopy and statistical modelling to derive accurate molecular counts. We have devised a system in which batches of a given biomolecule are differentially labelled with spectrally distinct fluorescent dyes (label A or B), and mixed such that B-labelled molecules are vastly outnumbered by those with label A. Complexes, containing this component, are then simply scored as either being positive or negative for label B. The frequency of positive complexes is directly related to the stoichiometry of interaction and molecular counts can be inferred by statistical modelling. We demonstrate this method using complexes of Adenovirus particles and monoclonal antibodies, achieving counts that are in excellent agreement with previous estimates. Beyond virology, this approach is readily transferable to other experimental systems and, therefore, provides a powerful tool for quantitative molecular biology.

Use of compressed sensing to expedite high-throughput diagnostic testing for COVID-19 and beyond

The rapid spread of SARS-CoV-2 has placed a significant burden on public health systems to provide swift and accurate diagnostic testing highlighting the critical need for innovative testing approaches for future pandemics. In this study, we present a novel sample pooling procedure based on compressed sensing theory to accurately identify virally infected patients at high prevalence rates utilizing an innovative viral RNA extraction process to minimize sample dilution. At prevalence rates ranging from 0-14.3%, the number of tests required to identify the infection status of all patients was reduced by 69.26% as compared to conventional testing in primary human SARS-CoV-2 nasopharyngeal swabs and a coronavirus model system. Our method provided quantification of individual sample viral load within a pool as well as a binary positive-negative result. Additionally, our modified pooling and RNA extraction process minimized sample dilution which remained constant as pool sizes increased. Compressed sensing can be adapted to a wide variety of diagnostic testing applications to increase throughput for routine laboratory testing as well as a means to increase testing capacity to combat future pandemics.

Single-molecule counting applied to the study of GPCR oligomerization

Single-molecule counting techniques enable a precise determination of the intracellular abundance and stoichiometry of proteins and macromolecular complexes. These details are often challenging to quantitatively assess yet are essential for our understanding of cellular function. Consider G-protein-coupled receptors-an expansive class of transmembrane signaling proteins that participate in many vital physiological functions making them a popular target for drug development. While early evidence for the role of oligomerization in receptor signaling came from ensemble biochemical and biophysical assays, innovations in single-molecule measurements are now driving a paradigm shift in our understanding of its relevance. Here, we review recent developments in single-molecule counting with a focus on photobleaching step counting and the emerging technique of quantitative single-molecule localization microscopy-with a particular emphasis on the potential for these techniques to advance our understanding of the role of oligomerization in G-protein-coupled receptor signaling.

Detection of fortunate molecules induce particle resolution shift (PAR-shift) toward single-molecule limit in SMLM: A technique for resolving molecular clusters in cellular system

Molecules capable of emitting a large number of photons (also known as fortunate molecules) are crucial for achieving a resolution close to single molecule limit (the actual size of a single molecule). We propose a long-exposure single molecule localization microscopy (leSMLM) technique that enables detection of fortunate molecules, which is based on the fact that detecting a relatively small subset of molecules with large photon emission increases its localization precision (∼r₀/N). Fortunate molecules have the ability to emit a large burst of photons over a prolonged time (> average blinking lifetime). So, a long exposure time allows the time window necessary to detect these elite molecules. The technique involves the detection of fortunate molecules to generate enough statistics for a quality reconstruction of the target protein distribution in a cellular system. Studies show a significant PArticle Resolution Shift (PAR-shift) of about 6 and 11 nm toward single-molecule-limit (far from diffraction-limit) for an exposure time window of 60 and 90 ms, respectively. In addition, a significant decrease in the fraction of fortunate molecules (single molecules with small localization precision) is observed. Specifically, 8.33% and 3.43% molecules are found to emit in 30-60  ms and >60 ms, respectively, when compared to single molecule localization microscopy (SMLM). The long exposure has enabled better visualization of the Dendra2HA molecular cluster, resolving sub-clusters within a large cluster. Thus, the proposed technique leSMLM facilitates a better study of cluster formation in fixed samples. Overall, leSMLM technique offers a spatial resolution improvement of ~ 10 nm compared to traditional SMLM at the cost of marginally poor temporal resolution.

Quantitative comparison of spinning disk geometries for PAINT based super-resolution microscopy

PAINT methods that use DNA- or protein- based exchangeable probes have become popular for super-resolution imaging and have been combined with spinning disk confocal microscopy for imaging thicker samples. However, the widely available spinning disks used for routine biological imaging are not optimized for PAINT-based applications and may compromise resolution and imaging speed. Here, we use Drosophila egg chambers in the presence of the actin-binding peptide Lifeact to study the performance of four different spinning disk geometries. We find that disk geometries with higher light collection efficiency perform better for PAINT-based super-resolution imaging due to increased photon numbers and, subsequently, detection of more blinking events.

Genetically encodable fluorescent protein markers in advanced optical imaging

Optical fluorescence microscopy plays a pivotal role in the exploration of biological structure and dynamics, especially on live specimens. Progress in the field relies, on the one hand, on technical advances in imaging and data processing and, on the other hand, on progress in fluorescent marker technologies. Among these, genetically encodable fluorescent proteins (FPs) are invaluable tools, as they allow facile labeling of live cells, tissues or organisms, as these produce the FP markers all by themselves after introduction of a suitable gene. Here we cover FP markers from the GFP family of proteins as well as tetrapyrrole-binding proteins, which further complement the FP toolbox in important ways. A broad range of FP variants have been endowed, by using protein engineering, with photophysical properties that are essential for specific fluorescence microscopy techniques, notably those offering nanoscale image resolution. We briefly introduce various advanced imaging methods and show how they utilize the distinct properties of the FP markers in exciting imaging applications, with the aim to guide researchers toward the design of powerful imaging experiments that are optimally suited to address their biological questions.

mEos4b Photoconversion Efficiency Depends on Laser Illumination Conditions Used in PALM

Green-to-red photoconvertible fluorescent proteins (PCFPs) are widely employed as markers in photoactivated localization microscopy (PALM). However, their highly complex photophysical behavior complicates their usage. The fact that only a limited fraction of a PCFP ensemble can form the photoconverted state upon near-UV light illumination, termed photoconversion efficiency (PCE), lowers the achievable spatial resolution in PALM and creates undercounting errors in quantitative counting applications. Here, we show that the PCE of mEos4b is not a fixed property of this PCFP but strongly depends on illumination conditions. Attempts to reduce long-lived blinking in red mEos4b by application of 488 nm light lead to a reduction of the PCE. Furthermore, the PCE of mEos4b strongly depends on the applied 405 nm power density. A refined photophysical model of mEos4b accounts for the observed effects, involving nonlinear green-state photobleaching upon violet light illumination favored by photon absorption by a putative radical dark state.

Modeling Non-additive Effects in Neighboring Chemically Identical Fluorophores

Quantitative fluorescence analysis is often used to derive chemical properties, including stoichiometries, of biomolecular complexes. One fundamental underlying assumption in the analysis of fluorescence data─whether it be the determination of protein complex stoichiometry by super-resolution, or step-counting by photobleaching, or the determination of RNA counts in diffraction-limited spots in RNA fluorescence in situ hybridization (RNA-FISH) experiments─is that fluorophores behave identically and do not interact. However, recent experiments on fluorophore-labeled DNA origami structures such as fluorocubes have shed light on the nature of the interactions between identical fluorophores as these are brought closer together, thereby raising questions on the validity of the modeling assumption that fluorophores do not interact. Here, we analyze photon arrival data under pulsed illumination from fluorocubes where distances between dyes range from 2 to 10 nm. We discuss the implications of non-additivity of brightness on quantitative fluorescence analysis.

Correction of multiple-blinking artifacts in photoactivated localization microscopy

Photoactivated localization microscopy (PALM) produces an array of localization coordinates by means of photoactivatable fluorescent proteins. However, observations are subject to fluorophore multiple blinking and each protein is included in the dataset an unknown number of times at different positions, due to localization error. This causes artificial clustering to be observed in the data. We present a 'model-based correction' (MBC) workflow using calibration-free estimation of blinking dynamics and model-based clustering to produce a corrected set of localization coordinates representing the true underlying fluorophore locations with enhanced localization precision, outperforming the state of the art. The corrected data can be reliably tested for spatial randomness or analyzed by other clustering approaches, and descriptors such as the absolute number of fluorophores per cluster are now quantifiable, which we validate with simulated data and experimental data with known ground truth. Using MBC, we confirm that the adapter protein, the linker for activation of T cells, is clustered at the T cell immunological synapse.

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.

Super-Resolution Microscopy and Tracking of DNA-Binding Proteins in Bacterial Cells

The ability to detect individual fluorescent molecules inside living cells has enabled a range of powerful microscopy techniques that resolve biological processes on the molecular scale. These methods have also transformed the study of bacterial cell biology, which was previously obstructed by the limited spatial resolution of conventional microscopy. In the case of DNA-binding proteins, super-resolution microscopy can visualize the detailed spatial organization of DNA replication, transcription, and repair processes by reconstructing a map of single-molecule localizations. Furthermore, DNA-binding activities can be observed directly by tracking protein movement in real time. This allows identifying subpopulations of DNA-bound and diffusing proteins, and can be used to measure DNA-binding times in vivo. This chapter provides a detailed protocol for super-resolution microscopy and tracking of DNA-binding proteins in Escherichia coli cells. The protocol covers the genetic engineering and fluorescent labeling of strains and describes data acquisition and analysis procedures, such as super-resolution image reconstruction, mapping single-molecule tracks, computing diffusion coefficients to identify molecular subpopulations with different mobility, and analysis of DNA-binding kinetics. While the focus is on the study of bacterial chromosome biology, these approaches are generally applicable to other molecular processes and cell types.

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.

An expectation-maximization approach to quantifying protein stoichiometry with single-molecule imaging

Motivation

Single-molecule localization microscopy (SMLM) is a super-resolution technique capable of rendering nanometer scale images of cellular structures. Recently, much effort has gone into developing algorithms for extracting quantitative features from SMLM datasets, such as the abundance and stoichiometry of macromolecular complexes. These algorithms often require knowledge of the complicated photophysical properties of photoswitchable fluorophores.

Results

Here, we develop a calibration-free approach to quantitative SMLM built upon the observation that most photoswitchable fluorophores emit a geometrically distributed number of blinks before photobleaching. From a statistical model of a mixture of monomers, dimers and trimers, the method employs an adapted expectation-maximization algorithm to learn the protomer fractions while simultaneously determining the single-fluorophore blinking distribution. To illustrate the utility of our approach, we benchmark it on both simulated datasets and experimental datasets assembled from SMLM images of fluorescently labeled DNA nanostructures.

Availability and implementation

An implementation of our algorithm written in Python is available at: https://www.utm.utoronto.ca/milsteinlab/resources/Software/MMCode/.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

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.

Photobleaching step analysis for robust determination of protein complex stoichiometries

The counting of discrete photobleaching steps in fluorescence microscopy is ideally suited to study protein complex stoichiometry in situ. The counting range of photobleaching step analysis has been significantly improved with more-sophisticated algorithms for step detection, albeit at an increasing computational cost and with the necessity for high-quality data. Here, we address concerns regarding robustness, automation, and experimental validation, optimizing both data acquisition and analysis. To make full use of the potential of photobleaching step analysis, we evaluate various labeling strategies with respect to their molecular brightness, photostability, and photoblinking. The developed analysis algorithm focuses on automation and computational efficiency. Moreover, we validate the developed methods with experimental data acquired on DNA origami labeled with defined fluorophore numbers, demonstrating counting of up to 35 fluorophores. Finally, we show the power of the combination of optimized trace acquisition and automated data analysis by counting labeled nucleoporin 107 in nuclear pore complexes of intact U2OS cells. The successful in situ application promotes this framework as a new resource enabling cell biologists to robustly determine the stoichiometries of molecular assemblies at the single-molecule level in an automated manner.

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.

Breaking the diffraction limit in absorption spectroscopy using upconverting nanoparticles

We employ a single optically trapped upconverting nanoparticle (UCNP) of NaYF4:Yb,Er of diameter about 100 nm as a subdiffractive source to perform absorption spectroscopy. The experimentally expected mode volume of 100 nm of the backscatter profile of the nanoparticle matches well with a numerical simulation of the dominant backscattering modes to confirm our assertion of achieving a source dimension considerably lower than the diffraction limit set by the excitation wavelength of 975 nm for the UCNP. We perform absorption spectroscopy of several diverse entities such as the dye Rhodamine B in water, a thin gold film of thickness 30 nm, and crystalline soft oxometalates micro-patterned on a glass substrate using the UCNP as a source. The initial results lead to unambiguous utility of UCNPs as single nanoscopic sources for absorption spectroscopy of ultra-small sample volumes (femtolitres), and lead us to hypothesize a possible Resonance Energy Transfer mechanism between the UCNP and the molecules of the ambient medium, which may even lead to single molecule absorption spectroscopy applications.

Quantitative live-cell PALM reveals nanoscopic Faa4 redistributions and dynamics on lipid droplets during metabolic transitions of yeast

Lipid droplets (LDs) are dynamic organelles for lipid storage and homeostasis. Cells respond to metabolic changes by regulating the spatial distribution of LDs and enzymes required for LD growth and turnover. The small size of LDs precludes the observation of their associated enzyme densities and dynamics with conventional fluorescence microscopy. Here we employ quantitative photo-activated localization microscopy to study the density of the fatty acid (FA) activating enzyme Faa4 on LDs in live yeast cells with single-molecule sensitivity and 30 nm resolution. During the log phase LDs colocalize with the endoplasmic reticulum (ER) where their emergence and expansion are mediated by the highest observed Faa4 densities. During transition to the stationary phase, LDs with a ∼2-fold increased surface area translocate to the vacuolar surface and lumen and exhibit a ∼2.5-fold increase in Faa4 density. The increased Faa4 density on LDs further suggests its role in LD expansion, is caused by its ∼5-fold increased expression level, and is specific to exogenous FA chain-lengths. When lipolysis is induced by refreshed medium, Faa4 shuttles through ER- and lipophagy to the vacuole, where it may activate FAs for membrane expansion and degrade Faa4 to reset its cellular abundance to levels in the log phase.

How Single-Molecule Localization Microscopy Expanded Our Mechanistic Understanding of RNA Polymerase II Transcription

Classical models of gene expression were built using genetics and biochemistry. Although these approaches are powerful, they have very limited consideration of the spatial and temporal organization of gene expression. Although the spatial organization and dynamics of RNA polymerase II (RNAPII) transcription machinery have fundamental functional consequences for gene expression, its detailed studies have been abrogated by the limits of classical light microscopy for a long time. The advent of super-resolution microscopy (SRM) techniques allowed for the visualization of the RNAPII transcription machinery with nanometer resolution and millisecond precision. In this review, we summarize the recent methodological advances in SRM, focus on its application for studies of the nanoscale organization in space and time of RNAPII transcription, and discuss its consequences for the mechanistic understanding of gene expression.

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.

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.

Probing Biosensing Interfaces With Single Molecule Localization Microscopy (SMLM)

Far field single molecule localization microscopy (SMLM) has been established as a powerful tool to study biological structures with resolution far below the diffraction limit of conventional light microscopy. In recent years, the applications of SMLM have reached beyond traditional cellular imaging. Nanostructured interfaces are enriched with information that determines their function, playing key roles in applications such as chemical catalysis and biological sensing. SMLM enables detailed study of interfaces at an individual molecular level, allowing measurements of reaction kinetics, and detection of rare events not accessible to ensemble measurements. This paper provides an update to the progress made to the use of SMLM in characterizing nanostructured biointerfaces, focusing on practical aspects, recent advances, and emerging opportunities from an analytical chemistry perspective.