Automated Analysis of Single-Molecule Photobleaching Data by Statistical Modeling of Spot Populations

Single-Molecule Stoichiometry of Supramolecular Complexes

The use of single-molecule microscopy is introduced as a method to quantify the photophysical properties of supramolecular complexes rapidly at ultra low concentrations (<1 nM), previously inaccessible. Using a model supramolecular system based on the host-guest complexation of cucurbit[n]uril (CB[n]) macrocycles together with a fluorescent guest (Ant910Me), we probe fluorescent CB[n] host-guest complexes in the single molecule regime. We show quantification and differentiation of host-guest photophysics and stoichiometries, both in aqueous media and noninvasively in hydrogel, by thresholding detected photons. This methodology has wide reaching implications in aiding the design of next-generation materials with programmed and controlled properties.

Purification Analysis, Intracellular Tracking, and Colocalization of Extracellular Vesicles Using Atomic Force and 3D Single-Molecule Localization Microscopy

Extracellular vesicles (EVs) play a key role in cell-cell communication and thus have great potential to be utilized as therapeutic agents and diagnostic tools. In this study, we implemented single-molecule microscopy techniques as a toolbox for a comprehensive characterization as well as measurement of the cellular uptake of HEK293T cell-derived EVs (eGFP-labeled) in HeLa cells. A combination of fluorescence and atomic force microscopy revealed a fraction of 68% fluorescently labeled EVs with an average size of ∼45 nm. Two-color single-molecule fluorescence microscopy analysis elucidated the 3D dynamics of EVs entering HeLa cells. 3D colocalization analysis of two-color direct stochastic optical reconstruction microscopy (dSTORM) images revealed that 25% of EVs that experienced uptake colocalized with transferrin, which has been linked to early recycling of endosomes and clathrin-mediated endocytosis. The localization analysis was combined with stepwise photobleaching, providing a comparison of protein aggregation outside and inside the cells.

Deep-Learning-Enhanced Diffusion Imaging Assay for Resolving Local-Density Effects on Membrane Receptors

G-protein-coupled receptor (GPCR) density at the cell surface is thought to regulate receptor function. Spatially resolved measurements of local-density effects on GPCRs are needed but technically limited by density heterogeneity and mobility of membrane receptors. We now develop a deep-learning (DL)-enhanced diffusion imaging assay that can measure local-density effects on ligand-receptor interactions in the plasma membrane of live cells. In this method, the DL algorithm allows the transformation of 100 ms exposure images to density maps that report receptor numbers over any specified region with ∼95% accuracy by 1 s exposure images as ground truth. With the density maps, a diffusion assay is further established for spatially resolved measurements of receptor diffusion coefficient as well as to express relationships between receptor diffusivity and local density. By this assay, we scrutinize local-density effects on chemokine receptor CXCR4 interactions with various ligands, which reveals that an agonist prefers to act with CXCR4 at low density while an inverse agonist dominates at high density. This work suggests a new insight into density-dependent receptor regulation as well as provides an unprecedented assay that can be applicable to a wide variety of receptors in live cells.

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.

Quantification of Available Ligand Density on the Surface of Targeted Liposomal Nanomedicines at the Single-Particle Level

Active targeting has been hailed as one of the most promising strategies to further enhance the therapeutic efficacy of liposomal nanomedicines. Owing to the critical role of ligand density in mediating cellular uptake and the intrinsic heterogeneity of liposomal formulations, precise quantification of the surface ligand density on a single-particle basis is of fundamental importance. In this work, we report a method to simultaneously measure the particle size and the number of ligands on the same liposomal nanoparticles by nanoflow cytometry. Then the ligand density for each individual liposome can be determined. With an analysis rate up to 10 000 particles per minute, a statistically representative distribution of ligand density could be determined in minutes. By utilizing fluorescently labeled recombinant receptors as the detection probe against the conjugated ligands, only those available for cell targeting can be exclusively detected. The influence of ligand input, conjugation strategy, and the polyethylene glycol spacer length on the available ligand density of folate-modified liposomes was investigated. The correlation between the available ligand density and cell targeting capability was assessed in a quantitative perspective for liposomes modified with three different targeting moieties. The optimal ligand density was determined to be 0.5-2.0, 0.7, and 0.2 ligand per 100 nm² for folate-, transferrin-, and HER2-antibody-conjugated liposomes, respectively. These optimal values agreed well with the spike density of the natural counterparts, viruses. The as-developed approach is generally applicable to a wide range of active-targeting nanocarriers.

Detection and quantification of the vacuolar H+ATPase using the Legionella effector protein SidK

Acidification of secretory and endocytic organelles is required for proper receptor recycling, membrane traffic, protein degradation, and solute transport. Proton-pumping vacuolar H+ ATPases (V-ATPases) are responsible for this luminal acidification, which increases progressively as secretory and endocytic vesicles mature. An increasing density of V-ATPase complexes is thought to account for the gradual decrease in pH, but available reagents have not been sufficiently sensitive or specific to test this hypothesis. We introduce a new probe to localize and quantify V-ATPases. The probe is derived from SidK, a Legionella pneumophila effector protein that binds to the V-ATPase A subunit. We generated plasmids encoding fluorescent chimeras of SidK1-278, and labeled recombinant SidK1-278 with Alexa Fluor 568 to visualize and quantify V-ATPases with high specificity in live and fixed cells, respectively. We show that V-ATPases are acquired progressively during phagosome maturation, that they distribute in discrete membrane subdomains, and that their density in lysosomes depends on their subcellular localization.

Exon-independent recruitment of SRSF1 is mediated by U1 snRNP stem-loop 3

SRSF1 protein and U1 snRNPs are closely connected splicing factors. They both stimulate exon inclusion, SRSF1 by binding to exonic splicing enhancer sequences (ESEs) and U1 snRNPs by binding to the downstream 5' splice site (SS), and both factors affect 5' SS selection. The binding of U1 snRNPs initiates spliceosome assembly, but SR proteins such as SRSF1 can in some cases substitute for it. The mechanistic basis of this relationship is poorly understood. We show here by single-molecule methods that a single molecule of SRSF1 can be recruited by a U1 snRNP. This reaction is independent of exon sequences and separate from the U1-independent process of binding to an ESE. Structural analysis and cross-linking data show that SRSF1 contacts U1 snRNA stem-loop 3, which is required for splicing. We suggest that the recruitment of SRSF1 to a U1 snRNP at a 5'SS is the basis for exon definition by U1 snRNP and might be one of the principal functions of U1 snRNPs in the core reactions of splicing in mammals.

Live-cell imaging shows uneven segregation of extrachromosomal DNA elements and transcriptionally active extrachromosomal DNA hubs in cancer

Oncogenic extrachromosomal DNA elements (ecDNAs) play an important role in tumor evolution, but our understanding of ecDNA biology is limited. We determined the distribution of single-cell ecDNA copy number across patient tissues and cell line models and observed how cell-to-cell ecDNA frequency greatly varies. The exceptional intratumoral heterogeneity of ecDNA suggested ecDNA-specific replication and propagation mechanisms. To evaluate the transfer of ecDNA genetic material from parental to offspring cells during mitosis, we established the CRISPR-based ecTag method. EcTag leverages ecDNA-specific breakpoint sequences to tag ecDNA with fluorescent markers in living cells. Applying ecTag during mitosis revealed disjointed ecDNA inheritance patterns, enabling rapid ecDNA accumulation in individual cells. Post-mitosis, ecDNAs clustered into ecDNA hubs, and ecDNA hubs colocalized with RNA polymerase II, promoting transcription of cargo oncogenes. Our observations provide direct evidence for uneven segregation of ecDNA and shed new light on mechanisms through which ecDNAs contribute to oncogenesis.

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.

Determining stoichiometry of ion channel complexes using single subunit counting

Most membrane proteins, and ion channels in particular, assemble to multimeric biological complexes. This starts with the quarternary structure and continues with the recruitment of auxiliary subunits and oligomerization or clustering of the complexes. While the quarternary structure is best determined by atomic-scale structures, stoichiometry of heteromers and dynamic changes in the assembly cannot necessarily be investigated with structural methods. Here, single subunit counting has proven a powerful method to study the composition of these complexes. Single subunit counting uses the irreversible photodestruction of fluorescent tags as means to directly count a labeled subunit and thereby derive the composition of the assemblies. In this chapter, we discuss single subunit counting and its limitations. We present alternative methods and provide a detailed protocol for recording and analysis of single subunit counting data.

Smart-ORF: a single-molecule method for accessing ribosome dynamics in both upstream and main open reading frames

Upstream open reading frame (uORF) translation disrupts scanning 43S flux on mRNA and modulates main open reading frame (mORF) translation efficiency. Current tools, however, have limited access to ribosome dynamics in both upstream and main ORFs of an mRNA. Here, we develop a new two-color in vitro fluorescence assay, Smart-ORF, that monitors individual uORF and mORF translation events in real-time with single-molecule resolution. We demonstrate the utility of Smart-ORF by applying it to uORF-encoded arginine attenuator peptide (AAP)-mediated translational regulation. The method enabled quantification of uORF and mORF initiation efficiencies, 80S dwell time, polysome formation, and the correlation between uORF and mORF translation dynamics. Smart-ORF revealed that AAP-mediated 80S stalling in the uORF stimulates the uORF initiation efficiency and promotes clustering of slower uORF-translating ribosomes. This technology provides a new tool that can reveal previously uncharacterized dynamics of uORF-containing mRNA translation.

Tetrameric architecture of an active phenol-bound form of the AAA+ transcriptional regulator DmpR

The Pseudomonas putida phenol-responsive regulator DmpR is a bacterial enhancer binding protein (bEBP) from the AAA⁺ ATPase family. Even though it was discovered more than two decades ago and has been widely used for aromatic hydrocarbon sensing, the activation mechanism of DmpR has remained elusive. Here, we show that phenol-bound DmpR forms a tetramer composed of two head-to-head dimers in a head-to-tail arrangement. The DmpR-phenol complex exhibits altered conformations within the C-termini of the sensory domains and shows an asymmetric orientation and angle in its coiled-coil linkers. The structural changes within the phenol binding sites and the downstream ATPase domains suggest that the effector binding signal is propagated through the coiled-coil helixes. The tetrameric DmpR-phenol complex interacts with the σ⁵⁴ subunit of RNA polymerase in presence of an ATP analogue, indicating that DmpR-like bEBPs tetramers utilize a mechanistic mode distinct from that of hexameric AAA⁺ ATPases to activate σ⁵⁴-dependent transcription.

Determining the correct stoichiometry of Kv2.1/Kv6.4 heterotetramers, functional in multiple stoichiometrical configurations

The electrically silent (KvS) members of the voltage-gated potassium (Kv) subfamilies Kv5, Kv6, Kv8, and Kv9 selectively modulate Kv2 subunits by forming heterotetrameric Kv2/KvS channels. Based on the reported 3:1 stoichiometry of Kv2.1/Kv9.3 channels, we tested the hypothesis that Kv2.1/Kv6.4 channels express, in contrast to the assumed 3:1, in a 2:2 stoichiometry. We investigate the Kv2.1/Kv6.4 stoichiometry using single subunit counting and functional characterization of tetrameric concatemers. For selecting the most probable stoichiometry, we introduce a model-selection method that is applicable for any multimeric complex by investigating the stoichiometry of Kv2.1/Kv6.4 channels. Weighted likelihood calculations bring rigor to a powerful technique. Using the weighted-likelihood model-selection method and analysis of electrophysiological data, we show that Kv2.1/Kv6.4 channels express, in contrast to the assumed 3:1, in a 2:2 stoichiometry. Within this stoichiometry, the Kv6.4 subunits have to be positioned alternating with Kv2.1 to express functional channels. The variability in Kv2/KvS assembly increases the diversity of heterotetrameric configurations and extends the regulatory possibilities of KvS by allowing the presence of more than one silent subunit.

Studying Tau-Microtubule Interaction Using Single-Molecule TIRF Microscopy

Microtubule architecture depends on a complex network of microtubule-associated proteins (MAPs) that act in concert to modulate microtubule assembly/disassembly and spatial arrangement. In vitro reconstitution of cytoskeleton dynamics coupled to single-molecule fluorescence assays has opened new perspectives to quantify the interaction of MAPs with microtubules. Here, we present a Total Internal Reflection Fluorescence (TIRF) microscopy-based assay enabling the characterization of Tau interaction with dynamic microtubules at the single-molecule level. We describe protein sample preparation in flow cells, single-molecule acquisitions by TIRF microscopy, and quantitative analysis of Tau oligomerization states and dwell time on microtubules.

Monitoring Transcription Factor Oligomerization in Single Living Cells by Number and Brightness Analysis

One key step in the activation of inducible transcription factors is their homooligomerization, which can be measured in individual living cells by a fluorescence microscopy technique called Number and Brightness analysis (N&B). In this chapter we describe how to acquire and analyze confocal microscopy time-series to provide information about transcription factor oligomerization in living cells using this technique.

Quantifying the Degree of Aggregation from Fluorescent Dye-Conjugated DNA Probe by Single Molecule Photobleaching Technology for the Ultrasensitive Detection of Adenosine

In this work, we demonstrated a single molecule photobleaching-based strategy for the ultrasensitive detection of adenosine. A modified split aptamer was designed to specifically recognize individual adenosine molecules in solution. The specific binding of dye-labeled short strand DNA probes onto the elongated aptamer strand in the presence of adenosine resulted in a concentration-dependent self-aggregation process. The degree-of-aggregation (DOA) of the short DNA probes on the elongated aptamer strand could then be accurately determined based on the single molecule photobleaching measurement. Through statistically analyzing the DOA under different target concentrations, a well-defined curvilinear relationship between the DOA and target molecule concentration (e.g., adenosine) was established. The limit-of-detection (LOD) is down to 44.5 pM, which is lower than those recently reported results with fluorescence-based analysis. Owing to the high sensitivity and excellent selectivity, the sensing strategy described herein would find broad applications in biomolecule analysis under complicated surroundings.

Single-molecule techniques in biophysics: a review of the progress in methods and applications

Single-molecule biophysics has transformed our understanding of biology, but also of the physics of life. More exotic than simple soft matter, biomatter lives far from thermal equilibrium, covering multiple lengths from the nanoscale of single molecules to up to several orders of magnitude higher in cells, tissues and organisms. Biomolecules are often characterized by underlying instability: multiple metastable free energy states exist, separated by levels of just a few multiples of the thermal energy scale k _B T, where k _B is the Boltzmann constant and T absolute temperature, implying complex inter-conversion kinetics in the relatively hot, wet environment of active biological matter. A key benefit of single-molecule biophysics techniques is their ability to probe heterogeneity of free energy states across a molecular population, too challenging in general for conventional ensemble average approaches. Parallel developments in experimental and computational techniques have catalysed the birth of multiplexed, correlative techniques to tackle previously intractable biological questions. Experimentally, progress has been driven by improvements in sensitivity and speed of detectors, and the stability and efficiency of light sources, probes and microfluidics. We discuss the motivation and requirements for these recent experiments, including the underpinning mathematics. These methods are broadly divided into tools which detect molecules and those which manipulate them. For the former we discuss the progress of super-resolution microscopy, transformative for addressing many longstanding questions in the life sciences, and for the latter we include progress in 'force spectroscopy' techniques that mechanically perturb molecules. We also consider in silico progress of single-molecule computational physics, and how simulation and experimentation may be drawn together to give a more complete understanding. Increasingly, combinatorial techniques are now used, including correlative atomic force microscopy and fluorescence imaging, to probe questions closer to native physiological behaviour. We identify the trade-offs, limitations and applications of these techniques, and discuss exciting new directions.

Time-resolved molecule counting by photon statistics across the visible spectrum

In the past few years quantification of fluorescently labeled (bio-) molecules has become of increasing importance and several approaches have been developed to address this task. Counting by photon statistics measures the distribution of multiple photon detection events that carry information about the number and brightness of independently emitting fluorophores. The method enables absolute and non-destructive quantification, with the quality of estimates critically depending on the ability to accurately measure said photon statistics. Here, we present a combination of simulations and experiments that relate fundamental properties of fluorophores, i.e. their molecular brightness and photostability, to important experimental conditions, i.e. excitation power and acquisition time. Thereby, experimental settings and analysis parameters can be quantitatively evaluated, making counting by photon statistics a robust method for absolute counting of the number of emitters in a diffraction limited observation volume. We show that the time-resolution of counting varies with the fluorophore brightness and can be as fast as 10-100 ms. At the same time, the range of suitable fluorophores can be easily assessed. We evaluated the brightness and photostability of 16 organic dyes across the visible spectrum, providing information crucial for a range of single-molecule spectroscopy applications. This opens up exciting possibilities to analyze absolute stoichiometries in dynamic multi-component complexes.

Quantitative microscopy based on single-molecule fluorescence

Quantitative microscopy is needed to understand reactions or phenomena carried out by biological molecules such as enzymes, receptors, and membrane-localized proteins. Counting the biomolecules of interest in single organelles or cellular compartments is critical in these approaches. In this brief perspective, we focus on the development of quantitative fluorescence microscopies that measure the precise copy numbers of proteins in cellular organelles or purified samples. We introduce recent improvements in quantitative microscopies to overcome undercounting or overcounting errors in certain conditions. We conclude by discussing biological applications.

Unraveling the Thousand Word Picture: An Introduction to Super-Resolution Data Analysis

Super-resolution microscopy provides direct insight into fundamental biological processes occurring at length scales smaller than light's diffraction limit. The analysis of data at such scales has brought statistical and machine learning methods into the mainstream. Here we provide a survey of data analysis methods starting from an overview of basic statistical techniques underlying the analysis of super-resolution and, more broadly, imaging data. We subsequently break down the analysis of super-resolution data into four problems: the localization problem, the counting problem, the linking problem, and what we've termed the interpretation problem.

Monitoring Changes in the Oligomeric State of a Candidate Endoplasmic Reticulum (ER) Ceramide Sensor by Single-molecule Photobleaching

Single-molecule photobleaching has emerged as a powerful non-invasive approach to extract the stoichiometry of multimeric membrane proteins in their native cellular environment. However, this method has mainly been used to determine the subunit composition of ion channels and receptors at the plasma membrane. Here, we applied single-molecule photobleaching to analyze the oligomeric state of an endoplasmic reticulum (ER) resident candidate ceramide sensor protein, SMSr/SAMD8. Co-immunoprecipitation and chemical cross-linking studies previously revealed that the N-terminal sterile alpha motif (or SAM) domain of SMSr drives self-assembly of the protein into oligomers and that SMSr oligomerization is promoted by curcumin, a drug known to perturb ER ceramide and calcium homeostasis. Application of cell spreading surface-active coating materials in combination with total internal reflection fluorescence (TIRF) microscopy allowed us to image GFP-tagged SMSr proteins as single fluorescent spots in the ER of HeLa cells in which expression of endogenous SMSr was abolished. In line with our biochemical analysis, we find that the number of bleaching steps in SMSr-GFP-positive spots displays a substantial drop after removal of the SAM domain. In contrast, treatment of cells with curcumin increased the number of bleaching steps. Our results document the first successful application of single-molecule photobleaching to resolve drug-induced and domain-dependent changes in the oligomeric state of an ER-resident membrane protein, hence establishing a complementary method to unravel the mechanism by which SMSr controls ceramide levels in the ER.

A novel method to accurately locate and count large numbers of steps by photobleaching

Photobleaching event counting is a single-molecule fluorescence technique that is increasingly being used to determine the stoichiometry of protein and RNA complexes composed of many subunits in vivo as well as in vitro. By tagging protein or RNA subunits with fluorophores, activating them, and subsequently observing as the fluorophores photobleach, one obtains information on the number of subunits in a complex. The noise properties in a photobleaching time trace depend on the number of active fluorescent subunits. Thus, as fluorophores stochastically photobleach, noise properties of the time trace change stochastically, and these varying noise properties have created a challenge in identifying photobleaching steps in a time trace. Although photobleaching steps are often detected by eye, this method only works for high individual fluorophore emission signal-to-noise ratios and small numbers of fluorophores. With filtering methods or currently available algorithms, it is possible to reliably identify photobleaching steps for up to 20-30 fluorophores and signal-to-noise ratios down to ∼1. Here we present a new Bayesian method of counting steps in photobleaching time traces that takes into account stochastic noise variation in addition to complications such as overlapping photobleaching events that may arise from fluorophore interactions, as well as on-off blinking. Our method is capable of detecting ≥50 photobleaching steps even for signal-to-noise ratios as low as 0.1, can find up to ≥500 steps for more favorable noise profiles, and is computationally inexpensive.