A Platform To Enhance Quantitative Single Molecule Localization Microscopy

Single Extracellular VEsicle Nanoscopy-Universal Protocol (SEVEN-UP): Accessible Imaging Platform for Quantitative Characterization of Single Extracellular Vesicles

Extracellular vesicles (EVs), membrane-encapsulated nanoparticles shed from all cells, are tightly involved in critical cellular functions. Moreover, EVs have recently emerged as exciting therapeutic modalities, delivery vectors, and biomarker sources. However, EVs are difficult to characterize, because they are typically small and heterogeneous in size, origin, and molecular content. Recent advances in single EV methods have addressed some of these challenges by providing sensitive tools for assessing individual vesicles; one example is our recently developed Single Extracellular VEsicle Nanoscopy (SEVEN) approach. However, these tools are typically not universally available to the general research community, as they require highly specialized equipment. Here, we show how single EV studies may be democratized via a novel method that employs super-resolution radial fluctuations (SRRF) microscopy and advanced data analysis. SRRF is compatible with a wide range of microscopes and fluorophores. We herein quantified individual EVs by combining affinity isolation (analytical protocol based on SEVEN) with SRRF microscopy and new analysis algorithms supported by machine learning-based EV assessment. Using SEVEN, we first optimized the workflow and validated the data obtained on wide-field and total internal reflection fluorescence microscopes. We further demonstrated that our approach, which we call the SEVEN-Universal Protocol (SEVEN-UP), can robustly assess the number, size, and content of plasma and recombinant EVs. Finally, we used the platform to assess RNA in EVs from conditioned cell culture media. Using SYTO RNASelect dye, we found that 18% of EVs from HEK 293T cells appear to contain RNA; these EVs were significantly larger compared with the general EV population. Altogether, we developed an economical, multiparametric, single EV characterization approach for the research community.

Phenotypic Biomarkers of Aqueous Extracellular Vesicles from Retinoblastoma Eyes

Recent advancements in aqueous humor (AH) cell-free DNA (cfDNA) genomics have opened new avenues for ex vivo molecular profiling of retinoblastoma (RB), the most common pediatric intraocular malignancy, where biopsy is typically prohibited. While these insights offer a genetic blueprint of the tumor, they lack multi-omic molecular phenotyping, which is essential for understanding the functional state. Extracellular vesicles (EVs), naturally present in AH, are promising by offering time-resolved phenotypic information. We employed multiplex bead-based flow cytometry and Single Extracellular Vesicle Nanoscopy (SEVEN) to analyze EV phenotypes in AH from a cohort of five RB, with three uveal melanoma (UM) and two age-matched glaucoma (GLC) samples serving as controls. The studies identified CD133-enriched EVs uniquely in RB AH, absent in both GLC and UM AH. This was corroborated by further analysis of five RB cell lines, including two commercial (Y79, Weri) and three in-house developed lines, confirming CD133 enrichment and supporting its role as an RB-specific EV marker. Single-vesicle analysis demonstrated a strong association of CD133 with CD81 and CD63, with minimal CD9 presence. These results, validated through complementary techniques, position CD133 as a critical marker in RB-derived EVs, paving the way for enhanced multi-omic RB characterization and potential advancements in clinical diagnostics.

Pancreatic β-cells package double C2-like domain beta protein into extracellular vesicles via tandem C2 domains

Introduction

Double C2-like domain beta (DOC2B) is a vesicle priming protein critical for glucose-stimulated insulin secretion in β-cells. Individuals with type 1 diabetes (T1D) have lower levels of DOC2B in their residual functional β-cell mass and platelets, a phenotype also observed in a mouse model of T1D. Thus, DOC2B levels could provide important information on β-cell dys(function).

Objective

Our objective was to evaluate the DOC2B secretome of β-cells. In addition to soluble extracellular protein, we assessed DOC2B localized within membrane-delimited nanoparticles - extracellular vesicles (EVs). Moreover, in rat clonal β-cells, we probed domains required for DOC2B sorting into EVs.

Method

Using Single Extracellular VEsicle Nanoscopy, we quantified EVs derived from clonal β-cells (human EndoC-βH1, rat INS-1 832/13, and mouse MIN6); two other cell types known to regulate glucose homeostasis and functionally utilize DOC2B (skeletal muscle rat myotube L6-GLUT4myc and human neuronal-like SH-SY5Y cells); and human islets sourced from individuals with no diabetes (ND). EVs derived from ND human plasma, ND human islets, and cell lines were isolated with either size exclusion chromatography or differential centrifugation. Isolated EVs were comprehensively characterized using dotblots, transmission electron microscopy, nanoparticle tracking analysis, and immunoblotting.

Results

DOC2B was present within EVs derived from ND human plasma, ND human islets, and INS-1 832/13 β-cells. Compared to neuronal-like SH-SY5Y cells and L6-GLUT4myc myotubes, clonal β-cells (EndoC-βH1, INS-1 832/13, and MIN6) produced significantly more EVs. DOC2B levels in EVs (over whole cell lysates) were higher in INS-1 832/13 β-cells compared to L6-GLUT4myc myotubes; SH-SY5Y neuronal-like cells did not release appreciable DOC2B. Mechanistically, we show that DOC2B was localized to the EV lumen; the tandem C2 domains were sufficient to confer sorting to INS-1 832/13 β-cell EVs.

Discussion

Clonal β-cells and ND human islets produce abundant EVs. In cell culture, appreciable DOC2B can be packaged into EVs, and a small fraction is excreted as a soluble protein. While DOC2B-laden EVs and soluble protein are present in ND plasma, further studies will be necessary to determine if DOC2B originating from β-cells significantly contributes to the plasma secretome.

Comparison of nanoimaging and nanoflow based detection of extracellular vesicles at a single particle resolution

The characterization of single extracellular vesicle (EV) has been an emerging tool for the early detection of various diseases despite there being challenges regarding how to interpret data with different protocols or instruments. In this work, standard EV particles were characterized for single CD9+, single CD81+ or double CD9+/CD81+ tetraspanin molecule positivity with two single EV analytic technologies in order to optimize their EV sample preparation after antibody labelling and analysis methods: NanoImager for direct stochastic optical reconstruction microscopy (dSTORM)-based EV imaging and characterization, and Flow NanoAnalyzer for flow-based EV quantification and characterization. False positives from antibody aggregates were found during dSTORM-based NanoImager imaging. Analysis of particle radius with lognormal fittings of probability density histogram enabled the removal of antibody aggregates and corrected EV quantification. Furthermore, different machine learning models were trained to differentiate antibody aggregates from EV particles and correct EV quantification with increased double CD9+/CD81+ population. With Flow NanoAnalyzer, EV samples were prepared with different dilution or fractionation methods, which increased the detection rate of CD9+/CD81+ EV population. Comparing the EV phenotype percentages measured by two instruments, differences in double positive and single positive particles existed after percentage correction, which might be due to the different detection limit of each instrument. Our study reveals that the characterization of individual EVs for tetraspanin positivity varies between two platforms-the NanoImager and the Flow NanoAnalyzer-depending on the EV sample preparation methods used after antibody labelling. Additionally, we applied machine learning models to correct for false positive particles identified in imaging-based results by fitting size distribution data.

Multiparametric profiling of HER2-enriched extracellular vesicles in breast cancer using Single Extracellular VEsicle Nanoscopy

BACKGROUND

Patients with HER2-positive breast cancer can significantly benefit from HER2-directed therapy - such as the monoclonal antibody trastuzumab. However, some patients can develop therapy resistance or change HER2 status. Thus, we urgently need new, noninvasive strategies to monitor patients frequently. Extracellular vesicles (EVs) secreted from tumor cells are emerging as potential biomarker candidates. These membrane-delimited nanoparticles harbor molecular signatures of their origin cells; report rapidly on changes to cellular status; and can be frequently sampled from accessible biofluids.

RESULTS

Using Single Extracellular VEsicle Nanoscopy (SEVEN) platform that combines affinity isolation of EVs with super-resolution microscopy, here we provide multiparametric characterization of EVs with ~ 8 nm precision and molecular sensitivity. We first interrogated cell culture EVs affinity-enriched in tetraspanins CD9, CD63, and CD81; these transmembrane proteins are commonly found on EV membranes. SEVEN robustly provided critical parameters of individual, tetraspanin-enriched EVs: concentration, size, shape, molecular cargo content, and heterogeneity. Trastuzumab-resistant cells (vs. trastuzumab-sensitive) secreted more EVs. Additionally, EVs from trastuzumab-resistant cells had lower tetraspanin density and higher HER2 density. We also evaluated EVs affinity-enriched in HER2; we found that these EVs (vs. tetraspanin-enriched) were larger and more elongated. We further optimized analytical sample processing to assess a rare population of HER2-enriched EVs from patient plasma. In breast cancer patients with elevated HER2 protein expression (vs. controls), HER2-enriched EVs had distinct characteristics including typically increased number of tetraspanin molecules and larger size. Importantly, these EVs were on average 25-fold more abundant compared to no cancer controls.

CONCLUSIONS

SEVEN revealed unique characteristics of HER2-enriched EVs in cultured cells and complex biological fluid. In combination with current clinical approaches, this method is well poised to support precise therapeutic decisions.

Exomap1 mouse: A transgenic model for in vivo studies of exosome biology

Exosomes are small extracellular vesicles (sEVs) of ~30-150 nm in diameter that are enriched in exosome marker proteins and play important roles in health and disease. To address large unanswered questions regarding exosome biology in vivo, we created the Exomap1 transgenic mouse, which in response to Cre recombinase expresses the most highly enriched exosomal marker protein known, human CD81, fused to mNeonGreen (HsCD81mNG), and prior to Cre expresses a mitochondrial red fluorescent protein. Validation of the exomap1 mouse with eight distinct Cre drivers demonstrated that HsCD81mNG was expressed only in response to Cre, that murine cells correctly localized HsCD81mNG to the plasma membrane, and that this led to the secretion of HsCD81mNG in EVs that had the size (~70-80 nm), topology, and composition of exosomes. Furthermore, cell type-specific activation of the exomap1 transgene allowed us to use quantitative single molecule localization microscopy to calculate the cell type-specific contribution to biofluid exosome populations. Specifically, we show that neurons contribute ~1% to plasma and cerebrospinal fluid exosome populations whereas hepatocytes contribute ~15% to plasma exosome populations, numbers that reflect the known vascular permeabilities of brain and liver. These observations validate the use of Exomap1 mouse models for in vivo studies of exosome biology.

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.

Syntenin and CD63 Promote Exosome Biogenesis from the Plasma Membrane by Blocking Cargo Endocytosis

Exosomes are small extracellular vesicles important in health and disease. Syntenin is thought to drive the biogenesis of CD63 exosomes by recruiting Alix and the ESCRT machinery to endosomes, initiating an endosome-mediated pathway of exosome biogenesis. Contrary to this model, we show here that syntenin drives the biogenesis of CD63 exosomes by blocking CD63 endocytosis, thereby allowing CD63 to accumulate at the plasma membrane, the primary site of exosome biogenesis. Consistent with these results, we find that inhibitors of endocytosis induce the exosomal secretion of CD63, that endocytosis inhibits the vesicular secretion of exosome cargo proteins, and that high-level expression of CD63 itself also inhibits endocytosis. These and other results indicate that exosomes bud primarily from the plasma membrane, that endocytosis inhibits their loading into exosomes, that syntenin and CD63 are expression-dependent regulators of exosome biogenesis, and that syntenin drives the biogenesis of CD63 exosomes even in Alix knockout cells.

Using quantitative single molecule localization microscopy to optimize multivalent HER2-targeting ligands

Introduction

The progression-free survival of patients with HER2-positive metastatic breast cancer is significantly extended by a combination of two monoclonal antibodies, trastuzumab and pertuzumab, which target independent epitopes of the extracellular domain of HER2. The improved efficacy of the combination over individual antibody therapies targeting HER2 is still being investigated, and several molecular mechanisms may be in play: the combination downregulates HER2, improves antibody-dependent cell mediated cytotoxicity, and/or affects the organization of surface-expressed antigens, which may attenuate downstream signaling.

Methods

By combining protein engineering and quantitative single molecule localization microscopy (qSMLM), here we both assessed and optimized clustering of HER2 in cultured breast cancer cells.

Results

We detected marked changes to the cellular membrane organization of HER2 when cells were treated with therapeutic antibodies. When we compared untreated samples to four treatment scenarios, we observed the following HER2 membrane features: (1) the monovalent Fab domain of trastuzumab did not significantly affect HER2 clustering; (2) individual therapy with either trastuzumab or (3) pertuzumab produced significantly higher levels of HER2 clustering; (4) a combination of trastuzumab plus pertuzumab produced the highest level of HER2 clustering. To further enhance this last effect, we created multivalent ligands using meditope technology. Treatment with a tetravalent meditope ligand combined with meditope-enabled trastuzumab resulted in pronounced HER2 clustering. Moreover, compared to pertuzumab plus trastuzumab, at early time points this meditope-based combination was more effective at inhibiting epidermal growth factor (EGF) dependent activation of several downstream protein kinases.

Discussion

Collectively, mAbs and multivalent ligands can efficiently alter the organization and activation of the HER2 receptors. We expect this approach could be used in the future to develop new therapeutics.

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.

Molecular Assessment of HER2 to Identify Signatures Associated with Therapy Response in HER2-Positive Breast Cancer

Trastuzumab, the prototype HER2-directed therapy, has markedly improved survival for women with HER2-positive breast cancers. However, only 40-60% of women with HER2-positive breast cancers achieve a complete pathological response to chemotherapy combined with HER2-directed therapy. The current diagnostic assays have poor positive-predictive accuracy in identifying therapy-responsive breast cancers. Here, we deployed quantitative single molecule localization microscopy to assess the molecular features of HER2 in a therapy-responsive setting. Using fluorescently labeled trastuzumab as a probe, we first compared the molecular features of HER2 in trastuzumab-sensitive (BT-474 and SK-BR-3) and trastuzumab-resistant (BT-474R and JIMT-1) cultured cell lines. Trastuzumab-sensitive cells had significantly higher detected HER2 densities and clustering. We then evaluated HER2 in pre-treatment core biopsies from women with breast cancer undergoing neoadjuvant therapy. A complete pathological response was associated with a high detected HER2 density and significant HER2 clustering. These results established the nano-organization of HER2 as a potential signature of therapy-responsive disease.

Current Knowledge on Exosome Biogenesis, Cargo-Sorting Mechanism and Therapeutic Implications

Extracellular vesicles (EVs) are nanoscale membrane vesicles released by donor cells that can be taken up by recipient cells. The study of EVs has the potential to identify unknown cellular and molecular mechanisms in intercellular communication and disease. Exosomes, with an average diameter of ≈100 nanometers, are a subset of EVs. Different molecular families have been shown to be involved in the formation of exosomes and subsequent secretion of exosomes, which largely leads to the complexity of the form, structure and function of exosomes. In addition, because of their low immunogenicity and ability to transfer a variety of bioactive components to recipient cells, exosomes are regarded as effective drug delivery systems. This review summarizes the known mechanisms of exosomes biogenesis, cargo loading, exosomes release and bioengineering, which is of great importance for further exploration into the clinical applications of EVs.

Molecular Imaging of HER2 in Patient Tissues with Touch Prep-Quantitative Single Molecule Localization Microscopy

Biomolecules can be investigated at the nanoscale with quantitative single molecule localization microscopy (qSMLM). This technique, which achieves single molecule sensitivity, can probe how membrane receptors are organized under both normal and pathological conditions. While a number of receptors have been extensively studied in cultured cells, technical challenges have largely impeded their robust quantification in tissue samples. To rigorously interrogate tissue samples, methodological advancements are needed in three areas: analytical preparation of the sample, proper characterization of fluorescent reporters, and rapid/unbiased data analysis. Towards these ends, we have combined qSMLM with a touch preparation technique (touch prep-qSMLM). In this new method, touch prep is first used to obtain monolayers of patient cells. Then, highly selective, fluorescently labeled probes are used to detect the receptors of interest on the plasma membranes of cells. Finally, quantitative algorithms are used to analyze the imaging data. Using this touch prep-qSMLM methodology, we interrogated the density and nano-organization of human epidermal growth factor receptor 2 (HER2) in fresh breast cancer tissues. Touch prep-qSMLM agreed well with current clinical methods. Importantly, touch prep-qSMLM can be easily extended to other pathological conditions and ultimately used in precision medicine.

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.

Characterizing Binding Interactions That Are Essential for Selective Transport through the Nuclear Pore Complex

Specific macromolecules are rapidly transported across the nuclear envelope via the nuclear pore complex (NPC). The selective transport process is facilitated when nuclear transport receptors (NTRs) weakly and transiently bind to intrinsically disordered constituents of the NPC, FG Nups. These two types of proteins help maintain the selective NPC barrier. To interrogate their binding interactions in vitro, we deployed an NPC barrier mimic. We created the stationary phase by covalently attaching fragments of a yeast FG Nup called Nsp1 to glass coverslips. We used a tunable mobile phase containing NTR, nuclear transport factor 2 (NTF2). In the stationary phase, three main factors affected binding: the number of FG repeats, the charge of fragments, and the fragment density. We also identified three main factors affecting binding in the mobile phase: the avidity of the NTF2 variant for Nsp1, the presence of nonspecific proteins, and the presence of additional NTRs. We used both experimentally determined binding parameters and molecular dynamics simulations of Nsp1FG fragments to create an agent-based model. The results suggest that NTF2 binding is negatively cooperative and dependent on the density of Nsp1FG molecules. Our results demonstrate the strengths of combining experimental and physical modeling approaches to study NPC-mediated transport.

Challenges facing quantitative large-scale optical super-resolution, and some simple solutions

Optical super-resolution microscopy (SRM) has enabled biologists to visualize cellular structures with near-molecular resolution, giving unprecedented access to details about the amounts, sizes, and spatial distributions of macromolecules in the cell. Precisely quantifying these molecular details requires large datasets of high-quality, reproducible SRM images. In this review, we discuss the unique set of challenges facing quantitative SRM, giving particular attention to the shortcomings of conventional specimen preparation techniques and the necessity for optimal labeling of molecular targets. We further discuss the obstacles to scaling SRM methods, such as lengthy image acquisition and complex SRM data analysis. For each of these challenges, we review the recent advances in the field that circumvent these pitfalls and provide practical advice to biologists for optimizing SRM experiments.

Spatiotemporal strategies to identify aggressive biology in precancerous breast biopsies

Over 90% of breast cancer is cured; yet there remain highly aggressive breast cancers that develop rapidly and are extremely difficult to treat, much less prevent. Breast cancers that rapidly develop between breast image screening are called "interval cancers." The efforts of our team focus on identifying multiscale integrated strategies to identify biologically aggressive precancerous breast lesions. Our goal is to identify spatiotemporal changes that occur prior to development of interval breast cancers. To accomplish this requires integration of new technology. Our team has the ability to perform single cell in situ transcriptional profiling, noncontrast biological imaging, mathematical analysis, and nanoscale evaluation of receptor organization and signaling. These technological innovations allow us to start to identify multidimensional spatial and temporal relationships that drive the transition from biologically aggressive precancer to biologically aggressive interval breast cancer. This article is categorized under: Cancer > Computational Models Cancer > Molecular and Cellular Physiology Cancer > Genetics/Genomics/Epigenetics.

Exosomes from adipose-derived stem cells and application to skin wound healing

Skin wound healing is an intractable problem that represents an urgent clinical need. To solve this problem, a large number of studies have focused on the use of exosomes (EXOs) derived from adipose‐derived stem cells (ADSCs). This review describes the mechanisms whereby ADSCs‐EXOs regulate wound healing and their clinical application. In the wound, ADSCs‐EXOs modulate immune responses and inflammation. They also promote angiogenesis, accelerate proliferation and re‐epithelization of skin cells, and regulate collagen remodelling which inhibits scar hyperplasia. Compared with ADSCs therapeutics, ADSCs‐EXOs have highly stability and are easily stored. Additionally, they are not rejected by the immune system and have a homing effect and their dosage can be easily controlled. ADSCs‐EXOs can improve fat grafting and promote wound healing in patients with diabetes mellitus. They can also act as a carrier and combined scaffold for treatment, leading to scarless cutaneous repair. Overall, ADSCs‐EXOs have the potential to be used in the clinic to promote wound healing.

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.

Exosomes

Exosomes are small, single-membrane, secreted organelles of ∼30 to ∼200 nm in diameter that have the same topology as the cell and are enriched in selected proteins, lipids, nucleic acids, and glycoconjugates. Exosomes contain an array of membrane-associated, high-order oligomeric protein complexes, display pronounced molecular heterogeneity, and are created by budding at both plasma and endosome membranes. Exosome biogenesis is a mechanism of protein quality control, and once released, exosomes have activities as diverse as remodeling the extracellular matrix and transmitting signals and molecules to other cells. This pathway of intercellular vesicle traffic plays important roles in many aspects of human health and disease, including development, immunity, tissue homeostasis, cancer, and neurodegenerative diseases. In addition, viruses co-opt exosome biogenesis pathways both for assembling infectious particles and for establishing host permissiveness. On the basis of these and other properties, exosomes are being developed as therapeutic agents in multiple disease models.

A Review of Super-Resolution Single-Molecule Localization Microscopy Cluster Analysis and Quantification Methods

Single-molecule localization microscopy (SMLM) is a relatively new imaging modality, winning the 2014 Nobel Prize in Chemistry, and considered as one of the key super-resolution techniques. SMLM resolution goes beyond the diffraction limit of light microscopy and achieves resolution on the order of 10-20 nm. SMLM thus enables imaging single molecules and study of the low-level molecular interactions at the subcellular level. In contrast to standard microscopy imaging that produces 2D pixel or 3D voxel grid data, SMLM generates big data of 2D or 3D point clouds with millions of localizations and associated uncertainties. This unprecedented breakthrough in imaging helps researchers employ SMLM in many fields within biology and medicine, such as studying cancerous cells and cell-mediated immunity and accelerating drug discovery. However, SMLM data quantification and interpretation methods have yet to keep pace with the rapid advancement of SMLM imaging. Researchers have been actively exploring new computational methods for SMLM data analysis to extract biosignatures of various biological structures and functions. In this survey, we describe the state-of-the-art clustering methods adopted to analyze and quantify SMLM data and examine the capabilities and shortcomings of the surveyed methods. We classify the methods according to (1) the biological application (i.e., the imaged molecules/structures), (2) the data acquisition (such as imaging modality, dimension, resolution, and number of localizations), and (3) the analysis details (2D versus 3D, field of view versus region of interest, use of machine-learning and multi-scale analysis, biosignature extraction, etc.). We observe that the majority of methods that are based on second-order statistics are sensitive to noise and imaging artifacts, have not been applied to 3D data, do not leverage machine-learning formulations, and are not scalable for big-data analysis. Finally, we summarize state-of-the-art methodology, discuss some key open challenges, and identify future opportunities for better modeling and design of an integrated computational pipeline to address the key challenges.

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.

Single molecule characterization of individual extracellular vesicles from pancreatic cancer

Biofluid-accessible extracellular vesicles (EVs) may represent a new means to improve the sensitivity and specificity of detecting disease. However, current methods to isolate EVs encounter challenges when they are used to select specific populations. Moreover, it has been difficult to comprehensively characterize heterogeneous EV populations at the single vesicle level. Here, we robustly assessed heterogeneous EV populations from cultured cell lines via nanoparticle tracking analysis, proteomics, transcriptomics, transmission electron microscopy, and quantitative single molecule localization microscopy (qSMLM). Using qSMLM, we quantified the size and biomarker content of individual EVs. We applied qSMLM to patient plasma samples and identified a pancreatic cancer-enriched EV population. Our goal is to advance single molecule characterization of EVs for early disease detection.

Abbreviations: EV: Extracellular Vesicle; qSMLM: quantitative Single Molecule Localization Microscopy; PDAC: Pancreatic Ductal Adenocarcinoma; EGFR: epidermal growth factor receptor 1; CA19-9: carbohydrate antigen 19-9; SEC: size exclusion chromatography; WGA: wheat germ agglutinin; AF647: Alexa Fluor 647; Ab: antibody; HPDEC: Healthy Pancreatic Ductal Epithelial Cell; TEM: Transmission Electron Microscopy.

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.

Ethanol and Naltrexone Have Distinct Effects on the Lateral Nano-organization of Mu and Kappa Opioid Receptors in the Plasma Membrane

The complex spatiotemporal organization of proteins and lipids in the plasma membrane is an important determinant of receptor function. Certain substances, such as ethanol, can penetrate into the hydrophobic regions of the plasma membrane. By altering protein-lipid and protein-protein interactions, these substances can modify the dynamic lateral organization and the function of plasma membrane receptors. To assess changes in plasma membrane receptor organization, we used photoactivated localization microscopy (PALM). This single molecule localization microscopy technique was employed to quantitatively characterize the effects of pharmacologically relevant concentrations of ethanol and naltrexone (an opioid receptor antagonist and medication used to treat alcohol use disorders) on the lateral nano-organization of mu and kappa opioid receptors (MOR and KOR, respectively). Ethanol affected the lateral organization of MOR and KOR similarly: It reduced the size and occupancy of opioid receptor nanodomains and increased the fraction of opioid receptors residing outside of nanodomains. In contrast, naltrexone affected MOR and KOR lateral organization differently. It significantly increased KOR surface density, nanodomain size, and the occupancy of KOR nanodomains. However, naltrexone marginally affected these parameters for MOR. Pretreatment with naltrexone largely protected against ethanol-induced changes in MOR and KOR lateral organization. Based on these data, we propose a putative mechanism of naltrexone action that operates in addition to its canonical antagonistic effect on MOR- and KOR-mediated signaling.