Ångström-resolution fluorescence microscopy.

Fluorescence microscopy, with its molecular specificity, is one of the major characterization methods used in the life sciences to understand complex biological systems. Super-resolution approaches1-6 can achieve resolution in cells in the range of 15 to 20 nm, but interactions between individual biomolecules occur at length scales below 10 nm and characterization of intramolecular structure requires Ångström resolution. State-of-the-art super-resolution implementations7-14 have demonstrated spatial resolutions down to 5 nm and localization precisions of 1 nm under certain in vitro conditions. However, such resolutions do not directly translate to experiments in cells, and Ångström resolution has not been demonstrated to date. Here we introdue a DNA-barcoding method, resolution enhancement by sequential imaging (RESI), that improves the resolution of fluorescence microscopy down to the Ångström scale using off-the-shelf fluorescence microscopy hardware and reagents. By sequentially imaging sparse target subsets at moderate spatial resolutions of >15 nm, we demonstrate that single-protein resolution can be achieved for biomolecules in whole intact cells. Furthermore, we experimentally resolve the DNA backbone distance of single bases in DNA origami with Ångström resolution. We use our method in a proof-of-principle demonstration to map the molecular arrangement of the immunotherapy target CD20 in situ in untreated and drug-treated cells, which opens possibilities for assessing the molecular mechanisms of targeted immunotherapy. These observations demonstrate that, by enabling intramolecular imaging under ambient conditions in whole intact cells, RESI closes the gap between super-resolution microscopy and structural biology studies and thus delivers information key to understanding complex biological systems.

Quality assessment in light microscopy for routine use through simple tools and robust metrics.

Although there is a need to demonstrate reproducibility in light microscopy acquisitions, the lack of standardized guidelines monitoring microscope health status over time has so far impaired the widespread use of quality control (QC) measurements. As scientists from 10 imaging core facilities who encounter various types of projects, we provide affordable hardware and open source software tools, rigorous protocols, and define reference values to assess QC metrics for the most common fluorescence light microscopy modalities. Seven protocols specify metrics on the microscope resolution, field illumination flatness, chromatic aberrations, illumination power stability, stage drift, positioning repeatability, and spatial-temporal noise of camera sensors. We designed the MetroloJ_QC ImageJ/Fiji Java plugin to incorporate the metrics and automate analysis. Measurements allow us to propose an extensive characterization of the QC procedures that can be used by any seasoned microscope user, from research biologists with a specialized interest in fluorescence light microscopy through to core facility staff, to ensure reproducible and quantifiable microscopy results.

Best practices and tools for reporting reproducible fluorescence microscopy methods.

Although fluorescence microscopy is ubiquitous in biomedical research, microscopy methods reporting is inconsistent and perhaps undervalued. We emphasize the importance of appropriate microscopy methods reporting and seek to educate researchers about how microscopy metadata impact data interpretation. We provide comprehensive guidelines and resources to enable accurate reporting for the most common fluorescence light microscopy modalities. We aim to improve microscopy reporting, thus improving the quality, rigor and reproducibility of image-based science.

Expectation maximization based framework for joint localization and parameter estimation in single particle tracking from segmented images.

Single Particle Tracking (SPT) is a well known class of tools for studying the dynamics of biological macromolecules moving inside living cells. In this paper, we focus on the problem of localization and parameter estimation given a sequence of segmented images. In the standard paradigm, the location of the emitter inside each frame of a sequence of camera images is estimated using, for example, Gaussian fitting (GF), and these locations are linked to provide an estimate of the trajectory. Trajectories are then analyzed by using Mean Square Displacement (MSD) or Maximum Likelihood Estimation (MLE) techniques to determine motion parameters such as diffusion coefficients. However, the problems of localization and parameter estimation are clearly coupled. Motivated by this, we have created an Expectation Maximization (EM) based framework for simultaneous localization and parameter estimation. We demonstrate this framework through two representative methods, namely, Sequential Monte Carlo combined with Expectation Maximization (SMC-EM) and Unscented Kalman Filter combined with Expectation Maximization (U-EM). Using diffusion in two-dimensions as a prototypical example, we conduct quantitative investigations on localization and parameter estimation performance across a wide range of signal to background ratios and diffusion coefficients and compare our methods to the standard techniques based on GF-MSD/MLE. To demonstrate the flexibility of the EM based framework, we do comparisons using two different camera models, an ideal camera with Poisson distributed shot noise but no readout noise, and a camera with both shot noise and the pixel-dependent readout noise that is common to scientific complementary metal-oxide semiconductor (sCMOS) camera. Our results indicate our EM based methods outperform the standard techniques, especially at low signal levels. While U-EM and SMC-EM have similar accuracy, U-EM is significantly more computationally efficient, though the use of the Unscented Kalman Filter limits U-EM to lower diffusion rates.

Practical Aspects of Super-Resolution Imaging and Segmentation of Macromolecular Complexes by dSTORM.

Super-resolution fluorescence microscopy allows imaging macromolecular complexes down to the nanoscopic scale and thus is a great tool to combine and integrate cellular imaging in the native cellular environment with structural analysis by X-ray crystallography or high-resolution cryo electron microscopy or tomography. Here we describe practical aspects of SMLM imaging by dSTORM, from the initial sample preparation using mounting media, antibodies and fluorescent markers, the experimental setup for data acquisition including multi-color colocalization and 3D data acquisition, and finally tips and clues on advanced data processing that includes image reconstruction and data segmentation using 2D or 3D clustering methods. This approach opens the path toward multi-resolution integration in cellular structural biology.

Deep learning extended depth-of-field microscope for fast and slide-free histology.

Microscopic evaluation of resected tissue plays a central role in the surgical management of cancer. Because optical microscopes have a limited depth-of-field (DOF), resected tissue is either frozen or preserved with chemical fixatives, sliced into thin sections placed on microscope slides, stained, and imaged to determine whether surgical margins are free of tumor cells-a costly and time- and labor-intensive procedure. Here, we introduce a deep-learning extended DOF (DeepDOF) microscope to quickly image large areas of freshly resected tissue to provide histologic-quality images of surgical margins without physical sectioning. The DeepDOF microscope consists of a conventional fluorescence microscope with the simple addition of an inexpensive (less than $10) phase mask inserted in the pupil plane to encode the light field and enhance the depth-invariance of the point-spread function. When used with a jointly optimized image-reconstruction algorithm, diffraction-limited optical performance to resolve subcellular features can be maintained while significantly extending the DOF (200 µm). Data from resected oral surgical specimens show that the DeepDOF microscope can consistently visualize nuclear morphology and other important diagnostic features across highly irregular resected tissue surfaces without serial refocusing. With the capability to quickly scan intact samples with subcellular detail, the DeepDOF microscope can improve tissue sampling during intraoperative tumor-margin assessment, while offering an affordable tool to provide histological information from resected tissue specimens in resource-limited settings.

Pyrene Excimer-Based Fluorescent Labeling of Cysteines Brought into Close Proximity by Protein Dynamics: ASEM-Induced Thiol-Ene Click Reaction for High Spatial Resolution CLEM.

Fluorescence microscopy (FM) has revealed vital molecular mechanisms of life. Mainly, molecules labeled by fluorescent probes are imaged. However, the diversity of labeling probes and their functions remain limited. We synthesized a pyrene-based fluorescent probe targeting SH groups, which are important for protein folding and oxidative stress sensing in cells. The labeling achieved employs thiol-ene click reactions between the probes and SH groups and is triggered by irradiation by UV light or an electron beam. When two tagged pyrene groups were close enough to be excited as a dimer (excimer), they showed red-shifted fluorescence; theoretically, the proximity of two SH residues within ~30 Å can thus be monitored. Moreover, correlative light/electron microscopy (CLEM) was achieved using our atmospheric scanning electron microscope (ASEM); radicals formed in liquid by the electron beam caused the thiol-ene click reactions, and excimer fluorescence of the labeled proteins in cells and tissues was visualized by FM. Since the fluorescent labeling is induced by a narrow electron beam, high spatial resolution labeling is expected. The method can be widely applied to biological fields, for example, to study protein dynamics with or without cysteine mutagenesis, and to beam-induced micro-fabrication and the precise post-modification of materials.

How good are my data? Reference standards in superresolution microscopy.

Superresolution microscopy is becoming increasingly widespread in biological labs. While it holds enormous potential for biological discovery, it is a complex imaging technique that requires thorough optimization of various experimental parameters to yield data of the highest quality. Unfortunately, it remains challenging even for seasoned users to judge from the acquired images alone whether their superresolution microscopy pipeline is performing at its optimum, or if the image quality could be improved. Here, we describe how superresolution microscopists can objectively characterize their imaging pipeline using suitable reference standards, which are stereotypic so that the same structure can be imaged everywhere, every time, on every microscope. Quantitative analysis of reference standard images helps characterizing the performance of one's own microscopes over time, allows objective benchmarking of newly developed microscopy and labeling techniques, and finally increases comparability of superresolution microscopy data between labs.

LIVE-PAINT allows super-resolution microscopy inside living cells using reversible peptide-protein interactions.

We present LIVE-PAINT, a new approach to super-resolution fluorescent imaging inside live cells. In LIVE-PAINT only a short peptide sequence is fused to the protein being studied, unlike conventional super-resolution methods, which rely on directly fusing the biomolecule of interest to a large fluorescent protein, organic fluorophore, or oligonucleotide. LIVE-PAINT works by observing the blinking of localized fluorescence as this peptide is reversibly bound by a protein that is fused to a fluorescent protein. We have demonstrated the effectiveness of LIVE-PAINT by imaging a number of different proteins inside live S. cerevisiae. Not only is LIVE-PAINT widely applicable, easily implemented, and the modifications minimally perturbing, but we also anticipate it will extend data acquisition times compared to those previously possible with methods that involve direct fusion to a fluorescent protein.

Topical dual-probe staining using quantum dot-labeled antibodies for identifying tumor biomarkers in fresh specimens.

PURPOSE: Rapid, intra-operative identification of tumor tissue in the margins of excised specimens has become an important focus in the pursuit of reducing re-excision rates, especially for breast conserving surgery. Dual-probe difference specimen imaging (DDSI) is an emerging approach that uses the difference in uptake/clearance kinetics between a pair of fluorescently-labeled stains, one targeted to a biomarker-of-interest and the other an untargeted isotype, to reveal receptor-specific images of the specimen. Previous studies using antibodies labeled with either enhanced Raman particles or organic fluorophores have shown promising tumor vs. normal diagnostic performance. Yet, the unique properties of quantum dot-labeled antibody complexes (QDACs), which provide spectrally-distinct fluorescence emission from a common excitation source, make them ideal candidates for this application. Herein, we evaluate the diagnostic performance of QDAC-based DDSI in excised xenografts. PROCEDURES: Excised fresh specimens of normal tissue and human tumor xenografts with elevated expression of HER2 were stained with a HER2-targeted QDAC and an untargeted QDAC isotype. Stained specimens were imaged on a custom hyperspectral imaging system capable of spectrally separating the quantum dot signatures, and images processed using the DDSI approach. The diagnostic performance of this technique under different incubation temperatures and probe concentrations was evaluated using receiver-operator characteristic analysis. RESULTS: HER2-targeted QDAC-DDSI was able to distinguish HER2(+) tumors from normal tissue with reasonably high diagnostic performance; however, this performance was sensitive to temperature during the staining procedure. Area under the curve values were 0.61 when staining at room temperature but increased to over 0.81 when staining at 37 °C. Diagnostic performance was not affected by increasing stain concentration. CONCLUSIONS: This study is the first to report dual-probe difference imaging of specimens using QDACs and hyperspectral imaging. Our results show promising diagnostic performance under certain conditions, and compel further optimization and evaluation of this intra-operative margin assessment technique.

Correcting Artifacts in Single Molecule Localization Microscopy Analysis Arising from Pixel Quantum Efficiency Differences in sCMOS Cameras.

Optimal analysis of single molecule localization microscopy (SMLM) data acquired with a scientific Complementary Metal-Oxide-Semiconductor (sCMOS) camera relies on statistical compensation for its pixel-dependent gain, offset and readout noise. In this work we show that it is also necessary to compensate for differences in the relative quantum efficiency (RQE) of each pixel. We found differences in RQE on the order of 4% in our tested sCMOS sensors. These differences were large enough to have a noticeable effect on analysis algorithm results, as seen both in simulations and biological imaging data. We discuss how the RQE differences manifest themselves in the analysis results and present the modifications to the Poisson maximum likelihood estimation (MLE) sCMOS analysis algorithm that are needed to correct for the RQE differences.

Simultaneous Polychromatic Immunofluorescent Staining of Tissue Sections and Consecutive Imaging of up to Seven Parameters by Standard Confocal Microscopy.

Confocal microscopy has been an important imaging tool for life scientists for over 20 years. Early techniques focused on indirect staining processes that involved staining with an unconjugated primary antibody, followed by incubation with a secondary fluorescent antibody that would reveal and amplify the signal of the primary antibody. With more and more directly conjugated fluorescent primary antibodies becoming commercially available, staining with multiple fluorescent primary antibodies is now more frequent. To date, staining with up to three primary antibodies and a nuclear dye is widely practiced. Here, we describe an important improvement to the standard polychromatic immunofluorescent staining protocol that allows the simultaneous detection of seven fluorescent parameters using a standard confocal laser scanning microscope with four laser lines and four photomultiplier tubes. By incorporating recently available tandem dyes that emit in the blue and violet regions of the visible light spectrum (Brilliant Blue and Brilliant Violet), we were able to differentiate several additional fluorochromes simultaneously. Due to the added complexity of 7-color immunofluorescent imaging, we developed a clear methodology to optimize antibody concentrations and simple guidelines on how to identify and correct non-specific signals. These are detailed in the following protocol. © 2019 by John Wiley & Sons, Inc. Basic Protocol: 7-Color immunofluorescent staining protocol using directly conjugated antibodies Support Protocol 1: Antibody titration protocol Support Protocol 2: Spillover optimization protocol.

Nuclear pores as versatile reference standards for quantitative superresolution microscopy.

Quantitative fluorescence and superresolution microscopy are often limited by insufficient data quality or artifacts. In this context, it is essential to have biologically relevant control samples to benchmark and optimize the quality of microscopes, labels and imaging conditions. Here, we exploit the stereotypic arrangement of proteins in the nuclear pore complex as in situ reference structures to characterize the performance of a variety of microscopy modalities. We created four genome edited cell lines in which we endogenously labeled the nucleoporin Nup96 with mEGFP, SNAP-tag, HaloTag or the photoconvertible fluorescent protein mMaple. We demonstrate their use (1) as three-dimensional resolution standards for calibration and quality control, (2) to quantify absolute labeling efficiencies and (3) as precise reference standards for molecular counting. These cell lines will enable the broader community to assess the quality of their microscopes and labels, and to perform quantitative, absolute measurements.

Evaluation of the automated indirect immunofluorescence test for anti-dsDNA antibodies.

BACKGROUND: Anti-dsDNA antibody is a specific antibody in systemic lupus erythematosus (SLE). Indirect immunofluorescence test (IIFT) is a highly specific method in detecting anti-dsDNA antibody. The application of automated system has gained better consistency than manual operation. This study detected anti-dsDNA antibodies using EUROPattern Computer-aided immunofluorescence microscopy (EPA), and evaluated the performance of the automated system. METHODS: The sera of 96 patients with suspected SLE and 102 control patients were examined using IIFT. The consistency between the EPA and manual reading was analyzed. RESULTS: Analysis of 198 samples showed that the overall consistency of the negative/positive results between the EPA and manual reading was 94.95%. Based on the manual reading results, the sensitivity and specificity of EPA were 95.70% and 94.29%, respectively. The analysis of 57 samples with non-specific fluorescence showed that the overall consistency of the negative/positive results was 96.49%. The analysis of the antibody titer of 89 positive samples showed that the consistency between the EPA and manual reading was 97.75%. CONCLUSION: EPA was consistent with the manual reading with regard to qualitative reading and antibody titer. With low-exposure function, EPA could read samples with non-specific fluorescence. EPA was superior to manual reading in automation and standardization.

Quantitative accounting of dye leakage and photobleaching in single lipid vesicle measurements: Implications for biomacromolecular interaction analysis.

Highly parallel measurements on single, tethered lipid vesicles enable real-time monitoring of dynamic membrane interactions of relevance to medical, pharmaceutical, and biotechnological applications. Monitoring the time-dependent release of entrapped fluorescent dyes is a popular measurement approach, although it is often challenging to accurately extract quantitative biochemical parameters. Key issues include dye leakage and imaging-related photobleaching, and corrective measures are needed. Herein, we present an extended analytical framework to collect and interpret time-lapsed fluorescence microscopy imaging data, and demonstrate its utility for tracking membrane-peptide interactions. Our approach is focused on improving platform design and data analysis. First, we identified suitable membrane compositions to minimize dye leakage while enhancing the biomimetic character of lipid vesicles. Second, a data normalization procedure was developed to correct for experimental artifacts, namely dye leakage and photobleaching, and hence improve measurement accuracy. This analytical procedure was applied to experimentally determine the rate of peptide-induced pore formation in single lipid vesicles, and there was up to a nearly three-fold decrease in the measured rate, as compared to uncorrected data. Taken together, the results present a broadly applicable analytical framework to account for experimental artifacts and improve measurement accuracy in highly parallel, single lipid vesicle arrays.

Rapid fluorescent focus inhibition test optimization and validation: Improved detection of neutralizing antibodies to rabies virus.

The rabies rapid fluorescent focus inhibition test (RFFIT) is the most widely used cell-based assay for detecting and quantitating rabies virus neutralizing antibodies (RVNA) in human serum. However, it is a complex, labor intensive, and somewhat subjective manual assay, the performance of which may be affected by a number of factors including the quality of cells and virus, variability of assay reagents and the skill and expertise of analysts. This study sought to identify and evaluate conditions that may impact RFFIT performance and RVNA detection by evaluating assay parameters including: different serial dilution scheme of serum samples in a 96-well microplate using semi-automated pipetting systems, the range of dose of challenge virus standard (CVS-11) strain of rabies virus, the effect of complement (C'), the effect of cell seeding density and passage number, the effect of diethylaminoethyl (DEAE) dextran concentration on virus infectivity, and the assay incubation period prior to immunostaining. In addition the evaluation of counting fluorescent foci using a microscope versus using scanned images from a cell imaging reader was performed in an effort to ease the reading of slides and have permanent records of the raw data. The results from optimization of each parameter are presented along with subsequent assay validation in accordance with the International Conference on Harmonization (ICH) guidelines. The improved and optimized RFFIT accuracy, linearity and sensitivity was demonstrated by testing World Health Organization (WHO)-1 and WHO-2 Standard Rabies Immune Globulins (SRIGs) and complete assay development and validation was performed in compliance with Good Clinical Laboratory Practice (GCLP) guidelines.

Validating the sensitivity of inhomogeneous magnetization transfer (ihMT) MRI to myelin with fluorescence microscopy.

Inhomogeneous Magnetization Transfer (ihMT) is a development from the MT MRI technique. IhMT can be considered as a dipolar order relaxation time (T1D) weighted imaging modality whose signal has shown an enhanced selectivity for myelin-rich structures. However, a formal validation of the ihMT sensitivity relative to a gold standard myelin density measurement has not yet been reported. To address this need, we compared ihMT MRI with green fluorescence protein (GFP) microscopy, in a study performed on genetically-modified plp-GFP mice, considered as a reference technique for myelin-content assessment. Various ihMT protocols consisting of variable T1D-filtering and radiofrequency power temporal distributions, were used for comparison with fluorescence microscopy. Strong and significant linear relationships (r2 (0.87-0.96), p < 0.0001) were found between GFP and ihMT ratio signals across brain regions for all tested protocol variants. Conventional MT ratios showed weaker correlations (r2 (0.24-0.78), p ≤ 0.02) and a much larger signal fraction unrelated to myelin, hence corresponding to a much lower specificity for myelin. T1D-filtering reduced the ihMT signal fraction not attributed to myelin by almost twofold relative to zero filtering suggesting that at least half of the unrelated signal has a substantially shorter T1D than myelin. Overall, these results strongly support the sensitivity of ihMT to myelin content.

Rapid Quantification of Protein Particles in High-Concentration Antibody Formulations.

Current technologies for monitoring the subvisible particles that may be generated during fill-finish operations for protein formulations are cumbersome. Measurement times are generally too long for real-time analysis, and the high protein concentrations that are characteristic of many antibody products interfere with common optical techniques for particle analysis. To rapidly monitor protein particle levels in high-concentration protein solutions, we developed a fluorescence-based method that uses extrinsic fluorescent dyes such as 4,4'-dianilino-1,1'-binaphthyl-5,5'-disulfonic acid that are sensitive to the presence of aggregated protein. To test the method, antibody formulations containing various concentrations of protein particles were generated by application of various mechanical and freeze-thaw stresses. After addition of fluorescent dyes, fluorescence intensities were measured and compared to fluorescence intensities in particle-free formulations. The differences in fluorescence intensities were linearly proportional to protein particle levels, which for calibration purposes were measured offline by fluid imaging microscopy and protein assays. Protein particle levels could be measured without requiring sample dilution, even in high-concentration (e.g., 40 mg/mL) antibody formulations.

Resolution limit of image analysis algorithms.

The resolution of an imaging system is a key property that, despite many advances in optical imaging methods, remains difficult to define and apply. Rayleigh's and Abbe's resolution criteria were developed for observations with the human eye. However, modern imaging data is typically acquired on highly sensitive cameras and often requires complex image processing algorithms to analyze. Currently, no approaches are available for evaluating the resolving capability of such image processing algorithms that are now central to the analysis of imaging data, particularly location-based imaging data. Using methods of spatial statistics, we develop a novel algorithmic resolution limit to evaluate the resolving capabilities of location-based image processing algorithms. We show how insufficient algorithmic resolution can impact the outcome of location-based image analysis and present an approach to account for algorithmic resolution in the analysis of spatial location patterns.

Imaging Flies by Fluorescence Microscopy: Principles, Technologies, and Applications.

The development of fluorescent labels and powerful imaging technologies in the last two decades has revolutionized the field of fluorescence microscopy, which is now widely used in diverse scientific fields from biology to biomedical and materials science. Fluorescence microscopy has also become a standard technique in research laboratories working on Drosophila melanogaster as a model organism. Here, we review the principles of fluorescence microscopy technologies from wide-field to Super-resolution microscopy and its application in the Drosophila research field.