Quantifying and optimizing single-molecule switching nanoscopy at high speeds

StayGold variants for molecular fusion and membrane-targeting applications

Although StayGold is a bright and highly photostable fluorescent protein, its propensity for obligate dimer formation may hinder applications in molecular fusion and membrane targeting. To attain monovalent as well as bright and photostable labeling, we engineered tandem dimers of StayGold to promote dispersibility. On the basis of the crystal structure of this fluorescent protein, we disrupted the dimerization to generate a monomeric variant that offers improved photostability and brightness compared to StayGold. We applied the new monovalent StayGold tools to live-cell imaging experiments using spinning-disk laser-scanning confocal microscopy or structured illumination microscopy. We achieved cell-wide, high-spatiotemporal resolution and sustained imaging of dynamic subcellular events, including the targeting of endogenous condensin I to mitotic chromosomes, the movement of the Golgi apparatus and its membranous derivatives along microtubule networks, the distribution of cortical filamentous actin and the remolding of cristae membranes within mobile mitochondria.

openFrame: A modular, sustainable, open microscopy platform with single-shot, dual-axis optical autofocus module providing high precision and long range of operation

'openFrame' is a modular, low-cost, open-hardware microscopy platform that can be configured or adapted to most light microscopy techniques and is easily upgradeable or expandable to multiple modalities. The ability to freely mix and interchange both open-source and proprietary hardware components or software enables low-cost, yet research-grade instruments to be assembled and maintained. It also enables rapid prototyping of advanced or novel microscope systems. For long-term time-lapse image data acquisition, slide-scanning or high content analysis, we have developed a novel optical autofocus incorporating orthogonal cylindrical optics to provide robust single-shot closed-loop focus lock, which we have demonstrated to accommodate defocus up to ±37 μm with <200 nm accuracy, and a two-step autofocus mode which we have shown can operate with defocus up to ±68 μm. We have used this to implement automated single molecule localisation microscopy (SMLM) in a relatively low-cost openFrame-based instrument using multimode diode lasers for excitation and cooled CMOS cameras.

An integrated platform for high-throughput nanoscopy

Single-molecule localization microscopy enables three-dimensional fluorescence imaging at tens-of-nanometer resolution, but requires many camera frames to reconstruct a super-resolved image. This limits the typical throughput to tens of cells per day. While frame rates can now be increased by over an order of magnitude, the large data volumes become limiting in existing workflows. Here we present an integrated acquisition and analysis platform leveraging microscopy-specific data compression, distributed storage and distributed analysis to enable an acquisition and analysis throughput of 10,000 cells per day. The platform facilitates graphically reconfigurable analyses to be automatically initiated from the microscope during acquisition and remotely executed, and can even feed back and queue new acquisition tasks on the microscope. We demonstrate the utility of this framework by imaging hundreds of cells per well in multi-well sample formats. Our platform, implemented within the PYthon-Microscopy Environment (PYME), is easily configurable to control custom microscopes, and includes a plugin framework for user-defined extensions.

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

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

Fluorescence fluctuation-based super-resolution microscopy: Basic concepts for an easy start

Due to the wave nature of light, optical microscopy has a lower-bound lateral resolution limit of approximately half of the wavelength of visible light, that is, within the range of 200 to 350 nm. Fluorescence fluctuation-based super-resolution microscopy (FF-SRM) is a term used to encompass a collection of image analysis techniques that rely on the statistical processing of temporal variations of the fluorescence signal. FF-SRM aims to reduce the uncertainty of the location of fluorophores within an image, often improving spatial resolution by several tens of nanometers. FF-SRM is suitable for live-cell imaging due to its compatibility with most fluorescent probes and relatively simple instrumental and experimental requirements, which are mostly camera-based epifluorescence instruments. Each FF-SRM approach has strengths and weaknesses, which depend directly on the underlying statistical principles through which enhanced spatial resolution is achieved. In this review, the basic concepts and principles behind a range of FF-SRM methods published to date are described. Their operational parameters are explained and guidance for their selection is provided.

Super-Resolution Microscopy for Structural Cell Biology

Super-resolution microscopy techniques, and specifically single-molecule localization microscopy (SMLM), are approaching nanometer resolution inside cells and thus have great potential to complement structural biology techniques such as electron microscopy for structural cell biology. In this review, we introduce the different flavors of super-resolution microscopy, with a special emphasis on SMLM and MINFLUX (minimal photon flux). We summarize recent technical developments that pushed these localization-based techniques to structural scales and review the experimental conditions that are key to obtaining data of the highest quality. Furthermore, we give an overview of different analysis methods and highlight studies that used SMLM to gain structural insights into biologically relevant molecular machines. Ultimately, we give our perspective on what is needed to push the resolution of these techniques even further and to apply them to investigating dynamic structural rearrangements in living cells. Expected final online publication date for the Annual Review of Biophysics, Volume 51 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Resonant Electro-Optic Imaging for Microscopy at Nanosecond Resolution

We demonstrate an electro-optic wide-field method to enable fluorescence lifetime microscopy (FLIM) with high throughput and single-molecule sensitivity. Resonantly driven Pockels cells are used to efficiently gate images at 39 MHz, allowing fluorescence lifetime to be captured on standard camera sensors. Lifetime imaging of single molecules is enabled in wide field with exposure times of less than 100 ms. This capability allows combination of wide-field FLIM with single-molecule super-resolution localization microscopy. Fast single-molecule dynamics such as FRET and molecular binding events are captured from wide-field images without prior spatial knowledge. A lifetime sensitivity of 1.9 times the photon shot-noise limit is achieved, and high throughput is shown by acquiring wide-field FLIM images with millisecond exposure and >10⁸ photons per frame. Resonant electro-optic FLIM allows lifetime contrast in any wide-field microscopy method.

Estimating the dynamic range of quantitative single-molecule localization microscopy

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

Advancing biological super-resolution microscopy through deep learning: a brief review

Biological super-resolution microscopy is a new generation of imaging techniques that overcome the ~200 nm diffraction limit of conventional light microscopy in spatial resolution. By providing novel spatial or spatiotemporal information on biological processes at nanometer resolution with molecular specificity, it plays an increasingly important role in biomedical sciences. However, its technical constraints also require trade-offs to balance its spatial resolution, temporal resolution, and light exposure of samples. Recently, deep learning has achieved breakthrough performance in many image processing and computer vision tasks. It has also shown great promise in pushing the performance envelope of biological super-resolution microscopy. In this brief review, we survey recent advances in using deep learning to enhance the performance of biological super-resolution microscopy, focusing primarily on computational reconstruction of super-resolution images. Related key technical challenges are discussed. Despite the challenges, deep learning is expected to play an important role in the development of biological super-resolution microscopy. We conclude with an outlook into the future of this new research area.

Fast widefield scan provides tunable and uniform illumination optimizing super-resolution microscopy on large fields

Non-uniform illumination limits quantitative analyses of fluorescence imaging techniques. In particular, single molecule localization microscopy (SMLM) relies on high irradiances, but conventional Gaussian-shaped laser illumination restricts the usable field of view to around 40 µm × 40 µm. We present Adaptable Scanning for Tunable Excitation Regions (ASTER), a versatile illumination technique that generates uniform and adaptable illumination. ASTER is also highly compatible with optical sectioning techniques such as total internal reflection fluorescence (TIRF). For SMLM, ASTER delivers homogeneous blinking kinetics at reasonable laser power over fields-of-view up to 200 µm × 200 µm. We demonstrate that ASTER improves clustering analysis and nanoscopic size measurements by imaging nanorulers, microtubules and clathrin-coated pits in COS-7 cells, and β2-spectrin in neurons. ASTER's sharp and quantitative illumination paves the way for high-throughput quantification of biological structures and processes in classical and super-resolution fluorescence microscopies.

Extraction of rapid kinetics from smFRET measurements using integrative detectors

Hidden Markov models (HMMs) are used to learn single-molecule kinetics across a range of experimental techniques. By their construction, HMMs assume that single-molecule events occur on slower timescales than those of data acquisition. To move beyond that HMM limitation and allow for single-molecule events to occur on any timescale, we must treat single-molecule events in continuous time as they occur in nature. We propose a method to learn kinetic rates from single-molecule Förster resonance energy transfer (smFRET) data collected by integrative detectors, even if those rates exceed data acquisition rates. To achieve that, we exploit our recently proposed "hidden Markov jump process" (HMJP), with which we learn transition kinetics from parallel measurements in donor and acceptor channels. HMJPs generalize the HMM paradigm in two critical ways: (1) they deal with physical smFRET systems as they switch between conformational states in continuous time, and (2) they estimate transition rates between conformational states directly without having recourse to transition probabilities or assuming slow dynamics. Our continuous-time treatment learns the transition kinetics and photon emission rates for dynamic regimes that are inaccessible to HMMs, which treat system kinetics in discrete time. We validate our framework's robustness on simulated data and demonstrate its performance on experimental data from FRET-labeled Holliday junctions.

Blinking Statistics and Molecular Counting in direct Stochastic Reconstruction Microscopy (dSTORM)

MOTIVATION

Many recent advancements in single molecule localisation microscopy exploit the stochastic photo-switching of fluorophores to reveal complex cellular structures beyond the classical diffraction limit. However, this same stochasticity makes counting the number of molecules to high precision extremely challenging, preventing key insight into the cellular structures and processes under observation.

RESULTS

Modelling the photo-switching behaviour of a fluorophore as an unobserved continuous time Markov process transitioning between a single fluorescent and multiple dark states, and fully mitigating for missed blinks and false positives, we present a method for computing the exact probability distribution for the number of observed localisations from a single photo-switching fluorophore. This is then extended to provide the probability distribution for the number of localisations in a dSTORM experiment involving an arbitrary number of molecules. We demonstrate that when training data is available to estimate photoswitching rates, the unknown number of molecules can be accurately recovered from the posterior mode of the number of molecules given the number of localisations. Finally, we demonstrate the method on experimental data by quantifying the number of adapter protein Linker for Activation of T cells (LAT) on the cell surface of the T cell immunological synapse.

AVAILABILITY

Software available at https://github.com/lp1611/mol_count_dstorm.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Generalizing HMMs to Continuous Time for Fast Kinetics: Hidden Markov Jump Processes

The hidden Markov model (HMM) is a framework for time series analysis widely applied to single-molecule experiments. Although initially developed for applications outside the natural sciences, the HMM has traditionally been used to interpret signals generated by physical systems, such as single molecules, evolving in a discrete state space observed at discrete time levels dictated by the data acquisition rate. Within the HMM framework, transitions between states are modeled as occurring at the end of each data acquisition period and are described using transition probabilities. Yet, whereas measurements are often performed at discrete time levels in the natural sciences, physical systems evolve in continuous time according to transition rates. It then follows that the modeling assumptions underlying the HMM are justified if the transition rates of a physical process from state to state are small as compared to the data acquisition rate. In other words, HMMs apply to slow kinetics. The problem is, because the transition rates are unknown in principle, it is unclear, a priori, whether the HMM applies to a particular system. For this reason, we must generalize HMMs for physical systems, such as single molecules, because these switch between discrete states in "continuous time". We do so by exploiting recent mathematical tools developed in the context of inferring Markov jump processes and propose the hidden Markov jump process. We explicitly show in what limit the hidden Markov jump process reduces to the HMM. Resolving the discrete time discrepancy of the HMM has clear implications: we no longer need to assume that processes, such as molecular events, must occur on timescales slower than data acquisition and can learn transition rates even if these are on the same timescale or otherwise exceed data acquisition rates.

Accelerating 3D single-molecule localization microscopy using blind sparse inpainting

SIGNIFICANCE

Single-molecule localization-based super-resolution microscopy has enabled the imaging of microscopic objects beyond the diffraction limit. However, this technique is limited by the requirements of imaging an extremely large number of frames of biological samples to generate a super-resolution image, thus requiring a longer acquisition time. Additionally, the processing of such a large image sequence leads to longer data processing time. Therefore, accelerating image acquisition and processing in single-molecule localization microscopy (SMLM) has been of perennial interest.

AIM

To accelerate three-dimensional (3D) SMLM imaging by leveraging a computational approach without compromising the resolution.

APPROACH

We used blind sparse inpainting to reconstruct high-density 3D images from low-density ones. The low-density images are generated using much fewer frames than usually needed, thus requiring a shorter acquisition and processing time. Therefore, our technique will accelerate 3D SMLM without changing the existing standard SMLM hardware system and labeling protocol.

RESULTS

The performance of the blind sparse inpainting was evaluated on both simulation and experimental datasets. Superior reconstruction results of 3D SMLM images using up to 10-fold fewer frames in simulation and up to 50-fold fewer frames in experimental data were achieved.

CONCLUSIONS

We demonstrate the feasibility of fast 3D SMLM imaging leveraging a computational approach to reduce the number of acquired frames. We anticipate our technique will enable future real-time live-cell 3D imaging to investigate complex nanoscopic biological structures and their functions.

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

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

Single-molecule localization microscopy

Single-molecule localization microscopy (SMLM) describes a family of powerful imaging techniques that dramatically improve spatial resolution over standard, diffraction-limited microscopy techniques and can image biological structures at the molecular scale. In SMLM, individual fluorescent molecules are computationally localized from diffraction-limited image sequences and the localizations are used to generate a super-resolution image or a time course of super-resolution images, or to define molecular trajectories. In this Primer, we introduce the basic principles of SMLM techniques before describing the main experimental considerations when performing SMLM, including fluorescent labelling, sample preparation, hardware requirements and image acquisition in fixed and live cells. We then explain how low-resolution image sequences are computationally processed to reconstruct super-resolution images and/or extract quantitative information, and highlight a selection of biological discoveries enabled by SMLM and closely related methods. We discuss some of the main limitations and potential artefacts of SMLM, as well as ways to alleviate them. Finally, we present an outlook on advanced techniques and promising new developments in the fast-evolving field of SMLM. We hope that this Primer will be a useful reference for both newcomers and practitioners of SMLM.

Optimizing imaging speed and excitation intensity for single-molecule localization microscopy

High laser powers are common practice in single molecule localization microscopy (SMLM) to speed up data acquisition. Here, we systematically quantified how excitation intensity influences localization precision and labeling density, the two main factors determining data quality. We found a strong trade-off between imaging speed and quality and present optimized imaging protocols for high-throughput, multi-color and 3D SMLM with greatly improved resolution and effective labeling efficiency.

The cell biologist's guide to super-resolution microscopy

Fluorescence microscopy has become a ubiquitous method to observe the location of specific molecular components within cells. However, the resolution of light microscopy is limited by the laws of diffraction to a few hundred nanometers, blurring most cellular details. Over the last two decades, several techniques - grouped under the 'super-resolution microscopy' moniker - have been designed to bypass this limitation, revealing the cellular organization down to the nanoscale. The number and variety of these techniques have steadily increased, to the point that it has become difficult for cell biologists and seasoned microscopists alike to identify the specific technique best suited to their needs. Available techniques include image processing strategies that generate super-resolved images, optical imaging schemes that overcome the diffraction limit and sample manipulations that expand the size of the biological sample. In this Cell Science at a Glance article and the accompanying poster, we provide key pointers to help users navigate through the various super-resolution methods by briefly summarizing the principles behind each technique, highlighting both critical strengths and weaknesses, as well as providing example images.

Three-Dimensional Single-Molecule Localization Microscopy in Whole-Cell and Tissue Specimens

Super-resolution microscopy techniques are versatile and powerful tools for visualizing organelle structures, interactions, and protein functions in biomedical research. However, whole-cell and tissue specimens challenge the achievable resolution and depth of nanoscopy methods. We focus on three-dimensional single-molecule localization microscopy and review some of the major roadblocks and developing solutions to resolving thick volumes of cells and tissues at the nanoscale in three dimensions. These challenges include background fluorescence, system- and sample-induced aberrations, and information carried by photons, as well as drift correction, volume reconstruction, and photobleaching mitigation. We also highlight examples of innovations that have demonstrated significant breakthroughs in addressing the abovementioned challenges together with their core concepts as well as their trade-offs.

Optimizing the performance of multiline-scanning confocal microscopy

Line-scanning confocal microscopy provides high imaging speed and moderate optical sectioning strength, which makes it a useful tool for imaging various biospecimens ranging from living cells to fixed tissues. Conventional line-scanning systems have only used a single excitation line and slit, and thus have not fully exploited benefits of parallelization. Here we investigate the optical performance of multi-line scanning confocal microscopy (mLS) by employing a digital micro-mirror that provides programmable patterns of the illumination beam and the detection slit. Through experimental results and optical simulations, we assess the depth discrimination of mLS under different optical parameters and compare it with multi-point systems such as scanning disk confocal microscopy (SDCM). Under the same illumination duty cycle, we find that mLS has better optical sectioning than SDCM at a high degree of parallelization. The optimized mLS provides a low photobleaching rate and video-rate imaging while its optical sectioning is similar to single line-scanning confocal microscopy.

Cost-efficient open source laser engine for microscopy

Scientific-grade lasers are costly components of modern microscopes. For high-power applications, such as single-molecule localization microscopy, their price can become prohibitive. Here, we present an open-source high-power laser engine that can be built for a fraction of the cost. It uses affordable, yet powerful laser diodes at wavelengths of 405 nm, 488 nm and 638 nm and optionally a 561 nm diode-pumped solid-state laser. The light is delivered to the microscope via an agitated multimode fiber in order to suppress speckles. We provide the parts list, CAD files and detailed descriptions, allowing any research group to build their own laser engine.

A HIDDEN MARKOV MODEL APPROACH TO CHARACTERIZING THE PHOTO-SWITCHING BEHAVIOR OF FLUOROPHORES

Fluorescing molecules (fluorophores) that stochastically switch between photon-emitting and dark states underpin some of the most celebrated advancements in super-resolution microscopy. While this stochastic behavior has been heavily exploited, full characterization of the underlying models can potentially drive forward further imaging methodologies. Under the assumption that fluorophores move between fluorescing and dark states as continuous time Markov processes, the goal is to use a sequence of images to select a model and estimate the transition rates. We use a hidden Markov model to relate the observed discrete time signal to the hidden continuous time process. With imaging involving several repeat exposures of the fluorophore, we show the observed signal depends on both the current and past states of the hidden process, producing emission probabilities that depend on the transition rate parameters to be estimated. To tackle this unusual coupling of the transition and emission probabilities, we conceive transmission (transition-emission) matrices that capture all dependencies of the model. We provide a scheme of computing these matrices and adapt the forward-backward algorithm to compute a likelihood which is readily optimized to provide rate estimates. When confronted with several model proposals, combining this procedure with the Bayesian Information Criterion provides accurate model selection.

3D super-resolution microscopy performance and quantitative analysis assessment using DNA-PAINT and DNA origami test samples

Assessment of the imaging quality in localisation-based super-resolution techniques relies on an accurate characterisation of the imaging setup and analysis procedures. Test samples can provide regular feedback on system performance and facilitate the implementation of new methods. While multiple test samples for regular, 2D imaging are available, they are not common for more specialised imaging modes. Here, we analyse robust test samples for 3D and quantitative super-resolution imaging, which are straightforward to use, are time- and cost-effective and do not require experience beyond basic laboratory and imaging skills. We present two options for assessment of 3D imaging quality, the use of microspheres functionalised for DNA-PAINT and a commercial DNA origami sample. A method to establish and assess a qPAINT workflow for quantitative imaging is demonstrated with a second, commercially available DNA origami sample.

Nanoscopy on-a-chip: super-resolution imaging on the millimeter scale

Optical nanoscopy techniques can image intracellular structures with high specificity at sub-diffraction limited resolution, bridging the resolution gap between optical microscopy and electron microscopy. So far conventional nanoscopy lacks the ability to generate high throughput data, as the imaged region is small. Photonic chip-based nanoscopy has demonstrated the potential for imaging large areas, but at a lateral resolution of 130 nm. However, all the existing super-resolution methods provide a resolution of 100 nm or better. In this work, chip-based nanoscopy is demonstrated with a resolution of 75 nm over an extraordinarily large area of 0.5 mm × 0.5 mm, using a low magnification and high N.A. objective lens. Furthermore, the performance of chip-based nanoscopy is benchmarked by studying the localization precision and illumination homogeneity for different waveguide widths. The advent of large field-of-view chip-based nanoscopy opens up new routes in diagnostics where high throughput is needed for the detection of non-diffuse disease, or rare events such as the early detection of cancer.

A Polymerizable Photoswitchable Fluorophore for Super-Resolution Imaging of Polymer Self-Assembly and Dynamics

Single-molecule super-resolution microscopy has become a standard imaging tool in the life sciences for visualizing nanostructures in situ, but the application of this technique in polymer science is much less explored. A key bottleneck is the lack of fluorophores and simple covalent attachment strategies onto polymer chains. Here, we report a functional diarylethene-based photoswitchable fluorophore that can be directly incorporated into polymer backbones through copolymerization, which significantly streamlines the labeling strategy, with no further postcoupling reactions or purifications needed. The attachment of fluorophores onto selectively labeled polymers enables super-resolution imaging of a series of model polymer blend systems with different nanostructures and chemical compositions. As each individual fluorophore is able to switch several times on average between its bright and dark state, multiple time-lapse images can be acquired to observe the dynamic nanostructural evolution of polymer blends upon solvent vapor annealing. With this demonstration of a universal, simplified labeling strategy and the ability to image polymer assembly under native conditions, this reported fluorophore may promote the widespread use of super-resolution microscopy in the polymer community.

Excitation-multiplexed multicolor superresolution imaging with fm-STORM and fm-DNA-PAINT

Recent advancements in single-molecule-based superresolution microscopy have made it possible to visualize biological structures with unprecedented spatial resolution. Determining the spatial coorganization of these structures within cells under physiological and pathological conditions is an important biological goal. This goal has been stymied by the current limitations of carrying out superresolution microscopy in multiple colors. Here, we develop an approach for simultaneous multicolor superresolution imaging which relies solely on fluorophore excitation, rather than fluorescence emission properties. By modulating the intensity of the excitation lasers at different frequencies, we show that the color channel can be determined based on the fluorophore's response to the modulated excitation. We use this frequency multiplexing to reduce the image acquisition time of multicolor superresolution DNA-PAINT while maintaining all its advantages: minimal color cross-talk, minimal photobleaching, maximal signal throughput, ability to maintain the fluorophore density per imaged color, and ability to use the full camera field of view. We refer to this imaging modality as "frequency multiplexed DNA-PAINT," or fm-DNA-PAINT for short. We also show that frequency multiplexing is fully compatible with STORM superresolution imaging, which we term fm-STORM. Unlike fm-DNA-PAINT, fm-STORM is prone to color cross-talk. To overcome this caveat, we further develop a machine-learning algorithm to correct for color cross-talk with more than 95% accuracy, without the need for prior information about the imaged structure.

Autonomous illumination control for localization microscopy

Super-resolution fluorescence microscopy improves spatial resolution, but this comes at a loss of image throughput and presents unique challenges in identifying optimal acquisition parameters. Microscope automation routines can offset these drawbacks, but thus far have required user inputs that presume a priori knowledge about the sample. Here, we develop a flexible illumination control system for localization microscopy comprised of two interacting components that require no sample-specific inputs: a self-tuning controller and a deep learning-based molecule density estimator that is accurate over an extended range of densities. This system obviates the need to fine-tune parameters and enables robust, autonomous illumination control for localization microscopy.

A Platform To Enhance Quantitative Single Molecule Localization Microscopy

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

Impact of Bacterial Membrane Fatty Acid Composition on the Failure of Daptomycin To Kill Staphylococcus aureus

Daptomycin is a last-resort membrane-targeting lipopeptide approved for the treatment of drug-resistant staphylococcal infections, such as bacteremia and implant-related infections. Although cases of resistance to this antibiotic are rare, increasing numbers of clinical, in vitro, and animal studies report treatment failure, notably against Staphylococcus aureus The aim of this study was to identify the features of daptomycin and its target bacteria that lead to daptomycin treatment failure. We show that daptomycin bactericidal activity against S. aureus varies significantly with the growth state and strain, according to the membrane fatty acid composition. Daptomycin efficacy as an antibiotic relies on its ability to oligomerize within membranes and form pores that subsequently lead to cell death. Our findings ascertain that daptomycin interacts with tolerant bacteria and reaches its membrane target, regardless of its bactericidal activity. However, the final step of pore formation does not occur in cells that are daptomycin tolerant, strongly suggesting that it is incapable of oligomerization. Importantly, membrane fatty acid contents correlated with poor daptomycin bactericidal activity, which could be manipulated by fatty acid addition. In conclusion, daptomycin failure to treat S. aureus is not due to a lack of antibiotic-target interaction, but is driven by its capacity to form pores, which depends on membrane composition. Manipulation of membrane fluidity to restore S. aureus daptomycin bactericidal activity in vivo could open the way to novel antibiotic treatment strategies.

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

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

3D super-resolution microscopy reflects mitochondrial cristae alternations and mtDNA nucleoid size and distribution

3D super-resolution microscopy based on the direct stochastic optical reconstruction microscopy (dSTORM) with primary Alexa-Fluor-647-conjugated antibodies is a powerful method for accessing changes of objects that could be normally resolved only by electron microscopy. Despite the fact that mitochondrial cristae yet to become resolved, we have indicated changes in cristae width and/or morphology by dSTORM of ATP-synthase F₁ subunit α (F₁α). Obtained 3D images were analyzed with the help of Ripley's K-function modeling spatial patterns or transferring them into distance distribution function. Resulting histograms of distances frequency distribution provide most frequent distances (MFD) between the localized single antibody molecules. In fasting state of model pancreatic β-cells, INS-1E, MFD between F₁α were ~80 nm at 0 and 3 mM glucose, whereas decreased to 61 nm and 57 nm upon glucose-stimulated insulin secretion (GSIS) at 11 mM and 20 mM glucose, respectively. Shorter F₁α interdistances reflected cristae width decrease upon GSIS, since such repositioning of F₁α correlated to average 20 nm and 15 nm cristae width at 0 and 3 mM glucose, and 9 nm or 8 nm after higher glucose simulating GSIS (11, 20 mM glucose, respectively). Also, submitochondrial entities such as nucleoids of mtDNA were resolved e.g. after bromo-deoxyuridine (BrDU) pretreatment using anti-BrDU dSTORM. MFD in distances distribution histograms reflected an average nucleoid diameter (<100 nm) and average distances between nucleoids (~1000 nm). Double channel PALM/dSTORM with Eos-lactamase-β plus anti-TFAM dSTORM confirmed the latter average inter-nucleoid distance. In conclusion, 3D single molecule (dSTORM) microscopy is a reasonable tool for studying mitochondrion.

The Role of Probe Photophysics in Localization-Based Superresolution Microscopy

Fluorescent proteins are used extensively for biological imaging applications; photoactivatable and photoconvertible fluorescent proteins (PAFPs) are used widely in superresolution localization microscopy methods such as fluorescence photoactivation localization microscopy and photoactivated localization microscopy. However, their optimal use depends on knowledge of not only their bulk fluorescence properties, but also their photophysical properties at the single molecule level. We have used fluorescence correlation spectroscopy and cross-correlation spectroscopy to quantify the diffusion, photobleaching, fluorescence intermittency, and photoconversion dynamics of Dendra2, a well-known PAFP used in localization microscopy. Numerous dark states of Dendra2 are observed both in inactive (green fluorescent) and active (orange fluorescent) forms; the interconversion rates are both light- and pH-dependent, as observed for other PAFPs. The dark states limit the detected count rate per molecule, which is a crucial parameter for localization microscopy. We then developed, to our knowledge, a new mathematical estimate for the resolution in localization microscopy as a function of the measured photophysical parameters of the probe such as photobleaching quantum yield, count rate per molecule, and intensity of saturation. The model was used to predict the dependence of resolution on acquisition parameters such as illumination intensity and time per frame, demonstrating an optimal set of acquisition parameters for a given probe for a variety of measures of resolution. The best possible resolution was then compared for Dendra2 and other widely used probes, including Alexa dyes and quantum dots. This work establishes a framework for determination of the best possible resolution using a localization microscope to image a particular fluorophore, and suggests that development of probes for use in superresolution localization microscopy must consider the count rate per molecule, the saturation intensity, the photobleaching yield, and, crucially, management of bright/dark state transitions, to optimize image resolution.

Characterization of an industry-grade CMOS camera well suited for single molecule localization microscopy - high performance super-resolution at low cost

Many commercial as well as custom-built fluorescence microscopes use scientific-grade cameras that represent a substantial share of the instrument's cost. This holds particularly true for super-resolution localization microscopy where high demands are placed especially on the detector with respect to sensitivity, noise, and also image acquisition speed. Here, we present and carefully characterize an industry-grade CMOS camera as a cost-efficient alternative to commonly used scientific cameras. Direct experimental comparison of these two detector types shows widely similar performance for imaging by single molecule localization microscopy (SMLM). Furthermore, high image acquisition speeds are demonstrated for the CMOS detector by ultra-fast SMLM imaging.

Long time-lapse nanoscopy with spontaneously blinking membrane probes

Imaging cellular structures and organelles in living cells by long time-lapse super-resolution microscopy is challenging, as it requires dense labeling, bright and highly photostable dyes, and non-toxic conditions. We introduce a set of high-density, environment-sensitive (HIDE) membrane probes, based on the membrane-permeable silicon-rhodamine dye HMSiR, that assemble in situ and enable long time-lapse, live-cell nanoscopy of discrete cellular structures and organelles with high spatiotemporal resolution. HIDE-enabled nanoscopy movies span tens of minutes, whereas movies obtained with labeled proteins span tens of seconds. Our data reveal 2D dynamics of the mitochondria, plasma membrane and filopodia, and the 2D and 3D dynamics of the endoplasmic reticulum, in living cells. HIDE probes also facilitate acquisition of live-cell, two-color, super-resolution images, expanding the utility of nanoscopy to visualize dynamic processes and structures in living cells.

Eigen-analysis reveals components supporting super-resolution imaging of blinking fluorophores

This paper presents eigen-analysis of image stack of blinking fluorophores to identify the components that enable super-resolved imaging of blinking fluorophores. Eigen-analysis reveals that the contributions of spatial distribution of fluorophores and their temporal photon emission characteristics can be completely separated. While cross-emitter cross-pixel information of spatial distribution that permits super-resolution is encoded in two matrices, temporal statistics weigh the contribution of these matrices to the measured data. The properties and conditions of exploitation of these matrices are investigated. Con-temporary super-resolution imaging methods that use blinking for super-resolution are studied in the context of the presented analysis. Besides providing insight into the capabilities and limitations of existing super-resolution methods, the analysis shall help in designing better super-resolution techniques that directly exploit these matrices.

SPAD imagers for super resolution localization microscopy enable analysis of fast fluorophore blinking

sCMOS imagers are currently utilized (replacing EMCCD imagers) to increase the acquisition speed in super resolution localization microscopy. Single-photon avalanche diode (SPAD) imagers feature frame rates per bit depth comparable to or higher than sCMOS imagers, while generating microsecond 1-bit-frames without readout noise, thus paving the way to in-depth time-resolved image analysis. High timing resolution can also be exploited to explore fluorescent dye blinking and other photophysical properties, which can be used for dye optimization. We present the methodology for the blinking analysis of fluorescent dyes on experimental data. Furthermore, the recent use of microlenses has enabled a substantial increase of SPAD imager overall sensitivity (12-fold in our case), reaching satisfactory values for sensitivity-critical applications. This has allowed us to record the first super resolution localization microscopy results obtained with a SPAD imager, with a localization uncertainty of 20 nm and a resolution of 80 nm.

Local dimensionality determines imaging speed in localization microscopy

Localization microscopy allows biological samples to be imaged at a length scale of tens of nanometres. Live-cell super-resolution imaging is rare, as it is generally assumed to be too slow for dynamic samples. The speed of data acquisition can be optimized by tuning the density of activated fluorophores in each time frame. Here, we show that the maximum achievable imaging speed for a particular structure varies by orders of magnitude, depending on the sample dimensionality (that is, whether the sample is more like a point, a strand or an extended structure such as a focal adhesion). If too high an excitation density is used, we demonstrate that the analysis undergoes silent failure, resulting in reconstruction artefacts. We are releasing a tool to allow users to identify areas of the image in which the activation density was too high and correct for them, in both live- and fixed-cell experiments.

Localisation microscopy enables nanometre-scale imaging of biological samples, but the method is too slow to use on dynamic systems. Here, the authors develop a mathematical model that optimises the number of frames required and estimates the maximum speed for super-resolution imaging.

Promoting convergence: The integrated graduate program in physical and engineering biology at Yale University, a new model for graduate education

In 2008, we established the Integrated Graduate Program in Physical and Engineering Biology (IGPPEB) at Yale University. Our goal was to create a comprehensive graduate program to train a new generation of scientists who possess a sophisticated understanding of biology and who are capable of applying physical and quantitative methodologies to solve biological problems. Here we describe the framework of the training program, report on its effectiveness, and also share the insights we gained during its development and implementation. The program features co-teaching by faculty with complementary specializations, student peer learning, and novel hands-on courses that facilitate the seamless blending of interdisciplinary research and teaching. It also incorporates enrichment activities to improve communication skills, engage students in science outreach, and foster a cohesive program cohort, all of which promote the development of transferable skills applicable in a variety of careers. The curriculum of the graduate program is integrated with the curricular requirements of several Ph.D.-granting home programs in the physical, engineering, and biological sciences. Moreover, the wide-ranging recruiting activities of the IGPPEB serve to enhance the quality and diversity of students entering graduate school at Yale. We also discuss some of the challenges we encountered in establishing and optimizing the program, and describe the institution-level changes that were catalyzed by the introduction of the new graduate program. The goal of this article is to serve as both an inspiration and as a practical "how to" manual for those who seek to establish similar programs at their own institutions. © 2016 by The International Union of Biochemistry and Molecular Biology, 44(6):537-549, 2016.

Congenital Heart Disease Genetics Uncovers Context-Dependent Organization and Function of Nucleoporins at Cilia

Human genomics is identifying candidate genes for congenital heart disease (CHD), but discovering the underlying mechanisms remains challenging. In a patient with CHD and heterotaxy (Htx), a disorder of left-right patterning, we previously identified a duplication in Nup188. However, a mechanism to explain how a component of the nuclear pore complex (NPC) could cause Htx/CHD was undefined. Here, we show that knockdown of Nup188 or its binding partner Nup93 leads to a loss of cilia during embryonic development while leaving NPC function largely intact. Many data, including the localization of endogenous Nup188/93 at cilia bases, support their direct role at cilia. Super-resolution imaging of Nup188 shows two barrel-like structures with dimensions and organization incompatible with an NPC-like ring, arguing against a proposed "ciliary pore complex." We suggest that the nanoscale organization and function of nucleoporins are context dependent in a way that is required for the structure of the heart.

Ultra-High Resolution 3D Imaging of Whole Cells

Fluorescence nanoscopy, or super-resolution microscopy, has become an important tool in cell biological research. However, because of its usually inferior resolution in the depth direction (50-80 nm) and rapidly deteriorating resolution in thick samples, its practical biological application has been effectively limited to two dimensions and thin samples. Here, we present the development of whole-cell 4Pi single-molecule switching nanoscopy (W-4PiSMSN), an optical nanoscope that allows imaging of three-dimensional (3D) structures at 10- to 20-nm resolution throughout entire mammalian cells. We demonstrate the wide applicability of W-4PiSMSN across diverse research fields by imaging complex molecular architectures ranging from bacteriophages to nuclear pores, cilia, and synaptonemal complexes in large 3D cellular volumes.

Single objective light-sheet microscopy for high-speed whole-cell 3D super-resolution

We have developed a method for performing light-sheet microscopy with a single high numerical aperture lens by integrating reflective side walls into a microfluidic chip. These 45° side walls generate light-sheet illumination by reflecting a vertical light-sheet into the focal plane of the objective. Light-sheet illumination of cells loaded in the channels increases image quality in diffraction limited imaging via reduction of out-of-focus background light. Single molecule super-resolution is also improved by the decreased background resulting in better localization precision and decreased photo-bleaching, leading to more accepted localizations overall and higher quality images. Moreover, 2D and 3D single molecule super-resolution data can be acquired faster by taking advantage of the increased illumination intensities as compared to wide field, in the focused light-sheet.

PALM and STORM: Into large fields and high-throughput microscopy with sCMOS detectors

Single Molecule Localization Microscopy (SMLM) techniques such as Photo-Activation Localization Microscopy (PALM) and Stochastic Optical Reconstruction Microscopy (STORM) enable fluorescence microscopy super-resolution: the overcoming of the resolution barrier imposed by the diffraction of light. These techniques are based on acquiring hundreds or thousands of images of single molecules, locating them and reconstructing a higher-resolution image from the high-precision localizations. These methods generally imply a considerable trade-off between imaging speed and resolution, limiting their applicability to high-throughput workflows. Recent advancements in scientific Complementary Metal-Oxide Semiconductor (sCMOS) camera sensors and localization algorithms reduce the temporal requirements for SMLM, pushing it toward high-throughput microscopy. Here we outline the decisions researchers face when considering how to adapt hardware on a new system for sCMOS sensors with high-throughput in mind.