Localization Microscopy Methods Research Articles

Three-color single-molecule localization microscopy in chromatin.

Super-resolution microscopy has revolutionized our ability to visualize structures below the diffraction limit of conventional optical microscopy and is particularly useful for investigating complex biological targets like chromatin. Chromatin exhibits a hierarchical organization with structural compartments and domains at different length scales, from nanometers to micrometers. Single molecule localization microscopy (SMLM) methods, such as STORM, are essential for studying chromatin at the supra-nucleosome level due to their ability to target epigenetic marks that determine chromatin organization. Multi-label imaging of chromatin is necessary to unpack its structural complexity. However, these efforts are challenged by the high-density nuclear environment, which can affect antibody binding affinities, diffusivity and non-specific interactions. Optimizing buffer conditions, fluorophore stability, and antibody specificity is crucial for achieving effective antibody conjugates. Here, we demonstrate a sequential immunolabeling protocol that reliably enables three-label studies within the dense nuclear environment. This protocol couples multiplexed localization datasets with a robust analysis algorithm, which utilizes localizations from one target as seed points for distance, density and multi-label joint affinity measurements to explore complex organization of all three targets. Applying this multi-plexed algorithm to analyze distance and joint density reveals that heterochromatin and euchromatin are not-distinct territories, but that localization of transcription and euchromatin couple with the periphery of heterochromatic clusters. This work is a crucial step in molecular imaging of the dense nuclear environment as multi-label capacity enables for investigation of complex multi-component systems like chromatin with enhanced accuracy.

A Forked Microvascular Phantom for Ultrasound Localization Microscopy Investigations.

In the development of ultrasound localization microscopy (ULM) methods, appropriate test beds are needed to facilitate algorithmic performance calibration. Here, we present the design of a new ULM-compatible microvascular phantom with a forked, V-shaped wall-less flow channel pair ( 250 μ m channel width) that is bifurcated at a separation rate of 50 μ m/mm. The lumen core was fabricated using additive manufacturing, and it was molded within a polyvinyl alcohol (PVA) tissue-mimicking slab using the lost-core casting method. Measured using optical microscopy, the lumen core's flow channel width was found to be 252 ± 15 μ m with a regression-derived flow channel separation gradient of 50.89 μ m/mm. The new phantom's applicability in ULM performance analysis was demonstrated by feeding microbubble (MB) contrast flow (1.67 to 167 μ L/s flow rates) through the phantom's inlet and generating ULM images with a previously reported method. Results showed that, with longer acquisition times (10 s or longer), ULM image quality was expectedly improved, and the variance of ULM-derived flow channel measurements was reduced. Also, at axial depths near the lumen's bifurcation point, the current ULM algorithm showed difficulty in properly discerning between the two flow channels because of the narrow channel-to-channel separation distance. Overall, the new phantom serves well as a calibration tool to test the performance of ULM methods in resolving small vasculature.

PCNA as Protein-Based Nanoruler for Sub-10nm Fluorescence Imaging.

Super-resolution microscopy has revolutionized biological imaging enabling direct insight into cellular structures and protein arrangements with so far unmatched spatial resolution. Today, refined single-molecule localization microscopy methods achieve spatial resolutions in the one-digit nanometer range. As the race for molecular resolution fluorescence imaging with visible light continues, reliable biologically compatible reference structures will become essential to validate the resolution power. Here, PicoRulers (protein-based imaging calibration optical rulers), multilabeled oligomeric proteins designed as advanced molecular nanorulers for super-resolution fluorescence imaging are introduced. Genetic code expansion (GCE) is used to site-specifically incorporate three noncanonical amino acids (ncAAs) into the homotrimeric proliferating cell nuclear antigen (PCNA) at 6nm distances. Bioorthogonal click labeling with tetrazine-dyes and tetrazine-functionalized oligonucleotides allows efficient labeling of the PicoRuler with minimal linkage error. Time-resolved photoswitching fingerprint analysis is used to demonstrate the successful synthesis and DNA-based points accumulation for imaging in nanoscale topography (DNA-PAINT) is used to resolve 6nm PCNA PicoRulers. Since PicoRulers maintain their structural integrity under cellular conditions they represent ideal molecular nanorulers for benchmarking the performance of super-resolution imaging techniques, particularly in complex biological environments.

Machine learning framework to segment sarcomeric structures in SMLM data

Object detection is an image analysis task with a wide range of applications, which is difficult to accomplish with traditional programming. Recent breakthroughs in machine learning have made significant progress in this area. However, these algorithms are generally compatible with traditional pixelated images and cannot be directly applied for pointillist datasets generated by single molecule localization microscopy (SMLM) methods. Here, we have improved the averaging method developed for the analysis of SMLM images of sarcomere structures based on a machine learning object detection algorithm. The ordered structure of sarcomeres allows us to determine the location of the proteins more accurately by superimposing SMLM images of identically assembled proteins. However, the area segmentation process required for averaging can be extremely time-consuming and tedious. In this work, we have automated this process. The developed algorithm not only finds the regions of interest, but also classifies the localizations and identifies the true positive ones. For training, we used simulations to generate large amounts of labelled data. After tuning the neural network’s internal parameters, it could find the localizations associated with the structures we were looking for with high accuracy. We validated our results by comparing them with previous manual evaluations. It has also been proven that the simulations can generate data of sufficient quality for training. Our method is suitable for the identification of other types of structures in SMLM data.

Precision in iterative modulation enhanced single-molecule localization microscopy

Modulation enhanced single-molecule localization microscopy (meSMLM) methods improve the localization precision by using patterned illumination to encode additional position information. Iterative meSMLM (imeSMLM) methods iteratively generate prior information on emitter positions, used to locally improve the localization precision during subsequent iterations. The Cramér-Rao lower bound cannot incorporate prior information to bound the best achievable localization precision because it requires estimators to be unbiased. By treating estimands as random variables with a known prior distribution, the Van Trees inequality (VTI) can be used to bound the best possible localization precision of imeSMLM methods. An imeSMLM method is considered, where the positions of in-plane standing-wave illumination patterns are controlled over the course of multiple iterations. Using the VTI, we analytically approximate a lower bound on the maximum localization precision of imeSMLM methods that make use of standing-wave illumination patterns. In addition, we evaluate the maximally achievable localization precision for different illumination pattern placement strategies using Monte Carlo simulations. We show that in the absence of background and under perfect modulation, the information content of signal photons increases exponentially as a function of the iteration count. However, the information increase is no longer exponential as a function of the iteration count under non-zero background, imperfect modulation, or limited mechanical resolution of the illumination positioning system. As a result, imeSMLM with two iterations reaches at most a fivefold improvement over SMLM at 8 expected background photons per pixel and 95% modulation contrast. Moreover, the information increase from imeSMLM is balanced by a reduced signal photon rate. Therefore, SMLM outperforms imeSMLM when considering an equal measurement time and illumination power per iteration. Finally, the VTI is an excellent tool for the assessment of the performance of illumination control and is therefore the method of choice for optimal design and control of imeSMLM methods.

A single-molecule localization microscopy method for tissues reveals nonrandom nuclear pore distribution in Drosophila.

ABSTRACTSingle-molecule localization microscopy (SMLM) can provide nanoscale resolution in thin samples but has rarely been applied to tissues because of high background from out-of-focus emitters and optical aberrations. Here, we describe a line scanning microscope that provides optical sectioning for SMLM in tissues. Imaging endogenously-tagged nucleoporins and F-actin on this system using DNA- and peptide-point accumulation for imaging in nanoscale topography (PAINT) routinely gives 30 nm resolution or better at depths greater than 20 µm. This revealed that the nuclear pores are nonrandomly distributed in most Drosophila tissues, in contrast to what is seen in cultured cells. Lamin Dm0 shows a complementary localization to the nuclear pores, suggesting that it corrals the pores. Furthermore, ectopic expression of the tissue-specific Lamin C causes the nuclear pores to distribute more randomly, whereas lamin C mutants enhance nuclear pore clustering, particularly in muscle nuclei. Given that nucleoporins interact with specific chromatin domains, nuclear pore clustering could regulate local chromatin organization and contribute to the disease phenotypes caused by human lamin A/C laminopathies.

Single Molecules Are Your Quanta: A Bottom-Up Approach toward Multidimensional Super-resolution Microscopy.

The rise of single-molecule localization microscopy (SMLM) and related super-resolution methods over the past 15 years has revolutionized how we study biological and materials systems. In this Perspective, we reflect on the underlying philosophy of how diffraction-unlimited pictures containing rich spatial and functional information may gradually emerge through the local accumulation of single-molecule measurements. Starting with the basic concepts, we analyze the uniqueness of and opportunities in building up the final picture one molecule at a time. After brief introductions to the more established multicolor and three-dimensional measurements, we highlight emerging efforts to extend SMLM to new dimensions and functionalities as fluorescence polarization, emission spectra, and molecular motions, and discuss rising opportunities and future directions. With single molecules as our quanta, the bottom-up accumulation approach provides a powerful conduit for multidimensional microscopy at the nanoscale.

Three-dimensional total-internal reflection fluorescence nanoscopy with nanometric axial resolution by photometric localization of single molecules

Single-molecule localization microscopy enables far-field imaging with lateral resolution in the range of 10 to 20 nanometres, exploiting the fact that the centre position of a single-molecule’s image can be determined with much higher accuracy than the size of that image itself. However, attaining the same level of resolution in the axial (third) dimension remains challenging. Here, we present Supercritical Illumination Microscopy Photometric z-Localization with Enhanced Resolution (SIMPLER), a photometric method to decode the axial position of single molecules in a total internal reflection fluorescence microscope. SIMPLER requires no hardware modification whatsoever to a conventional total internal reflection fluorescence microscope and complements any 2D single-molecule localization microscopy method to deliver 3D images with nearly isotropic nanometric resolution. Performance examples include SIMPLER-direct stochastic optical reconstruction microscopy images of the nuclear pore complex with sub-20 nm axial localization precision and visualization of microtubule cross-sections through SIMPLER-DNA points accumulation for imaging in nanoscale topography with sub-10 nm axial localization precision.

New ℓ2 − ℓ0 algorithm for single-molecule localization microscopy

Among the many super-resolution techniques for microscopy, single-molecule localization microscopy methods are widely used. This technique raises the difficult question of precisely localizing fluorophores from a blurred, under-resolved, and noisy acquisition. In this work, we focus on the grid-based approach in the context of a high density of fluorophores formalized by a ℓ2 least-square term and sparsity term modeled with ℓ0 pseudo-norm. We consider both the constrained formulation and the penalized formulation. Based on recent results, we formulate the ℓ0 pseudo-norm as a convex minimization problem. This is done by introducing an auxiliary variable. An exact biconvex reformulation of the ℓ2 - ℓ0 constrained and penalized problems is proposed with a minimization algorithm. The algorithms, named CoBic (Constrained Biconvex) and PeBic (Penalized Biconvex) are applied to the problem of single-molecule localization microscopy and we compare the results with other recently proposed methods.

Multicolor localization microscopy and point-spread-function engineering by deep learning.

Deep learning has become an extremely effective tool for image classification and image restoration problems. Here, we apply deep learning to microscopy and demonstrate how neural networks can exploit the chromatic dependence of the point-spread function to classify the colors of single emitters imaged on a grayscale camera. While existing localization microscopy methods for spectral classification require additional optical elements in the emission path, e.g., spectral filters, prisms, or phase masks, our neural net correctly identifies static and mobile emitters with high efficiency using a standard, unmodified single-channel configuration. Furthermore, we show how deep learning can be used to design new phase-modulating elements that, when implemented into the imaging path, result in further improved color differentiation between species, including simultaneously differentiating four species in a single image.

Spatial mapping of affinity changes for the integrin LFA-1 during cell migration using clusters identified based on local density.

Localization microscopy methods like Stochastic Optical Reconstruction Microscopy (STORM) are very well suited for exploring clustering of proteins, as the data inherently provide a list of molecular coordinates. Here we use state-of-art cluster analysis algorithms (DBSCAN) to explore the clustering behaviour of different affinity forms of the integrin LFA-1. It has been suggested that LFA-1 may form clusters, in order to increase the avidity to ICAM-1. However, this hypothesis still seems to be controversial. In this study, we found, variations in clustering behaviour among the different affinity forms of LFA-1 in migrating T-cells. We found that panLFA-1 is located in clusters throughout the polarised cell on ICAM-1, with an increased density of molecules and clusters in the mid area and rear of the cell, whereas the intermediate and high affinity form of LFA-1 showed an increased number in the mid area of a migrating cell and the high affinity form of LFA-1 in the front and rear. Together, these data suggest that, in addition to LFA-1 conformation, protein clustering might play a role in controlling cell-substrate adhesion on ICAM-1.By applying the cluster analysis algorithm DBSCAN to localization microscopy data, integrin clusters could be identified and different cluster parameters could be quantified.

Quantitative fibre analysis of single-molecule localization microscopy data

Single molecule localization microscopy (SMLM) methods produce data in the form of a spatial point pattern (SPP) of all localized emitters. Whilst numerous tools exist to quantify molecular clustering in SPP data, the analysis of fibrous structures has remained understudied. Taking the SMLM localization coordinates as input, we present an algorithm capable of tracing fibrous structures in data generated by SMLM. Based upon a density parameter tracing routine, the algorithm outputs several fibre descriptors, such as number of fibres, length of fibres, area of enclosed regions and locations and angles of fibre branch points. The method is validated in a variety of simulated conditions and experimental data acquired using the image reconstruction by integrating exchangeable single-molecule localization (IRIS) technique. For this, the nanoscale architecture of F-actin at the T cell immunological synapse in both untreated and pharmacologically treated cells, designed to perturb actin structure, was analysed.

Rhodamine-Derived Fluorescent Dye with Inherent Blinking Behavior for Super-Resolution Imaging.

Super-resolution microscopy enables imaging of structures smaller than the diffraction limit. Single-molecule localization microscopy methods, such as photoactivation localization microscopy and stochastic optical reconstruction microscopy, reconstruct images by plotting the centroids of fluorescent point sources from a series of frames in which only a few molecules are fluorescing at a time. These approaches require simpler instrumentation than methods that depend on structured illumination and thus are becoming widespread. The functionalized rhodamine derivative reported in this paper spontaneously converts between a bright and dark state due to pH-dependent cyclization. At pH 7, less than 0.5% of the dye molecules are fluorescent at any given time. Blinking occurs on time scales of seconds to minutes and can therefore be used for single-molecule localization microscopy without sample treatment or activation. The dye is bright and straightforward to use, and it is easy to synthesize and functionalize. Thus, it has potential to become a new and powerful addition to the toolset for super-resolution imaging.

Extended-Depth 3D Super-Resolution Imaging Using Probe-Refresh STORM

Single-molecule localization microscopy methods for super-resolution fluorescence microscopy such as STORM (stochastic optical reconstruction microscopy) are generally limited to thin three-dimensional (3D) sections (≤600 nm) because of photobleaching of molecules outside the focal plane. Although multiple focal planes may be imaged before photobleaching by focusing progressively deeper within the sample, image quality is compromised in this approach because the total number of measurable localizations is divided between detection planes. Here, we solve this problem on fixed samples by developing an imaging method that we call probe-refresh STORM (prSTORM), which allows bleached fluorophores to be straightforwardly replaced with nonbleached fluorophores. We accomplish this by immunostaining the sample with DNA-conjugated antibodies and then reading out their distribution using fluorescently-labeled DNA-reporter oligonucleotides that can be fully replaced in successive rounds of imaging. We demonstrate that prSTORM can acquire 3D images over extended depths without sacrificing the density of localizations at any given plane. We also show that prSTORM can be adapted to obtain high-quality, 3D multichannel images with extended depth that would be challenging or impossible to achieve using established probe methods.

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 PS-CFP2 for Reliable Super-Resolution Microscopy

Single molecule localization microscopy (SMLM) methods constitute an elegant way to infer information about cellular organization at high resolution, e.g. distinguished structures such as the cytoskeleton or the nuclear pore complex. Hence, their application to identify (nano-)clustering on the plasma membrane, which is widely acknowledged to be a common feature of many proteins, is well reasoned. Identifying those, however, ultimately converges to quantitation of SMLM images. Overcounting artefacts caused by multiple observations of the same fluorophore molecules due to blinking or incomplete bleaching can be easily introduced. In this study we aimed at characterizing the blinking behaviour of the commonly used fluorescent protein, PS-CFP2. Recombinant, his-tagged PS-CFP2 was anchored to supported lipid bilayers via DGS-NTA(Ni), representing a system with adjustable surface densities and diffusion characteristics. Our data suggests the existence of several prolonged bright and dark states resulting in off times up to several seconds. Only about 66% of PS-CFP2 molecules were identified in a single image. Merging localisations from consecutive images increased this fraction to 77%. Although the maximum number of localisations per PS-CFP2 was greater than 10 in only ∼3% of the cases, the influence of these molecules on the resulting image is rigorous. Including this blinking statistics in simulations and evaluation using popular clustering algorithms, such as Ripley's K function, showed no differences between randomly distributed data containing blinks versus clustered non-blinking data. We conclude, that SMLM methods possess limitations for investigating protein clusters. Merging can be used for the correction of suboptimal bleaching, however, for considering blinking of fluorophores, this correction is - by the nature of the imaging method itself - inherently limited. Appropriate ways to tackle the investigation of possible clustering include varying the labelling density and multi-color colocalization techniques.

DNA-Paint Imaging of DNA-Origami Rings Mimicking Biologically Relevant Structures

Single-molecule localization microscopy methods such as DNA-PAINT (point accumulation for imaging in nanoscale topography), utilize successive localizations of single molecules over time to reveal of biological structures with photon-limited resolution1,2. However, visualization of sub-diffracted discrete bimolecular assemblies still remains a challenge. “DNA origami” has emerged as powerful nano-templating technique capable of generating stable self-assembled scaffold for positioning of molecular species of interest with nanometer precision3,4. Recent studies of DNA-PAINT have focused on imaging different molecular species, such as fluorophores and proteins, positioned on synthetic grid-like DNA nanostructures1,4. These grids are well suited for determining the resolution limit of sparsely labelled points (e.g. one fluorophore per 5x5 nm2). However, biological structures often have a much higher local density and complex structure, making imaging more challenging. In this study, as a proof-of-concept, we explored imaging of circular “ring-like” DNA-origami nanostructures of dimension mimicking small bio-molecular structures (25-50 nm inner diameter), like membrane receptors, ion channels etc. Using a TIRF-based imaging technique, we have optimized the fluorophores density and its positioning on DNA-origami rings to reconstruct “doughnut” shaped images and have been able to resolve inner diameter of ∼25 to 50 nm. We have carried out these analyses on glass surfaces and also on supported bilayers. Our study utilizing DNA rings provides challenging targets for DNA-PAINT technology and underscores the use of size-templated nanostructures, as approximates for bio-molecular complexes, to optimize imaging and analysis protocols independent of biological sample preparation.1. Dai et al. (2016) Nat. Nanotechnol. 11:798-807.2. Baddeley, D. (2015) Nat. Methods 12:1019-1020.3. Yang et al. (2016) Nat. Chem. 8:476-483.4. Schlichthaerle et al. (2016) Curr. Opin. Biotechnol. 39: 41-47.

New data on structures formed by the FtsZ protein during the cell division process in Escherichia coli obtained using the localization microscopy method

The FtsZ protein, a bacterial tubulin homolog, is one of the key proteins in bacterial cell division, forming a contractile Z-ring in the middle of the dividing cell. In the present study, immunofluorescence staining, in combination with the localization microscopy method, was used for visualization of the structures formed by unlabelled FtsZ in Escherrichia coli cells. The techniques employed allowed reconstruction of the multistep mechanism of formation of FtsZ structures during the cytokinesis process. New data were obtained confirming the hypothesis that FtsZ is a helixlike structure that constricts during the division, producing constriction between the daughter cells.

High density 3D localization microscopy using sparse support recovery.

Single-molecule localization microscopy methods offer high spatial resolution, but they are not always suitable for live cell imaging due to limited temporal resolution. One strategy is to increase the density of photoactivated molecules present in each image, however suitable analysis algorithms for such data are still lacking. We present 3denseSTORM, a new algorithm for localization microscopy which is able to recover 2D or 3D super-resolution images from a sequence of diffraction limited images with high densities of photoactivated molecules. The algorithm is based on sparse support recovery and uses a Poisson noise model, which becomes critical in low-light conditions. For 3D data reconstruction we use the astigmatism and biplane imaging methods. We derive the theoretical resolution limits of the method and show examples of image reconstructions in simulations and in real 2D and 3D biological samples. The method is suitable for fast image acquisition in densely labeled samples and helps facilitate live cell studies with single molecule localization microscopy.

Interferometric three-dimensional single molecule localization microscopy using a single high-numerical-aperture objective.

Interferometric detection of the fluorescence emission from a single molecule [interferometric photoactivated localization microscopy (iPALM)] enables a localization accuracy of nanometers in axial localization for 3D superresolution imaging. However, iPALM uses two high-numerical-aperture (NA) objectives in juxtaposition for fluorescence collection (a 4Pi microscope geometry), increasing expense and limiting samples that can be studied. Here, we propose an interferometric single molecule localization microscopy method using a single high-NA objective. The axial position of single molecules can be unambiguously determined from the phase-shifted interference signals with nanometer precision and over a range of 2λ. The use of only one objective simplifies the system configuration and sample mounting. In addition, due to the use of wavefront-splitting interference in our approach, the two parts of the wavefront that eventually merge and interfere with each other travel along nearly equivalent optical paths, which should minimize the effect of drift for long-term 3D superresolution imaging.