Mapping Synaptic Input Fields of Neurons with Super-Resolution Imaging.

As a basic functional unit in neural circuits, each neuron integrates input signals from hundreds to thousands of synapses. Knowledge of the synaptic input fields of individual neurons, including the identity, strength, and location of each synapse, is essential for understanding how neurons compute. Here, we developed a volumetric super-resolution reconstruction platform for large-volume imaging and automated segmentation of neurons and synapses with molecular identity information. We used this platform to map inhibitory synaptic input fields of On-Off direction-selective ganglion cells (On-Off DSGCs), which are important for computing visual motion direction in the mouse retina. The reconstructions of On-Off DSGCs showed a GABAergic, receptor subtype-specific input field for generating direction selective responses without significant glycinergic inputs for mediating monosynaptic crossover inhibition. These results demonstrate unique capabilities of this super-resolution platform for interrogating neural circuitry.

Breaking the diffraction barrier: super-resolution imaging of cells.

Anyone who has used a light microscope has wished that its resolution could be a little better. Now, after centuries of gradual improvements, fluorescence microscopy has made a quantum leap in its resolving power due, in large part, to advancements over the past several years in a new area of research called super-resolution fluorescence microscopy. In this Primer, we explain the principles of various super-resolution approaches, such as STED, (S)SIM, and STORM/(F)PALM. Then, we describe recent applications of super-resolution microscopy in cells, which demonstrate how these approaches are beginning to provide new insights into cell biology, microbiology, and neurobiology.

The DDR at telomeres lacking intact shelterin does not require substantial chromatin decompaction.

Telomeres are protected by shelterin, a six-subunit protein complex that represses the DNA damage response (DDR) at chromosome ends. Extensive data suggest that TRF2 in shelterin remodels telomeres into the t-loop structure, thereby hiding telomere ends from double-stranded break repair and ATM signaling, whereas POT1 represses ATR signaling by excluding RPA. An alternative protection mechanism was suggested recently by which shelterin subunits TRF1, TRF2, and TIN2 mediate telomeric chromatin compaction, which was proposed to minimize access of DDR factors. We performed superresolution imaging of telomeres in mouse cells after conditional deletion of TRF1, TRF2, or both, the latter of which results in the complete loss of shelterin. Upon removal of TRF1 or TRF2, we observed only minor changes in the telomere volume in most of our experiments. Upon codeletion of TRF1 and TRF2, the telomere volume increased by varying amounts, but even those samples exhibiting small changes in telomere volume showed DDR at nearly all telomeres. Upon shelterin removal, telomeres underwent 53BP1-dependent clustering, potentially explaining at least in part the apparent increase in telomere volume. Furthermore, chromatin accessibility, as determined by ATAC-seq (assay for transposase-accessible chromatin [ATAC] with high-throughput sequencing), was not substantially altered by shelterin removal. These results suggest that the DDR induced by shelterin removal does not require substantial telomere decompaction.

Publisher Correction: Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software.

In the version of this paper originally published, Figure 4a contained errors that were introduced during typesetting. The bottom 11° ThunderSTORM image is an xz view but was incorrectly labeled as xy, and the low x-axis value in the four line profiles was incorrectly set as -60 instead of -50. These errors have been corrected in the PDF and HTML versions of the paper.

Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software.

With the widespread uptake of two-dimensional (2D) and three-dimensional (3D) single-molecule localization microscopy (SMLM), a large set of different data analysis packages have been developed to generate super-resolution images. In a large community effort, we designed a competition to extensively characterize and rank the performance of 2D and 3D SMLM software packages. We generated realistic simulated datasets for popular imaging modalities-2D, astigmatic 3D, biplane 3D and double-helix 3D-and evaluated 36 participant packages against these data. This provides the first broad assessment of 3D SMLM software and provides a holistic view of how the latest 2D and 3D SMLM packages perform in realistic conditions. This resource allows researchers to identify optimal analytical software for their experiments, allows 3D SMLM software developers to benchmark new software against the current state of the art, and provides insight into the current limits of the field.

Imaging-based pooled CRISPR screening reveals regulators of lncRNA localization.

Pooled-library CRISPR screening provides a powerful means to discover genetic factors involved in cellular processes in a high-throughput manner. However, the phenotypes accessible to pooled-library screening are limited. Complex phenotypes, such as cellular morphology and subcellular molecular organization, as well as their dynamics, require imaging-based readout and are currently beyond the reach of pooled-library CRISPR screening. Here we report an all imaging-based pooled-library CRISPR screening approach that combines high-content phenotype imaging with high-throughput single guide RNA (sgRNA) identification in individual cells. In this approach, sgRNAs are codelivered to cells with corresponding barcodes placed at the 3' untranslated region of a reporter gene using a lentiviral delivery system with reduced recombination-induced sgRNA-barcode mispairing. Multiplexed error-robust fluorescence in situ hybridization (MERFISH) is used to read out the barcodes and hence identify the sgRNAs with high accuracy. We used this approach to screen 162 sgRNAs targeting 54 RNA-binding proteins for their effects on RNA localization to nuclear compartments and uncovered previously unknown regulatory factors for nuclear RNA localization. Notably, our screen revealed both positive and negative regulators for the nuclear speckle localization of a long noncoding RNA, MALAT1, suggesting a dynamic regulation of lncRNA localization in subcellular compartments.

Iterative expansion microscopy.

We recently developed a method called expansion microscopy, in which preserved biological specimens are physically magnified by embedding them in a densely crosslinked polyelectrolyte gel, anchoring key labels or biomolecules to the gel, mechanically homogenizing the specimen, and then swelling the gel-specimen composite by ∼4.5× in linear dimension. Here we describe iterative expansion microscopy (iExM), in which a sample is expanded ∼20×. After preliminary expansion a second swellable polymer mesh is formed in the space newly opened up by the first expansion, and the sample is expanded again. iExM expands biological specimens ∼4.5 × 4.5, or ∼20×, and enables ∼25-nm-resolution imaging of cells and tissues on conventional microscopes. We used iExM to visualize synaptic proteins, as well as the detailed architecture of dendritic spines, in mouse brain circuitry.

High-throughput single-cell gene-expression profiling with multiplexed error-robust fluorescence in situ hybridization.

Image-based approaches to single-cell transcriptomics, in which RNA species are identified and counted in situ via imaging, have emerged as a powerful complement to single-cell methods based on RNA sequencing of dissociated cells. These image-based approaches naturally preserve the native spatial context of RNAs within a cell and the organization of cells within tissue, which are important for addressing many biological questions. However, the throughput of these image-based approaches is relatively low. Here we report advances that lead to a drastic increase in the measurement throughput of multiplexed error-robust fluorescence in situ hybridization (MERFISH), an image-based approach to single-cell transcriptomics. In MERFISH, RNAs are identified via a combinatorial labeling approach that encodes RNA species with error-robust barcodes followed by sequential rounds of single-molecule fluorescence in situ hybridization (smFISH) to read out these barcodes. Here we increase the throughput of MERFISH by two orders of magnitude through a combination of improvements, including using chemical cleavage instead of photobleaching to remove fluorescent signals between consecutive rounds of smFISH imaging, increasing the imaging field of view, and using multicolor imaging. With these improvements, we performed RNA profiling in more than 100,000 human cells, with as many as 40,000 cells measured in a single 18-h measurement. This throughput should substantially extend the range of biological questions that can be addressed by MERFISH.

Dual-objective STORM reveals three-dimensional filament organization in the actin cytoskeleton.

By combining astigmatism imaging with a dual-objective scheme, we improved the image resolution of stochastic optical reconstruction microscopy (STORM) and obtained <10-nm lateral resolution and <20-nm axial resolution when imaging biological specimens. Using this approach, we resolved individual actin filaments in cells and revealed three-dimensional ultrastructure of the actin cytoskeleton. We observed two vertically separated layers of actin networks with distinct structural organizations in sheet-like cell protrusions.

Super-resolution fluorescence imaging of organelles in live cells with photoswitchable membrane probes.

Imaging membranes in live cells with nanometer-scale resolution promises to reveal ultrastructural dynamics of organelles that are essential for cellular functions. In this work, we identified photoswitchable membrane probes and obtained super-resolution fluorescence images of cellular membranes. We demonstrated the photoswitching capabilities of eight commonly used membrane probes, each specific to the plasma membrane, mitochondria, the endoplasmic recticulum (ER) or lysosomes. These small-molecule probes readily label live cells with high probe densities. Using these probes, we achieved dynamic imaging of specific membrane structures in living cells with 30-60 nm spatial resolution at temporal resolutions down to 1-2 s. Moreover, by using spectrally distinguishable probes, we obtained two-color super-resolution images of mitochondria and the ER. We observed previously obscured details of morphological dynamics of mitochondrial fusion/fission and ER remodeling, as well as heterogeneous membrane diffusivity on neuronal processes.

Fast compressed sensing analysis for super-resolution imaging using L1-homotopy.

In super-resolution imaging techniques based on single-molecule switching and localization, the time to acquire a super-resolution image is limited by the maximum density of fluorescent emitters that can be accurately localized per imaging frame. In order to increase the imaging rate, several methods have been recently developed to analyze images with higher emitter densities. One powerful approach uses methods based on compressed sensing to increase the analyzable emitter density per imaging frame by several-fold compared to other reported approaches. However, the computational cost of this approach, which uses interior point methods, is high, and analysis of a typical 40 µm x 40 µm field-of-view super-resolution movie requires thousands of hours on a high-end desktop personal computer. Here, we demonstrate an alternative compressed-sensing algorithm, L1-Homotopy (L1H), which can generate super-resolution image reconstructions that are essentially identical to those derived using interior point methods in one to two orders of magnitude less time depending on the emitter density. Moreover, for an experimental data set with varying emitter density, L1H analysis is ~300-fold faster than interior point methods. This drastic reduction in computational time should allow the compressed sensing approach to be routinely applied to super-resolution image analysis.

Statistical deconvolution for superresolution fluorescence microscopy.

Superresolution microscopy techniques based on the sequential activation of fluorophores can achieve image resolution of ∼10 nm but require a sparse distribution of simultaneously activated fluorophores in the field of view. Image analysis procedures for this approach typically discard data from crowded molecules with overlapping images, wasting valuable image information that is only partly degraded by overlap. A data analysis method that exploits all available fluorescence data, regardless of overlap, could increase the number of molecules processed per frame and thereby accelerate superresolution imaging speed, enabling the study of fast, dynamic biological processes. Here, we present a computational method, referred to as deconvolution-STORM (deconSTORM), which uses iterative image deconvolution in place of single- or multiemitter localization to estimate the sample. DeconSTORM approximates the maximum likelihood sample estimate under a realistic statistical model of fluorescence microscopy movies comprising numerous frames. The model incorporates Poisson-distributed photon-detection noise, the sparse spatial distribution of activated fluorophores, and temporal correlations between consecutive movie frames arising from intermittent fluorophore activation. We first quantitatively validated this approach with simulated fluorescence data and showed that deconSTORM accurately estimates superresolution images even at high densities of activated fluorophores where analysis by single- or multiemitter localization methods fails. We then applied the method to experimental data of cellular structures and demonstrated that deconSTORM enables an approximately fivefold or greater increase in imaging speed by allowing a higher density of activated fluorophores/frame.

Multiplexed detection of RNA using MERFISH and branched DNA amplification.

Multiplexed error-robust fluorescence in situ hybridization (MERFISH) allows simultaneous imaging of numerous RNA species in their native cellular environment and hence spatially resolved single-cell transcriptomic measurements. However, the relatively modest brightness of signals from single RNA molecules can become limiting in a number of applications, such as increasing the imaging throughput, imaging shorter RNAs, and imaging samples with high degrees of background, such as some tissue samples. Here, we report a branched DNA (bDNA) amplification approach for MERFISH measurements. This approach produces a drastic signal increase in RNA FISH samples without increasing the fluorescent spot size for individual RNAs or increasing the variation in brightness from spot to spot, properties that are important for MERFISH imaging. Using this amplification approach in combination with MERFISH, we demonstrated RNA imaging and profiling with a near 100% detection efficiency. We further demonstrated that signal amplification improves MERFISH performance when fewer FISH probes are used for each RNA species, which should allow shorter RNAs to be imaged. We anticipate that the combination of bDNA amplification with MERFISH should facilitate many other applications and extend the range of biological questions that can be addressed by this technique in both cell culture and tissues.

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.

Multiplane and Spectrally-Resolved Single Molecule Localization Microscopy with Industrial Grade CMOS cameras.

This work explores the use of industrial grade CMOS cameras for single molecule localization microscopy (SMLM). We show that industrial grade CMOS cameras approach the performance of scientific grade CMOS cameras at a fraction of the cost. This makes it more economically feasible to construct high-performance imaging systems with multiple cameras that are capable of a diversity of applications. In particular we demonstrate the use of industrial CMOS cameras for biplane, multiplane and spectrally resolved SMLM. We also provide open-source software for simultaneous control of multiple CMOS cameras and for the reduction of the movies that are acquired to super-resolution images.

Analyzing Single Molecule Localization Microscopy Data Using Cubic Splines.

The resolution of super-resolution microscopy based on single molecule localization is in part determined by the accuracy of the localization algorithm. In most published approaches to date this localization is done by fitting an analytical function that approximates the point spread function (PSF) of the microscope. However, particularly for localization in 3D, analytical functions such as a Gaussian, which are computationally inexpensive, may not accurately capture the PSF shape leading to reduced fitting accuracy. On the other hand, analytical functions that can accurately capture the PSF shape, such as those based on pupil functions, can be computationally expensive. Here we investigate the use of cubic splines as an alternative fitting approach. We demonstrate that cubic splines can capture the shape of any PSF with high accuracy and that they can be used for fitting the PSF with only a 2-3x increase in computation time as compared to Gaussian fitting. We provide an open-source software package that measures the PSF of any microscope and uses the measured PSF to perform 3D single molecule localization microscopy analysis with reasonable accuracy and speed.

Blind sparse inpainting reveals cytoskeletal filaments with sub-Nyquist localization.

Single-molecule localization microscopy (SMLM), such as stochastic optical reconstruction microscopy and (fluorescence) photoactivated localization microscopy, has enabled superresolution microscopy beyond the diffraction limit. However, the temporal resolution of SMLM is limited by the time needed to acquire sufficient sparse single-molecule activation events to successfully construct a superresolution image. Here, a novel fast SMLM technique is developed to achieve superresolution imaging within a much shortened duration. This technique does not require a faster switching rate or a higher activation density, which may cause signal degradation or photodamage/bleaching, but relies on computational algorithms to reconstruct a high-density superresolution image from a low-density one using the concept of blind image inpainting. Our results demonstrate that the technique reduces the acquisition time by up to two orders of magnitude compared to the conventional method while achieving the same high resolution. We anticipate our technique to enable future real-time live cell imaging with even higher resolution.

Correlative stochastic optical reconstruction microscopy and electron microscopy.

Correlative fluorescence light microscopy and electron microscopy allows the imaging of spatial distributions of specific biomolecules in the context of cellular ultrastructure. Recent development of super-resolution fluorescence microscopy allows the location of molecules to be determined with nanometer-scale spatial resolution. However, correlative super-resolution fluorescence microscopy and electron microscopy (EM) still remains challenging because the optimal specimen preparation and imaging conditions for super-resolution fluorescence microscopy and EM are often not compatible. Here, we have developed several experiment protocols for correlative stochastic optical reconstruction microscopy (STORM) and EM methods, both for un-embedded samples by applying EM-specific sample preparations after STORM imaging and for embedded and sectioned samples by optimizing the fluorescence under EM fixation, staining and embedding conditions. We demonstrated these methods using a variety of cellular targets.

Dynamics and configurational fluctuations of single DNA molecules in linear mixed flows.

We examine the dynamics of DNA molecules in mixed flows where the ratio of vorticity to strain rate may be slightly above or below unity via Brownian dynamics simulation. We find that the chain dynamics in these flows are dramatically different than those found for simple shear flow. When the strain rate exceeds vorticity, the dynamics are found to be driven by the extra amount of straining. For vorticity-dominated flows, a periodicity in chain extension is observed with considerable chain deformation.

Developmental mechanism of the periodic membrane skeleton in axons.

Actin, spectrin, and associated molecules form a periodic sub-membrane lattice structure in axons. How this membrane skeleton is developed and why it preferentially forms in axons are unknown. Here, we studied the developmental mechanism of this lattice structure. We found that this structure emerged early during axon development and propagated from proximal regions to distal ends of axons. Components of the axon initial segment were recruited to the lattice late during development. Formation of the lattice was regulated by the local concentration of ßII spectrin, which is higher in axons than in dendrites. Increasing the dendritic concentration of ßII spectrin by overexpression or by knocking out ankyrin B induced the formation of the periodic structure in dendrites, demonstrating that the spectrin concentration is a key determinant in the preferential development of this structure in axons and that ankyrin B is critical for the polarized distribution of ßII spectrin in neurites.