Fast, single-molecule localization that achieves theoretically minimum uncertainty

Universal inverse modeling of point spread functions for SMLM localization and microscope characterization

The point spread function (PSF) of a microscope describes the image of a point emitter. Knowing the accurate PSF model is essential for various imaging tasks, including single-molecule localization, aberration correction and deconvolution. Here we present universal inverse modeling of point spread functions (uiPSF), a toolbox to infer accurate PSF models from microscopy data, using either image stacks of fluorescent beads or directly images of blinking fluorophores, the raw data in single-molecule localization microscopy (SMLM). Our modular framework is applicable to a variety of microscope modalities and the PSF model incorporates system- or sample-specific characteristics, for example, the bead size, field- and depth- dependent aberrations, and transformations among channels. We demonstrate its application in single or multiple channels or large field-of-view SMLM systems, 4Pi-SMLM, and lattice light-sheet microscopes using either bead data or single-molecule blinking data.

Toward drift-free high-throughput nanoscopy through adaptive intersection maximization

Single-molecule localization microscopy (SMLM) often suffers from suboptimal resolution due to imperfect drift correction. Existing marker-free drift correction algorithms often struggle to reliably track high-frequency drift and lack the computational efficiency to manage large, high-throughput localization datasets. We present an adaptive intersection maximization-based method (AIM) that leverages the entire dataset's information content to minimize drift correction errors, particularly addressing high-frequency drift, thereby enhancing the resolution of existing SMLM systems. We demonstrate that AIM can robustly and efficiently achieve an angstrom-level tracking precision for high-throughput SMLM datasets under various imaging conditions, resulting in an optimal resolution in simulated and biological experimental datasets. We offer AIM as one simple, model-free software for instant resolution enhancement with standard CPU devices.

Multiparatopic antibodies induce targeted downregulation of programmed death-ligand 1

Programmed death-ligand 1 (PD-L1) drives inhibition of antigen-specific T cell responses through engagement of its receptor programmed death-1 (PD-1) on activated T cells. Overexpression of these immune checkpoint proteins in the tumor microenvironment has motivated the design of targeted antibodies that disrupt this interaction. Despite clinical success of these antibodies, response rates remain low, necessitating novel approaches to enhance performance. Here, we report the development of antibody fusion proteins that block immune checkpoint pathways through a distinct mechanism targeting molecular trafficking. By engaging multiple receptor epitopes on PD-L1, our engineered multiparatopic antibodies induce rapid clustering, internalization, and degradation in an epitope- and topology-dependent manner. The complementary mechanisms of ligand blockade and receptor downregulation led to more durable immune cell activation and dramatically reduced PD-L1 availability in mouse tumors. Collectively, these multiparatopic antibodies offer mechanistic insight into immune checkpoint protein trafficking and how it may be manipulated to reprogram immune outcomes.

Build and operation of a custom 3D, multicolor, single-molecule localization microscope

Single-molecule localization microscopy (SMLM) enables imaging scientists to visualize biological structures with unprecedented resolution. Particularly powerful implementations of SMLM are capable of three-dimensional, multicolor and high-throughput imaging and can yield key biological insights. However, widespread access to these technologies is limited, primarily by the cost of commercial options and complexity of de novo development of custom systems. Here we provide a comprehensive guide for interested researchers who wish to establish a high-end, custom-built SMLM setup in their laboratories. We detail the initial configuration and subsequent assembly of the SMLM, including the instructions for the alignment of all the optical pathways, the software and hardware integration, and the operation of the instrument. We describe the validation steps, including the preparation and imaging of test and biological samples with structures of well-defined geometries, and assist the user in troubleshooting and benchmarking the system's performance. Additionally, we provide a walkthrough of the reconstruction of a super-resolved dataset from acquired raw images using the Super-resolution Microscopy Analysis Platform. Depending on the instrument configuration, the cost of the components is in the range US$95,000-180,000, similar to other open-source advanced SMLMs, and substantially lower than the cost of a commercial instrument. A builder with some experience of optical systems is expected to require 4-8 months from the start of the system construction to attain high-quality three-dimensional and multicolor biological images.

Quantifying the minimum localization uncertainty of image scanning localization microscopy

Modulation enhanced single-molecule localization microscopy (meSMLM), where emitters are sparsely activated with sequentially applied patterned illumination, increases the localization precision over single-molecule localization microscopy (SMLM). The precision improvement of modulation enhanced SMLM is derived from retrieving the position of an emitter relative to individual illumination patterns, which adds to existing point spread function information from SMLM. Here, we introduce SpinFlux: modulation enhanced localization for spinning disk confocal microscopy. SpinFlux uses a spinning disk with pinholes in its illumination and emission paths, to sequentially illuminate regions in the sample during each measurement. The resulting intensity-modulated emission signal is analyzed for each individual pattern to localize emitters with improved precision. We derive a statistical image formation model for SpinFlux and we quantify the theoretical minimum localization uncertainty in terms of the Cramér-Rao lower bound. Using the theoretical minimum uncertainty, we compare SpinFlux to localization on Fourier reweighted image scanning microscopy reconstructions. We find that localization on image scanning microscopy reconstructions with Fourier reweighting ideally results in a global precision improvement of 2.1 over SMLM. When SpinFlux is used for sequential illumination with three patterns around the emitter position, the localization precision improvement over SMLM is twofold when patterns are focused around the emitter position. If four donut-shaped illumination patterns are used for SpinFlux, the maximum local precision improvement over SMLM is increased to 3.5. Localization of image scanning microscopy reconstructions thus has the largest potential for global improvements of the localization precision, where SpinFlux is the method of choice for local refinements.

Distinct interactions stabilize EGFR dimers and higher-order oligomers in cell membranes

The epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase with important roles in many cellular processes as well as in cancer and other diseases. EGF binding promotes EGFR dimerization and autophosphorylation through interactions that are well understood structurally. How these dimers relate to higher-order EGFR oligomers seen in cell membranes, however, remains unclear. Here, we used single-particle tracking (SPT) and Förster resonance energy transfer imaging to examine how each domain of EGFR contributes to receptor oligomerization and the rate of receptor diffusion in the cell membrane. Although the extracellular region of EGFR is sufficient to drive receptor dimerization, we find that the EGF-induced EGFR slowdown seen by SPT requires higher-order oligomerization-mediated in part by the intracellular tyrosine kinase domain when it adopts an active conformation. Our data thus provide important insight into the interactions required for higher-order EGFR assemblies involved in EGF signaling.

Bayesian posterior density estimation reveals degeneracy in three-dimensional multiple emitter localization

Single-molecule localization microscopy requires sparse activation of emitters to circumvent the diffraction limit. In densely labeled or thick samples, overlap of emitter images is inevitable. Single-molecule localization of these samples results in a biased parameter estimate with a wrong model of the number of emitters. On the other hand, multiple emitter fitting suffers from point spread function degeneracy, which increases model and parameter uncertainty. To better estimate the model, parameters and uncertainties, a three-dimensional Bayesian multiple emitter fitting algorithm was constructed using Reversible Jump Markov Chain Monte Carlo. It reconstructs the posterior density of both the model and the parameters, namely the three-dimensional position and photon intensity, of overlapping emitters. The ability of the algorithm to separate two emitters at varying distance was evaluated using an astigmatic point spread function. We found that for astigmatic imaging, the posterior distribution of the emitter positions is multimodal when emitters are within two times the in-focus standard deviation of the point spread function. This multimodality describes the ambiguity in position that astigmatism introduces in localization microscopy. Biplane imaging was also tested, proving capable of separating emitters up to 0.75 times the in-focus standard deviation of the point spread function while staying free of multimodality. The posteriors seen in astigmatic and biplane imaging demonstrate how the algorithm can identify point spread function degeneracy and evaluate imaging techniques for three-dimensional multiple-emitter fitting performance.

Optimal sampling rate for 3D single molecule localization

Resolution of single molecule localization microscopy (SMLM) depends on the localization accuracy, which can be improved by utilizing engineered point spread functions (PSF) with delicate shapes. However, the intrinsic pixelation effect of the detector sensor will deteriorate PSFs under different sampling rates. The influence of the pixelation effect to the achieved 3D localization accuracy for different PSF shapes under different signal to background ratio (SBR) and pixel dependent readout noise has not been investigated in detail so far. In this work, we proposed a framework to characterize the 3D localization accuracy of pixelated PSF at different sampling rates. Four different PSFs (astigmatic PSF, double helix (DH) PSF, Tetrapod PSF and 4Pi PSF) were evaluated and the pixel size with optimal 3D localization performance were derived. This work provides a theoretical guide for the optimal design of sampling rate for 3D super resolution imaging.

Deep learning-driven adaptive optics for single-molecule localization microscopy

The inhomogeneous refractive indices of biological tissues blur and distort single-molecule emission patterns generating image artifacts and decreasing the achievable resolution of single-molecule localization microscopy (SMLM). Conventional sensorless adaptive optics methods rely on iterative mirror changes and image-quality metrics. However, these metrics result in inconsistent metric responses and thus fundamentally limit their efficacy for aberration correction in tissues. To bypass iterative trial-then-evaluate processes, we developed deep learning-driven adaptive optics for SMLM to allow direct inference of wavefront distortion and near real-time compensation. Our trained deep neural network monitors the individual emission patterns from single-molecule experiments, infers their shared wavefront distortion, feeds the estimates through a dynamic filter and drives a deformable mirror to compensate sample-induced aberrations. We demonstrated that our method simultaneously estimates and compensates 28 wavefront deformation shapes and improves the resolution and fidelity of three-dimensional SMLM through >130-µm-thick brain tissue specimens.

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.

Universal inverse modelling of point spread functions for SMLM localization and microscope characterization

The point spread function (PSF) of a microscope describes the image of a point emitter. Knowing the accurate PSF model is essential for various imaging tasks, including single molecule localization, aberration correction and deconvolution. Here we present uiPSF (universal inverse modelling of Point Spread Functions), a toolbox to infer accurate PSF models from microscopy data, using either image stacks of fluorescent beads or directly images of blinking fluorophores, the raw data in single molecule localization microscopy (SMLM). The resulting PSF model enables accurate 3D super-resolution imaging using SMLM. Additionally, uiPSF can be used to characterize and optimize a microscope system by quantifying the aberrations, including field-dependent aberrations, and resolutions. Our modular framework is applicable to a variety of microscope modalities and the PSF model incorporates system or sample specific characteristics, e.g., the bead size, depth dependent aberrations and transformations among channels. We demonstrate its application in single or multiple channels or large field-of-view SMLM systems, 4Pi-SMLM, and lattice light-sheet microscopes using either bead data or single molecule blinking data.

Dectin-1 multimerization and signaling depends on fungal β-glucan structure and exposure

Dectin-1A is a C-type lectin innate immunoreceptor that recognizes β-(1,3;1,6)-glucan, a structural component of Candida species cell walls. β-Glucans can adopt solution structures ranging from random coil to insoluble fiber due to tertiary (helical) and quaternary structure. Fungal β-glucans of medium and high molecular weight are highly structured, but low molecular weight glucan is much less structured. Despite similar affinity for Dectin-1, the ability of glucans to induce Dectin-1A-mediated signaling correlates with degree of structure. Glucan denaturation experiments showed that glucan structure determines agonistic potential, but not receptor binding affinity. We explored the impact of glucan structure on molecular aggregation of Dectin-1A. Stimulation with glucan signaling decreased Dectin-1A diffusion coefficient. Fluorescence measurements provided direct evidence of ligation-induced Dectin-1A aggregation, which positively correlated with increasing glucan structure content. In contrast, Dectin-1A is predominantly in a low aggregation state in resting cells. Molecular aggregates formed during interaction with highly structured, agonistic glucans did not exceed relatively small (<15 nm) clusters of a few engaged receptors. Finally, we observed increased molecular aggregation of Dectin-1A at fungal particle contact sites in a manner that positively correlated with the degree of exposed glucan on the particle surface. These results indicate that Dectin-1A senses the solution conformation of β-glucans through their varying ability to drive receptor dimer/oligomer formation and activation of membrane proximal signaling events.

Antigen Geometry Tunes Mast Cell Signaling Through Distinct FcεRI Aggregation and Structural Changes

Immunoreceptor tyrosine-based activation motif (ITAM)-containing Fc receptors are critical components of the innate and adaptive immune systems. FcεRI mediates the allergic response via crosslinking of IgE-bound receptors by multivalent antigens. Yet, the underlying molecular mechanisms that govern the response of FcεRI to specific antigens remain poorly understood. We compared responses induced by two antigens with distinct geometries, high valency DNP-BSA and trivalent DF3, and found unique secretion and receptor phosphorylation profiles that are due to differential recruitment of Lyn and SHIP1. To understand how these two antigens can cause such markedly different outcomes, we used direct stochastic optical reconstruction microscopy (dSTORM) super-resolution imaging combined with Bayesian Grouping of Localizations (BaGoL) analysis to compare the nanoscale characteristics of FcεRI aggregates. DF3 aggregates were found to be smaller and more densely packed than DNP-BSA aggregates. Using lifetime-based Förster resonance energy transfer (FRET) measurements, we discovered that FcεRI subunits undergo structural rearrangements upon crosslinking with either antigen, and in response to interaction with monovalent antigen presented on a supported lipid bilayer. The extent of conformational change is positively correlated with signaling efficiency. Finally, we provide evidence for forces in optimizing FcεRI signaling, such that immobilizing DF3 on a rigid surface promoted degranulation while increasing DNP-BSA flexibility lowered degranulation. These results provide a link between the physical attributes of allergens, including size, shape, valency, and flexibility, and FcεRI signaling strength. Thus, the antigen modulates mast cell outcomes by creating unique aggregate geometries that tune FcεRI conformation, phosphorylation and signaling partner recruitment.

Mammalian ATG8 proteins maintain autophagosomal membrane integrity through ESCRTs

The canonical autophagy pathway in mammalian cells sequesters diverse cytoplasmic cargo within the double membrane autophagosomes that eventually convert into degradative compartments via fusion with endolysosomal intermediates. Here, we report that autophagosomal membranes show permeability in cells lacking principal ATG8 proteins (mATG8s) and are unable to mature into autolysosomes. Using a combination of methods including a novel in vitro assay to measure membrane sealing, we uncovered a previously unappreciated function of mATG8s to maintain autophagosomal membranes in a sealed state. The mATG8 proteins GABARAP and LC3A bind to key ESCRT-I components contributing, along with other ESCRTs, to the integrity and imperviousness of autophagic membranes. Autophagic organelles in cells lacking mATG8s are permeant, are arrested as amphisomes, and do not progress to functional autolysosomes. Thus, autophagosomal organelles need to be maintained in a sealed state in order to become lytic autolysosomes.

RegiSTORM: channel registration for multi-color stochastic optical reconstruction microscopy

BACKGROUND

Stochastic optical reconstruction microscopy (STORM), a super-resolution microscopy technique based on single-molecule localizations, has become popular to characterize sub-diffraction limit targets. However, due to lengthy image acquisition, STORM recordings are prone to sample drift. Existing cross-correlation or fiducial marker-based algorithms allow correcting the drift within each channel, but misalignment between channels remains due to interchannel drift accumulating during sequential channel acquisition. This is a major drawback in multi-color STORM, a technique of utmost importance for the characterization of various biological interactions.

RESULTS

We developed RegiSTORM, a software for reducing channel misalignment by accurately registering STORM channels utilizing fiducial markers in the sample. RegiSTORM identifies fiducials from the STORM localization data based on their non-blinking nature and uses them as landmarks for channel registration. We first demonstrated accurate registration on recordings of fiducials only, as evidenced by significantly reduced target registration error with all the tested channel combinations. Next, we validated the performance in a more practically relevant setup on cells multi-stained for tubulin. Finally, we showed that RegiSTORM successfully registers two-color STORM recordings of cargo-loaded lipid nanoparticles without fiducials, demonstrating the broader applicability of this software.

CONCLUSIONS

The developed RegiSTORM software was demonstrated to be able to accurately register multiple STORM channels and is freely available as open-source (MIT license) at https://github.com/oystein676/RegiSTORM.git and https://doi.org/10.5281/zenodo.5509861 (archived), and runs as a standalone executable (Windows) or via Python (Mac OS, Linux).

Nanoscale imaging of quantum dot dimers using time-resolved super-resolution microscopy combined with scanning electron microscopy

Time-resolved super-resolution microscopy was used in conjunction with scanning electron microscopy to image individual colloidal CdSe/CdS semiconductor quantum dots (QD) and QD dimers. The photoluminescence (PL) lifetimes, intensities, and structural parameters were acquired with nanometer scale spatial resolution and sub-nanosecond time resolution. The combination of these two techniques was more powerful than either alone, enabling us to resolve the PL properties of individual QDs within QD dimers as they blinked on and off, measure interparticle distances, and identify QDs that may be participating in energy transfer. The localization precision of our optical imaging technique was ∼3 nm, low enough that the emission from individual QDs within the dimers could be spatially resolved. While the majority of QDs within dimers acted as independent emitters, at least one pair of QDs in our study exhibited lifetime and intensity behaviors consistent with resonance energy transfer from a shorter lifetime and lower intensity donor QD to a longer lifetime and higher intensity acceptor QD. For this case, we demonstrate how the combined super-resolution optical imaging and scanning electron microscopy data can be used to characterize the energy transfer rate.

BNP-Track: A framework for multi-particle superresolved tracking

When tracking fluorescently labeled molecules (termed "emitters") under widefield microscopes, point spread function overlap of neighboring molecules is inevitable in both dilute and especially crowded environments. In such cases, superresolution methods leveraging rare photophysical events to distinguish static targets nearby in space introduce temporal delays that compromise tracking. As we have shown in a companion manuscript, for dynamic targets, information on neighboring fluorescent molecules is encoded as spatial intensity correlations across pixels and temporal correlations in intensity patterns across time frames. We then demonstrated how we used all spatiotemporal correlations encoded in the data to achieve superresolved tracking. That is, we showed the results of full posterior inference over both the number of emitters and their associated tracks simultaneously and self-consistently through Bayesian nonparametrics. In this companion manuscript we focus on testing the robustness of our tracking tool, BNP-Track, across sets of parameter regimes and compare BNP-Track to competing tracking methods in the spirit of a prior Nature Methods tracking competition. We explore additional features of BNP-Track including how a stochastic treatment of background yields greater accuracy in emitter number determination and how BNP-Track corrects for point spread function blur (or "aliasing") introduced by intraframe motion in addition to propagating error originating from myriad sources (such as criss-crossing tracks, out-of-focus particles, pixelation, shot and camera artefact, stochastic background) in posterior inference over emitter numbers and their associated tracks. While head-to-head comparison with other tracking methods is not possible (as competitors cannot simultaneously learn molecule numbers and associated tracks), we can give competing methods some advantages in order to perform approximate head-to-head comparison. We show that even under such optimistic scenarios, BNP-Track is capable of tracking multiple diffraction-limited point emitters conventional tracking methods cannot resolve thereby extending the superresolution paradigm to dynamical targets.

Distinct interactions stabilize EGFR dimers and higher-order oligomers in cell membranes

The epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase (RTK) with important roles in many cellular processes as well as cancer and other diseases. EGF binding promotes EGFR dimerization and autophosphorylation through interactions that are well understood structurally. However, it is not clear how these dimers relate to higher-order EGFR oligomers detected at the cell surface. We used single-particle tracking (SPT) and Förster resonance energy transfer (FRET) imaging to examine how each domain within EGFR contributes to receptor dimerization and the rate of its diffusion in the cell membrane. We show that the EGFR extracellular region is sufficient to drive receptor dimerization, but that the EGF-induced EGFR slow-down seen by SPT requires formation of higher order oligomers, mediated in part by the intracellular tyrosine kinase domain - but only when in its active conformation. Our data thus provide important insight into higher-order EGFR interactions required for EGF signaling.

Automated multi-target super-resolution microscopy with trust regions

We describe a dedicated microscope for automated sequential localization microscopy which we term Sequential Super-resolution Microscope (SeqSRM). This microscope automates precise stage stabilization on the order of 5-10 nanometers and data acquisition of all user-selected cells on a coverslip, limiting user interaction to only cell selection and buffer exchanges during sequential relabeling. We additionally demonstrate that nanometer-scale changes to cell morphology affect the fidelity of the resulting multi-target super-resolution overlay reconstructions generated by sequential super-resolution microscopy, and that regions affected by these shifts can be reliably detected and masked out using brightfield images collected periodically throughout the experiment. The SeqSRM enables automated multi-target imaging on multiple user-selected cells without the need for multiple distinct fluorophores and emission channels, while ensuring that the resulting multi-target localization data accurately reflect the relative organization of the underlying targets.

Measuring the Co-Localization and Dynamics of Mobile Proteins in Live Cells Undergoing Signaling Responses

Single molecule imaging in live cells enables the study of protein interactions and dynamics as they participate in signaling processes. When combined with fluorophores that stochastically transition between fluorescent and reversible dark states, as in super-resolution localization imaging, labeled molecules can be visualized in single cells over time. This improvement in sampling enables the study of extended cellular responses at the resolution of single molecule localization. This chapter provides optimized experimental and analytical methods used to quantify protein interactions and dynamics within the membranes of adhered live cells. Importantly, the use of pair-correlation functions resolved in both space and time allows researchers to probe interactions between proteins on biologically relevant distance and timescales, even though fluorescence localization methods typically require long times to assemble well-sampled reconstructed images. We describe an application of this approach to measure protein interactions in B cell receptor signaling and include sample analysis code for post-processing of imaging data. These methods are quantitative, sensitive, and broadly applicable to a range of signaling systems.

Maximum-likelihood model fitting for quantitative analysis of SMLM data

Quantitative data analysis is important for any single-molecule localization microscopy (SMLM) workflow to extract biological insights from the coordinates of the single fluorophores. However, current approaches are restricted to simple geometries or require identical structures. Here, we present LocMoFit (Localization Model Fit), an open-source framework to fit an arbitrary model to localization coordinates. It extracts meaningful parameters from individual structures and can select the most suitable model. In addition to analyzing complex, heterogeneous and dynamic structures for in situ structural biology, we demonstrate how LocMoFit can assemble multi-protein distribution maps of six nuclear pore components, calculate single-particle averages without any assumption about geometry or symmetry, and perform a time-resolved reconstruction of the highly dynamic endocytic process from static snapshots. We provide extensive simulation and visualization routines to validate the robustness of LocMoFit and tutorials to enable any user to increase the information content they can extract from their SMLM data.

High-precision estimation of emitter positions using Bayesian grouping of localizations

Single-molecule localization microscopy super-resolution methods rely on stochastic blinking/binding events, which often occur multiple times from each emitter over the course of data acquisition. Typically, the blinking/binding events from each emitter are treated as independent events, without an attempt to assign them to a particular emitter. Here, we describe a Bayesian method of inferring the positions of the tagged molecules by exploring the possible grouping and combination of localizations from multiple blinking/binding events. The results are position estimates of the tagged molecules that have improved localization precision and facilitate nanoscale structural insights. The Bayesian framework uses the localization precisions to learn the statistical distribution of the number of blinking/binding events per emitter and infer the number and position of emitters. We demonstrate the method on a range of synthetic data with various emitter densities, DNA origami constructs and biological structures using DNA-PAINT and dSTORM data. We show that under some experimental conditions it is possible to achieve sub-nanometer precision.

Enabling Spectrally Resolved Single-Molecule Localization Microscopy at High Emitter Densities

Single-molecule localization microscopy (SMLM) is a powerful super-resolution technique for elucidating structure and dynamics in the life- and material sciences. Simultaneously acquiring spectral information (spectrally resolved SMLM, sSMLM) has been hampered by several challenges: an increased complexity of the optical detection pathway, lower accessible emitter densities, and compromised spatio-spectral resolution. Here we present a single-component, low-cost implementation of sSMLM that addresses these challenges. Using a low-dispersion transmission grating positioned close to the image plane, the +1^stdiffraction order is minimally elongated and is analyzed using existing single-molecule localization algorithms. The distance between the 0^th and 1^st order provides accurate information on the spectral properties of individual emitters. This method enables a 5-fold higher emitter density while discriminating between fluorophores whose peak emissions are less than 15 nm apart. Our approach can find widespread use in single-molecule applications that rely on distinguishing spectrally different fluorophores under low photon conditions.

Adaptive optics in single objective inclined light sheet microscopy enables three-dimensional localization microscopy in adult Drosophila brains

Single-molecule localization microscopy (SMLM) enables the high-resolution visualization of organelle structures and the precise localization of individual proteins. However, the expected resolution is not achieved in tissue as the imaging conditions deteriorate. Sample-induced aberrations distort the point spread function (PSF), and high background fluorescence decreases the localization precision. Here, we synergistically combine sensorless adaptive optics (AO), in-situ 3D-PSF calibration, and a single-objective lens inclined light sheet microscope (SOLEIL), termed (AO-SOLEIL), to mitigate deep tissue-induced deteriorations. We apply AO-SOLEIL on several dSTORM samples including brains of adult Drosophila. We observed a 2x improvement in the estimated axial localization precision with respect to widefield without aberration correction while we used synergistic solution. AO-SOLEIL enhances the overall imaging resolution and further facilitates the visualization of sub-cellular structures in tissue.

Logic-gated antibody pairs that selectively act on cells co-expressing two antigens

The use of therapeutic monoclonal antibodies is constrained because single antigen targets often do not provide sufficient selectivity to distinguish diseased from healthy tissues. We present HexElect®, an approach to enhance the functional selectivity of therapeutic antibodies by making their activity dependent on clustering after binding to two different antigens expressed on the same target cell. lmmunoglobulin G (lgG)-mediated clustering of membrane receptors naturally occurs on cell surfaces to trigger complement- or cell-mediated effector functions or to initiate intracellular signaling. We engineer the Fc domains of two different lgG antibodies to suppress their individual homo-oligomerization while promoting their pairwise hetero-oligomerization after binding co-expressed antigens. We show that recruitment of complement component C1q to these hetero-oligomers leads to clustering-dependent activation of effector functions such as complement mediated killing of target cells or activation of cell surface receptors. HexElect allows selective antibody activity on target cells expressing unique, potentially unexplored combinations of surface antigens.

GDSC SMLM: Single-molecule localisation microscopy software for ImageJ

Single-molecule localisation microscopy (SMLM) uses software to extract super-resolved positions from microscope images of fluorescent molecules. These localisations can then be used to render super-resolution images or analysed to extract information about molecular behaviour. The GDSC SMLM software provides a set of tools for analysing SMLM data in a single cross-platform environment. The software identifies fluorescent molecules in raw microscope images and localises their positions using stages of spot detection, spot fitting and spot rejection. The resulting localisation data set can then be visualised, cropped and filtered. A suite of downstream analysis tools enable the user to perform single-particle tracking, cluster analysis and drift correction. In addition, GDSC SMLM also provides utility tools that enable modelling of EM-CCD and sCMOS cameras as well as point spread functions (PSFs) for data simulation. The software is written in Java and runs as a collection of plugins for the ImageJ software.

Recovering mixtures of fast-diffusing states from short single-particle trajectories

Single-particle tracking (SPT) directly measures the dynamics of proteins in living cells and is a powerful tool to dissect molecular mechanisms of cellular regulation. Interpretation of SPT with fast-diffusing proteins in mammalian cells, however, is complicated by technical limitations imposed by fast image acquisition. These limitations include short trajectory length due to photobleaching and shallow depth of field, high localization error due to the low photon budget imposed by short integration times, and cell-to-cell variability. To address these issues, we investigated methods inspired by Bayesian nonparametrics to infer distributions of state parameters from SPT data with short trajectories, variable localization precision, and absence of prior knowledge about the number of underlying states. We discuss the advantages and disadvantages of these approaches relative to other frameworks for SPT analysis.

Fast DNA-PAINT imaging using a deep neural network

DNA points accumulation for imaging in nanoscale topography (DNA-PAINT) is a super-resolution technique with relatively easy-to-implement multi-target imaging. However, image acquisition is slow as sufficient statistical data has to be generated from spatio-temporally isolated single emitters. Here, we train the neural network (NN) DeepSTORM to predict fluorophore positions from high emitter density DNA-PAINT data. This achieves image acquisition in one minute. We demonstrate multi-colour super-resolution imaging of structure-conserved semi-thin neuronal tissue and imaging of large samples. This improvement can be integrated into any single-molecule imaging modality to enable fast single-molecule super-resolution microscopy.

Giardial lipid rafts share virulence factors with secreted vesicles and participate in parasitic infection in mice

Giardia lamblia, a protozoan parasite, is a major cause of waterborne infection, worldwide. While the trophozoite form of this parasite induces pathological symptoms in the gut, the cyst form transmits the infection. Since Giardia is a noninvasive parasite, the actual mechanism by which it causes disease remains elusive. We have previously reported that Giardia assembles cholesterol and GM1 glycosphingolipid-enriched lipid rafts (LRs) that participate in encystation and cyst production. To further delineate the role of LRs in pathogenesis, we isolated LRs from Giardia and subjected them to proteomic analysis. Various cellular proteins including potential virulence factors—e.g., giardins, variant surface proteins, arginine deaminases, elongation factors, ornithine carbomyltransferases, and high cysteine-rich membrane proteins—were found to be present in LRs. Since Giardia secretes virulence factors encapsulated in extracellular vesicles (EVs) that induce proinflammatory responses in hosts, EVs released by the parasite were isolated and subjected to nanoparticle tracking and proteomic analysis. Two types of EV—i.e., small vesicles (SVs; <100 nm, exosome-like particles) and large vesicles (LVs; 100–400 nm, microvesicle-like particles)—were identified and found to contain a diverse group of proteins including above potential virulence factors. Although pretreatment of the parasite with two giardial lipid raft (gLR) disruptors, nystatin (27 μM) and oseltamivir (20 μM), altered the expression profiles of virulence factors in LVs and SVs, the effects were more robust in the case of SVs. To examine the potential role of rafts and vesicles in pathogenicity, Giardia-infected mice were treated with oseltamivir (1.5 and 3.0 mg/kg), and the shedding of cysts were monitored. We observed that this drug significantly reduced the parasite load in mice. Taken together, our results suggest that virulence factors partitioning in gLRs, released into the extracellular milieu via SVs and LVs, participate in spread of giardiasis and could be targeted for future drug development.

Estimating the localization spread function of static single-molecule localization microscopy images

Single-molecule localization microscopy (SMLM) permits the visualization of cellular structures an order of magnitude smaller than the diffraction limit of visible light, and an accurate, objective evaluation of the resolution of an SMLM data set is an essential aspect of the image processing and analysis pipeline. Here, we present a simple method to estimate the localization spread function (LSF) of a static SMLM data set directly from acquired localizations, exploiting the correlated dynamics of individual emitters and properties of the pair autocorrelation function evaluated in both time and space. The method is demonstrated on simulated localizations, DNA origami rulers, and cellular structures labeled by dye-conjugated antibodies, DNA-PAINT, or fluorescent fusion proteins. We show that experimentally obtained images have LSFs that are broader than expected from the localization precision alone, due to additional uncertainty accrued when localizing molecules imaged over time.

Enhanced Optical Biosensing by Aerotaxy Ga(As)P Nanowire Platforms Suitable for Scalable Production

Sensitive detection of low-abundance biomolecules is central for diagnostic applications. Semiconductor nanowires can be designed to enhance the fluorescence signal from surface-bound molecules, prospectively improving the limit of optical detection. However, to achieve the desired control of physical dimensions and material properties, one currently uses relatively expensive substrates and slow epitaxy techniques. An alternative approach is aerotaxy, a high-throughput and substrate-free production technique for high-quality semiconductor nanowires. Here, we compare the optical sensing performance of custom-grown aerotaxy-produced Ga(As)P nanowires vertically aligned on a polymer substrate to GaP nanowires batch-produced by epitaxy on GaP substrates. We find that signal enhancement by individual aerotaxy nanowires is comparable to that from epitaxy nanowires and present evidence of single-molecule detection. Platforms based on both types of nanowires show substantially higher normalized-to-blank signal intensity than planar glass surfaces, with the epitaxy platforms performing somewhat better, owing to a higher density of nanowires. With further optimization, aerotaxy nanowires thus offer a pathway to scalable, low-cost production of highly sensitive nanowire-based platforms for optical biosensing applications.

Imaging-based feedback cooling of a levitated nanoparticle

Imaging-based detection of the motion of levitated nanoparticles complements a widely used interferometric detection method, providing a precise and robust way to estimate the position of the particle. Here, we demonstrate a camera-based feedback cooling scheme for a charged nanoparticle levitated in a linear Paul trap. The nanoparticle levitated in vacuum was imaged using a complementary metal-oxide semiconductor (CMOS) camera system. The images were processed in real-time with a microcontroller integrated with a CMOS image sensor. The phase-delayed position signal was fed back to one of the trap electrodes, resulting in cooling by velocity damping. Our study provides a simple and versatile approach applicable for the control of low-frequency mechanical oscillators.

EWI2 prevents EGFR from clustering and endocytosis to reduce tumor cell movement and proliferation

EWI2 is a transmembrane immunoglobulin superfamily (IgSF) protein that physically associates with tetraspanins and integrins. It inhibits cancer cells by influencing the interactions among membrane molecules including the tetraspanins and integrins. The present study revealed that, upon EWI2 silencing or ablation, the elevated movement and proliferation of cancer cells in vitro and increased cancer metastatic potential and malignancy in vivo are associated with (i) increases in clustering, endocytosis, and then activation of EGFR and (ii) enhancement of Erk MAP kinase signaling. These changes in signaling make cancer cells (i) undergo partial epithelial-to-mesenchymal (EMT) for more tumor progression and (ii) proliferate faster for better tumor formation. Inhibition of EGFR or Erk kinase can abrogate the cancer cell phenotypes resulting from EWI2 removal. Thus, to inhibit cancer cells, EWI2 prevents EGFR from clustering and endocytosis to restrain its activation and signaling.

Photon-free (s)CMOS camera characterization for artifact reduction in high- and super-resolution microscopy

Modern implementations of widefield fluorescence microscopy often rely on sCMOS cameras, but this camera architecture inherently features pixel-to-pixel variations. Such variations lead to image artifacts and render quantitative image interpretation difficult. Although a variety of algorithmic corrections exists, they require a thorough characterization of the camera, which typically is not easy to access or perform. Here, we developed a fully automated pipeline for camera characterization based solely on thermally generated signal, and implemented it in the popular open-source software Micro-Manager and ImageJ/Fiji. Besides supplying the conventional camera maps of noise, offset and gain, our pipeline also gives access to dark current and thermal noise as functions of the exposure time. This allowed us to avoid structural bias in single-molecule localization microscopy (SMLM), which without correction is substantial even for scientific-grade, cooled cameras. In addition, our approach enables high-quality 3D super-resolution as well as live-cell time-lapse microscopy with cheap, industry-grade cameras. As our approach for camera characterization does not require any user interventions or additional hardware implementations, numerous correction algorithms that rely on camera characterization become easily applicable.

Global fitting for high-accuracy multi-channel single-molecule localization

Multi-channel detection in single-molecule localization microscopy greatly increases information content for various biological applications. Here, we present globLoc, a graphics processing unit based global fitting algorithm with flexible PSF modeling and parameter sharing, to extract maximum information from multi-channel single molecule data. As signals in multi-channel data are highly correlated, globLoc links parameters such as 3D coordinates or photon counts across channels, improving localization precision and robustness. We show, both in simulations and experiments, that global fitting can substantially improve the 3D localization precision for biplane and 4Pi single-molecule localization microscopy and color assignment for ratiometric multicolor imaging.

SOLEIL: single-objective lens inclined light sheet localization microscopy

High-NA light sheet illumination can improve the resolution of single-molecule localization microscopy (SMLM) by reducing the background fluorescence. These approaches currently require custom-made sample holders or additional specialized objectives, which makes the sample mounting or the optical system complex and therefore reduces the usability of these approaches. Here, we developed a single-objective lens-inclined light sheet microscope (SOLEIL) that is capable of 2D and 3D SMLM in thick samples. SOLEIL combines oblique illumination with point spread function PSF engineering to enable dSTORM imaging in a wide variety of samples. SOLEIL is compatible with standard sample holders and off-the-shelve optics and standard high NA objectives. To accomplish optimal optical sectioning we show that there is an ideal oblique angle and sheet thickness. Furthermore, to show what optical sectioning delivers for SMLM we benchmark SOLEIL against widefield and HILO microscopy with several biological samples. SOLEIL delivers in 15 μm thick Caco2-BBE cells a 374% higher intensity to background ratio and a 54% improvement in the estimated CRLB compared to widefield illumination, and a 184% higher intensity to background ratio and a 20% improvement in the estimated CRLB compared to HILO illumination.

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 (CRLB) 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 5-fold 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.

Time-modulated excitation for enhanced single-molecule localization microscopy

Structured illumination in single-molecule localization microscopy provides new information on the position of molecules and thus improves the localization precision compared to standard localization methods. Here, we used a time-shifted sinusoidal excitation pattern to modulate the fluorescence signal of the molecules whose position information is carried by the phase and recovered by synchronous demodulation. We designed two flexible fast demodulation systems located upstream of the camera, allowing us to overcome the limiting camera acquisition frequency and thus to maximize the collection of photons in the demodulation process. The temporally modulated fluorescence signal was then sampled synchronously on the same image, repeatedly during acquisition. This microscopy, called ModLoc, allows us to experimentally improve the localization precision by a factor of 2.4 in one direction, compared to classical Gaussian fitting methods. A temporal study and an experimental demonstration both show that the short lifetimes of the molecules in blinking regimes impose a modulation frequency in the kilohertz range, which is beyond the reach of current cameras. A demodulation system operating at these frequencies would thus be necessary to take full advantage of this new localization approach.

This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 2)'.

Molecular-Scale Dynamics of Long Range Retrograde Brain-Derived Neurotrophic Factor Transport Shaped by Cellular Spatial Context

Retrograde neurotrophin (NT) transport is a specialized form of signal transduction used to conduct information from axons to the cell bodies of central and peripheral nervous system neurons. It is activated upon NT-Trk receptor binding, NT-Trk internalization into signaling endosomes, and their motion along the axon toward the cell body. Brain-derived neurotrophic factor (BDNF) is an abundant NT that modulates key brain and spinal cord functions, and defects in BDNF trafficking are associated with neuronal death, neurodegenerative diseases and in nerve injury. Decades of study have yielded impressive progress in elucidating NT retrograde transport; however, much information remains unclear. For example, while it is known that NT function is dependent on tight control of NT-receptor intracellular trafficking, data describing the precise spatiotemporal molecular dynamics of their axonal to somatic transport are lacking. In past work, we showed the use of discrete, photo-bleaching-resistant quantum dot (QD)-BNDF probes to activate and track BDNF-TrkB receptor internalization; this revealed a rich diversity of molecular motions that intracellular BDNF signaling endosomes undergo within the soma of nodose ganglia sensory neurons. Here, we used combined techniques of discrete QD-BDNF tracking with compartmented microfluidic chambers to characterize retrograde BDNF-TrkB transport over long-ranging distances of primary dorsal root ganglion sensory neuronal axons. Our new findings show that axonal retrograde motion is comprised of heterogeneous mixtures of diffusive behaviors, pauses, and variations in net molecular-motor-dependent transport speeds. Notably, specific molecular dynamic features such as NT speed were dependent on spatial context that could be categorized in distance from distal axons and proximity to the soma and were not entirely dictated by active motor transport speed. The important implication is recognition that NT-receptor retrograde transport is comprised of molecular dynamics, which change over the course of long-range trafficking to shape overall transport and possibly signaling.

Robust and bias-free localization of individual fixed dipole emitters achieving the Cramér Rao bound for applications in cryo-single molecule localization microscopy

Single molecule localization microscopy (SMLM) has the potential to resolve structural details of biological samples at the nanometer length scale. Compared to room temperature experiments, SMLM performed under cryogenic temperature achieves higher photon yields and, hence, higher localization precision. However, to fully exploit the resolution it is crucial to account for the anisotropic emission characteristics of fluorescence dipole emitters with fixed orientation. In case of slight residual defocus, localization estimates may well be biased by tens of nanometers. We show here that astigmatic imaging in combination with information about the dipole orientation allows to extract the position of the dipole emitters without localization bias and down to a precision of 1 nm, thereby reaching the corresponding Cramér Rao bound. The approach is showcased with simulated data for various dipole orientations, and parameter settings realistic for real life experiments.

Raw Data to Results: A Hands-On Introduction and Overview of Computational Analysis for Single-Molecule Localization Microscopy

Single-molecule localization microscopy (SMLM) is an advanced microscopy method that uses the blinking of fluorescent molecules to determine the position of these molecules with a resolution below the diffraction limit (∼5-40 nm). While SMLM imaging itself is becoming more popular, the computational analysis surrounding the technique is still a specialized area and often remains a "black box" for experimental researchers. Here, we provide an introduction to the required computational analysis of SMLM imaging, post-processing and typical data analysis. Importantly, user-friendly, ready-to-use and well-documented code in Python and MATLAB with exemplary data is provided as an interactive experience for the reader, as well as a starting point for further analysis. Our code is supplemented by descriptions of the computational problems and their implementation. We discuss the state of the art in computational methods and software suites used in SMLM imaging and data analysis. Finally, we give an outlook into further computational challenges in the field.

Technological advances in super-resolution microscopy to study cellular processes

Since its initial demonstration in 2000, far-field super-resolution light microscopy has undergone tremendous technological developments. In parallel, these developments have opened a new window into visualizing the inner life of cells at unprecedented levels of detail. Here, we review the technical details behind the most common implementations of super-resolution microscopy and highlight some of the recent, promising advances in this field.

Super-Resolution Microscopy and Tracking of DNA-Binding Proteins in Bacterial Cells

The ability to detect individual fluorescent molecules inside living cells has enabled a range of powerful microscopy techniques that resolve biological processes on the molecular scale. These methods have also transformed the study of bacterial cell biology, which was previously obstructed by the limited spatial resolution of conventional microscopy. In the case of DNA-binding proteins, super-resolution microscopy can visualize the detailed spatial organization of DNA replication, transcription, and repair processes by reconstructing a map of single-molecule localizations. Furthermore, DNA-binding activities can be observed directly by tracking protein movement in real time. This allows identifying subpopulations of DNA-bound and diffusing proteins, and can be used to measure DNA-binding times in vivo. This chapter provides a detailed protocol for super-resolution microscopy and tracking of DNA-binding proteins in Escherichia coli cells. The protocol covers the genetic engineering and fluorescent labeling of strains and describes data acquisition and analysis procedures, such as super-resolution image reconstruction, mapping single-molecule tracks, computing diffusion coefficients to identify molecular subpopulations with different mobility, and analysis of DNA-binding kinetics. While the focus is on the study of bacterial chromosome biology, these approaches are generally applicable to other molecular processes and cell types.

Three-dimensional diffusion coefficient measurement by a large depth-of-field rotating point spread function

A prominent challenge in single-molecule localization microscopy is the real-time, fast, and accurate localization of nano-objects moving in three-dimensional (3D) samples. A well-established method for 3D single-molecule localization is the double-helix pointspread-function (DH-PSF) engineering, which uses additional optical elements to make the PSF exhibit different rotation angles with different nanoparticle depths. However, the compact main lobe size, effective detection depth, and precise conversion between rotation angle and depth are necessary, posing challenges to the DH-PSF generation method. Here we generate a more compact DH-PSF using Fresnel-zone-based spiral phases, and the pure phase mask achieves high transmission efficiency. The final generated DH-PSFs have a linear rotation rate at each axial position, showing a more accurate rotation angle and depth conversion. The Cramer-Rao lower limit calculation results show that the axial depth of DH-PSF extends to ∼11µm with an axial localization precision of ∼45nm at 3000 photons and average background noise of 15. We measured the diffusion coefficient of nanospheres in different concentrations of glycerol using the generated DH-PSF. The measured results are within 6% error from the theoretical values, indicating the superior performance of the DH-PSF for nanoparticle diffusion coefficient measurements.

Robust emitter localization with enhanced harmonic analysis

We present a non-iterative and model-free algorithm for three-dimensional (3D) single emitter localization. Our algorithm decodes the axial position and the emitter width via the ratio of the first and second Fourier harmonic. The retrieved width information is further used for dynamic extraction of the proper region of interest to robustly eliminate the outer noisy background, thus improving the localization precision over existing non-iterative algorithms. Using simulated and experimental datasets, we demonstrate that our algorithm achieves localization precision approaching the state-of-the-art iterative fitting-based methods in all three dimensions at two orders of magnitude faster speed, applicable in various 3D single-molecule localization techniques.

Super-resolution imaging to reveal the nanostructure of tripartite synapses

Even though neurons are the main drivers of information processing in the brain and spinal cord, other cell types are important to mediate adequate flow of information. These include electrically passive glial cells such as microglia and astrocytes, which recently emerged as active partners facilitating proper signal transduction. In disease, these cells undergo pathophysiological changes that propel disease progression and change synaptic connections and signal transmission. In the healthy brain, astrocytic processes contact pre- and postsynaptic structures. These processes can be nanoscopic, and therefore only electron microscopy has been able to reveal their structure and morphology. However, electron microscopy is not suitable in revealing dynamic changes, and it is labour- and time-intensive. The dawn of super-resolution microscopy, techniques that 'break' the diffraction limit of conventional light microscopy, over the last decades has enabled researchers to reveal the nanoscopic synaptic environment. In this review, we highlight and discuss recent advances in our understanding of the nano-world of the so-called tripartite synapses, the relationship between pre- and postsynapse as well as astrocytic processes. Overall, novel super-resolution microscopy methods are needed to fully illuminate the intimate relationship between glia and neuronal cells that underlies signal transduction in the brain and that might be affected in diseases such as Alzheimer's disease and epilepsy.

Theoretical minimum uncertainty of single-molecule localizations using a single-photon avalanche diode array

Single-photon avalanche diode (SPAD) arrays can be used for single-molecule localization microscopy (SMLM) because of their high frame rate and lack of readout noise. SPAD arrays have a binary frame output, which means photon arrivals should be described as a binomial process rather than a Poissonian process. Consequentially, the theoretical minimum uncertainty of the localizations is not accurately predicted by the Poissonian Cramér-Rao lower bound (CRLB). Here, we derive a binomial CRLB and benchmark it using simulated and experimental data. We show that if the expected photon count is larger than one for all pixels within one standard deviation of a Gaussian point spread function, the binomial CRLB gives a 46% higher theoretical uncertainty than the Poissonian CRLB. For typical SMLM photon fluxes, where no saturation occurs, the binomial CRLB predicts the same uncertainty as the Poissonian CRLB. Therefore, the binomial CRLB can be used to predict and benchmark localization uncertainty for SMLM with SPAD arrays for all practical emitter intensities.

Spatiotemporal Clustering of Repeated Super-Resolution Localizations via Linear Assignment Problem

Many fluorescence super-resolution techniques, such as (d)STORM, PALM, and DNA-PAINT, generate datasets wherein multiple localizations across many camera frames may arise from a single blinking event of an emitter. These repeated localizations not only hinder interpretation and analysis of such datasets, but also represent an incomplete use of the fluorescence photons. Such localizations are typically combined into a single localization either by clustering with hard distance and time thresholds, or by classical hypothesis testing assuming Gaussian localization errors. In this work, we describe a method for clustering that accounts for localization precision, local emitter density estimates, and a kinetic model for blinking which is used to optimize connections within a group of spatiotemporally colocated localizations.

Direct visualization of bottlebrush polymer conformations in the solid state

Although the behavior of single chains is integral to the foundation of polymer science, a clear and convincing image of single chains in the solid state has still not been captured. For bottlebrush polymers, understanding their conformation in bulk materials is especially important because their extended backbones may explain their self-assembly and mechanical properties that have been attractive for many applications. Here, single-bottlebrush chains are visualized using single-molecule localization microscopy to study their conformations in a polymer melt composed of linear polymers. By observing bottlebrush polymers with different side chain lengths and grafting densities, we observe the relationship between molecular architecture and conformation. We show that bottlebrushes are significantly more rigid in the solid state than previously measured in solution, and the scaling relationships between persistence length and side chain length deviate from those predicted by theory and simulation. We discuss these discrepancies using mechanisms inspired by polymer-grafted nanoparticles, a conceptually similar system. Our work provides a platform for visualizing single-polymer chains in an environment made up entirely of other polymers, which could answer a number of open questions in polymer science.