Video-rate nanoscopy using sCMOS camera-specific single-molecule localization algorithms

Approaching Maximum Resolution in Structured Illumination Microscopy via Accurate Noise Modeling

Biological images captured by microscopes are characterized by heterogeneous signal-to-noise ratios (SNRs) due to spatially varying photon emission across the field of view convoluted with camera noise. State-of-the-art unsupervised structured illumination microscopy (SIM) reconstruction algorithms, commonly implemented in the Fourier domain, do not accurately model this noise and suffer from high-frequency artifacts, user-dependent choices of smoothness constraints making assumptions on biological features, and unphysical negative values in the recovered fluorescence intensity map. On the other hand, supervised methods rely on large datasets for training, and often require retraining for new sample structures. Consequently, achieving high contrast near the maximum theoretical resolution in an unsupervised, physically principled, manner remains an open problem. Here, we propose Bayesian-SIM (B-SIM), an unsupervised Bayesian framework to quantitatively reconstruct SIM data, rectifying these shortcomings by accurately incorporating known noise sources in the spatial domain. To accelerate the reconstruction process, we use the finite extent of the point-spread-function to devise a parallelized Monte Carlo strategy involving chunking and restitching of the inferred fluorescence intensity. We benchmark our framework on both simulated and experimental images, and demonstrate improved contrast permitting feature recovery at up to 25% shorter length scales over state-of-the-art methods at both high- and low-SNR. B-SIM enables unsupervised, quantitative, physically accurate reconstruction without the need for labeled training data, democratizing high-quality SIM reconstruction and expands the capabilities of live-cell SIM to lower SNR, potentially revealing biological features in previously inaccessible regimes.

High-speed optical imaging with sCMOS pixel reassignment

Fluorescence microscopy has undergone rapid advancements, offering unprecedented visualization of biological events and shedding light on the intricate mechanisms governing living organisms. However, the exploration of rapid biological dynamics still poses a significant challenge due to the limitations of current digital camera architectures and the inherent compromise between imaging speed and other capabilities. Here, we introduce sHAPR, a high-speed acquisition technique that leverages the operating principles of sCMOS cameras to capture fast cellular and subcellular processes. sHAPR harnesses custom fiber optics to convert microscopy images into one-dimensional recordings, enabling acquisition at the maximum camera readout rate, typically between 25 and 250 kHz. We have demonstrated the utility of sHAPR with a variety of phantom and dynamic systems, including high-throughput flow cytometry, cardiomyocyte contraction, and neuronal calcium waves, using a standard epi-fluorescence microscope. sHAPR is highly adaptable and can be integrated into existing microscopy systems without requiring extensive platform modifications. This method pushes the boundaries of current fluorescence imaging capabilities, opening up new avenues for investigating high-speed biological phenomena.

Decreasing microtubule detyrosination modulates Nav1.5 subcellular distribution and restores sodium current in mdx cardiomyocytes

AIMS

The microtubule (MT) network plays a major role in the transport of the cardiac sodium channel Nav1.5 to the membrane, where the latter associates with interacting proteins such as dystrophin. Alterations in MT dynamics are known to impact on ion channel trafficking. Duchenne muscular dystrophy (DMD), caused by dystrophin deficiency, is associated with an increase in MT detyrosination, decreased sodium current (INa), and arrhythmias. Parthenolide (PTL), a compound that decreases MT detyrosination, has shown beneficial effects on cardiac function in DMD. We here investigated its impact on INa and Nav1.5 subcellular distribution.

METHODS AND RESULTS

Ventricular cardiomyocytes (CMs) from wild-type (WT) and mdx (DMD) mice were incubated with either 10 µM PTL, 20 µM EpoY, or dimethylsulfoxide (DMSO) for 3-5 h, followed by patch-clamp analysis to assess INa and action potential (AP) characteristics in addition to immunofluorescence and stochastic optical reconstruction microscopy (STORM) to investigate MT detyrosination and Nav1.5 cluster size and density, respectively. In accordance with previous studies, we observed increased MT detyrosination, decreased INa and reduced AP upstroke velocity (Vmax) in mdx CMs compared to WT. PTL decreased MT detyrosination and significantly increased INa magnitude (without affecting INa gating properties) and AP Vmax in mdx CMs, but had no effect in WT CMs. Moreover, STORM analysis showed that in mdx CMs, Nav1.5 clusters were decreased not only in the grooves of the lateral membrane (LM; where dystrophin is localized) but also at the LM crests. PTL restored Nav1.5 clusters at the LM crests (but not at the grooves), indicating a dystrophin-independent trafficking route to this subcellular domain. Interestingly, Nav1.5 cluster density was also reduced at the intercalated disc (ID) region of mdx CMs, which was restored to WT levels by PTL. Treatment of mdx CMs with EpoY, a specific MT detyrosination inhibitor, also increased INa density, while decreasing the amount of detyrosinated MTs, confirming a direct mechanistic link.

CONCLUSION

Attenuating MT detyrosination in mdx CMs restored INa and enhanced Nav1.5 localization at the LM crest and ID. Hence, the reduced whole-cell INa density characteristic of mdx CMs is not only the consequence of the lack of dystrophin within the LM grooves but is also due to reduced Nav1.5 at the LM crest and ID secondary to increased baseline MT detyrosination. Overall, our findings identify MT detyrosination as a potential therapeutic target for modulating INa and subcellular Nav1.5 distribution in pathophysiological conditions.

Ultra-high spatio-temporal resolution imaging with parallel acquisition-readout structured illumination microscopy (PAR-SIM)

Structured illumination microscopy (SIM) has emerged as a promising super-resolution fluorescence imaging technique, offering diverse configurations and computational strategies to mitigate phototoxicity during real-time imaging of biological specimens. Traditional efforts to enhance system frame rates have concentrated on processing algorithms, like rolling reconstruction or reduced frame reconstruction, or on investments in costly sCMOS cameras with accelerated row readout rates. In this article, we introduce an approach to elevate SIM frame rates and region of interest (ROI) coverage at the hardware level, without necessitating an upsurge in camera expenses or intricate algorithms. Here, parallel acquisition-readout SIM (PAR-SIM) achieves the highest imaging speed for fluorescence imaging at currently available detector sensitivity. By using the full frame-width of the detector through synchronizing the pattern generation and image exposure-readout process, we have achieved a fundamentally stupendous information spatial-temporal flux of 132.9 MPixels · s-1, 9.6-fold that of the latest techniques, with the lowest SNR of -2.11 dB and 100 nm resolution. PAR-SIM demonstrates its proficiency in successfully reconstructing diverse cellular organelles in dual excitations, even under conditions of low signal due to ultra-short exposure times. Notably, mitochondrial dynamic tubulation and ongoing membrane fusion processes have been captured in live COS-7 cell, recorded with PAR-SIM at an impressive 408 Hz. We posit that this novel parallel exposure-readout mode not only augments SIM pattern modulation for superior frame rates but also holds the potential to benefit other complex imaging systems with a strategic controlling approach.

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.

A statistical resolution measure of fluorescence microscopy with finite photons

First discovered by Ernest Abbe in 1873, the resolution limit of a far-field microscope is considered determined by the numerical aperture and wavelength of light, approximatelyλ 2 N A . With the advent of modern fluorescence microscopy and nanoscopy methods over the last century, this definition is insufficient to fully describe a microscope's resolving power. To determine the practical resolution limit of a fluorescence microscope, photon noise remains one essential factor yet to be incorporated in a statistics-based theoretical framework. We proposed an information density measure quantifying the theoretical resolving power of a fluorescence microscope in the condition of finite photons. The developed approach not only allows us to quantify the practical resolution limit of various fluorescence and super-resolution microscopy modalities but also offers the potential to predict the achievable resolution of a microscopy design under different photon levels.

RASP: Optimal Single Puncta Detection in Complex Cellular Backgrounds

Super-resolution and single-molecule microscopies have been increasingly applied to complex biological systems. A major challenge of these approaches is that fluorescent puncta must be detected in the low signal, high noise, heterogeneous background environments of cells and tissue. We present RASP, Radiality Analysis of Single Puncta, a bioimaging-segmentation method that solves this problem. RASP removes false-positive puncta that other analysis methods detect and detects features over a broad range of spatial scales: from single proteins to complex cell phenotypes. RASP outperforms the state-of-the-art methods in precision and speed using image gradients to separate Gaussian-shaped objects from the background. We demonstrate RASP's power by showing that it can extract spatial correlations between microglia, neurons, and α-synuclein oligomers in the human brain. This sensitive, computationally efficient approach enables fluorescent puncta and cellular features to be distinguished in cellular and tissue environments, with sensitivity down to the level of the single protein. Python and MATLAB codes, enabling users to perform this RASP analysis on their own data, are provided as Supporting Information and links to third-party repositories.

Latest assessment methods for mitochondrial homeostasis in cognitive diseases

Mitochondria play an essential role in neural function, such as supporting normal energy metabolism, regulating reactive oxygen species, buffering physiological calcium loads, and maintaining the balance of morphology, subcellular distribution, and overall health through mitochondrial dynamics. Given the recent technological advances in the assessment of mitochondrial structure and functions, mitochondrial dysfunction has been regarded as the early and key pathophysiological mechanism of cognitive disorders such as Alzheimer's disease, Parkinson's disease, Huntington's disease, mild cognitive impairment, and postoperative cognitive dysfunction. This review will focus on the recent advances in mitochondrial medicine and research methodology in the field of cognitive sciences, from the perspectives of energy metabolism, oxidative stress, calcium homeostasis, and mitochondrial dynamics (including fission-fusion, transport, and mitophagy).

Protocol for single-molecule labeling and tracking of bacterial cell division proteins

Here, we present a protocol for labeling and tracking individual molecules, particularly cell division proteins in live bacterial cells. The protocol encompasses strain construction, single-molecule imaging, trajectory segmentation, and motion property analysis. The protocol enables the identification of distinctive motion states associated with different cell division proteins. Subsequent assessments of the dynamic behaviors of these proteins provide insights into their activities and interactions at the septum during cell division. For complete details on the use and execution of this protocol, please refer to Yang et al. (2021),1 Lyu et al. (2022),2 and Mahone et al. (2024).3.

Inactive Parp2 causes Tp53-dependent lethal anemia by blocking replication-associated nick ligation in erythroblasts

PARP1&2 enzymatic inhibitors (PARPi) are promising cancer treatments. But recently, their use has been hindered by unexplained severe anemia and treatment-related leukemia. In addition to enzymatic inhibition, PARPi also trap PARP1&2 at DNA lesions. Here, we report that unlike Parp2 -/- mice, which develop normally, mice expressing catalytically-inactive Parp2 (E534A, Parp2 EA/EA ) succumb to Tp53- and Chk2 -dependent erythropoietic failure in utero , mirroring Lig1 -/- mice. While DNA damage mainly activates PARP1, we demonstrate that DNA replication activates PARP2 robustly. PARP2 is selectively recruited and activated by 5'-phosphorylated nicks (5'p-nicks) between Okazaki fragments, typically resolved by Lig1. Inactive PARP2, but not its active form or absence, impedes Lig1- and Lig3-mediated ligation, causing dose-dependent replication fork collapse, particularly harmful to erythroblasts with ultra-fast forks. This PARylation-dependent structural function of PARP2 at 5'p-nicks explains the detrimental effects of PARP2 inhibition on erythropoiesis, revealing the mechanism behind the PARPi-induced anemia and leukemia, especially those with TP53/CHK2 loss.

Significance

This work shows that the hematological toxicities associated with PARP inhibitors stem not from impaired PARP1 or PARP2 enzymatic activity but rather from the presence of inactive PARP2 protein. Mechanistically, these toxicities reflect a unique role of PARP2 at 5'-phosphorylated DNA nicks during DNA replication in erythroblasts.

Nanoscale organization of the endogenous ASC speck

The NLRP3 inflammasome is a central component of the innate immune system. Its activation leads to formation of the ASC speck, a supramolecular assembly of the inflammasome adaptor protein ASC. Different models, based on ASC overexpression, have been proposed for the structure of the ASC speck. Using dual-color 3D super-resolution imaging (dSTORM and DNA-PAINT), we visualized the ASC speck structure following NLRP3 inflammasome activation using endogenous ASC expression. A complete structure was only obtainable by labeling with both anti-ASC antibodies and nanobodies. The complex varies in diameter between ∼800 and 1000 nm, and is composed of a dense core with emerging filaments. Dual-color confocal fluorescence microscopy indicated that the ASC speck does not colocalize with the microtubule-organizing center at late time points after Nigericin stimulation. From super-resolution images of whole cells, the ASC specks were sorted into a pseudo-time sequence indicating that they become denser but not larger during formation.

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.

Stepwise requirements for polymerases δ and θ in theta-mediated end joining

Timely repair of chromosomal double-strand breaks is required for genome integrity and cellular viability. The polymerase theta-mediated end joining pathway has an important role in resolving these breaks and is essential in cancers defective in other DNA repair pathways, thus making it an emerging therapeutic target1. It requires annealing of 2-6 nucleotides of complementary sequence, microhomologies, that are adjacent to the broken ends, followed by initiation of end-bridging DNA synthesis by polymerase θ. However, the other pathway steps remain inadequately defined, and the enzymes required for them are unknown. Here we demonstrate requirements for exonucleolytic digestion of unpaired 3' tails before polymerase θ can initiate synthesis, then a switch to a more accurate, processive and strand-displacing polymerase to complete repair. We show the replicative polymerase, polymerase δ, is required for both steps; its 3' to 5' exonuclease activity for flap trimming, then its polymerase activity for extension and completion of repair. The enzymatic steps that are essential and specific to this pathway are mediated by two separate, sequential engagements of the two polymerases. The requisite coupling of these steps together is likely to be facilitated by physical association of the two polymerases. This pairing of polymerase δ with a polymerase capable of end-bridging synthesis, polymerase θ, may help to explain why the normally high-fidelity polymerase δ participates in genome destabilizing processes such as mitotic DNA synthesis2 and microhomology-mediated break-induced replication3.

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.

Fluorescence Microscopy: a statistics-optics perspective

Fundamental properties of light unavoidably impose features on images collected using fluorescence microscopes. Modeling these features is ever more important in quantitatively interpreting microscopy images collected at scales on par or smaller than light's wavelength. Here we review the optics responsible for generating fluorescent images, fluorophore properties, microscopy modalities leveraging properties of both light and fluorophores, in addition to the necessarily probabilistic modeling tools imposed by the stochastic nature of light and measurement.

Optimal sparsity allows reliable system-aware restoration of fluorescence microscopy images

Fluorescence microscopy is one of the most indispensable and informative driving forces for biological research, but the extent of observable biological phenomena is essentially determined by the content and quality of the acquired images. To address the different noise sources that can degrade these images, we introduce an algorithm for multiscale image restoration through optimally sparse representation (MIRO). MIRO is a deterministic framework that models the acquisition process and uses pixelwise noise correction to improve image quality. Our study demonstrates that this approach yields a remarkable restoration of the fluorescence signal for a wide range of microscopy systems, regardless of the detector used (e.g., electron-multiplying charge-coupled device, scientific complementary metal-oxide semiconductor, or photomultiplier tube). MIRO improves current imaging capabilities, enabling fast, low-light optical microscopy, accurate image analysis, and robust machine intelligence when integrated with deep neural networks. This expands the range of biological knowledge that can be obtained from fluorescence microscopy.

Investigating Uncertainties in Single-Molecule Localization Microscopy Using Experimentally Informed Monte Carlo Simulation

Single-molecule localization microscopy (SMLM) enables the visualization of cellular nanostructures in vitro with sub-20 nm resolution. While substructures can generally be imaged with SMLM, the structural understanding of the images remains elusive. To better understand the link between SMLM images and the underlying structure, we developed a Monte Carlo (MC) simulation based on experimental imaging parameters and geometric information to generate synthetic SMLM images. We chose the nuclear pore complex (NPC), a nanosized channel on the nuclear membrane which gates nucleo-cytoplasmic transport of biomolecules, as a test geometry for testing our MC model. Using the MC model to simulate SMLM images, we first optimized our clustering algorithm to separate >106 molecular localizations of fluorescently labeled NPC proteins into hundreds of individual NPCs in each cell. We then illustrated using our MC model to generate cellular substructures with different angles of labeling to inform our structural understanding through the SMLM images obtained.

Single-molecule tracking to determine the abundances and stoichiometries of freely-diffusing protein complexes in living cells: Past applications and future prospects

Most biological processes in living cells rely on interactions between proteins. Live-cell compatible approaches that can quantify to what extent a given protein participates in homo- and hetero-oligomeric complexes of different size and subunit composition are therefore critical to advance our understanding of how cellular physiology is governed by these molecular interactions. Biomolecular complex formation changes the diffusion coefficient of constituent proteins, and these changes can be measured using fluorescence microscopy-based approaches, such as single-molecule tracking, fluorescence correlation spectroscopy, and fluorescence recovery after photobleaching. In this review, we focus on the use of single-molecule tracking to identify, resolve, and quantify the presence of freely-diffusing proteins and protein complexes in living cells. We compare and contrast different data analysis methods that are currently employed in the field and discuss experimental designs that can aid the interpretation of the obtained results. Comparisons of diffusion rates for different proteins and protein complexes in intracellular aqueous environments reported in the recent literature reveal a clear and systematic deviation from the Stokes-Einstein diffusion theory. While a complete and quantitative theoretical explanation of why such deviations manifest is missing, the available data suggest the possibility of weighing freely-diffusing proteins and protein complexes in living cells by measuring their diffusion coefficients. Mapping individual diffusive states to protein complexes of defined molecular weight, subunit stoichiometry, and structure promises to provide key new insights into how protein-protein interactions regulate protein conformational, translational, and rotational dynamics, and ultimately protein function.

Single-frame deep-learning super-resolution microscopy for intracellular dynamics imaging

Single-molecule localization microscopy (SMLM) can be used to resolve subcellular structures and achieve a tenfold improvement in spatial resolution compared to that obtained by conventional fluorescence microscopy. However, the separation of single-molecule fluorescence events that requires thousands of frames dramatically increases the image acquisition time and phototoxicity, impeding the observation of instantaneous intracellular dynamics. Here we develop a deep-learning based single-frame super-resolution microscopy (SFSRM) method which utilizes a subpixel edge map and a multicomponent optimization strategy to guide the neural network to reconstruct a super-resolution image from a single frame of a diffraction-limited image. Under a tolerable signal density and an affordable signal-to-noise ratio, SFSRM enables high-fidelity live-cell imaging with spatiotemporal resolutions of 30 nm and 10 ms, allowing for prolonged monitoring of subcellular dynamics such as interplays between mitochondria and endoplasmic reticulum, the vesicle transport along microtubules, and the endosome fusion and fission. Moreover, its adaptability to different microscopes and spectra makes it a useful tool for various imaging systems.

Quantitative fluorescence emission anisotropy microscopy for implementing homo-fluorescence resonance energy transfer measurements in living cells

Quantitative fluorescence emission anisotropy microscopy reveals the organization of fluorescently labeled cellular components and allows their characterization in terms of changes in either rotational diffusion or homo-Förster's energy transfer characteristics in living cells. These properties provide insights into molecular organization, such as orientation, confinement, and oligomerization in situ. Here we elucidate how quantitative measurements of anisotropy using multiple microscope systems may be made by bringing out the main parameters that influence the quantification of fluorescence emission anisotropy. We focus on a variety of parameters that contribute to errors associated with the measurement of emission anisotropy in a microscope. These include the requirement for adequate photon counts for the necessary discrimination of anisotropy values, the influence of extinction ratios of the illumination source, the detector system, the role of numerical aperture, and excitation wavelength. All these parameters also affect the ability to capture the dynamic range of emission anisotropy necessary for quantifying its reduction due to homo-FRET and other processes. Finally, we provide easily implementable tests to assess whether homo-FRET is a cause for the observed emission depolarization.

Rapid detection of neurons in widefield calcium imaging datasets after training with synthetic data

Widefield microscopy can provide optical access to multi-millimeter fields of view and thousands of neurons in mammalian brains at video rate. However, tissue scattering and background contamination results in signal deterioration, making the extraction of neuronal activity challenging, laborious and time consuming. Here we present our deep-learning-based widefield neuron finder (DeepWonder), which is trained by simulated functional recordings and effectively works on experimental data to achieve high-fidelity neuronal extraction. Equipped with systematic background contribution priors, DeepWonder conducts neuronal inference with an order-of-magnitude-faster speed and improved accuracy compared with alternative approaches. DeepWonder removes background contaminations and is computationally efficient. Specifically, DeepWonder accomplishes 50-fold signal-to-background ratio enhancement when processing terabytes-scale cortex-wide functional recordings, with over 14,000 neurons extracted in 17 h.

Uncovering the cytotoxic effects of air pollution with multi-modal imaging of in vitro respiratory models

Annually, an estimated seven million deaths are linked to exposure to airborne pollutants. Despite extensive epidemiological evidence supporting clear associations between poor air quality and a range of short- and long-term health effects, there are considerable gaps in our understanding of the specific mechanisms by which pollutant exposure induces adverse biological responses at the cellular and tissue levels. The development of more complex, predictive, in vitro respiratory models, including two- and three-dimensional cell cultures, spheroids, organoids and tissue cultures, along with more realistic aerosol exposure systems, offers new opportunities to investigate the cytotoxic effects of airborne particulates under controlled laboratory conditions. Parallel advances in high-resolution microscopy have resulted in a range of in vitro imaging tools capable of visualizing and analysing biological systems across unprecedented scales of length, time and complexity. This article considers state-of-the-art in vitro respiratory models and aerosol exposure systems and how they can be interrogated using high-resolution microscopy techniques to investigate cell-pollutant interactions, from the uptake and trafficking of particles to structural and functional modification of subcellular organelles and cells. These data can provide a mechanistic basis from which to advance our understanding of the health effects of airborne particulate pollution and develop improved mitigation measures.

Enhancing Weak-Signal Extraction for Single-Molecule Localization Microscopy

Single-molecule localization microscopy (SMLM) has been widely used in biological imaging due to its ultrahigh spatial resolution. However, due to the strategy of reducing photodamage to living cells, the fluorescence signals of emitters are usually weak and the detector noises become non-negligible, which leads to localization misalignments and signal losses, thus deteriorating the imaging capability of SMLM. Here, we propose an active modulation method to control the fluorescence of the probe emitters. It actually marks the emitters with artificial blinking character, which directly distinguishes weak signals from multiple detector noises. We demonstrated from simulations and experiments that this method improves the signal-to-noise ratio by about 10 dB over the non-modulated method and boosts the sensitivity of single-molecule localization down to -4 dB, which significantly reduces localization misalignments and signal losses in SMLM. This signal-noise decoupling strategy is generally applicable to the super-resolution system with versatile labeled probes to improve their imaging capability. We also showed its application to the densely labeled sample, showing its flexibility in super-resolution nanoscopy.

HyU: Hybrid Unmixing for longitudinal in vivo imaging of low signal-to-noise fluorescence

The expansion of fluorescence bioimaging toward more complex systems and geometries requires analytical tools capable of spanning widely varying timescales and length scales, cleanly separating multiple fluorescent labels and distinguishing these labels from background autofluorescence. Here we meet these challenging objectives for multispectral fluorescence microscopy, combining hyperspectral phasors and linear unmixing to create Hybrid Unmixing (HyU). HyU is efficient and robust, capable of quantitative signal separation even at low illumination levels. In dynamic imaging of developing zebrafish embryos and in mouse tissue, HyU was able to cleanly and efficiently unmix multiple fluorescent labels, even in demanding volumetric timelapse imaging settings. HyU permits high dynamic range imaging, allowing simultaneous imaging of bright exogenous labels and dim endogenous labels. This enables coincident studies of tagged components, cellular behaviors and cellular metabolism within the same specimen, providing more accurate insights into the orchestrated complexity of biological systems.

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.

Single-virus tracking reveals variant SARS-CoV-2 spike proteins induce ACE2-independent membrane interactions

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) became a global health crisis after its emergence in 2019. Replication of the virus is initiated by binding of the viral spike (S) protein to human angiotensin-converting enzyme 2 (ACE2) on the target cell surface. Mutations acquired by SARS-CoV-2 S variants likely influence virus-target cell interaction. Here, using single-virus tracking to capture these initial steps, we observe how viruses carrying variant S interact with target cells. Specificity for ACE2 occurs for viruses with the reference sequence or D614G mutation. Analysis of the Alpha, Beta, and Delta SARS-CoV-2 variant S proteins revealed a progressive altered cell interaction with a reduced dependence on ACE2. Notably, the Delta variant S affinity was independent of ACE2. These enhanced interactions may account for the increased transmissibility of variants. Knowledge of how mutations influence cell interaction is essential for vaccine development against emerging variants of SARS-CoV-2.

Extending resolution within a single imaging frame

The resolution of fluorescence microscopy images is limited by the physical properties of light. In the last decade, numerous super-resolution microscopy (SRM) approaches have been proposed to deal with such hindrance. Here we present Mean-Shift Super Resolution (MSSR), a new SRM algorithm based on the Mean Shift theory, which extends spatial resolution of single fluorescence images beyond the diffraction limit of light. MSSR works on low and high fluorophore densities, is not limited by the architecture of the optical setup and is applicable to single images as well as temporal series. The theoretical limit of spatial resolution, based on optimized real-world imaging conditions and analysis of temporal image stacks, has been measured to be 40 nm. Furthermore, MSSR has denoising capabilities that outperform other SRM approaches. Along with its wide accessibility, MSSR is a powerful, flexible, and generic tool for multidimensional and live cell imaging applications.

Imp2p forms actin-dependent clusters and imparts stiffness to the contractile ring

The contractile ring must anchor to the plasma membrane and cell wall to transmit its tension. F-BAR domain containing proteins including Imp2p and Cdc15p in fission yeast are likely candidate anchoring proteins based on their mutant phenotypes. Cdc15p is a node component, links the actin bundle to the plasma membrane, recruits Bgs1p to the division plane, prevents contractile ring sliding, and contributes to the stiffness of the contractile ring. Less is known about Imp2p. We found that similarly to Cdc15p, Imp2p contributes to the stiffness of the contractile ring and assembles into protein clusters. Imp2p clusters contain approximately eight Imp2p dimers and depend on the actin network for their stability at the division plane. Importantly, Imp2p and Cdc15p reciprocally affect the amount of each other in the contractile ring, indicating that the two proteins influence each other during cytokinesis, which may partially explain their similar phenotypes.

The non-catalytic role of DNA polymerase epsilon in replication initiation in human cells

DNA polymerase epsilon (PolE) in an enzyme essential for DNA replication. Deficiencies and mutations in PolE cause severe developmental abnormalities and cancers. Paradoxically, the catalytic domain of yeast PolE catalytic subunit is dispensable for survival, and its non-catalytic essential function is linked with replicative helicase (CMG) assembly. Less is known about the PolE role in replication initiation in human cells. Here we use an auxin-inducible degron system to study the effect of POLE1 depletion on replication initiation in U2OS cells. POLE1-depleted cells were able to assemble CMG helicase and initiate DNA synthesis that failed shortly after. Expression of POLE1 non-catalytic domain rescued this defect resulting in slow, but continuous DNA synthesis. We propose a model where in human U2OS cells POLE1/POLE2 are dispensable for CMG assembly, but essential during later steps of replication initiation. Our study provides some insights into the role of PolE in replication initiation in human cells.

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

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

Single Photon Kilohertz Frame Rate Imaging of Neural Activity

Establishing the biological basis of cognition and its disorders will require high precision spatiotemporal measurements of neural activity. Recently developed genetically encoded voltage indicators (GEVIs) report both spiking and subthreshold activity of identified neurons. However, maximally capitalizing on the potential of GEVIs will require imaging at millisecond time scales, which remains challenging with standard camera systems. Here, application of single photon avalanche diode (SPAD) sensors is reported to image neural activity at kilohertz frame rates. SPADs are electronic devices that when activated by a single photon cause an avalanche of electrons and a large electric current. An array of SPAD sensors is used to image individual neurons expressing the GEVI Voltron-JF525-HTL. It is shown that subthreshold and spiking activity can be resolved with shot noise limited signals at frame rates of up to 10 kHz. SPAD imaging is able to reveal millisecond scale synchronization of neural activity in an ex vivo seizure model. SPAD sensors may have widespread applications for investigation of millisecond timescale neural dynamics.

Efficient and accurate conversion-gain estimation of a photon-counting image sensor based on the maximum likelihood estimation

We establish a method for estimating conversion gains of image sensors on the basis of a maximum likelihood estimation, one of the most common and well-established statistical approaches. A numerical simulation indicates the proposed method can evaluate the conversion gain more accurately with less data accumulation than known approaches. We also applied this method to experimental images accumulated under a photon-counting-regime illumination condition by a CMOS image sensor that can distinguish how many photoelectrons are generated in each pixel. Resultantly, the conversion gains were determined with an accuracy of three digits from 1000 observed images, whose number is at most 10 times smaller than that required for achieving a similar accuracy by known gain-estimation methods.

Pushing the colorimetry camera-based fluorescence microscopy to low light imaging by denoising and dye combination

Colorimetry camera-based fluorescence microscopy (CCFM) is a single-frame imaging method for observing multiple biological events simultaneously. Compared with the traditional multi-color fluorescence microscopy methods based on sequential excitation or spectral splitting, the CCFM method simplifies multi-color fluorescence imaging experiments, while keeping a high spatial resolution. However, when the level of the detected fluorescence signal decreases, the image quality, the demosaicking algorithm precision, and the discrimination of fluorescence channels on the colorimetry camera will also decrease. Thus, CCFM has a poor color resolution under a low signal level. For example, the crosstalk will be higher than 10% when the signal is less than 100 photons/pixel. To solve this problem, we developed a new algorithm that combines sCMOS noise correction with demosaicking, and a dye selection method based on the spectral response characteristics of the colorimetry camera. By combining the above two strategies, low crosstalk can be obtained with 4 ∼ 6 fold fewer fluorescence photons, and low light single-frame four-color fluorescence imaging was successfully performed on fixed cos-7 cells. This study expands the power of the CCFM method, and provides a simple and efficient way for various bioimaging applications in low-light conditions.

ResNet-based image inpainting method for enhancing the imaging speed of single molecule localization microscopy

Single molecule localization microscopy (SMLM) is a mainstream method in the field of super-resolution fluorescence microscopy that can achieve a spatial resolution of 20∼30 nm through a simple optical system. SMLM usually requires thousands of raw images to reconstruct a super-resolution image, and thus suffers from a slow imaging speed. Recently, several methods based on image inpainting have been developed to enhance the imaging speed of SMLM. However, these image inpainting methods may also produce erroneous local features (or called image artifacts), for example, incorrectly joined or split filaments. In this study, we use the ResNet generator, a network with strong local feature extraction capability, to replace the popularly-used U-Net generator to minimize the image artifact problem in current image inpainting methods, and develop an image inpainting method called DI-STORM. We validate our method using both simulated and experimental data, and demonstrate that DI-STORM has the best acceleration capability and produces the least artifacts in the repaired images, as compared with VDSR (the simplest CNN-based image inpainting method in SMLM) and ANNA-PALM (the best GAN-based image inpainting method in SMLM). We believe that DI-STORM could facilitate the application of deep learning-based image inpainting methods for SMLM.

Visualizing the Orientation of Single Polymers Induced by Spin-Coating

The orientation of chains within polymeric materials influences their electrical, mechanical, and thermal properties. While many techniques can infer the orientation distribution of a bulk ensemble, it is challenging to determine this information at the single-chain level, particularly in an environment of otherwise identical polymers. Here, we use single-molecule localization microscopy (SMLM) to visualize the directions of chains within spin-coated polymer films. We find a strong relationship between shear force and the degree and direction of orientation, and additionally, we reveal the effects of chain length and solvent evaporation rate. This work utilizes single-chain resolution to observe the important, though often overlooked, property of chain orientation in the common fabrication process of spin-coating.

Real-time image resolution measurement for single molecule localization microscopy

Recent advancements in single molecule localization microscopy (SMLM) have demonstrated outstanding potential applications in high-throughput and high-content screening imaging. One major limitation to such applications is to find a way to optimize imaging throughput without scarifying image quality, especially the homogeneity in image resolution, during the imaging of hundreds of field-of-views (FOVs) in heterogeneous samples. Here we introduce a real-time image resolution measurement method for SMLM to solve this problem. This method is under the heuristic framework of overall image resolution that counts on localization precision and localization density. Rather than estimating the mean localization density after completing the entire SMLM process, this method uses the spatial Poisson process to model the random activation of molecules and thus determines the localization density in real-time. We demonstrate that the method is valid in real-time resolution measurement and is effective in guaranteeing homogeneous image resolution across multiple representative FOVs with optimized imaging throughput.

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.

USP1-trapping lesions as a source of DNA replication stress and genomic instability

The deubiquitinase USP1 is a critical regulator of genome integrity through the deubiquitylation of Fanconi Anemia proteins and the DNA replication processivity factor, proliferating cell nuclear antigen (PCNA). Uniquely, following UV irradiation, USP1 self-inactivates through autocleavage, which enables its own degradation and in turn, upregulates PCNA monoubiquitylation. However, the functional role for this autocleavage event during physiological conditions remains elusive. Herein, we discover that cells harboring an autocleavage-defective USP1 mutant, while still able to robustly deubiquitylate PCNA, experience more replication fork-stalling and premature fork termination events. Using super-resolution microscopy and live-cell single-molecule tracking, we show that these defects are related to the inability of this USP1 mutant to be properly recycled from sites of active DNA synthesis, resulting in replication-associated lesions. Furthermore, we find that the removal of USP1 molecules from DNA is facilitated by the DNA-dependent metalloprotease Spartan to counteract the cytotoxicity caused by “USP1-trapping”. We propose a utility of USP1 inhibitors in cancer therapy based on their ability to induce USP1-trapping lesions and consequent replication stress and genomic instability in cancer cells, similar to how non-covalent DNA-protein crosslinks cause cytotoxicity by imposing steric hindrances upon proteins involved in DNA transactions.

Here the authors provide mechanistic insights into how auto-cleavage of the USP1 deubiquitinase regulates DNA replication and genome stability. Implications for the targeting of USP1 activity via protein-DNA trapping in cancer therapy are discussed.

sCMOS Noise-Corrected Superresolution Reconstruction Algorithm for Structured Illumination Microscopy

Structured illumination microscopy (SIM) is widely applied due to its high temporal and spatial resolution imaging ability. sCMOS cameras are often used in SIM due to their superior sensitivity, resolution, field of view, and frame rates. However, the unique single-pixel-dependent readout noise of sCMOS cameras may lead to SIM reconstruction artefacts and affect the accuracy of subsequent statistical analysis. We first established a nonuniform sCMOS noise model to address this issue, which incorporates the single-pixel-dependent offset, gain, and variance based on the SIM imaging process. The simulation indicates that the sCMOS pixel-dependent readout noise causes artefacts in the reconstructed SIM superresolution (SR) image. Thus, we propose a novel sCMOS noise-corrected SIM reconstruction algorithm derived from the imaging model, which can effectively suppress the sCMOS noise-related reconstruction artefacts and improve the signal-to-noise ratio (SNR).

Diffraction-limited molecular cluster quantification with Bayesian nonparametrics

Life’s fundamental processes involve multiple molecules operating in close proximity within cells. To probe the composition and kinetics of molecular clusters confined within small (diffraction-limited) regions, experiments often report on the total fluorescence intensity simultaneously emitted from labeled molecules confined to such regions. Methods exist to enumerate total fluorophore numbers (e.g., step counting by photobleaching). However, methods aimed at step counting by photobleaching cannot treat photophysical dynamics in counting nor learn their associated kinetic rates. Here we propose a method to simultaneously enumerate fluorophores and determine their individual photophysical state trajectories. As the number of active (fluorescent) molecules at any given time is unknown, we rely on Bayesian nonparametrics and use specialized Monte Carlo algorithms to derive our estimates. Our formulation is benchmarked on synthetic and real data sets. While our focus here is on photophysical dynamics (in which labels transition between active and inactive states), such dynamics can also serve as a proxy for other types of dynamics such as assembly and disassembly kinetics of clusters. Similarly, while we focus on the case where all labels are initially fluorescent, other regimes, more appropriate to photoactivated localization microscopy, where fluorophores are instantiated in a non-fluorescent state, fall within the scope of the framework. As such, we provide a complete and versatile framework for the interpretation of complex time traces arising from the simultaneous activity of up to 100 fluorophores.

Super-Resolution Microscopy for Structural Cell Biology

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

Bayesian machine learning analysis of single-molecule fluorescence colocalization images

Multi-wavelength single-molecule fluorescence colocalization (CoSMoS) methods allow elucidation of complex biochemical reaction mechanisms. However, analysis of CoSMoS data is intrinsically challenging because of low image signal-to-noise ratios, non-specific surface binding of the fluorescent molecules, and analysis methods that require subjective inputs to achieve accurate results. Here, we use Bayesian probabilistic programming to implement Tapqir, an unsupervised machine learning method that incorporates a holistic, physics-based causal model of CoSMoS data. This method accounts for uncertainties in image analysis due to photon and camera noise, optical non-uniformities, non-specific binding, and spot detection. Rather than merely producing a binary 'spot/no spot' classification of unspecified reliability, Tapqir objectively assigns spot classification probabilities that allow accurate downstream analysis of molecular dynamics, thermodynamics, and kinetics. We both quantitatively validate Tapqir performance against simulated CoSMoS image data with known properties and also demonstrate that it implements fully objective, automated analysis of experiment-derived data sets with a wide range of signal, noise, and non-specific binding characteristics.

Fluorescence nanoscopy at the sub-10 nm scale

Fluorescence nanoscopy represented a breakthrough for the life sciences as it delivers 20-30 nm resolution using far-field fluorescence microscopes. This resolution limit is not fundamental but imposed by the limited photostability of fluorophores under ambient conditions. This has motivated the development of a second generation of fluorescence nanoscopy methods that aim to deliver sub-10 nm resolution, reaching the typical size of structural proteins and thus providing true molecular resolution. In this review, we present common fundamental aspects of these nanoscopies, discuss the key experimental factors that are necessary to fully exploit their capabilities, and discuss their current and future challenges.

Single-Molecule Blinking Fluorescence Enhancement by Surface Plasmon-Coupled Emission-Based Substrates for Single-Molecule Localization Imaging

Surface plasmon-coupled emission (SPCE) substrates to enhance the blinking fluorescence of spontaneously blinking fluorophores in single-molecule localization microscopy (SMLM) were fabricated to reduce the excitation power density requirement and reveal the distribution of fluorophore-labeled proteins on a plasma membrane with nanoscale-level resolution. The systemic investigation of the contribution of local field enhancement, modified quantum yield, and emission coupling yield through glass coverslip substrates coated with metal layers of different thicknesses revealed that the silver-layer substrate with a thickness of 44 nm produces the highest SPCE fluorescence in spontaneously blinking fluorophores, and it has a highly directional SPCE fluorescence, which helps improve the detection efficiency. Moreover, the uniform and surface-enhanced field created on the substrate surface is beneficial for fluorescence background reduction in single fluorophore detection and localization, as well as for revealing the real position of fluorophores. Consequently, compared with a glass coverslip substrate, the presented SPCE substrate demonstrated a fluorescence enhancement of 480% and an increase in blinking events from a single spontaneously blinking fluorophore; moreover, the required excitation power density for SMLM imaging was significantly reduced to 23 W cm^-2 for visualizing the distribution of epidermal growth factor receptors (EGFRs) on the basal plasma membrane of A549 lung cancer cells with a localization precision of 19 ± 7 nm. Finally, the fluorophore-labeled EGFRs on the basal plasma membrane in the presence of PIKfyve-specific inhibitor treatment were explored using SPCE-SMLM imaging; the results revealed a distinct reduction in the density of localization events because of a decrease in EGFR abundance at the plasma membranes of the cells.

Single-molecule imaging of replication fork conflicts at genomic DNA G4 structures in human cells

DNA G-quadruplexes (G4s) are stable, non-canonical DNA secondary structures formed within guanine(G)-rich sequences. While extensively studied in vitro, evidence of the occurrence of G4s in vivo has only recently emerged. The formation of G4 structures may pose an obstacle for diverse DNA transactions including replication, which is linked to mutagenesis and genomic instability. A fundamental question in the field has been whether and how the formation of G4s is coupled to the progression of replication forks. This process has remained undefined largely due to the lack of experimental approaches capable of monitoring the presence of G4s and their association with the replication machinery in cells. Here, we describe a detailed multicolor single-molecule localization microscopy (SMLM) protocol for detecting nanoscale spatial-association of DNA G4s with the cellular replisome complex. This method offers a unique platform for visualizing the mechanisms of G4 formation at the molecular level, as well as addressing key biological questions as to the functional roles of these structures in the maintenance of genome integrity.

Live-Cell Probe for In Situ Single-Cell Monitoring of Mitochondrial DNA Methylation

Mitochondria, as the center of energy production, play an important role in cell homeostasis by regulating the cellular metabolism and mediating the cellular response to stress. Epigenetic changes such as DNA and histone methylation have been increasingly recognized to play a significant role in homeostasis and stress response. The cross-talking between the metabolome and the epigenome has attracted significant attention in recent years but with a major focus on how metabolism contributes to epigenomic changes. Few studies have focused on how epigenetic modifications may alter the mitochondrial composition and activity. In this work, we designed a novel probe targeting methylated CpGs of mitochondrial DNA (mtDNA). We demonstrated the capability of our probe to reveal the spatial distribution of methylated mtDNA and capture the mtDNA methylation changes at a single-cell level. We were also able to track single-cell mtDNA and nDNA methylation simultaneously and discovered the unsynchronized dynamics of the nucleus and mitochondria. Our tool offers a unique opportunity to understand the epigenetic regulation of mtDNA and its dynamic response to the microenvironment and cellular changes.

A basal-level activity of ATR links replication fork surveillance and stress response

Mammalian cells use diverse pathways to prevent deleterious consequences during DNA replication, yet the mechanism by which cells survey individual replisomes to detect spontaneous replication impediments at the basal level, and their accumulation during replication stress, remain undefined. Here, we used single-molecule localization microscopy coupled with high-order-correlation image-mining algorithms to quantify the composition of individual replisomes in single cells during unperturbed replication and under replicative stress. We identified a basal-level activity of ATR that monitors and regulates the amounts of RPA at forks during normal replication. Replication-stress amplifies the basal activity through the increased volume of ATR-RPA interaction and diffusion-driven enrichment of ATR at forks. This localized crowding of ATR enhances its collision probability, stimulating the activation of its replication-stress response. Finally, we provide a computational model describing how the basal activity of ATR is amplified to produce its canonical replication stress response.

Enhanced super-resolution microscopy by extreme value based emitter recovery

Super-resolution localization microscopy allows visualization of biological structure at nanoscale resolution. However, the presence of heterogeneous background can degrade the nanoscale resolution by tens of nanometers and introduce significant image artifacts. Here we investigate and validate an efficient approach, referred to as extreme value-based emitter recovery (EVER), to accurately recover the distorted fluorescent emitters from heterogeneous background. Through numerical simulation and biological experiments, we validated the accuracy of EVER in improving the fidelity of the reconstructed super-resolution image for a wide variety of imaging characteristics. EVER requires no manual adjustment of parameters and has been implemented as an easy-to-use ImageJ plugin that can immediately enhance the quality of reconstructed super-resolution images. This method is validated as an efficient way for robust nanoscale imaging of samples with heterogeneous background fluorescence, such as thicker tissue and cells.

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.