Super-resolution Structured Illumination Microscopy Research Articles

Direct measurement and optimization of the polarization-dependent modulation depth in super-resolution structured illumination microscopy

Direct measurement and optimization of the polarization-dependent modulation depth in super-resolution structured illumination microscopy

Quantitative evaluation of intensity fidelity of super-resolution reconstruction for structured illumination microscopy

Super-resolution structured illumination microscopy (SR-SIM) relies heavily on post-processing reconstruction to obtain high-quality SR images from raw data. Although many SIM reconstruction algorithms have been developed to recover fine cellular structures with high fidelity even from the noisy data, whether the pixel intensities of reconstructed SR images are still proportional to the original fluorescence intensity has been less explored. The linearity between the intensity before and after reconstruction is defined as the intensity fidelity. Here, we proposed a method to evaluate the reconstructed SR image intensity fidelity at different spatial frequencies. With the proposed metric, we systematically investigated the impact of the key factors on the intensity fidelity in the standard Wiener-SIM reconstructions with simulated data, then evaluated the intensity fidelity of the SR images reconstructed by representative open-source packages. Our work provides a reference for SR-SIM image intensity fidelity improvement.

Image restoration in frequency space using complex-valued CNNs.

Real-valued convolutional neural networks (RV-CNNs) in the spatial domain have outperformed classical approaches in many image restoration tasks such as image denoising and super-resolution. Fourier analysis of the results produced by these spatial domain models reveals the limitations of these models in properly processing the full frequency spectrum. This lack of complete spectral information can result in missing textural and structural elements. To address this limitation, we explore the potential of complex-valued convolutional neural networks (CV-CNNs) for image restoration tasks. CV-CNNs have shown remarkable performance in tasks such as image classification and segmentation. However, CV-CNNs for image restoration problems in the frequency domain have not been fully investigated to address the aforementioned issues. Here, we propose several novel CV-CNN-based models equipped with complex-valued attention gates for image denoising and super-resolution in the frequency domains. We also show that our CV-CNN-based models outperform their real-valued counterparts for denoising super-resolution structured illumination microscopy (SR-SIM) and conventional image datasets. Furthermore, the experimental results show that our proposed CV-CNN-based models preserve the frequency spectrum better than their real-valued counterparts in the denoising task. Based on these findings, we conclude that CV-CNN-based methods provide a plausible and beneficial deep learning approach for image restoration in the frequency domain.

Genome-wide analysis of the biophysical properties of chromatin and nuclear proteins in living cells with Hi-D.

To understand the dynamic nature of the genome, the localization and rearrangement of DNA and DNA-binding proteins must be analyzed across the entire nucleus of single living cells. Recently, we developed a computational light microscopy technique, called high-resolution diffusion (Hi-D) mapping, which can accurately detect, classify and map diffusion dynamics and biophysical parameters such as the diffusion constant, the anomalous exponent, drift velocity and model physical diffusion from the data at a high spatial resolution across the genome in living cells. Hi-D combines dense optical flow to detect and track local chromatin and nuclear protein motion genome-wide and Bayesian inference to characterize this local movement at nanoscale resolution. Here we present the Python implementation of Hi-D, with an option for parallelizing the calculations to run on multicore central processing units (CPUs). The functionality of Hi-D is presented to the users via user-friendly documented Python notebooks. Hi-D reduces the analysis time to less than 1 h using a multicore CPU with a single compute node. We also present different applications of Hi-D for live-imaging of DNA, histone H2B and RNA polymerase II sequences acquired with spinning disk confocal and super-resolution structured illumination microscopy.

A Denoise Network for Structured Illumination Microscopy with Low-Light Exposure

Super-resolution structured illumination microscopy (SR-SIM) is one of the important techniques that are most suitable for live-cell imaging. The reconstructed SR-SIM images are noisy once the raw images are recorded with low-light exposure. Here, we propose a new network (entitled the ND-SIM network) to denoise the SR images reconstructed using frequency-domain algorithms (FDAs). We demonstrate that ND-SIM can yield artifact-free SR images using raw images with an average photon count down to 20 per pixel while achieving comparable resolution to the ground truth (GT) obtained with high-light exposure. We can envisage that the ND-SIM will be widely applied for the long-term, super-resolution live-cell imaging of various bioprocesses in the future.

High-speed super-resolution structured illumination microscopy with a large field-of-view

Structured illumination microscopy (SIM) has been extensively employed for observing subcellular structures and dynamics. However, achieving high-speed super-resolution SIM with a large field of view (FOV) remains challenging due to the trade-offs among spatial resolution, imaging speed and FOV under limited bandwidth constraints. Here, we report a novel SIM technique to address this issue. By utilizing a high-speed camera and a rolling image reconstruction strategy to accelerate super-resolution image acquisition, as well as using a deep resolution enhancement to further improve spatial resolution, this SIM technique achieves imaging with a spatial resolution of 94 nm, a FOV of 102 × 102 µm2, and an imaging speed of 1333 frames per second. The exceptional imaging performance of this proposed SIM technique is experimentally demonstrated through the successful recording of the Brownian motion of fluorescent microspheres and the photobleaching of fluorescently labeled microtubules. This work offers a potential tool for the high-throughput observation of high-speed subcellular dynamics, which would bring significant applications in biomedical research.

Parameter-free super-resolution structured illumination microscopy via a physics-enhanced neural network.

With full-field imaging and high photon efficiency advantages, structured illumination microscopy (SIM) is one of the most potent super-resolution (SR) modalities in bioscience. Regarding SR reconstruction for SIM, spatial domain reconstruction (SDR) has been proven to be faster than traditional frequency domain reconstruction (FDR), facilitating real-time imaging of live cells. Nevertheless, SDR relies on high-precision parameter estimation for reconstruction, which tends to suffer from low signal-to-noise ratio (SNR) conditions and inevitably leads to artifacts that seriously affect the accuracy of SR reconstruction. In this Letter, a physics-enhanced neural network-based parameter-free SDR (PNNP-SDR) is proposed, which can achieve SR reconstruction directly in the spatial domain. As a result, the peak-SNR (PSNR) of PNNP-SDR is improved by about 4 dB compared to the cross-correlation (COR) SR reconstruction; meanwhile, the reconstruction speed of PNNP-SDR is even about five times faster than the fast approach based on principal component analysis (PCA). Given its capability of achieving parameter-free imaging, noise robustness, and high-fidelity and high-speed SR reconstruction over conventional SIM microscope hardware, the proposed PNNP-SDR is expected to be widely adopted in biomedical SR imaging scenarios.

Multi-color two-laser super-resolution structured illumination microscopy for the visualization of multi-organelle in living cells.

In this study, we introduced a novel dual-laser multi-color imaging system. Integrated with a multi-channel filter wheel, this system compared three spectral decontamination algorithms (nonnegative matrix factorization [NMF], RCAN, and PICASSO) showcasing its efficacy in achieving four-color imaging with only two laser sources. Combined with a reliable image reconstruction algorithm, the spatial resolution of four channels super-resolution four-color images reached 130, 125, 133, and 132 nm, respectively. Lipid droplets, mitochondria, lysosomes, and nuclei from the mouse hepatocytes (AML12), human neuroblastoma cells (SH-SY5Y), mouse hippocampal neuronal cells (HT-22), and immortalized murine bone marrow-derived macrophages were imaged. At the same time, the chromatin condensation, nuclear contraction, DNA fragmentation, apoptotic body formation, as well as the fusion of Mito and Lyso involved in mitochondrial autophagy were observed in HT-22 and SH-SY5Y cells suffering oxidative stress. Our multi-color SIM imaging system establishes a powerful platform for dynamic organelle studies and other high-resolution investigations in live cells.

Identifying Cell-Penetrating Peptides for Effectively Delivering Antimicrobial Molecules into Streptococcus suis.

Cell-penetrating peptides (CPPs) are promising carriers to effectively transport antisense oligonucleotides (ASOs), including peptide nucleic acids (PNAs), into bacterial cells to combat multidrug-resistant bacterial infections, demonstrating significant therapeutic potential. Streptococcus suis, a Gram-positive bacterium, is a major bacterial pathogen in pigs and an emerging zoonotic pathogen. In this study, through the combination of super-resolution structured illumination microscopy (SR-SIM), flow cytometry analysis, and toxicity analysis assays, we investigated the suitability of four CPPs for delivering PNAs into S. suis cells: HIV-1 TAT efficiently penetrated S. suis cells with low toxicity against S. suis; (RXR)4XB had high penetration efficiency with inherent toxicity against S. suis; (KFF)3K showed lower penetration efficiency than HIV-1 TAT and (RXR)4XB; K8 failed to penetrate S. suis cells. HIV-1 TAT-conjugated PNA specific for the essential gyrase A subunit gene (TAT-anti-gyrA PNA) effectively inhibited the growth of S. suis. TAT-anti-gyrA PNA exhibited a significant bactericidal effect on serotypes 2, 4, 5, 7, and 9 strains of S. suis, which are known to cause human infections. Our study demonstrates the potential of CPP-ASO conjugates as new antimicrobial compounds for combating S. suis infections. Furthermore, our findings demonstrate that applying SR-SIM and flow cytometry analysis provides a convenient, intuitive, and cost-effective approach to identifying suitable CPPs for delivering cargo molecules into bacterial cells.

Surpassing light inhomogeneities in structured-illumination microscopy with FlexSIM.

Super-resolution structured-illumination microscopy (SIM) is a powerful technique that allows one to surpass the diffraction limit by up to a factor two. Yet, its practical use is hampered by its sensitivity to imaging conditions which makes it prone to reconstruction artefacts. In this work, we present FlexSIM, a flexible SIM reconstruction method capable to handle highly challenging data. Specifically, we demonstrate the ability of FlexSIM to deal with the distortion of patterns, the high level of noise encountered in live imaging, as well as out-of-focus fluorescence. Moreover, we show that FlexSIM achieves state-of-the-art performance over a variety of open SIMdatasets.

Correlative single-molecule and structured illumination microscopy of fast dynamics at the plasma membrane

Total internal reflection fluorescence (TIRF) microscopy offers powerful means to uncover the functional organization of proteins in the plasma membrane with very high spatial and temporal resolution. Traditional TIRF illumination, however, shows a Gaussian intensity profile, which is typically deteriorated by overlaying interference fringes hampering precise quantification of intensities—an important requisite for quantitative analyses in single-molecule localization microscopy (SMLM). Here, we combine flat-field illumination by using a standard πShaper with multi-angular TIR illumination by incorporating a spatial light modulator compatible with fast super-resolution structured illumination microscopy (SIM). This distinct combination enables quantitative multi-color SMLM with a highly homogenous illumination. By using a dual camera setup with optimized image splitting optics, we achieve a versatile combination of SMLM and SIM with up to three channels. We deploy this setup for establishing robust detection of receptor stoichiometries based on single-molecule intensity analysis and single-molecule Förster resonance energy transfer (smFRET). Homogeneous illumination furthermore enables long-term tracking and localization microscopy (TALM) of cell surface receptors identifying spatial heterogeneity of mobility and accessibility in the plasma membrane. By combination of TALM and SIM, spatially and molecularly heterogenous diffusion properties can be correlated with nanoscale cytoskeletal organization and dynamics.

An optimized approach to study nanoscale sarcomere structure utilizing super-resolution microscopy with nanobodies.

The sarcomere is the fundamental contractile unit in skeletal muscle, and the regularity of its structure is critical for function. Emerging data demonstrates that nanoscale changes to the regularity of sarcomere structure can affect the overall function of the protein dense ~2μm sarcomere. Further, sarcomere structure is implicated in many clinical conditions of muscle weakness. However, our understanding of how sarcomere structure changes in disease, especially at the nanoscale, has been limited in part due to the inability to robustly detect and measure at sub-sarcomere resolution. We optimized several methodological steps and developed a robust pipeline to analyze sarcomere structure using structured illumination super-resolution microscopy in conjunction with commercially-available and fluorescently-conjugated Variable Heavy-Chain only fragment secondary antibodies (nanobodies), and achieved a significant increase in resolution of z-disc width (353nm vs. 62nm) compared to confocal microscopy. The combination of these methods provides a unique approach to probe sarcomere protein localization at the nanoscale and may prove advantageous for analysis of other cellular structures.

Microanatomy of the human tunnel of Corti structures and cochlear partition-tonotopic variations and transcellular signaling.

Auditory sensitivity and frequency resolution depend on the optimal transfer of sound-induced vibrations from the basilar membrane (BM) to the inner hair cells (IHCs), the principal auditory receptors. There remains a paucity of information on how this is accomplished along the frequency range in the human cochlea. Most of the current knowledge is derived either from animal experiments or human tissue processed after death, offering limited structural preservation and optical resolution. In our study, we analyzed the cytoarchitecture of the human cochlear partition at different frequency locations using high-resolution microscopy of uniquely preserved normal human tissue. The results may have clinical implications and increase our understanding of how frequency-dependent acoustic vibrations are carried to human IHCs. A 1-micron-thick plastic-embedded section (mid-modiolar) from a normal human cochlea uniquely preserved at lateral skull base surgery was analyzed using light and transmission electron microscopy (LM, TEM). Frequency locations were estimated using synchrotron radiation phase-contrast imaging (SR-PCI). Archival human tissue prepared for scanning electron microscopy (SEM) and super-resolution structured illumination microscopy (SR-SIM) were also used and compared in this study. Microscopy demonstrated great variations in the dimension and architecture of the human cochlear partition along the frequency range. Pillar cell geometry was closely regulated and depended on the reticular lamina slope and tympanic lip angle. A type II collagen-expressing lamina extended medially from the tympanic lip under the inner sulcus, here named "accessory basilar membrane." It was linked to the tympanic lip and inner pillar foot, and it may contribute to the overall compliance of the cochlear partition. Based on the findings, we speculate on the remarkable microanatomic inflections and geometric relationships which relay different sound-induced vibrations to the IHCs, including their relevance for the evolution of human speech reception and electric stimulation with auditory implants. The inner pillar transcellular microtubule/actin system's role of directly converting vibration energy to the IHC cuticular plate and ciliary bundle is highlighted.

Alcohol-induced Golgiphagy is triggered by the downregulation of Golgi GTPase RAB3D

ABSTRACT The development of alcohol-associated liver disease (ALD) is associated with disorganized Golgi apparatus and accelerated phagophore formation. While Golgi membranes may contribute to phagophores, association between Golgi alterations and macroautophagy/autophagy remains unclear. GOLGA4/p230 (golgin A4), a dimeric Golgi matrix protein, participates in phagophore formation, but the underlying mechanism is elusive. Our prior research identified ethanol (EtOH)-induced Golgi scattering, disrupting intra-Golgi trafficking and depleting RAB3D GTPase from the trans-Golgi. Employing various techniques, we analyzed diverse cellular and animal models representing chronic and chronic/binge alcohol consumption. In trans-Golgi of non-treated hepatocytes, we found a triple complex formed between RAB3D, GOLGA4, and MYH10/NMIIB (myosin, heavy polypeptide 10, non-muscle). However, EtOH-induced RAB3D downregulation led to MYH10 segregation from the Golgi, accompanied by Golgi fragmentation and tethering of the MYH10 isoform, MYH9/NMIIA, to dispersed Golgi membranes. EtOH-activated autophagic flux is evident through increased WIPI2 recruitment to the Golgi, phagophore formation, enhanced LC3B lipidation, and reduced SQSTM1/p62. Although GOLGA4 dimerization and intra-Golgi localization are unaffected, loss of RAB3D leads to an extension of the cytoplasmic N terminal domain of GOLGA4, forming GOLGA4-positive phagophores. Autophagy inhibition by hydroxychloroquine (HCQ) prevents alcohol-mediated Golgi disorganization, restores distribution of ASGR (asialoglycoprotein receptor), and mitigates COL (collagen) deposition and steatosis. In contrast to short-term exposure to HCQ, extended co-treatment with both EtOH and HCQ results in the depletion of LC3B protein via proteasomal degradation. Thus, (a) RAB3D deficiency and GOLGA4 conformational changes are pivotal in MYH9-driven, EtOH-mediated Golgiphagy, and (b) HCQ treatment holds promise as a therapeutic approach for alcohol-induced liver injury. Abbreviation: ACTB: actin, beta; ALD: alcohol-associated liver disease; ASGR: asialoglycoprotein receptor; AV: autophagic vacuoles; EM: electron microscopy; ER: endoplasmic reticulum; EtOH: ethanol; HCQ: hydroxychloroquine; IP: immunoprecipitation; KD: knockdown; KO: knockout; MYH10/NMIIB: myosin, heavy polypeptide 10, non-muscle; MYH9/NMIIA: myosin, heavy polypeptide 9, non-muscle; PLA: proximity ligation assay; ORO: Oil Red O staining; PM: plasma membrane; TGN: trans-Golgi network; SIM: structured illumination super-resolution microscopy.

Stable Super-Resolution Imaging of Cell Membrane Nanoscale Subcompartment Dynamics with a Buffering Cyanine Dye.

Super-resolution fluorescence imaging is a crucial method for visualizing the dynamics of the cell membrane involved in various physiological and pathological processes. This requires bright fluorescent dyes with excellent photostability and labeling stability to enable long-term imaging. In this context, we introduce a buffering-strategy-based cyanine dye, SA-Cy5, designed to identify and label carbonic anhydrase IX (CA IX) located in the cell membrane. The unique feature of SA-Cy5 lies in its ability to overcome photobleaching. When the dye on the cell membrane undergoes photobleaching, it is rapidly replaced by an intact probe from the buffer pool outside the cell membrane. This dynamic replacement ensures that the fluorescence intensity on the cell membrane remains stable over time. Under the super-resolution structured illumination microscopy (SIM), the cell membrane can be continuously imaged for 60 min with a time resolution of 20 s. This extended imaging period allows for the observation of substructural dynamics of the cell membrane, including the growth and fusion of filamentous pseudopodia and the fusion of vesicles. Additionally, this buffering strategy introduces a novel approach to address the issue of poor photostability associated with the cyanine dyes.

The Role of Neutral Sphingomyelinase-2 (NSM2) in the Control of Neutral Lipid Storage in T Cells.

The accumulation of lipid droplets (LDs) and ceramides (Cer) is linked to non-alcoholic fatty liver disease (NAFLD), regularly co-existing with type 2 diabetes and decreased immune function. Chronic inflammation and increased disease severity in viral infections are the hallmarks of the obesity-related immunopathology. The upregulation of neutral sphingomyelinase-2 (NSM2) has shown to be associated with the pathology of obesity in tissues. Nevertheless, the role of sphingolipids and specifically of NSM2 in the regulation of immune cell response to a fatty acid (FA) rich environment is poorly studied. Here, we identified the presence of the LD marker protein perilipin 3 (PLIN3) in the intracellular nano-environment of NSM2 using the ascorbate peroxidase APEX2-catalyzed proximity-dependent biotin labeling method. In line with this, super-resolution structured illumination microscopy (SIM) shows NSM2 and PLIN3 co-localization in LD organelles in the presence of increased extracellular concentrations of oleic acid (OA). Furthermore, the association of enzymatically active NSM2 with isolated LDs correlates with increased Cer levels in these lipid storage organelles. NSM2 enzymatic activity is not required for NSM2 association with LDs, but negatively affects the LD numbers and cellular accumulation of long-chain unsaturated triacylglycerol (TAG) species. Concurrently, NSM2 expression promotes mitochondrial respiration and fatty acid oxidation (FAO) in response to increased OA levels, thereby shifting cells to a high energetic state. Importantly, endogenous NSM2 activity is crucial for primary human CD4+ T cell survival and proliferation in a FA rich environment. To conclude, our study shows a novel NSM2 intracellular localization to LDs and the role of enzymatically active NSM2 in metabolic response to enhanced FA concentrations in T cells.

Evaluation of Swin Transformer and knowledge transfer for denoising of super-resolution structured illumination microscopy data.

Convolutional neural network (CNN)-based methods have shown excellent performance in denoising and reconstruction of super-resolved structured illumination microscopy (SR-SIM) data. Therefore, CNN-based architectures have been the focus of existing studies. However, Swin Transformer, an alternative and recently proposed deep learning-based image restoration architecture, has not been fully investigated for denoising SR-SIM images. Furthermore, it has not been fully explored how well transfer learning strategies work for denoising SR-SIM images with different noise characteristics and recorded cell structures for these different types of deep learning-based methods. Currently, the scarcity of publicly available SR-SIM datasets limits the exploration of the performance and generalization capabilities of deep learning methods. In this work, we present SwinT-fairSIM, a novel method based on the Swin Transformer for restoring SR-SIM images with a low signal-to-noise ratio. The experimental results show that SwinT-fairSIM outperforms previous CNN-based denoising methods. Furthermore, as a second contribution, two types of transfer learning-namely, direct transfer and fine-tuning-were benchmarked in combination with SwinT-fairSIM and CNN-based methods for denoising SR-SIM data. Direct transfer did not prove to be a viable strategy, but fine-tuning produced results comparable to conventional training from scratch while saving computational time and potentially reducing the amount of training data required. As a third contribution, we publish four datasets of raw SIM images and already reconstructed SR-SIM images. These datasets cover two different types of cell structures, tubulin filaments and vesicle structures. Different noise levels are available for the tubulin filaments. The SwinT-fairSIM method is well suited for denoising SR-SIM images. By fine-tuning, already trained models can be easily adapted to different noise characteristics and cell structures. Furthermore, the provided datasets are structured in a way that the research community can readily use them for research on denoising, super-resolution, and transfer learning strategies.

Digital micromirror device-based fast super-resolution lattice structured light illumination microscopy

Super-resolution structured illumination microscopy (SR-SIM) offers numerous advantages such as high temporal resolution, low photobleaching and phototoxicity, and no special requirements for fluorescent probes. It is particularly suitable for long-term SR imaging of living cells. By using two-dimensional lattice structured light serving as illumination, SR-SIM can achieve faster imaging speed and reduce phototoxicity, however, it is accompanied with system complexity increasing. To address this problem, in this work, we propose a fast SR lattice structured illumination microscopy imaging method based on a digital micromirror device (DMD), called DMD-Lattice-SIM. This method utilizes a DMD and synchronous time-sharing triggering with sCMOS to generate two-dimensional orthogonal lattice structured light. The proposed method only requires the collection of five phase-shifted raw images for SR image reconstruction, reducing the acquisition time by approximately 44.4% compared with the traditional SR-SIM method that requires nine phase-shifted raw images. In this work, we also introduce a rapid SR image reconstruction method called Lattice-JSFR-SIM, which combines the advantages of joint space and frequency reconstruction (JSFR)-SIM and Lattice-SIM. The raw images are pre-filtered in the frequency domain and then undergo SR reconstruction in the spatial domain. This approach reduces reconstruction time by approximately 55.6% compared with traditional frequency domain image reconstruction processing, within an imaging field of view of 512 pixels×512 pixels. The feasibility of the proposed method is demonstrated through experiments on cell microtubules and the observation of mitochondrial division and fusion in living cells. The findings presented in this paper hold great significance and application value for enabling real-time SR imaging of living cells.

Numerical Simulation of Super-Resolution Structured Illumination Microscopy (SIM) Using Heintzmann-Cremer Algorithm with Non-Continuous Spatial Frequency Support

Numerical Simulation of Super-Resolution Structured Illumination Microscopy (SIM) Using Heintzmann-Cremer Algorithm with Non-Continuous Spatial Frequency Support

Easily scalable multi-color DMD-based structured illumination microscopy.

Structured illumination microscopy (SIM) achieves super-resolution imaging using a series of phase-shifted sinusoidal illumination patterns to down-modulate high spatial-frequency information of samples. Digital micromirror devices (DMDs) have been increasingly used to generate SIM illumination patterns due to their high speed and moderate cost. However, a DMD micromirror array's blazed grating structure causes strong angular dispersion for different wavelengths of light, thus severely hampering its application in multicolor imaging. We developed a multi-color DMD-SIM setup that employs a diffraction grating to compensate the DMD's dispersion and demonstrate super-resolution SIM imaging of both fluorescent beads and live cells samples with four color channels. This simple but effective approach can be readily scaled to more color channels, thereby greatly expanding the application of SIM in the study of complex multi-component structures and dynamics in soft matter systems.