Single-molecule localization microscopy

Instant in situ highlighting of latent fingerprints by a green fluorescent probe based on aggregation-induced emission

Fluorescence sensing of latent fingerprints (LFPs) has gained extensive attention due to its high sensitivity, non-destructive testing, low biotoxicity, ease of operation, and the potential for in situ visualization. However, the realization of in situ visualization of LFPs especially with green emission and rapid speed is still a challenge. Herein, we synthesized an amphibious green-emission AIE-gen TPE-NI-AOH (PLQY = 62%) for instant in situ LFP detecting, which integrates the excellent fluorescence properties of naphthalimide (NI) with a hydrophilic head and the AIE character as well as the donating property of tetraphenylethene (TPE). TPE-NI-AOH in ethanol/water binary solvent was used as an environmentally friendly LFP developer and achieved in situ green-fluorescence visualization of LFPs. The fluorescence signal achieves its 60% saturated intensity in 0.37 s and nearly 100% in 2.50 s, which is an instant process for the naked eye. Moreover, level 3 details and super-resolution images of LFPs could be observed clearly. Besides, the TPE-NI-AOH developer could be stored for at least 6 months, suitable for long-term storage. This instant in situ highlighting method does not require post-processing operations, providing a more convenient, rapid, and efficient detection method of LFPs. This work would inspire the further advancement of fluorescent sensors for fingerprint imaging.

Anisotropic DBSCAN for 3D SMLM Data Clustering

Single-molecule localization microscopy (SMLM) advanced biological discoveries beyond the diffraction limit. Various implementations enable 3D SMLM to reconstruct volumetric cell images. Yet, the inherent anisotropic point spread function of optical microscopes often limits the localization precision in the axial direction compared to the lateral precision. Such localization anisotropy could also expand spherical cellular structures to ellipsoidal cellular structures. Structure identification, however, is often performed using DBSCAN cluster algorithms, considering an isotropic search volume. Here, we show that an anisotropic DBSCAN search volume identifies anisotropic clusters more reliably using simulated ground truth data sets. Given experimental localization precisions, we suggest optimized search parameters based on an expanded computational grid search and show an enhanced performance of anisotropic DBSCAN amidst variations in localization precision. We demonstrate the capability of anisotropic DBSCAN on experimental data and anticipate that the algorithm allows for a more rigorous identification of clusters in cells, considering the anisotropic localization precisions of astigmatism-based 3D SMLM.

Regulating Charge Transfer in Cyanine Dyes: A Universal Methodology for Enhancing Cancer Phototherapeutic Efficacy

ConspectusDue to the advantages of spatiotemporal selectivity and inherent noninvasiveness, cancer phototherapy, which includes both photodynamic therapy (PDT) and photothermal therapy (PTT), has garnered significant attention in recent years as a promising cancer treatment. Despite the commendable progress in this field, persistent challenges remain. In PDT, limitations in dyes manifest as low intersystem crossing (ISC) efficiency and oxygen-dependent photoactivity, resulting in unsatisfactory performance, particularly under hypoxic conditions. Similarly, PTT encounters consistent insufficiencies in the photothermal conversion efficiency (PCE) of dyes. Additionally, the suboptimal phototherapeutic efficacy often exhibits a limited immune response. These factors collectively impose significant constraints on phototherapy in oncological applications, leading to limited tumor inhibition, tumor recurrence, and even metastasis.Unlike strategies that rely on external assistance with complicated systems, manipulating excited-state deactivation pathways in biocompatible dyes offers a universal way to systematically address these challenges. Our group has devoted considerable effort to achieving this goal. In this Account, we present and discuss our journey in optimizing excited-state energy-release pathways through regulating molecular charge transfer based on cyanine dyes, which are renowned for their exceptional photophysical properties and harmonious biocompatibility. The investigation begins with the introduction of amino groups in the meso position of a heptamethine cyanine dye, where the intramolecular charge transfer (ICT) effect causes a significant enlargement of the Stokes shift. Subsequently, ICT induced by introducing functional electron-deficient groups in cyanines is found to decrease the overlap of electron distribution or narrow the energy gaps of molecular frontier orbitals. Such modifications result in a reduction of the energy gaps between singlet and triplet states or an improvement in internal conversion, ultimately promoting phototherapy efficacy in both primary and distant tumors. Furthermore, with the intensification of the charge transfer effect aided by light, photoinduced intramolecular electron transfer occurs in some cyanines, leading to complete charge separation in the excited state. This process enhances the transition to the ground or triplet states, improving tumor phototherapy and inhibiting metastasis by increasing the PCE or the yield of reactive oxygen species, respectively. Shifting focus from intramolecular to intermolecular interactions, we successfully constructed and explored cyanines based on intermolecular charge transfer. These dyes, with excited-state dynamics mimicking natural photosynthesis, generate radicals and facilitate oxygen-independent hypoxic tumor PDT. Finally, we outlined the existing challenges and future directions for optimizing phototherapeutic efficacy by regulating molecular charge transfer. This Account provides molecular-level insights into improving phototherapeutic performance, offering valuable perspectives, and inspiring the development of functional dyes in other application fields.

Multiplexed Nanoscopy via Buffer Exchange

Understanding cellular functions, particularly in their intricate complexity, can greatly benefit from the spatial mapping of diverse molecules through multitarget single-molecule localization microscopy (SMLM). Existing methodologies, primarily restricting the encoding dimensions to color and lifetime or requiring cyclic staining, often involve broad chromatic detection, specialized optical configurations, or sophisticated labeling techniques. Here, we propose a simple approach called buffer-exchange stochastic optical reconstruction microscopy (beSTORM), which introduces an additional dimension to differentiate between single molecules irrespective of their spectral properties. This method leverages the distinguishable photoblinking responses to distinct buffer conditions, offering a straightforward yet effective means of fluorophore discrimination. Through buffer exchanges, beSTORM achieves multitarget SMLM imaging with minimal crosstalk. Direct integration with expansion microscopy (ExM) demonstrates its capability to resolve up to six proteins at the molecular level within a single emission color without chromatic aberration. Overall, beSTORM presents a highly compatible imaging platform, promising significant advancements in highly multiplexed nanoscopy for exploring multiple targets in biological systems with nanoscale precision.

Formation of EGFRwt/EGFRvIII homo- and hetero-dimers in glioblastoma cells as detected by single molecule localization microscopy

Super-resolution microscopy has been used to show the formation of receptor clusters and adapted lipid organization of cell membranes for many members of the ErbB receptor family. The clustering behaviour depends on the receptor size and shape, possibly ligand binding or expression activity. Using single molecule localization microscopy (SMLM), we also showed this typical clustering for the epidermal growth factor receptor variant III (EGFRvIII) in glioblastoma multiforme (GBM) cells. EGFRvIII is co-expressed with the wild type (EGFRwt) and both receptors are assumed to preferentially form hetero-dimers leading to transactivation and elevated oncogenic EGFR-signalling in GBM cells. Here, we analysed EGFRvIII and EGFRwt co-localization using our already described model system of the glioblastoma cell line DKMG, displaying endogenous EGFRvIII expression. Using EGFRvIII and EGFRwt specific antibodies, EGFR localization and their potential for dimerization in a given membrane cluster were analysed by dual colour SMLM supported by novel approaches of mathematic evaluations including Ripley statistics, persistent homology and similarity algorithms. Surprisingly, cluster analysis, Ripley point-to-point distance statistics for cluster geometry and persistent homology comparing cluster topology, revealed that both EGFRvIII and EGFRwt do primarily not form hetero-dimers but the results support the hypothesis that they tend to form homo-dimers. The ratio of homo-dimers obtained by this calculation was significantly higher (>5σ, standard deviation) than expected from randomly arranged points. In comparison, hetero-dimer formation was only slightly increased. We confirmed these data by immunoprecipitation, which show no co-precipitation of EGFRvIII and EGFRwt. Furthermore, we showed that the topology of the clusters was more similar among the same type than among the different types of receptors. Taken together, these data indicate that EGFRvIII does induce oncogenic signalling by homo-dimerisation and not preferentially by hetero-dimer formation with EGFRwt. These data offer a new perspective on EGFRvIII signalling which will lead to a better understanding of this tumour associated receptor variant in GBM.

Genetic association and machine learning improves discovery and prediction of type 1 diabetes

Type 1 diabetes (T1D) has a large genetic component, and expanded genetic studies of T1D can lead to novel biological and therapeutic discovery and improved risk prediction. In this study, we performed genetic association and fine-mapping analyses in 817,718 European ancestry samples genome-wide and 29,746 samples at the MHC locus, which identified 165 independent risk signals for T1D of which 19 were novel. We used risk variants to train a machine learning model (named T1GRS) to predict T1D, which highly differentiated T1D from non-disease and type 2 diabetes (T2D) in Europeans as well as African Americans at or beyond the level of current standards. We identified extensive non-linear interactions between risk loci in T1GRS, for example between HLA-DQB1*57 and INS, coding and non-coding HLA alleles, and DEXI, INS and other beta cell loci, that provided mechanistic insight and improved risk prediction. T1D individuals formed distinct clusters based on genetic features from T1GRS which had significant differences in age of onset, HbA1c, and renal disease severity. Finally, we provided T1GRS in formats to enhance accessibility of risk prediction to any user and computing environment. Overall, the improved genetic discovery and prediction of T1D will have wide clinical, therapeutic, and research applications.

Self-Blinking Thioflavin T for Super-resolution Imaging

Thioflavin T (ThT) is a typical dye used to visualize the aggregation and formation of fibrillar structures, e.g., amyloid fibrils and peptide nanofibrils. ThT has been considered to produce stable fluorescence when interacting with aggregated proteins. For single-molecule localization microscopy (SMLM)-based optical super-resolution imaging, a photoswitching/blinking fluorescence property is required. Here we demonstrate that, in contrast to previous reports, ThT exhibits intrinsic stochastic blinking properties, without the need for blinking imaging buffer, in stable binding conditions. The blinking properties (photon number, blinking time, and on-off duty cycle) of ThT at the single-molecule level (for ultralow concentrations) were investigated under different conditions. As a proof of concept, we performed SMLM imaging of ThT-labeled α-synuclein fibrils measured in air and PBS buffer.

From Blur to Brilliance: The Ascendance of Advanced Microscopy in Neuronal Cell Biology

The intricate network of the brain's neurons and synapses poses unparalleled challenges for research, distinct from other biological studies. This is particularly true when dissecting how neurons and their functional units work at a cell biological level. While traditional microscopy has been foundational, it was unable to reveal the deeper complexities of neural interactions. However, an imaging renaissance has transformed our capabilities. Advancements in light and electron microscopy, combined with correlative imaging, now achieve unprecedented resolutions, uncovering the most nuanced neural structures. Maximizing these tools requires more than just technical proficiency. It is crucial to align research aims, allocate resources wisely, and analyze data effectively. At the heart of this evolution is interdisciplinary collaboration, where various experts come together to translate detailed imagery into significant biological insights. This review navigates the latest developments in microscopy, underscoring both the promise of and prerequisites for bending this powerful tool set to understanding neuronal cell biology.

Tuning the excitation laser power in a stochastic optical reconstruction microscope for Alexa Fluor 647 dye in Vectashield mounting media

Super-resolution imaging techniques have fundamentally changed our understanding of cellular architecture and dynamics by surpassing the diffraction limit and enabling the visualization of subcellular details. The popular super-resolution method known as stochastic optical reconstruction microscopy (STORM) relies on the exact localization of single fluorescent molecules. The significance of employing Vectashield as a mounting medium for the super-resolution imaging scheme called direct STORM has recently been explored. Alexa Fluor 647 (AF647), one of the most popular dyes, shows significant blinking in Vectashield. However, to observe prominent blinking of the fluorophore for the reconstruction of super-resolved images, the power of the excitation laser needs to be tuned. This work demonstrates the tuning of excitation power density in the sample plane for superior imaging performance using AF647 in Vectashield. Samples comprising MDA-MB-231 breast cancer cell line are used for the experiments. The actin filaments of the cell are stained with phalloidin-conjugated AF647 dye. For the experiment, we employ a low-cost openFrame-based STORM system equipped with a programmable Arduino-regulated laser source emitting at 638 nm. An excitation power density of 0.60 kW/cm2 at 638 nm in the sample plane is observed to maximize the signal-to-noise ratio, the number of switching events, and the number of photons detected per event during image acquisition, thereby leading to the best imaging performance in terms of resolution. The outcome of this work will promote further STORM-based super-resolved imaging applications in cell biology using Alexa Fluor 647 in Vectashield.

4D Single-particle tracking with asynchronous read-out single-photon avalanche diode array detector

Single-particle tracking techniques enable investigation of the complex functions and interactions of individual particles in biological environments. Many such techniques exist, each demonstrating trade-offs between spatiotemporal resolution, spatial and temporal range, technical complexity, and information content. To mitigate these trade-offs, we enhanced a confocal laser scanning microscope with an asynchronous read-out single-photon avalanche diode array detector. This detector provides an image of the particle's emission, precisely reflecting its position within the excitation volume. This localization is utilized in a real-time feedback system to drive the microscope scanning mechanism and ensure the particle remains centered inside the excitation volume. As each pixel is an independent single-photon detector, single-particle tracking is combined with fluorescence lifetime measurement. Our system achieves 40 nm lateral and 60 nm axial localization precision with 100 photons and sub-millisecond temporal sampling for real-time tracking. Offline tracking can refine this precision to the microsecond scale. We validated the system's spatiotemporal resolution by tracking fluorescent beads with diffusion coefficients up to 10 μm2/s. Additionally, we investigated the movement of lysosomes in living SK-N-BE cells and measured the fluorescence lifetime of the marker expressed on a membrane protein. We expect that this implementation will open other correlative imaging and tracking studies.

How Transcription Factor Clusters Shape the Transcriptional Landscape

In eukaryotic cells, gene transcription typically occurs in discrete periods of promoter activity, interspersed with intervals of inactivity. This pattern deviates from simple stochastic events and warrants a closer examination of the molecular interactions that activate the promoter. Recent studies have identified transcription factor (TF) clusters as key precursors to transcriptional bursting. Often, these TF clusters form at chromatin segments that are physically distant from the promoter, making changes in chromatin conformation crucial for promoter-TF cluster interactions. In this review, I explore the formation and constituents of TF clusters, examining how the dynamic interplay between chromatin architecture and TF clustering influences transcriptional bursting. Additionally, I discuss techniques for visualizing TF clusters and provide an outlook on understanding the remaining gaps in this field.

Integrating bioengineering, super-resolution microscopy and mechanobiology in autophagy research: addendum to the guidelines (4th edition)

Recent key technological developments, such as super-resolution microscopy and microfabrication, enabled investigation of biological processes, including macroautophagy/autophagy, with unprecedented spatiotemporal resolution and control over experimental conditions. Such disruptive innovations deepened our capability to provide mechanistic understandings of the autophagic process and its causes. This addendum aims to expand the guidelines on autophagy in three key directions: optical methods enabling visualization of autophagic machinery beyond the diffraction-limited resolution; bioengineering enabling accurate designs and control over experimental conditions; and theoretical advances in mechanobiology connecting autophagy and mechanical processes of the cell. Abbreviation: 3D: three-dimensional; SIM: structured illumination microscopy; STORM: stochastic optical reconstruction microscopy.

Automatic dendritic spine segmentation in widefield fluorescence images reveal synaptic nanostructures distribution with super-resolution imaging

Dendritic spines are the main sites for synaptic communication in neurons, and alterations in their density, size, and shapes occur in many brain disorders. Current spine segmentation methods perform poorly in conditions with low signal-to-noise and resolution, particularly in the widefield images of thick (⍰ 10 μm) brain slices. Here, we combined two open-source machine-learning models to achieve automatic 3D spine segmentation in widefield diffraction-limited fluorescence images of neurons in thick brain slices. We validated the performance by comparison with manually segmented super-resolution images of spines reconstructed from direct stochastic optical reconstruction microscopy (dSTORM). Lastly, we show an application of our approach by combining spine segmentation from diffraction-limited images with dSTORM of synaptic protein PSD-95 in the same field-of-view. This allowed us to automatically analyze and quantify the nanoscale distribution of PSD-95 inside the spine. Importantly, we found the numbers, but not the average sizes, of synaptic nanomodules and nanodomains increase with spine size.

Ultrafast Super-Resolution Imaging Exploiting Spontaneous Blinking of Static Excimer Aggregates

Single-molecule localization methods have been popularly exploited to obtain super-resolved images of biological structures. However, the low blinking frequency of randomly switching emission states of individual fluorophores greatly limits the imaging speed of single-molecule localization microscopy (SMLM). Here we present an ultrafast SMLM technique exploiting spontaneous fluorescence blinking of cyanine dye aggregates confined to DNA framework nanostructures. The DNA template guides the formation of static excimer aggregates as a "light-harvesting nanoantenna", whereas intermolecular excitation energy transfer (EET) between static excimers causes collective ultrafast fluorescence blinking of fluorophore aggregates. This DNA framework-based strategy enables the imaging of DNA nanostructures with 12.5-fold improvement in speed compared to conventional SMLM. Further, we demonstrate the use of this strategy to track the movement of super-resolved DNA nanostructures for over 20 min in a microfluidic system. Thus, this ultrafast SMLM holds great potential for revealing the dynamic processes of biomacromolecules in living cells.

Machine Learning for Single-Molecule Localization Microscopy: From Data Analysis to Quantification

Single-molecule localization microscopy (SMLM) is a versatile tool for realizing nanoscale imaging with visible light and providing unprecedented opportunities to observe bioprocesses. The integration of machine learning with SMLM enhances data analysis by improving efficiency and accuracy. This tutorial aims to provide a comprehensive overview of the data analysis process and theoretical aspects of SMLM, while also highlighting the typical applications of machine learning in this field. By leveraging advanced analytical techniques, SMLM is becoming a powerful quantitative analysis tool for biological research.

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.

Heterogeneous density-based clustering with a dual-functional memristive array

In the big data era, the requirement for data clustering methods that can handle massive and heterogeneous datasets with varying distributions increases. This study proposes a clustering algorithm for data sets with heterogeneous density using a dual-mode memristor crossbar array for data clustering. The array consists of a Ta/HfO2/RuO2 memristor operating in analog or digital modes, controlled by the reset voltage. The digital mode shows low dispersion and a high resistance ratio, and the analog mode enables precise conductance tuning. The local outlier factor is introduced to handle a heterogeneous density, and the required Euclidean and K-distances within the given dataset are calculated in the analog mode in parallel. In the digital mode, clustering is performed based on the connectivity among data points after excluding the detected outliers. The proposed algorithm boasts linear time complexity for the entire process. Extensive evaluations of synthetic datasets demonstrate significant improvement over representative density-based algorithms, and the datasets with heterogeneous density are clustered feasibly. Finally, the proposed algorithm is used to cluster the single-molecule localization microscopy data, demonstrating the feasibility of the suggested method for real-world problems.

Thermo-Optoplasmonic Single-Molecule Sensing on Optical Microcavities

Whispering-gallery-mode (WGM) resonators are powerful instruments for single-molecule sensing in biological and biochemical investigations. WGM sensors leveraged by plasmonic nanostructures, known as optoplasmonic sensors, provide sensitivity down to single atomic ions. In this article, we describe that the response of optoplasmonic sensors upon the attachment of single protein molecules strongly depends on the intensity of WGM. At low intensity, protein binding causes red shifts of WGM resonance wavelengths, known as the reactive sensing mechanism. By contrast, blue shifts are obtained at high intensities, which we explain as thermo-optoplasmonic (TOP) sensing, where molecules transform absorbed WGM radiation into heat. To support our conclusions, we experimentally investigated seven molecules and complexes; we observed blue shifts for dye molecules, amino acids, and anomalous absorption of enzymes in the near-infrared spectral region. As an example of an application, we propose a physical model of TOP sensing that can be used for the development of single-molecule absorption spectrometers.

Avalanche-assisted transient optical phenomenon in aggregated toluidine blue dye

Pulse-modulated CW laser heat deposition modulates the darkness or the transparency of an aggregated medium in the high signal optical regimen. A recently reported work found that transient optical responses of molecular aggregates can be different depending on whether the sample is excited with a laser wavelength tuned within the absorption band of the monomer or within the absorption band of the aggregates. The different transient responses were attributed to different dynamic processes during the laser-induced disassembling of the molecular aggregates and may have implications in the field of organic electronics and optical devices, such as optical logical gates, optical power limiters and all-optical switching. In this paper laser beams with wavelengths of 663 nm and 532 nm were used to produce sudden changes in the thermodynamic equilibrium of the aggregation states of the ortho-toluidine blue dye, which allowed to observe the occurrence of the avalanche - mediated transient phenomenon in the laser-induced disassembling of ortho-toluidine blue (TBO) aggregates. A double exponential model was adjusted to the registered transient data. The obtained values for the fast components of the transient time responses of ortho-toluidine blue dye, for the studied concentrations, ranged from ∼ 6.5 to 9.5 ms at 532 nm, and from ∼ 43 to 48 ms at 663 nm. A single beam experiment was employed to evaluate the performance of the ortho-toluidine blue dye in a beam power-damping device, driven by the simultaneous and cooperative actions of the laser induced disassembling of aggregated dye units and the thermal lensing effect. It was found that the phenomenon of laser-induced dye disassembling of TBO, acting cooperatively with the thermal lensing effect, damps the laser beam power faster than the thermal lensing phenomenon alone. In addition, the results showed that the speed of the laser beam power-damping is dye dependent.

Near-Infrared Spontaneously Blinking Fluorophores for Live Cell Super-Resolution Imaging with Minimized Phototoxicity

Single-molecule localization microscopy (SMLM) requires high-intensity laser irradiation, typically exceeding kW/cm2, to yield a sufficient photon count. However, this intense visible light exposure incurs substantial cellular toxicity, hindering its use in living cells. Here, we developed a class of near-infrared (NIR) spontaneously blinking fluorophores for SMLM. These NIR fluorophores are a combination of rhodamine spirolactams and merocyanine derivatives, where the rhodamine spirolactam component converts between a bright and dark state based on pH-dependent spirocyclization and merocyanine derivatives shift the excitation wavelength into the infrared. Single-molecule characterizations demonstrated their potential for SMLM. At a moderate power density of 3.93 kW/cm2, these probes exhibit duty cycle as low as 0.18% and an emission rate as high as 26,700 photons/s. Phototoxicity assessment under single-molecule imaging conditions reveals that NIR illumination (721 nm) minimizes harm to living cells. Employing these NIR fluorophores, we successfully captured time-lapse super-resolution tracking of mitochondria at a Fourier ring correlation (FRC) resolution of 69.4 nm and reconstructed the ultrastructures of endoplasmic reticulum (ER) in living cells.

Temporal-Focusing Multiphoton Excitation Single-Molecule Localization Microscopy Using Spontaneously Blinking Fluorophores

Single-molecule localization microscopy (SMLM) based on temporal-focusing multiphoton excitation (TFMPE) and single-wavelength excitation is used to visualize the three-dimensional (3D) distribution of spontaneously blinking fluorophore-labeled subcellular structures in a thick specimen with a nanoscale-level spatial resolution. To eliminate the photobleaching effect of unlocalized molecules in out-of-focus regions for improving the utilization rate of the photon budget in 3D SMLM imaging, SMLM with single-wavelength TFMPE achieves wide-field and axially confined two-photon excitation (TPE) of spontaneously blinking fluorophores. TPE spectral measurement of blinking fluorophores is then conducted through TFMPE imaging at a tunable excitation wavelength, yielding the optimal TPE wavelength for increasing the number of detected photons from a single blinking event during SMLM. Subsequently, the TPE fluorescence of blinking fluorophores is recorded to obtain a two-dimensional TFMPE-SMLM image of the microtubules in cancer cells with a localization precision of 18±6 nm and an overall imaging resolution of approximately 51 nm, which is estimated based on the contribution of Nyquist resolution and localization precision. Combined with astigmatic imaging, the system is capable of 3D TFMPE-SMLM imaging of brain tissue section of a 5XFAD transgenic mouse with the pathological features of Alzheimer's disease, revealing the distribution of neurotoxic amyloid-beta peptide deposits.

Photoswitching Reagent for Super-Resolution Fluorescence Microscopy

Single-molecule localization microscopy (SMLM) has revolutionized optical microscopy by exceeding the diffraction limit and revealing previously unattainable nanoscale details of cellular structures and molecular dynamics. This super-resolution imaging capability relies on fluorophore photoswitching, which is crucial for optimizing the imaging conditions and accurately determining the fluorophore positions. To understand the general on and off photoswitching mechanisms of single dye molecules, various photoswitching reagents were evaluated. Systematic measurement of the single-molecule-level fluorescence on and off rates (kon and koff) in the presence of various photoswitching reagents and theoretical calculation of the structure of the photoswitching reagent-fluorophore pair indicated that the switch-off mechanism is mainly determined by the nucleophilicity of the photoswitching reagent, and the switch-on mechanism is a two-photon-induced dissociation process, which is related to the power of the illuminating laser and bond dissociation energy of this pair. This study contributes to a broader understanding of the molecular photoswitching mechanism in SMLM imaging and provides a basis for designing improved photoswitching reagents with potential applications extending to materials science and chemistry.

From feulgen to modern methods: marking a century of DNA imaging advances

The mystery of how human DNA is compactly packaged into a nucleus-a space a hundred thousand times smaller-while still allowing for the regulation of gene function, has long been one of the greatest enigmas in cell biology. This puzzle is gradually being solved, thanks in part to the advent of new technologies. Among these, innovative genome-labeling techniques combined with high-resolution imaging methods have been pivotal. These methods facilitate the visualization of DNA within intact nuclei and have significantly contributed to our current understanding of genome organization. This review will explore various labeling and imaging approaches that are revolutionizing our understanding of the three-dimensional organization of the genome, shedding light on the relationship between its structure and function.

Practical Bayesian Inference in Neuroscience: Or How I Learned to Stop Worrying and Embrace the Distribution

Typical statistical practices in the biological sciences have been increasingly called into question due to difficulties in the replication of an increasing number of studies, many of which are confounded by the relative difficulty of null significance hypothesis testing designs and interpretation of p-values. Bayesian inference, representing a fundamentally different approach to hypothesis testing, is receiving renewed interest as a potential alternative or complement to traditional null significance hypothesis testing due to its ease of interpretation and explicit declarations of prior assumptions. Bayesian models are more mathematically complex than equivalent frequentist approaches, which have historically limited applications to simplified analysis cases. However, the advent of probability distribution sampling tools with exponential increases in computational power now allows for quick and robust inference under any distribution of data. Here we present a practical tutorial on the use of Bayesian inference in the context of neuroscientific studies in both rat electrophysiological and computational modeling data. We first start with an intuitive discussion of Bayes' rule and inference followed by the formulation of Bayesian-based regression and ANOVA models using data from a variety of neuroscientific studies. We show how Bayesian inference leads to easily interpretable analysis of data while providing an open-source toolbox to facilitate the use of Bayesian tools.

3D Traction Force Microscopy in Biological Gels: From Single Cells to Multicellular Spheroids

Cell traction force plays a critical role in directing cellular functions, such as proliferation, migration, and differentiation. Current understanding of cell traction force is largely derived from 2D measurements where cells are plated on 2D substrates. However, 2D measurements do not recapitulate a vital aspect of living systems; that is, cells actively remodel their surrounding extracellular matrix (ECM), and the remodeled ECM, in return, can have a profound impact on cell phenotype and traction force generation. This reciprocal adaptivity of living systems is encoded in the material properties of biological gels. In this review, we summarize recent progress in measuring cell traction force for cells embedded within 3D biological gels, with an emphasis on cell-ECM cross talk. We also provide perspectives on tools and techniques that could be adapted to measure cell traction force in complex biochemical and biophysical environments.

DNA Framework-Guided Self-Limiting Aggregation for Highly Luminescent Metal Cluster Nanoaggregates

The photoluminescent properties of atomically precise metal nanoclusters (MCs) have garnered significant attention in the fields of chemical sensing and biological imaging. However, the limited brightness of single-component nanoclusters hinders their practical applications, and the conventional ligand engineering approaches have proven insufficient in enhancing the emission efficiency of MCs. Here, we present a DNA framework-guided strategy to prepare highly luminescent metal cluster nanoaggregates. Our approach involves an amphiphilic DNA framework comprising a hydrophobic alkyl core and a rigid DNA framework shell, serving as a nucleation site and providing well-defined nanoconfinements for the self-limiting aggregation of MCs. Through this method, we successfully produced homogeneous MC nanoaggregates (10.1 ± 1.2 nm) with remarkable nanoscale precision. Notably, this strategy proves adaptable to various MCs, leading to a substantial enhancement in emission and quantum yield, up to 3011- and 87-fold, respectively. Furthermore, our investigation using total internal reflection fluorescence microscopy at the single-particle level uncovered a more uniform photon number distribution and higher photostability for MC nanoaggregates compared to template-free counterparts. This DNA-templating strategy introduces a conceptually innovative approach for studying the photoluminescent properties of aggregates with nanoscale precision and holds promise for constructing highly luminescent MC nanoparticles for diverse applications.

Development and Application of Cationic Nile Blue Probes in Live-Cell Super-Resolution Imaging and Specific Targeting to Mitochondria

Mitochondria are essential organelles involved in various metabolic processes in eukaryotes. The imaging, targeting, and investigation of cell death mechanisms related to mitochondria have garnered significant interest. Small-molecule fluorescent probes have proven to be robust tools for utilizing light to advance the study of mitochondrial biology. In this study, we present the rational design of cationic Nile blue probes carrying a permanent positive charge for these purposes. The cationic Nile blue probes exhibit excellent mitochondrial permeability, unique solvatochromism, and resistance to oxidation. We observed weaker fluorescence in aqueous solutions compared to lipophilic solvents, thereby minimizing background fluorescence in the cytoplasm. Additionally, we achieved photoredox switching of the cationic Nile blue probes under mild conditions. This enabled us to demonstrate their application for the first time in single-molecule localization microscopy of mitochondria, allowing us to observe mitochondrial fission and fusion behaviors. Compared to conventional cyanine fluorophores, this class of dyes demonstrated prolonged resistance to photobleaching, likely due to their antioxidation properties. Furthermore, we extended the application of cationic Nile blue probes to the mitochondria-specific delivery of taxanes, facilitating the study of direct interactions between the drug and organelles. Our approach to triggering cell death without reliance on microtubule binding provides valuable insights into anticancer drug research and drug-resistance mechanisms.

Nanoscale insights into hematology: super-resolved imaging on blood cell structure, function, and pathology

Fluorescence nanoscopy, also known as super-resolution microscopy, has transcended the conventional resolution barriers and enabled visualization of biological samples at nanometric resolutions. A series of super-resolution techniques have been developed and applied to investigate the molecular distribution, organization, and interactions in blood cells, as well as the underlying mechanisms of blood-cell-associated diseases. In this review, we provide an overview of various fluorescence nanoscopy technologies, outlining their current development stage and the challenges they are facing in terms of functionality and practicality. We specifically explore how these innovations have propelled forward the analysis of thrombocytes (platelets), erythrocytes (red blood cells) and leukocytes (white blood cells), shedding light on the nanoscale arrangement of subcellular components and molecular interactions. We spotlight novel biomarkers uncovered by fluorescence nanoscopy for disease diagnosis, such as thrombocytopathies, malignancies, and infectious diseases. Furthermore, we discuss the technological hurdles and chart out prospective avenues for future research directions. This review aims to underscore the significant contributions of fluorescence nanoscopy to the field of blood cell analysis and disease diagnosis, poised to revolutionize our approach to exploring, understanding, and managing disease at the molecular level.

Single-Digit Nanobubble Sensing via Nanopore Technology

Nanobubbles play an important role in diverse fields, including engineering, medicine, and agriculture. Understanding the characteristics of individual nanobubbles is essential for comprehending fluid dynamics behaviors and advancing nanoscale science across various fields. Here, we report a strategy based on nanopore sensors for characterizing single-digit nanobubbles. We investigated the sizes and diffusion coefficients of nanobubbles at different voltages. Additionally, the finite element simulation and molecular dynamics simulation were introduced to account for counterion concentration variation around nanobubbles in the nanopore. In particular, the differences in stability and surface charge density of nanobubbles under various solution environments have been studied by the ion-stabilized model and the DLVO theory. Additionally, a straightforward method to mitigate nanobubble generation in the bulk for reducing current noise in nanopore sensing was suggested. The results hold significant implications for enhancing the understanding of individual nanobubble characterizations, especially in the nanofluid field.

Can repetitive mechanical motion cause structural damage to axons?

Biological structures have evolved to very efficiently generate, transmit, and withstand mechanical forces. These biological examples have inspired mechanical engineers for centuries and led to the development of critical insights and concepts. However, progress in mechanical engineering also raises new questions about biological structures. The past decades have seen the increasing study of failure of engineered structures due to repetitive loading, and its origin in processes such as materials fatigue. Repetitive loading is also experienced by some neurons, for example in the peripheral nervous system. This perspective, after briefly introducing the engineering concept of mechanical fatigue, aims to discuss the potential effects based on our knowledge of cellular responses to mechanical stresses. A particular focus of our discussion are the effects of mechanical stress on axons and their cytoskeletal structures. Furthermore, we highlight the difficulty of imaging these structures and the promise of new microscopy techniques. The identification of repair mechanisms and paradigms underlying long-term stability is an exciting and emerging topic in biology as well as a potential source of inspiration for engineers.

Cis inhibition of co-expressed DIPs and Dprs shapes neural development

In Drosophila , two interacting adhesion protein families, Dprs and DIPs, coordinate the assembly of neural networks. While intercellular DIP/Dpr interactions have been well characterized, DIPs and Dprs are often co-expressed within the same cells, raising the question as to whether they also interact in cis . We show, in cultured cells and in vivo, that DIP-α and DIP-δ can interact in cis with their ligands, Dpr6/10 and Dpr12, respectively. When co-expressed in cis with their cognate partners, these Dprs regulate the extent of trans binding, presumably through competitive cis interactions. We demonstrate the neurodevelopmental effects of cis inhibition in fly motor neurons and in the mushroom body. We further show that a long disordered region of DIP-α at the C-terminus is required for cis but not trans interactions, likely because it alleviates geometric constraints on cis binding. Thus, the balance between cis and trans interactions plays a role in controlling neural development.

OM2Seq: learning retrieval embeddings for optical genome mapping

Motivation

Genomics-based diagnostic methods that are quick, precise, and economical are essential for the advancement of precision medicine, with applications spanning the diagnosis of infectious diseases, cancer, and rare diseases. One technology that holds potential in this field is optical genome mapping (OGM), which is capable of detecting structural variations, epigenomic profiling, and microbial species identification. It is based on imaging of linearized DNA molecules that are stained with fluorescent labels, that are then aligned to a reference genome. However, the computational methods currently available for OGM fall short in terms of accuracy and computational speed.

Results

This work introduces OM2Seq, a new approach for the rapid and accurate mapping of DNA fragment images to a reference genome. Based on a Transformer-encoder architecture, OM2Seq is trained on acquired OGM data to efficiently encode DNA fragment images and reference genome segments to a common embedding space, which can be indexed and efficiently queried using a vector database. We show that OM2Seq significantly outperforms the baseline methods in both computational speed (by 2 orders of magnitude) and accuracy.

Availability and implementation

https://github.com/yevgenin/om2seq.

Super-resolution microscopies, technological breakthrough to decipher mitochondrial structure and dynamic

Mitochondria are complex organelles with an outer membrane enveloping a second inner membrane that creates a vast matrix space partitioned by pockets or cristae that join the peripheral inner membrane with several thin junctions. Several micrometres long, mitochondria are generally close to 300 nm in diameter, with membrane layers separated by a few tens of nanometres. Ultrastructural data from electron microscopy revealed the structure of these mitochondria, while conventional optical microscopy revealed their extraordinary dynamics through fusion, fission, and migration processes but its limited resolution power restricted the possibility to go further. By overcoming the limits of light diffraction, Super-Resolution Microscopy (SRM) now offers the potential to establish the links between the ultrastructure and remodelling of mitochondrial membranes, leading to major advances in our understanding of mitochondria's structure-function. Here we review the contributions of SRM imaging to our understanding of the relationship between mitochondrial structure and function. What are the hopes for these new imaging approaches which are particularly important for mitochondrial pathologies?

hydroSIM: super-resolution speckle illumination microscopy with a hydrogel diffuser

Super-resolution microscopy has emerged as an indispensable methodology for probing the intricacies of cellular biology. Structured illumination microscopy (SIM), in particular, offers an advantageous balance of spatial and temporal resolution, allowing for visualizing cellular processes with minimal disruption to biological specimens. However, the broader adoption of SIM remains hampered by the complexity of instrumentation and alignment. Here, we introduce speckle-illumination super-resolution microscopy using hydrogel diffusers (hydroSIM). The study utilizes the high scattering and optical transmissive properties of hydrogel materials and realizes a remarkably simplified approach to plug-in super-resolution imaging via a common epi-fluorescence platform. We demonstrate the hydroSIM system using various phantom and biological samples, and the results exhibited effective 3D resolution doubling, optical sectioning, and high contrast. We foresee hydroSIM, a cost-effective, biocompatible, and user-accessible super-resolution methodology, to significantly advance a wide range of biomedical imaging and applications.

Site-specific protein labeling strategies for super-resolution microscopy

Super-resolution microscopy (SRM) has transformed our understanding of proteins' subcellular organization and revealed cellular details down to nanometers, far beyond conventional microscopy. While localization precision is independent of the number of fluorophores attached to a biomolecule, labeling density is a decisive factor for resolving complex biological structures. The average distance between adjacent fluorophores should be less than half the desired spatial resolution for optimal clarity. While this was not a major limitation in recent decades, the success of modern microscopy approaching molecular resolution down to the single-digit nanometer range will depend heavily on advancements in fluorescence labeling. This review highlights recent advances and challenges in labeling strategies for SRM, focusing on site-specific labeling technologies. These advancements are crucial for improving SRM precision and expanding our understanding of molecular interactions.

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

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

Triggered cagedSTORM microscopy

In standard SMLM methods, the photoswitching of single fluorescent molecules and the data acquisition processes are independent, which leads to the detection of single molecule blinking events on several consecutive frames. This mismatch results in several data points with reduced localization precision, and it also increases the possibilities of overlapping. Here we discuss how the synchronization of the fluorophores' ON state to the camera exposure time increases the average intensity of the captured point spread functions and hence improves the localization precision. Simulations and theoretical results show that such synchronization leads to fewer localizations with 15% higher sum signal on average, while reducing the probability of overlaps by 10%.

Fluorogenic polymethine dyes by intramolecular cyclization

Fluorescence imaging plays a pivotal role in the study of biological processes, and cell-permeable fluorogenic dyes are crucial to visualize intracellular structures with high specificity. Polymethine dyes are vitally important fluorophores in single-molecule localization microscopy and in vivo imaging, but their use in live cells has been limited by high background fluorescence and low membrane permeability. In this review, we summarize recent advances in the development of fluorogenic polymethine dyes via intramolecular cyclization. Finally, we offer an outlook on the prospects of fluorogenic polymethine dyes for bioimaging.

Single-Molecule Spectroscopy and Super-Resolution Mapping of Physicochemical Parameters in Living Cells

By superlocalizing the positions of millions of single molecules over many camera frames, a class of super-resolution fluorescence microscopy methods known as single-molecule localization microscopy (SMLM) has revolutionized how we understand subcellular structures over the past decade. In this review, we highlight emerging studies that transcend the outstanding structural (shape) information offered by SMLM to extract and map physicochemical parameters in living mammalian cells at single-molecule and super-resolution levels. By encoding/decoding high-dimensional information-such as emission and excitation spectra, motion, polarization, fluorescence lifetime, and beyond-for every molecule, and mass accumulating these measurements for millions of molecules, such multidimensional and multifunctional super-resolution approaches open new windows into intracellular architectures and dynamics, as well as their underlying biophysical rules, far beyond the diffraction limit.

Sub-Diffraction Correlation of Quantum Emitters and Local Strain Fields in Strain-Engineered WSe2 Monolayers

Strain-engineering in atomically thin metal dichalcogenides is a useful method for realizing single-photon emitters (SPEs) for quantum technologies. Correlating SPE position with local strain topography is challenging due to localization inaccuracies from the diffraction limit. Currently, SPEs are assumed to be positioned at the highest strained location and are typically identified by randomly screening narrow-linewidth emitters, of which only a few are spectrally pure. In this work, hyperspectral quantum emitter localization microscopy is used to locate 33 SPEs in nanoparticle-strained WSe2 monolayers with sub-diffraction-limit resolution (≈30 nm) and correlate their positions with the underlying strain field via image registration. In this system, spectrally pure emitters are not concentrated at the highest strain location due to spectral contamination; instead, isolable SPEs are distributed away from points of peak strain with an average displacement of 240 nm. These observations point toward a need for a change in the design rules for strain-engineered SPEs and constitute a key step toward realizing next-generation quantum optical architectures.

Live-cell imaging powered by computation

The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. The prevailing challenge in live-cell fluorescence microscopy is capturing intra-cellular dynamics while preserving cell viability. Computational methods can help to address this challenge and are now shifting the boundaries of what is possible to capture in living systems. In this Review, we discuss these computational methods focusing on artificial intelligence-based approaches that can be layered on top of commonly used existing microscopies as well as hybrid methods that integrate computation and microscope hardware. We specifically discuss how computational approaches can improve the signal-to-noise ratio, spatial resolution, temporal resolution and multi-colour capacity of live-cell imaging.

IgG and IgM differentiation in a particle-based agglutination assay by control over antigen surface density

Point-of-care (POC) testing offers fast and on-site diagnostics and can be crucial against many infectious diseases and in screening. One remaining challenge in serological POC testing is the quantification of immunoglobulin G (IgG) and immunoglobulin M (IgM). Quantification of IgG/IgM can be important to evaluate immunity and to discriminate recent infections from past infections and primary infections from secondary infections. POC tests such as lateral flow immunoassays allow IgG and IgM differentiation; however, a remaining limitation is their incapacity to provide quantitative results. In this work, we show how samples containing IgG or IgM can be distinguished in a nanoparticle-based agglutination biosensing assay by tuning the density of antigens on the nanoparticles' surface. We employ direct STochastic Optical Reconstruction Microscopy to quantify the accessible SARS-CoV-2 trimeric spike proteins conjugated to magnetic nanoparticles at a single-particle level and gain insight into the protein distribution provided by the conjugation procedure. Furthermore, we measure the anti-SARS-CoV-2 IgG/IgM induced agglutination using an optomagnetic readout principle. We show that particles with high antigen density have a relatively higher sensitivity toward IgM compared to IgG, whereas low antigen density provides a relatively higher sensitivity to IgG. The finding paves the way for its implementation for other agglutination-based serology tests, allowing for more accurate disease diagnosis.

Deep learning-based spectroscopic single-molecule localization microscopy

Significance

Spectroscopic single-molecule localization microscopy (sSMLM) takes advantage of nanoscopy and spectroscopy, enabling sub-10 nm resolution as well as simultaneous multicolor imaging of multi-labeled samples. Reconstruction of raw sSMLM data using deep learning is a promising approach for visualizing the subcellular structures at the nanoscale.

Aim

Develop a novel computational approach leveraging deep learning to reconstruct both label-free and fluorescence-labeled sSMLM imaging data.

Approach

We developed a two-network-model based deep learning algorithm, termed DsSMLM, to reconstruct sSMLM data. The effectiveness of DsSMLM was assessed by conducting imaging experiments on diverse samples, including label-free single-stranded DNA (ssDNA) fiber, fluorescence-labeled histone markers on COS-7 and U2OS cells, and simultaneous multicolor imaging of synthetic DNA origami nanoruler.

Results

For label-free imaging, a spatial resolution of 6.22 nm was achieved on ssDNA fiber; for fluorescence-labeled imaging, DsSMLM revealed the distribution of chromatin-rich and chromatin-poor regions defined by histone markers on the cell nucleus and also offered simultaneous multicolor imaging of nanoruler samples, distinguishing two dyes labeled in three emitting points with a separation distance of 40 nm. With DsSMLM, we observed enhanced spectral profiles with 8.8% higher localization detection for single-color imaging and up to 5.05% higher localization detection for simultaneous two-color imaging.

Conclusions

We demonstrate the feasibility of deep learning-based reconstruction for sSMLM imaging applicable to label-free and fluorescence-labeled sSMLM imaging data. We anticipate our technique will be a valuable tool for high-quality super-resolution imaging for a deeper understanding of DNA molecules' photophysics and will facilitate the investigation of multiple nanoscopic cellular structures and their interactions.

LiveLattice: Real-time visualization of tilted light-sheet microscopy data using a memory-efficient transformation algorithm

Light-sheet fluorescence microscopy (LSFM), a prominent fluorescence microscopy technique, offers enhanced temporal resolution for imaging biological samples in four dimensions (4D; x, y, z, time). Some of the most recent implementations, including inverted selective plane illumination microscopy (iSPIM) and lattice light-sheet microscopy (LLSM), rely on a tilting of the sample plane with respect to the light sheet of 30-45 degrees to ease sample preparation. Data from such tilted-sample-plane LSFMs require subsequent deskewing and rotation for proper visualization and analysis. Such transformations currently demand substantial memory allocation. This poses computational challenges, especially with large datasets. The consequence is long processing times compared to data acquisition times, which currently limits the ability for live-viewing the data as it is being captured by the microscope. To enable the fast preprocessing of large light-sheet microscopy datasets without significant hardware demand, we have developed WH-Transform, a novel GPU-accelerated memory-efficient algorithm that integrates deskewing and rotation into a single transformation, significantly reducing memory requirements and reducing the preprocessing run time by at least 10-fold for large image stacks. Benchmarked against conventional methods and existing software, our approach demonstrates linear scalability. Processing large 3D stacks of up to 15 GB is now possible within one minute using a single GPU with 24 GB of memory. Applied to 4D LLSM datasets of human hepatocytes, human lung organoid tissue, and human brain organoid tissue, our method outperforms alternatives, providing rapid, accurate preprocessing within seconds. Importantly, such processing speeds now allow visualization of the raw microscope data stream in real time, significantly improving the usability of LLSM in biology. In summary, this advancement holds transformative potential for light-sheet microscopy, enabling real-time, on-the-fly data processing, visualization, and analysis on standard workstations, thereby revolutionizing biological imaging applications for LLSM, SPIM and similar light microscopes.

Advancements and Practical Considerations for Biophysical Research: Navigating the Challenges and Future of Super-resolution Microscopy

The introduction of super-resolution microscopy (SRM) has significantly advanced our understanding of cellular and molecular dynamics, offering a detailed view previously beyond our reach. Implementing SRM in biophysical research, however, presents numerous challenges. This review addresses the crucial aspects of utilizing SRM effectively, from selecting appropriate fluorophores and preparing samples to analyzing complex data sets. We explore recent technological advancements and methodological improvements that enhance the capabilities of SRM. Emphasizing the integration of SRM with other analytical methods, we aim to overcome inherent limitations and expand the scope of biological insights achievable. By providing a comprehensive guide for choosing the most suitable SRM methods based on specific research objectives, we aim to empower researchers to explore complex biological processes with enhanced precision and clarity, thereby advancing the frontiers of biophysical research.

Enhanced fluorescence blinking of AF647 fluorophores in Mowiol via violet and UV light induced recovery for superior localization microscopy

Blinking of fluorophores is essential in the context of single molecule localization-based optical super-resolution microscopy methods. To make the fluorescence molecule undergo blinking specific complex chemical mounting buffer systems, combined with suitable oxygen scavengers, and reducing agents are required. For instance to realise blinking in widely used fluorescence tags, like Alexa Fluor 647 (AF647), they are to be mounted on anti-fading buffer such as Mowiol and reducing agent such as Beta (β) - ME. However, the quality of the super-resolved images is decided by the total number of blinking events or in other words net duration for which the fluorescence blinking persists. In this paper we investigate how a violet and UV light induced fluorescence recovery mechanism can enhance the duration of fluorescence blinking. Our study uses AF647 dye conjugated with Phalloidin antibody in U87MG cell line mounted on Mowiol andβ- ME. On the basis of the investigation we optimize the intensity, at the sample plane, of fluorescence excitation laser at 638 nm and fluorescence recovery beam at 405 nm or in the UV giving the maximum possible fluorescence blinking duration. We observe that the longer blinking duration, using the optimized illumination scheme, has brought down the resolution in the super-resolved image, as given by Fourier Ring Correlation method, from 168 nm to 112 nm, while the separation between two nearby resolvable filaments has been brought down to ≤ 60 nm.

STORM Super-Resolution Visualization of Self-Assembled γPFD Chaperone Ultrastructures in Methanocaldococcus jannaschii

Gamma-prefoldin (γPFD), a unique chaperone found in the extremely thermophilic methanogen Methanocaldococcus jannaschii, self-assembles into filaments in vitro, which so far have been observed using transmission electron microscopy and cryo-electron microscopy. Utilizing three-dimensional stochastic optical reconstruction microscopy (3D-STORM), here we achieve ∼20 nm resolution by precisely locating individual fluorescent molecules, hence resolving γPFD ultrastructure both in vitro and in vivo. Through CF647 NHS ester labeling, we first demonstrate the accurate visualization of filaments and bundles with purified γPFD. Next, by implementing immunofluorescence labeling after creating a 3xFLAG-tagged γPFD strain, we successfully visualize γPFD in M. jannaschii cells. Through 3D-STORM and two-color STORM imaging with DNA, we show the widespread distribution of filamentous γPFD structures within the cell. These findings provide valuable insights into the structure and localization of γPFD, opening up possibilities for studying intriguing nanoscale components not only in archaea but also in other microorganisms.

Single-molecule localization microscopy at 2.4-fold resolution improvement with optical lattice pattern illumination

Traditional camera-based single-molecule localization microscopy (SMLM), with its high imaging resolution and localization throughput, has made significant advancements in biological and chemical researches. However, due to the limitation of the fluorescence signal-to-noise ratio (SNR) of a single molecule, its resolution is difficult to reach to 5 nm. Optical lattice produces a nondiffracting beam pattern that holds the potential to enhance microscope performance through its high contrast and penetration depth. Here, we propose a new method named LatticeFLUX which utilizes the wide-field optical lattice pattern illumination for individual molecule excitation and localization. We calculated the Cramér-Rao lower bound of LatticeFLUX resolution and proved that our method can improve the single molecule localization precision by 2.4 times compared with the traditional SMLM. We propose a scheme using 9-frame localization, which solves the problem of uneven lattice light illumination. Based on the experimental single-molecule fluorescence SNR, we coded the image reconstruction software to further verify the resolution enhancement capability of LatticeFLUX on simulated punctate DNA origami, line pairs, and cytoskeleton. LatticeFLUX confirms the feasibility of using 2D structured light illumination to obtain high single-molecule localization precision under high localization throughput. It paves the way for further implementation of ultra-high resolution full 3D structured-light-illuminated SMLM.