Biological Insight from Super-Resolution Microscopy: What We Can Learn from Localization-Based Images

Resolution in super-resolution microscopy - facts, artifacts, technological advancements and biological applications

Super-resolution microscopy (SRM) has undeniable potential for scientific discovery, yet still presents many challenges that hinder its widespread adoption, including technical trade-offs between resolution, speed and photodamage, as well as limitations in imaging live samples and larger, more complex biological structures. Furthermore, SRM often requires specialized expertise and complex instrumentation, which can deter biologists from fully embracing the technology. In this Perspective, a follow-up to our recent Q&A article, we aim to demystify these challenges by addressing common questions and misconceptions surrounding SRM. Experts offer practical insights into how biologists can maximize the benefits of SRM while navigating issues such as photobleaching, image artifacts and the limitations of existing techniques. We also highlight recent developments in SRM that continue to push the boundaries of resolution. Our goal is to equip researchers with the crucial knowledge they need to harness the full potential of SRM.

Super-resolution algorithms for imaging FCS enhancement: A comparative study

Understanding the structure and dynamics of biological systems is often limited by the trade-off between spatial and temporal resolution. Imaging fluorescence correlation spectroscopy (ImFCS) is a powerful technique for capturing molecular dynamics with high temporal precision but remains diffraction limited. This constraint poses challenges for quantifying dynamics of subcellular structures like membrane-proximal cortical actin fibers. Computational super-resolution microscopy (CSRM) presents an accessible strategy for enhancing spatial resolution without specialized instrumentation, enabling compatibility with ImFCS. In this study, we evaluated various CSRM techniques, including super-resolution radial fluctuations, mean-shift super-resolution, and multiple signal classification imaging, using total internal reflection fluorescence datasets of actin fibers labeled with F-tractin-mApple. By combining structural masks from total internal reflection fluorescence and CSRM, we distinguished off-fiber, mixed, and on-fiber regions for region-specific diffusion analyses. Although all CSRM algorithms improve ImFCS data analysis, super-resolution radial fluctuations demonstrated superior performance in identifying cortical actin fibers, showing minimal variance in on-fiber diffusion coefficients. These findings establish a framework for integrating CSRM with ImFCS to achieve high-resolution spatial and dynamic characterization of subcellular structures from single measurements.

Microscopy methods for the in vivo study of nanoscale nuclear organization

Eukaryotic genomes are highly compacted within the nucleus and organized into complex 3D structures across various genomic and physical scales. Organization within the nucleus plays a key role in gene regulation, both facilitating regulatory interactions to promote transcription while also enabling the silencing of other genes. Despite the functional importance of genome organization in determining cell identity and function, investigating nuclear organization across this wide range of physical scales has been challenging. Microscopy provides the opportunity for direct visualization of nuclear structures and has pioneered key discoveries in this field. Nonetheless, visualization of nanoscale structures within the nucleus, such as nucleosomes and chromatin loops, requires super-resolution imaging to go beyond the ~220 nm diffraction limit. Here, we review recent advances in imaging technology and their promise to uncover new insights into the organization of the nucleus at the nanoscale. We discuss different imaging modalities and how they have been applied to the nucleus, with a focus on super-resolution light microscopy and its application to in vivo systems. Finally, we conclude with our perspective on how continued technical innovations in super-resolution imaging in the nucleus will advance our understanding of genome structure and function.

Modelling 3D supramolecular structure from sparse single-molecule localisation microscopy data

Single-molecule localisation microscopy (SMLM) has the potential to reveal the underlying organisation of specific molecules within supramolecular complexes and their conformations, which is not possible with conventional microscope resolution. However, the detection efficiency for fluorescent molecules in cells can be limited in SMLM, even to below 1% in thick and dense samples. Segmentation of individual complexes can also be challenging. To overcome these problems, we have developed a software package termed PERPL: Pattern Extraction from Relative Positions of Localisations. This software assesses the relative likelihoods of models for underlying patterns behind incomplete SMLM data, based on the relative positions of pairs of localisations. We review its principles and demonstrate its use on the 3D lattice of Z-disk proteins in mammalian cardiomyocytes. We find known and novel features at ~20 nm with localisations of less than 1% of the target proteins, using mEos fluorescent protein constructs.

Transient, nano-scale, liquid-like molecular assemblies coming of age

This review examines the dynamic mechanisms underlying cellular signaling, communication, and adhesion via transient, nano-scale, liquid-like molecular assemblies on the plasma membrane (PM). Traditional views posit that stable, solid-like molecular complexes perform these functions. However, advanced imaging reveals that many signaling and scaffolding proteins only briefly reside in these molecular complexes and that micron-scale protein assemblies on the PM, including cell adhesion structures and synapses, are likely made of archipelagoes of nanoliquid protein islands. Borrowing the concept of liquid-liquid phase separation to form micron-scale biocondensates, we propose that these nano-scale oligomers and assemblies are enabled by multiple weak but specific molecular interactions often involving intrinsically disordered regions. The signals from individual nanoliquid signaling complexes would occur as pulses. Single-molecule imaging emerges as a crucial technique for characterizing these transient nanoliquid assemblies on the PM, suggesting a shift toward a model where the fluidity of interactions underpins signal regulation and integration.

Impaired Experience-Dependent Theta Oscillation Synchronization and Inter-Areal Synaptic Connectivity in the Visual Cortex of Fmr1 KO Mice

Fragile X syndrome (FX) is the most prevalent inheritable form of autism spectrum disorder (ASD), characterized by hypersensitivity, difficulty in habituating to new sensory stimuli, and intellectual disability. Individuals with FX often experience visual perception and learning deficits. Visual experience leads to the emergence of the familiarity-evoked theta band oscillations in the primary visual cortex (V1) and the lateromedial area (LM) of mice. These theta oscillations in V1 and LM are synchronized with each other, providing a mechanism of sensory multi-areal binding. However, how this multi-areal binding and the corresponding theta oscillations are altered in FX is not known. Using iDISCO whole brain clearing with light-sheet microscopy, we quantified immediate early gene Fos expression in V1 and LM, identifying deficits in experience-dependent neural activity in FX mice. We performed simultaneous in vivo recordings with silicon probes in V1 and LM of awake mice and channelrhodopsin-2-assisted circuit mapping (CRACM) in acute brain slices to examine the neural activity and strength of long-range synaptic connections between V1 and LM in both wildtype (WT) and Fmr1 knockout (KO) mice, the model of FX, before and after visual experience. Our findings reveal synchronized familiarity-evoked theta oscillations in V1 and LM, the increased strength of V1→LM functional and synaptic connections, which correlated with the corresponding changes of presynaptic short-term plasticity in WT mice. The LM oscillations were attenuated in FX mice and correlated with impaired functional and synaptic connectivity and short-term plasticity in the feedforward (FF) V1→LM and feedback (FB) LM→V1 pathways. Finally, using 4Pi single-molecule localization microscopy (SMLM) in thick brain tissue, we identified experience-dependent changes in the density and shape of dendritic spines in layer 5 pyramidal cells of WT mice, which correlated with the functional synaptic measurements. Interestingly, there was an increased dendritic spine density and length in naïve FX mice that failed to respond to experience. Our study provides the first comprehensive characterization of the role of visual experience in triggering inter-areal neural synchrony and shaping synaptic connectivity in WT and FX mice.

Semiconducting polymer dots for multifunctional integrated nanomedicine carriers

The expansion applications of semiconducting polymer dots (Pdots) among optical nanomaterial field have long posed a challenge for researchers, promoting their intelligent application in multifunctional nano-imaging systems and integrated nanomedicine carriers for diagnosis and treatment. Despite notable progress, several inadequacies still persist in the field of Pdots, including the development of simplified near-infrared (NIR) optical nanoprobes, elucidation of their inherent biological behavior, and integration of information processing and nanotechnology into biomedical applications. This review aims to comprehensively elucidate the current status of Pdots as a classical nanophotonic material by discussing its advantages and limitations in terms of biocompatibility, adaptability to microenvironments in vivo, etc. Multifunctional integration and surface chemistry play crucial roles in realizing the intelligent application of Pdots. Information visualization based on their optical and physicochemical properties is pivotal for achieving detection, sensing, and labeling probes. Therefore, we have refined the underlying mechanisms and constructed multiple comprehensive original mechanism summaries to establish a benchmark. Additionally, we have explored the cross-linking interactions between Pdots and nanomedicine, potential yet complete biological metabolic pathways, future research directions, and innovative solutions for integrating diagnosis and treatment strategies. This review presents the possible expectations and valuable insights for advancing Pdots, specifically from chemical, medical, and photophysical practitioners' standpoints.

Nanoscale cellular organization of viral RNA and proteins in SARS-CoV-2 replication organelles

The SARS-CoV-2 viral infection transforms host cells and produces special organelles in many ways, and we focus on the replication organelles, the sites of replication of viral genomic RNA (vgRNA). To date, the precise cellular localization of key RNA molecules and replication intermediates has been elusive in electron microscopy studies. We use super-resolution fluorescence microscopy and specific labeling to reveal the nanoscopic organization of replication organelles that contain numerous vgRNA molecules along with the replication enzymes and clusters of viral double-stranded RNA (dsRNA). We show that the replication organelles are organized differently at early and late stages of infection. Surprisingly, vgRNA accumulates into distinct globular clusters in the cytoplasmic perinuclear region, which grow and accommodate more vgRNA molecules as infection time increases. The localization of endoplasmic reticulum (ER) markers and nsp3 (a component of the double-membrane vesicle, DMV) at the periphery of the vgRNA clusters suggests that replication organelles are encapsulated into DMVs, which have membranes derived from the host ER. These organelles merge into larger vesicle packets as infection advances. Precise co-imaging of the nanoscale cellular organization of vgRNA, dsRNA, and viral proteins in replication organelles of SARS-CoV-2 may inform therapeutic approaches that target viral replication and associated processes.

Nanoscale cellular organization of viral RNA and proteins in SARS-CoV-2 replication organelles

The SARS-CoV-2 viral infection transforms host cells and produces special organelles in many ways, and we focus on the replication organelle where the replication of viral genomic RNA (vgRNA) occurs. To date, the precise cellular localization of key RNA molecules and replication intermediates has been elusive in electron microscopy studies. We use super-resolution fluorescence microscopy and specific labeling to reveal the nanoscopic organization of replication organelles that contain vgRNA clusters along with viral double-stranded RNA (dsRNA) clusters and the replication enzyme, encapsulated by membranes derived from the host endoplasmic reticulum (ER). We show that the replication organelles are organized differently at early and late stages of infection. Surprisingly, vgRNA accumulates into distinct globular clusters in the cytoplasmic perinuclear region, which grow and accommodate more vgRNA molecules as infection time increases. The localization of ER labels and nsp3 (a component of the double-membrane vesicle, DMV) at the periphery of the vgRNA clusters suggests that replication organelles are enclosed by DMVs at early infection stages which then merge into vesicle packets as infection progresses. Precise co-imaging of the nanoscale cellular organization of vgRNA, dsRNA, and viral proteins in replication organelles of SARS-CoV-2 may inform therapeutic approaches that target viral replication and associated processes.

Bridging Smart Nanosystems with Clinically Relevant Models and Advanced Imaging for Precision Drug Delivery

Intracellular delivery of nano-drug-carriers (NDC) to specific cells, diseased regions, or solid tumors has entered the era of precision medicine that requires systematic knowledge of nano-biological interactions from multidisciplinary perspectives. To this end, this review first provides an overview of membrane-disruption methods such as electroporation, sonoporation, photoporation, microfluidic delivery, and microinjection with the merits of high-throughput and enhanced efficiency for in vitro NDC delivery. The impact of NDC characteristics including particle size, shape, charge, hydrophobicity, and elasticity on cellular uptake are elaborated and several types of NDC systems aiming for hierarchical targeting and delivery in vivo are reviewed. Emerging in vitro or ex vivo human/animal-derived pathophysiological models are further explored and highly recommended for use in NDC studies since they might mimic in vivo delivery features and fill the translational gaps from animals to humans. The exploration of modern microscopy techniques for precise nanoparticle (NP) tracking at the cellular, organ, and organismal levels informs the tailored development of NDCs for in vivo application and clinical translation. Overall, the review integrates the latest insights into smart nanosystem engineering, physiological models, imaging-based validation tools, all directed towards enhancing the precise and efficient intracellular delivery of NDCs.

Unraveling cellular complexity with transient adapters in highly multiplexed super-resolution imaging

Mapping the intricate spatial relationships between the many different molecules inside a cell is essential to understanding cellular functions in all their complexity. Super-resolution fluorescence microscopy offers the required spatial resolution but struggles to reveal more than four different targets simultaneously. Exchanging labels in subsequent imaging rounds for multiplexed imaging extends this number but is limited by its low throughput. Here, we present a method for rapid multiplexed super-resolution microscopy that can, in principle, be applied to a nearly unlimited number of molecular targets by leveraging fluorogenic labeling in conjunction with transient adapter-mediated switching for high-throughput DNA-PAINT (FLASH-PAINT). We demonstrate the versatility of FLASH-PAINT with four applications: mapping nine proteins in a single mammalian cell, elucidating the functional organization of primary cilia by nine-target imaging, revealing the changes in proximity of thirteen different targets in unperturbed and dissociated Golgi stacks, and investigating and quantifying inter-organelle contacts at 3D super-resolution.

Correlative super-resolution bright-field and fluorescence imaging by microsphere assisted microscopy

The resolution of fluorescence imaging has been significantly enhanced with the development of super-resolution imaging techniques, surpassing the diffraction limit and reaching sub-diffraction scales of tens of nanometers. However, the resolution of the bright-field images of cells is restricted by the diffraction limit, leading to a significant gap between the resolutions of fluorescence and bright-field imaging, which hinders the research of the precise distribution of intracellular nanostructures. A microsphere superlens offers a promising solution by providing label-free super-resolution imaging capabilities compatible with fluorescence super-resolution imaging. In this study, we used microsphere superlenses to simultaneously enhance the resolution of bright-field and fluorescence imaging, achieving correlated super-resolution bright-field and fluorescence imaging. Compared to conventional bright-field images, we improved the imaging resolution from λ/1.3 to λ/4.2. A correlative super-resolution of mouse skeletal muscle cells was achieved, enabling the clear observation of the precise distribution of nanoparticles in mouse skeletal muscle cells. Furthermore, microsphere superlenses inherit the advantages of optical imaging, which is expected to enable the capturing of ultrafast biological activity within living cells with extremely high temporal resolutions.

Oligomeric organization of membrane proteins from native membranes at nanoscale spatial and single-molecule resolution

The oligomeric organization of membrane proteins in native cell membranes is a critical regulator of their function. High-resolution quantitative measurements of oligomeric assemblies and how they change under different conditions are indispensable to understanding membrane protein biology. We report Native-nanoBleach, a total internal reflection fluorescence microscopy-based single-molecule photobleaching step analysis technique to determine the oligomeric distribution of membrane proteins directly from native membranes at an effective spatial resolution of ~10 nm. We achieved this by capturing target membrane proteins in native nanodiscs with their proximal native membrane environment using amphipathic copolymers. We applied Native-nanoBleach to quantify the oligomerization status of structurally and functionally diverse membrane proteins, including a receptor tyrosine kinase (TrkA) and a small GTPase (KRas) under growth-factor binding and oncogenic mutations, respectively. Our data suggest that Native-nanoBleach provides a sensitive, single-molecule platform to quantify membrane protein oligomeric distributions in native membranes under physiologically and clinically relevant conditions.

Small-Angle X-Ray Scattering for Macromolecular Complexes

Small angle X-ray scattering (SAXS) is a versatile technique that can provide unique insights in the solution structure of macromolecules and their complexes, covering the size range from small peptides to complete viral assemblies. Technological and conceptual advances in the last two decades have tremendously improved the accessibility of the technique and transformed it into an indispensable tool for structural biology. In this chapter we introduce and discuss several approaches to collecting SAXS data on macromolecular complexes, including several approaches to online chromatography. We include practical advice on experimental design and point out common pitfalls of the technique.

Roadmap on Label-Free Super-Resolution Imaging

Label-free super-resolution (LFSR) imaging relies on light-scattering processes in nanoscale objects without a need for fluorescent (FL) staining required in super-resolved FL microscopy. The objectives of this Roadmap are to present a comprehensive vision of the developments, the state-of-the-art in this field, and to discuss the resolution boundaries and hurdles which need to be overcome to break the classical diffraction limit of the LFSR imaging. The scope of this Roadmap spans from the advanced interference detection techniques, where the diffraction-limited lateral resolution is combined with unsurpassed axial and temporal resolution, to techniques with true lateral super-resolution capability which are based on understanding resolution as an information science problem, on using novel structured illumination, near-field scanning, and nonlinear optics approaches, and on designing superlenses based on nanoplasmonics, metamaterials, transformation optics, and microsphere-assisted approaches. To this end, this Roadmap brings under the same umbrella researchers from the physics and biomedical optics communities in which such studies have often been developing separately. The ultimate intent of this paper is to create a vision for the current and future developments of LFSR imaging based on its physical mechanisms and to create a great opening for the series of articles in this field.

An integrated platform for high-throughput nanoscopy

Single-molecule localization microscopy enables three-dimensional fluorescence imaging at tens-of-nanometer resolution, but requires many camera frames to reconstruct a super-resolved image. This limits the typical throughput to tens of cells per day. While frame rates can now be increased by over an order of magnitude, the large data volumes become limiting in existing workflows. Here we present an integrated acquisition and analysis platform leveraging microscopy-specific data compression, distributed storage and distributed analysis to enable an acquisition and analysis throughput of 10,000 cells per day. The platform facilitates graphically reconfigurable analyses to be automatically initiated from the microscope during acquisition and remotely executed, and can even feed back and queue new acquisition tasks on the microscope. We demonstrate the utility of this framework by imaging hundreds of cells per well in multi-well sample formats. Our platform, implemented within the PYthon-Microscopy Environment (PYME), is easily configurable to control custom microscopes, and includes a plugin framework for user-defined extensions.

Imagining the future of optical microscopy: everything, everywhere, all at once

The optical microscope has revolutionized biology since at least the 17th Century. Since then, it has progressed from a largely observational tool to a powerful bioanalytical platform. However, realizing its full potential to study live specimens is hindered by a daunting array of technical challenges. Here, we delve into the current state of live imaging to explore the barriers that must be overcome and the possibilities that lie ahead. We venture to envision a future where we can visualize and study everything, everywhere, all at once - from the intricate inner workings of a single cell to the dynamic interplay across entire organisms, and a world where scientists could access the necessary microscopy technologies anywhere.

The nanoscale organization of reticulon 4 shapes local endoplasmic reticulum structure in situ

The endoplasmic reticulum's (ER's) structure is directly linked to the many functions of the ER, but its formation is not fully understood. We investigate how the ER-membrane curving protein reticulon 4 (Rtn4) localizes to and organizes in the membrane and how that affects the local ER structure. We show a strong correlation between the local Rtn4 density and the local ER membrane curvature. Our data further reveal that the typical ER tubule possesses an elliptical cross-section with Rtn4 enriched at either end of the major axis. Rtn4 oligomers are linear shaped, contain about five copies of the protein, and preferentially orient parallel to the tubule axis. Our observations support a mechanism in which oligomerization leads to an increase of the local Rtn4 concentration with each molecule, increasing membrane curvature through a hairpin wedging mechanism. This quantitative analysis of Rtn4 and its effects on the ER membrane result in a new model of tubule shape as it relates to Rtn4.

Extracting nanoscale membrane morphology from single-molecule localizations

Membrane surface reconstruction at the nanometer scale is required for understanding mechanisms of subcellular shape change. This historically has been the domain of electron microscopy, but extraction of surfaces from specific labels is a difficult task in this imaging modality. Existing methods for extracting surfaces from fluorescence microscopy have poor resolution or require high-quality super-resolution data that are manually cleaned and curated. Here, we present NanoWrap, a new method for extracting surfaces from generalized single-molecule localization microscopy data. This makes it possible to study the shape of specifically labeled membranous structures inside cells. We validate NanoWrap using simulations and demonstrate its reconstruction capabilities on single-molecule localization microscopy data of the endoplasmic reticulum and mitochondria. NanoWrap is implemented in the open-source Python Microscopy Environment.

Introducing Diinamic, a flexible and robust method for clustering analysis in single-molecule localization microscopy

Super-resolution microscopy allowed major improvements in our capacity to describe and explain biological organization at the nanoscale. Single-molecule localization microscopy (SMLM) uses the positions of molecules to create super-resolved images, but it can also provide new insights into the organization of molecules through appropriate pointillistic analyses that fully exploit the sparse nature of SMLM data. However, the main drawback of SMLM is the lack of analytical tools easily applicable to the diverse types of data that can arise from biological samples. Typically, a cloud of detections may be a cluster of molecules or not depending on the local density of detections, but also on the size of molecules themselves, the labeling technique, the photo-physics of the fluorophore, and the imaging conditions. We aimed to set an easy-to-use clustering analysis protocol adaptable to different types of data. Here, we introduce Diinamic, which combines different density-based analyses and optional thresholding to facilitate the detection of clusters. On simulated or real SMLM data, Diinamic correctly identified clusters of different sizes and densities, being performant even in noisy datasets with multiple detections per fluorophore. It also detected subdomains ("nanodomains") in clusters with non-homogeneous distribution of detections.

Tracking the Message: Applying Single Molecule Localization Microscopy to Cellular RNA Imaging

RNA function is increasingly appreciated to be more complex than merely communicating between DNA sequence and protein structure. RNA localization has emerged as a key contributor to the intricate roles RNA plays in the cell, and the link between dysregulated spatiotemporal localization and disease warrants an exploration beyond sequence and structure. However, the tools needed to visualize RNA with precise resolution are lacking in comparison to methods available for studying proteins. In the past decade, many techniques have been developed for imaging RNA, and in parallel super resolution and single-molecule techniques have enabled imaging of single molecules in cells. Of these methods, single molecule localization microscopy (SMLM) has shown significant promise for probing RNA localization. In this review, we highlight current approaches that allow super resolution imaging of specific RNA transcripts and summarize challenges and future opportunities for developing innovative RNA labeling methods that leverage the power of SMLM.

OregonFluor enables quantitative intracellular paired agent imaging to assess drug target availability in live cells and tissues

Non-destructive fluorophore diffusion across cell membranes to provide an unbiased fluorescence intensity readout is critical for quantitative imaging applications in live cells and tissues. Commercially available small-molecule fluorophores have been engineered for biological compatibility, imparting high water solubility by modifying rhodamine and cyanine dye scaffolds with multiple sulfonate groups. The resulting net negative charge, however, often renders these fluorophores cell-membrane-impermeant. Here we report the design and development of our biologically compatible, water-soluble and cell-membrane-permeable fluorophores, termed OregonFluor (ORFluor). By adapting previously established ratiometric imaging methodology using bio-affinity agents, it is now possible to use small-molecule ORFluor-labelled therapeutic inhibitors to quantitatively visualize their intracellular distribution and protein target-specific binding, providing a chemical toolkit for quantifying drug target availability in live cells and tissues.

Nondestructive inspection of surface nanostructuring using label-free optical super-resolution imaging

Ultrafast laser processing can induce surface nanostructurating (SNS) in most materials with dimensions close to the irradiation laser wavelength. In-situ SNS characterization could be key for laser parameter's fine-tuning, essential for the generation of complex and/or hybrid nanostructures. Laser Induced Periodic Surface Structures (LIPSS) created in the ultra-violet (UV) range generate the most fascinating effects. They are however highly challenging to characterize in a non-destructive manner since their dimensions can be as small as 100 nm. Conventional optical imaging methods are indeed limited by diffraction to a resolution of [Formula: see text] nm. Although optical super-resolution techniques can go beyond the diffraction limit, which in theory allows the visualization of LIPSS, most super-resolution methods require the presence of small probes (such as fluorophores) which modifies the sample and is usually incompatible with a direct surface inspection. In this paper, we demonstrate that a modified label-free Confocal Reflectance Microscope (CRM) in a photon reassignment regime (also called re-scan microscopy) can detect sub-diffraction limit LIPSS. SNS generated on a titanium sample irradiated with a [Formula: see text] nm femtosecond UV-laser were characterized with nanostructuring period ranging from 105 to 172 nm. Our label-free, non-destructive optical surface inspection was done at 180 [Formula: see text]m[Formula: see text]/s, and the results are compared with commercial SEM showing the metrological efficiency of our approach.

Advanced image-free analysis of the nano-organization of chromatin and other biomolecules by Single Molecule Localization Microscopy (SMLM)

The cell as a system of many components, governed by the laws of physics and chemistry drives molecular functions having an impact on the spatial organization of these systems and vice versa. Since the relationship between structure and function is an almost universal rule not only in biology, appropriate methods are required to parameterize the relationship between the structure and function of biomolecules and their networks, the mechanisms of the processes in which they are involved, and the mechanisms of regulation of these processes. Single molecule localization microscopy (SMLM), which we focus on here, offers a significant advantage for the quantitative parametrization of molecular organization: it provides matrices of coordinates of fluorescently labeled biomolecules that can be directly subjected to advanced mathematical analytical procedures without the need for laborious and sometimes misleading image processing. Here, we propose mathematical tools for comprehensive quantitative computer data analysis of SMLM point patterns that include Ripley distance frequency analysis, persistent homology analysis, persistent 'imaging', principal component analysis and co-localization analysis. The application of these methods is explained using artificial datasets simulating different, potentially possible and interpretatively important situations. Illustrative analyses of real complex biological SMLM data are presented to emphasize the applicability of the proposed algorithms. This manuscript demonstrated the extraction of features and parameters quantifying the influence of chromatin (re)organization on genome function, offering a novel approach to study chromatin architecture at the nanoscale. However, the ability to adapt the proposed algorithms to analyze essentially any molecular organizations, e.g., membrane receptors or protein trafficking in the cytosol, offers broad flexibility of use.

Extracting nanoscale membrane morphology from single-molecule localizations

Membrane surface reconstruction at the nanometer scale is required for understanding mechanisms of subcellular shape change. This historically has been the domain of electron microscopy, but extraction of surfaces from specific labels is a difficult task in this imaging modality. Existing methods for extracting surfaces from fluorescence microscopy have poor resolution or require high-quality super-resolution data that is manually cleaned and curated. Here we present a new method for extracting surfaces from generalized single-molecule localization microscopy (SMLM) data. This makes it possible to study the shape of specifically-labelled membraneous structures inside of cells. We validate our method using simulations and demonstrate its reconstruction capabilities on SMLM data of the endoplasmic reticulum and mitochondria. Our method is implemented in the open-source Python Microscopy Environment.

SIGNIFICANCE

We introduce a novel tool for reconstruction of subcellular membrane surfaces from single-molecule localization microscopy data and use it to visualize and quantify local shape and membrane-membrane interactions. We benchmark its performance on simulated data and demonstrate its fidelity to experimental data.

Super-resolution microscopy and studies of peroxisomes

Fluorescence microscopy is an important tool for studying cellular structures such as organelles. Unfortunately, many details in the corresponding images are hidden due to the resolution limit of conventional lens-based far-field microscopy. An example is the study of peroxisomes, where important processes such as molecular organization during protein important can simply not be studied with conventional far-field microscopy methods. A remedy is super-resolution fluorescence microscopy, which is nowadays a well-established technique for the investigation of inner-cellular structures but has so far to a lesser extent been applied to the study of peroxisomes. To help advancing the latter, we here give an overview over the different super-resolution microscopy approaches and their potentials and challenges in cell-biological research, including labelling issues and a focus on studies on peroxisomes. Here, we also highlight experiments beyond simple imaging such as observations of diffusion dynamics of peroxisomal proteins.

Determination of oligomeric organization of membrane proteins from native membranes at nanoscale-spatial and single-molecule resolution

The oligomeric organization of membrane proteins in native cell membranes is a critical regulator of their function. High-resolution quantitative measurements of oligomeric assemblies and how they change under different conditions are indispensable to the understanding of membrane protein biology. We report a single-molecule imaging technique (Native-nanoBleach) to determine the oligomeric distribution of membrane proteins directly from native membranes at an effective spatial resolution of ∼10 nm. We achieved this by capturing target membrane proteins in "native nanodiscs" with their proximal native membrane environment using amphipathic copolymers. We established this method using structurally and functionally diverse membrane proteins with well-established stoichiometries. We then applied Native-nanoBleach to quantify the oligomerization status of a receptor tyrosine kinase (TrkA) and a small GTPase (KRas) under conditions of growth-factor binding or oncogenic mutations, respectively. Native-nanoBleach provides a sensitive, single-molecule platform to quantify membrane protein oligomeric distributions in native membranes at an unprecedented spatial resolution.

The nanoscale organization of reticulon 4 shapes local endoplasmic reticulum structure in situ

The endoplasmic reticulum’s (ER) structure is directly linked to the many functions of the ER but its formation is not fully understood. We investigate how the ER-membrane curving protein reticulon 4 (Rtn4) localizes to and organizes in the membrane and how that affects local ER structure. We show a strong correlation between the local Rtn4 density and the local ER membrane curvature. Our data further reveal that the typical ER tubule possesses an elliptical cross-section with Rtn4 enriched at either end of the major axis. Rtn4 oligomers are linear-shaped, contain about five copies of the protein, and preferentially orient parallel to the tubule axis. Our observations support a mechanism in which oligomerization leads to an increase of the local Rtn4 concentration with each molecule increasing membrane curvature through a hairpin wedging mechanism. This quantitative analysis of Rtn4 and its effects on the ER membrane result in a new model of tubule shape as it relates to Rtn4.

SUMMARY

Rtn4 forms linear-shaped oligomers that contain an average of five Rtn4 proteins, localize to the sides of elliptical tubules, prefer orientations near parallel to the tubule axis, and increase local curvature of the ER membrane by increasing local Rtn4 density.

STORM Super-Resolution Imaging of CB1 Receptors in Tissue Preparations

Single-molecule localization microscopy (SMLM) opened new possibilities to study the spatial arrangement of molecular distribution and disease-associated redistribution at a previously unprecedented resolution that was not achievable with optical microscopy approaches. Recent discoveries based on SMLM techniques uncovered specific nanoscale organizational principles of signaling proteins in several biological systems including the chemical synapses in the brain. Emerging data suggest that the spatial arrangement of the molecular players of the endocannabinoid system is also precisely regulated at the nanoscale level in synapses and in other neuronal and glial subcellular compartments. The precise nanoscale distribution pattern is likely to be important to subserve several specific signaling functions of this important messenger system in a cell-type- and subcellular domain-specific manner.STochastic Optical Reconstruction Microscopy (STORM) is an especially suitable SMLM modality for cell-type-specific nanoscale molecular imaging due to its compatibility with traditional diffraction-limited microscopy approaches and classical staining methods. Here, we describe a detailed protocol for STORM imaging in mouse brain tissue samples with a focus on the CB₁ cannabinoid receptor, one of the most abundant synaptic receptors in the brain. We also summarize important conceptual and methodical details that are essential for the valid interpretation of single-molecule localization microscopy data.

Unbiased choice of global clustering parameters for single-molecule localization microscopy

Single-molecule localization microscopy resolves objects below the diffraction limit of light via sparse, stochastic detection of target molecules. Single molecules appear as clustered detection events after image reconstruction. However, identification of clusters of localizations is often complicated by the spatial proximity of target molecules and by background noise. Clustering results of existing algorithms often depend on user-generated training data or user-selected parameters, which can lead to unintentional clustering errors. Here we suggest an unbiased algorithm (FINDER) based on adaptive global parameter selection and demonstrate that the algorithm is robust to noise inclusion and target molecule density. We benchmarked FINDER against the most common density based clustering algorithms in test scenarios based on experimental datasets. We show that FINDER can keep the number of false positive inclusions low while also maintaining a low number of false negative detections in densely populated regions.

Unbiased choice of global clustering parameters for single-molecule localization microscopy

Single-molecule localization microscopy resolves objects below the diffraction limit of light via sparse, stochastic detection of target molecules. Single molecules appear as clustered detection events after image reconstruction. However, identification of clusters of localizations is often complicated by the spatial proximity of target molecules and by background noise. Clustering results of existing algorithms often depend on user-generated training data or user-selected parameters, which can lead to unintentional clustering errors. Here we suggest an unbiased algorithm (FINDER) based on adaptive global parameter selection and demonstrate that the algorithm is robust to noise inclusion and target molecule density. We benchmarked FINDER against the most common density based clustering algorithms in test scenarios based on experimental datasets. We show that FINDER can keep the number of false positive inclusions low while also maintaining a low number of false negative detections in densely populated regions.

Convex hull as diagnostic tool in single-molecule localization microscopy

MOTIVATION

Single-molecule localization microscopy resolves individual fluorophores or fluorescence-labeled biomolecules. Data are provided as a set of localizations that distribute normally around the true fluorophore position with a variance determined by the localization precision. Characterizing the spatial fluorophore distribution to differentiate between resolution-limited localization clusters, which resemble individual biomolecules, and extended structures, which represent aggregated molecular complexes, is a common challenge.

RESULTS

We demonstrate the use of the convex hull and related hull properties of localization clusters for diagnostic purposes, as a parameter for cluster selection or as a tool to determine localization precision.

AVAILABILITY AND IMPLEMENTATION

https://github.com/super-resolution/Ebert-et-al-2022-supplement.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Single-molecule counting applied to the study of GPCR oligomerization

Single-molecule counting techniques enable a precise determination of the intracellular abundance and stoichiometry of proteins and macromolecular complexes. These details are often challenging to quantitatively assess yet are essential for our understanding of cellular function. Consider G-protein-coupled receptors-an expansive class of transmembrane signaling proteins that participate in many vital physiological functions making them a popular target for drug development. While early evidence for the role of oligomerization in receptor signaling came from ensemble biochemical and biophysical assays, innovations in single-molecule measurements are now driving a paradigm shift in our understanding of its relevance. Here, we review recent developments in single-molecule counting with a focus on photobleaching step counting and the emerging technique of quantitative single-molecule localization microscopy-with a particular emphasis on the potential for these techniques to advance our understanding of the role of oligomerization in G-protein-coupled receptor signaling.

Stable, Bright, and Long-Fluorescence-Lifetime Dyes for Deep-Near-Infrared Bioimaging

Near-infrared (NIR) fluorophores absorbing maximally in the region beyond 800 nm, i.e., deep-NIR spectral region, are actively sought for biomedical applications. Ideal dyes are bright, nontoxic, photostable, biocompatible, and easily derivatized to introduce functionalities (e.g., for bioconjugation or aqueous solubility). The rational design of such fluorophores remains a major challenge. Silicon-substituted rhodamines have been successful for bioimaging applications in the red spectral region. The longer-wavelength silicon-substituted congeners for the deep-NIR spectral region are unknown to date. We successfully prepared four silicon-substituted bis-benzannulated rhodamine dyes (ESi5a-ESi5d), with an efficient five-step cascade on a gram-scale. Because of the extensive overlapping of their HOMO-LUMO orbitals, ESi5a-ESi5d are highly absorbing (λ_abs ≈ 865 nm and ε > 10⁵ cm^-1 M^-1). By restraining both the rotational freedom via annulation and the vibrational freedom via silicon-imparted strain, the fluorochromic scaffold of ESi5 is highly rigid, resulting in an unusually long fluorescence lifetime (τ > 700 ps in CH₂Cl₂) and a high fluorescence quantum yield (ϕ = 0.14 in CH₂Cl₂). Their half-lives toward photobleaching are 2 orders of magnitude longer than the current standard (ICG in serum). They are stable in the presence of biorelevant concentration of nucleophiles or reactive oxygen species. They are minimally toxic and readily metabolized. Upon tail vein injection of ESi5a (as an example), the vasculature of a nude mouse was imaged with a high signal-to-background ratio. ESi5 dyes have broad potentials for bioimaging in the deep-NIR spectral region.

Real-time image resolution measurement for single molecule localization microscopy

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

Nanoscale fluorescence imaging of biological ultrastructure via molecular anchoring and physical expansion

Nanoscale imaging of biological samples can provide rich morphological and mechanistic information about biological functions and dysfunctions at the subcellular and molecular level. Expansion microscopy (ExM) is a recently developed nanoscale fluorescence imaging method that takes advantage of physical enlargement of biological samples. In ExM, preserved cells and tissues are embedded in a swellable hydrogel, to which the molecules and fluorescent tags in the samples are anchored. When the hydrogel swells several-fold, the effective resolution of the sample images can be improved accordingly via physical separation of the retained molecules and fluorescent tags. In this review, we focus on the early conception and development of ExM from a biochemical and materials perspective. We first examine the general workflow as well as the numerous variations of ExM developed to retain and visualize a broad range of biomolecules, such as proteins, nucleic acids, and membranous structures. We then describe a number of inherent challenges facing ExM, including those associated with expansion isotropy and labeling density, as well as the ongoing effort to address these limitations. Finally, we discuss the prospect and possibility of pushing the resolution and accuracy of ExM to the single-molecule scale and beyond.

Genetically encodable fluorescent protein markers in advanced optical imaging

Optical fluorescence microscopy plays a pivotal role in the exploration of biological structure and dynamics, especially on live specimens. Progress in the field relies, on the one hand, on technical advances in imaging and data processing and, on the other hand, on progress in fluorescent marker technologies. Among these, genetically encodable fluorescent proteins (FPs) are invaluable tools, as they allow facile labeling of live cells, tissues or organisms, as these produce the FP markers all by themselves after introduction of a suitable gene. Here we cover FP markers from the GFP family of proteins as well as tetrapyrrole-binding proteins, which further complement the FP toolbox in important ways. A broad range of FP variants have been endowed, by using protein engineering, with photophysical properties that are essential for specific fluorescence microscopy techniques, notably those offering nanoscale image resolution. We briefly introduce various advanced imaging methods and show how they utilize the distinct properties of the FP markers in exciting imaging applications, with the aim to guide researchers toward the design of powerful imaging experiments that are optimally suited to address their biological questions.

Combining multiple fluorescence imaging techniques in biology: when one microscope is not enough

While fluorescence microscopy has proven to be an exceedingly useful tool in bioscience, it is difficult to offer simultaneous high resolution, fast speed, large volume, and good biocompatibility in a single imaging technique. Thus, when determining the image data required to quantitatively test a complex biological hypothesis, it often becomes evident that multiple imaging techniques are necessary. Recent years have seen an explosion in development of novel fluorescence microscopy techniques, each of which features a unique suite of capabilities. In this Technical Perspective, we highlight recent studies to illustrate the benefits, and often the necessity, of combining multiple fluorescence microscopy modalities. We provide guidance in choosing optimal technique combinations to effectively address a biological question. Ultimately, we aim to promote a more well-rounded approach in designing fluorescence microscopy experiments, leading to more robust quantitative insight.

Fluorogenic DNA-PAINT for faster, low-background super-resolution imaging

DNA-based points accumulation for imaging in nanoscale topography (DNA-PAINT) is a powerful super-resolution microscopy method that can acquire high-fidelity images at nanometer resolution. It suffers, however, from high background and slow imaging speed, both of which can be attributed to the presence of unbound fluorophores in solution. Here we present two-color fluorogenic DNA-PAINT, which uses improved imager probe and docking strand designs to solve these problems. These self-quenching single-stranded DNA probes are conjugated with a fluorophore and quencher at the terminals, which permits an increase in fluorescence by up to 57-fold upon binding and unquenching. In addition, the engineering of base pair mismatches between the fluorogenic imager probes and docking strands allowed us to achieve both high fluorogenicity and the fast binding kinetics required for fast imaging. We demonstrate a 26-fold increase in imaging speed over regular DNA-PAINT and show that our new implementation enables three-dimensional super-resolution DNA-PAINT imaging without optical sectioning.

A coordinate-based co-localization index to quantify and visualize spatial associations in single-molecule localization microscopy

Visualizing the subcellular distribution of proteins and determining whether specific proteins co-localize is one of the main strategies in determining the organization and potential interactions of protein complexes in biological samples. The development of super-resolution microscopy techniques such as single-molecule localization microscopy (SMLM) has tremendously increased the ability to resolve protein distribution at nanometer resolution. As super-resolution imaging techniques are becoming instrumental in revealing novel biological insights, new quantitative approaches that exploit the unique nature of SMLM datasets are required. Here, we present a new, local density-based algorithm to quantify co-localization in dual-color SMLM datasets. We show that this method is broadly applicable and only requires molecular coordinates and their localization precision as inputs. Using simulated point patterns, we show that this method robustly measures the co-localization in dual-color SMLM datasets, independent of localization density, but with high sensitivity towards local enrichments. We further validated our method using SMLM imaging of the microtubule network in epithelial cells and used it to study the spatial association between proteins at neuronal synapses. Together, we present a simple and easy-to-use, but powerful method to analyze the spatial association of molecules in dual-color SMLM datasets.

LOCAN: a python library for analyzing single-molecule localization microscopy data

SUMMARY

Single-molecule localization microscopy has become an important part of the super-resolution microscopy toolbox in biomedical research. Software platforms for applying analytical methods to the point-based data structures are needed that offer both routine application and flexible customization of analysis procedures. We present a python library called LOCAN that consists of well-defined data structures and analysis methods for analyzing localization data in a script or computable notebook.

AVAILABILITY AND IMPLEMENTATION

The package source code is released open-source under a BSD-3 license at https://github.com/super-resolution/Locan. It can be installed form the Python Package Index at https://pypi.org/project/locan. Documentation is available at https://locan.readthedocs.io.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Don’t Be Fooled by Randomness: Valid p-Values for Single Molecule Microscopy

The human mind shows extraordinary capability at recognizing patterns, while at the same time tending to underestimate the natural scope of random processes. Taken together, this easily misleads researchers in judging whether the observed characteristics of their data are of significance or just the outcome of random effects. One of the best tools to assess whether observed features fall into the scope of pure randomness is statistical significance testing, which quantifies the probability to falsely reject a chosen null hypothesis. The central parameter in this context is the p-value, which can be calculated from the recorded data sets. In case of p-values smaller than the level of significance, the null hypothesis is rejected, otherwise not. While significance testing has found widespread application in many sciences including the life sciences, it is hardly used in (bio-)physics. We propose here that significance testing provides an important and valid addendum to the toolbox of quantitative (single molecule) biology. It allows to support a quantitative judgement (the hypothesis) about the data set with a probabilistic assessment. In this manuscript we describe ways for obtaining valid p-values in two selected applications of single molecule microscopy: (i) Nanoclustering in single molecule localization microscopy. Previously, we developed a method termed 2-CLASTA, which allows to calculate a valid p-value for the null hypothesis of an underlying random distribution of molecules of interest while circumventing overcounting issues. Here, we present an extension to this approach, yielding a single overall p-value for data pooled from multiple cells or experiments. (ii) Single molecule trajectories. Data from a single molecule trajectory are inherently correlated, thus prohibiting a direct analysis via conventional statistical tools. Here, we introduce a block permutation test, which yields a valid p-value for the analysis and comparison of single molecule trajectory data. We exemplify the approach based on FRET trajectories.

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

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

Imaging Approaches for the Study of Metabolism in Real Time Using Genetically Encoded Reporters

Metabolism comprises of two axes in order to serve homeostasis: anabolism and catabolism. Both axes are interbranched with the so-called bioenergetics aspect of metabolism. There is a plethora of analytical biochemical methods to monitor metabolites and reactions in lysates, yet there is a rising need to monitor, quantify and elucidate in real time the spatiotemporal orchestration of complex biochemical reactions in living systems and furthermore to analyze the metabolic effect of chemical compounds that are destined for the clinic. The ongoing technological burst in the field of imaging creates opportunities to establish new tools that will allow investigators to monitor dynamics of biochemical reactions and kinetics of metabolites at a resolution that ranges from subcellular organelle to whole system for some key metabolites. This article provides a mini review of available toolkits to achieve this goal but also presents a perspective on the open space that can be exploited to develop novel methodologies that will merge classic biochemistry of metabolism with advanced imaging. In other words, a perspective of "watching metabolism in real time."

Branched Proximity Hybridization Assay for the Quantification of Nanoscale Protein-Protein Proximity

To better quantify the nanoscale protein-protein proximity, we developed a new branched proximity hybridization assay (bPHA). In this assay, oligo-coupled target protein-binding reagents, such as aptamer, nanobody, and antibodies, are used to convert the proximity of target proteins to the proximity of a pair of designed oligos. The closely positioned oligo pair then serve as a template for a maximum of 400-fold linear signal amplification through branched DNA (bDNA). The amplified bPHA signal is recorded and quantified by flow cytometer, providing high throughput, multiplexing, and single-cell resolution for nanoscale protein proximity studies.

Single-Molecule Localization Microscopy of Subcellular Protein Distribution in Neurons

Over the past years several forms of superresolution fluorescence microscopy have been developed that offer the possibility to study cellular structures and protein distribution at a resolution well below the diffraction limit of conventional fluorescence microscopy (<200 nm). A particularly powerful superresolution technique is single-molecule localization microscopy (SMLM). SMLM enables the quantitative investigation of subcellular protein distribution at a spatial resolution up to tenfold higher than conventional imaging, even in live cells. Not surprisingly, SMLM has therefore been used in many applications in biology, including neuroscience. This chapter provides a step-by-step SMLM protocol to visualize the nanoscale organization of endogenous proteins in dissociated neurons but can be extended to image other adherent cultured cells. We outline a number of methods to visualize endogenous proteins in neurons for live-cell and fixed application, including immunolabeling, the use of intrabodies for live-cell SMLM, and endogenous tagging using CRISPR/Cas9.

Snake Toxins Labeled by Green Fluorescent Protein or Its Synthetic Chromophore are New Probes for Nicotinic acetylcholine Receptors

Fluorescence can be exploited to monitor intermolecular interactions in real time and at a resolution up to a single molecule. It is a method of choice to study ligand-receptor interactions. However, at least one of the interacting molecules should possess good fluorescence characteristics, which can be achieved by the introduction of a fluorescent label. Gene constructs with green fluorescent protein (GFP) are widely used to follow the expression of the respective fusion proteins and monitor their function. Recently, a small synthetic analogue of GFP chromophore (p-HOBDI-BF₂) was successfully used for tagging DNA molecules, so we decided to test its applicability as a potential fluorescent label for proteins and peptides. This was done on α-cobratoxin (α-CbTx), a three-finger protein used as a molecular marker of muscle-type, neuronal α7 and α9/α10 nicotinic acetylcholine receptors (nAChRs), as well as on azemiopsin, a linear peptide neurotoxin selectively inhibiting muscle-type nAChRs. An activated N-hydroxysuccinimide ester of p-HOBDI-BF₂ was prepared and utilized for toxin labeling. For comparison we used a recombinant α-CbTx fused with a full-length GFP prepared by expression of a chimeric gene. The structure of modified toxins was confirmed by mass spectrometry and their activity was characterized by competition with iodinated α-bungarotoxin in radioligand assay with respective receptor preparations, as well as by thermophoresis. With the tested protein and peptide neurotoxins, introduction of the synthetic GFP chromophore induced considerably lower decrease in their affinity for the receptors as compared with full-length GFP attachment. The obtained fluorescent derivatives were used for nAChR visualization in tissue slices and cell cultures.