PYMEVisualize: an open-source tool for exploring 3D super-resolution data

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.

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.

Super-Resolution Analysis of the Origins of the Elementary Events of ER Calcium Release in Dorsal Root Ganglion Neurons

Coordinated events of calcium (Ca2+) released from the endoplasmic reticulum (ER) are key second messengers in excitable cells. In pain-sensing dorsal root ganglion (DRG) neurons, these events can be observed as Ca2+ sparks, produced by a combination of ryanodine receptors (RyR) and inositol 1,4,5-triphosphate receptors (IP3R1). These microscopic signals offer the neuronal cells with a possible means of modulating the subplasmalemmal Ca2+ handling, initiating vesicular exocytosis. With super-resolution dSTORM and expansion microscopies, we visualised the nanoscale distributions of both RyR and IP3R1 that featured loosely organised clusters in the subplasmalemmal regions of cultured rat DRG somata. We adapted a novel correlative microscopy protocol to examine the nanoscale patterns of RyR and IP3R1 in the locality of each Ca2+ spark. We found that most subplasmalemmal sparks correlated with relatively small groups of RyR whilst larger sparks were often associated with larger groups of IP3R1. These data also showed spontaneous Ca2+ sparks in <30% of the subplasmalemmal cell area but consisted of both these channel species at a 3.8-5 times higher density than in nonactive regions of the cell. Taken together, these observations reveal distinct patterns and length scales of RyR and IP3R1 co-clustering at contact sites between the ER and the surface plasmalemma that encode the positions and the quantity of Ca2+ released at each Ca2+ spark.

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.

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.

Correlative super-resolution analysis of cardiac calcium sparks and their molecular origins in health and disease

Rapid release of calcium from internal stores via ryanodine receptors (RyRs) is one of the fastest types of cytoplasmic second messenger signalling in excitable cells. In the heart, rapid summation of the elementary events of calcium release, 'calcium sparks', determine the contraction of the myocardium. We adapted a correlative super-resolution microscopy protocol to correlate sub-plasmalemmal spontaneous calcium sparks in rat right ventricular myocytes with the local nanoscale RyR2 positions. This revealed a steep relationship between the integral of a calcium spark and the sum of the local RyR2s. Segmentation of recurring spark sites showed evidence of repeated and triggered saltatory activation of multiple local RyR2 clusters. In myocytes taken from failing right ventricles, RyR2 clusters themselves showed a dissipated morphology and fragmented (smaller) clusters. They also featured greater heterogeneity in both the spark properties and the relationship between the integral of the calcium spark and the local ensemble of RyR2s. While fragmented (smaller) RyR2 clusters were rarely observed directly underlying the larger sparks or the recurring spark sites, local interrogation of the channel-to-channel distances confirmed a clear link between the positions of each calcium spark and the tight, non-random clustering of the local RyR2 in both healthy and failing ventricles.

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.

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.

The miEye: Bench-top super-resolution microscope with cost-effective equipment

Commercial super-resolution (SR) imaging systems require a high budget, while current more affordable open source microscopy systems lack modularity and sometimes are too complex or lack reliability. We present miEye - a cost-effective microscope designed for high-resolution wide-field fluorescence imaging. The build is constructed using a CNC milled aluminum microscope body and commercially available optomechanics, with open-source Python-based microscope control, data visualization, and analysis software integration. The data acquisition software works robustly with commonly used industrial-grade complementary metal oxide semiconductor (iCMOS) cameras, performs IR beam back-reflection-based automatic focus stabilization, and allows for laser control via an Arduino-based laser relay. The open-source nature of the design is aimed to facilitate adaptation by the community. The build can be constructed for a cost of roughly 50 k €. It contains SM-fiber and MM-fiber excitation paths that are easy to interchange and an adaptable emission path. Also, it ensures <5 nm/min stability of the sample on all axes, and allows achieving <30 nm lateral resolution for dSTORM and DNA-PAINT single-molecule localization microscopy (SMLM) experiments. Thus it serves as a cost-effective and adaptable addition to the open source microscopy community and potentially will allow high-quality SR imaging even for limited-budget research groups.

Isotropic imaging across spatial scales with axially swept light-sheet microscopy

Light-sheet fluorescence microscopy is a rapidly growing technique that has gained tremendous popularity in the life sciences owing to its high-spatiotemporal resolution and gentle, non-phototoxic illumination. In this protocol, we provide detailed directions for the assembly and operation of a versatile light-sheet fluorescence microscopy variant, referred to as axially swept light-sheet microscopy (ASLM), that delivers an unparalleled combination of field of view, optical resolution and optical sectioning. To democratize ASLM, we provide an overview of its working principle and applications to biological imaging, as well as pragmatic tips for the assembly, alignment and control of its optical systems. Furthermore, we provide detailed part lists and schematics for several variants of ASLM that together can resolve molecular detail in chemically expanded samples, subcellular organization in living cells or the anatomical composition of chemically cleared intact organisms. We also provide software for instrument control and discuss how users can tune imaging parameters to accommodate diverse sample types. Thus, this protocol will serve not only as a guide for both introductory and advanced users adopting ASLM, but as a useful resource for any individual interested in deploying custom imaging technology. We expect that building an ASLM will take ~1-2 months, depending on the experience of the instrument builder and the version of the instrument.

A density-based enrichment measure for assessing colocalization in single-molecule localization microscopy data

Dual-color single-molecule localization microscopy (SMLM) provides unprecedented possibilities for detailed studies of colocalization of different molecular species in a cell. However, the informational richness of the data is not fully exploited by current analysis tools that often reduce colocalization to a single value. Here, we describe a tool specifically designed for determination of co-localization in both 2D and 3D from SMLM data. The approach uses a function that describes the relative enrichment of one molecular species on the density distribution of a reference species. The function reframes the question of colocalization by providing a density-context relevant to multiple biological questions. Moreover, the function visualize enrichment (i.e. colocalization) directly in the images for easy interpretation. We demonstrate the approach’s functionality on both simulated data and cultured neurons, and compare it to current alternative measures. The method is available in a Python function for easy and parameter-free implementation.

Full information gained from single-molecule localisation microscopy (SMLM) isn't exploited by current analysis tools. Here the authors report relative enrichment which uses a density-based colocalisation measure for both 2D and 3D SMLM data; they apply it to both simulated data and cultured neurons.

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.

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.

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

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