Versatile, do-it-yourself, low-cost spinning disk confocal microscope.

Expansion microscopy (ExM) is a powerful high-resolution imaging technique that enhances the spatial resolution of conventional light microscopy by physically enlarging biological specimens by embedding and cross-linking them in a swellable polymer network. This review explores the combination of ExM with commonly used advanced fluorescence imaging modalities, including light sheet fluorescence microscopy (LSFM), stimulated emission depletion (STED), structured illumination microscopy (SIM), single-molecule localisation microscopy (SMLM), and computational super-resolution radial fluctuations (SRRF) to push the boundaries of achievable resolution in biological imaging. By integrating ExM with these optical and analytical approaches, researchers can visualise subcellular structures and molecular complexes with unprecedented clarity, enabling the study of intricate biological processes that are otherwise inaccessible with conventional light microscopy methods. The review covers the theoretical resolutions attainable with each combined technique, example biological questions they can address, and key considerations for optimising their use. Together, these advancements offer novel insights into nanoscale cellular and subcellular structures, opening new avenues for exploration in fields such as neuroscience, cancer research, and developmental biology.

Caveolae are plasma membrane invaginations whose formation requires caveolin-1 (Cav1), the adaptor protein polymerase I, and the transcript release factor (PTRF or CAVIN1). Caveolae have an important role in cell functioning, signaling, and disease. In the absence of CAVIN1/PTRF, Cav1 forms non-caveolar membrane domains called scaffolds. In this work, we train machine learning models to automatically distinguish between caveolae and scaffolds from single molecule localization microscopy (SMLM) data. We apply machine and deep learning algorithms to discriminate biological structures from SMLM data. Our work is the first that is leveraging machine and deep learning approaches to automatically identifying biological structures from SMLM data. In particular, we develop and compare three binary classification methods to identify whether or not a given 3D cluster of Cav1 proteins is a caveolae. The first uses a random forest classifier applied to 28 hand-picked features, the second uses a convolutional neural net (CNN) applied to a projection of the point clouds onto three planes, and the third uses a PointNet model, a recent development that can directly take point clouds as its input. We validate our methods on a dataset of super-resolution microscopy images of PC3 prostate cancer cells labeled for Cav1. Specifically, we have images from two cell populations: 10 PC3 and 10 CAVIN1/PTRF-transfected PC3 cells (PC3-PTRF cells) that form caveolae. We obtained a balanced set of 1714 different cellular structures. Our results show that both the random forest on hand selected features and the deep learning approach achieve high accuracy in distinguishing the intrinsic features of the caveolae and non-caveolae biological structures. More specifically, both random forest and deep CNN classifiers achieve classification accuracy reaching 94% on our test set, while the PointNet model only reached 83% accuracy. We also discuss the pros and cons of the different approaches. Additional information about individual files is in the accompanying CSV file (item_metadata.csv). This dataset was originally deposited in the Simon Fraser University institutional repository.

Chapter 5 Multicolor laser scanning confocal immunofluorescence microscopy: Practical application and limitations

Label-retention expansion microscopy toward molecular resolution

The workhorse of developmental biology is the confocal microscope, which allows researchers to determine the three-dimensional localization of tagged molecules within complex biological samples. While traditional confocal microscopes allow one to resolve two adjacent fluorescent point sources located a few hundred nanometers apart, observing the finer details of subcellular biology requires the ability to resolve signals in the order of tens of nanometers. Numerous hardware-based methods for super-resolution microscopy have been developed to allow researchers to sidestep such resolution limits, although these methods require specialized microscopes that are not available to all researchers. An alternative method for increasing resolving power is to isotropically enlarge the sample itself through a process known as expansion microscopy (ExM), which was first described by the Boyden group in 2015. ExM is not a type of microscopy per se but is rather a method for swelling a sample while preserving the relative spatial organization of its constituent molecules. The expanded sample can then be observed at an effectively increased resolution using a traditional confocal microscope. Here, we describe a protocol for implementing ExM in whole-mount Drosophila embryos, which is used to examine the localization of Par-3, myosin II, and mitochondria within the surface epithelial cells. This protocol yields an approximately four-fold increase in sample size, allowing for the detection of subcellular details that are not visible with conventional confocal microscopy. As proof of principle, an anti-GFP antibody is used to distinguish distinct pools of myosin-GFP between adjacent cell cortices, and fluorescently labeled streptavidin is used to detect endogenous biotinylated molecules to reveal the fine details of the mitochondrial network architecture. This protocol utilizes common antibodies and reagents for fluorescence labeling, and it should be compatible with many existing immunofluorescence protocols.

Expansion microscopy (ExM) enables nanoscale imaging using a standard confocal microscope through the physical, isotropic expansion of fixed immunolabeled specimens. ExM is widely employed to image proteins, nucleic acids, and lipid membranes in single cells; however, current methods limit the number of samples that can be processed simultaneously. We developed High-throughput Expansion Microscopy (HiExM), a robust platform that enables expansion microscopy of cells cultured in a standard 96-well plate. Our method enables ~4.2 x expansion of cells within individual wells, across multiple wells, and between plates. We also demonstrate that HiExM can be combined with high-throughput confocal imaging platforms to greatly improve the ease and scalability of image acquisition. As an example, we analyzed the effects of doxorubicin, a known cardiotoxic agent, on human cardiomyocytes (CMs) as measured by the Hoechst signal across the nucleus. We show a dose-dependent effect on nuclear DNA that is not observed in unexpanded CMs, suggesting that HiExM improves the detection of cellular phenotypes in response to drug treatment. Our method broadens the application of ExM as a tool for scalable super-resolution imaging in biological research applications.

Purpose 3 D imaging of the lung is not a trivial undertaking as during preparation the lung may collapse. Also serial sections and scans followed by 3 D reconstruction may lead to artifacts. The present study aims to figure out the best way to perform 3 D imaging in lung research. Materials and Methods We applied an optical tissue clearing (OTC) method, which uses ethyl cinnamate (ECi) as a fast, nontoxic and cheap clearing solvent, for 3 D imaging of retrograde perfused lungs by laser confocal fluorescence microscopy and light sheet fluorescence microscopy. We also introduced expansion microscopy (ExM), a cutting-edge technique, in 3 D imaging of lungs. We examined and compared the usefulness of these techniques for 3 D lung imaging. The ExM protocol was further extended to paraffin-embedded lung metastases blocks. Results The MHI148-PEI labeled lung vasculature was visualized by retrograde perfusion combined with trachea ligation and ECi based OTC. As compared with trans-cardiac perfusion, the retrograde perfusion results in a better maintenance of lung morphology. 3 D structure of alveoli, vascular branches and cilia in lung were revealed by immunofluorescence staining after ExM. 3 D distribution of microvasculature and neutrophil cells in 10 years old paraffin-embedded lung metastases were analyzed by ExM. Conclusions The retrograde perfusion combined with trachea ligation technique could be applied in the lung research in mice. 3 D structure of lung vasculature can be visualized by MHI148-PEI perfusion and ECi based OTC in an efficient way. ExM and immunofluorescence staining protocol is highly recommended to perform 3 D imaging of fresh fixed lung as well as paraffin-embedded lung blocks.

Photomodulable fluorescent probes are drawing increasing attention due to their applications in advanced bioimaging. Whereas photoconvertible probes can be advantageously used in tracking, photoswitchable probes constitute key tools for single-molecule localization microscopy to perform super-resolution imaging. Herein, we shed light on a red and far-red BODIPY, namely, BDP-576 and BDP-650, which possess both properties of conversion and switching. Our study demonstrates that these pyrrolyl-BODIPYs convert into typical green- and red-emitting BODIPYs that are perfectly adapted to microscopy. We also showed that this pyrrolyl-BODIPYs undergo Directed Photooxidation Induced Conversion, a photoconversion mechanism that we recently introduced, where the pyrrole moiety plays a central role. These unique features were used to develop targeted photoconvertible probes toward different organelles or subcellular units (plasma membrane, mitochondria, nucleus, actin, Golgi apparatus, etc.) using chemical targeting moieties and a Halo tag. We notably showed that BDP-650 could be used to track intracellular vesicles over more than 20 min in two-color imagings with laser scanning confocal microscopy, demonstrating its robustness. The switching properties of these photoconverters were studied at the single-molecule level and were then successfully used in live single-molecule localization microscopy in epithelial cells and neurons. Both membrane- and mitochondria- targeted probes could be used to decipher membrane 3D architecture and mitochondrial dynamics at the nanoscale. This study builds a bridge between the photoconversion and photoswitching properties of probes undergoing directed photooxidation and shows the versatility and efficacy of this mechanism in advanced live imaging.

Single-molecule localization microscopy (SMLM), a type of super-resolution fluorescence microscopy, has become a strong technique in the toolbox of chemists, biologists, physicists, and engineers in recent years for its unique ability to resolve characteristic features at the nanoscopic level. It drastically improves the resolution of optical microscopes beyond the diffraction limit, with which previously unresolvable structures can now be studied. Spectrally resolved super-resolution fluorescence microscopy via multiplexing of different fluorophores is one of the greatest advancements among SMLM techniques. However, current spectrally resolved SMLM (SR-SMLM) methodologies present low spatial resolution due to loss of photons, low throughput due to spectral interferences, or require complex optical systems. Here, we overcome these drawbacks by developing a SR-SMLM methodology using a color glass filter. It enables high throughput and improved photon usage for hyperspectral imaging at the nanoscopic level. Our methodology can readily distinguish fluorophores of close spectral emission and achieves sub-10 nm localization and sub-5 nm spectral precisions.

Cell Biological Applications of Confocal Microscopy

Chapter Thirteen - Localization Microscopy

Having discussed the propagation and focusing of optical fields, we now start to browse through the most important experimental and technical configurations employed in high-resolution optical microscopy. Various topics discussed in the previous chapters will be revisited from an experimental perspective. We shall describe both far-field and near-field techniques. Far-field microscopy, scanning confocal optical microscopy in particular, is discussed because the size of the focal spot routinely reaches the diffraction limit. Many of the experimental concepts that are used in confocal microscopy have naturally been transferred to near-field optical microscopy. In a near-field optical microscope a nanoscale optical probe is raster scanned across a surface much as in AFM or STM. There is a variety of possible experimental realizations in scanning near-field optical microscopy while in AFM and STM a (more or less) unique set-up exists. The main difference between AFM/STM and near-field optical microscopy is that in the latter an optical near-field has to be created at the sample or at the probe apex before any interaction can be ineasured. Depending how the near-field is measured, one distinguishes between different configurations. These are summarized in Table 5.1. Far-field illumination and detection Confocal microscopy Confocal microscopy employs far-field illumination and far-field detection and has been discussed previously in Section 4.3. Despite the limited bandwidth of spatial frequencies imposed by far-field illumination and detection, confocal microscopy is successfully employed for high-position-accuracy measurements as discussed in Section 4.5 and for high-resolution imaging by exploiting nonlinear or saturation effects as discussed in Section 4.2.3.

Lacrimal Gland in Sjögren's Syndrome

Correlative light and electron microscopy (CLEM) methods are powerful methods that combine molecular organization (from light microscopy) with ultrastructure (from electron microscopy). However, CLEM methods pose high cost/difficulty barriers to entry and have very low experimental throughput. Therefore, we have developed an indirect correlative light and electron microscopy (iCLEM) pipeline to sidestep the rate-limiting steps of CLEM (i.e., preparing and imaging the same samples on multiple microscopes) and correlate multiscale structural data gleaned from separate samples imaged using different modalities by exploiting biological structures identifiable by both light and electron microscopy as intrinsic fiducials. We demonstrate here an application of iCLEM, where we utilized gap junctions and mechanical junctions between muscle cells in the heart as intrinsic fiducials to correlate ultrastructural measurements from transmission electron microscopy (TEM), and focused ion beam scanning electron microscopy (FIB-SEM) with molecular organization from confocal microscopy and single molecule localization microscopy (SMLM). We further demonstrate how iCLEM can be integrated with computational modeling to discover structure-function relationships. Thus, we present iCLEM as a novel approach that complements existing CLEM methods and provides a generalizable framework that can be applied to any set of imaging modalities, provided suitable intrinsic fiducials can be identified.

Superresolution microscopy by single-molecule photoactivation or photoswitching and position determination (localization microscopy) has the potential to fundamentally revolutionize our understanding of how cells function at a molecular level. Single-molecule localization microscopy (SMLM) can provide single-molecule information about the distribution and even the absolute numbers of proteins in subcellular compartments. During this webinar, our speakers will introduce the basic requirements of SMLM and its potential use for quantitative molecular imaging. Obstacles and how to bypass them will be discussed, as well as the advantages of direct stochastic optical reconstruction microscopy (dSTORM) for quantitative imaging of proteins. Furthermore, the influence of different environmental and artificial variables on the survival of different cell lines will be demonstrated. The speakers will present data on different image capture technologies for SMLM, focusing on electron multiplying charge-coupled device (EMCCD) and scientific complementary metal-oxide semiconductor (sCMOS) cameras, discussing frame rates and the need for sensitive detectors to harvest the comparatively low light levels associated with single-molecule fluorescence emission. Information on how to optimize your camera setup for superresolution imaging will also be provided.