Super-resolution imaging of platelet-activation process and its quantitative analysis

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

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

12/15-Lipooxygenase Inhibition Reduces Microvessel Constriction and Microthrombi after Subarachnoid Hemorrhage in Mice

Background and Purpose Impaired cerebral circulation, induced by blood vessel constrictions and microthrombi, leads to delayed cerebral ischemia after subarachnoid hemorrhage (SAH). 12/15-Lipooxygenase (12/15-LOX) overexpression has been implicated in worsening early brain injury outcomes following SAH. However, it is unknown if 12/15-LOX is important in delayed pathophysiological events after SAH. Since 12/15-LOX produces metabolites that induce inflammation and vasoconstriction, we hypothesized that 12/15-LOX leads to microvessel constriction and microthrombi formation after SAH, and thus 12/15-LOX is an important target to prevent delayed cerebral ischemia. Methods SAH was induced in C57BL/6 and 12/15-LOX -/- mice of both sexes by endovascular perforation. Expression of 12/15-LOX was assessed in brain tissue slices and in vitro . C57BL/6 mice were administered either ML351 (12/15-LOX inhibitor) or vehicle. Mice were evaluated for daily neuroscore and euthanized on day five to assess cerebral 12/15-LOX expression, vessel constrictions, platelet activation, microthrombi, neurodegeneration, infarction, cortical perfusion, and for development of delayed deficits. Finally, the effect of 12/15-LOX inhibition on platelet activation was assessed in SAH patient samples using a platelet spreading assay. Results In SAH mice, 12/15-LOX was upregulated in brain vascular cells and there was an increase in 12-S-HETE. Inhibition of 12/15-LOX improved brain perfusion on days 4-5 and attenuated delayed pathophysiological events, including microvessel constrictions, microthrombi, neuronal degeneration, and infarction. Additionally, 12/15-LOX inhibition reduced platelet activation in human and mouse blood samples. Conclusions Cerebrovascular 12/15-LOX overexpression plays a major role in brain dysfunction after SAH by triggering microvessel constrictions and microthrombi formation, which reduces brain perfusion. Inhibiting 12/15-LOX may be a therapeutic target to improve outcomes after SAH.

Single molecule studies of dynamic platelet interactions with endothelial cells

A biotechnological platform consisting of two-color 3D super-resolution readout and a microfluidic system was developed to investigate platelet interaction with a layer of perfused endothelial cells under flow conditions. Platelet activation has been confirmed via CD62P clustering on the membrane and mitochondrial morphology of ECs at the single cell level were examined using 3D two-color single-molecule localization microscopy and classified applying machine learning. To compare binding of activated platelets to intact or stressed ECs, a femtosecond laser was used to induced damage to single ECs within the perfused endothelial layer. We observed that activated platelets bound to the perfused ECs layer preferentially in the proximity to single stressed ECs. Platelets activated under flow were ∼6 times larger compared to activated ones under static conditions. The CD62P expression indicated more CD62P proteins on membrane of dynamically activated platelets, with a tendency to higher densities at the platelet/EC interface. Platelets activated under static conditions showed a less pronounced CD62P top/bottom asymmetry. The clustering of CD62P in the platelet membrane differs depending on the activation conditions. Our results confirm that nanoscopic analysis using two-color 3D super-resolution technology can be used to assess platelet interaction with a stressed endothelium under dynamic conditions.

Approaching Thrombospondin-1 as a Potential Target for Mesenchymal Stromal Cells to Support Liver Regeneration after Partial Hepatectomy in Mouse and Humans

Extended liver resection carries the risk of post-surgery liver failure involving thrombospondin-1-mediated aggravation of hepatic epithelial plasticity and function. Mesenchymal stromal cells (MSCs), by interfering with thrombospondin-1 (THBS1), counteract hepatic dysfunction, though the mechanisms involved remain unknown. Herein, two-thirds partial hepatectomy in mice increased hepatic THBS1, downstream transforming growth factor-β3, and perturbation of liver tissue homeostasis. All these events were ameliorated by hepatic transfusion of human bone marrow-derived MSCs. Treatment attenuated platelet and macrophage recruitment to the liver, both major sources of THBS1. By mitigating THBS1, MSCs muted surgery-induced tissue deterioration and dysfunction, and thus supported post-hepatectomy regeneration. After liver surgery, patients displayed increased tissue THBS1, which is associated with functional impairment and may indicate a higher risk of post-surgery complications. Since liver dysfunction involving THBS1 improves with MSC treatment in various animal models, it seems feasible to also modulate THBS1 in humans to impede post-surgery acute liver failure.

Evaluation of human platelet granules by structured illumination laser fluorescence microscopy

Many roles of human platelets in health and disease are linked to their ability to transport and secrete a variety of small molecules and proteins carried in dense (δ-) and α-granules. Determination of granule number and content is important for diagnosis of platelet disorders and for studies of platelet structure, function, and development. We have optimized methods for detection and localization of platelet proteins via antibody and lectin staining, imaging via structured illumination laser fluorescence microscopy (SIM), and three-dimension (3D) image analysis. The methods were validated via comparison with published studies based on electron microscopy and high-resolution fluorescence microscopy. The α-granule cargo proteins thrombospondin-1 (TSP1), osteonectin (SPARC), fibrinogen (FGN), and Von Willebrand factor (VWF) were localized within the granule lumen, as was the proteoglycan serglycin (SRGN). Colocalization analysis indicates that staining with fluorescently labeled wheat germ agglutinin (WGA) allows detection of α-granules as effectively as immunostaining for cargo proteins, with the advantage of not requiring antibodies. RAB27B was observed to be concentrated at dense granules, allowing them to be counted via visual scoring and object analysis. We present a workflow for counting dense and α-granules via object analysis of 3D SIM images of platelets stained for RAB27B and with WGA.Abbreviation: SIM: structured illumination microscopy; WGA: wheat germ agglutinin; FGN: fibrinogen; TSP1: thrombospondin 1; ER: endoplasmic reticulum.

The fate of mitochondria during platelet activation

Blood platelets undergo several successive motor-driven reorganizations of the cytoskeleton when they are recruited to an injured part of a vessel. These reorganizations take place during the platelet activation phase, the spreading process on the injured vessel or between fibrin fibers of the forming clot, and during clot retraction. All these steps require a lot of energy, especially the retraction of the clot when platelets develop strong forces similar to those of muscle cells. Platelets can produce energy through glycolysis and mitochondrial respiration. However, although resting platelets have only 5 to 8 individual mitochondria, they produce adenosine triphosphate predominantly via oxidative phosphorylation. Activated, spread platelets show an increase in size compared with resting platelets, and the question arises as to where the few mitochondria are located in these larger platelets. Using expansion microscopy, we show that the number of mitochondria per platelet is increased in spread platelets. Live imaging and focused ion beam-scanning electron microscopy suggest that a mitochondrial fission event takes place during platelet activation. Fission is Drp1 dependent because Drp1-deficient platelets have fused mitochondria. In nucleated cells, mitochondrial fission is associated with a shift to a glycolytic phenotype, and using clot retraction assays, we show that platelets have a more glycolytic energy production during clot retraction and that Drp1-deficient platelets show a defect in clot retraction.

Superresolution Fluorescence Microscopy of Platelet Subcellular Structures as a Potential Tumor Liquid Biopsy

Blood-based tumor liquid biopsies are promising as an alternative or complement to tissue biopsies due to their noninvasiveness, convenience, and safety, and there is still a great demand for the discovery of new biomarkers for these biopsies. Here, nanoscale distribution patterns of subcellular structures in platelets, as imaged by structured illumination superresolution fluorescence microscopy, as a new type of potential biomarker for tumor liquid biopsies are presented. A standardized protocol for platelet sample preparation and developed an automated high-throughput image analysis workflow is established. The diagnostic capability based on the statistical analysis of 280 000 superresolution images of individual platelets from a variety of tumor patients, benign mass patients, and healthy volunteers (n = 206) is explored. These results suggest that the nanoscale distribution patterns of α-granules in platelets have the potential to be biomarkers for several cancers, including glioma and cervical, endometrial, and ovarian cancers, facilitating not only diagnosis but also therapeutic monitoring. This study provides a promising novel type of platelet parameter for tumor liquid biopsies at the subcellular level rather than the existing cellular or molecular level and opens up a new avenue for clinical applications of superresolution imaging techniques.

Dynamic investigation of zein-based degradable and hemocompatible coatings for drug-eluting stents: a microfluidic approach

Biodegradable stent coatings have shown great potential in terms of delivering drugs to a damaged vessel wall, and their release profiles are key elements governing the overall performance of drug-eluting stents (DESs). However, release and degradation kinetics are usually not tested under simulated physiological conditions or in dynamic environments, both essential aspects in the design of novel DESs. To bridge this gap, fused silica-based microfluidic systems, with either round or square channel cross-sections, were designed to mimic the microenvironment of a stented vessel. In particular, we fabricated and characterized microfluidic chips based on customizable channels, which were spray-coated with a naturally-derived, rutin-loaded zein solution, to perform a comprehensive study under flow conditions. Dynamic assays after 6 hours showed how the degradation of the zein matrix was affected by the cross-sectional conformation (∼69% vs. ∼61%, square and round channel, respectively) and the simulated blood fluid components (∼55%, round channel with a more viscous solution). The released amount of rutin was ∼81% vs. ∼77% and ∼78% vs. ∼74% from the square and round channels, using the less and more viscous blood-simulated fluids, respectively. Fitting the drug release data to Korsmeyer-Peppas and first-order mathematical models provided further insight into the mechanism of rutin release and coating behavior under flowing conditions. More importantly, whole blood tests with our newly developed microfluidic platforms confirmed the hemocompatibility of our zein-based coating. In detail, in-flow and static studies on the blood cell behavior showed a significant reduction of platelet adhesion (∼73%) and activation (∼93%) compared to the stainless-steel substrate, confirming the benefits of using such naturally-derived coatings to avoid clogging. Overall, our microfluidic designs can provide a key practical tool for assessing polymer degradation and drug release from degradable matrices under flowing conditions, thus aiding future studies on the development of hemocompatible, controlled-release coatings for DESs.

Recent development of computational cluster analysis methods for single-molecule localization microscopy images

With the development of super-resolution imaging techniques, it is crucial to understand protein structure at the nanoscale in terms of clustering and organization in a cell. However, cluster analysis from single-molecule localization microscopy (SMLM) images remains challenging because the classical computational cluster analysis methods developed for conventional microscopy images do not apply to pointillism SMLM data, necessitating the development of distinct methods for cluster analysis from SMLM images. In this review, we discuss the development of computational cluster analysis methods for SMLM images by categorizing them into classical and machine-learning-based methods. Finally, we address possible future directions for machine learning-based cluster analysis methods for SMLM data.

Visualizing extracellular vesicle biogenesis in gram-positive bacteria using super-resolution microscopy

BACKGROUND

Recently, bacterial extracellular vesicles (EVs) have been considered to play crucial roles in various biological processes and have great potential for developing cancer therapeutics and biomedicine. However, studies on bacterial EVs have mainly focused on outer membrane vesicles released from gram-negative bacteria since the outermost peptidoglycan layer in gram-positive bacteria is thought to preclude the release of EVs as a physical barrier.

RESULTS

Here, we examined the ultrastructural organization of the EV produced by gram-positive bacteria using super-resolution stochastic optical reconstruction microscopy (STORM) at the nanoscale, which has not been resolved using conventional microscopy. Based on the super-resolution images of EVs, we propose three major mechanisms of EV biogenesis, i.e., membrane blebbing (mechanisms 1 and 2) or explosive cell lysis (mechanism 3), which are different from the mechanisms in gram-negative bacteria, despite some similarities.

CONCLUSIONS

These findings highlight the significant role of cell wall degradation in regulating various mechanisms of EV biogenesis and call for a reassessment of previously unresolved EV biogenesis in gram-positive bacteria.

Development of Deep-Learning-Based Single-Molecule Localization Image Analysis

Recent developments in super-resolution fluorescence microscopic techniques (SRM) have allowed for nanoscale imaging that greatly facilitates our understanding of nanostructures. However, the performance of single-molecule localization microscopy (SMLM) is significantly restricted by the image analysis method, as the final super-resolution image is reconstructed from identified localizations through computational analysis. With recent advancements in deep learning, many researchers have employed deep learning-based algorithms to analyze SMLM image data. This review discusses recent developments in deep-learning-based SMLM image analysis, including the limitations of existing fitting algorithms and how the quality of SMLM images can be improved through deep learning. Finally, we address possible future applications of deep learning methods for SMLM imaging.

Emerging Technologies for Understanding Platelet Diversity

This review discusses our understanding of platelet diversity with implications for the roles of platelets in hemostasis and thrombosis and identifies advanced technologies set to provide new insights. We use the term diversity to capture intrasubject platelet variability that can be intrinsic or governed by the environment and lead to a heterogeneous response pattern of aggregation, clot promotion, and external communication. Using choice examples, we discuss how the use of advanced technologies can provide new insights into the underlying causes of platelet molecular, structural, and functional diversity. As sources of diversity, we discuss the proliferating megakaryocytes with different allele-specific expression patterns, the asymmetrical formation of proplatelets, changes in platelets induced by aging and priming, interplatelet heterogeneity in thrombus organization and stability, and platelet-dependent communications. We provide indications how current knowledge gaps can be addressed using promising technologies, such as next-generation sequencing, proteomic approaches, advanced imaging techniques, multicolor flow and mass cytometry, multifunctional microfluidics assays, and organ-on-a-chip platforms. We then argue how this technology base can aid in characterizing platelet populations and in identifying platelet biomarkers relevant for the treatment of cardiovascular disease.

Blood Cell Analysis: From Traditional Methods to Super-Resolution Microscopy

Blood cell analysis is essential for the diagnosis and identification of hematological malignancies. The use of digital microscopy systems has been extended in clinical laboratories. Super-resolution microscopy (SRM) has attracted wide attention in the medical field due to its nanoscale spatial resolution and high sensitivity. It is considered to be a potential method of blood cell analysis that may have more advantages than traditional approaches such as conventional optical microscopy and hematology analyzers in certain examination projects. In this review, we firstly summarize several common blood cell analysis technologies in the clinic, and analyze the advantages and disadvantages of these technologies. Then, we focus on the basic principles and characteristics of three representative SRM techniques, as well as the latest advances in these techniques for blood cell analysis. Finally, we discuss the developmental trend and possible research directions of SRM, and provide some discussions on further development of technologies for blood cell analysis.

Recent Developments in Correlative Super-Resolution Fluorescence Microscopy and Electron Microscopy

The recently developed correlative super-resolution fluorescence microscopy (SRM) and electron microscopy (EM) is a hybrid technique that simultaneously obtains the spatial locations of specific molecules with SRM and the context of the cellular ultrastructure by EM. Although the combination of SRM and EM remains challenging owing to the incompatibility of samples prepared for these techniques, the increasing research attention on these methods has led to drastic improvements in their performances and resulted in wide applications. Here, we review the development of correlative SRM and EM (sCLEM) with a focus on the correlation of EM with different SRM techniques. We discuss the limitations of the integration of these two microscopy techniques and how these challenges can be addressed to improve the quality of correlative images. Finally, we address possible future improvements and advances in the continued development and wide application of sCLEM approaches.

Development of a New Approach for Low-Laser-Power Super-Resolution Fluorescence Imaging

The development of super-resolution fluorescence microscopy over the past decade has drastically improved the resolution of light microscopy to ∼10 nm. Stochastic optical reconstruction microscopy (STORM) can be used to achieve subdiffraction-limit resolution by sequentially imaging and localizing individual fluorophores. In principle, the super-resolution of STORM can be obtained by high-accuracy localization of photoswitchable fluorophores, which require fast photoswitching and bright fluorescence intensity from a single emitter. It is known that the switching rate of photoswitchable fluorophores depends on the laser power─a high laser power being required for the enhancement of imaging resolution. However, high laser power is usually harmful to biological specimens and limits the imaging time because of its photobleaching effects and high phototoxicity. In this study, we attempted to overcome this problem by improving the STORM resolution at a lower laser power. Through the quantitative analysis of the photoswitching behavior of single fluorophores under different laser power conditions, we developed a new approach to achieve super-resolution fluorescence images at a laser power 10 times lower than had previously been reported. This approach is expected to play an increasingly significant role in super-resolution imaging of power-sensitive samples.