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It is essential for cells to control which genes are transcribed into RNA. In eukaryotes, two major control points are recruitment of RNA polymerase II (Pol II) into a paused state, and subsequent pause release toward transcription. Pol II recruitment and pause release occur in association with macromolecular clusters, which were proposed to be formed by a liquid–liquid phase separation mechanism. How such a phase separation mechanism relates to the interaction of Pol II with DNA during recruitment and transcription, however, remains poorly understood. Here, we use live and super‐resolution microscopy in zebrafish embryos to reveal Pol II clusters with a large variety of shapes, which can be explained by a theoretical model in which regulatory chromatin regions provide surfaces for liquid‐phase condensation at concentrations that are too low for canonical liquid–liquid phase separation. Model simulations and chemical perturbation experiments indicate that recruited Pol II contributes to the formation of these surface‐associated condensates, whereas elongating Pol II is excluded from these condensates and thereby drives their unfolding. Synopsis Recruited RNA polymerase II forms clusters via surface condensation on regulatory chromatin. These clusters unfold due to the exclusion of elongating polymerase from condensates. Pluripotent zebrafish embryos exhibit prominent and long‐lived clusters enriched in recruited RNA polymerase II. Clusters form similar to a liquid film that coats condensation surfaces provided by regulatory genomic regions. Genomic regions that undergo transcription elongation are excluded from the liquid film, resulting in the unfolding of the clusters. Graphical Abstract Recruited RNA polymerase II forms clusters via surface condensation on regulatory chromatin. These clusters unfold due to the exclusion of elongating polymerase from condensates.

INTRODUCTION The monoclonal antibodies Aducanumab, Lecanemab, Gantenerumab, and Donanemab were developed for the treatment of Alzheimer's disease (AD). METHODS We used single‐molecule detection and super‐resolution imaging to characterize the binding of these antibodies to diffusible amyloid beta (Aβ) aggregates generated in‐vitro and harvested from human brains. RESULTS Lecanemab showed the best performance in terms of binding to the small‐diffusible Aβ aggregates, affinity, aggregate coating, and the ability to bind to post‐translationally modified species, providing an explanation for its therapeutic success. We observed a Braak stage–dependent increase in small‐diffusible aggregate quantity and size, which was detectable with Aducanumab and Gantenerumab, but not Lecanemab, showing that the diffusible Aβ aggregates change with disease progression and the smaller aggregates to which Lecanemab preferably binds exist at higher quantities during earlier stages. DISCUSSION These findings provide an explanation for the success of Lecanemab in clinical trials and suggests that Lecanemab will be more effective when used in early‐stage AD. Highlights Anti amyloid beta therapeutics are compared by their diffusible aggregate binding characteristics. In‐vitro and brain‐derived aggregates are tested using single‐molecule detection. Lecanemab shows therapeutic success by binding to aggregates formed in early disease. Lecanemab binds to these aggregates with high affinity and coats them better.

To understand the structure and function of large molecular machines, accurate knowledge of their stoichiometry is essential. In this study, we developed an integrated targeted proteomics and super‐resolution microscopy approach to determine the absolute stoichiometry of the human nuclear pore complex (NPC), possibly the largest eukaryotic protein complex. We show that the human NPC has a previously unanticipated stoichiometry that varies across cancer cell types, tissues and in disease. Using large‐scale proteomics, we provide evidence that more than one third of the known, well‐defined nuclear protein complexes display a similar cell type‐specific variation of their subunit stoichiometry. Our data point to compositional rearrangement as a widespread mechanism for adapting the functions of molecular machines toward cell type‐specific constraints and context‐dependent needs, and highlight the need of deeper investigation of such structural variants. The stoichiometry of the human nuclear pore complex is revealed by targeted mass spectrometry and super‐resolution microscopy. The analysis reveals that the composition of the nuclear pore and other nuclear protein complexes is remodeled as a function of the cell type. Synopsis The stoichiometry of the human nuclear pore complex is revealed by targeted mass spectrometry and super‐resolution microscopy. The analysis reveals that the composition of the nuclear pore and other nuclear protein complexes is remodeled as a function of the cell type. The human NPC has a previously unanticipated stoichiometry that varies across cell types. Primarily functional Nups are dynamic, while the NPC scaffold is static. Stoichiometries of many complexes are fine‐tuned toward cell type‐specific needs.

Extracellular vesicles (EVs) are secreted from all cell types and are intimately involved in tissue homeostasis. They are being explored as vaccine and gene therapy platforms, as well as potential biomarkers. As their size is below the diffraction limit of light microscopy, direct visualizations have been daunting and single‐particle studies under physiological conditions have been hampered. Here, direct stochastic optical reconstruction microscopy (dSTORM) was employed to visualize EVs in three‐dimensions and to localize molecule clusters such as the tetraspanins CD81 and CD9 on the surface of individual EVs. These studies demonstrate the existence of membrane microdomains on EVs. These were confirmed by Cryo‐EM. Individual particle visualization provided insights into the heterogeneity, structure, and complexity of EVs not previously appreciated

Tissue engineering aims to restore or replace damaged organs using scaffolds, cells, and biomolecules. A key challenge remains: visualizing the intricate cellular and molecular interactions within engineered environments. Traditional imaging methods struggle to capture the nanoscale details essential for understanding stem cell behavior, tissue formation, and cell‐scaffold interactions. Super‐resolution microscopy (SRM) offers a solution by enabling imaging beyond the diffraction limit, revealing critical nanoscale processes involved in tissue engineering. SRM provides valuable insights into cell adhesion, migration, and differentiation, and facilitates the optimization of scaffold designs by visualizing the organization of cellular components and their relationship to the extracellular matrix. By integrating SRM into preclinical studies, researchers can improve the assessment and development of tissue‐engineered constructs, bridging the gap between basic research and clinical applications. Overall, SRM holds substantial promise for accelerating progress in organ regeneration by uncovering previously inaccessible details that drive functional tissue integration. Super‐resolution microscopy (SRM) has advanced tissue engineering by providing nanoscale insights into cellular interactions. It reveals detailed cell membrane structures, tracks vesicle and virus entry, and visualizes the cytoskeleton. SRM also improves understanding of cell migration, facilitating tissue regeneration, vascularization, immune integration, and accelerating the development of regenerative therapies.

Tissue expansion techniques physically expand swellable gel‐embedded biological specimens to overcome the resolution limit of light microscopy. As the benefits of expansion come at the expense of signal concentration, imaging volume and time, and mechanical integrity of the sample, the optimal expansion ratio may widely differ depending on the experiment. However, existing expansion methods offer only fixed expansion ratios that cannot be easily adjusted to balance the gain and loss associated with expansion. Here, a hydrogel conversion‐based expansion method is presented, that enables easy adjustment of the expansion ratio for individual needs, simply by changing the duration of a heating step. This method, termed ZOOM, isotropically expands samples up to eightfold in a single expansion process. ZOOM preserves biomolecules for post‐processing labelings and supports multi‐round expansion for the imaging of a single sample at multiple zoom factors. ZOOM can be flexibly and scalably applied to nanoscale imaging of diverse samples, ranging from cultured cells to thick tissues, as well as bacteria, exoskeletal Caenorhabditis elegans, and human brain samples. ZOOM, a new tissue expansion technique based on the hydrogel conversion reaction, is developed to enable scalable and isotropic expansion of biological samples with easily tunable expansion ratio (up to eightfold). This method allows for simple and flexible expansion of a wide range of biological samples, from bacteria to human brain tissues, for super‐resolution imaging of samples with ordinary microscopes.

Increasing the information depth of single kidney biopsies can improve diagnostic precision, personalized medicine and accelerate basic kidney research. Until now, information on mRNA abundance and morphologic analysis has been obtained from different samples, missing out on the spatial context and single‐cell correlation of findings. Herein, we present scoMorphoFISH, a modular toolbox to obtain spatial single‐cell single‐mRNA expression data from routinely generated kidney biopsies. Deep learning was used to virtually dissect tissue sections in tissue compartments and cell types to which single‐cell expression data were assigned. Furthermore, we show correlative and spatial single‐cell expression quantification with super‐resolved podocyte foot process morphometry. In contrast to bulk analysis methods, this approach will help to identify local transcription changes even in less frequent kidney cell types on a spatial single‐cell level with single‐mRNA resolution. Using this method, we demonstrate that ACE2 can be locally upregulated in podocytes upon injury. In a patient suffering from COVID‐19‐associated collapsing FSGS, ACE2 expression levels were correlated with intracellular SARS‐CoV‐2 abundance. As this method performs well with standard formalin‐fixed paraffin‐embedded samples and we provide pretrained deep learning networks embedded in a comprehensive image analysis workflow, this method can be applied immediately in a variety of settings.

The diverse origins, nanometre‐scale and invasive isolation procedures associated with extracellular vesicles (EVs) mean they are usually studied in bulk and disconnected from their parental cell. Here, we used super‐resolution microscopy to directly compare EVs secreted by individual human monocyte‐derived macrophages (MDMs). MDMs were differentiated to be M0‐, M1‐ or M2‐like, with all three secreting EVs at similar densities following activation. However, M0‐like cells secreted larger EVs than M1‐ and M2‐like macrophages. Proteomic analysis revealed variations in the contents of differently sized EVs as well as between EVs secreted by different MDM phenotypes. Super resolution microscopy of single‐cell secretions identified that the class II MHC protein, HLA‐DR, was expressed on ∼40% of EVs secreted from M1‐like MDMs, which was double the frequency observed for M0‐like and M2‐like EVs. Strikingly, human macrophages, isolated from the resected lungs of cancer patients, secreted EVs that expressed HLA‐DR at double the frequency and with greater intensity than M1‐like EVs. Quantitative analysis of single‐cell EV profiles from all four macrophage phenotypes revealed distinct secretion types, five of which were consistent across multiple sample cohorts. A sub‐population of M1‐like MDMs secreted EVs similar to lung macrophages, suggesting an expansion or recruitment of cells with a specific EV secretion profile within the lungs of cancer patients. Thus, quantitative analysis of EV heterogeneity can be used for single cell profiling and to reveal novel macrophage biology.

The ‛stickiness’ of extracellular vesicles (EVs) can pose challenges for EV processing and storage, but adhesive properties may also be exploited to immobilise EVs directly on surfaces for various measurement techniques, including super‐resolution microscopy (SRM). Direct adhesion to surfaces may allow the examination of broader populations of EVs than molecular affinity approaches, which can also involve specialised, expensive affinity reagents. Here, we report on the interaction of EVs with borosilicate glass and quartz coverslips and on the effects of pre‐coating coverslips with poly‐L‐lysine (PLL), a reagent commonly used to facilitate interactions between negatively charged surfaces of cells and amorphous surfaces. Additionally, we compared two mounting media conditions for SRM imaging and used immobilised EVs for a B‐cell interaction test. Our findings suggest that borosilicate glass coverslips immobilise EVs better than quartz glass coverslips. We also found that PLL is not strictly required for EV retention but contributes to the uniform distribution of EVs on borosilicate glass coverslips. Overall, these findings suggest that standard lab materials like borosilicate glass coverslips, with or without PLL, can be effectively used for the immobilisation of EVs in specific imaging techniques.

High‐resolution optical microscopy, particularly super‐resolution localization microscopy, requires precise real‐time drift correction to maintain constant focus at nanoscale precision during the prolonged data acquisition. Existing methods, such as fiducial marker tracking, reflection monitoring, and bright‐field image correlation, each provide certain advantages but are limited in their broad applicability. In this work, a versatile and robust drift correction technique is presented for single‐molecule localization‐based super‐resolution microscopy. It is based on the displacement analysis of bright‐field image features of the specimen with oblique illumination. By leveraging the monotonic relationship between the displacement of image features and axial positions, this method can precisely measure the drift of the imaging system in real‐time with sub‐nanometer precision in all three dimensions, over a broad axial range, and for various samples, including those with closely matched refractive indices. The performance of this method is validated against conventional marker‐assisted techniques and demonstrates its high precision in super‐resolution imaging across various biological samples. This method paves the way for fully automated drift‐free super‐resolution imaging systems. This study introduces a robust marker‐free drift correction method for single‐molecule localization‐based super‐resolution microscopy. Utilizing oblique illumination, it analyzes bright‐field image feature displacement to achieve sub‐nanometer precision in real‐time drift tracking across all dimensions. Validated against conventional techniques, this versatile approach supports automated drift‐free imaging, ensuring nanoscale precision for prolonged high‐resolution microscopy in diverse biological samples.