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.

Spatial proteomics in neurons at single-protein resolution.

To understand biological processes, it is necessary to reveal the molecular heterogeneity of cells by gaining access to the location and interaction of all biomolecules. Significant advances were achieved by super-resolution microscopy, but such methods are still far from reaching the multiplexing capacity of proteomics. Here, we introduce secondary label-based unlimited multiplexed DNA-PAINT (SUM-PAINT), a high-throughput imaging method that is capable of achieving virtually unlimited multiplexing at better than 15 nm resolution. Using SUM-PAINT, we generated 30-plex single-molecule resolved datasets in neurons and adapted omics-inspired analysis for data exploration. This allowed us to reveal the complexity of synaptic heterogeneity, leading to the discovery of a distinct synapse type. We not only provide a resource for researchers, but also an integrated acquisition and analysis workflow for comprehensive spatial proteomics at single-protein resolution.

Temporally multiplexed imaging of dynamic signaling networks in living cells.

Molecular signals interact in networks to mediate biological processes. To analyze these networks, it would be useful to image many signals at once, in the same living cell, using standard microscopes and genetically encoded fluorescent reporters. Here, we report temporally multiplexed imaging (TMI), which uses genetically encoded fluorescent proteins with different clocklike properties-such as reversibly photoswitchable fluorescent proteins with different switching kinetics-to represent different cellular signals. We linearly decompose a brief (few-second-long) trace of the fluorescence fluctuations, at each point in a cell, into a weighted sum of the traces exhibited by each fluorophore expressed in the cell. The weights then represent the signal amplitudes. We use TMI to analyze relationships between different kinase activities in individual cells, as well as between different cell-cycle signals, pointing toward broad utility throughout biology in the analysis of signal transduction cascades in living systems.

Live-cell imaging powered by computation.

The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. The prevailing challenge in live-cell fluorescence microscopy is capturing intra-cellular dynamics while preserving cell viability. Computational methods can help to address this challenge and are now shifting the boundaries of what is possible to capture in living systems. In this Review, we discuss these computational methods focusing on artificial intelligence-based approaches that can be layered on top of commonly used existing microscopies as well as hybrid methods that integrate computation and microscope hardware. We specifically discuss how computational approaches can improve the signal-to-noise ratio, spatial resolution, temporal resolution and multi-colour capacity of live-cell imaging.

Deciphering cell signaling networks with massively multiplexed biosensor barcoding.

Genetically encoded fluorescent biosensors are powerful tools for monitoring biochemical activities in live cells, but their multiplexing capacity is limited by the available spectral space. We overcome this problem by developing a set of barcoding proteins that can generate over 100 barcodes and are spectrally separable from commonly used biosensors. Mixtures of barcoded cells expressing different biosensors are simultaneously imaged and analyzed by deep learning models to achieve massively multiplexed tracking of signaling events. Importantly, different biosensors in cell mixtures show highly coordinated activities, thus facilitating the delineation of their temporal relationship. Simultaneous tracking of multiple biosensors in the receptor tyrosine kinase signaling network reveals distinct mechanisms of effector adaptation, cell autonomous and non-autonomous effects of KRAS mutations, as well as complex interactions in the network. Biosensor barcoding presents a scalable method to expand multiplexing capabilities for deciphering the complexity of signaling networks and their interactions between cells.

Single-Molecule Kinetics in Living Cells.

In the past decades, advances in microscopy have made it possible to study the dynamics of individual biomolecules in vitro and resolve intramolecular kinetics that would otherwise be hidden in ensemble averages. More recently, single-molecule methods have been used to image, localize, and track individually labeled macromolecules in the cytoplasm of living cells, allowing investigations of intermolecular kinetics under physiologically relevant conditions. In this review, we illuminate the particular advantages of single-molecule techniques when studying kinetics in living cells and discuss solutions to specific challenges associated with these methods.

DNA Microscopy: Optics-free Spatio-genetic Imaging by a Stand-Alone Chemical Reaction.

Analyzing the spatial organization of molecules in cells and tissues is a cornerstone of biological research and clinical practice. However, despite enormous progress in molecular profiling of cellular constituents, spatially mapping them remains a disjointed and specialized machinery-intensive process, relying on either light microscopy or direct physical registration. Here, we demonstrate DNA microscopy, a distinct imaging modality for scalable, optics-free mapping of relative biomolecule positions. In DNA microscopy of transcripts, transcript molecules are tagged in situ with randomized nucleotides, labeling each molecule uniquely. A second in situ reaction then amplifies the tagged molecules, concatenates the resulting copies, and adds new randomized nucleotides to uniquely label each concatenation event. An algorithm decodes molecular proximities from these concatenated sequences and infers physical images of the original transcripts at cellular resolution with precise sequence information. Because its imaging power derives entirely from diffusive molecular dynamics, DNA microscopy constitutes a chemically encoded microscopy system.

Mapping Local and Global Liquid Phase Behavior in Living Cells Using Photo-Oligomerizable Seeds.

Liquid-liquid phase separation plays a key role in the assembly of diverse intracellular structures. However, the biophysical principles by which phase separation can be precisely localized within subregions of the cell are still largely unclear, particularly for low-abundance proteins. Here, we introduce an oligomerizing biomimetic system, "Corelets," and utilize its rapid and quantitative light-controlled tunability to map full intracellular phase diagrams, which dictate the concentrations at which phase separation occurs and the transition mechanism, in a protein sequence dependent manner. Surprisingly, both experiments and simulations show that while intracellular concentrations may be insufficient for global phase separation, sequestering protein ligands to slowly diffusing nucleation centers can move the cell into a different region of the phase diagram, resulting in localized phase separation. This diffusive capture mechanism liberates the cell from the constraints of global protein abundance and is likely exploited to pattern condensates associated with diverse biological processes. VIDEO ABSTRACT.

In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Images.

Microscopy is a central method in life sciences. Many popular methods, such as antibody labeling, are used to add physical fluorescent labels to specific cellular constituents. However, these approaches have significant drawbacks, including inconsistency; limitations in the number of simultaneous labels because of spectral overlap; and necessary perturbations of the experiment, such as fixing the cells, to generate the measurement. Here, we show that a computational machine-learning approach, which we call "in silico labeling" (ISL), reliably predicts some fluorescent labels from transmitted-light images of unlabeled fixed or live biological samples. ISL predicts a range of labels, such as those for nuclei, cell type (e.g., neural), and cell state (e.g., cell death). Because prediction happens in silico, the method is consistent, is not limited by spectral overlap, and does not disturb the experiment. ISL generates biological measurements that would otherwise be problematic or impossible to acquire.

Light-Sheet Microscopy and Its Potential for Understanding Developmental Processes.

The ability to visualize and quantitatively measure dynamic biological processes in vivo and at high spatiotemporal resolution is of fundamental importance to experimental investigations in developmental biology. Light-sheet microscopy is particularly well suited to providing such data, since it offers exceptionally high imaging speed and good spatial resolution while minimizing light-induced damage to the specimen. We review core principles and recent advances in light-sheet microscopy, with a focus on concepts and implementations relevant for applications in developmental biology. We discuss how light-sheet microcopy has helped advance our understanding of developmental processes from single-molecule to whole-organism studies, assess the potential for synergies with other state-of-the-art technologies, and introduce methods for computational image and data analysis. Finally, we explore the future trajectory of light-sheet microscopy, discuss key efforts to disseminate new light-sheet technology, and identify exciting opportunities for further advances.

Independent and Stochastic Action of DNA Polymerases in the Replisome.

It has been assumed that DNA synthesis by the leading- and lagging-strand polymerases in the replisome must be coordinated to avoid the formation of significant gaps in the nascent strands. Using real-time single-molecule analysis, we establish that leading- and lagging-strand DNA polymerases function independently within a single replisome. Although average rates of DNA synthesis on leading and lagging strands are similar, individual trajectories of both DNA polymerases display stochastically switchable rates of synthesis interspersed with distinct pauses. DNA unwinding by the replicative helicase may continue during such pauses, but a self-governing mechanism, where helicase speed is reduced by ∼80%, permits recoupling of polymerase to helicase. These features imply a more dynamic, kinetically discontinuous replication process, wherein contacts within the replisome are continually broken and reformed. We conclude that the stochastic behavior of replisome components ensures complete DNA duplication without requiring coordination of leading- and lagging-strand synthesis. PAPERCLIP.

Ultra-High Resolution 3D Imaging of Whole Cells.

Fluorescence nanoscopy, or super-resolution microscopy, has become an important tool in cell biological research. However, because of its usually inferior resolution in the depth direction (50-80 nm) and rapidly deteriorating resolution in thick samples, its practical biological application has been effectively limited to two dimensions and thin samples. Here, we present the development of whole-cell 4Pi single-molecule switching nanoscopy (W-4PiSMSN), an optical nanoscope that allows imaging of three-dimensional (3D) structures at 10- to 20-nm resolution throughout entire mammalian cells. We demonstrate the wide applicability of W-4PiSMSN across diverse research fields by imaging complex molecular architectures ranging from bacteriophages to nuclear pores, cilia, and synaptonemal complexes in large 3D cellular volumes.

Fluorescence nanoscopy in cell biology.

Fluorescence nanoscopy uniquely combines minimally invasive optical access to the internal nanoscale structure and dynamics of cells and tissues with molecular detection specificity. While the basic physical principles of 'super-resolution' imaging were discovered in the 1990s, with initial experimental demonstrations following in 2000, the broad application of super-resolution imaging to address cell-biological questions has only more recently emerged. Nanoscopy approaches have begun to facilitate discoveries in cell biology and to add new knowledge. One current direction for method improvement is the ambition to quantitatively account for each molecule under investigation and assess true molecular colocalization patterns via multi-colour analyses. In pursuing this goal, the labelling of individual molecules to enable their visualization has emerged as a central challenge. Extending nanoscale imaging into (sliced) tissue and whole-animal contexts is a further goal. In this Review we describe the successes to date and discuss current obstacles and possibilities for further development.

Ångström-resolution fluorescence microscopy.

Fluorescence microscopy, with its molecular specificity, is one of the major characterization methods used in the life sciences to understand complex biological systems. Super-resolution approaches1-6 can achieve resolution in cells in the range of 15 to 20 nm, but interactions between individual biomolecules occur at length scales below 10 nm and characterization of intramolecular structure requires Ångström resolution. State-of-the-art super-resolution implementations7-14 have demonstrated spatial resolutions down to 5 nm and localization precisions of 1 nm under certain in vitro conditions. However, such resolutions do not directly translate to experiments in cells, and Ångström resolution has not been demonstrated to date. Here we introdue a DNA-barcoding method, resolution enhancement by sequential imaging (RESI), that improves the resolution of fluorescence microscopy down to the Ångström scale using off-the-shelf fluorescence microscopy hardware and reagents. By sequentially imaging sparse target subsets at moderate spatial resolutions of >15 nm, we demonstrate that single-protein resolution can be achieved for biomolecules in whole intact cells. Furthermore, we experimentally resolve the DNA backbone distance of single bases in DNA origami with Ångström resolution. We use our method in a proof-of-principle demonstration to map the molecular arrangement of the immunotherapy target CD20 in situ in untreated and drug-treated cells, which opens possibilities for assessing the molecular mechanisms of targeted immunotherapy. These observations demonstrate that, by enabling intramolecular imaging under ambient conditions in whole intact cells, RESI closes the gap between super-resolution microscopy and structural biology studies and thus delivers information key to understanding complex biological systems.

Initiation of T cell signaling by CD45 segregation at 'close contacts'.

It has been proposed that the local segregation of kinases and the tyrosine phosphatase CD45 underpins T cell antigen receptor (TCR) triggering, but how such segregation occurs and whether it can initiate signaling is unclear. Using structural and biophysical analysis, we show that the extracellular region of CD45 is rigid and extends beyond the distance spanned by TCR-ligand complexes, implying that sites of TCR-ligand engagement would sterically exclude CD45. We also show that the formation of 'close contacts', new structures characterized by spontaneous CD45 and kinase segregation at the submicron-scale, initiates signaling even when TCR ligands are absent. Our work reveals the structural basis for, and the potent signaling effects of, local CD45 and kinase segregation. TCR ligands have the potential to heighten signaling simply by holding receptors in close contacts.

Opposing Effects of Cohesin and Transcription on CTCF Organization Revealed by Super-resolution Imaging.

CCCTC-binding factor (CTCF) and cohesin play critical roles in organizing mammalian genomes into topologically associating domains (TADs). Here, by combining genetic engineering with quantitative super-resolution stimulated emission depletion (STED) microscopy, we demonstrate that in living cells, CTCF forms clusters typically containing 2-8 molecules. A fraction of CTCF clusters, enriched for those with ≥3 molecules, are coupled with cohesin complexes with a characteristic physical distance suggestive of a defined molecular interaction. Acute degradation of the cohesin unloader WAPL or transcriptional inhibition (TI) result in increased CTCF clustering. Furthermore, the effect of TI on CTCF clusters is alleviated by the acute loss of the cohesin subunit SMC3. Our study provides quantitative characterization of CTCF clusters in living cells, uncovers the opposing effects of cohesin and transcription on CTCF clustering, and highlights the power of quantitative super-resolution microscopy as a tool to bridge the gap between biochemical and genomic methodologies in chromatin research.

Acto3D: an open-source user-friendly volume rendering software for high-resolution 3D fluorescence imaging in biology.

Advances in fluorescence microscopy and tissue-clearing have revolutionised 3D imaging of fluorescently labelled tissues, organs and embryos. However, the complexity and high cost of existing software and computing solutions limit their widespread adoption, especially by researchers with limited resources. Here, we present Acto3D, an open-source software, designed to streamline the generation and analysis of high-resolution 3D images of targets labelled with multiple fluorescent probes. Acto3D provides an intuitive interface for easy 3D data import and visualisation. Although Acto3D offers straightforward 3D viewing, it performs all computations explicitly, giving users detailed control over the displayed images. Leveraging an integrated graphics processing unit, Acto3D deploys all pixel data to system memory, reducing visualisation latency. This approach facilitates accurate image reconstruction and efficient data processing in 3D, eliminating the need for expensive high-performance computers and dedicated graphics processing units. We have also introduced a method for efficiently extracting lumen structures in 3D. We have validated Acto3D by imaging mouse embryonic structures and by performing 3D reconstruction of pharyngeal arch arteries while preserving fluorescence information. Acto3D is a cost-effective and efficient platform for biological research.

BNP-Track: a framework for superresolved tracking.

Superresolution tools, such as PALM and STORM, provide nanoscale localization accuracy by relying on rare photophysical events, limiting these methods to static samples. By contrast, here, we extend superresolution to dynamics without relying on photodynamics by simultaneously determining emitter numbers and their tracks (localization and linking) with the same localization accuracy per frame as widefield superresolution on immobilized emitters under similar imaging conditions (≈50 nm). We demonstrate our Bayesian nonparametric track (BNP-Track) framework on both in cellulo and synthetic data. BNP-Track develops a joint (posterior) distribution that learns and quantifies uncertainty over emitter numbers and their associated tracks propagated from shot noise, camera artifacts, pixelation, background and out-of-focus motion. In doing so, we integrate spatiotemporal information into our distribution, which is otherwise compromised by modularly determining emitter numbers and localizing and linking emitter positions across frames. For this reason, BNP-Track remains accurate in crowding regimens beyond those accessible to other single-particle tracking tools.

Effects and avoidance of photoconversion-induced artifacts in confocal and STED microscopy.

Fluorescence microscopy is limited by photoconversion due to continuous illumination, which results in not only photobleaching but also conversion of fluorescent molecules into species of different spectral properties through photoblueing. Here, we determined different fluorescence parameters of photoconverted products for various fluorophores under standard confocal and stimulated emission depletion (STED) microscopy conditions. We observed changes in both fluorescence spectra and lifetimes that can cause artifacts in quantitative measurements, which can be avoided by using exchangeable dyes.

Pretraining a foundation model for generalizable fluorescence microscopy-based image restoration.

Fluorescence microscopy-based image restoration has received widespread attention in the life sciences and has led to significant progress, benefiting from deep learning technology. However, most current task-specific methods have limited generalizability to different fluorescence microscopy-based image restoration problems. Here, we seek to improve generalizability and explore the potential of applying a pretrained foundation model to fluorescence microscopy-based image restoration. We provide a universal fluorescence microscopy-based image restoration (UniFMIR) model to address different restoration problems, and show that UniFMIR offers higher image restoration precision, better generalization and increased versatility. Demonstrations on five tasks and 14 datasets covering a wide range of microscopy imaging modalities and biological samples demonstrate that the pretrained UniFMIR can effectively transfer knowledge to a specific situation via fine-tuning, uncover clear nanoscale biomolecular structures and facilitate high-quality imaging. This work has the potential to inspire and trigger new research highlights for fluorescence microscopy-based image restoration.