Generation of densely labeled oligonucleotides for the detection of small genomic elements.

The genome contains numerous regulatory elements that may undergo complex interactions and contribute to the establishment, maintenance, and change of cellular identity. Three-dimensional genome organization can be explored with fluorescence in situ hybridization (FISH) at the single-cell level, but the detection of small genomic loci remains challenging. Here, we provide a rapid and simple protocol for the generation of bright FISH probes suited for the detection of small genomic elements. We systematically optimized probe design and synthesis, screened polymerases for their ability to incorporate dye-labeled nucleotides, and streamlined purification conditions to yield nanoscopy-compatible oligonucleotides with dyes in variable arrays (NOVA probes). With these probes, we detect genomic loci ranging from genome-wide repetitive regions down to non-repetitive loci below the kilobase scale. In conclusion, we introduce a simple workflow to generate densely labeled oligonucleotide pools that facilitate detection and nanoscopic measurements of small genomic elements in single cells.

Detection of fluorescent protein mechanical switching in cellulo.

The ability of cells to sense and respond to mechanical forces is critical in many physiological and pathological processes. However, determining the mechanisms by which forces affect protein function inside cells remains challenging. Motivated by in vitro demonstrations of fluorescent proteins (FPs) undergoing reversible mechanical switching of fluorescence, we investigated whether force-sensitive changes in FP function could be visualized in cells. Guided by a computational model of FP mechanical switching, we develop a formalism for its detection in Förster resonance energy transfer (FRET)-based biosensors and demonstrate its occurrence in cellulo within a synthetic actin crosslinker and the mechanical linker protein vinculin. We find that in cellulo mechanical switching is reversible and altered by manipulation of cell force generation, external stiffness, and force-sensitive bond dynamics of the biosensor. This work describes a framework for assessing FP mechanical stability and provides a means of probing force-sensitive protein function inside cells.

"Forcing" new interpretations of molecular tension sensor studies.

Molecular tension sensors are central tools for mechanobiology studies but have limitations in interpretation. Reporting in Cell Reports Methods, Shoyer et al. discover that fluorescent protein photoswitching in concert with sensor extension may expand the use and interpretation of common force-sensing tools.

DNA-PAINT adaptors make for efficient multiplexing.

Multiplexed super-resolution imaging offers a route to spatial proteomics; however, time-efficient mapping of many protein species has been challenging. Two recent works in Cell highlight SUM-PAINT and FLASH-PAINT, methods that leverage adaptor DNA strand design to combine advances in multiplexing with increases in speed of label exchange. These advances permit unbiased omics-style analyses to advance biological insights from super-resolution images.

Live-cell biosensors based on the fluorescence lifetime of environment-sensing dyes.

In this work, we examine the use of environment-sensitive fluorescent dyes in fluorescence lifetime imaging microscopy (FLIM) biosensors. We screened merocyanine dyes to find an optimal combination of environment-induced lifetime changes, photostability, and brightness at wavelengths suitable for live-cell imaging. FLIM was used to monitor a biosensor reporting conformational changes of endogenous Cdc42 in living cells. The ability to quantify activity using phasor analysis of a single fluorophore (e.g., rather than ratio imaging) eliminated potential artifacts. We leveraged these properties to determine specific concentrations of activated Cdc42 across the cell.

Discontinuity third harmonic generation microscopy for label-free imaging and quantification of intraepidermal nerve fibers.

Label-free imaging methodologies for nerve fibers rely on spatial signal continuity to identify fibers and fail to image free intraepidermal nerve endings (FINEs). Here, we present an imaging methodology-called discontinuity third harmonic generation (THG) microscopy (dTHGM)-that detects three-dimensional discontinuities in THG signals as the contrast. We describe the mechanism and design of dTHGM and apply it to reveal the bead-string characteristics of unmyelinated FINEs. We confirmed the label-free capability of dTHGM through a comparison study with the PGP9.5 immunohistochemical staining slides and a longitudinal spared nerve injury study. An intraepidermal nerve fiber (IENF) index based on a discontinuous-dot-connecting algorithm was developed to facilitate clinical applications of dTHGM. A preliminary clinical study confirmed that the IENF index was highly correlated with skin-biopsy-based IENF density (Pearson's correlation coefficient R = 0.98) and could achieve differential identification of small-fiber neuropathy (p = 0.0102) in patients with diabetic peripheral neuropathy.

Pooled CRISPR screening of high-content cellular phenotypes using ghost cytometry.

Recent advancements in image-based pooled CRISPR screening have facilitated the mapping of diverse genotype-phenotype associations within mammalian cells. However, the rapid enrichment of cells based on morphological information continues to pose a challenge, constraining the capacity for large-scale gene perturbation screening across diverse high-content cellular phenotypes. In this study, we demonstrate the applicability of multimodal ghost cytometry-based cell sorting, including both fluorescent and label-free high-content phenotypes, for rapid pooled CRISPR screening within vast cell populations. Using the high-content cell sorter operating in fluorescence mode, we successfully executed kinase-specific CRISPR screening targeting genes influencing the nuclear translocation of RelA. Furthermore, using the multiparametric, label-free mode, we performed large-scale screening to identify genes involved in macrophage polarization. Notably, the label-free platform can enrich target phenotypes without requiring invasive staining, preserving untouched cells for downstream assays and expanding the potential for screening cellular phenotypes even when suitable markers are absent.

Modular dual-color BiAD sensors for locus-specific readout of epigenome modifications in single cells.

Dynamic changes in the epigenome at defined genomic loci play crucial roles during cellular differentiation and disease development. Here, we developed dual-color bimolecular anchor detector (BiAD) sensors for high-sensitivity readout of locus-specific epigenome modifications by fluorescence microscopy. Our BiAD sensors comprise an sgRNA/dCas9 complex as anchor and double chromatin reader domains as detector modules, both fused to complementary parts of a split IFP2.0 fluorophore, enabling its reconstitution upon binding of both parts in close proximity. In addition, a YPet fluorophore is recruited to the sgRNA to mark the genomic locus of interest. With these dual-color BiAD sensors, we detected H3K9me2/3 and DNA methylation and their dynamic changes upon RNAi or inhibitor treatment with high sensitivity at endogenous genomic regions. Furthermore, we showcased locus-specific H3K36me2/3 readout as well as H3K27me3 and H3K9me2/3 enrichment on the inactive X chromosome, highlighting the broad applicability of our dual-color BiAD sensors for single-cell epigenome studies.

GAUSS-EM, guided accumulation of ultrathin serial sections with a static magnetic field for volume electron microscopy.

Serial sectioning electron microscopy (EM) of millimeter-scale three-dimensional (3D) anatomical volumes requires the collection of thousands of ultrathin sections. Here, we report a high-throughput automated approach, GAUSS-EM (guided accumulation of ultrathin serial sections-EM), utilizing a static magnetic field to collect and densely pack thousands of sections onto individual silicon wafers. The method is capable of sectioning hundreds of microns of tissue per day at section thicknesses down to 35 nm. Relative to other automated volume EM approaches, GAUSS-EM democratizes the ability to collect large 3D EM volumes because it is simple and inexpensive to implement. We present two exemplar EM volumes of a zebrafish eye and mouse olfactory bulb collected with the method.

Long-term, high-resolution in vivo calcium imaging in pigeons.

In vivo 2-photon calcium imaging has led to fundamental advances in our understanding of sensory circuits in mammalian species. In contrast, few studies have exploited this methodology in birds, with investigators primarily relying on histological and electrophysiological techniques. Here, we report the development of in vivo 2-photon calcium imaging in awake pigeons. We show that the genetically encoded calcium indicator GCaMP6s, delivered by the adeno-associated virus rAAV2/7, allows high-quality, stable, and long-term imaging of neuronal populations at single-cell and single-dendrite resolution in the pigeon forebrain. We demonstrate the utility of our setup by investigating the processing of colors in the visual Wulst, the avian homolog of the visual cortex. We report that neurons in the Wulst are color selective and display diverse response profiles to light of different wavelengths. This technology provides a powerful tool to decipher the operating principles that underlie sensory encoding in birds.

PXPermute reveals staining importance in multichannel imaging flow cytometry.

Imaging flow cytometry (IFC) allows rapid acquisition of numerous single-cell images per second, capturing information from multiple fluorescent channels. However, the traditional process of staining cells with fluorescently labeled conjugated antibodies for IFC analysis is time consuming, expensive, and potentially harmful to cell viability. To streamline experimental workflows and reduce costs, it is crucial to identify the most relevant channels for downstream analysis. In this study, we introduce PXPermute, a user-friendly and powerful method for assessing the significance of IFC channels, particularly for cell profiling. Our approach evaluates channel importance by permuting pixel values within each channel and analyzing the resulting impact on machine learning or deep learning models. Through rigorous evaluation of three multichannel IFC image datasets, we demonstrate PXPermute's potential in accurately identifying the most informative channels, aligning with established biological knowledge. PXPermute can assist biologists with systematic channel analysis, experimental design optimization, and biomarker identification.

Using MitER for 3D analysis of mitochondrial morphology and ER contacts.

We have developed an open-source workflow that allows for quantitative single-cell analysis of organelle morphology, distribution, and inter-organelle contacts with an emphasis on the analysis of mitochondria and mitochondria-endoplasmic reticulum (mito-ER) contact sites. As the importance of inter-organelle contacts becomes more widely recognized, there is a concomitant increase in demand for tools to analyze subcellular architecture. Here, we describe a workflow we call MitER (pronounced "mightier"), which allows for automated calculation of organelle morphology, distribution, and inter-organelle contacts from 3D renderings by employing the animation software Blender. We then use MitER to quantify the variations in the mito-ER networks of Saccharomyces cerevisiae, revealing significantly more mito-ER contacts within respiring cells compared to fermenting cells. We then demonstrate how this workflow can be applied to mammalian systems and used to monitor mitochondrial dynamics and inter-organelle contact in time-lapse studies.

Live-cell imaging of endogenous CSB-mScarletI as a sensitive marker for DNA-damage-induced transcription stress.

Transcription by RNA polymerase II (RNA Pol II) is crucial for cellular function, but DNA damage severely impedes this process. Thus far, transcription-blocking DNA lesions (TBLs) and their repair have been difficult to quantify in living cells. To overcome this, we generated, using CRISPR-Cas9-mediated gene editing, mScarletI-tagged Cockayne syndrome group B protein (CSB) and UV-stimulated scaffold protein A (UVSSA) knockin cells. These cells allowed us to study the binding dynamics of CSB and UVSSA to lesion-stalled RNA Pol II using fluorescence recovery after photobleaching (FRAP). We show that especially CSB mobility is a sensitive transcription stress marker at physiologically relevant DNA damage levels. Transcription-coupled nucleotide excision repair (TC-NER)-mediated repair can be assessed by studying CSB immobilization over time. Additionally, flow cytometry reveals the regulation of CSB protein levels by CRL4CSA-mediated ubiquitylation and deubiquitylation by USP7. This approach allows the sensitive detection of TBLs and their repair and the study of TC-NER complex assembly and stability in living cells.

u-track3D: Measuring, navigating, and validating dense particle trajectories in three dimensions.

We describe u-track3D, a software package that extends the versatile u-track framework established in 2D to address the specific challenges of 3D particle tracking. First, we present the performance of the new package in quantifying a variety of intracellular dynamics imaged by multiple 3D microcopy platforms and on the standard 3D test dataset of the particle tracking challenge. These analyses indicate that u-track3D presents a tracking solution that is competitive to both conventional and deep-learning-based approaches. We then present the concept of dynamic region of interest (dynROI), which allows an experimenter to interact with dynamic 3D processes in 2D views amenable to visual inspection. Third, we present an estimator of trackability that automatically defines a score for every trajectory, thereby overcoming the challenges of trajectory validation by visual inspection. With these combined strategies, u-track3D provides a complete framework for unbiased studies of molecular processes in complex volumetric sequences.

Instant processing of large-scale image data with FACT, a real-time cell segmentation and tracking algorithm.

Quantifying cellular characteristics from a large heterogeneous population is essential to identify rare, disease-driving cells. A recent development in the combination of high-throughput screening microscopy with single-cell profiling provides an unprecedented opportunity to decipher disease-driving phenotypes. Accurately and instantly processing large amounts of image data, however, remains a technical challenge when an analysis output is required minutes after data acquisition. Here, we present fast and accurate real-time cell tracking (FACT). FACT can segment ∼20,000 cells in an average of 2.5 s (1.9-93.5 times faster than the state of the art). It can export quantifiable features minutes after data acquisition (independent of the number of acquired image frames) with an average of 90%-96% precision. We apply FACT to identify directionally migrating glioblastoma cells with 96% precision and irregular cell lineages from a 24 h movie with an average F1 score of 0.91.

Machine learning for cross-scale microscopy of viruses.

Despite advances in virological sciences and antiviral research, viruses continue to emerge, circulate, and threaten public health. We still lack a comprehensive understanding of how cells and individuals remain susceptible to infectious agents. This deficiency is in part due to the complexity of viruses, including the cell states controlling virus-host interactions. Microscopy samples distinct cellular infection stages in a multi-parametric, time-resolved manner at molecular resolution and is increasingly enhanced by machine learning and deep learning. Here we discuss how state-of-the-art artificial intelligence (AI) augments light and electron microscopy and advances virological research of cells. We describe current procedures for image denoising, object segmentation, tracking, classification, and super-resolution and showcase examples of how AI has improved the acquisition and analyses of microscopy data. The power of AI-enhanced microscopy will continue to help unravel virus infection mechanisms, develop antiviral agents, and improve viral vectors.

Tailoring confocal microscopy for real-time analysis of photosynthesis at single-cell resolution.

Photoautotrophs' environmental responses have been extensively studied at the organism and ecosystem level. However, less is known about their photosynthesis at the single-cell level. This information is needed to understand photosynthetic acclimation processes, as light changes as it penetrates cells, layers of cells, or organs. Furthermore, cells within the same tissue may behave differently, being at different developmental/physiological stages. Here, we describe an approach for single-cell and subcellular photophysiology based on the customization of confocal microscopy to assess chlorophyll fluorescence quenching by the saturation pulse method. We exploit this setup to (1) reassess the specialization of photosynthetic activities in developing tissues of non-vascular plants; (2) identify a specific subpopulation of phytoplankton cells in marine photosymbiosis, which consolidate energetic connections with their hosts; and (3) examine the link between light penetration and photoprotection responses inside the different tissues that constitute a plant leaf anatomy.

Assessing crosstalk in simultaneous multicolor single-molecule localization microscopy.

Single-molecule localization microscopy (SMLM) can reach sub-50 nm resolution using techniques such as stochastic optical reconstruction microscopy (STORM) or DNA-point accumulation for imaging in nanoscale topography (PAINT). Here we implement two approaches for faster multicolor SMLM by splitting the emitted fluorescence toward two cameras: simultaneous two-color DNA-PAINT (S2C-DNA-PAINT) that images spectrally separated red and far-red imager strands on each camera, and spectral demixing dSTORM (SD-dSTORM) where spectrally close far-red fluorophores appear on both cameras before being identified by demixing. Using S2C-DNA-PAINT as a reference for low crosstalk, we evaluate SD-dSTORM crosstalk using three types of samples: DNA origami nanorulers of different sizes, single-target labeled cells, or cells labeled for multiple targets. We then assess if crosstalk can affect the detection of biologically relevant subdiffraction patterns. Extending these approaches to three-dimensional acquisition and SD-dSTORM to three-color imaging, we show that spectral demixing is an attractive option for robust and versatile multicolor SMLM investigations.

Three-dimensional multi-color optical nanoscopy at sub-10-nm resolution based on small-molecule organic probes.

Achieving nanometer-scale resolution remains challenging in expansion microscopy due to photon loss. To address this concern, here we develop a multi-color expansion stimulated emission depletion technique based on small-molecule probes to realize high labeling density and intensity. Our method substantially lowers the barrier to visualizing diverse intracellular proteins and their interactions in three dimensions. It enables us to achieve sub-10-nm resolution in structures such as microfilaments, lysosomes, and mitochondria, providing new insights into cell biology.

CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia.

Decades of research have not yet fully explained the mechanisms of epithelial self-organization and 3D packing. Single-cell analysis of large 3D epithelial libraries is crucial for understanding the assembly and function of whole tissues. Combining 3D epithelial imaging with advanced deep-learning segmentation methods is essential for enabling this high-content analysis. We introduce CartoCell, a deep-learning-based pipeline that uses small datasets to generate accurate labels for hundreds of whole 3D epithelial cysts. Our method detects the realistic morphology of epithelial cells and their contacts in the 3D structure of the tissue. CartoCell enables the quantification of geometric and packing features at the cellular level. Our single-cell cartography approach then maps the distribution of these features on 2D plots and 3D surface maps, revealing cell morphology patterns in epithelial cysts. Additionally, we show that CartoCell can be adapted to other types of epithelial tissues.