Cell Reports Methods

Targeted protein degradation using conditional degron tag (CDT) technology is a powerful method for rapidly degrading a protein of interest (POI) upon the addition of a degrader drug. A prerequisite for the temporally controlled degradation of an endogenous POI is the generation of homozygous knock-in cells with the degron tag integrated at either the N- or C-terminus of their gene loci. However, obtaining those homozygous knock-in cells often requires selecting many single-cell clones, as human cells typically exhibit low homology-directed repair (HDR) activities. Additionally, tagging a degron to an endogenous protein may inadvertently reduce protein expression, potentially affecting protein function even before the drug is administered. Here, we develop a method for generating degron-tagged knock-in cells that allows us to skip the laborious single-cell cloning. This method arose from our observation that most knock-in cells carry the degron tag only in one allele (heterozygous), while the other allele typically harbors a frameshift insertion/deletion. This observation allowed us to bypass the need for single-cell cloning. We validated our method by knocking in degron tags at the N-terminus of cytoplasmic dynein1 subunits or Adaptor Protein 2 (AP2) subunit. Our experiments confirmed the rapid degradation of these proteins and their functional inhibition in bulk cell populations. Additionally, to mitigate the reduced expression often associated with the degron tagging, we established a method to control expression levels by inserting a mini-promoter immediately upstream of the knock-in cassette. Our method simplifies the workflow for degron tag knock-ins and enhances the versatility of these valuable technologies.

DNA methylation is informative for liquid biopsy, but low template abundance, distributed methylation signals and workflow complexity limit implementation. Here we present Delta-HLD, a PCR-compatible methylation assay platform that quantifies methylation directly in native DNA through sequential hybridization, ligation and methylation-sensitive digestion. The assay co-reports methylation-dependent signals from multiple loci through a shared amplification architecture, generating a single panel-level PCR readout. We established the chemistry, optimized panel size and composition through model-guided experiments, and implemented the assay as a triplex qPCR workflow with per-sample internal process controls. Plasma proof-of-concept analyses showed discriminatory signal in CRC and proof-of-concept transferability to hepatocellular carcinoma. Additional platelet-retaining experiments identified a strategy to increase recovery of analyzable circulating templates while reducing genomic DNA recognition. Delta-HLD provides a compact PCR-compatible framework for low-input methylation analysis without base conversion.

The success of Chimeric Antigen Receptor (CAR) T cell therapy is heavily dependent on the quality of the final cellular product. Current expansion protocols often rely on reagents that require removal from cell culture media, posing logistical challenges in manufacturing, and can also lead to terminal differentiation. Here, we evaluate the use of a soluble, bead-free T cell activator, T cell expansion protein (T-CEP), as a streamlined alternative for generating potent CAR-T cells. Human T cells were activated with T-CEP or known T cell activators (Dynabeads and TransAct) and transduced with either CD19 or interleukin-13 (IL-13) mutein (tetravariant-13; TV-13)-based CAR lentiviral vectors. Our results demonstrate that T-CEP supports robust CAR-T cell expansion and achieves transduction efficiencies comparable to commercial reagents for both types of CAR-T cells. Notably, T-CEP significantly favored the expansion of CD8+ T cells, yielding an enhanced CD27+ phenotype and a lower CD4:CD8 ratio compared to TransAct. Cytotoxicity assays confirmed that T-CEP-expanded CAR-T cells possess cytolytic function equivalent to commercial reagents for both CARs, while exhibiting lower levels of inflammatory cytokine secretion. In summary, T-CEP represents a competitive alternative to existing expansion agents, as it does not require its removal during CAR-T manufacturing and generates a CD8+ dominant, less-differentiated phenotype without compromising efficacy.

The binding of transmembrane (TM) ligands to their cognate TM receptors on neighboring cells governs intercellular adhesion and direct cell-cell communication. However, these interactions are difficult to study in vitro because they depend on membrane presentation, ligand orientation, receptor clustering, and avidity, features often not captured by soluble recombinant ligands or cell-free assays. Here, we describe a flow cytometry-based assay using fluorescent, lentiviral-derived virus-like particles (VLPs) displaying TM ligands to quantify binding to their receptors on target cells. Fluorescent VLPs are generated in-house by plasmid transfection in HEK293T cells and enable direct fluorescent detection without fluorochrome-conjugated secondary antibodies. The system is modular and readily accommodates engineered ligand constructs, including patient-derived variants. We applied this platform to generate ICAM-1-displaying fluorescent VLPs and to study human LFA-1 function in patient-derived leukocytes. This protocol provides a detailed workflow for VLP production and in vitro binding assays, offering a simple, quantitative, and cost-effective approach for studying TM ligand-receptor interactions in a membrane context. The system is well suited for mechanistic studies, functional assessment of patient-derived variants, and direct binding assays using patient-derived cells. Integrating the assay into multicolor flow cytometry panels enables simultaneous immunophenotyping and quantification of up to four ligand-receptor interactions at single-cell resolution. Key featuresO_LIQuantifies TM ligand-receptor binding in a membrane context using fluorescent VLPs and flow cytometry. C_LIO_LIFully in-house, modular system based on plasmid transfection in HEK293T cells, without reliance on recombinant ligands or fluorochrome-conjugated secondary antibodies. C_LIO_LISupports testing of engineered ligand variants, including patient-derived alleles, and direct functional studies on patient-derived cells. C_LIO_LICompatible with multicolor flow cytometry panels, enabling simultaneous immunophenotyping and quantification of up to four ligand-receptor interactions at single-cell resolution. C_LI Graphical overview O_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC="FIGDIR/small/725198v1_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@a43069org.highwire.dtl.DTLVardef@166491borg.highwire.dtl.DTLVardef@49c7d4org.highwire.dtl.DTLVardef@1de36a0_HPS_FORMAT_FIGEXP M_FIG C_FIG

Resolving the morphology of individual neurons in densely packed brain regions remains challenging. Sparse labeling is essential for delineating cellular architecture, yet achieving reproducible low-density labeling e.g. < 1% has been a persistent technical hurdle/problem. We present a genetically encoded two-step strategy, GT-SPARCL (Genetic Two-Step Sparse Cre/FLPe Combination Labeling), which leverages two independent stochastic recombination events to deliver stable, tunable low-density labeling in mice. As a proof of concept, we applied this method to visualizing arginine vasopressin (AVP) neurons in the suprachiasmatic nucleus (SCN), the master circadian pacemaker composed of [~]10,000 neurons per side in mice. Using two-photon imaging of whole-mount SCN blocks, we reconstructed individual AVP neurons and uncovered previously under-resolved morphological heterogeneity. Based on axonal trajectories, we distinguished five structural types, including subclasses with commissural projections to the contralateral SCN and others extending projections beyond the nucleus. The majority ([~]70%) exhibited projections both within and outside the ipsilateral SCN, whereas the second most dominant subset ([~]20%) projected exclusively outside the SCN, representing an output-biased type. In contrast, neurons projecting exclusively within the ipsilateral SCN were exceptionally rare, suggesting that "dedicated" local-circuit AVP neurons do not form a major structural subtype. Collectively, our data indicate that AVP neurons are not structurally uniform but instead comprise diverse projection-defined subtypes, implying subtype-depen-dent contributions to intra-SCN communication, bilateral coupling, and circadian output. Beyond the SCN, our GT-SPARCL method may be applicable for achieving low-density labelling of neurons that can be defined by other specific Cre mouse lines.

Double-stranded RNA (dsRNA) is recognized by cellular receptors as a sign of viral infection, triggering the innate immune response. Increasing evidence shows that cellular dysregulation, for example in immune disorders and neurodegenerative diseases, can also lead to accumulation of endogenously produced dsRNA that stimulates a viral-like immune response. Additionally, dsRNA contamination in RNA therapeutics can lead to harmful side effects via a similar pathway. Despite the clinical relevance of dsRNA, reliable tools for its detection remain limited. At present, dsRNA detection relies almost exclusively on the monoclonal antibodies J2 and K1, which suffer from sequence bias and low sensitivity, limiting their reliability. To address this challenge, we aimed to repurpose naturally occurring dsRNA-binding domains (dsRBDs) to produce reliable, pan-specific affinity reagents for dsRNA. We first systematically screened the dsRBDs of the three human adenosine deaminases acting on RNA (ADARs). This analysis identified ADAR3 dsRBDs as promising candidates due to their reduced sequence dependence compared to the dsRBDs of ADAR1 and ADAR2. We then engineered ADAR3-derived dsRBD constructs having varying linker lengths and domain combinations, allowing us to specifically vary the length cutoff of dsRNA detected, thus creating dsRNA accumulation detected by ADAR3 RBDs (dsRADAR) affinity reagents. Finally, we demonstrate the superior performance of dsRADAR over currently available dsRNA antibodies in a cell model of viral infection and a tissue model of gastric inflammation. Together, dsRADAR provides a sensitive and reliable approach for imaging and quantifying diverse dsRNA structures in a variety of biological contexts. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=124 SRC="FIGDIR/small/724404v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@1d89c30org.highwire.dtl.DTLVardef@1f64fc1org.highwire.dtl.DTLVardef@1ee391forg.highwire.dtl.DTLVardef@e834a6_HPS_FORMAT_FIGEXP M_FIG C_FIG

With the expansion of therapeutic gene editing technology, small animal models provide essential platforms to evaluate the function of these new approaches in vivo. As part of the Somatic Cell Genome Editing (SCGE) Consortium, we developed next-generation murine reporters that overcome current model limitations and broaden detectable in vivo editing outcomes. These include two mouse models built on the "traffic light" reporter concept. This system enables fluorescent detection of both gene repair (green) and CRISPR-generated indels (red) events following editing by a single guide and either dsDNA or single-stranded oligonucleotide donor. We also generated a third reporter model that efficiently detects A-base editor activity. Reporters were validated in cultured embryos, via germline editing, and through activation in vivo by AAV transduction or direct ribonucleoprotein delivery. Together, these new models provide a valuable resource for improved detection of genome editing events in vivo.

The role of antigen-specific T cells responding to antigen is a topic of intense studies, and critical for mechanistic insight of diseases and development of therapeutic strategies. Methods for broad-scale detection of antigen-specific CD4 T cells are lacking, while such methods have demonstrated great value in exploring CD8 T cell response in health and disease. Furthermore, major histocompatibility complex II (MHCII) assays are technically challenging due to high HLA diversity, lower binding affinities, low frequencies of ex vivo antigen-specific CD4 T cells and several bottlenecks in production and peptide exchange of MHCII monomers. Here we use peptide-loaded MHCII (pMHCII) proteins multimerized on a barcode- and fluorophore-labelled dextran backbone to provide a method for the detection of peptide-specific CD4 T cells by using a large display of MHCII-associated peptides. We have established a protocol for MHCII production and peptide-exchange suitable for the generation of large libraries of peptide-MHCII complexes. We validate the use of such pMHCII complexes in the form of barcode-labelled MHCII multimers to detect antigen-specific CD4 T cells. We demonstrate that we can identify antigen specific CD4 T cells, using these DNA barcoded peptide-MHCII multimer. The multimer bound CD4 T cells were selected based on the fluorochrome signal, and the co-attached DNA barcodes were hereafter amplified and used to identify the peptide-MHCII response/binding. In cases where the peptide-specific CD4 T cells frequencies are very low, we expanded the cell population with peptide-pools and in the presence of IL2. The given CD4 T cell populations hereby reach a cell number allowing for the DNA-barcoded pMHCII multimers to detect responses otherwise missed out. Applying this technology, we utilized a panel of 150 peptides derived from human cytomegalo virus (CMV), Epstein barr virus (EBV), Influenza (Flu), SARS CoV 2 and SARS CoV1, Hepatitis B virus (HBV), and Hepatitis C virus (HCV) loaded onto HLA-DRB1*01:01 and DRB1*04:01 to screen peripheral blood mononuclear cells (PBMC). We assessed ex vivo responses in 16 participants with HCV infection, and successfully detected naturally occurring viral-specific CD4 T cells at frequencies as low as 0.004% of total CD4 T cells. The low-frequency responses, identified via the barcode screen, were rigorously validated using individual fluorophore-labelled tetramer staining after a peptide-driven expansion in 15 participants. Furthermore, we assessed the recognition of novel HCV epitopes in 11 additional participants. Through this, we identified a total of 12 distinct HCV epitopes, including 9 that have not been previously utilized in assays to detect CD4 T cells. Overall, this barcoded-multimer platform provides a powerful tool for the large-scale discovery of class II epitopes and the broad profiling of CD4 T cell specificities. This method will allow for in-depth analyses of immune interactions, provide a better understanding of the antigen-driven associations between CD4 and CD8 T cell responses, and help dissect the complexities of CD4 T cell protection in HCV infection.

Recent widespread adoption of cerebral organoid protocols has led to many new studies assessing the human-specific features of neural diseases. However, not all organoid studies employ proper quality control, which limits the physiological relevance of their findings. Here, we discuss the stages of in vivo neocortex formation and how those stages are recapitulated in organoid protocols. We then present the first guide for real-time operator removal of maldeveloped organoids in shaking culture. Finally, we show preliminary work on an organoid imaging and mesofluidic control platform for automated quality control of organoid development. Taken together, this approach for assessing the morphological features of organoids will improve the rigor and reproducibility of organoid studies, increase effect sizes of physiologically relevant disease etiology, and pave the way for cortical organoid GMP in high-throughput. Clinical RelevanceThis establishes high-throughput, visual brain organoid quality control for disease studies and preclinical testing.

Real-time assessment of human pluripotent stem cell (hPSC) quality is critical for reproducibility and safety in regenerative medicine, yet current methods are invasive, labor-intensive, or highly operator-dependent. We present DeepHOPE (Deep-learning-guided Holotomography for Pluripotency Evaluation), a non-invasive, automatizable, and statistics-driven platform that integrates three-dimensional (3D) refractive index imaging with deep learning to assess pluripotency. DeepHOPE performs robustly across diverse contexts, including germ-layer differentiation, retinoic acid-induced differentiation, and mid-reprogramming cultures, enabling streamlined cell production workflows and improving the efficiency of midbrain dopaminergic neuron differentiation through informed colony selection. Mechanistically, DeepHOPE detects minute colony-scale topological changes that precede molecular loss of pluripotency. These early changes are associated with rapid F-actin remodeling, including apical-to-basal redistribution during early differentiation. Consistent with a functional role for cytoskeletal regulation in state transitions, sustained reduction of actomyosin tension decreases pluripotency, identifying cytoskeletal dynamics as an upstream determinant of early pluripotency exit. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/720508v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@1d73508org.highwire.dtl.DTLVardef@1dab29aorg.highwire.dtl.DTLVardef@1039f76org.highwire.dtl.DTLVardef@da29a1_HPS_FORMAT_FIGEXP M_FIG C_FIG

Downstream analysis in single-cell and spatial transcriptomics is highly dependent on a sequence of upstream modeling choices. The non-canonicity of these choices presents challenges for reproducibility. In particular, measures of cellular heterogeneity and diversity do not solely reflect biological variation, but are also sensitive to parameter settings. A diversity measure that is robust to modeling choices, such as clustering resolution, is therefore desirable to improve reproducibility and interpretability. Here, we introduce scDIV, a similarity-sensitive measure of cellular diversity inspired by mathematical ideas in ecological science, which is robust to graph-based clustering parameters and remains applicable even in the absence of cell-type clusters. We use scDIV to quantitatively track the progress of tissue differentiation in both single-cell and spatial mouse development datasets and to evaluate different engineered stem-cell-based embryo models. In contrast to traditional entropy-based methods, such as the Hill number, used to quantify biodiversity, scDIV remains robust to clustering.

Behavior arises from the complex interplay between an organisms nervous system, its genetic makeup, and the environment. High-resolution, high-throughput behavioral quantification is essential for dissecting biological function and the effects of genetic perturbation, but automated analysis remains challenging. Here, we present Autobehaver, an automated behavioral analysis pipeline based on a low-cost, high-throughput recording platform that captures videos of individual Drosophila. From each video, we extracted keypoints and used a custom Transformer to assign frame-wise behavior and orientation labels. We then converted these predictions into high-dimensional per-animal feature vectors and trained XGBoost ensembles to classify animals and identify the features that separated groups. By applying SHAP analysis to the classifier ensemble, we identified the behavioral features most informative for distinguishing groups of flies. We demonstrated the approach in several ways. First, we recovered known behavioral changes associated with heat-activated dTrpA1 activity in specific neural circuits. Second, we detected age-associated behavioral changes consistent with gradual impairment of locomotor and climbing ability. Finally, we used Autobehavers classifier ensemble to place animals with intermediate phenotypes along a behavioral axis and used feature-importance analysis to reveal the behavioral features underlying those intermediate states. Together, Autobehaver provides an interpretable framework for quantitative behavioral phenotyping and comparative analysis of complex genotypes.

Virus infected cells release viral particles, which have variable protein content and are functionally diverse. Deciphering this heterogeneity remains a challenge. Here, we adapt flow virometry to detect and phenotype severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) particles. In supernatants of infected cells, we observe particles measuring 70-100 nm. The appearance of these particles is associated to the increase in viral RNA and infectivity. Sample inactivation using temperature or detergent leads to the disappearance of these particles. Using antibodies and dyes for lipid membranes and nucleic acids, we detect the spike protein, the lipid envelope and the RNA genome. We further confirm the presence of viral particles by electron microscopy. Analyzing different viral preparations demonstrate that spike detection in particles outcompetes particle concentration to predict infectivity. Antibodies against different spike epitopes enable probing of spike conformation changes in the presence of soluble ACE2. Lastly, we detect SARS-CoV-2 particles in PCR-confirmed patient nasal swabs without prior purification steps. In summary, we developed an efficient framework to detect and characterize single SARS-CoV-2 particles.

Proteins are major drivers of biological functions. Single-cell, organ-scale multiplexed protein imaging can reveal high-dimensional molecular and structural features of individual cells and their interactions, enabling an in-depth understanding of complex biological systems. However, such imaging has remained an elusive goal due to hurdles in multiplexed immunolabeling (mIF) of intact organs and integrative image analysis. Here, we present 3D CYCLIC, an organ-scale multiplexed immunolabeling technique, and TACTIC, a single-cell-level, organ-scale image co-registration algorithm. 3D CYCLIC combines ultrafast, versatile 3D immunolabeling with a cleavable crosslinker that preserves signals by protecting bound antibodies during optical clearing while enabling their detachment for subsequent rounds of immunolabeling. TACTIC uses deep warping networks coupled with a propagation-based cell-pair search to co-register individual cells across whole-brain images acquired from the same tissue across multiple rounds of 3D CYCLIC labeling. 3D CYCLIC enabled 6-plex protein profiling of a mouse brain hemisphere, with images that can be combined with TACTIC for integrative analysis. 3D CYCLIC and TACTIC will facilitate a holistic, unbiased understanding of diverse complex multicellular organ systems.

This step-by-step protocol provides a cross-species, non-surgical approach that enables prenatal gene delivery to the developing nervous system in rats and marmosets. Under transabdominal ultrasound guidance, intracerebroventricular injection of recombinant adeno-associated virus vectors into the fetal brain achieves robust and long-term transduction from prenatal stages into adulthood. This approach can be adapted to other species and target sites outside nervous system, enabling safe and selective intrauterine manipulation and the generation of diverse experimental models for basic and preclinical research. For complete details on the use and execution of this protocol, please refer to Ribeiro Gomes et al (2026)1. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=181 SRC="FIGDIR/small/737050v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@696364org.highwire.dtl.DTLVardef@fc3c7forg.highwire.dtl.DTLVardef@1e7c7caorg.highwire.dtl.DTLVardef@1edcef0_HPS_FORMAT_FIGEXP M_FIG C_FIG Before you beginExperimental procedures during gestation allow researchers to study developmental processes, including how manipulations of the fetus and its intrauterine environment influence biological outcomes. Ultrasound imaging guidance greatly facilitates such interventions by providing safe and targeted access to fetal compartments, including for prenatal gene delivery to developing neural cell populations. Critically, delivery of recombinant adeno-associated viruses (rAAVs) into the cerebrospinal fluid (CSF) of developing animals enables widespread gene transfer across the brain. The efficiency and distribution of transduction are strongly influenced by developmental stage, making the timing of delivery an important experimental variable. In altricial species such as mice, major developmental processes, including cortical lamination and the establishment of long-range connections, begin prenatally but continue throughout early postnatal life. In primates, however, development is more advanced at birth, and many equivalent developmental events are shifted to the prenatal period. Consequently, developmental stages that can be targeted postnatally in mice require prenatal access in primates. Here, we present a step-by-step protocol for ultrasound-guided fetal intracerebroventricular viral injection (FIVI) of rAAV in marmosets (Callithrix jacchus) and rats (Rattus norvegicus). The procedure was initially developed and optimized in rats before being translated to marmosets, small New World primates that share key developmental, anatomical, and functional characteristics with humans. Together, these models illustrate the cross-species applicability of the approach, while providing gene delivery strategies for both a genetically tractable rodent model and a translationally relevant nonhuman primate. FIVI enables broad gene transfer and stable, long-term transgene expression in wild type animals, facilitating the generation of complementary quasi-transgenic models for research and translational applications from prenatal development through adulthood.

Antigen specificity of T cells defines the adaptive immune response, yet the vast majority of known T cell receptors (TCRs) lack annotated antigen targets. Single-cell peptide-MHC (pMHC) multimer assays offer a scalable approach to map TCR-antigen interactions. Still, their utility is limited by pervasive non-specific binding and severe overlap between signal and noise, which confound the accurate identification of antigen-specific cells. To address these limitations, we present DextraDemixer, a Bayesian hierarchical mixture model that disentangles antigen-specific T cells from background noise in pMHC multimer data. The model integrates information from negative controls and clonotype structure while providing calibrated uncertainty estimates for classification. We further introduce a dynamic thresholding scheme that enables credible interval-bounded control of the false discovery rate. Extensive benchmarking on simulated datasets and antigen-specific spike-in experiments demonstrated the model's robustness and improved accuracy over established methods. In a longitudinal SARS-CoV-2 vaccine study, DextraDemixer identified antigen-specific TCRs characterized by high sequence similarity, elevated antigen-specificity prediction scores, and strong clonal purity. Annotations showed high concordance with external validation data and supported the identification of antigen-specific motifs. Overall, DextraDemixer provides a principled probabilistic framework for reliable identification of antigen-specific TCRs from single-cell pMHC-multimer assays.

Self-assembling protein fibers enable to record events in single cells, bypassing the need for long-term time-lapse imaging. Fluorescent marks introduced within the growing fiber at user-defined times provide timestamps, giving access to the temporal dynamics of the recorded event. Here, we introduce CATCHFiber, a single-color timestamping strategy for tracing cellular events with high temporal resolution into self-assembling protein fibers. Relying on chemically-induced dimerization to precisely and rapidly control the incorporation of fluorescent proteins into the fiber, CATCHFiber allows the introduction of short 30-min spaced timestamps, significantly increasing the precision of event timings compared to existing methods. This increase in temporal resolution expands the use of fiber-based recorders beyond transcriptional activity, allowing to trace the kinetics of faster processes such as protein degradation, protein neosynthesis and kinase activity, and to determine the timing of cell cycle steps.

Human midbrain organoids (hMBOs) are emerging in vitro models to mirror the cellular diversity and the structural complexity of the developing human brain. However, the dense neural network, limits the investigation of individual cells morphology or cell-cell connectivity, which is mostly restricted to fixed organoids following extensive optical clearing techniques. To better resolve individual cells within a brain organoid and for longitudinal tracking of its growth and development, we turned to adeno-associated virus (AAVs) for targeted gene delivery. In particular, we applied AAVs for expressing specific markers that provide the foundation to image individual cells within 3D hMBOs. Thus, we developed a phenotypic platform to specifically inspect the neuronal and astrocytic cytoarchitecture and to examine their connectivity in living hMBOs derived from two genetically unrelated control iPSC lines. We demonstrate that through AAV transduction, we could capture and reconstruct the 3D architecture of both neurons and astrocytes within the hMBO as a whole. Transduced cells exhibited an intrinsic heterogeneity in term of soma volume, arbor complexity and territory covered, regardless of both genetic background, age, and cell-type. Yet, these cellular morphometrics remained equivalent between the two cell lines, indicative of homogeneity in hMBO cellular development. We were able to establish longitudinal profiling of transduced cells, demonstrating how neurons and astrocytes could expand their network over time. Lastly, we describe time-lapse studies to track cellular motility and morphology fluctuations in neurons and astrocytes over time, highlighting the dynamic nature of these cells within the ramified architecture of the neural network in the developing hMBOs. Overall, our platform underscores the versatility of AAVs in studying single cell-morphometrics and cellular connectivity for longitudinal monitoring of cellular dynamics in live 3D hMBOs instead of a static snapshot.

Abstract/SummaryQuantifying low-frequency chromosomal alterations in living cell populations at early stages is essential in many fields including cancer studies and chromosome engineering, yet selection-based readouts impose delays and can lose fragile positives before readout, biasing frequency estimates; CRISPR imaging rarely reports detection limits at 10^-4. Here, we developed High-throughput CRISPR Imaging (Hi-CRI), integrating engineered dCas9-sgRNA ribonucleoprotein (RNP) labeling, suppression of nonspecific aggregates via metabolic modulation and protease treatment, high-speed volumetric imaging by oblique plane microscopy, GPU-accelerated image analysis, and an explicit error-controlled detection-limit framework. Using per-cell signal-to-noise ratio calling, Hi-CRI achieves a 0.01% detection limit for target-positive cell fractions. In microcell-mediated chromosome transfer of a mouse artificial chromosome (MAC) into HT1080 recipients, Hi-CRI measured 0.03% MAC-positive cells among 184,235 recipients at day 1 post-fusion, versus 0.0007% by antibiotic-selection-based clonogenic assay at day 8 post-fusion, consistent with substantial loss before readout (pre-readout attrition). Hi-CRI enables viability-preserving, selection-independent quantification of low-frequency chromosomal states. TeaserRare chromosome events can be counted in living cells by high-throughput CRISPR imaging before selection hides them.

Plasma membrane sheets generated by controlled mechanical disruption provide direct access to the cytosolic face of the plasma membrane while preserving the native organization of membrane-associated proteins and lipids. Here, we present a protocol for generating and validating sonication-derived plasma membrane sheets from cultured cells, primary neurons, and isolated synaptosomes. We further describe their application for live and fixed imaging of membrane protein localization, organization, conformational dynamics, and protein-protein interactions, as well as quantitative membrane-associated synaptic vesicle recruitment assays. This versatile platform preserves the native membrane environment while enabling direct visualization and quantitative analysis of membrane-associated processes at high spatial resolution. The protocol can be readily adapted to investigate diverse membrane proteins, lipid-dependent mechanisms, and vesicle tethering events across a wide range of cellular systems.