Cell Reports Methods

Cortical organoids (COs) represent a powerful in vitro model system that recapitulates key aspects of human brain development, enabling the study of neurodevelopmental processes, cellular diversity, and disease mechanisms in a physiologically relevant 3D environment. However, traditional histological analysis of COs relies on tissue sectioning, which limits the ability to capture the full spatial complexity of organoid architecture. In this study, we establish a framework for applying CLARI-O, an improved tissue-clearing technique, for intact COs and organoid-based systems, enabling comprehensive 3D visualization and analysis of 3D organizational features. Using CLARI-O in combination with high-resolution imaging, we demonstrate the utility of tissue clearing for studying glial populations, including oligodendrocytes and microglia, considered to be underrepresented in COs, and their interactions with neurons. Additionally, we apply this method to forebrain assembloids (FAs) to visualize cellular heterogeneity and the interface between ventral and dorsal regions. Finally, we use CLARI-O to study mouse brains containing xenotransplanted COs (MB-COs) to evaluate human cell integration, migration, vascularization, and structural connectivity. This is the first study to demonstrate how tissue clearing can be used after functional assays such as calcium imaging to correlate neural activity with post hoc structural analysis in MB-COs. Together, this work establishes CLARI-O as a powerful tool for advancing 3D structural and functional interrogation of human CO-derived systems, enhancing their value for disease modeling, drug screening, and translational neuroscience. MotivationCortical organoids have become an increasingly powerful tool in neuroscience. Their complexity has expanded substantially, now incorporating exogenous lineages, fusing organoids with distinct regional identities (assembloids), and enabling xenotransplantation into in-vivo environments. These advancements require more sophisticated technological approaches that are capable of capturing the intricate three-dimensional cyotarchitecture and organization of intact organoid systems both in vitro and after xenotransplantation in vivo. Tissue-clearing methodologies offer a unique opportunity to visualize these structural and cellular features with exceptional depth and resolution. Graphical abstract HighlightsO_LIWe optimized clearing protocols to develop an organoid specific clearing method (CLARI-O) that enables high-resolution visualization of diverse neuronal and glial populations without tissue sectioning, preserving long-range connections and cellular processes. C_LIO_LIForebrain assembloids used to study neuronal and oligodendrocyte migration can be effectively processed using CLARI-O, allowing detailed visualization of fusion interface. C_LIO_LIWe established a robust framework for CLARI-O-based clearing of mouse brain tissue containing xenotransplanted human cortical organoids, enabling comprehensive 3D analysis of graft development, integration, and vascularization in vivo. C_LI

To improve our understanding of synapse assembly, there is a need for robust, easy-to-use, and physiologically relevant in-vitro models allowing the controllable formation of neuronal contacts in a reasonable time, whose structure and function can be investigated using advanced microscopy. To address this challenge, we engineered 3D cultures from rodent dissociated hippocampal cells, that spontaneously assemble in low attachment U-bottom wells into compact spheroids of reproducible dimensions (100-300 microns), determined by the number of seeded cells. These neurospheres contain a mix of neurons and glial cells and grow over time in culture, through the combination of cell proliferation and neurite extension. Neurospheres were immunostained in fluid phase, and/or sparsely electroporated for the multi-color visualization of synaptic proteins. Neurons extend an elaborate network of axons and dendrites, forming within 2 weeks numerous excitatory and inhibitory synapses identified at the structural level by confocal and electron microscopy, and at the functional level by electrophysiology. Periodic calcium oscillations throughout neurospheres further highlight network activity. Finally, we demonstrate the potential of neurospheres to study synaptogenesis by modulating and visualizing the adhesion protein neuroligin-1. Overall, neurospheres represent a standardized and cost-effective system to study synapse structure and function at high resolution in 3D, that should be quite appealing to the cellular neurobiology community.

Ex vivo expansion of mobilized peripheral blood (mPB) hematopoietic stem cells (HSCs) represents a promising approach to advance cell and gene therapy strategies yet is hampered by loss of stem cell function when applying commonly used culture protocols. We performed in-depth characterization of mPB expansion cultures by single cell RNA sequencing, which highlighted differentiation trajectories with preservation of lineage fidelity in committed progenitors. Defining a putative HSC cluster allowed an estimation of transduction efficiency in ex vivo cultures, which correlated with long-term gene marking in xenografts and patients enrolled in a gene therapy study. We then developed a clinically translatable, GMP-compliant process to expand lentivirus (LV)-transduced HSCs from mPB of pediatric patients and adult donors, by biologically informed protocol improvements of cytokine supplementation, media choice, timing of LV transduction and combinations of small molecules preventing the activation of differentiation programs. Our optimized process outperforms validated state-of-the-art cord blood expansion protocols when applied to mPB. LV integration site analysis and genomic barcode-based clonal tracking provided definitive proof for symmetric HSC self-renewal divisions occurring during ex vivo culture. These results warrant clinical testing of this HSC transduction/expansion process in an upcoming clinical gene therapy trial for autosomal recessive osteopetrosis (EU CT 2024-518972-30). One Sentence SummaryA mobilized peripheral blood HSC expansion protocol optimized for gene therapy allows robust polyclonal long-term engraftment of LV-transduced cells.

The establishment of genetic circuits in pluripotent stem cells (PSCs) allows to model and manipulate developmental events. However, prototyping complex circuitry remains challenging, due to limitations in screening circuit components and transgene silencing. Here, we introduce KELPE: PSCs with two silencing-resistant insulated genomic landing pads targeted to genomic safe harbour sites. KELPE cells enable the stable integration of multiple transgenes into the same genomic region, facilitating fair comparisons of genetic circuit components. We demonstrate this by fine-tuning "synthetic neighbour-labelling" technologies. We first generate optimised PUFFFIN PSCs, which report on cell-cell interactions by fluorescently labelling wild-type neighbours. We then generate new synNotch "receiver" PSCs, which can trigger expression of any transgene following interaction with a synthetic ligand presented by "sender" cells of interest. We describe an optimised circuit syntax that abolishes ligand-independent transgene induction in receiver PSCs, and showcase this by synthetically programming cell death in receiver cells engineered to express a toxin following interaction with sender cells. In summary, we describe a new cell line that facilitates silencing-resistant transgene expression and prototyping of synthetic biology tools in a developmentally-relevant model.

Cellular therapies, toxicity screening, and regenerative medicine depend on selecting mammalian cell types with optimal lifespan, persistence post-transplant, immunogenicity, and chemical resilience. This review synthesizes data from over 50 immune, parenchymal, stem, and emerging engineered cell populations--including gamma-delta T cells, iNKT cells, CAR-macrophages, and hypoimmune iPSC derivatives--drawing from in vivo lifespan studies (including 1{blacksquare}C birth-dating and deuterium labeling), engraftment dynamics, immune rejection risk, and stress sensitivity profiles. We introduce a Programmability & Persistence Score (PPS; 0-20) that integrates these features into a unified metric, complemented by Pareto frontier analysis to visualize multi-objective trade-offs. High-PPS cell types (e.g., HLA-matched HSCs, hypoimmune iPSCs, chondrocytes) are suited for long-term regenerative applications, while low-PPS sentinels (e.g., neutrophils, enterocytes) serve acute assays. We discuss mathematical extensions including multi-criteria decision analysis, fuzzy membership functions, and Bayesian frameworks that address limitations of linear additive scoring. Together, these integrated profiles support cell selection for gene editing, organ-on-chip systems, in vivo cell programming, and immunotherapy, bridging cell biology with translational engineering.

Traumatic brain injury (TBI) is a major cause of mortality and long-term disability worldwide, giving rise to complex neurological complications that impact millions of individuals each year. Cellular stress and neuronal injury vary dramatically across cortical layers, vascular niches, and between the ipsilateral (injured) or contralateral (uninjured) hemispheres. There is a critical need for quantitative measures that capture the spatial distribution of injury-induced cellular changes, as well as the gene regulatory elements that drive them. Here, we developed OmicGlaze, an experimental and computational workflow for systematically profiling the spatial transcriptome and epigenome of mouse brains following mild traumatic brain injury. We established a spatial scoring system, and identified region-specific biological processes post injury, including changes in neuronal activities, cellular stress, immune response, and gliosis. Spatial assay for transposase-accessible chromatin with sequencing (Spatial ATAC-seq) generated the first epigenetic map of traumatic brain injury near single-cell resolution. Notably, we identified the Activator Protein-1 family transcription factor Atf3 as a key gene regulator of injury-induced cellular stress. Together, these spatial multi-omics analyses revealed gene regulatory network in TBI and provided a broadly applicable framework for dissecting cellular and molecular mechanisms underlying complex neurological disorders.

Long noncoding RNAs (lncRNAs) regulate gene expression through binding to DNA, various RNAs, and proteins, playing potentially important but poorly understood roles in diseases. Existing approaches for profiling lncRNA-chromatin interactions at the genome scale require large quantities of input material (e.g., 100 million cells per assay). Applying these technologies to tissue samples has been challenging especially when examination of a specific cell type is desired. Here we demonstrate a low-input microfluidic technology based on Chromatin Isolation by RNA Purification (ChIRP) for mapping lncRNA-chromatin interactions using as few as 50,000 cells. We validate our technology, muChIRP-seq, on two lncRNAs of different sizes (GOMAFU and TERC) in human and mouse cell lines and in brain tissues. Furthermore, we profile neuronal nuclei from postmortem human brain tissues of schizophrenia and control subjects. Our profiling data reveal distinct roles and levels of involvement for the two lncRNAs in contribution to schizophrenia. Our multimodal integrative analysis suggests coordination between lncRNA binding and other epigenomic mechanisms such as histone modifications in schizophrenia pathogenesis. Our technology enables lncRNA studies in tissue samples and in a cell-type-specific fashion, unlocking new opportunities to screen and understand lncRNA involvement in diseases.

Synapses are evolutionarily conserved structures that form the fundamental units of neural communication. In the adult mouse cerebral cortex, most synapses are enveloped by glial protrusions from astrocytes and microglia, forming multi-partite synapses. Despite their prevalence, quantitative tools to systematically analyse these multi-cellular structures are limited to two or at most three markers. Here, we present Synapse Thresholding Image Analyser (SynThIA), an open-source, Python-based pipeline for high-throughput and accurate quantification of synapses, including multi-partite synapses. SynThIA enables multichannel analysis of up to four markers, providing detailed measurements of synaptic composition and distribution. The pipeline features an intuitive graphical interface allowing for users with minimal programming experience and a modular design that allows customization for advanced users. By combining accessibility and precision, SynThIA addresses a key methodological gap in multi-partite synaptic image analysis and provides a robust platform for studying synaptic organization in both in situ and ex situ preparation.

We previously developed synthetic Notch (synNotch)-chimeric antigen receptor (CAR)-T cells to improve the safety and efficacy of CAR-T therapy for glioblastoma. In this system, an anti-EphA2/IL13R2-dual-CAR is expressed only upon recognition of tumor- or brain-specific "priming" antigens, EGFRvIII (termed E-SYNC cells) or brevican (B-SYNC), respectively, with E-SYNC currently under phase I clinical evaluation (NCT06186401). However, tracking and profiling these engineered cells in vivo remain challenging, limiting our understanding of their activity and therapeutic potential. To address this gap, we developed a single-cell RNA-sequencing (scRNA-seq) workflow with custom spike-in probes for synNotch-CAR transcripts, enabling simultaneous detection of engineered cells and transcriptomic profiling. In vitro, integration of multiple probes using machine-learning-assisted classifiers detected 78.2% of E-SYNC cells and 60.0% of B-SYNC cells with 98.0% specificity. In a xenograft model, synNotch-positive cells were detected across the spleen, lung, and brain, with the highest frequency and most robust priming and activation observed in the brain. Single-cell transcriptomic analyses revealed tissue-specific differentiation programs, including cytotoxicity, proliferation, metabolic activity, and acquisition of tissue-resident memory phenotypes, shaped by both environmental cues and synNotch-mediated antigen recognition. In summary, this spike-in probe-enhanced scRNA-seq workflow enables robust detection and high-resolution characterization of synNotch-CAR-T cell dynamics and provides a broadly applicable platform for monitoring engineered immune cells in diverse clinical contexts. One Sentence SummaryOur spike-in probe-enhanced single-cell RNA-sequencing method enables analysis of tissue-dependent activation and transcriptional states of synNotch-CAR-T cells, providing a robust and scalable platform for in vivo tracking and transcriptomic profiling of engineered cell therapies.

Extracellular vesicles are key intercellular messengers that modulate the function of target cells by carrying effectors, either at their surface or in their lumen. In the latter case, their action depends on the ability to deliver their content into the cytosol of target cells. How efficiently EVs deliver their content upon interaction with their target cell is thus a central question for understanding the functional impact of this mode of action. To address this question, signal-driven bimolecular interactions between two partners located respectively in the EV lumen and the target cell cytosol have become a widely used strategy to detect the cytosolic delivery EV content. However, the detection of cytosolic delivery with these assays was often tributary to the artificial enhancement of the fusion between EV and cell membranes, through for instance VSV-G fusogenic protein expression. Here we provide a robust and quantitative LUCiferase-based complementation assay (HiBiT/LgBiT), to quantify the Internalization and cytosolic Delivery of EV content: LUCID-EV. By optimizing the signal-to-noise ratio of the assay, the method for loading HiBiT fragment into EVs (fusion to a lipid-binding domain rather than to tetraspanins), and the intracellular position of LgBiT (associated to membranes), we could quantify cytosolic delivery from various non-VSV-G-expressing EVs into target immune dendritic cells. Importantly, this delivery did not involve the acidic late endosomes environment required for VSV-G-dependent EV cytosolic delivery. The limited efficacy of the process highlights the need for highly sensitive assays like the one described here. Further development of the LUCID-EV assay could help identifying EV/target cells pairs with enhanced cytosolic delivery properties and characterize the cellular route for delivery.

The auxin-inducible degron (AID) technology is a convenient and powerful tool for protein functional characterization in a broad array of eukaryotic species. We recently demonstrated that the original AID and improved AID2 systems are very effective at rapid protein depletion in Candida albicans and described a limited set of reagents for their use in certain auxotrophic lab strains. With an eye towards broader applicability with improved flexibility, we report here a new series of template vectors suitable for employing AID2 technology in prototrophic C. albicans strains, including clinical isolates. We adapted a common recyclable antibiotic marker system for the required genome editing steps and developed a strategy for simultaneous CRISPR/Cas9-mediated tagging of both target alleles. We also developed a composite all-in-one tagging cassette that combines the degron tag and the OsTIR1F74A gene for single step strain engineering. We added a fluorescent protein tag option and designed and validated an approach for N-terminal tagging that retains natural promoter control. We also compared effectiveness of the two commonly used synthetic auxins, 5-Ph-IAA and 5-Ad-IAA and the two common OsTIR1 variants, F74A and F74G, and provide guidelines for using the new AID2 system. Finally, using the novel all-in-one cassette, we demonstrate that the AID2 system also works in Candida auris. The new reagents should enhance the convenience and accessibility of the AID2 system for the Candida research community. IMPORTANCEInvasive fungal infections, including those caused by Candida species, are a persistent global health problem, and their treatment is hindered by limited antifungal options and the emergence of drug resistance. There is an urgent need for tools and methods to accelerate discovery of novel therapeutic targets. The expanded and optimized auxin-inducible degron system described herein provides a versatile platform for characterizing protein function and dissecting pathways governing important traits like virulence, stress tolerance, and antifungal resistance. The new reagents make AID technology applicable to any strain. Ultimately, this enhanced toolkit has the potential to help identify and validate new high-value drug targets and deepen our understanding of molecular mechanisms that drive pathogenicity of Candida and other fungal pathogen species.

Early human development involves dynamic transitions in cell identity, including transient transcriptional modulation and stable lineage commitment. Distinguishing these types of gene expression changes is challenging and can be further exacerbated by genetic and experimental heterogeneity in the context of human pluripotent stem cell (hPSC) research. To address this challenge and help uncover transcriptional changes indicative of true developmental state, we establish a curated, cross-platform marker framework for robust identification of pluripotency and early germ-layer identity. Starting from an unbiased RNA-seq discovery set, we systematically validate candidate markers across qPCR, bulk and single-cell RNA sequencing, and quantitative proteomics platforms, yielding a refined panel of 67 markers (20 for the undifferentiated state, 17 for endoderm, 15 for ectoderm, and 15 for mesoderm). We show that this framework reliably identifies early developmental states across heterogeneous datasets, generalizes to in vivo human embryo cell types, and preserves lineage identity despite substantial transcriptional variability. Furthermore, we demonstrate concordant protein-level expression for a subset of markers, supported by deep proteomic profiling of the reference line KOLF2.1J. To enable broad application, we introduce DeepDiff, a web-based resource integrating the validated markers, allowing automated fate classification in a user-friendly interface. Together, this work provides a standardized framework for defining early human developmental identity and disentangling lineage commitment from context-dependent modulation.

Engineering macrophages with chimeric antigen receptors is emerging as a promising cancer therapeutic. Chimeric antigen receptor-expressing macrophages (CAR-Ms) engineered to recognize tumor-specific antigens have been shown to inhibit tumor growth and activate adaptive immune responses, leading to robust tumor control in animal studies. Based on this work, clinical trials have been initiated. While the trials have shown promise, challenges remain. The dynamic interactions between CAR-Ms and cancer cells and the exact mechanisms driving anti-tumor effects remain poorly defined. Defining the dynamic interactions between CAR-Ms and cancer cells will provide critical insights for optimizing future CAR-M design and improving therapeutic efficacy. We sought to directly visualize CAR-M interactions with glioblastoma cells at high-resolution and in real-time using CAR-Ms engineered to recognize Neural-Glial Antigen 2 (NG2), an antigen expressed on glioblastoma cells. Using patient-derived glioblastoma cells, we formed glioblastoma spheroids and embedded them in a 3D matrix together with CAR-Ms. Using time-lapse microscopy, as expected, we found that NG2-targeting CAR-Ms engulfed glioblastoma cells. However, excitingly, we found that NG2-targeting CAR-Ms blocked >85% of glioblastoma cell invasion in 3D. This inhibition of glioblastoma invasion was not due to a significant change in CAR-M polarization states. Together, these data suggest that NG2-targeting CAR-Ms both engulf glioblastoma cells and block glioblastoma invasive behavior.

Human brain organoids are valuable models for studying human brain development and disorders. Although organoids enable multi-omics analyses, understanding developmental mechanisms requires precise three-dimensional mapping of cell types and their dynamics within their cytoarchitecture. Traditional thin-section immunohistochemistry and imaging provide insights but disrupt spatial information. Light-sheet microscopy allows volumetric imaging of intact organoids, but methods and analytical algorithms remain technically challenging. Here, we introduce LUCID-org, an optimized and reproducible technique for Light-sheet imaging of Unsectioned, Cleared, Immunolabeled, and Depth-resolved human brain organoids. Coupled with machine-learning-based quantitative analysis, LUCID-org enables unbiased 3D characterization of cell-type composition and cytoarchitecture. We validated this approach using brain organoids derived from a patient with CENPJ-mutated microcephaly, revealing quantifiable defects in the ventricular zone (VZ), progenitor density, dynamics, cell-type variability, VZ lumen volume, and neuronal distribution compared with healthy controls. The LUCID-org pipeline is straightforward, taking approximately one week, significantly cheaper, non-toxic, and compatible with standard light-sheet microscopes. Therefore, the LUCID-org method could serve as a benchmark for comprehensive 3D analysis of human brain organoids.

We present a workflow for cell-type-enriched epigenomic profiling of the neurovascular unit and associated cell types, including brain endothelial cells, mural cells, microglia, astrocytes, neurons, and oligodendrocytes isolated from frozen unfixed human and mouse brain tissue. The workflow consists of an unfixed nuclei isolation with improved vascular nuclei release, fluorescence-activated nuclei sorting (FANS) based on cell-type-specific DNA-bound proteins, and nanoCUT&Tag for epigenomic profiling. The nanoCUT&Tag uses Tn5 transposase fused to a single-chain nanobody with secondary antibody-like properties. This allows low-input epigenomic profiling that is compatible with FANS-enriched nuclei immunolabeled for transcription factor markers, which is not possible with traditional CUT&Tag approaches. The protocol allows studying the human brain epigenome in a cell type-specific manner, which is increasingly associated with neurodegenerative diseases. The workflow can be used on various tissue sources, including resected and post-mortem archived brain tissue and can be coupled to multiple-omics approaches including single nuclei (sn)RNA-seq, snATAC-seq, and proteomics.

The B-cell receptor (BCR) repertoire serves as a historical record of immunological events. However, deciphering antigen-specific sequences from this vast dataset remains a challenge, particularly for novel pathogens where prior knowledge is absent. While time-course analysis methods such as QASAS have proven effective for tracking immune responses, they rely on existing antibody databases, limiting their applicability to emerging diseases. To overcome this limitation, we introduce LM-QASAS, a reference-free computational framework that integrates antibody language models with repertoire dynamics. By mapping sequences into a high-dimensional semantic embedding space, LM-QASAS identifies functionally convergent clusters of sequences that are semantically similar and exhibit transient expansion upon immune stimulation. In healthy individuals vaccinated with SARS-CoV-2 mRNA vaccines, our method identified spike-specific sequences with over 90\% purity, significantly outperforming methods based on simple sequence identity or abundance. Leave-one-out cross-validation demonstrated that LM-QASAS could accurately reconstruct immune dynamics in unseen individuals without external references. Conversely, the method showed limited sensitivity in an influenza vaccine cohort, revealing that the approach is most effective under conditions of robust clonal expansion (high signal-to-noise ratio), such as those induced by mRNA vaccines. LM-QASAS provides a rapid, high-precision platform for monitoring humoral immunity against emerging threats.

DNA methylation analysis using bisulfite sequencing is widely used to investigate epigenetic regulation at single-base resolution; however, conventional analysis workflows primarily rely on site-wise averaging, which obscures contiguous methylation patterns encoded within individual DNA molecules and limits interpretation of epiallelic heterogeneity in targeted amplicon studies. Here, we present PANDA (Phased ANalysis of DNA Amplicons), an end-to-end graphical pipeline that restores contiguous single-molecule methylation patterns by linking unmerged paired-end reads to reconstruct epiallelic patterns across unsequenced regions. PANDA supports both Sanger and next-generation sequencing inputs, providing a unified workflow for alignment, read-level methylation calling, phased visualization, and quantification of within-sample methylation heterogeneity. Using synthetic benchmarking datasets, we demonstrated that in silico motif filtering isolates specific target reads, enabling the accurate detection of allele-specific methylation and loss of imprinting. Furthermore, the re-analysis of primate placentae datasets confirmed that long-range phasing across unsequenced regions successfully restored the original epiallelic architectures. PANDA establishes a robust, practical approach to single-molecule epigenomic profiling using targeted bisulfite amplicon sequencing.

Human brain function is dependent on synaptic architecture and function between a range of different cell types. Glutamatergic and GABAergic neurons provide the basis by which the excitatory and inhibitory balance is achieved in cortical networks, and microglia interact with them to shape synaptic architecture and neural networks. Understanding the interactions between these cell types is crucial to elucidating mechanisms relevant to brain physiology and, potentially, to neurodevelopmental and neurological disorders. Here, we establish a rapid and reproducible human tri-culture platform comprising deterministically-programmed glutamatergic neurons, GABAergic neurons, and microglia to facilitate cell-cell interaction studies during human cortical development. Using these deterministically-programmed ioCells, we systematically optimised neuronal ratios, culture conditions, and the timing of microglial integration to generate a stable neuronal network prior to microglia incorporation. Multi-electrode arrays (MEAs) recordings identified an 80:20 glutamatergic-to-GABAergic ratio as the most robust configuration for sustained and reproducible network activity in this context. Structural characterisation using automated high-content imaging confirmed the formation of both excitatory and inhibitory synapses, while longitudinal MEA recordings demonstrated stable network maturation following microglial incorporation. Microglia incorporation influenced neuronal firing dynamics, increasing burst activity without disrupting early synapse formation. As a proof of concept for disease modelling, we incorporated microglia carrying the Alzheimers disease-associated TREM2 R47H mutation and detected subtle but reproducible alterations in neuronal burst dynamics. Together, this work establishes a defined human neuron-microglia triculture platform that enables scalable investigation of neuroimmune interactions and genetic variants, laying the foundations for more complex future models.

Accurate quantification of rodent licking behavior is essential for studies of fluid intake, including investigations of alcohol use disorder and obesity. Existing lickometry systems vary widely in sensing modality, cost, scalability, and data resolution, and many available systems either require specialized housing or store only binary lick/no lick data based on thresholding. Here we present CLiQR (Capacitive Lick Quantification in Rodents), an open-source capacitive lickometry system designed for high-throughput recording of licking behavior in home-cage environments while preserving the full capacitance time series. The system uses MPR121 capacitive sensors connected to custom metal-tipped serological pipette sippers and a centralized desktop computer to record data from up to 24 animals concurrently, with capacity for two-bottle choice experiments. Validation experiments demonstrated that the capacitive signals reliably distinguish licking from non-licking interactions. Total lick counts showed a strong positive correlation with measured fluid consumption (r = 0.827, p < 0.0001), confirming that detected events provide a meaningful proxy for intake. All information necessary to reproduce the system is shared openly in this manuscript and online. By combining scalability, full-trace data acquisition, and low cost, CLiQR provides a flexible and extensible platform for high-throughput behavioral neuroscience experiments and enables retrospective improvement of lick-detection algorithms. Significance StatementUnderstanding ingestive behavior requires measuring both total consumption and consumption pattern. Licking microstructure provides information about motivation, palatability, and behavioral strategies (i.e., binge-like front-loading); yet many existing lickometry systems are limited by high cost, low scalability, specialized housing requirements, or loss of information due to event-only data storage. We introduce CLiQR, an open-source capacitive lickometry system that enables high-throughput, home-cage recording from dozens of animals while preserving the full time series of capacitance data. By retaining raw data, CLiQR allows post hoc validation and reanalysis of licking behavior, addressing a key limitation of many current systems. This approach increases experimental flexibility, improves data transparency, and lowers barriers to large-scale studies of ingestive behavior.

Cell-cell fusion is a fundamental biological process underlying diverse physiological and pathological phenomena, yet its quantitative analysis remains methodologically challenging due to its dynamic, heterogeneous, and multistep nature. Existing approaches to assess fusion largely rely on endpoint assays or manual scoring, limiting temporal resolution, scalability, and reproducibility. Here, we present a label-free, high-content live-cell imaging pipeline for real-time quantification of cell fusion dynamics, developed and validated using trophoblast syncytialization as a model system. The method integrates automated image acquisition with a reproducible, stepwise analysis workflow combining supervised texture-based segmentation, morphology-based measurements, and intensity-independent texture analysis. We define quantitative metrics, including the ratio of total cluster area to the number of detected clusters and cytoplasmic granularity features, that together discriminate bona fide fusion events from non-fusion-related cellular clustering or proliferation. Using canonical pharmacological inducers and inhibitors of fusion, we demonstrate the specificity and sensitivity of these parameters for detecting fusion-associated remodeling over time. We further demonstrate the scalability of the pipeline through high-throughput screening of biologically relevant growth factors, hormones, and inhibitors, enabling classification of modulators based on their independent, synergistic, or antagonistic effects on fusion dynamics. Consistent results obtained in an independent model further support its potential applications to additional fusion systems. By providing a robust, reproducible, and adaptable framework for time-resolved fusion analysis, this methodology bridges the gap between qualitative observation and quantitative kinetic assessment. Thus, the approach could be readily extended to other cell fusion systems following system-specific parameter optimization, offering a versatile platform for both mechanistic studies and discovery-driven screening applications.