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PubMed2025

Differentiation latency and dormancy signatures define fetal liver hematopoietic stem cells at single-cell resolution.

Decoding the mechanisms governing the self-renewal of hematopoietic stem cells (HSCs) during their expansion in the fetal liver (FL) could unlock novel therapeutic strategies to expand transplantable HSCs, a long-standing challenge. To explore intrinsic and extrinsic regulation of FL-HSC self-renewal at single-cell resolution, we engineered a culture platform replicating the FL endothelial niche that supports the amplification of serially engraftable HSCs. Leveraging this platform together with single-cell index flow cytometry, live imaging, transplantation assays, and single-cell RNA sequencing, we demonstrate that differentiation latency, cell-division symmetry, and transcriptional signatures of biosynthetic dormancy are distinguishing properties of rare FL-HSCs capable of serial multilineage hematopoietic reconstitution. Our findings support a paradigm in which intrinsic programs and niche-derived signals together facilitate the symmetric self-renewal of FL-HSCs while delaying their active participation in hematopoiesis. Our study also provides a resource for future investigations into intrinsic and extrinsic signaling pathways governing FL-HSC self-renewal.

Hematopoietic Stem Cells↗

PubMed2025

Stereo-cell: Spatial enhanced-resolution single-cell sequencing with high-density DNA nanoball-patterned arrays.

Single-cell sequencing technologies have advanced our understanding of cellular heterogeneity and biological complexity. However, existing methods face limitations in throughput, capture uniformity, cell size flexibility, and technical extensibility. We present Stereo-cell, a spatial enhanced-resolution single-cell sequencing platform based on high-density DNA nanoball (DNB)-patterned arrays, which enables scalable and unbiased cell capture at a wide input range and supports high-fidelity transcriptome profiling. Stereo-cell further allows integration with imaging-based modalities and multiomics strategies, including immunofluorescence and epitope profiling. This platform is also compatible with profiling extracellular vesicles, microstructures, and large cells, whereas its spatial resolution facilitates in situ analysis of cell-cell interactions, cellular microenvironments, and subcellular transcript localization. Together, Stereo-cell provides a flexible framework for expanding single-cell research applications.

Animals↗

PubMed2026

Spatially guided in vivo single-cell functional genomics of postnatal heart.

Understanding how spatial organization and cell-cell interactions shape gene regulatory programs is central to decoding tissue development and function. The transition at birth, marked by increased circulatory demands and rapid tissue growth, requires precise spatiotemporal coordination of cardiac maturation. In this study, we generated a high-resolution spatial and temporal atlas of the postnatal mouse heart by integrating single-nucleus RNA sequencing with image-based spatial transcriptomics. This framework revealed dynamic cellular interactions, niche-specific signaling and transcriptional programs guiding cardiomyocyte maturation. To functionally test prioritized regulators in vivo and at scale, we developed PIP-seq (probe-based indel-detectable Perturb-seq), a high-throughput platform that detects single guide RNA identity, infers gene editing and profiles transcription from fixed nuclei. Applying PIP-seq to the developing postnatal heart, we identified 21 previously uncharacterized regulators of cardiomyocyte maturation, including genes essential for sarcomere assembly, metabolic reprogramming and electrophysiological transitions. Together, our findings define how microenvironmental signals and intrinsic gene programs cooperate to guide heart maturation and establish a broadly applicable framework for functional genomics in complex tissues.

Animals↗

PubMed2025

MitoTracer facilitates the identification of informative mitochondrial mutations for precise lineage reconstruction.

Mitochondrial (MT) mutations serve as natural genetic markers for inferring clonal relationships using single cell sequencing data. However, the fundamental challenge of MT mutation-based lineage tracing is automated identification of informative MT mutations. Here, we introduced an open-source computational algorithm called "MitoTracer", which accurately identified clonally informative MT mutations and inferred evolutionary lineage from scRNA-seq or scATAC-seq samples. We benchmarked MitoTracer using the ground-truth experimental lineage sequencing data and demonstrated its superior performance over the existing methods measured by high sensitivity and specificity. MitoTracer is compatible with multiple single cell sequencing platforms. Its application to a cancer evolution dataset revealed the genes related to primary BRAF-inhibitor resistance from scRNA-seq data of BRAF-mutated cancer cells. Overall, our work provided a valuable tool for capturing real informative MT mutations and tracing the lineages among cells.

Humans↗

PubMed2025

BOGO: A Proteome-Wide Gene Overexpression Platform for Discovering Rational Cancer Combination Therapies.

Cancer drug resistance remains a major barrier to durable treatment success, often leading to relapse despite advances in precision oncology. While combination therapies are being increasingly investigated, such as chemotherapy with small molecule inhibitors, predicting drug response and identifying rational drug combinations based on resistance mechanisms remain major challenges. Therefore, a proteome-wide, single-gene overexpression screening platform is essential for guiding rational therapy selection. Here, we present BOGO (Bxb1-landing pad human ORFeome-integrated system for a proteome-wide Gene Overexpression), a robust, scalable, and reproducible screening platform that enables single-copy, site-specific integration and overexpression of ~19,000 human open across cancer cell models. Using BOGO, we identified drug-specific response drivers for 16 chemotherapeutic agents and integrated clinical datasets to uncover proliferation and resistance-associated genes with prognostic potential. Drug response similarity networks revealed both shared and unique mechanisms, highlighting key pathways such as autophagy, apoptosis, and Wnt signaling, and notable resistance-associated genes including BCL2, POLD2, and TRADD. In particular, we proposed a synergistic combination of the BCL2 family inhibitor ABT-263 (Navitoclax®) and the DNA analog TAS-102 (Lonsurf®), which revealed that lysosomal modulation is a key mechanism driving DNA analog resistance. This combination therapy selectively enhanced cytotoxicity in colorectal and pancreatic cancer cells in vitro, and demonstrated therapeutic benefit in vivo in both cell line-derived xenograft (CDX) and patient-derived xenograft (PDX) models. Together, these findings establish BOGO as a powerful gene overexpression perturbation platform for systematically identifying chemoresistance and chemosensitization drivers, and for discovering rational combination therapies. Its scalability and reproducibility position BOGO as a broadly applicable tool for functional genomics and therapeutic discovery beyond cancer resistance.

Journal Article↗

PubMed2026

Exploratory single-nucleus multiomics analysis of myeloid cell states associated with neoadjuvant chemotherapy response in pancreatic ductal adenocarcinoma.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) continues to be one of the most lethal human malignancies, with the vast majority of patients ineligible for immunotherapy. Tumour-associated macrophages (TAMs) are key regulators of the PDAC tumour microenvironment (TME), yet their transcriptional and epigenomic heterogeneity in the context of chemotherapy response is poorly understood. Therefore, we performed an exploratory single nucleus multiomics analysis of PDAC tumors stratified by histopathologic response to neoadjuvant chemotherapy. METHODS: Surgical resection specimens from PDAC patients were classified as responders or non-responders using the American College of Pathologists (CAP) histopathologic criteria. Frozen tissue underwent simultaneous snRNA-seq and snATAC-seq on the 10x Genomics Chromium Single Cell Multiome platform, followed by downstream analyses such as differential gene expression, GO and hallmark pathway enrichment, pseudotime trajectory inference and ChromVAR transcription factor motif analysis. RESULTS: Multiomics profiling of 30 840 high-quality nuclei revealed a myeloid compartment that differed in composition and transcriptional state between CAP-defined responders and non-responders in this small cohort. We observed a trend toward higher LAM-like state proportions in the responders than non-responders (38.4% vs. 26.7%), although this disparity did not achieve statistical significance. The transcriptional programs of the responder myeloid cells are associated with phagocytosis and lipid handling. Chromatin accessibility analysis further suggested candidate response-associated transcription factor motif accessibility patterns. CONCLUSIONS: Neoadjuvant-treated PDAC tumours from CAP-defined responders in this cohort myeloid landscape with apparent enrichment of LAM-like states and immune-activating transcriptional/epigenetic programs. However, these findings are preliminary and hypothesis-generating because of the small cohort size, heterogeneous treatment regimens, absence of matched pre-treatment biopsies, and lack of knockout validation. Larger treatment cohorts and functional/mechanistic studies are needed to determine whether LAM-like myeloid programs contribute to chemotherapy response or reflect a consequence of chemotherapy treatment.

Humans↗

PubMed2025

Tracking Somatic Mutations for Lineage Reconstruction.

The human genome is composed of distinct genomic regions that are susceptible to various types of somatic mutations. Among these, Short Tandem Repeats (STRs) stand out as the most mutable genetic elements. STRs are short repetitive polymorphic sequences, predominantly situated within noncoding sectors of the genome. The intrinsic repetition characterizing these sequences makes them highly mutable in vivo. Consequently, this characteristic provides the chance to unravel the natural developmental history of human viable cells retrospectively. However, STRs also introduce stutter noise in vitro amplification, which makes their analysis challenging. Here we describe our integrated biochemical-computational platform for single-cell lineage analysis. It consists of a pipeline whose inputs are single cells and whose output is a lineage tree of input cells.

Humans↗

PubMed1978

Visuomotor restriction of one eye in kittens reared with alternate monocular deprivation.

It is known that kittens reared in ways that restrict movement while visual stimulation is received exhibit deficits in visually guided behavior. Presumably, the behavioral dysfunction is due to a lack of sensorimotor coordination during visual exposure. The current investigation was undertaken to study this effect both physiologically and behaviorally. Two groups of kittens were normally reared until they were nearly 4 weeks old. They were then placed in a darkroom and exposed daily for 1--2 hours while one eye was occluded. On alternate days, alternate eyes were covered. One group was restrained in a body cast while a given eye was exposed, but the kittens were free to move about while the other eye received visual experience. A second control group was alternately occluded, but freely mobile during all exposures. An additional cat was also unrestrained during daily rearing periods and neither eye was ever occluded. Behavioral tests showed clear deficits when the "passive" eye of the restrained-unrestrained group was used. Deficiencies were found in visually guided paw placing, pursuit eye movements, and jumping behavior to a platform. Responses of single cells were studied in area 17 of the visual cortex. Ocular dominance distributions showed marked reductions in binocularity for alternated occluder cats. The eye that had received exposure while animals were active in the restrained-unrestrained group also tended to predominate but the difference was not statistically significant.

Animals↗

PubMed2026

CRISPR screens for the discovery of novel ferroptosis targets: progress and perspectives.

Ferroptosis is a distinct, iron-dependent form of regulated cell death characterized by lipid peroxidation. Despite its growing significance in physiology and disease, the molecular networks that govern ferroptosis are not yet fully understood. Genome-wide CRISPR screens have broadened the regulatory landscape of ferroptosis by revealing both conserved and context-dependent mechanisms. In this review, we summarize recent advances in CRISPR-based ferroptosis screens, highlighting a transition from in vitro CRISPR screens to in vivo platforms and single-cell CRISPR screens. We also discuss the potential translation of key targets, focusing on their structural druggability and therapeutic potential. By outlining objective-driven screening strategies, this review seeks to provide options for exploring the distinct mechanisms of ferroptosis and to accelerate its translation into therapeutic opportunities for various diseases.

CRISPR screens↗

PubMed2023

MitoTracer facilitates the identification of informative mitochondrial mutations for precise lineage reconstruction.

Journal Article↗

PubMed2026

Characterization of METTL3/14-mediated m6A modification in human transcriptome using Nanopore direct RNA sequencing.

Post-transcriptional RNA modifications modulate diverse aspects of RNA metabolism. N6-methyladenosine (m6A), one of the most abundant internal RNA modifications, is deposited by the core methyltransferase complex, METTL3 and METTL14. Oxford Nanopore Technologies (ONT) platform permits direct, single RNA molecule sequencing while preserving native modifications. However, without rigorous benchmarking, the accuracy and reproducibility of modification detection remain uncertain. Here, we leveraged ONT to comprehensively profile bona fide m6A modifications in cellular RNAs at single-nucleotide resolution by integrating two direct RNA sequencing chemistries (RNA002 and RNA004) with the m6Anet and Dorado modification-detection models. We independently depleted METTL3 and METTL14 in human cells and rigorously validated modification calls through several assays and independent orthogonal methods (GLORI and miCLIP). We find that Dorado detected a higher number of m6A events and enabled simultaneous detection of other RNA modifications (5-methylcytosine, pseudouridine, and inosine). Pairing Dorado with an in vitro transcribed, unmodified control under stringent filtering, we provide compelling evidence supporting a global reduction in m6A sites and stoichiometry within coding sequences and across genes, particularly in highly modified genes and sites, and at consensus DRACH motifs. We report a differential and complex regulation of modified transcripts, accompanied by a global reduction in poly(A) tail length. Notably, METTL3 and METTL14 depletion produced distinct transcript-specific effects, supporting non-redundant roles within the m6A writer complex. Together, our study illustrates a notable advancement of ONT capabilities and establishes a robust transcriptome-wide framework for RNA modification detection, thereby laying the groundwork for exploring the contribution of METTL3/METTL14 to cellular functions and disease.

Humans↗

PubMed2026

A scalable, low-cost, sample hashing workflow for multiomic single-cell analysis using the Seq-Well S3 platform.

In-depth analyses of clinical samples have the potential to provide unparalleled insights into the cellular mechanisms that underlie both health and disease, as well as therapeutic and prophylactic responses. However, these specimens are often paucicellular, necessitating the use of workflows that maximize the amount of information that can be learned. Here we provide a detailed protocol for generating and analyzing single-cell multiomic data from low-input samples with the Seq-Well S3 platform. We further describe a matched pipeline for sample hashing that reduces costs and sources of technical variation in the resulting data while also enhancing throughput. In brief, our streamlined and efficient methodology involves: (1) optionally staining single-cell suspensions with antibody-oligonucleotide conjugates for cell surface protein quantification and/or sample multiplexing; (2) generating Seq-Well S3 sequencing libraries; (3) optionally producing bulk-RNA sequencing libraries via SMART-seq2 to support genetic demultiplexing; and (4) computationally analyzing the resulting data. Each step herein has been designed to leverage readily available reagents and standard laboratory equipment, substantially lowering barriers to entry for researchers. The overall Protocol can yield high-quality multiomic insights from samples in under a week.

Single-Cell Analysis↗

PubMed2026

Barcoded oligonucleotide system (BOLT) for targeted organ delivery.

The therapeutic potential of oligonucleotides (oligos) is limited by insufficient delivery to extrahepatic tissues. In vitro assays often fail to accurately predict in vivo behavior, while testing each oligo candidate in animals remains inherently low throughput. Here, we conceive a barcoded oligonucleotide system (BOLT), a platform that enables high-throughput in vivo evaluations of small-molecule ligands and identifies tissue-specific oligo delivery. BOLT integrates rational design of oligo barcodes, modular conjugation chemistry, and next-generation sequencing (NGS)-based quantification, allowing simultaneous evaluation of many chemically diverse ligand-oligo conjugates within a single animal. Notably, this platform is applicable in both mice and nonhuman primates (NHPs). Using BOLT, we discovered ligands with tropism for tissues such as the brain, lung, and muscle. Collectively, these results indicate that the BOLT platform can accelerate the discovery of tissue-targeting ligands for broad oligo therapeutics.

Journal Article↗

PubMed2026

VINE-seq and MultiVINE-seq for single-nucleus and multiome profiling of the brain vasculature.

The human cerebrovasculature is a critical yet historically understudied component of neurological health. Dysfunction of the diverse endothelial, mural, and perivascular cells that comprise cerebral vessels is central to diseases ranging from stroke to Alzheimer's disease. However, characterizing these cell populations at a molecular level has proven exceptionally challenging. Encased within a robust basement membrane, vascular cells resist standard dissociation methods, leading to their systematic depletion and underrepresentation in existing single-nucleus genomic atlases. This has created a major blind spot in neuroscience. To overcome this barrier, we developed vessel isolation and nucleus extraction for sequencing (VINE-seq) and its advanced iteration, MultiVINE-seq. The protocol provides a robust, reproducible workflow for the enrichment and high-resolution profiling of vascular, perivascular, and immune cells from fresh or frozen human and mouse brain tissue. First, intact vessels (predominantly capillaries and small arterioles/venules, 100 µm in diameter) are isolated from homogenized brain tissue via dextran-based density-gradient centrifugation, separating the vascular pellet from myelin and the parenchymal fraction. Second, the collected vessels are rigorously washed over a cell strainer to remove trapped contaminants. A critical innovation lies in the third stage: the optimized extraction of nuclei from purified vessels using enzymatic digestion. After extraction, the protocol uses fluorescence-activated cell sorting (FACS) to ensure collection of high-purity nuclei suitable for widely used droplet-based sequencing platforms (e.g., 10x Genomics single cell 3' or multiome). This protocol requires 4-5 h to complete and can be carried out by researchers with single-cell and flow cytometry training.

Journal Article↗

PubMed2026

Metal-organic frameworks nanozyme-integrated portable microneedle patch for visual bacterial monitoring in meat.

Foodborne microbial contamination is a major global health concern, with conventional methods often being time-consuming and complex. Herein, we developed a novel portable biosensor by integrating microneedle patch technology and a metal-organic framework (Fe/Cu-NBDC MOF) nanozyme, enabling rapid, on-site, visual detection of bacteria in meat. The sensing system works by encapsulating aptamer-functionalized MOF nanozymes within a hydrogel patch, where their catalytic sites are initially blocked by the aptamer. In the presence of Staphylococcus aureus (S. aureus) as the target, the specific aptamer's binding to bacteria exposes numerous catalytic sites, further activating the chromogenic reaction of the tetramethylbenzidine‑hydrogen peroxide (TMB-H₂O₂) system, enabling visual detection of S. aureus. The biosensor demonstrates a detection limit of 82 CFU/mL with excellent specificity to successfully apply to commercial mutton. By integrating sampling, enrichment, and visual detection into a single compact device, this platform offers a practical, efficient solution for rapid on-site screening of foodborne pathogens.

Biosensing Techniques↗

PubMed2026

Multi-omic analyses of the same sample using metabolomics, lipidomics, proteomics, phosphoproteomics, and glycoproteomics.

Mass spectrometry (MS)-based multi-omics offers powerful tools to comprehensively characterize proteins, post-translational modifications, metabolites, and lipids. However, these measurements are typically performed using separate sample preparation workflows and modality-specific liquid chromatography mass spectrometry (LC-MS) platforms, limiting integration and constraining applications to small amounts of sample materials, especially scarce clinical specimens. Here, we describe a unified nano-LC-MS framework that enables metabolomic, lipidomic, proteomic, phosphoproteomic, and glycoproteomic analyses from the same starting material using a single nano-LC-MS platform, with only the chromatographic conditions, acquisition methods, and enrichment procedures tailored to each omics. This integrated strategy reduces workflow complexity and sample consumption while improves analytical continuity across molecular layers. By enabling deep multi-omics characterization from the same sample, this platform provides a practical foundation for comprehensive analysis of precious clinical samples.

Proteomics↗

PubMed2026

A single-cell atlas of multiple myeloma defines malignant archetypes and proliferative states.

Multiple myeloma (MM) is a plasma-cell malignancy with extensive genomic and transcriptional heterogeneity, limiting disease classification and precision therapy. Here we generated a clinically annotated, population-scale, single-cell atlas of MM from 341 individuals spanning the disease and treatment continuum. We identified five recurrent malignant transcriptional archetypes and an orthogonal proliferative program associated with genomic features, therapeutic resistance and clinical outcomes. Validation in the independent CoMMpass cohort demonstrated robustness, prognostic relevance and portability across platforms. We developed a single-cell, target-discovery pipeline prioritizing malignant enrichment, cell-type specificity and tissue restriction, identifying FCRL2 as a plasma-restricted or B cell-lineage-restricted surface target expressed by malignant plasma cells. FCRL2-targeted chimeric antigen receptor T cells demonstrated antigen-specific activity in vitro and survival benefit in vivo. Together, these data provide a clinically actionable blueprint for patient stratification and precision target nomination in plasma-cell malignancies.

Multiple Myeloma↗

PubMed2026

Multiomics approaches to cardiovascular disease: technological innovations and clinical translation.

Cardiovascular diseases (CVDs) remain the leading cause of global morbidity and mortality, reflecting a persistent gap between clinical phenotyping and the molecular mechanisms that govern disease initiation, progression, and interindividual variability. Recent advances in emerging technologies have fundamentally reshaped cardiovascular physiology by enabling high-resolution, cross-layer profiling of the heart and vasculature across genomic, epigenomic, transcriptomic, proteomic, metabolomic, lipidomic, glycomic, and fluxomic layers, increasingly at single-cell and spatial resolution. These approaches reveal CVD as a coordinated, multilayered process driven by dynamic interactions among cell types, regulatory programs, and metabolic states, rather than isolated gene-level defects. In this review, we synthesize how emerging multiomic, computational, and functional genomic technologies are redefining the study of cardiovascular disease across molecular, cellular, and tissue levels. We highlight recent innovations in single-cell and spatial atlases, long-read sequencing, proteomics and metabolomics, integrative data modeling, and functional omics approaches, including genome-scale perturbation screens and single-cell perturbation frameworks. These platforms enable mechanistic dissection of regulatory circuits, distinguish primary disease drivers from secondary adaptations, and directly assess therapeutic reversibility, advancing the field beyond associative biomarker discovery toward mechanism-guided target prioritization. We further discuss key methodological and translational challenges accompanying high-dimensional cardiovascular data, including preanalytical variability, control selection, temporal misalignment across molecular layers, population diversity, and reference bias. By integrating technological innovation with computational rigor and functional validation, this review frames emerging omics-enabled strategies as a unified, physiologically grounded framework for translating molecular insight into clinically meaningful cardiovascular phenotypes and advancing precision cardiovascular medicine.

Humans↗