Biology subjects

Yeung, J.

Publications and source records attributed to Yeung, J..

At least 19 recordsLinked to original sources

bioRxiv2026

The Aging Brain Matrix: Cross-Species Evidence Linking FREM3 to Brain and Cognitive Aging

The human extracellular-matrix-related FREM3 gene is strongly age-dependent, enriched in age-sensitive excitatory long-range-projecting neurons, and implicated in neurodegenerative diseases. To establish the first translationally relevant causal evidence for the role of FREM3 in brain structure and cognition, we developed an excitatory-neuron-specific Frem3 conditional knockout mouse model (Frem3-cKO) and computed genetically regulated expression of FREM3 (FREM3-GReX) in humans, enabling convergent neurostructural and cognitive characterizations. Frem3-cKO mice showed widespread lower global and regional brain volume in middle age vs young adulthood, consistent with drastic age-dependent volume loss absent in wildtype mice. These effects were strongest in cognitively relevant cortical regions and paralleled by lower cognitive performance. In humans, lower FREM3-GReX was associated with lower total surface area, which further mediated an indirect link to lower cognitive performance across multiple age-sensitive domains. We provide the first translationally relevant cross-species evidence supporting a key role for FREM3/Frem3 in maintaining brain and cognitive health across aging.

neuroscience↗

bioRxiv2026

Joint analysis of multiply perturbed cells improves statistical power and cost efficiency in Perturb-seq

Perturb-seq measures transcriptomic responses to genetic perturbations at scale, but conventional designs that enrich for one guide RNA per cell remain resource-intensive. Standard analyses discard cells carrying multiple guides, further limiting the usable yield from each experiment. Here, we characterize how incorporating these guide multiplets affects signal recovery, information loss, and cost reduction. At the highest guide burden, cells showed increased stress and suppressed cell-cycle progression. We develop PerturbMatch, a scalable statistical framework to analyze guide multiplets. Among different classes of guide multiplets, doublets and triplets recovered perturbation responses more accurately than higher-order multiplets. Across three 5000-gene Perturb-seq screens with increasing guide loading, per-cell costs decreased by up to 81% while information loss remained within 1.5-fold of the loss observed between technical replicates. In existing genome-wide Perturb-seq data, incorporating previously discarded guide multiplets increased usable cell numbers and improved statistical power. Compared with a singlet holdout set, adding guide multiplets moved signal recovery closer to the theoretical expected reproducibility. Overall, we recommend a design that intentionally includes single-guide cells, guide doublets, and guide triplets to improve cost efficiency while preserving signal recovery.

genomics↗

bioRxiv2026

Multicellular Spatial Programs Define the Histopathological Architecture of Meningioma

Tumors are often described by cell types or gradients, but the organizing units of tumor tissue remain unclear. Using meningiomas, which show marked morphologic diversity despite constrained and recurrent genetics, we identify reproducible multicellular spatial molecular programs (SMPs) characterized by recurring cell-type mixtures that combine in different proportions across tumors. We built a multi-omic atlas of 147 human meningiomas (1.6 million cells/spots), integrating scRNA-seq, Visium, CosMx-RNA, and CosMx-Protein. Across platforms, SMPs mapped onto canonical whorl-lobule architecture and defined a structured ecological landscape linking hypoxic, immune-evasive states to vascularized, matrix-remodeling, and mineralization-rich states. For translation, we developed MeningNet, a hybrid ConvNeXt-Vision Transformer that infers SMPs directly from hematoxylin-and-eosin sections. MeningNet generalized across an internal replication cohort and 465 external whole-slide images, recovering cross-platform inference and showing significant association with CNS-WHO grade. These findings establish meningioma architecture as a reproducible histopathological framework for inferring spatial molecular state from routine pathology.

Cancer Biology↗

bioRxiv2026

Distinct fibrotic, epithelial and immune transcriptomic programs in phenotypes of chronic lung allograft dysfunction

BackgroundChronic lung allograft dysfunction (CLAD) is the major cause of late mortality after lung transplantation and includes two principal phenotypes, bronchiolitis obliterans syndrome (BOS) and restrictive allograft syndrome (RAS). RAS and other phenotypes with RAS-like opacities (RLO) on chest imaging have a poorer prognosis. Despite clear clinical and pathological differences, molecular distinctions between phenotypes remain poorly defined. We aimed to explore gene transcriptional profiles across CLAD phenotypes and relevant controls. MethodsWe performed bulk RNA sequencing on explanted lung tissue from 45 lung transplant recipients with end-stage CLAD (20 with RLO and 25 without RLO). Samples from twenty-seven control donor and lobectomy lungs and sixteen idiopathic pulmonary fibrosis (IPF) lungs served as comparators. Non-negative matrix factorization (NMF) was used to identify latent transcriptomic signatures, which were correlated with clinical, radiologic, and histopathologic features. ResultsNMF identified seven distinct gene signatures that segregated CLAD phenotypes. RLO-CLAD lungs were enriched for extracellular matrix remodeling and B-cell/plasma cell-associated signatures, overlapping partly with IPF, whereas non-RLO-CLAD showed relative enrichment of epithelial injury and surfactant-response pathways. Signatures related to epithelial homeostasis and ciliary/microtubule function were progressively reduced from control lungs to non-RLO-CLAD and were most suppressed in RLO-CLAD. ConclusionsRLO-CLAD and non-RLO-CLAD, aligning with RAS and BOS phenotypes, show distinct transcriptomic signatures. RLO-CLAD is characterized by profibrotic and humoral immune signatures with profound epithelial dysfunction, whereas non-RLO-CLAD shows relative enrichment of epithelial injury responses. These data provide molecular stratification of CLAD and support the development of phenotype-specific biomarkers and targeted therapies.

bioinformatics↗

bioRxiv2026

Fishash: A contingency table approach to Perturb-seq guide assignment

BackgroundSingle-cell pooled CRISPR screens (Perturb-seq) are a powerful tool in functional genomics. A key preprocessing step is to determine which cells received which perturbations based on possibly noisy sequencing counts of the guide RNA library. Many existing approaches to this problem require fitting probabilistic models which may be computationally expensive on large screens with 10s of thousands of cells and guides. ResultsWe propose to view the guide count matrix as a contingency table and use Fishers Exact Test to test for associations between cell and guide barcodes. This approach is fast, normalizes for both cell and guide-specific size factors, and provides a p-value for each cell-guide pair. Our method further uses a multiple testing correction approach that accounts for the correlation structure between the tests, and a correction for Simpsons paradox that arises due to hidden confounding. Additionally, to facilitate the development and benchmarking of guide assignment methods, we propose a framework for simulating guide counts with a realistic model of sequencing noise. ConclusionsWe find that our method compares favorably to existing methods in both accuracy and runtime on simulated and real datasets. We provide our method in an easy to use R package, fishash, available at https://github.com/jackkamm/fishash. Additionally, the code to reproduce the results of this manuscript is available at https://github.com/jackkamm/fishash_analysis.

genomics↗

bioRxiv2025

Corticosterone-linked microglial activity underpins sexually dimorphic neuroplasticity after ketamine anesthesia.

Anesthesia recovery is critical for resuming normal physiological and neuronal functions; however, the mechanisms involved remain elusive. Here, we identify a female-selective corticosterone-mediated microglia-neuron interaction in vivo during ketamine anesthesia recovery, absent in males. This microglia-neuron interaction induces plastic and functional neuronal changes, as evidenced by increased spine density and mEPSC frequency, which is occluded upon microglia depletion. We show that this process is driven through upregulation of the stress-responsive co-chaperone Fkbp5 mRNA and its protein, FKBP51, in female microglia. Fkbp5/FKBP51 is a key intermediary in a corticosteroid-induced stress response, and its involvement points towards a critical interface between endocrine signaling and microglia. Thus, to counteract the observed KXA-mediated corticosterone increase in the blood, we remove the primary source of corticosterone through adrenalectomy. Close microglia-neuron interaction was absent, but was reinstated after corticosterone injection. Our findings offer a new mechanism of microglia-mediated neuronal plasticity during anesthesia recovery, which is mediated through corticosterone, enhancing our understanding of sex differences in brain function.

neuroscience↗

bioRxiv2025

Innovations in spinal cord cell type heterogeneity across vertebrate evolution

Vertebrates display remarkable diversity of sensorimotor behaviors, each adapted to distinct ecological and survival demands. This diversity raises fundamental questions about the evolutionary origin of motor control: do conserved spinal circuits underlie these behaviors, and how have they diverged across species. Recent studies detail spinal cell-type architecture in mammals but comparable, high-resolution atlases of the non-mammalian spinal cord are lacking. Here, we compare spinal cord cell types between fish, frogs, mice and humans, spanning [~]450 million years of evolution. Across species, we define highly conserved programs of cell type specification that segregate spinal neurons into nearly identical cardinal classes during development. This contrasts with adult stages, when spinal cell-type composition selectively diverges for excitatory neuron subpopulations. Using spatial transcriptomics, we localize this species divergence to the superficial, dorsal spinal cord, where variant neuropeptide expression defines mammalian-specific cell types. The most dorsal spinal cord thus emerges as a recently evolved hub for sensory integration in mammals, a neospinal cord analogous to the neocortex.

neuroscience↗

bioRxiv2025

MYD88 mutations in clonal hematopoiesis promote inflammation and hematopoietic stem cell expansion

Clonal hematopoiesis of indeterminate potential (CHIP) is characterized by expansion of mutant hematopoietic stem and progenitor cells (HSPCs) and an increased risk of chronic diseases and cancers. While mutations in DNMT3A, TET2, and ASXL1 are common in CHIP, the contribution of less frequent gene mutations is not well understood. Here, we report MYD88 mutations, including lymphoma-associated and novel variants in blood cells of the general population and newly diagnosed solid cancer patients. MYD88 CHIP mutations in HSPCs activate NF-{kappa}B, indicating a gain-of-function activity. Modeling MYD88 CHIP in mice, Myd88L252P (equivalent of human L265P) expression resulted in a competitive fitness advantage of HSPCs. Myd88L252P HSPCs exhibit a myeloid cell bias and inflammation, leading to hematologic disease. Single-cell RNA sequencing indicated that Myd88L252P expands distinct hematopoietic and immune cell clusters and activates immune-related pathways in HSPCs. An IRAK1/4 inhibitor suppressed MYD88-dependent NF-{kappa}B activation and reversed Myd88L252P cell expansion. Overall, MYD88 mutations contribute to CHIP by inducing innate immune pathways in HSPCs and inflammatory disease.

cancer biology↗

bioRxiv2025

NEMO recruitment at single cytokine-receptor complexes shows quantized dynamics independent of ligand affinity

Cells use a limited number of receptors to sense and process molecular information from their environment. In the classical view of signaling, receptor-ligand affinities determine binding kinetics, in timescales of diffusion, where their time-averaged contact duration regulates rapid cytoplasmic signaling events to coordinate cellular responses. For some cytokines, single receptor-ligand binding events can initiate large multiprotein complexes in the cytoplasm that assemble over tens of minutes, bringing to question how cytokine affinity influences the sensitivity and strength of signaling. Here, we leverage naturally occurring variation of IL-1{beta} from multiple species to determine the impact of affinity on human IL-1 receptor signaling. Using experiments and models we investigate single receptor complexes activated by ligands that vary across multiple orders of magnitude in affinity. Our results show that while the receptor-ligand affinity establishes cytokine response sensitivity, activated IL-1 receptor complexes signal as discrete, quantized packets of signaling flux independent of affinity.

systems biology↗

bioRxiv2025

Machine learning ensemble identifies distinct age-related response to spaceflight in mammary tissue

BackgroundSpaceflight presents unique environmental stressors, such as microgravity and radiation, that significantly affect biological systems at the molecular, cellular, and organismal levels. Astronauts face an increased risk of developing cancer due to exposure to ionizing radiation and other spaceflight-related factors. Age plays a crucial role in the bodys response to the cellular stresses that lead to cancer, with younger organisms generally exhibiting more efficient response mechanisms than older ones. The vast majority of research investigating breast cancer risk from spaceflight is done in vitro, using cell lines exposed to simulated radiation and microgravity. ObjectivesThe primary objective of this observational study is to characterize the response to spaceflight of in vivo murine mammary tissue and identify the molecular biomarkers enriched in this response using mice flown on the International Space Station. The secondary objective is to determine if age plays a role in this response. MethodsThe NASA Open Science Data Repository (OSDR) has curated transcriptomic data obtained from murine mammary tissue in a controlled experiment (OSD-511) which includes 43 young and old female mice. In this study, we utilized an ensemble of four machine learning binary classifiers (logistic regression, support vector machine, random forest, and single-layer perceptron) to analyze gene expression profiles to predict age (old vs young) and condition (spaceflight vs ground control). Using the genes our ensemble identified as most predictive, we performed pathway enrichment analysis to investigate the molecular pathways involved in spaceflight-related health risks, particularly in the context of breast cancer. ResultsAll space-flown mice responded to spaceflight with evidence of systemic metabolic reprogramming and mitochondrial adaptation to microgravity and radiation as compared to their 33 ground control counterparts. For the 10 mice flown in space, older mice exhibited chronic, significantly enriched pathways related to cell adhesion and extracellular matrix (ECM) structure, while younger mice showed acute activation of pathways involved in cortisol synthesis and adrenergic stress response (with false discovery rate adjusted q-values < .001). These results provide putative biomarkers for monitoring and treating breast cancer. ConclusionsThese findings highlight the critical role of age in modulating the response to spaceflight-induced stress and suggest that these molecular pathways may contribute to differential outcomes in tissue homeostasis, metabolic disorders, and breast cancer tumorigenesis. Moreover, our computational methodology may be applied to several unexplored datasets in OSDR and beyond.

bioinformatics↗

bioRxiv2024

Same-Slide Spatial Multi-Omics Integration Reveals Tumor Virus-Linked Spatial Reorganization of the Tumor Microenvironment

The advent of spatial transcriptomics and spatial proteomics have enabled profound insights into tissue organization to provide systems-level understanding of diseases. Both technologies currently remain largely independent, and emerging same slide spatial multi-omics approaches are generally limited in plex, spatial resolution, and analytical approaches. We introduce IN-situ DEtailed Phenotyping To High-resolution transcriptomics (IN-DEPTH), a streamlined and resource-effective approach compatible with various spatial platforms. This iterative approach first entails single-cell spatial proteomics and rapid analysis to guide subsequent spatial transcriptomics capture on the same slide without loss in RNA signal. To enable multi-modal insights not possible with current approaches, we introduce k-bandlimited Spectral Graph Cross-Correlation (SGCC) for integrative spatial multi-omics analysis. Application of IN-DEPTH and SGCC on lymphoid tissues demonstrated precise single-cell phenotyping and cell-type specific transcriptome capture, and accurately resolved the local and global transcriptome changes associated with the cellular organization of germinal centers. We then implemented IN-DEPTH and SGCC to dissect the tumor microenvironment (TME) of Epstein-Barr Virus (EBV)-positive and EBV-negative diffuse large B-cell lymphoma (DLBCL). Our results identified a key tumor-macrophage-CD4 T-cell immunomodulatory axis differently regulated between EBV-positive and EBV-negative DLBCL, and its central role in coordinating immune dysfunction and suppression. IN-DEPTH enables scalable, resource-efficient, and comprehensive spatial multi-omics dissection of tissues to advance clinically relevant discoveries.

systems biology↗

bioRxiv2024

Mechanistic Insights into Dengue Virus Inhibition by a Clinical Trial Compound NITD-688

Dengue, caused by the dengue virus (DENV), presents a significant public health challenge with limited effective treatments. NITD-688 is a potent pan-serotype DENV inhibitor currently in Phase II clinical trials. However, its mechanism of action is not fully understood. Here, we present the molecular details of how NITD-688 inhibits DENV. NITD-688 binds directly to the nonstructural protein 4B (NS4B) with nanomolar affinities across all four DENV serotypes and specifically disrupts the interaction between NS4B and nonstructural protein 3 (NS3) without significantly changing the interactions between NS4B and other viral or host proteins. NS4B mutations that confer resistance to NITD-688 reduce both NITD-688 binding to NS4B and disruption of the NS4B/NS3 interaction. Specifically, NITD-688 blocks the interaction of NS3 with a cytosolic loop within NS4B. This inhibits the formation of new NS4B/NS3 complexes and disrupts pre-existing complexes in vitro and DENV-infected cells, ultimately inhibiting viral replication. Consistent with this mechanism, NITD-688 retains greater potency in cellular assays with delayed treatment compared to JNJ-1802, another NS4B inhibitor that has been studied in Phase II clinical trials. Together, these findings provide critical insights into the mechanism of action of NITD-688, facilitating the development of novel flavivirus NS4B inhibitors and informing future clinical interventions against DENV.

microbiology↗

bioRxiv2024

Cross-domain information fusion for enhanced cell population delineation in single-cell spatial-omics data

Cell population delineation and identification is an essential step in single-cell and spatial-omics studies. Spatial-omics technologies can simultaneously measure information from three complementary domains related to this task: expression levels of a panel of molecular biomarkers at single-cell resolution, relative positions of cells, and images of tissue sections, but existing computational methods for performing this task on single-cell spatial-omics datasets often relinquish information from one or more domains. The additional reliance on the availability of "atlas" training or reference datasets limits cell type discovery to well-defined but limited cell population labels, thus posing major challenges for using these methods in practice. Successful integration of all three domains presents an opportunity for uncovering cell populations that are functionally stratified by their spatial contexts at cellular and tissue levels: the key motivation for employing spatial-omics technologies in the first place. In this work, we introduce Cell Spatio- and Neighborhood-informed Annotation and Patterning (CellSNAP), a self-supervised computational method that learns a representation vector for each cell in tissue samples measured by spatial-omics technologies at the single-cell or finer resolution. The learned representation vector fuses information about the corresponding cell across all three aforementioned domains. By applying CellSNAP to datasets spanning both spatial proteomic and spatial transcriptomic modalities, and across different tissue types and disease settings, we show that CellSNAP markedly enhances de novo discovery of biologically relevant cell populations at fine granularity, beyond current approaches, by fully integrating cells molecular profiles with cellular neighborhood and tissue image information.

bioinformatics↗

bioRxiv2024

Epstein-Barr Virus Orchestrates Spatial Reorganization and Immunomodulation within the Classic Hodgkin Lymphoma Tumor Microenvironment

Classic Hodgkin Lymphoma (cHL) is a tumor composed of rare malignant Hodgkin and Reed-Sternberg (HRS) cells nested within a T-cell rich inflammatory immune infiltrate. cHL is associated with Epstein-Barr Virus (EBV) in 25% of cases. The specific contributions of EBV to the pathogenesis of cHL remain largely unknown, in part due to technical barriers in dissecting the tumor microenvironment (TME) in high detail. Herein, we applied multiplexed ion beam imaging (MIBI) spatial pro-teomics on 6 EBV-positive and 14 EBV-negative cHL samples. We identify key TME features that distinguish between EBV-positive and EBV-negative cHL, including the relative predominance of memory CD8 T cells and increased T-cell dysfunction as a function of spatial proximity to HRS cells. Building upon a larger multi-institutional cohort of 22 EBV-positive and 24 EBV-negative cHL samples, we orthogonally validated our findings through a spatial multi-omics approach, coupling whole transcriptome capture with antibody-defined cell types for tu-mor and T-cell populations within the cHL TME. We delineate contrasting transcriptomic immunological signatures between EBV-positive and EBV-negative cases that differently impact HRS cell proliferation, tumor-immune interactions, and mecha-nisms of T-cell dysregulation and dysfunction. Our multi-modal framework enabled a comprehensive dissection of EBV-linked reorganization and immune evasion within the cHL TME, and highlighted the need to elucidate the cellular and molecular fac-tors of virus-associated tumors, with potential for targeted therapeutic strategies.

cancer biology↗

bioRxiv2024

A Spatial Multi-Modal Dissection of Host-Microbiome Interactions within the Colitis Tissue Microenvironment

The intricate and dynamic interactions between the host immune system and its microbiome constituents undergo dynamic shifts in response to perturbations to the intestinal tissue environment. Our ability to study these events on the systems level is significantly limited by in situ approaches capable of generating simultaneous insights from both host and microbial communities. Here, we introduce Microbiome Cartography (MicroCart), a framework for simultaneous in situ probing of host features and its microbiome across multiple spatial modalities. We demonstrate MicroCart by comprehensively investigating the alterations in both gut host and microbiome components in a murine model of colitis by coupling MicroCart with spatial proteomics, transcriptomics, and glycomics platforms. Our findings reveal a global but systematic transformation in tissue immune responses, encompassing tissue-level remodeling in response to host immune and epithelial cell state perturbations, and bacterial population shifts, localized inflammatory responses, and metabolic process alterations during colitis. MicroCart enables a deep investigation of the intricate interplay between the host tissue and its microbiome with spatial multiomics.

immunology↗

bioRxiv2023

Emergence of a senescent and inflammatory pulmonary CD4+ T cell population prior to lung allograft failure

Lung transplantation is a life-saving therapy for end-stage pulmonary disease, but its long-term outlook is poor due to a high incidence of chronic lung allograft dysfunction (CLAD). CLAD results from alloimmune-mediated progressive fibrosis and culminates in death or the need for re-transplantation after a median of 6 years. Existing immunosuppression fails to prevent CLAD, suggesting the existence of alloimmune pathways resistant to these drugs. Here, we used mass cytometry to identify cell populations enriched in the bronchoalveolar lavage (BAL) of patients with subsequent allograft dysfunction. We show that CD4+CD57+PD1+ T cells emerge in stable lung transplant recipients in the first year post-transplant, conferring heightened risks for CLAD and death or re-transplantation. CD4+CD57+PD1+ T cells display features of senescence and secrete inflammatory cytokines. Cellular indexing by transcriptomes and epitopes (CITE-Seq) on BAL CD4+ T cells revealed the existence of 2 oligoclonal CD57+ subsets with putative cytotoxic and follicular helper functions. Finally, we observed that CD4+CD57+PD1+ T cells are associated with lung allograft fibrosis in a mouse model and in human explanted CLAD lungs, where they localize near airway epithelium and B cells. Together, our findings reveal the existence of an inflammatory T cell population that predicts future lung allograft dysfunction and may represent a rational therapeutic target in lung transplant recipients.

immunology↗

bioRxiv2023

Msx genes delineate a novel molecular map of the developing cerebellar neuroepithelium.

In the early cerebellar primordium, there are two progenitor zones, the ventricular zone (VZ) residing atop the IVth ventricle and the rhombic lip (RL) at the lateral edges of the developing cerebellum. These zones give rise to the several cell types that form the GABAergic and glutamatergic populations of the adult cerebellum, respectively. Recently, an understanding of the molecular compartmentation of these zones has emerged. The Msx genes are a family of three transcription factors that are expressed downstream of Bone Morphogenetic Protein (BMP) signaling in these zones. Using fluorescent RNA in situ hybridization, we have characterized the Msx (Msh Homeobox) genes and demonstrated that their spatiotemporal pattern segregates specific regions in the progenitor regions. Msx1 and Msx2 are compartmentalized within the rhombic lip (RL), while Msx3 is localized within the ventricular zone (VZ). The relationship of the Msx genes with an early marker of the glutamatergic lineage, Atoh1, was examined in Atoh1-null mice and it was found that the expression of Msx genes persisted. Importantly, Msx1 and Msx3 expressions expanded in response to the elimination of Atoh1. These results point to early markers of cerebellar progenitor zones and more importantly to an updated view of the molecular parcellation of the RL with respect to the canonical marker of the RL, Atoh1.

developmental biology↗

bioRxiv2023

MAPS: Pathologist-level cell type annotation from tissue images through machine learning

Highly multiplexed protein imaging is emerging as a potent technique for analyzing protein distribution within cells and tissues in their native context. However, existing cell annotation methods utilizing high-plex spatial proteomics data are resource intensive and necessitate iterative expert input, thereby constraining their scalability and practicality for extensive datasets. We introduce MAPS (Machine learning for Analysis of Proteomics in Spatial biology), a machine learning approach facilitating rapid and precise cell type identification with human-level accuracy from spatial proteomics data. Validated on multiple in-house and publicly available MIBI and CODEX datasets, MAPS outperforms current annotation techniques in terms of speed and accuracy, achieving pathologist-level precision even for challenging cell types, including tumor cells of immune origin. By democratizing rapidly deployable and scalable machine learning annotation, MAPS holds significant potential to expedite advances in tissue biology and disease comprehension.

cancer biology↗