Biology subjects

Yeo, Y. Y.

Publications and source records attributed to Yeo, Y. Y..

11 recordsLinked to original sources

bioRxiv2026

A Human Genome-wide CRISPR-Cas9 Screen Reveals Host Factors That Support Epstein-Barr Virus B cell infection

Epstein-Barr virus (EBV) infects 90% of the population worldwide and is associated with multiple malignancies, including Burkitt, Hodgkin and post-transplant lymphomas, nasopharyngeal and gastric carcinoma. EBV also triggers autoimmune diseases, including multiple sclerosis and systemic lupus erythematosus. While host factors important for EBV B-cell entry have been defined, including CD21/CR2, MHC class II and R9AP, much remains to be learned about host factors that support post-entry steps of EBV infection. To gain insight, we conducted a human genome-wide CRISPR-Cas9 screen. In addition to known EBV B cell receptors/co-receptors, we identified multiple new factors and pathways essential for EBV B cell infection. These included multiple B cell signaling pathways, actin cytoskeleton and nuclear import factors. Knockout of CD19, its tetraspanin chaperone CD81 or karyopherin subunit alpha 1 (KPNA1, also called importin-5) significantly impaired establishment of EBV infection. EBV and CD19 co-localized at early stages of EBV infection, and the CD19 cytoplasmic tail was important for EBV infection, suggesting CD19 signaling supports EBV uptake. Depletion of KPNA1 significantly impaired establishment of EBV infection, but did not impair production of infectious EBV upon reactivation of latently infected B cells. Together, these results provide insights into pathways that support EBV B cell infection and identify potential therapeutic targets.

microbiology↗

bioRxiv2026

Coordinated immune-epithelial dynamics in the nasal epithelium protect against respiratory virus infection

Epithelial remodeling is a hallmark of host antiviral responses that strengthen barrier defenses against infection. Our current understanding of viral pathophysiology within the nasal epithelium, the initial site of most respiratory viral infections, remains incomplete due to limited understanding of the native tissue architecture and protective epithelial remodeling during immune events. Leveraging coronavirus disease 2019 (COVID-19) as a model, we applied spatial multi-omics on nasal cross-sectional tissues to characterize the immune-epithelial landscape during infection, identifying a coordinated increase in goblet cells and suppressive macrophages associated with elevated IL13 in the immune compartment. Our results further reveal that goblet cell and suppressive macrophage enrichment are spatially linked in proximity to IL13-expressing CD4 T cells, consistent with IL13-driven remodeling in situ. Using a primary human nasal air-liquid interface model, we demonstrate that IL13 alone is sufficient to remodel epithelial composition and morphology, subsequently restricting viral infection by reshaping the apical mucus barrier of the nasal epithelium. Our findings uncover a spatially organized, IL13-driven circuit for immune-epithelial remodeling as a protective barrier against respiratory viral infections.

immunology↗

bioRxiv2026

Single-Cell and Spatial Methods for Multimodal Functional Glycan Profiling in Tissues

Glycans regulate multiple physiological processes, including immune recognition and cancer progression. In disease, altered glycan landscapes are interpreted by human lectins. Functional glycan-lectin interactions are difficult to profile because glycans are not genome-encoded and their changes are poorly captured by existing multimodal methods. We present two platforms, single-cell outlining and transcriptome sequencing (scGOAT-seq) and GlycoScope, which use human lectins to enable functional glycan accessibility into single-cell and spatial multiomic measurements. ScGOAT-seq quantifies lectin-accessible glycan states with gene expression, while GlycoScope enables multiplexed in situ co-detection of glycans and proteins in tissues. Applying these approaches to immune cells, we identify stimulus-specific glycan remodeling and show that distinct Siglec-ligand-defined programs stratify immune activation states not captured by traditional methods; in follicular lymphoma, GlycoScope, resolves spatial glycan programs associated with malignant B cells and localized immune microenvironments. The presented methods provide a general framework for integrating functional glycan accessibility into single-cell and spatial multiomics.

molecular biology↗

bioRxiv2026

Spatial immune hubs defined by conserved activated dendritic cells are remodeled by immunotherapy

Dendritic cells (DCs) orchestrate anti-tumor immune responses, yet the full extent of their phenotypic diversity, and spatial dynamics within the tumor microenvironment (TME) remains incompletely understood. Here, we constructed an integrated atlas of tumor-infiltrating DCs by harmonizing single-cell transcriptomic data from 12 murine tumor studies and 28 published human cancer datasets, together with newly generated single-cell-resolved multiplexed tissue imaging across immunotherapy conditions in a murine model. We noted conserved transcriptional states across species, including canonical conventional type 1 DCs (cDC1s), diverse type 2 DC (cDC2) subpopulations, and two activation states characterized by CCR7 expression (CCR7+ DCs) or interferon-stimulated gene expression (ISG DCs). Spatial transcriptomics analyses from human TMEs revealed that CCR7+ DCs and ISG DCs reside in distinct T cell-enriched regions that are embedded within distinct signaling environments. High-dimensional multiplexed proteomic imaging demonstrated that these DC-T cell niches undergo divergent remodeling across multiple immunotherapy conditions. Notably, this spatial reorganization occurred despite minimal detectable changes in DC transcriptional states. This study delineates conserved DC activation states and their spatial organization within tumors and captures the therapy-dependent remodeling, providing a framework for studying therapy-associated remodeling of DC immune programs in cancer.

immunology↗

bioRxiv2025

PASTA: Versatile Tyramine-oligonucleotide Amplification for Multi-modal Spatial Biology

Spatial proteomics techniques have revolutionized our understanding of tissue architecture, but are frequently limited by detection sensitivity, bioconjugation limitations, multiplexing capacity, and multi-modal integration. Here we present Protein and nucleic Acid Serial Tyramine Amplification (PASTA), a novel signal amplification approach that significantly enhances detection sensitivity while maintaining compatibility with diverse spatial profiling methodologies. PASTA utilizes horseradish peroxidase (HRP) recruitment pathways to generate tyramine radicals that deposit oligonucleotides, enabling adaptable signal amplification across multiple biomarkers at high-plex via cyclical imaging using complementary fluorophore-labeled oligonucleotides. We demonstrate that PASTA achieves up to 100-fold signal enhancement for markers with minimal background in blank controls. The method is compatible with in situ hybridization for DNA/RNA detection, proximity ligation assays for protein-protein interactions, sequential antibody staining protocols, or any modular combination thereof. PASTA enables antibody rescue of markers with suboptimal signal-to-noise ratios and is versatile in its applications to unconjugated antibodies, and multi-round probe-based RNA detection systems beyond current capabilities. This technique addresses key limitations in spatial-omics by enhancing sensitivity for challenging targets while maintaining compatibility with established multiplexing strategies, providing a versatile, cost-efficient, and valuable tool for comprehensive spatial tissue analysis in both research and clinical applications.

molecular biology↗

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

SARS-CoV-2 Nsp15 antagonizes the cGAS-STING-mediated antiviral innate immune responses

Coronavirus (CoV) Nsp15 is a viral endoribonuclease (EndoU) with a preference for uridine residues. CoV Nsp15 is an innate immune antagonist which prevents dsRNA sensor recognition and stress granule formation by targeting viral and host RNAs. SARS-CoV-2 restricts and delays the host antiviral innate immune responses through multiple viral proteins, but the role of SARS-CoV-2 Nsp15 in innate immune evasion is not completely understood. Here, we generate an EndoU activity knockout rSARS-CoV-2Nsp15-H234A to elucidate the biological functions of Nsp15. Relative to wild-type rSARS-CoV-2, replication of rSARS-CoV-2Nsp15-H234A was significantly decreased in IFN-responsive A549-ACE2 cells but not in its STAT1 knockout counterpart. Transcriptomic analysis revealed upregulation of innate immune response genes in cells infected with rSARS-CoV-2Nsp15-H234A relative to wild-type virus, including cGAS-STING, cytosolic DNA sensors activated by both DNA and RNA viruses. Treatment with STING inhibitors H-151 and SN-011 rescued the attenuated phenotype of rSARS-CoV-2Nsp15-H234A. SARS-CoV-2 Nsp15 inhibited cGAS-STING-mediated IFN-{beta} promoter and NF-{kappa}B reporter activity, as well as facilitated the replication of EV-D68 and NDV by diminishing cGAS and STING expression and downstream innate immune responses. Notably, the decline in cGAS and STING was also apparent during SARS-CoV-2 infection. The EndoU activity was essential for SARS-CoV-2 Nsp15-mediated cGAS and STING downregulation, but not all HCoV Nsp15 share the consistent substrate selectivity. In the hamster model, rSARS-CoV-2Nsp15-H234A replicated to lower titers in the nasal turbinates and lungs and induced higher innate immune responses. Collectively, our findings exhibit that SARS-CoV-2 Nsp15 serves as a host innate immune antagonist by targeting host cGAS and STING. Significance statementHost innate immune system serves as the primary defense against pathogens, including SARS-CoV-2. Co-evolving with the hosts, viruses develop multiple approaches to escape the host surveillance. SARS-CoV-2 silences and dysregulates innate immune responses, and the chaos of antiviral IFN responses highly correlates to COVID-19 disease severity. Nsp15 is a conventional innate immune antagonist across coronaviruses, but the biological impact about SARS-CoV-2 Nsp15 is still unclear. Here, we provide a novel insight that SARS-CoV-2 Nsp15 hampers the expression of innate immune regulator - cGAS and STING via its endoribonuclease activity, then further ameliorates virus replication.

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

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↗