Biology subjects

Feng, F.

Publications and source records attributed to Feng, F..

At least 19 recordsLinked to original sources

bioRxiv2026

mBACS enhances pseudouridine profiling through efficient and robust chemical conversion

Pseudouridine ({Psi}) is the most abundant RNA modification and regulates RNA stability, splicing, and translation. Utilizing the dual nucleophilic N1 and O2 of {Psi}, we previously developed 2-bromoacrylamide-assisted cyclization sequencing (BACS) for quantitative, single-base {Psi} detection. Here, we screened new dual electrophiles and developed methyl 2-bromoacrylate-assisted cyclization sequencing (mBACS), which achieves higher {Psi} conversion efficiency and lower false-positive rates, enabling more sensitive and robust {Psi} detection. The enhanced sensitivity of mBACS uncovered new {Psi} sites in human tRNAs. mBACS further revealed TRUB1 and PUS10 as the exclusive redundant writers of the conserved tRNA {Psi}55 modification and uncovered crosstalk between {Psi}55 and other tRNA modifications. It also revealed 5-fluorouracil as a pan-pseudouridine synthase inhibitor that induces widespread but site-specific pseudouridylation remodelling. Finally, mBACS supported robust {Psi} profiling from as little as 10 ng of total RNA, establishing it as a sensitive, quantitative, and low-input second-generation platform.

biochemistry↗

bioRxiv2026

The Human Pancreas Cell Atlas defines a healthy reference framework for disease contextualization and translational benchmarking

A central challenge in single-cell biology is distinguishing disease-associated remodeling from normal cellular heterogeneity. Addressing this challenge requires healthy reference frameworks that capture cellular diversity across individuals, technologies, and biological contexts. Here we present the Human Pancreas Cell Atlas (HPCA), a reference atlas of the healthy human pancreas integrating 815,126 single-cell and single-nucleus transcriptomes from 109 donors across 12 studies, diverse technologies, and demographics. Using benchmarked integration and community-driven annotations, HPCA defines 94 cell types and transcriptional states spanning endocrine, exocrine, immune, and stromal compartments. The atlas identifies rare endocrine populations, including a putative, spatially supported polyhormonal alpha-beta-delta state, and provides a unified framework for interpreting pancreatic cellular variation across diverse biological and demographic covariates. Projection of disease and model-system datasets onto HPCA contextualized endocrine and epithelial remodeling relative to healthy pancreatic states. Diabetes-associated endocrine cells remained embedded within the healthy endocrine state space while exhibiting disease-specific changes, as supported by spatial and eQTL concordance analyses. Integration with a pancreatic ductal adenocarcinoma atlas resolved injury-associated and malignant epithelial ecosystem regions across donors. Finally, the HPCA enables quantitative benchmarking of murine diabetes models and stem-cell-derived islets against human pancreatic reference states. Together, the HPCA establishes a healthy transcriptional coordinate system for interpreting disease-associated pathophysiology, experimental perturbation, and regenerative fidelity, illustrating how reference atlases can function as analytical frameworks rather than static cell catalogs.

bioinformatics↗

bioRxiv2026

PanKbase Integrated Single-Cell Map: A Comprehensive Atlas of Human Pancreatic Islets

Single-cell RNA sequencing (scRNA-seq) of human pancreatic islet tissue is a powerful tool for investigating type 1 diabetes (T1D). However, individual datasets are limited in size and fragmented across donors, laboratories, and experimental conditions. To address this, we constructed a comprehensive, integrated scRNA-seq atlas of isolated human pancreatic islets by collating publicly available data generated from tissue provided by resources including the Human Pancreas Analysis Program, the Integrated Islet Distribution Program, and Prodo Labs. Systematic quality controls were implemented to select high-quality samples, reads, and cells. During integration, we accounted for important variables such as age, sex, body mass index, origin study, treatments, islet distribution resources, and sequencing chemistry. Our single-cell atlas comprises 191 high-quality samples from 140 donors (59 female, 81 male) across five phenotypic groups: no diabetes (controls, n=69), autoantibody positivity without diabetes (n=12), pre-diabetes (n=11), T1D (n=12), and type 2 diabetes (T2D) (n=36). In total, the atlas contains 448,935 cells, capturing 13 distinct populations, including alpha cells (43.3%) and beta cells (26.8%), as well as groups such as immune cells (0.6%). Publicly available at www.pankbase.org, this atlas provides a platform for hypothesis-driven investigation of diabetes pathophysiology and, given rigorous quality control, is well-suited for downstream machine-learning applications. Article HighlightsO_LICurrent scRNA-seq datasets of pancreatic islet tissue are limited in size and scattered across donors, laboratories, and experimental conditions, underscoring the need for a consolidated resource. C_LIO_LIWe harmonized datasets from multiple sources to build a comprehensive single-cell map of isolated human pancreatic islets. C_LIO_LIOur atlas captures 448,935 cells from 191 high-quality samples across 140 donors and multiple phenotypic groups, identifying 13 distinct cell populations. C_LIO_LIAvailable at www.pankbase.org, the atlas provides a scalable, rigorously curated platform to support hypothesis-driven diabetes research and can enable a broad range of downstream computational applications. C_LI

genomics↗

bioRxiv2026

Extending structural surfaceomics to identify aberrant conformations of tumor surface proteins as potential immunotherapy targets

The complement of tumor cell surface proteins, or "surfaceome", is a rich source of potential immunotherapy targets. To move beyond expression-based target discovery, we previously described "structural surfaceomics," combining crosslinking mass spectrometry (XL-MS) with surface protein biotinylation to identify conformation-selective targets. In our prior work, we applied this method to a single model of acute myeloid leukemia (AML), identifying active integrin beta-2 as a promising target. Here, we expand structural surfaceomics to identify additional immunotherapy targets and surface protein biology across additional models of AML, multiple myeloma, and prostate cancer, as well as donor peripheral blood mononuclear cells. Utilizing these models and different chemical crosslinkers, we compile an extensive database of 5,209 crosslinks. We characterize both shared and unique crosslink-based features, identifying 1,612 disease model-specific crosslinks, including 212 potentially defining tumor-specific conformations based on distance constraint violations relative to AlphaFold predictions. We further implement a suite of emerging modeling tools to predict tumor-specific protein structures. We probe crosslinking patterns suggesting multiple myeloma-specific CD48 and AML-specific integrin 1/{beta}4 heterodimer conformations. This work establishes a resource for cancer structural biology by implementation of structural surfaceomics. Our findings also point toward more realistic protein design models, potentially enabling systematic detection of targetable cancer-specific epitopes for next-generation immunotherapies.

cancer biology↗

bioRxiv2025

Benchmarking TCR-pMHC structure prediction: a unified evaluation and CDR3-based functional insights

Interactions between T cell receptors (TCRs) and peptide-major histocompatibility complexes (pMHCs) are central to adaptive immunity. Recent advances in structure prediction tools have enabled atomic-level modeling of TCR-pMHC interactions. However, the lack of systematic evaluation forces practitioners to invest substantial resources in selecting appropriate tools. Here, we present a comprehensive benchmark of TCR-pMHC structure prediction with 70 previously unseen complexes and ten models spanning MSA-based, PLM-based, and docking-based approaches, revealing the superior modeling accuracy and docking quality of MSA-based methods, especially AlphaFold3. To further enhance the utility of AlphaFold3 predictions, we identify the pLDDT score of the TCR CDR3 region as an informative indicator of both structural correctness and functional relevance. Specifically, it enables up to 4.3% Top-1 success gain through reranking and captures mutation-induced affinity changes in over 80% of cases. Overall, our analysis would facilitate the practical usage of immune structure prediction models and guide the advancement of these models.

bioinformatics↗

bioRxiv2025

Development of Long-Term Human Adipocyte Organoids Manifesting Aging in Response to Intermittent Hypoxia

Obstructive sleep apnea (OSA) (and consequent intermittent hypoxia (IH)) is increasingly recognized as a driver of adipose tissue dysfunction, insulin resistance, and aging. However, current in vitro experimental models inadequately capture the long-term effects of IH on human adipocytes. Here, we report the development and optimization of a robust long-term human adipocyte organoid culture system that faithfully recapitulates IH-induced adipocyte aging in vitro. Human stromal vascular fraction (SVF) cells, isolated from subcutaneous abdominal fat biopsies, were embedded in Matrigel and seeded into Biofloat U-bottom 96-well plates. Using a 1:1 Matrigel-cell mixture and optimized seeding volumes (5-20 {micro}L), we established adipocyte organoids that formed within 10-12 days and remained viable with stable morphology for up to 90 days or more. Matrigel was essential for organoid integrity, while alternative matrices such as gelatin and low-melting agarose failed to support proper organoid formation. Subcutaneous preadipocyte medium with 10% FBS from ZenBio was superior to "Advanced/F12K" medium for adipogenic differentiation and long-term maintenance. To model OSA-related hypoxic stress, we exposed organoids to intermittent hypoxia using a programmable hypoxia chamber. IH treatment suppressed adipogenesis, as shown by reduced lipid accumulation, downregulation of adipogenic markers (e.g., PPAR{gamma}, adiponectin, FABP4), and smaller intracellular lipid droplets. Transmission electron microscopy (TEM) revealed IH-induced structural abnormalities, including ER fragmentation, mitochondrial disruption, nuclear enlargement, and heterochromatin formation, all of which are hallmarks of cellular aging. Furthermore, IH upregulated HIF1, H2AX, and aging-associated histone methylation markers (H3K9me3, H3K79me3, H4K20me3), as well as extracellular matrix remodeling proteins such as fibronectin and LOX. Insulin signaling was also impaired, evidenced by decreased phosphorylation of PI3K and AKT. Collectively, these results establish a reliable platform for long-term human adipocyte organoid culture and demonstrate its utility in modeling IH-induced adipocyte dysfunction and aging. This system offers a physiologically relevant tool for mechanistic studies and preclinical therapeutic screening targeting hypoxia-related metabolic disorders.

cell biology↗

bioRxiv2025

Pan-cancer 3D genomic analysis revealed extremely long Polycomb loops as the biomarker for sensitivity to Polycomb inhibition

Polycomb targeted loci form long-range chromatin interactions independent of CTCF-cohesion and are demarcated by low DNA methylation(1-3). Polycomb targets form extremely long-range loops (long Polycomb loops) that can separate anchors up to 60 Mb. These loops predominantly occur in cells of self-renewal status, such as human hematopoietic stem cells (HSC) and mouse embryonic stem cells (ESC), but rarely in cell lines. To identify long Polycomb loops in cancer, we initiated a pan-cancer survey of long Polycomb loops in a collection of 264 tumor samples (33 acute myeloid leukemias, 17 T cell lymphoblastic leukemia, 29 Breast cancer samples, 63 pediatric brain tumors, 70 prostate cancers, and 42 colon cancers). We found most cancers, including all prostate cancers and colon cancers, lack long Polycomb loops except pediatric brain tumors and certain AMLs. In pediatric brain tumors, we found 30% of the ependymoma PFA subtype (which shows globally depleted H3K27me3) notably displayed strong long Polycomb loop interactions. AML displayed more diverse levels of long Polycomb loop interactions. Most AMLs lost both long Polycomb loops with Polycomb binding loss at the loop anchors. Whereas 10% of AMLs retain long Polycomb loops as strong as in HSCs. These AMLs recurrently carry mutations in CEBPA and STAG2, which are not associated with the Polycomb complex or DNA methylation machinery. We found that long Polycomb loop strong AML is sensitive to EZH2 inhibition, which induces cell differentiation. Conversely, PRC1 component dependency can be used to predict long Polycomb loop formation in B-cell lymphoblastic leukemia cell lines. Our analysis suggests that the oncogenesis process antagonizes the long Polycomb loop maintenance in most cancers, yet certain cancers may still preserve strong long Polycomb loops from cell-of-origin. The maintenance of long Polycomb loops sensitizes cells to Polycomb inhibition, indicating that such loops could be an epigenomic biomarker for pharmacological or genetic Polycomb inhibition.

cancer biology↗

bioRxiv2025

UHRF1 restricts HCoV-229E infection through epigenetic silencing of the viral receptor APN

The emergence of SARS-CoV-2 has posed significant threats to global health, particularly for the older population. Similarly, common human coronaviruses, such as HCoV-229E, which typically cause mild cold-like symptoms, have also been linked to severe diseases, underscoring the need to understand virus-host interactions and identify host factors contributing to viral pathogenesis and disease progression. In this study, we performed a genome-wide CRISPR knockout screen using HCoV-229E and identified Ubiquitin-like with PHD and RING finger domain 1 (UHRF1) as a potent restriction factor. Mechanistically, UHRF1 suppressed HCoV-229E infection by downregulating the expression of its cell entry receptor, aminopeptidase N (APN), through promoter hypermethylation. Focused CRISPR activation screens of UHRF1-downregulated genes confirmed the critical role of APN in HCoV-229E infection and identified additional genes (e.g., SIGLEC1, PLAC8, and heparan sulfate biosynthesis genes) contributing to the restrictive functions of UHRF1. Transcriptomic and single-cell RNA sequencing analysis revealed that UHRF1 expression decreases with age, negatively correlating with increased APN expression. This age-related decline in UHRF1 was further validated in primary alveolar macrophages isolated from elderly individuals, which exhibited heightened susceptibility to HCoV-229E infection compared to those from younger individuals. Our findings highlight UHRF1 as a key age-related host defense factor against coronavirus infection and provide novel insights into the epigenetic regulation of viral entry receptors.

microbiology↗

bioRxiv2025

Genetic and Epigenetic Reprogramming of Transposable Elements Drives ecDNA-Mediated Metastatic Prostate Cancer

Extrachromosomal DNAs (ecDNAs), which replicate and segregate in a non-Mendelian manner, serve as vectors for accelerated tumor evolution. By integrating chromatin accessibility, whole-genome sequencing, and Hi-C-based genome topology data from a cohort of metastatic Castration-Resistant Prostate Cancer (mCRPC) cases, we show that epigenetically activated repeat DNA, amplified in ecDNAs, drive oncogene overexpression. Specifically, we identify a subgroup of mCRPCs (20%) characterized by clusters of accessible LINE1 repeat DNA elements flanking the androgen receptor (AR) gene. These LINE1 elements are co-amplified with AR and provide binding sites for prostate-lineage transcription factors, including AR, FOXA1 and HOXB13. Accessible LINE1 elements establish novel 3D chromatin interactions with the AR gene, forging a new regulatory plexus driving AR overexpression and confers resistance to androgen signaling inhibitors. Our findings indicate how tumor evolution is driven by the convergence of genetic and epigenetic alterations on repeat DNA, activating and amplifying them to allow oncogene overexpression. Statement of significanceWe show how tumor evolution is driven by the convergence of genetic and epigenetic alterations on repeat DNA elements, resulting in their activation as regulatory elements and co-amplification in ecDNAs with oncogenes in mCRPC.

cancer biology↗

bioRxiv2025

Structural assembly of maize CRY-GL2 photosignaling complex provides insights into its regulatory role in cuticular wax biosynthesis

Cryptochromes (CRYs) are blue-light photoreceptors in plants that regulate diverse physiological processes through oligomerization-dependent interactions with downstream effectors. While numerous light-inducible CRY-binding proteins have been identified, the structural basis for photoactivated CRY-effector assembly remains poorly understood. Here we report the crystal structure of a constitutively active maize CRY1c photolyase homology region (ZmCRY1c-PHRW368A) in complex with ZmGL2, a BAHD ptotein directing very-long-chain fatty acid (VLCFA) elongation for cuticular wax biosynthesis. Structural analysis reveals that light-activated ZmCRY1c forms a homotetrameric scaffold generating four symmetric binding sites at subunit interfaces. Each ZmCRY1c protomer engages one ZmGL2 molecule through conformational reorganization of its 16-17 loop and 17 helix, establishing a 4:4 hetero-octameric photosignaling complex validated by mutational profiling and optical design. Remarkably, structural alignment with the ZmCER6-ZmGL2 complex reveals substantial overlap (78%) in ZmGL2 binding interfaces. Biochemical quantification demonstrates that ZmCRY1c suppresses ZmCER6-GL2 enzyme activity in a dose dependent manner, unveiling a light-dependent regulatory switch controlling VLCFA elongation efficiency, though in vivo physiological investigation is awaited. Collectively, our work not only establishes the atomic model of light-activated plant CRY-effector assembly, but also uncovers a previously unrecognized spatial competition between photoreceptor and metabolic enzyme complexes that might function as a photoregulatory paradigm in cuticular wax biosynthesis.

plant biology↗

bioRxiv2025

ZmCRY1s interact with GL2 in a blue light dependent manner to regulate epidermal wax composition in Zea mays

Cryptochromes (CRYs) are photolyase-like blue-light / ultraviolet-A (UV-A) receptors that regulate diverse aspects of plant growth. Maize (Zea mays), a major crop often grown under high UV-B radiation, possesses four copies of CRY. However, it remains unclear whether the multiple copies of CRY in maize have evolved to improve UV tolerance or to acquire new functions. In this study, CRISPR-Cas9-engineered Zmcry mutants were used to investigate the functions of four cryptochromes (ZmCRYs) in maize. The findings revealed that ZmCRYs play a redundant role in mediating blue light signaling and in inhibiting the elongation of the mesocotyl. The results also demonstrated that ZmCRYs mediated blue light-enhanced UV-B stress tolerance in Zea mays by upregulating the expression of genes involved in UV-B stress tolerance-related metabolites such as phenylpropanoid, flavonoid, and fatty acid biosynthesis. Furthermore, blue light was found to influence both the accumulation and composition of epidermal waxes, suggesting that blue light enhances epidermal wax accumulation for UV-B stress tolerance. Additionally, it was discovered that ZmCRY1 directly interacted with GLOSSY2 (GL2) in a blue light dependent manner to mediate blue light promoted C32 aldehyde accumulation, shedding new light on the enigma of aldehyde-forming. These results highlight the critical roles of ZmCRY1s in mediating blue light regulated epidermal wax biosynthesis and UV-B tolerance in Zea mays.

plant biology↗

bioRxiv2025

GENERanno: A Genomic Foundation Model for Metagenomic Annotation

The rapid growth of genomic and metagenomic data has underscored the pressing need for advanced computational tools capable of deciphering complex biological sequences. In this study, we introduce Generanno, a compact yet powerful genomic foundation model (GFM) specifically optimized for metagenomic annotation. Trained on an extensive dataset comprising 715 billion base pairs (bp) of prokaryotic DNA, Generanno employs a transformer encoder architecture with 500 million parameters, enabling bidirectional attention over sequences up to 8192 bp at single-nucleotide resolution. This design addresses key limitations of existing methods, including the inability of traditional Hidden Markov Models (HMMs) to handle fragmented DNA sequences from multi-species microbial communities, as well as the suboptimal tokenization schemes of existing GFMs that compromise fine-grained analysis. At its core, Generanno excels in identifying coding regions from fragmented and mixed DNA sequences--a hallmark of metagenomic analysis. It achieves superior accuracy compared to traditional HMM-based methods (e.g., GLIMMER3, GeneMarkS2, Prodigal) and recent LLM-based approaches (e.g., GeneLM), while demonstrating robust generalization ability on archaeal genomes. Leveraging its advanced contextual understanding capability, Generanno further enables two essential functions: pseudogene prediction and taxonomic classification--both performed based solely on raw sequence data, without reliance on reference databases or comparative genomics. These functionalities collectively streamline the metagenomic analysis pipeline, significantly reducing preprocessing requirements and enabling end-to-end interpretation of sequencing data. Beyond its primary role in metagenomic annotation, Generanno also serves as a powerful GFM. To evaluate its broader utility, we curated the Prokaryotic Gener Tasks--a comprehensive benchmark suite specifically tailored for prokaryotic genomic analysis. It includes gene fitness prediction, antibiotic resistance identification, gene classification, and taxonomic classification, reflecting diverse aspects of functional genomics. On this benchmark, Generanno consistently outperforms existing GFMs such as DNABERT-2, NT-v2, and GenomeOcean, demonstrating strong generalization capabilities across a wide range of genomic tasks. Overall, Generanno provides a unified framework that integrates multiple critical functions for metagenomic annotation and beyond. By eliminating dependencies on external resources and offering rich contextual understanding of genomic sequences, this work delivers a foundational tool for advancing functional genomics in complex microbial communities. Implementation details and supplementary resources are available at https://github.com/GenerTeam/GENERanno.

genomics↗

bioRxiv2025

Identification and Characterization of PLUTO-201, a Novel Long Non-Coding RNA Associated with Poor Outcomes in Prostate Cancer

Background: Despite extensive investigation, the factors promoting aggressive prostate cancer are poorly understood. In particular, despite a few prominent examples, the role of long non-coding RNAs (lncRNAs) is largely unknown. Methods: We performed a comprehensive analysis of whole-genome transcriptome data to identify differential expression across 1,567 patients with prostate cancer, then correlated differential expression with risk of metastatic recurrence. We characterized the lncRNA most associated with metastasis in vitro and in vivo to investigate the mechanism by which it promotes aggressive prostate cancer. Results: We have identified a novel lncRNA, Prostate Cancer Associated hnRNPK Interacting Transcript (PCAHIT), which is strongly associated with metastasis and poor overall survival in men with prostate cancer. We find that overexpression/knockdown of PCAHIT in pre-clinical models of prostate cancer modulates proliferation rates and markers of an aggressive phenotype through regulation of steroid biosynthesis and expression of the MHC class I complex, driving increased growth in androgen-depleted conditions and decreased susceptibility to T cell-mediated cytotoxicity. We further find that the heterogeneous nuclear ribonucleoprotein hnRNPK directly binds PCAHIT and is indispensable for its activity. Conclusions: Overall, our findings indicate that PCAHIT is a driver of aggressive prostate cancer phenotypes and poor clinical outcomes through suppression of the immune response and increased androgen-independent cancer growth. PCAHIT is a potential biomarker of aggressive disease.

cancer biology↗

bioRxiv2025

Genome structure mapping with high-resolution 3D genomics and deep learning

Gene expression is often regulated by distal enhancers through cell-type-specific 3D looping interactions, but compre-hensive mapping of these interactions across cell types is experimentally intractable. To address this gap, we introduce an integrated approach where we generate ultra-deep Region Capture Micro-C (RCMC) and Micro-C data specifically designed for state-of-the-art deep learning architectures. We developed Cleopatra, an attention-based deep learning model that takes epigenomic inputs and is pre-trained on genome-wide Micro-C data followed by fine-tuning with high-resolution RCMC data. Cleopatra accurately predicts 3D maps at sub-kilobase bin sizes and unprecedented resolution, enabling us to generate ultra-high-resolution, genome-wide 3D contact maps across four human cell types. These maps revealed cell-type-specific microcompartments and over 900,000 loops across the cell types, about half of which are cell-type-specific. Using Cleopatra maps, we observe that promoters form about a dozen loops on average, and that expression increases monotonically with the number of loops, indicating that looping is associated with higher gene expression. We further show the enhancer-promoter loops are often anchored by CTCF, and nominate new transcription factors that may regulate cell-type-specific enhancer-promoter interactions. Overall, we establish a framework for ultra-high-resolution 3D genome mapping, providing a broadly applicable resource for gaining new insights into cell-type-specific gene regulation.

genomics↗

bioRxiv2025

Glycosylphosphatidylinositol biosynthesis restricts coronavirus infection via the regulation of LY6E

Coronaviruses, including SARS-CoV-2, rely on host factors for their replication and pathogenesis, while hosts deploy defense mechanisms to counteract viral infections. Although numerous host proviral factors have been identified, the landscape of host restriction factors and their underlying mechanisms remain less explored. Here, we conducted genome-wide CRISPR knockout screens using three distinct coronaviruses--SARS-CoV-2, HCoV-OC43 (a common cold human virus from the genus Betacoronavirus) and porcine epidemic diarrhea virus (Alphacoronavirus) to identify conserved host restriction factors. We identified glycosylphosphatidylinositol (GPI) biosynthesis as the pan-coronavirus host factor that restrict viral entry by disrupting spike protein-mediated membrane fusion at both endosomal and plasma membranes. GPI biosynthesis generates GPI moieties that covalently anchor proteins (GPI-anchored proteins [GPI-APs]) to the cell membrane, playing essential roles in various cellular processes. Through focused CRISPR knockout screens targeting 193 GPI-APs, we identified LY6E as the key downstream effector mediating the antiviral activity of the GPI biosynthesis pathway. These findings reveal a novel role for GPI biosynthesis as a conserved host defense mechanism against coronaviruses and highlight LY6E as a critical antiviral effector. This study provides new insights into virus-host interactions and the development of host-directed antiviral therapies.

microbiology↗

bioRxiv2025

DAZAP2 functions as a pan-coronavirus restriction factor by inhibiting viral entry and genomic replication

The SARS-CoV-2 pandemic and the emergence of novel variants underscore the need to understand host-virus interactions and identify host factors that restrict viral infection. Here, we perform a genome-wide CRISPR knockout screen to identify host restriction factors for SARS-CoV-2, revealing DAZAP2 as a potent antiviral gene. DAZAP2, previously implicated in SARS-CoV-2 restriction, is found to inhibit viral entry by blocking virion fusion with both endolysosomal and plasma membranes. Additionally, DAZAP2 suppresses genomic RNA replication without affecting the primary translation of viral replicases. We demonstrate that DAZAP2 functions as a pan-coronavirus restriction factor across four genera of coronaviruses. Importantly, knockout of DAZAP2 enhances SARS-CoV-2 infection in mouse models and in human primary airway epithelial cells, confirming its physiological relevance. Mechanistically, antiviral activity of DAZAP2 appears to be indirect, potentially through the regulation of host gene expression, as it primarily localizes to the nucleus. Our findings provide new insights into the host defense system against coronaviruses and highlight DAZAP2 as a potential target for host-directed antiviral therapies. IMPORTANCEDuring viral infection, the host defense response is mediated by a variety of host factors through distinct mechanisms that have yet to be fully elucidated. Although DAZAP2 was previously implicated in SARS-CoV-2 restriction, its mechanisms of action and in vivo relevance remain unclear. In this study, we identify the DAZAP2 as a potent pan-coronavirus restriction factor that inhibits viral infection through dual mechanisms: blocking virion fusion with both endolysosomal and plasma membranes, and suppressing genomic RNA replication. We confirm its physiological relevance in host defense using mouse models and primary cell cultures. This study advances our understanding of host-pathogen interactions. Targeting DAZAP2 or its regulatory pathways could provide a new approach to enhance host defense against current and future coronavirus threats.

microbiology↗

bioRxiv2025

The single amino acid change of R516K enables efficient generation of vesicular stomatitis virus-based Crimean-Congo hemorrhagic fever reporter virus

Crimean-Congo hemorrhagic fever virus (CCHFV) is a medically important tick-borne virus, causing severe hemorrhagic diseases in humans. There is no approved vaccines and therapeutics for CCHFV infection. The study of CCHFV authentic virus requires biosafety level 3 facilities, hindering the research and development of antivirals. Here we report the generation of a recombinant vesicular stomatitis virus (VSV) bearing both CCHFV glycoprotein precursor (GPC) and EGFP reporter (rVSV-CCHFV-GFP). We also find that the acquisition of an unexpected single R516K mutation in the GPC protein enables the packaging of high-titer pseudotyped particles. The replication-competent rVSV-CCHFV-GFP reporter virus resembles the entry properties of authentic virus and allows for rapid assessment of susceptible cell lines, neutralizing antibodies, and host entry factors such as heparan sulfate in fluorescence-based assays. This study provides valuable strategy for packaging of high-titer CCHFV pseudovirus, and the tool generated here can be served for the identification and evaluation of countermeasures against the cell entry of CCHFV.

microbiology↗

bioRxiv2024

Heterogeneous endocrine cell composition defines human islet functional phenotypes

Phenotyping and genotyping initiatives within the Integrated Islet Distribution Program (IIDP), the largest source of human islets for research in the U.S., provide standardized assessment of islet preparations distributed to researchers, enabling the integration of multiple data types. Data from islets of the first 299 organ donors without diabetes, analyzed using this pipeline, highlights substantial heterogeneity in islet cell composition associated with hormone secretory traits, sex, reported race and ethnicity, genetically predicted ancestry, and genetic risk for type 2 diabetes (T2D). While and {beta} cell composition influenced insulin and glucagon secretory traits, the abundance of {delta} cells showed the strongest association with insulin secretion and was also associated with the genetic risk score (GRS) for T2D. These findings have important implications for understanding mechanisms underlying diabetes heterogeneity and islet dysfunction and may provide insight into strategies for personalized medicine and {beta} cell replacement therapy.

physiology↗