Biology subjects

Zhu, J.

Publications and source records attributed to Zhu, J..

At least 145 records · Page 8Linked to original sources

bioRxiv2025

Engineering Treg-mediated immune tolerance via foxp3a overexpression to evade allograft transplantation barriers in zebrafish

In mammals, regulatory T cells (Treg) cells have been utilized to enhance tolerance in organ transplantation. Although transplanting germline stem cells (GSCs) or gonadal primordia into immunodeficient zebrafish have shown to be an important technique which can bypass the juvenile phase and expedite gamete generation, it remains challenging to raise the immunodeficient fish. Here, we achieved in vivo induction of Tregs by overexpressing the key transcription factor Foxp3a, generating transgenic zebrafish with robust immune tolerance. This was characterized by a significant downregulation of T cell development and homing-related genes, accompanied by a marked upregulation of immunosuppressive factors. Using these immune-tolerant fish as hosts for subcutaneous gonadal primordium transplantation (SGPT) and intraperitoneal GSC transplantation (IGCT), we markedly accelerated germ cell maturation and efficiently established stable transgenic lines. Transcriptomic analyses demonstrated that transgenic hosts demonstrated a phenotypic profile characterized by delayed immune activation, attenuated responsiveness, and enhanced graft survival. Thus, we present a Treg-induction-based approach in fish that resolves the intrinsic conflict between high embryonic transgenesis efficiency and early lethality, while significantly improving overall transgenesis success rates. Moreover, it offers a practical alternative to immunodeficient recipients, avoiding the challenges of complex husbandry and compromised fertility.

genetics↗

bioRxiv2025

Pan-genome analyses of 226 finger millet-infecting Magnaporthe oryzae strains from eastern Africa reveal two lineages that differ in their genetic make-up, virulence and effector gene content with gene loss driven by homologous recombination between Pot2 elements

Blast disease, caused by the filamentous ascomycete Magnaporthe oryzae, is the main biotic constraint to finger millet production in eastern Africa. M. oryzae is a pathogen on many grass species, but the high host-specificity of blast isolates underscores the need to study pathogen diversity and virulence at the host level. Here, we fill a void on knowledge on finger millet-infecting strains of M. oryzae by sequencing 226 isolates pure-cultured from infected tissues, mainly peduncles and panicles, sampled from field-grown finger millet accessions across Ethiopia, Kenya, Tanzania and Uganda. Phylogenetic analysis showed that eastern African isolates are genetically distinct from Asian isolates, and differentiated into two groups potentially driven by climate variables. One group was dominated by isolates from Kenya and Uganda (KU group), and the other by isolates from Ethiopia and Tanzania (ET group). Analysis of the portfolio of 887 predicted effector genes showed that the KU group had significantly fewer effectors, concomitant with higher virulence levels on the two finger millet accessions tested. We demonstrate that homologous recombination between transposable elements, leading to genomic deletions, plays a key role in gene removal. Transcript profiling of fungal genes in compatible and incompatible interactions revealed upregulation in the incompatible interaction as a characteristic of an estimated 30% of effector genes, including seven of the eight homologs of known avirulence genes from rice-infecting M. oryzae identified in our study. Prioritization of these effectors for functional validation will pave the way for identifying cognate resistance genes and improving finger millet for resistance to blast disease.

plant biology↗

bioRxiv2025

Computer Vision Methods for Spatial Transcriptomics: A Survey

Spatial transcriptomics (ST) enables the simultaneous measurement of gene expression and spatial localization within tissue sections, providing unprecedented opportunities to dissect tissue architecture and functional organization. As a relatively new omics technology, bioinformatics has driven much of the innovation in ST. However, within these frameworks, "spatial" information is often reduced to locations and relationships between molecular profiles, without fully leveraging the wealth of submicron morphological detail and histological knowledge available. Advances in computer vision-based artificial intelligence (AI) are opening exciting new avenues beyond conventional bioinformatics approaches by modeling complex histological patterns and linking morphology to molecular states. More excitingly, they bring fresh perspectives to potentially address key limitations of ST, including its high cost, limited clinical applicability, and reliance on twodimensional (2D) analysis of inherently three-dimensional (3D) tissues. For instance, models that predict ST directly from histology images enable "virtual sequencing," drastically reducing costs while integrating morphological insights from pathology with molecular biomarkers, thus accelerating clinical translation. Moreover, computer vision techniques can reconstruct pixel-aligned 3D tissue models, overcoming the technical barriers of 2D acquisition and advancing 3D spatial omics analytics. In this paper, we present the first systematic survey of computer vision AI models for ST analytics, categorizing approaches across architectures, learning paradigms, tasks, and datasets, and tracing their technological evolution. We highlight key challenges and future directions, offering a panoramic perspective on vision-driven ST and its potential to transform both basic research and clinical practice. The curated collection of vision-driven spatial transcriptomics papers is available at https://github.com/hrlblab/computer_vision_spatial_omics.

bioinformatics↗

bioRxiv2025

Asynchronous firing and off-states in working memory maintenance

Persistent spiking activity and activity-silent mechanisms have been proposed as neural correlates of working memory. To determine their relative contribution, we recorded neural activity from the lateral prefrontal and posterior parietal cortex of two male macaques using high-density microelectrode probes. We found that, when averaged across all neurons, persistent delay activity was observable throughout the duration of single trials in populations of prefrontal neurons with silent periods that did not deviate significantly from chance. However, temporal fluctuations in activity-dependent mnemonic information were present and weakly correlated between the prefrontal and posterior parietal cortices, suggesting at least partial, long-distance synchronization of off-states. Decoding accuracy of neurons recorded simultaneously was also reduced relatively to pseudo-populations constructed by splicing different trials together. Our results support an asynchronous state of working memory, maintained by the distributed pattern of persistent discharges across cortical neurons, which is subject to widely distributed fluctuations in information representation fidelity.

neuroscience↗

bioRxiv2025

FlexRibbon: Joint Sequence and Structure Pretraining for Protein Modeling

AO_SCPLOWBSTRACTC_SCPLOWProtein foundation models have advanced rapidly, with most approaches falling into two dominant paradigms. Sequence-based language models (e.g., ESM-2) capture sequence semantics at scale, and a number of recent works incorporate structural signals into sequence encoders. MSA-based predictors (e.g., AlphaFold 2/3) achieve accurate folding by exploiting evolutionary couplings, but their reliance on homologous sequences makes them less reliable in highly mutated or alignment-sparse regimes. We present FlexRibbon{ddagger}, a pretrained protein model that jointly learns from amino acid sequences and three-dimensional structures. Our pretraining strategy combines masked language modeling with diffusion-based denoising, enabling bidirectional sequence-structure learning without requiring MSAs. Trained on both experimentally resolved structures and AlphaFold 2 predictions, FlexRibbon captures global folds as well as flexible conformations critical for biological function. Evaluated across diverse tasks spanning interface design, intermolecular interaction prediction, and protein function prediction, FlexRibbon establishes new state-of-the-art performance on 12 different tasks, with particularly strong gains in mutation-rich settings where MSA-based methods often struggle.

molecular biology↗

bioRxiv2025

Comprehensive gene heritability estimation reveals the genetic architecture of rare coding variants underlying complex traits

Whole-exome sequencing (WES) enables high-resolution interrogation of the contribution of rare coding variants to complex trait variation. However, existing methods for heritability estimation attributed to rare-coding variants are often limited by the effects of linkage disequilibrium (LD) and by the sparse nature of rare variant data. We introduce FLEX (Fast, LD-aware Estimation of eXome-wide and gene-level heritability), a scalable and flexible framework for estimating and partitioning heritability across genes or sets of genes using WES data. FLEX integrates all coding variants- from common to ultra-rare - within a unifled model and corrects for LD-induced effects to improve the accuracy of heritability estimates. In addition, FLEX supports both individual-level and summary statistic data and is computationally efflcient for biobank-scale datasets. Through extensive simulations, we show that FLEX is well-calibrated while providing accurate heritability estimates. We applied FLEX to WES data across N = 153, 351 unrelated European ancestry individuals and 20 quantitative traits in the UK Biobank. We identifled 64 gene-trait pairs with signiflcant gene-level heritability (p < 0.05/18, 624 accounting for the number of protein-coding genes tested), among which rare coding variants explained 38% of gene-level heritability, on average. Compared to heritability estimates from genome-wide imputed SNPs, incorporation of rare and ultra-rare coding variants led to a 24.8% increase in heritability on average, while effect sizes at rare and ultra-rare variants are substantially larger ({approx} 18x on average). Partitioning across variant effect annotations, we flnd that predicted loss-of-function variants had stronger individual effects than missense variants (24% on average) while missense variants accounted for a greater share of rare coding heritability. Together, FLEX provides an adaptable and accurate approach for quantifying gene-level heritability, advancing our understanding of the genetic architecture of complex traits, and facilitating the discovery of trait-relevant genes.

genetics↗

bioRxiv2025

De Novo Design of Anti-Aging Peptides

Aging, a universal biological process in complex organisms, is increasingly recognized to be driven by progressive loss of epigenetic information, as proposed in the Information Theory of Aging (ITOA). However, research on anti-aging peptides remains scarce, with most existing efforts confined to derivatives of natural proteins, while systematic design attempts are virtually absent. This limitation not only restricts discovery within the evolutionary sequence space but also hampers the identification of candidates with novel mechanisms and improved efficacy. Here, we present ElixirSeeker2, the first computational framework for de novo design of anti-aging peptides. By integrating modeling of known anti-aging peptides, activity scoring from the IC50 database, and penalty constraints from toxic peptides, ElixirSeeker2 enables large-scale virtual screening and identification of novel peptide candidates. Several lead peptides demonstrated significant effects in delaying cellular senescence, restoring cellular functions in vitro and in enhancing locomotor activity of aged Caenorhabditis elegans. This study not only validates the feasibility of de novo design in anti-aging interventions but also establishes a strategy for the development of next-generation biologics.

bioinformatics↗

bioRxiv2025

Differential contributions of an antimicrobial effector from Verticillium dahliae to virulence and tomato microbiota assembly across natural soils

Throughout their life cycle plants associate with diverse and complex microbial communities, known as their microbiota. These microbiota contribute to plant performance and health, in part by providing a microbial barrier against invading plant pathogens. To colonize plant hosts, pathogens not only have to overcome host immune responses, but also breach the microbial barrier, for which they secrete so-called effector proteins. Accordingly, the soil-borne fungal plant pathogen Verticillium dahliae secretes the antimicrobial effector Ave1 to suppress antagonistic microbes and facilitate host colonization. Notably, many pathogens, including V. dahliae, have life stages outside their host plants, for instance in soil, where they encounter diverse microbial communities. Yet, how antimicrobial effectors support establishment across these environments remains poorly understood. To address this, we established a collection of natural soil samples with diverse physicochemical properties and microbiota compositions. Using this collection, we show for three plant species, barley, tomato and cotton, that root-associated bacterial and fungal communities are primarily shaped by the type of soil, whereas the phyllosphere microbiota is mainly determined by plant species. On tomato, we furthermore show that Ave1 differentially contributes to virulence on diverse soils, as Ave1 altered the tomato microbiota on all soils tested, but the taxa affected by these shifts varied depending on the specific soils. Our findings suggest that while Ave1-mediated microbiota manipulation occurs across soils, its impact on fungal virulence is influenced by the specific composition of the soil-derived microbiota assembled by the host.

plant biology↗

bioRxiv2025

SpaceSequest: A unified pipeline for spatial transcriptomics data analysis

BackgroundSpatial transcriptomics has emerged as one of the most powerful tools for gaining biological insights, enabling researchers to uncover intricate relationships between gene expression patterns and tissue architecture. Recent advances in the field have resulted in a variety of new platforms, including Visium, Visium HD, and Xenium from 10x Genomics, as well as GeoMx and CosMx from NanoString Technologies, which has now been acquired by the Bruker Corporation. However, the existence of diverse spatial transcriptomics platforms and various data formats poses challenges in standardizing data analysis. Thus, there remains a critical gap in the availability of a comprehensive pipeline capable of conducting end-to-end analysis that is necessary to extract biological insights from multiple spatial transcriptomics platforms. ResultsHere, we present SpaceSequest, a tailored pipeline that utilizes cutting-edge computational methodologies to conduct a thorough analysis, enabling the extraction of crucial biological insights from five major spatial transcriptomics technologies. SpaceSequest performs (1) standardized quality control and general data processing, (2) key analyses customized for each spatial platform, (3) automated cell type annotation and deconvolution, and (4) high-quality figure and analysis result generation. In addition, SpaceSequest allows for smooth integration with cellxgene VIP and Quickomics for user-friendly data access and interactive visualization. ConclusionsSpaceSequest is a unified and comprehensive pipeline designed for the analysis, visualization, and publication of spatial transcriptomics data from various platforms. The source code is available at https://github.com/interactivereport/SpaceSequest. To facilitate seamless installation and usage, we have also created a detailed Bookdown tutorial that can be accessed through https://interactivereport.github.io/SpaceSequest/tutorial/docs/index.html.

bioinformatics↗

bioRxiv2025

Candida albicans infiltrates colon and rectal cancers causing therapeutic resistance and decreased survival

The microbiome is increasingly recognized as a modifier of cancer progression and therapy response, yet the role of intratumoral fungi remains poorly defined. Here, we identify Candida albicans colonization within human colorectal tumors as a predictor of reduced survival and impaired radiation response. Leveraging the Oncology Research Information Exchange Network (ORIEN) cohort, we show that high intratumoral Candida burden is associated with decreased survival across multiple gastrointestinal cancers, with the strongest treatment-specific effect in rectal cancer patients receiving radiotherapy. This observation was validated in independent rectal cancer cohorts using RNA sequencing and quantitative PCR. In immune-competent murine colorectal cancer models, oral gavage of C. albicans resulted in intratumoral colonization, accelerated tumor growth, and radiation resistance, effects not observed with Saccharomyces cerevisiae or PBS controls. Colonized tumors exhibited increased hypoxia, altered metabolic and transcriptional programs, and distinct expression of genes linked to cytokine signaling and cell survival. Hypoxia conditioned C. albicans secreted metabolites that directly conferred radiation resistance to colorectal cancer cells in vitro, implicating a cancer cell intrinsic mechanism independent of immune signaling. Untargeted metabolomics revealed enrichment of nucleosides and lipid oxidation intermediates under hypoxia, suggesting that C. albicans metabolites may provide substrates facilitating tumor recovery after irradiation. These findings establish C. albicans as a causal modifier of tumor biology and radiation response, highlighting intratumoral fungi as future potential therapeutic targets. Modulating fungal colonization or metabolism may improve radiotherapy outcomes and broaden our understanding of interactions between microbes and tumors.

cancer biology↗

bioRxiv2025

Integrative Systems Biology Identifies the AHR Signaling Axis as a Mechanistic Basis for Xiaobi Plaster in Lumbar Disc Degeneration

BackgroundLumbar disc degeneration (LDD) is characterized by chronic inflammation, oxidative stress, and extracellular matrix (ECM) breakdown, yet current therapies provide only symptomatic relief. Xiaobi Plaster (XBG), a traditional Chinese transdermal herbal preparation, has shown clinical benefit, but its molecular mechanisms remain unclear. MethodsWe applied an integrative systems biology framework combining network pharmacology, machine learning, and transcriptomic validation to identify candidate targets of Xiaobi Plaster in LDD. Molecular docking, dynamics simulations, and immune infiltration analysis further elucidated the underlying mechanisms, which were experimentally validated in a rat puncture-induced degeneration model. ResultsThree key targets--AHR, PTPN2, and SOAT1--were identified, with AHR emerging as the central regulator. Differential expression and enrichment analyses highlighted inflammatory and ECM-remodeling pathways, which overlapped with AHR-specific GSEA, underscoring its hub role in integrating immune and redox signaling with matrix turnover. Molecular docking and 100-ns molecular dynamics confirmed rutaecarpine (MOL002662) as the most stable AHR ligand. Transcriptomic data further showed AHR expression correlates with degeneration severity and mast cell infiltration. In vivo qPCR and Western blotting validated upregulation of AHR and supporting roles of PTPN2 and SOAT1 in degenerative discs. ConclusionThis study elucidates the multi-target and multi-pathway mechanisms of XBG in LDD, highlighting AHR as a pivotal therapeutic target modulated by rutaecarpine, with PTPN2 and SOAT1 serving as auxiliary regulators. These findings provide mechanistic insights into the transdermal application of XBG and support the therapeutic relevance of targeting the AHR signaling axis in LDD.

bioinformatics↗

bioRxiv2025

DynaFold: A Latent Diffusion Based Generative Framework for Protein Dynamic Trajectory

The dynamic process of protein folding and conformation switching describes the basis of protein functions. Molecular dynamics (MD) simulations are precise computational tools for exploring protein dynamics, but the high computational costs make it difficult to scale up. Deep learning methods have been used to model the Boltzmann distribution of molecular simulations, but achieving MD-level accuracy remains a major challenge. Here, we present DynaFold, a generative deep learning framework based on latent diffusion for sampling protein dynamic trajectories. DynaFold accepts an initial structure and generalizes the conformational dynamics of different proteins with minimal trajectory data during training. It achieves state-of-the-art accuracy in predicting conformational ensembles and sampling conformational transition pathways, demonstrating superior generalization capability and computational efficiency compared to existing methods. Our framework provides a general solution for generating conformation distributions and transition processes between different conformations for proteins, enabling rapid sampling of structural ensembles and analysis of Boltzmann systems.

bioinformatics↗

bioRxiv2025

Stable characteristics of intrapopulation heterogeneity in virus-specific Th1 cells during chronic viral challenge infection

Virus-specific CD4+ T cells typically undergo T helper (Th) 1 differentiation and contribute to a type 1 immune response in infection with lymphocytic choriomeningitis virus (LCMV). Using this model pathogen, we performed an in-depth analysis of the quantitative expression stability of the Th1 key transcription factor T-bet. Previously, it was shown that virus-specific Th1 cells arising in acute infections expressed T-bet at distinct intensities and maintained their T-bet expression differences after viral clearance as memory cells for weeks in the steady state. However, it was unclear whether differential T-bet expression was associated with heterogeneity inside the Th1 population and if the quantitative T-bet memory, particularly of those cells expressing T-bet at low levels, could withhold the strong and continuous stimulation present during chronic infection. Using T-bet-ZsGreen reporter mice, virus-specific Th1 cells were characterized phenotypically at protein, RNA, and DNA/chromatin accessibility levels. The Th1 cells arising during acute LCMV Armstrong infection showed a continuous spectrum of T-bet expression, ranging from cells with very high T-bet to cells with low T-bet. Even though the cells with low T-bet expression clearly possessed Th1 characteristics, they additionally showed certain Tfh-like features at protein and RNA level. When virus-specific Th1 cells were sorted according to T-bet-ZsGreen reporter expression intensity, adoptively transferred, and rechallenged by infecting the host animals with the chronic Clone 13 strain of LCMV, they maintained quantitative differences in T-bet reporter and IFN-{gamma} expression levels. A subpopulation of the progeny of the former T-betlow cells still showed a mild Tfh-associated phenotype. Independent of their past and present T-bet expression level, all virus-reactive CD4+ T cells acquired phenotypic signs of exhaustion as characterized by upregulation of PD-1, LAG3, and TOX and vast absence of effector cytokine co-expression in the chronic infection environment. Collectively, our findings highlight the heterogeneity of T-bet+ antiviral CD4+ T cells and the stability of quantitative differences in individual virus-specific CD4+ T cells during chronic viral challenge infection.

immunology↗

bioRxiv2025

Structure and Function of Lens Suture Examined by 2-photon Fluorescence Microscopic Imaging

We have applied 2-photon fluorescence microscopy (2PFM) to investigate the structures and functions of mouse eye lenses, especially lens sutures, using wildtype (WT) and KLPH-KO suture-cataract lenses in vivo. Dynamic structures of lens sutures have been hypothesized to act as pathways carrying fluid containing ions, nutrients, and other factors as part of microcirculation for maintaining lens homeostasis and transparency. 3D imaging results show both typical "Y" and "double Y" shaped suture structures in WT lenses, diverse suture patterns including "star" shapes with variations appearing at different depths, and misaligned suture planes in KLPH-KO lenses. The variability in suture patterns, quantified using the mean of image stacks similarity indices (SSIM) to the mean projection of the stack, reveals a significant increase (p<0.05) in pattern randomization for KLPH-KO lenses. Both WT and KLPH-KO lenses exhibit voids around sutures and enlarged vacuoles throughout the lens structure in vivo. Pathological features like irregular and larger central voids containing 2~5-{micro}m-diameter amorphous structures that might result from membrane protein remnants/aggregates in the KLPH-KO mouse eye lens were observed. In conclusion, this work provides new morphological markers for characterizing suture cataract and fiber pathological features. Lens sutures are stabilized structures that are impermeable to dyes, and the extracellular spaces of lens peripheral fibers provide efficient diffusion pathways for lens microcirculation.

biophysics↗

bioRxiv2025

Dysregulation of innate immunity and cellular metabolism through virus-induced deISGylation

Interferon-stimulated gene 15 (ISG15) regulates diverse cellular responses including antiviral immunity through its conjugation to proteins, a process known as ISGylation. Several pathogens, including SARS-CoV-2, subvert ISGylation by encoding deISGylating enzymes. However, the direct targets and physiological consequences of coronaviral deISGylation remain poorly defined. Here, we ablated the deISGylating activity of the SARS-CoV-2 papain-like protease (PLpro) and found that loss of deISGylation boosted innate immune activation, attenuated virus replication, and promoted viral clearance in human cells and in mice. Through untargeted metabolomics and ISGylome proteomics analyses, combined with functional studies, we discovered in molecular detail how the activities of key metabolic enzymes in glycolysis, the pentose phosphate pathway, and oxidative stress are controlled by PLpro deISGylation. These findings provide fundamental new insight into how reversible ISGylation regulates immunity and metabolic processes at the molecular level and highlight viral deISGylation as a major viral tactic for rewiring immunometabolism.

microbiology↗

bioRxiv2025

Mechanical Memory Primes Cells for Confined Migration

When migratory cells move from one stiffness niche to another in vivo, they are exposed to highly confined spaces imposed by dense extracellular matrix (ECM) networks and inter-tissue boundaries. Cells that originate from one niche possess distinct mechanosensitive adaptations that influence their response to their new niche, a concept known as mechanical memory. However, the mechanisms by which this memory is acquired, and the degree to which it influences migratory potential and decision-making processes in confinement remain poorly understood. Here, we combine stiffness priming using polyacrylamide hydrogels with a confinement platform to screen mechanical memory across healthy and transformed cells. Using a dose-and- passage approach, we find that in stiffness-sensitive cells primed on soft substrates navigate confinement more efficiently. Bulk RNA sequencing identifies NFATC2 as a transcription factor that mediates mechanical memory by reprogramming gene expression in stiffness-sensitive cells. siRNA-induced knockdown of NFATC2 in memory-sensitive cells confirmed its necessity for mechanical memory acquisition and subsequent confined migration enhancement. Interestingly, highly invasive cancer cells exhibit minimal sensitivity to prior mechanical priming, suggesting differential adaptation strategies. These findings reveal mechanical memory as a cell-intrinsic property shaped by past mechanical environments and highlight potential implications for controlling migration in wound repair, fibrosis, and disease progression.

cell biology↗

bioRxiv2025

Scaffolded hiPSC liver organoids recapitulating bile duct tubulogenesis and periportal architecture.

Recapitulating the liver periportal area in vitro remains a major challenge due to its complex cellular composition and the coordinated development of both ductal and endothelial networks. Most existing bile duct organoid models fail to reproduce tubular extension and multicellular organization. We present a 3D ECM micro-rods system biofunctionalized with grafted growth factors mimicking fetal liver paracrine signaling to initiate and to coordinate the development of bile ducts, parenchymal cells, and vascular structures. Our system recapitulates key developmental stages, from the formation of the ductal plate to the emergence of elongated tubular ducts. The ECM rod alone provides the biophysical cues initiating the elongation of the bile ducts and the spatial structuration of the cellular organization, while the biofunctionalization with growth factors enhance the organization and maturation of the biliary and vascular systems. We further demonstrate that this approach is scalable and amenable to quantitative analysis through label-free Optical Coherence Tomography combined with AI-driven 3D segmentation.

cell biology↗

bioRxiv2025

NAT10 Suppresses RNA Sensing Induced IFN-β Transactivation to Promote Viral Infection via Interfering with IRF3 Activities

Cells can sense invading viruses and trigger type I interferons (IFN-/{beta}) to evoke antiviral innate immune response. Induction of IFNs needs to be fine-tuned to achieve the antiviral consequence while avoiding severe disruption of host cell homeostasis. Here, we reported that NAT10, the acetyltransferase of histone and N4-acetylcytidine (ac4C) RNA modification, promotes infection of RNA viruses via regulation of type I IFN signaling. Depletion of NAT10 increased the expression of IFN-{beta} and interferon-stimulated genes (ISGs) upon stimulation of type I IFN antiviral signaling, while it impaired viral replication. NAT10 dynamically associated with the IFN-{beta} promotor and negatively regulated IRF3 through modulation of long non-coding RNAs (lncRNAs) that inhibit IRFs. Consistently, the small molecule inhibitor of NAT10, Remodelin, increased IFN-{beta} expression while inhibiting viral infections. Overall, our findings indicated that NAT10 is a negative regulator of type I IFN signaling, suggesting its potential as a target of antiviral treatment.

microbiology↗