Biology subjects

Huang, Z.

Publications and source records attributed to Huang, Z..

At least 73 records · Page 4Linked to original sources

bioRxiv2026

SELECTIVE TRANSCRIPTOMIC VULNERABILITY OF MEMBRANE-INTEGRATED ARCHITECTURES DURING NEURAL TISSUE VITRIFICATION

Cryopreservation is essential for long-term storage of biological tissues. Yet, surprisingly, the precise molecular impact of cryopreservation on tissue transcriptomes remains poorly defined. This study provides the first resource of whole-genome transcriptomic changes following cryopreservation. This study used bulk RNA sequencing to examine how preservation method (snap freezing or vitrification) affects transcriptomes in mouse cerebral cortex and hippocampus. This allowed us to separate cryoprotectant-specific changes from cold induced-changes via snap freezing. In a subset of genes, tissues processed under vitrification conditions showed selective under-representation of a small but structurally coherent group of transcripts, with the hippocampus exhibiting greater vulnerability than the cortex. UniProt annotation revealed that affected transcripts were strongly enriched for proteins with membrane-associated, secretory-pathway, and multi-pass topologies, indicating that structurally complex membrane-integrated architectures are disproportionately sensitive to vitrification. Pathway-level analysis using iPANDA further showed that negative preservation scores in vitrified tissue clustered primarily within signal transduction and metabolic pathways, suggesting coordinated pathway-level disruption rather than global transcript loss. Together, these results demonstrate that vitrification conditions induce selective and structured molecular perturbations in neural tissue, defined by the under-recovery of transcripts associated with membrane and secretory pathway organization. This work highlights molecular vulnerability during vitrification and emphasizes the need for transcript-level evaluation when optimizing cryopreservation approaches for neural systems.

molecular biology↗

bioRxiv2026

Gene-First Identity Construction for Robust Cell Identification in Single-Cell Transcriptomics

The precise delineation of cell types is fundamental to single-cell transcriptomics, yet current clustering pipelines often violate an axiomatic principle: hierarchical consistency. Existing methods measure cell-to-cell distances within a fixed global feature space, disregarding the fact that biological distinctions are inherently context-dependent lineage separation requires different gene programs than subtype resolution. Mathematically, this implies that the similarity metric itself should not be a static functional, but a pair-dependent energy functional evaluated within a specific Hilbert subspace determined by the biological comparison at hand. The challenge lies in the fact that allowing pair-dependent metrics typically destroys the global geometric consistency required for downstream analysis, unless the family of Hilbert subspaces is given strong biological structure. To resolve this geometric dilemma, we introduce GeCCo (Gene Co-expression Constructed identity), which constructs identities by projecting cells onto a rigorously derived hierarchy of gene programs. To construct this hierarchy, GeCCo first quantifies Boolean regulatory logic via the{phi} coefficient, and subsequently employs a greedy topological inference to organize genes based on their synergistic and antagonistic relationships. Benchmarking on human immune atlases demonstrates that GeCCo achieves superior hierarchical consistency, ensuring that globally inferred cell identities rigorously match locally refined subtypes. Furthermore, in pancreatic endocrine progenitors, GeCCo resolves a hidden mitotic bridge state, suggesting a concentrated division phase prior to differentiation. Ultimately, GeCCo shifts the paradigm from ad hoc clustering to programmatic cell typing, offering a mathematically grounded framework for scalable atlases of cellular discovery.

bioinformatics↗

bioRxiv2026

SMCHD1 loss re-wires MYOD1 enhancer nexuses and chromatin accessibility landscapes in muscle cells

Human SMCHD1 (Structural Maintenance of Chromosomes Flexible Hinge Domain Containing 1) is a chromatin architectural protein linked to heterochromatin repression. Loss of function mutations of SMCHD1 cause facioscapulohumeral muscular dystrophy type 2 (FSHD2) through activation of the DUX4 homeobox transcription factor gene. However, it is unknown how SMCHD1 may regulate myogenic transcription independently of DUX4. Here, we show that SMCHD1 safeguards enhancer organization within the three-dimensional (3D) genome in human myoblasts. Loss of SMCHD1 leads to widespread gains in chromatin accessibility, aberrant transcription and a global redistribution of the myogenic transcription factor MYOD1. Integrative analyses of histone modifications, chromatin accessibility, Hi-C looping, and activity-by-contact enhancer-gene modeling reveal that SMCHD1 loss rewires the landscape of clustered enhancers and promotes the emergence of a new MYOD1-related network of enhancer elements, termed MYOD1 enhancer nexuses. These structures are marked by increased enhancer-enhancer connectivity, increased local 3D chromatin interactions, and coordinated activation of genes likely relevant for FSHD pathology. Together, our findings identify SMCHD1 as a key architectural constraint that suppresses hyperactive enhancer networks, thereby preserving transcriptional homeostasis in myoblasts.

molecular biology↗

bioRxiv2026

Cell Type Architecture and Positional Gene Gradients in an Adult Animal at Subcellular Resolution

The spatial organization of cell types and gene expression underlies tissue architecture and organismal physiology. However, resolving complete cellular and molecular landscapes within a three-dimensional context remains challenging, particularly in organisms with high cellular heterogeneity and complex geometry. Here, we developed a semi-supervised workflow to reconstruct high-resolution three-dimensional spatial transcriptomic models of the planarian Schmidtea mediterranea at single-cell resolution. Planarians are basal bilaterians capable of regenerating body structures after injury. Our reconstruction maps the distribution of cell types and spatially patterned gene expression across the intact organism and identifies 119 candidate positional control genes (PCGs). These genes are expressed across muscle, neural, and epidermal populations. Functional perturbation of selected candidates, including pitx3, ptpn11, pi4ka, upf3b, and cul1, revealed roles in regeneration following injury. In addition, we identify intestinal cells as prominent components of the microenvironment surrounding adult tgs1 pluripotent stem cells (neoblasts). Together, these results demonstrate the utility of three-dimensional spatial transcriptomic reconstruction for mapping cellular architecture and positional gene regulation in complex adult organisms.

developmental biology↗

bioRxiv2026

4D Single-Cell Spatial Transcriptomics Reveals Dynamic Morphogenetic Gradients and Regenerative Domains in Planarians

Regeneration relies on precise spatiotemporal gene expression and cellular responses to establish tissue identity and body patterning. Using high-resolution Stereo-seq (715 nm) on 353 sections from 16 whole animals at 8 regeneration timepoints, we constructed a 4D spatiotemporal transcriptomic map of planarian regeneration. Our analysis captured 36 refined cell types from 3,508,004 segmented cells, enabling genome-wide transcriptional imputation of gene expression dynamics across body axes at cellular, tissue, and organismal scales. We identified dynamic positional gradients and distinct spatially distributed cell types during regeneration, including an injury-induced Anterior Regenerative Zone (ARZ). The ARZ exhibited enriched positional signals in epidermal, muscle, and neural cells and was regulated by Mediator 8, which is crucial for polarity remodeling and blastema formation. This study provides a comprehensive spatial molecular and cellular map of regenerative processes, highlighting injury-induced spatial domains and key regulatory factors in planarian regeneration. We also provide an interactive web portal, offering a valuable resource for exploring and analyzing regeneration mechanisms in a spatiotemporal context.

developmental biology↗

bioRxiv2026

Pharmacological recruitment of a VTA glutamatergic arousal circuit by the natural product BN3 drives broad-spectrum emergence from general anesthesia

Pharmacological control of emergence from general anesthesia remains strikingly limited. Clinically available antagonists are largely drug-class specific, leaving recovery dependent on anesthetic clearance rather than to an actively programmable switch in brain state. Through phenotypic screening of a structurally diverse natural-product library, we identified BN3 (L-(-)-camphor) as a broad-spectrum emergence agent. BN3 robustly shortened recovery from propofol anesthesia across species--from mice and rats to rabbits, dogs, and rhesus monkeys--and remained effective after continuous infusion. In rodents, BN3 also accelerated emergence from mechanistically distinct anesthetics, including etomidate, remimazolam, sodium {gamma} - hydroxybutyrate, midazolam, ketamine, sodium pentobarbital, and isoflurane. EEG recordings revealed a rapid cortical shift from slow-wave dominance to a wake-like high-frequency spectrum. Mechanistically, BN3 preferentially recruited ventral tegmental area (VTA) glutamatergic neurons: chemogenetic silencing abolished the BN3-evoked EEG spectral shift and strongly attenuated behavioral acceleration of emergence, whereas optogenetic activation of these neurons was sufficient to promote recovery. BN3 increased glutamate release in the nucleus accumbens and medial prefrontal cortex, and projection-specific inhibition of VTA[->]NAc or VTA[->]mPFC outputs blunted BN3-induced emergence. These findings define a VTA-centered glutamatergic arousal circuit that can be pharmacologically recruited as a common gateway for anesthetic-independent emergence.

neuroscience↗

bioRxiv2026

Opposing Network Patterns of Integration-Segregation in Psychedelic and Sedated States of Consciousness

Understanding the relationship of conscious states to large-scale brain dynamics remains a central challenge in neuroscience. Here, diverse pharmacological and physiological perturbations--including psychedelic states, sleep, and propofol sedation--were used to examine integration-segregation organization of brain networks across altered states of consciousness in humans using functional MRI. Across analyses, psychedelic and sedative states exhibited a robust "mirror-image" pattern of integration and segregation. Psychedelics were characterized by increased large-scale integration and reduced segregation of brain network interactions, whereas sleep and propofol sedation showed the opposite configuration. These opposing integration-segregation patterns were consistently indexed by complementary measures of functional connectivity, network topology, and interaction complexity, capturing non-redundant dimensions of large-scale brain organization. Importantly, this mirror-image organization generalized across multiple spatial levels and reliably differentiated conscious states in an unbiased, data-driven manner. Together, these findings demonstrate that psychedelic and sedated states are characterized by systematic and opposing shifts in large-scale integration and segregation, with implications for mechanisms of consciousness.

neuroscience↗

bioRxiv2026

Multi-agent reasoning enables predictive design of living materials

Artificial intelligence is increasingly used to accelerate scientific discovery, but most successful frameworks operate within well-defined molecular, protein or materials spaces. Living materials present a more formidable computational problem because functions emerge from context dependent coupling among cells, matrices, fabrication processes and evaluation conditions. Here we introduce LiveMat, a multi-agent reasoning framework that transforms unstructured literature into a computable design space for living materials. LiveMat standardizes 34,215 living material records, integrating 16,769 microorganism and 17,446 polymer entries into a knowledge graph linking living components, abiotic matrices, functional outputs, evaluation contexts and performance metrics. Benchmarking across five large language models shows that living material reasoning is limited mainly by cross-domain feature integration rather than coarse classification. LiveMat overcomes this limitation through constraint decomposition, provenance-aware extraction, consistency checking and expert-anchored ranking. In a prospective wound-healing task, it prioritizes a four-component design with state-of-the-art in vivo performance, establishing a scalable infrastructure for interpretable, evidence-grounded living material discovery.

biochemistry↗

bioRxiv2026

Selective Cortical Myelination Reflects Axon-Driven Progression of the BCAS1-positive Oligodendrocyte Lineage

Myelination in the cerebral cortex is sparse, discontinuous, showing marked heterogeneity across cortical areas and along individual axons, yet the mechanisms that establish this complex and selective architecture remain unclear. Using histological mapping of oligodendrocyte lineage cells across cortical areas combined with longitudinal in vivo imaging, we find that initial myelination is highly targeted: up to 80 percent of the earliest segments arise consecutively along the same subset of axons. We observed that oligodendrocyte precursor cells enter a premyelinating BCAS1-positive state even within cortical regions that remain poorly myelinated or unmyelinated. However, the progression beyond early premyelinating morphologies correlates with local myelin levels and with interactions with specific neuronal partners. BCAS1-positive ensheathments show a preferential stabilisation and elongation along parvalbumin interneurons compared with somatostatin interneurons, linking regional neuronal composition to differential myelin levels. These findings indicate that cortical myelination emerges from intrinsic lineage programs that are refined through selective interactions with axons, thereby linking neuronal diversity to cortical myelin distribution and providing a framework to understand why remyelination may fail in regions where myelination supportive neuronal populations are reduced.

neuroscience↗

bioRxiv2026

Insight into the scaffolding function of USP18 from a high resolution cryo-EM structure of STAT2-USP18-ISG15 ternary complex

USP18 is a primary negative regulator of the type I interferon (IFN-I) signaling which regulates hundreds of IFN-stimulated genes for viral protection and anti-cancer immunity. USP18 plays dual roles in the IFN-I signaling: 1) deubiquitinase enzymatic function which cleaves ISG15 from its substrates and 2) scaffolding function through forming a complex with STAT2 to suppress IFN-I signaling. Targeting the scaffolding function of USP18, instead of its enzyme activity, is crucial for reducing cancer cell fitness and boosting anti-tumor immunity. However, the molecular basis of USP18s scaffolding function remains unclear due to the lack of structural information. Here, using a fusion tag strategy, we captured the transient USP18-STAT2 complex and determined a ternary complex structure of STAT2-USP18-ISG15 at 3.05 [A] resolution by cryogenic electron microscopy (cryo-EM) that delineated detailed USP18-STAT2 interactions. Remarkably, the ternary complex impairs USP18s enzymatic function by STAT2-mediated disruption of its catalytic triad. Structural analysis and mutagenesis identify specific USP18 point mutations, facilitating further investigation into the role of USP18 in IFN-I signaling. Taken together, our findings suggest that USP18s scaffolding function could present an untapped opportunity for cancer therapy.

molecular biology↗

bioRxiv2026

VC-RDAgent: An efficient rare disease diagnosis agent via virtual case construction informed by hybrid statistical-metric and hyperbolic-semantic prioritization

While Large Language Models (LLMs) have shown promise in clinical decision support, current Retrieval-Augmented Generation (RAG) paradigms face a fundamental bottleneck in rare disease diagnosis: the scarcity, privacy restrictions, and extreme heterogeneity of real-world patient records. This reliance on sparse or inaccessible data leads to a severe "retrieval mismatch," where the lack of high-quality reference cases causes diagnostic performance to degrade sharply. To break this deadlock, we propose VC-RDAgent, a privacy-preserving and offline-capable framework that decouples diagnostic reasoning from sensitive real-world records by synthesizing virtual standardized cases. The system is powered by VC-Ranker, a multi-dimensional engine that integrates statistical-metric measures with hyperbolic-semantic embeddings to capture deep hierarchical ontology relationships. This approach allows for the dynamic generation of high-fidelity virtual references directly from authoritative knowledge bases. Extensive benchmarking across four diverse datasets demonstrates that VC-RDAgent effectively functions as a "performance equalizer." It boosts average Top-1 hit rates by 8.7% to 85.9% over zero-case baselines, enabling lightweight open-source models to rival frontier commercial systems. Notably, VC-Ranker alone achieved an aggregate Top-10 hit rate of 0.819, outperforming prior state-of-the-art methods by 6%. By eliminating the dependency on real-time web retrieval and private case sharing, VC-RDAgent provides a scalable, robust, and clinically deployable solution to shorten the diagnostic odyssey, which is made accessible through an intuitive, chat-based web application https://rarellm.service.bio-it.tech/rdagent/.

bioinformatics↗

bioRxiv2026

ATG-18 drives longevity in an HLH-30-dependent manner

Enhancing autophagy increases lifespan and healthspan in animal models, yet the precise molecular mechanisms underlying these effects are not fully understood. Here we show that overexpression of the essential autophagic gene atg-18 extends the lifespan of C. elegans. We describe a previously unknown, pleiotropic mechanism by which atg-18 impacts lysosomes and extends lifespan through the transcription factor hlh-30, the master regulator of lysosomal biogenesis. We show that, under stress conditions, HLH-30 requires atg-18 for nuclear translocation. Furthermore, atg-18 overexpression broadly improves health and stress resilience yet paradoxically increases early-life susceptibility to lethal heat stress. In contrast, enhances heat-stress survival a loss-of-function of function mutation in atg-18 enhances heat-stress survival, uncovering a temporal-specific effect of atg-18. These finding suggest an ATG-18--HLH-30 autophagy--lysosome pathway that plays a key role in lifespan and healthspan. Bulleted main discoveriesO_LIATG-18 overexpression increases C. elegans lifespan and plays an important role in resilience against starvation and heat stress. C_LIO_LIATG-18 is required for nuclear translocation of HLH-30 C_LIO_LIHLH-30 is required for ATG-18--mediated lifespan extension C_LIO_LIATG-18 positively regulates lysosomal biogenesis, suggesting a novel role as a molecular coordinator between autophagy and the lysosomal network. C_LI

molecular biology↗

bioRxiv2026

Choice of phenotype scale is critical in biobank-based GxE tests

The importance of gene-environment interactions (GxE) for complex human traits is heavily debated. Recently, biobank-based GWAS have revealed many statistically significant GxE signals, though most lack clear evidence of biological significance. Here, we partly explain this discrepancy by showing that many GxE signals simplify to additive effects on a different phenotype scale, a classical concern that is currently underappreciated. Our results clearly distinguish GxSex effects on height, which vanish on the log scale, from GxSex effects on testosterone, where the log scale uncovers biologically meaningful female-specific effects. Across 32 phenotypes in UK Biobank, we find that scaling by a power transformation can explain 46% of PGSxSex interactions, and that simple log transformation can explain 23%, with similar results for other environments. We also show that phenotype scale can substantially impact GWAS discovery and the construction and evaluation of polygenic scores. Finally, we provide a set of guidelines to consider and choose phenotype scale in modern genetic studies.

genetics↗

bioRxiv2026

Gn1a rice promotes symbiotic fish growth via reprogramming soil microbiome

Rice-fish symbiotic ecosystems significantly contribute to world food supply. Mutation in rice (Oryza sativa) quantitative trait locus Gn1a, encoding a cytokinin oxidase/dehydrogenase (OsCKX2), leads to cytokinin accumulation in plant, which promotes tillering and panicle branching to achieved higher yield and also shows a selective effect on soil microbial composition. Given that the growth of aquatic animals can be shaped by their surrounding microbial communities, we asked whether adjusting rice cytokinin levels might synergistically boosts both rice yield and fish growth. Herein, we co-cultured common carp (Cyprinus carpio) with ckx2 rice plants to determine the effect of cytokinins on fish. Surprisingly, compared to wild-type plants, the ckx2 plants enhanced nearly 10% fish growth and improved fish antibacterial capacity against Aeromonas hydrophila and Edwardsiella tarda. In fact, the growth-promoting effect on fish requires mediation by the soil microbiota. Mechanistically, ckx2 plants secreted more cytokinins into soil to reprogram the microbial composition, which subsequently translocated to fish gut and modulated the keystone microbes in gut to facilitate short-chain fatty acid production and carbohydrate degradation. These findings provide the first evidence that rice-derived cytokinins exert a cross-kingdom growth-promoting effect on fish, providing a boosting dual-production strategy for advancing rice-fish symbiotic ecosystem.

plant biology↗

bioRxiv2026

Dual Engram Architecture within a Single Striatal Cell Type Distinctly Controls Alcohol Relapse and Extinction

Relapse is a major obstacle in the treatment of alcohol and drug addiction and is thought to be driven by persistent drug-associated memories formed during their use. Behavioral therapies such as extinction training can reduce relapse and are proposed to work by creating a competing memory trace. However, where and how these opposing memories are stored in the brain is unknown. Here, we show that two anatomically and functionally distinct engram ensembles within the same genetically defined striatal cell type, direct-pathway medium spiny neurons (dMSNs), encode these opposing memories. Using engram-tagging tools in mice, we found that the acquisition of operant alcohol learning recruits a dMSN ensemble enriched in the striatal matrix compartment that stores alcohol-associated memories and whose activation selectively promotes relapse. Conversely, extinction of alcohol seeking recruits a dMSN ensemble enriched in the striosome compartment that stores extinction-related memories and whose activation suppresses relapse. Furthermore, we reveal that the physical memory trace storing the relapse-promoting memory is embedded within persistently strengthened corticostriatal synapses engaged during learning, and that artificially reproducing this plasticity is sufficient to trigger relapse-like behavior. These findings uncover a dual-engram architecture within dMSNs that governs relapse and extinction, providing a mechanistic framework for understanding how competing memories regulate drug-seeking behavior. HighlightsO_LIAcquisition and extinction of alcohol learning recruits distinct dMSN ensembles. C_LIO_LIAcquisition recruits matrix-enriched dMSN ensembles to promote relapse. C_LIO_LIExtinction recruits striosome-enriched dMSN ensembles to suppress relapse. C_LIO_LIEngram dMSNs show lasting synaptic potentiation and mimicking this potentiation triggers relapse. C_LI

neuroscience↗

bioRxiv2026

Early-Stage Corticostriatal Circuit Hyperactivity Impairs Cholinergic Function and Cognitive Flexibility in an Alzheimer's Model

Cognitive flexibility deficits are a hallmark of early-stage Alzheimers disease (AD), but the underlying circuit mechanisms remain poorly understood. Here, we show that the 5xFAD mouse model of AD neuropathology exhibited early deficits in instrumental reversal learning, indicating cognitive inflexibility preceding spatial memory deficits. This impairment was associated with excessive neuronal reactivation in the medial prefrontal cortex (mPFC) and dorsomedial striatum (DMS), key regions for goal-directed behavior. Electrophysiological recordings revealed that mPFC neurons in young 5xFAD mice were hyperexcitable and received elevated excitatory input. Moreover, the mPFC-to-direct pathway medium spiny neuron (dMSN) circuit and the dMSNs themselves were selectively hyperactive. These hyperactive dMSNs exerted increased inhibitory control over cholinergic interneurons (CINs) in the DMS, coinciding with reduced CIN firing and diminished striatal acetylcholine (ACh) release. Critically, sustained chemogenetic inhibition of the mPFC-to-DMS circuit in 5xFAD mice reduced cortical A{beta} accumulation, normalized glutamatergic transmission in both the mPFC and DMS, restored striatal ACh levels, and rescued reversal learning deficits. Together, these findings identify a hyperactive mPFC-to-DMS circuit that disrupts corticostriatal and cholinergic signaling, contributing to cognitive inflexibility in 5xFAD mice. Targeting this circuit may offer a therapeutic strategy to preserve cognitive function in the early stages of AD. HighlightsO_LI5xFAD mice exhibit early cognitive deficits in instrumental reversal learning. C_LIO_LImPFC neurons and corticostriatal circuits are hyperactive, while cholinergic neurons are hypoactive in 5xFAD mice. C_LIO_LISustained inhibition of mPFC-to-DMS circuit hyperactivity normalizes glutamatergic transmission and slows A{beta} accumulation in 5xFAD mice. C_LIO_LISustained inhibition of the mPFC-to-DMS circuit rescues reversal learning deficits in 5xFAD mice. C_LI

neuroscience↗

bioRxiv2026

Single-Cell Multi-Omics Insights into BMI-Mediated Immune-Related Disease Risk

This study is based on the Chinese Immune Multi-Omics Atlas (CIMA) cohort and performs an integrated single-cell multi-omics analysis of peripheral blood mononuclear cells (PBMCs) from 210 individuals aged 20-29, comprising 3,311,699 scRNA-seq cells and 1,839,860 scATAC-seq cells, to decipher immune characteristics across different body mass index (BMI) categories. By integrating gene regulatory network (GRN) and cell type-level molecular quantitative trait loci (xQTL) data, and conducting summary-data-based Mendelian randomization (SMR) analysis in conjunction with genome-wide association studies (GWAS) of BMI-mediated immune-related diseases, we identified key disease-associated cell types and molecular features. Using rheumatoid arthritis (RA) as an example, multi-omics evidence revealed that in MAIT-SLC4A10 cells of underweight individuals, increased chromatin accessibility at the CCR6 locus (chr6:167119627-167120128) and enhanced transcriptional activity of RORC/RORA collectively drive elevated CCR6 expression, which may represent a potential molecular mechanism underlying the higher risk of RA in underweight populations. Our study leverages single-cell multi-omics data to systematically dissect the molecular mechanisms by which different BMI categories mediate susceptibility to immune-related diseases through coordinated regulation of immune cell chromatin accessibility, transcription factor activity, and downstream gene expression.

bioinformatics↗

bioRxiv2026

Poly(A)-tail-length-dependent surveillance of viral RNA by PABPC1 orchestrates broad-spectrum antiviral defense

RNA processing and modification are critical for virus replication and pathogenesis, yet how the host exploits viral RNA features--particularly the poly(A) tail--for antiviral defense remains unclear. Through multi-omics integration and systematic functional screening, we identify the poly(A)-binding protein PABPC1 as a broad-spectrum restriction factor against multiple coronaviruses. We demonstrate that PABPC1 preferentially binds viral RNAs bearing short poly(A) tails--distinct from the longer and more heterogeneous host poly(A) tails--and, in a poly(A)-length-dependent manner, recruits the mitochondrial exonuclease EXD2 to assemble a degradative RNA-protein complex. Both the recognition and subsequent degradation of viral RNA strictly depend on poly(A) tail length, enabling selective decay of short-tailed viral transcripts while sparing host mRNAs. Importantly, inflammatory signaling enhances the expression of PABPC1 and EXD2, suggesting its role as an inducible host defense pathway activated during viral infection. Capitalizing on this discovery, we engineered a synthetic fusion protein mimicking the PABPC1-EXD2 complex and achieved efficient delivery using lipid nanoparticles (LNPs). This rationally designed therapeutic exhibits robust suppression of coronavirus replication in both cellular and murine models. Collectively, our findings uncover a novel host antiviral strategy that targets a conserved viral RNA structural element and provide a conceptual framework for developing host-derived and broad-spectrum anti-coronavirus therapeutics.

microbiology↗