Biology subjects

Liu, S.

Publications and source records attributed to Liu, S..

At least 109 records · Page 6Linked to original sources

bioRxiv2026

Identification of scavenger receptor BI as a scavenger of free heme that is essential for protection against hemolysis

Severe hemolysis is a life-threatening condition with limited therapeutic options. Although haptoglobin and hemopexin sequester hemoglobin and heme, these protective systems are rapidly saturated during acute hemolysis, leading to the accumulation of cytotoxic free heme. In this study, we identify scavenger receptor BI (SR-BI) as a critical mediator of free heme clearance. SR-BI binds heme and facilitates its hepatic uptake under pathological conditions. Mice lacking hepatic SR-BI exhibit impaired heme clearance and increased susceptibility to heme- and hemolysis-induced lethality. Pharmacological upregulation of hepatic SR-BI via imatinib or adenoviral delivery confers protection against heme toxicity. Using a humanized model of sickle cell disease (SCD), we further demonstrate that sickle hepatopathy significantly reduces hepatic SR-BI expression compared to non-SCD littermates, potentially increasing vulnerability to heme-induced injury. Notably, adenoviral-mediated SR-BI upregulation rescues SCD mice from heme toxicity. These findings reveal a previously unrecognized mechanism of heme detoxification via hepatic SR-BI and identify a promising therapeutic target for hemolytic disorders. One-Sentence SummaryIdentification of scavenger receptor BI as a targetable scavenger of heme in hemolysis

physiology↗

bioRxiv2026

Ecology of metagenomes: incorporating genotype-to-phenotype maps into ecological models

A major theoretical problem in community ecology is to understand how genes, organisms, and environments combine to shape the structure and diversity of ecological communities. However, most classic ecological models work entirely with phenotypic parameters, neglecting the central role played by genes. This limitation is particularly acute in microbial ecology, where the widespread use of sequencing technologies allows researchers to directly measure the genomic and metagenomic properties of communities. Here, we bridge this gap by incorporating genotype-to-phenotype maps into classical ecological models, including the generalized Lotka-Volterra model (GLV) and consumer resource models (CRMs). We focus on the case where genotype-to-phenotype maps are linear, which provides a tractable yet powerful framework for analyzing complex traits. Even in this simple setting, the resulting ecological dynamics give rise to novel gene-level ecological dynamics that can be recast entirely in terms of genes, allowing us to develop an ecology of metagenomes. We find that ecological interactions between genes lead to pervasive "metagenomic hitchhiking" -- low-fitness genes can survive in the ecosystem because they are integrated into genomes of high-fitness species. We also show that phylogenetic relationships between species mold the ability of closely related strains to stably coexist in complex communities. This highlights how lineage structure and competitive interactions jointly shape community composition. Our framework provides a principled foundation for interpreting metagenomic data through the lens of ecological theory. Author summaryRecent advances in sequencing technologies have transformed our ability to characterize microbial communities at the genomic level. However, most classic ecological models work entirely with phenotypic parameters, neglecting the central role played by genes. Here, we address this gap by extending classical ecological models to explicitly include genotype-to-phenotype maps. We focus on complex traits where the genotype-to-phenotype map is approximately linear. We show that the resulting ecological dynamics that can be recast entirely in terms of genes, allowing us to develop an ecology of metagenomes. Our framework provides a novel perspective for interpreting metagenomic data through the lens of ecological theory.

ecology↗

bioRxiv2026

Domesticated pennycress is a self-pollinated crop

CoverCress is a new winter annual oilseed crop developed from field pennycress within the past 20 years. Field pennycress is commonly considered to be self-pollinated but little basic research has been published and there is some misalignment of conclusions. Our experience working with pennycress plant growth in greenhouse and field conditions over the past 13 years suggests that outcrossing is uncommon. We conducted lab, greenhouse, and field experiments to strengthen the body of work. Pollen viability kinetics analysis showed that longevity of pollen viability is negatively impacted by increasing temperatures and by direct exposure to light. Samples treated at 4C declined to 50% viability in 12 hours while it took just 2.5 hrs at 37C, and 1.6 hrs in full sunlight on a cool early April day. Cross-pollination was absent among greenhouse-grown plants flowering inside an agitated plastic pollen-containment covering. Across greenhouse tests, high rates of cross-pollination occurred only in an emasculation treatment that rendered flowers male sterile and opened the pistil to cross-fertilization. Field trials designed to measure pollen flow distance using a trackable fae1 knockout reporter gene failed to show detectable movement of pollen under field conditions in two locations. This data strongly suggests that domesticated field pennycress may be considered a self-pollinated crop and managed as such.

plant biology↗

bioRxiv2026

Degradable porous PLGA/PCL membrane enable a lung alveoli-on-a-chip for modeling particulate-induced alveolar injury

Understanding how airborne particulates disrupt the alveolar barrier requires in vitro systems that recapitulate both the structure and transport properties of the lung air-blood interface. Here, we report a biodegradable lung alveoli-on-a-chip enabled by porous poly(lactic-co-glycolic acid)/polycaprolactone (PLGA/PCL) membranes with an interconnected porous architecture generated via porogen-assisted phase separation process. The membrane exhibits tunable degradation behavior, allowing progressive increases in surface porosity ([~]40%) and reduction in thickness ([~]3 {micro}m) during culture, while PCL maintains mechanical integrity under dynamic conditions. These degradation-driven structural changes regulate membrane transport properties, leading to enhanced permeability and supporting the formation of a functional epithelial-endothelial barrier under air-liquid interface (ALI) culture with breathing-mimetic cycling strain. Primary human alveolar epithelial and microvascular endothelial cells formed confluent, junctional monolayers on opposing membrane surfaces, exhibiting stable barrier function and high viability throughout the culture period. As a functional application, the platform was used to assess diesel particulate matter (DPM)-induced alveolar injury. Apical exposure to DPM induced dose-dependent cytotoxicity, increased barrier permeability, elevated reactive oxygen species, and DNA damage in both epithelial and endothelial layers, demonstrating trans-barrier propagation of particulate-induced injury. Pharmacological modulation with roflumilast-N-oxide (RNO), a phosphodiesterase-4 (PDE4) inhibitor, selectively attenuated oxidative stress and inflammatory responses, with limited effects on barrier integrity. Together, this work establishes degradable PLGA/PCL membranes as tunable interface materials for lung-on-a-chip systems, where structural evolution during degradation directly governs transport and barrier function. The resulting platform provides a physiologically relevant approach for studying particulate toxicity and therapeutic modulation at the alveolar interface.

bioengineering↗

bioRxiv2026

HeteroRC: Decoding latent information from dynamic neural responses with interpretable heterogeneous reservoir computing

Time-resolved neural decoding is widely used to track information represented in neural activity, but conventional linear decoders primarily capture phase-locked evoked responses and often fail to recover representations embedded in nonlinear or non-phase-locked dynamics, potentially limiting the interpretation of neural coding. Here, we introduce HeteroRC, a biologically inspired and interpretable decoding framework based on heterogeneous reservoir computing. HeteroRC projects neural signals into a high-dimensional recurrent state space with heterogeneous time constants, enabling nonlinear feature expansion and multiscale temporal integration directly from raw neural time series. Simulations demonstrate that HeteroRC significantly outperforms linear decoders and a suite of artificial neural networks (including RNNs, LSTMs, Transformers and EEGNet) on evoked responses while robustly capturing induced oscillatory power, phase synchrony, and aperiodic modulations--dynamics that are largely latent to conventional linear methods. We further validate HeteroRC on two empirical EEG datasets. In a motor imagery task, it substantially improves decoding accuracy and exhibits superior cross-temporal generalisation, revealing dynamic representational transformations. In an attentional priority task, HeteroRC uncovers statistically learned spatial priority information that remains hidden from conventional methods, successfully decoding these latent states previously thought to be activity-silent. Furthermore, we develop a dual-level interpretability framework linking reservoir dynamics to virtual sources and sensor space, revealing the temporal, spectral, and spatial signatures underlying decoding performance at both the individual and group levels. Together, HeteroRC offers an interpretable approach to decode information from dynamic neural responses, broadening the analytical scope of neural decoding while remaining computationally efficient and free from manual feature engineering, making it particularly suitable for small-sample electrophysiological studies.

neuroscience↗

bioRxiv2026

From nucleotides to semantics: genomic representation learning via joint-embedding predictive architecture

Decoding the regulatory syntax encoded in genomic sequences is a central objective in computational biology. Most existing genomic foundation models treat DNA as a language and adopt pretraining objectives from natural language processing. DNA sequences, however, lack explicit semantic boundaries and contain substantial evolutionary noise. Nucleotide-level reconstruction in a low-dimensional input space can therefore increase computational overhead and may yield representations with limited discriminative capacity. Downstream tasks often depend on expensive finetuning, which restricts practical use in many biology laboratories. Here we present GenoJEPA, a genomic representation learning framework based on joint-embedding predictive architecture. GenoJEPA combines continuous patching with semantic alignment, shifting the optimization from local base reconstruction to semantic alignment in latent space. Across 55 downstream tasks, GenoJEPA shows strong representational capacity and robust generalization while reducing parameter count and computational cost. The resulting semantic vectors from frozen GenoJEPA support lightweight GPU-free classifiers to achieve competitive accuracy. These results suggest a practical route towards efficient training and broad application of larger-scale genomic foundation models.

bioinformatics↗

bioRxiv2026

Structural principles of transcriptional collisions

RNA polymerase (RNAP) must navigate crowded genomic tracks to robustly produce transcripts. DNA-bound proteins act as transcription-impeding roadblocks, which are eventually overcome by RNAPs through unclear mechanisms. Here, we use cryo-electron microscopy to visualize actively transcribing E. coli RNAP upon collision with an inactivated restriction enzyme (EcoRI*) or with another converging RNAP. Both collisions induce RNAP backtracking into an inactive swiveled state. Swiveling is coupled to DNA deformation through a characteristic structural landscape, mediating RNAP pause stabilization across distinct collision geometries. EcoRI* roadblock bypass efficiency is impacted by factors that modulate RNAP swiveling, backtracking rescue, and roadblock stability. In comparison, head-on RNAP-RNAP collisions feature substantial heterogeneity suggestive of sustained dynamics, with variable inter-RNAP distances that are modulated by nascent transcript hairpins which position bidirectional termination sites. By resolving, to our knowledge, novel structures of actively transcribing RNAP undergoing collisions, we provide a mechanistic framework for interpreting mechanical conflicts during transcription.

biophysics↗

bioRxiv2026

Genetic dissection of rapid proteolysis identifies TXNDC15 as a key factor of ERAD and lipid homeostasis

Biological systems face a constantly changing environment and must swiftly respond to stimuli, yet how cells sense and adapt to environmental and physiological cues is incompletely understood. Short-lived proteins can be rapidly induced upon perturbation, enabling swift activation of adaptive cellular responses. Leveraging genome-wide data on protein-transcript correlation, we systematically searched for rapid proteolysis substrates whose abundance reflects the activity of the underlying proteolytic machinery. Here, focusing on the candidate substrate ABHD2, we employed CRISPR-based functional screens to dissect its degradation and identified TXNDC15 as an essential factor in MARCHF6-mediated ER-associated protein degradation (ERAD). Unexpectedly, TXNDC15 supports substrate exit and degradation from the ER via a catalysis-independent mechanism. Loss of TXNDC15 remodels the ER proteome and lipid homeostasis. Together, our work defines a missing component of ERAD and provides a generalizable strategy to decode post-translational regulatory circuits.

cell biology↗

bioRxiv2026

Hierarchical Assembly of Native Cytoplasmic Lattices Revealed by Cryo-EM

Oocytes depend on maternal factors for maturation and early embryogenesis. Cytoplasmic lattices (CPLs) are distinctive fibrillar structures in mammalian oocyte cytoplasm implicated in maternal factor storage and developmental competence, yet their molecular composition and architecture remain elusive. Here, we use cryo-electron microscopy to resolve the high-resolution structure of native mouse oocyte CPLs. We identify 14 intrinsic components of multiple copies that assemble into filaments in which PADI6-mediated self-assembly and two subtypes of subcortical maternal complexes (SCMCs) form the core scaffold. Unexpectedly, we discover that /{beta}-tubulin dimers and two autoinhibited ubiquitination modules (UHRF1-UBE2D3, SKP1-FBXW18) are internal components of CPLs. We also uncover multivalent interactions that organize adjacent CPL filaments into higher-order helical bundles. By integrating CPL structure with biochemical and proteomic data, we propose a hierarchical assembly mechanism of CPLs, from subcomplexes to filaments to supramolecular lattices. Our study offers mechanistic insights into how maternal proteins are spatially organized to ensure successful early embryonic development and provides a structural foundation for understanding female infertility related to CPL-associated gene mutations.

developmental biology↗

bioRxiv2026

Sequence-Independent In Situ Imaging of GlycoRNA in Living Cells and Tissues based on COMPASS

Current methods for the imaging of glycosylated RNAs (glycoRNAs) focus on limited types with identified RNA sequences, making the distribution of global glycoRNAs at single-cell and tissue levels largely unexplored. To address this gap, we developed a co-metabolic proximity labeling assay (COMPASS) for sequence-independent imaging of glycoRNAs. COMPASS employs metabolic chemical reporters (MCRs) to label glycans and RNAs, followed by click-chemistry-based dye conjugation to generate Forster resonance energy transfer (FRET) signals. The MCR-enabled RNA labeling allows for sequence-independent imaging, and FRET ensures accurate localization of glycoRNA distributions. COMPASS facilitates glycoRNA imaging across multiple cell lines, cerebral organoids, and mouse tissues. We observed the downregulation of glycoRNAs in metastatic lung nodules and upregulation in original regions of brain development in cerebral organoids, suggesting their potential association with carcinogenesis and neurogenesis. COMPASS illuminates previously invisible glycoRNAs and offers a comprehensive profile of glycoRNA distribution for studying their functions.

bioengineering↗

bioRxiv2026

Architecture Matters: Design Rules for Multigene IDO1/PD L1 Cassettes in Human Skin Cells

Allogeneic cell therapies require the coordinated expression of multiple immunomodulatory genes, yet multigene circuits that function in permissive cell lines often fail in differentiated human tissues for unclear reasons. Here, we systematically dissect how transcriptional architecture governs functional immunoregulation in engineered human keratinocyte and fibroblast lines. Using site-specific large-cargo integration (eePASSIGE) as an enabling tool, we determined that genomic insertion efficiency was not the limiting factor for phenotype; rather, promoter arrangement and gene order dictated expression hierarchy. A single-promoter EF1-IDO1-T2A-GFP design that expressed robustly in HEK293T cells was nearly silent in skin-derived cells, preventing reporter-based enrichment. In dual- and tri-modular cassettes, we observed severe transcriptional interference: a downstream CMV promoter driving GFP or PD-L1/iCasp9 (via EMCV-IRES) markedly suppressed the upstream EF1-IDO1 unit, despite intact integration (resulting in [~]175-625-fold attenuation), demonstrating strong promoter interference within the circuit. Functionally, co-culture assays revealed a hierarchical immunomodulatory logic: high IDO1 expression proved to be a requisite threshold for T-cell suppression, whereas PD-L1 provided measurable benefit only against highly activated, PD-1+ T cells in vitro. Collectively, these data establish a site-specific framework for generating immune-tuned skin cells and define essential design rules for avoiding promoter interference in next-generation translational skin substitutes.

bioengineering↗

bioRxiv2026

ASFV early protein p30 suppresses antiviral type I IFN induction by targeting TRIM21 and RIG-I like receptor signaling adaptor MAVS

African swine fever (ASF) is a highly pathogenic disease caused by the African swine fever virus (ASFV) infection, which can affect pigs of all ages and breeds, posing significant threat to the global pig farming industry. The ASFV p30 protein is an early-expressed viral structural protein; however, its function is not fully understood. In this study, the interaction of viral p30 with host TRIM21 was identified. The ectopic TRIM21 inhibited ASFV replication, while knockdown or knockout of TRIM21 promoted ASFV replication. Further, p30 was found to interact with RIG-I-like receptor (RLR) signaling adaptor MAVS, and during ASFV infection, p30-TRIM21-MAVS interacted with each other. Mechanistically, TRIM21 activated the K27 polyubiquitination of MAVS to induce IRF3 mediated type I interferon (IFN) production, whereas p30 counteracted TRIM21 activated MAVS K27 polyubiquitination to evade RLR signaling mediated antiviral IFN induction. In summary, our study revealed a novel function of ASFV p30, and provided new insights into the immune evasion of ASFV.

immunology↗

bioRxiv2026

Sustained Relief of Chronic Pain via a Nav1.7_Targeting ASO_siRNA Conjugate

Chronic pain affects billions globally, yet safe, long-lasting, and non-addictive analgesics remain lacking. Nav1.7 is a genetically validated pain target, but traditional small molecules have repeatedly failed. Therapeutic oligonucleotides-antisense oligonucleotides (ASOs) and siRNAs-offer selective, durable silencing. We developed N02C0702, an ASO-siRNA conjugate (ASC), achieving robust Nav1.7 knockdown and sustained analgesia without additional delivery vehicles. N02C0702 outperformed individual ASO (N02A114) and siRNA (N02S154) moieties at mRNA and protein levels and in pain relief. In CFA-induced inflammatory pain, a single intrathecal dose exceeded naproxen and suzetrigine, while in SNL neuropathic pain, efficacy persisted up to 56 days, comparable to or surpassing pregabalin. Genome-wide RNA sequencing confirmed minimal off-target effects. N02C0702 highlights Nav1.7 as a key analgesic target and demonstrates the ASC platforms potential for chronic pain and other CNS-related pathologies, offering durable, selective, and safe therapeutic effects.

neuroscience↗

bioRxiv2026

Identification of a lineage-agnostic splicing signature caused by PRMT5 inhibition

PRMT5 is a type II arginine methyltransferase that forms an active complex with methylosome protein WDR77 (MEP50) to catalyze the symmetric dimethylation (SDMA) of arginine residues in proteins that regulate biological roles including apoptosis, DNA damage response and RNA processing. Some of the best characterized PRMT5 substrates are the small nuclear ribonucleoproteins SNRPB, SNRPD1 and SNRPD3, which are critical for spliceosome assembly and RNA splicing fidelity. MTAP-deleted cancers exhibit increased sensitivity to PRMT5 inhibition due to elevated levels of methylthioadenosine (MTA), a natural inhibitor of PRMT5. This vulnerability is exploited by MTA-cooperative PRMT5 inhibitors, exemplified by TNG908 and TNG462 which selectively target PRMT5 in MTAP-deleted cells while sparing MTAP-wildtype (WT) cells. Consistent with this mechanism, treatment with TNG908 in preclinical studies induces widespread splicing alterations in MTAP-deleted cancer models, with minimal effects in MTAP-WT cells. These splicing changes are consistent across diverse MTAP-deleted tumor types, including glioblastoma, pancreatic, and non-small cell lung cancer, indicating a histology-agnostic response to PRMT5 inhibition. Moreover, treatment of MTAP-WT cells with exogenous MTA mimics the splicing alterations observed with PRMT5 inhibition, as does pharmacologic inhibition of MTAP further supporting a mechanistic link between MTA accumulation, PRMT5 modulation, and aberrant splicing. Given that MTAP deletions occur in approximately 10-15% of human cancers, the identification of a robust RNA splicing signature offers a valuable pharmacodynamic biomarker for monitoring the activity of PRMT5 inhibitors. This splicing-based readout may also serve as a predictive biomarker of therapeutic response, offering greater specificity than global SDMA levels. Collectively these data suggest that a PRMT5-dependent RNA splicing signature can monitor the pharmacodynamic activity of MTA-cooperative PRMT5 inhibitors in MTAP-deleted cells.

cancer biology↗

bioRxiv2026

Hormonal stimulation induces broader decidualization responses than cAMP alone in 3D human endometrial organoids

The human endometrium undergoes cyclic, hormone-driven remodeling that establishes a transient window of receptivity required for embryo implantation, placentation, and maintenance of pregnancy. Decidualization of endometrial stromal cells is a central component of this process and can be induced in vitro using cAMP alone or in combination with ovarian steroid hormones (EPC: estradiol, progesterone, and cAMP). Although cAMP activates the core decidual transcriptional program, whether hormone supplementation induces a more physiologically relevant response remains unclear, particularly in 3D endometrial organoid (Endo-organoid) models which have emerged as a new alternative methodology (NAM). Here, we compared morphological and transcriptomic responses of human endometrial stromal cell-derived Endo-organoids undergoing decidualization induced by cAMP or EPC stimulation. EPC-treated Endo-organoids exhibited enhanced structural remodeling and more advanced morphological transformation compared with cAMP-treated organoids. RNA-seq analysis revealed substantial overlap in canonical decidual gene expression between the two conditions, but EPC induced broader transcriptional and pathway-level changes, including enrichment of metabolic, stress-response, and differentiation-related processes. Together, these findings demonstrate that while cAMP activates the core decidual program, EPC elicits a broader and more physiologically relevant decidualization response in 3D human Endo-organoids, providing guidance for optimizing Endo-organoids to study endometrial receptivity, implantation, and early pregnancy success.

physiology↗

bioRxiv2026

The tumour suppressor RBM5 activates the helicase DHX15 to regulate splicing

Pre-mRNA splicing determines the expressed proteome and is frequently dysregulated in cancer. The tumour-suppressor RBM5 controls an exon network regulating apoptosis, yet its molecular mechanism is elusive. Using in vivo spliceosome capture and cryogenic electron microscopy, we determined structures of precatalytic spliceosomes arrested by RBM5 immediately after U2 snRNP branchpoint recognition. Despite intron diversity, the U2-pre-mRNA duplex, branchpoint adenine, and downstream polypyrimidine tract are well-resolved. RBM5 binds the outer SF3B1 HEAT surface and performs dual functions: First, its helix-loop-helix motif and upstream zinc-finger domain sterically block tri-snRNP and Prp8 docking and prevent progression to pre-B and Bact complexes; Second, its G-patch activates DHX15 and places this DExH-box helicase on the pre-mRNA as it exits SF3B1, poised for branch helix unwinding. DHX15 binding to SF3B1 is facilitated by U2SURP/SR140, which engages SF3B1 near RBM5s helix-loop-helix. Functional assays confirm that disruption of the RBM5 interfaces with either DHX15 or SF3B1 inhibit exon repression. Mutations at these regulatory interfaces are common in cancer genomes and predicted to disrupt its regulation of apoptotic isoforms. Thus, RBM5 acts as a dual-action spliceosome gatekeeper that couples helicase activation with physical stalling to enforce tumour-suppressive alternative splicing programmes.

molecular biology↗

bioRxiv2026

Transient contractility attenuation reprograms epithelial cells into a protrusion-driven state that drives tissue fluidization

Collective cell migration drives tissue morphogenesis, repair and remodeling, and is often accompanied by transitions from solid-like to fluid-like states. While such tissue fluidization has been linked to physical parameters such as cell density, shape and activity, how it is actively regulated by mechano-chemical interplay remains unclear. Previous research has shown that transient attenuation of actomyosin contractility induces a transition from pulsatile, spatially confined motion to coherent, persistent long-range collective flow; however, the underlying cellular and signaling mechanisms remain unclear. Here we uncover the mechanistic basis by which transient perturbation of cell contractility reprograms the migration mode of confluent epithelial cells into a protrusion-driven, fluidizing state, by combining kinase-reporter live imaging, force measurements and mathematical modeling. This transition arises from coordinated changes in cell morphology and mechanics, including reduced cortical tension and greater stretch-induced cell strain, together with enhanced cell-substrate adhesion and force transmission. At the signaling level, this process is accompanied by a rewiring of extracellular signal-regulated kinase (ERK)-mediated mechanotransduction toward a protrusion-coupled mode that sustains migration even under fully confluent conditions. Consistently, a multicellular computational model further demonstrates that protrusion-driven migration is sufficient to promote shape-velocity alignment and drive a transition from caged to flocking-like collective states. Together, our results identify transient contractility attenuation followed by recovery as a trigger for a protrusion-driven state that fluidizes confluent epithelial tissues through coordinated remodeling of cytoskeletal, adhesive, and signaling systems.

synthetic biology↗

bioRxiv2026

Coronavirus envelope protein drives iron sensing disorder by hijacking the TAp73-FDXR axis

Iron overload is increasingly recognized as a critical contributor to coronavirus pathogenesis1, yet the underlying induction mechanisms remain unclear. Here, we uncover a fundamental pathway by which coronavirus drives IRP1 RNA-binding activity to induce iron accumulation2 via targeting the TAp73-FDXR axis. Specifically, coronavirus infection represses transcription of FDXR (encoding the key rate-limiting enzyme in host iron-sulfur cluster synthesis3), thereby impairing host iron-sulfur cluster generation to trigger the functional conversion of the cytosolic aconitase 1 (ACO1) into iron-regulatory protein 1 (IRP1)4, ultimately leading to the hosts persistently false perception of iron deficiency. We identify TAp73 as the primary transcription factor governing FDXR expression, and demonstrate that the coronavirus envelope protein (CoV-E) orchestrates TAp73 nuclear export. Subsequently, CoV-E binds TAp73 through a critical valine residue within its C-terminal PBM domain, inducing the K48-linked ubiquitination and proteasomal degradation of TAp73. Furthermore, we developed a CoV-E-targeting molecule, DPTP-FC, which blocks CoV-E-TAp73 interaction via forming steric hindrance and effectively alleviates iron accumulation and tissue damage caused by PEDV, PDCoV, and SARS-CoV-2 infection. Our study reveals the central role of the TAp73-FDXR axis in CoV-induced iron accumulation, highlighting CoV-E as an attractive antiviral target and DPTP-FC as a promising therapeutic candidate.

microbiology↗