Biology subjects

Liu, Q.

Publications and source records attributed to Liu, Q..

At least 109 records · Page 6Linked to original sources

bioRxiv2026

MYC-ATF4-ASS1 axis governs intracellular arginine synthesis and dictates the immune microenvironment in melanoma

Drug resistance is a major challenge for both targeted therapies and immunotherapies in cancer. Arginine starvation has proven a promising strategy to overcome recurrent tumors. However, key molecules involved and how immune responses are elicited are not well understood. Here we identify in melanoma cells MYC-ATF4-ASS1 signaling as a pathway, which not only governs intracellular arginine synthesis but also modulates antitumor immunity. ATF4 knockout in melanoma cells phenocopied ASS1 knockout in the same cells, both showing greater sensitivity to arginine depletors such as ADI-PEG20. A combination strategy of BRAF/MEK inhibitors and an arginine depletor shows significant therapeutic effects in a immune-compromised mouse model. Both Atf4 and Ass1 knockout melanomas exhibited enhanced infiltration of Cd8+ T cells and significantly reduced tumor growth in a syngeneic mouse model. Single cell transcriptomics profiled the reshaped tumor microenvironment and revealed that a subset of resident macrophages were reprogrammed by endogenous arginine blockade. Overall, our findings reveal that the MYC-ATF4-ASS1 axis not only controls arginine vulnerability of melanomas but also shapes the immune microenvironment.

cancer biology↗

bioRxiv2026

The Spatiotemporal Proteome Landscape of Aging: Structural determinants of age-sensitive proteome remodeling

Aging is marked by a decline in cellular functions accompanied by widespread changes in mRNA and protein abundance, yet whether aging broadly remodels subcellular protein localization and concentration--and why some proteins change while others remain stable--remains unclear. This gap matters because cellular function depends not only on expression levels but also on correct spatial organization. Using yeast replicative aging as a model, we built a robotic pipeline to enrich old cells from 5,661 strains, acquired 90 million single-cell 3D images, and applied machine learning to map proteome-wide changes in localization, concentration, and aggregation throughout aging. This age-resolved single-cell atlas uncovers widespread proteome remodeling and rewiring of protein interaction networks. Moreover, structural analysis reveals biophysical determinants of age-sensitive proteome remodeling across ages and species. Together, these results reveal a structure-encoded intrinsic principle underlying spatial proteome breakdown during aging and provide a resource to dissect mechanistic links among aging hallmarks.

systems biology↗

bioRxiv2026

Opposing regulatory logics converge on ABA receptors to govern the trade-off between growth and drought acclimation

Plants dynamically balance growth with stress responses through abscisic acid (ABA). How ABA signaling, but how ABA sensitivity is finely tuned is unclear. Here, we uncover a regulatory network of leucine-rich repeat receptor-like kinases (LRR-RLKs) that directly controls ABA receptors stability. We identify GASSHO1 (GSO1) as a core component that phosphorylates the PYL2 and PYL4 receptors, targeting them for degradation and thus serving as a brake on ABA signaling. Under drought stress, ABA accumulates and suppresses expression of GSO1-activating CIF peptides, releasing this brake to increase PYLs and sensitivity. This mechanism opposes our previously identified CEPR2 pathway, where drought-induced CEP peptides inhibit the kinase to stabilize PYLs. The integration of these two antagonistic modules within an LRR-RLK network enables precise, dynamic control of ABA perception. This work reveals a molecular framework explaining how plants calibrate the critical balance between growth and drought acclimation.

molecular biology↗

bioRxiv2026

SNAP18 Truncation Triggers a Competitive Binding Switch Between NSF and ATG8f, Balancing Vesicular Trafficking and Autophagy for SCN Resistance in Soybean

Soybean cyst nematode (SCN, Heterodera glycines) poses the most devastating biotic threat to global soybean production. Traditional SCN resistance mediated by the Rhg1 locus predominantly relies on gene copy number expansion and elevated -SNAP protein dosage. Here, we report a novel resistance mechanism in a single-copy rhg1-c background, wherein a C-terminal 24-amino-acid truncation of SNAP18 (designated SNAP18lmm3) triggers a functional switch from vesicular trafficking to autophagic degradation. Biochemical assays and structural modeling demonstrate that this truncation severely impairs the canonical interaction between SNAP18 and N-ethylmaleimide-sensitive factor (NSF), disrupting SNARE complex recycling and inducing localized cytotoxicity. Concomitantly, the truncated SNAP18lmm3 exposes a binding interface for the autophagy-related protein ATG8f, routing the aberrant protein for selective autophagic clearance. This constitutively activated autophagic flux acts as a systemic detoxification system, preventing widespread cell death and ensuring normal plant growth under non-stressed conditions. Upon SCN infection, SNAP18lmm3 specifically hyper-accumulates within nematode-induced syncytia. This accumulation reaches levels fourfold higher than in adjacent cells, which overwhelms the local autophagic capacity and triggering targeted cell death that arrests nematode development. By elucidating this competitive molecular switch between NSF and ATG8f binding, our study establishes a "self-degrading toxin" model that resolves the inherent trade-off between plant growth and immunity. This work provides a new theoretical framework for engineering cellular homeostasis to enhance durable crop resistance against parasitic nematodes.

plant biology↗

bioRxiv2026

NRF2 pathway activation and SPP1⁺TREM2⁺ macrophages drive chemoradiotherapy resistance in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is among the most aggressive cancers, with low rates of durable response to chemoradiotherapy and limited therapeutic options for relapsed disease. To uncover mechanisms of treatment resistance and relapse, we performed comprehensive multi-omics profiling of >100 pre-treatment and post-relapse ESCC tumors from a prospective clinical trial (NCT04694391), integrating whole-exome/genome sequencing, bulk RNA-sequencing, single-cell RNA sequencing, and spatial transcriptomics. We identify somatic alterations in NFE2L2/KEAP1 in nearly 40% of relapsed patients, which are associated with upregulation of NRF2 signaling targets in resistant tumors and cell line models. At single-cell and spatial resolution, relapsed tumors are enriched for NRF2-activated epithelial cells that physically co-localize with immunosuppressive SPP1TREM2 macrophages. This co-localization suggests a synergistic interaction between NRF2-driven tumor programs and macrophage-mediated immune suppression that promotes relapse after chemoradiotherapy. Our findings nominate NFE2L2/KEAP1 mutations as predictive biomarkers for patient stratification and highlight therapeutic targeting of NRF2 signaling and SPP1TREM2 macrophages as rational strategies to overcome resistance in ESCC.

cancer 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

Human Cerebral Cortex Organization Characterized by Functional PET-FDG "Metabolic Connectivity"

PurposeIn this study, we characterize the spatiotemporal organization of resting-state metabolic connectivity (RSMC) in the human brain, as measured by [18F]- fluorodeoxyglucose (FDG) functional PET (fPET-FDG). We examine the relationship between RSMC organization and resting-state functional connectivity (RSFC) derived from functional magnetic resonance imaging and other known cortical organizational principles. MethodsResting-state fPET-FDG data from 24 individuals were obtained from a publicly available repository. We characterized local metabolic organization using connectivity-based boundary mapping, with adaptations to account for the low signal-to-noise ratio of fPET-FDG data. We then estimated global metabolic organization through community detection-based network and principal gradient analyses. Furthermore, we examined how metabolic connectivity is shaped by temporal-frequency-specific components of fPET-FDG signal. Finally, we contextualized metabolic organization by relating metabolic gradients to anatomical, functional, and energetic reference measures. ResultsAt the local scale, boundary mapping results indicated structured transitions shaped by a combination of both fast and slow fPET-FDG signals, partly overlapping with RSFC boundary maps. Globally, RSMC analyses revealed a robust metabolic structure organized along a superior-inferior cortical gradient. This pattern remained consistent across network community detection and principal gradient analyses and was primarily driven by low-frequency, minute-scale fPET-FDG dynamics. The identified large-scale metabolic profile aligns closely with several known anatomical and energetic constraints. ConclusionThis study characterizes the spatiotemporal organizational principles of RSMC, deepening insight into the brains energetic framework and providing a basis for future cognitive and clinical investigations of metabolic connectivity organization.

neuroscience↗

bioRxiv2026

Anti-IL1RAP Antibodies for Pan-Inhibition of IL-1 Family Cytokine Signaling in Inflammatory Diseases and Oncology

The interleukin-1 (IL-1) superfamily of cytokines--comprising the IL-1, IL-33, and IL-36 subfamilies--orchestrates a vast array of innate and adaptive immune responses. While physiological activation of these pathways is essential for host defense and tissue repair, their chronic dysregulation is pathognomonic of a broad spectrum of autoimmune diseases and malignancies. Current therapeutic modalities largely rely on the neutralization of single cytokines, an approach often limited by the functional redundancy and compensatory signaling loops inherent to the IL-1 superfamily. The Interleukin-1 Receptor Accessory Protein (IL1RAP) serves as an obligatory co-receptor for IL-1, IL-33, and IL-36 subfamilies, functioning as a molecular bottleneck for pro-inflammatory signaling. Herein, we report the development and comprehensive characterization of two humanized monoclonal antibodies, DXP-006 and DXP-106, which target a unique epitope on domain 2 of IL1RAP. Cryo-electron microscopy studies at 3.55 [A] resolution reveal that these antibodies lock the critical c2d2 loop of IL1RAP, sterically occluding its recruitment to IL-1R1, ST2 and IL-36R binary complexes and potently blockade IL-1, IL33, and IL-36 signaling. DXP-006, engineered with a half-life-extended and effector-silenced Fc, exerts profound efficacy in murine models of psoriasis, superior to the clinical benchmark bimekizumab. Conversely, DXP-106, engineered with a defucosylated Fc to enhance antibody-dependent cellular cytotoxicity, exhibits potent antitumor activity in non-small cell lung cancer xenografts. These findings position DXP-006 and DXP-106 as ideal therapeutics for IL-1 family-driven autoimmunity and IL1RAP-positive cancers. One Sentence SummaryAnti-IL1RAP antibodies block multiple IL-1 family cytokines simultaneously, showing superior efficacy in inflammation and cancer models.

immunology↗

bioRxiv2026

Antibiotic Persistence Emerges from Cell-State-Driven Transcriptional Reprogramming

Antibiotic persistence allows a subpopulation of bacterial cells to survive antibiotic treatment without acquiring resistance mutations, often contributing to treatment failure. Although many genes have been linked to persistence, their deletion rarely abolishes the phenotype, highlighting redundancy in persistence mechanisms. Moreover, the transient and heterogeneous nature of persister formation has made it difficult to resolve its molecular basis using bulk analyses. Here, we use bacterial single-cell RNA sequencing and functional assays in Klebsiella pneumoniae to demonstrate how transcriptional heterogeneity and redundancy in stress responses shape persistence outcomes. Using growth phase as a biologically meaningful axis of transcriptional variation, we reveal that even within an isogenic population, distinct transcriptional responses can be induced and co-contribute to survival. These responses are shaped by the cells pre-treatment transcriptional state and the mechanism of antibiotic action. Genetic and environmental perturbations, such as rpoS deletion and nutrient supplementation, shift pre-treatment cell states and alter persistence frequencies. Our findings establish the biological significance of transcriptional heterogeneity shaped by pre-treatment cell states, providing a systems-level framework for understanding persistence and suggesting strategies to enhance antibiotic efficacy by modulating cell states.

microbiology↗

bioRxiv2026

Enzyme Classification via Semi-Supervised Functional ResidueLearning

Predicting enzymatic function from a protein sequence is a fundamental task in protein discovery and engineering. In this paper, we present Semi-supervised Learning for Enzyme Classification (SLEEC): a semi-supervised learning framework that learns a function-aware protein representation for Enzyme Commision (EC) number prediction. SLEEC achieves SOTA performance on standard bench-marks and provides interpretable, residue-level annotations. We further demonstrate that our framework is robust to benign sequence modifications routinely observed in protein engineering workflows- such as appending functional tags- a desirable property that current ML frameworks lack. Our main technical contribution is a multiple sequence alignment (MSA)-based data augmentation technique for discovering sparse residue activations within a given enzyme sequence.

bioengineering↗

bioRxiv2026

Enhancing Pan-cancer Spatial Transcriptomics atSingle-cell Resolution with stPainter

Subcellular spatial transcriptomics technologies offer unprecedented views of tissue architecture but are fundamentally constrained by sparse gene panels and limited detection sensitivity. Current computational enhancement strategies typically rely on tissue-matched single-cell RNA sequencing (scRNA-seq) references and necessitate computationally intensive retraining for each dataset, impeding their scalability and clinical applicability. Here, we present STPAINTER, a conditional generative model that leverages a massive pretraining pan-cancer scRNA-seq atlas to universally enhance spatial transcriptomics data. Built upon a latent diffusion architecture with stochastic differential equation-guided generation, STPAINTER learns a universal manifold of cellular states to reconstruct genome-wide expression profiles from sparse spatial measurements. Uniquely, our pretraining paradigm enables zero-shot generalization and empowers downstream tasks by providing imputed transcriptomes and informative latent variables to enhance resolution at both the gene and cluster levels. Applied STPAINTER upon 6 spatial transcriptomics datasets of different cancer types, we demonstrate that our model empowers high-fidelity downstream analyses, including fine-grained subpopulation clustering and pathway enrichment. Furthermore, cross-validation with spatially resolved proteomics (CODEX) confirms the biological veracity of the imputed cellular landscapes. STPAINTER provides a robust, scalable framework for decoding complex tumor microenvironments without the need for auxiliary sequencing data.

bioinformatics↗

bioRxiv2026

EBNA1 INHIBITORS REVEAL CDC7 AND POU2F1 AS DIRECT FUNCTIONAL TARGETS IN EBV EPITHELIAL CANCERS

Epstein-Barr virus (EBV) latent infection is causally linked to several epithelial cancers, including endemic forms of undifferentiated nasopharyngeal carcinoma (NPC) and to a subtype of gastric cancer (GC). EBNA1 is the viral-encoded sequence-specific DNA-binding protein required for episome maintenance but also contributes to host-cell survival through multiple mechanisms including binding to host chromosome. We previously developed small molecule inhibitors of EBNA1 DNA-binding that block host cell cycle progression and growth of EBV+ tumors in vivo. However, the underlying molecular mechanisms of EBNA1 function and inhibition have not been completely elucidated. In this study, we employ VK1727 to inhibit EBNA1 DNA-binding to viral and cellular genomes in three EBV+ epithelial tumors (PDX C15, C666-1 and SNU719). We integrate EBNA1ChIP-seq and transcriptomic RNA-seq analyses to identify the cell cycle dependent kinase CDC7 and a stem cell transcription factor POU2F1 as direct functional targets of EBNA1 in these epithelial cancers. EBNA1 binding to CDC7 promoter and POU2F1 intron promotes RNA Pol II-pS5 to initiate transcription of these two genes. We show that CDC7 inhibitor Simurosertib is epistatic, while Bcl2 inhibitor Venetoclax is synergistic with VK1727 in the inhibition of EBV+ epithelial cancer cell proliferation and survival. Our study reveals new functional gene targets and pathways of VK1727 in EBV+ epithelial cancers that provide new biomarkers and combinatorial strategies to treat EBV-driven cancers. IMPORTANCEEBNA1 is essential for EBV latency and tumorigenesis, but its mechanism of action on host gene expression is not yet known. Small molecule inhibitors of EBNA1 DNA-binding block cell cycle progression and inhibit growth of EBV+ tumors. In this study, we use the EBNA1 small molecule inhibitor VK1727 to identify cellular gene targets that are bound by EBNA1 and deregulated by its pharmacological inhibition in EBV+ epithelial cancer cell lines and an NPC PDX mouse model. We identify cycle dependent kinase CDC7 and the stem cell transcription factor POU2F1 as EBNA1 bound and regulated genes important for EBV epithelial cancer proliferation. These findings not only decipher molecular mechanism how VK1727 blocks cell cycle progression and inhibits cell proliferation but also provide two new cellular gene targets and pathways for therapeutic intervention in EBV+ epithelial cancers.

microbiology↗

bioRxiv2026

Molecular architecture of the tumor microenvironment caused by BRCA1 and BRCA2 somatic mutations in lung adenocarcinoma

ObjectivesHomologous recombination repair (HRR) deficiency is associated with improved immunotherapy responses in non-small cell lung cancer (NSCLC) patients. The HRR genes BRCA1/2 are key regulators of DNA repair, yet their impact on the tumor microenvironment (TME) in lung adenocarcinoma (LUAD) remains unclear. MethodsUsing single-cell sequencing and multi-omics data, we characterized BRCA1/2 mutation-associated transcriptional programs, immune cell composition, and functional alterations in T cells, investigating the molecular and immune architecture of BRCA-mutant LUAD patients. ResultsBRCA1/2 mutations were associated with increased genomic instability and poor prognosis in LUAD patients, but predicted better clinical outcomes following immune checkpoint blockade (ICB) treatment. BRCA1 mutations correlated with an upregulated type I IFN/IFN-{gamma} signature and CD8+ T cell activation. BRCA2 mutations were associated with alveolar/stress/inflammatory responses and enhanced MHC-II antigen presentation, linked to CD4+ T cell differentiation. Both alterations coincided with reduced CD28 co-stimulation and CTL activity, hinting of immune evasion. We identified two tissue-resident memory T cell (Trm) subsets as predictors of clinical outcomes and ICB response. BRCA1 mutations were associated with CD8+ Trm expansion, whereas BRCA2 mutations linked to tumor CD4+ Trm expansion and peripheral T/NK cell cytotoxicity. Furthermore, a cancer-promoting program activated by BRCA1 mutation was vulnerable to histone deacetylase inhibitors, which inhibited LUAD tumor growth. ConclusionsThis study provides a preliminary characterization of the BRCA-mutant TME in LUAD patients, revealing distinct transcriptional and immune patterns that highlight differences in BRCA1/2-associated molecular architecture and offer a framework for improving therapy efficacy in LUAD.

cancer biology↗

bioRxiv2026

Structure and ligand specificity of Borrelia burgdorferi BmpA

BmpA is a putative substrate-binding protein from Borrelia burgdorferi, the causative agent of Lyme disease, an organism with limited metabolic capacity that relies on salvage pathways rather than de novo nucleotide biosynthesis. Here, we determine the crystal structure of BmpA to a resolution of 2.6 [A], revealing a conserved substrate-binding protein fold with a deeply buried nucleoside-binding pocket. Using microscale thermophoresis, we show that BmpA binds thymidine with high affinity followed by cytidine and adenosine, whereas binding to ribose, guanosine, inosine, and uridine was not detected. Structure-guided mutagenesis further demonstrates that two conserved aromatic residues (Phe27 and Phe176) are essential for thymidine recognition, as alanine substitution at either position abolishes detectable binding. Additionally, a Foldseek-based structural homology search identified related proteins across diverse bacterial and archaeal species that share a conserved overall fold and binding-site architecture despite low sequence similarity, consistent with an evolutionarily conserved scaffold that can accommodate distinct nucleoside ligands. Together, our work illustrates how conserved binding protein architectures enable selective nucleoside acquisition and provides a foundation for understanding nutrient uptake strategies in organisms with reduced genomes.

biochemistry↗

bioRxiv2026

Melatonin alleviates acid-induced stress in peanut (Arachis hypogaea L.) through physiological, antioxidative regulation and molecular defense mechanisms

Acidic stress severely restricts crop growth by disrupting nutrient uptake, redox homeostasis, and membrane stability, yet mitigation strategies remain limited. Here, we investigated the role of melatonin (MT) in regulating growth, photosynthesis, oxidative stress, antioxidant defense and proton transport in peanut seedlings under controlled hydroponics acidic (pH 4.0) and near-optimal (pH 6.5) conditions, and validated these findings in naturally acidic field soil (pH 4.3-4.5). Acid stress markedly reduced biomass accumulation, chlorophyll content, and redox balance, while enhancing ROS (H2O2) and lipid peroxidation (MDA). Exogenous MT application, particularly at 50-100 {micro}M, significantly improved shoot and root biomass, restored chlorophyll pigments and reduced H2O2 and MDA accumulation, with more pronounced effects under pH 4.0 than pH 6.5. MT strongly activated antioxidant enzymes (SOD, CAT, APX), while POD activity declined, reflecting melatonins dual role as both a direct ROS scavenger and a regulator of enzymatic redox networks. Notably, MT induced strong, dose-dependent upregulation of HL-ATPase genes (AH1 and AH2) in both leaves and roots under acidic conditions, suggesting enhanced proton extrusion, intracellular pH homeostasis, and stress adaptation. The soil validation experiment confirmed the agronomic relevance of these findings, where MT dose-dependent concentrations improved germination, vegetative growth, chlorophyll fluorescence (Fv/Fm), and yield-related traits under natural acidic conditions. Although MT also conferred benefits at pH 6.5, responses were generally moderate compared with acid stress. Collectively, these results demonstrate that MT enhances peanut tolerance to acid stress across both controlled and natural field-relevant environments, highlighting its potential application for sustainable crop production on low-pH soils.

plant biology↗

bioRxiv2026

Breast cancer radiogenomics analysis via computational perturbation on AI-driven multi-omics guided image synthesis

Radiogenomics offers a promising non-invasive approach for characterizing breast cancer (BC), yet its progress is often limited by the scarcity of cohorts containing matched imaging and multi-omics data. Recent advances in generative AI have enabled the synthesis of imaging phenotypes from genomic features, but prior work has focused on the combined influence of all genomic signals rather than isolating the effects of specific biological pathways. In this study, we introduce a perturbation-based radiogenomic framework that integrates multi-omics meta-genes with a conditional generative adversarial network (cGAN) to examine how pathway-level alterations influence synthetic BC MRI phenotypes. Seventeen meta-genes derived from Bayesian Tensor Factorization were perturbed at three levels (overexpression, base case, knockout) and synthetic DCE-MRI volumes were generated for each condition. Radiomic features were extracted using MedSAM-guided segmentation and PyRadiomics, followed by statistical evaluation using one-way ANOVA and Tukey post-hoc testing. Among the 17 pathways analyzed, only two meta-genes, representing cell cycle regulation and steroid hormone biosynthesis, produced significant and biologically interpretable changes in tumor size, heterogeneity, and textural patterns. These findings show that computational perturbation can uncover pathway-specific imaging signatures and offer mechanistic insights that complement traditional radiogenomics and explainable AI approaches. This work demonstrates the potential of perturbation-driven generative models to advance precision imaging genomics in BC.

cancer biology↗

bioRxiv2026

GmEBS7a-E2 complex dissociation hyperactivates ERAD to impair plant immunity against Phytophthora pathogens

Endoplasmic reticulum-associated degradation (ERAD) pathways are crucial for maintaining plant development and stress responses. While ERAD has been extensively studied for its role in regulating responses to abiotic stress, its specific manipulation by eukaryotic pathogens stress remains unclear. Here, we reported that soybean GmEBS7a, a plant-specific ERAD component, is targeted and stabilized by a transmembrane domain-containing effector Avh131 from Phytophthora sojae. GmEBS7a enhances plant disease susceptibility by increasing ERAD efficiency and ER stress sensitivity. Mechanistically, Avh131 competitively disrupts the interaction with GmEBS7a and the ubiquitin-conjugating enzyme GmUBC32, reducing ubiquitination of GmEBS7a and subsequent inhibition of its degradation. These findings demonstrate that excessive ERAD triggered by stabilized GmEBS7a and its partnering E3 ligase impairs the plants response to biotic stress. Our study uncovers a fine-tuning of the ER protein-folding capacity to promote infection, thereby expanding our understanding of ER-centered immunity during plant-pathogen interactions.

immunology↗