Biology subjects

Lin, Z.

Publications and source records attributed to Lin, Z..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Dehydration/1,6-addition-based Site-specific Bioconjugation Unveils Norepinephrinylation as a Widespread Post-translational Modification in the Cellular Proteome

Norepinephrine (NE) is a key neurotransmitter and hormone involved in diverse physiological and pathological processes. Beyond its canonical non-covalent signaling through binding adrenergic receptors, NE also induces protein post-translational modifications (PTMs), representing an emerging regulatory mechanism. Two major forms of NE-derived PTMs have been proposed: non-enzymatic norepinephrinylation (NEylation) of cysteine residues mediated by NE quinone and transglutaminase 2 (TG2)-catalyzed NEylation of glutamine residues. However, the cellular abundance, biochemical basis, and pathophysiological roles of NEylation remain poorly understood due to limited detection tools. Here, we report a novel bioconjugation chemistry for selective labeling and enrichment of the endogenous NEylation proteome in cell lines and tissues, which is based on acid-catalyzed dehydration and 1,6-addition to thiol probes. This strategy enables fluorescence imaging and chemical proteomic profiling, revealing NEylation as a widespread PTM that affects enzymatic activities of modified proteins, including protein tyrosine-protein phosphatase non-receptor type 11 (PTPN11). Visual Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=75 SRC="FIGDIR/small/731782v3_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@406ac5org.highwire.dtl.DTLVardef@121d6b9org.highwire.dtl.DTLVardef@98354corg.highwire.dtl.DTLVardef@d312ef_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2026

Predicting Immunotherapy Response Through Chemotherapy-Induced Tumor Microenvironment Remodeling

BackgroundChemotherapy before immunotherapy improves outcomes in multiple cancers, but the benefit is heterogeneous: only some tumors undergo the immune remodeling that makes subsequent immunotherapy effective, and no biomarker identifies these patients prospectively, leading to uniform use of chemo-immunotherapy and avoidable toxicity. MethodsA random forest model of tumor-microenvironment (TME) favorability, trained on 1,936 immunotherapy-treated patients, was applied to 334 paired pre-/post-chemotherapy biopsies across 19 studies to identify TME "converters," from which a 50-gene baseline signature was derived. The signature was tested in IMvigor210 (the only cohort containing both treatment arms) and in five independent chemo-immunotherapy validation cohorts, and for specificity against 22 immunotherapy-only cohorts. ResultsOf 209 paired-biopsy patients with unfavorable baseline TME, 61 (29%) converted to a favorable state after chemotherapy; converters were indistinguishable from non-converters at baseline by cell composition, motivating a gene-level signature. In IMvigor210, the signature discriminated responders among chemotherapy-primed patients with unfavorable baseline TME (AUC = 0.80, 95% CI: 0.67-0.94) but showed no signal in the trials immunotherapy-only arm (interaction OR = 4.42, p = 0.006). Across five independent chemo-immunotherapy cohorts, responders consistently scored higher than non-responders, yielding a significant pooled effect by meta-analysis (pooled g = 0.59, 95% CI: 0.11-1.08, p = 0.017) and individual significance in two (LUD2015-005, p = 0.009; GSE165252, p = 0.02). A meta-analysis of 22 immunotherapy-only cohorts constrained any effect there to a small magnitude (Hedges g = 0.08, 95% CI: -0.08 to 0.23), and five established immune signatures did not reproduce this treatment-context specificity. Converter tumors harbored coordinated baseline programs of proliferative stress, innate and adaptive immune readiness, and functional vasculature. ConclusionsA baseline transcriptomic signature predicts immunotherapy response specifically in chemotherapy-primed patients, a treatment-context specificity not shown by established immune biomarkers. These findings support prospective validation of the signature to guide chemotherapy- immunotherapy sequencing. SignificanceChemotherapy is now added to immunotherapy across a growing list of cancers, yet every eligible patient receives it even though only some tumors need it, and current biomarkers (PD-L1, tumor mutational burden, microsatellite instability) cannot identify which. We report the first biomarker to predict benefit from the chemotherapy component itself: a baseline gene-expression signature that flags likely responders in chemotherapy-primed settings while remaining silent under immunotherapy alone. This treatment-context specificity shifts the biomarker question from "who responds to immunotherapy" to "who needs the chemotherapy," pointing toward a way to spare patients unnecessary toxicity and rationally sequence chemo-immunotherapy.

Cancer Biology↗

bioRxiv2026

Language Modeling Materializes a World Model of Protein Biology

Proteins are fundamental to life. The full extent of their biology is beyond our ability to characterize with experimental approaches in the physical laboratory. Accurate digital representations could accelerate the discovery of protein biology through virtual experiments. We propose language modeling to learn unified and general representations that can be scaled to all of protein biology. Building on these representations, we develop a structure prediction model that exceeds the performance of established methods for biomolecular complex prediction across benchmarks, including for the interactions of antibodies with their targets. A simple search procedure yields high experimental success rates for the discovery of proteins with nanomolar binding affinities for both miniproteins and single-chain antibodies, a modality critical for therapeutic design. Study of the concepts in the language models representation space reveals a systematic organization aligned with the reductionist understanding of proteins developed through empirical science. Leveraging this organization, we generate a comprehensive map of protein biology encompassing over 6.8 billion sequences and 1.1 billion predicted structures, identifying connections across known and unknown biology. As a whole, this shows language modeling as a powerful substrate for representing the biology of proteins, operating across scales from the prediction and design of protein interactions at the atomic level, to identifying properties of proteins at different levels of granularity and abstraction, to the scale of mapping connections between proteins across billions of years of evolution.

bioinformatics↗

bioRxiv2026

Candida albicans reprograms host inosine metabolism to drive immunosuppressive macrophage polarization and gastric cancer carcinogenesis

Gastric cancer (GC) is strongly associated with changes in the gastric microbiome. However, the direct contribution of individual pathogenic species to tumor initiation and progression remains poorly defined. Here, we identified Candida albicans (C. albicans), a fungus that ranks as the most significantly enriched taxon in GC tissues, can directly promote gastric carcinogenesis. We found that when C. albicans alone was colonized into the gastric mucosa of mice, it induced the complete sequence of GC-associated preneoplastic lesions, including chronic gastritis, mucinous metaplasia, and atypical hyperplasia, with 16% of colonized animals progressing to low-grade intraepithelial dysplasia. In K19-C2mE transgenic mice, a model of spontaneous GC formation, infection with C. albicans significantly accelerated GC formation, with synergistic effects observed upon co-infection with the well-known gastric carcinogen, Helicobacter pylori. Mechanistically, C. albicans upregulated inosine levels in both gastric tissues and circulation. This inosine promoted polarization of macrophages toward an M2-like phenotype by activating the adenosine A2a receptor (A2aR), creats an immunosuppressive microenvironment that protects GC cells from the tumoricidal effects of anti-tumor immunity. Depletion of M2 macrophages or pharmacological inhibition of A2aR attenuated C. albicans-mediated tumorigenesis. Clinically, elevated inosine levels correlated with prior C. albicans exposure and poorer outcomes of GC patients. Our findings establish C. albicans as a direct pro-tumorigenic pathogen in GC and highlight the inosine-A2aR-M2 macrophage axis as a promising target for therapeutic intervention.

cancer biology↗

bioRxiv2026

Comprehensive Complete-Genome Analysis of Lactobacillaceae and Bifidobacteriaceae Reveals Strain-Specific Metabolic Interactions in Chinese Gut Microbiota

Bifidobacteriaceae and Lactobacillaceae are key probiotic families and widely used in food production, yet a comprehensive understanding of strain functions and their gut microbial interactions based on complete genomes remain understudied. Here we constructed a complete-genome dataset of 3,300 strains from these two families, including 1,151 newly isolated from China. Compared with draft assemblies, complete genomes substantially recovered a gene functional landscape encompassing stress tolerance, surface exopolysaccharide synthesis, nutrient utilization, and mobile genetic elements. Major species from both families exhibited a prevalence >60% in the Chinese population, far higher than that in US/Dutch cohorts. Notably, as a core probiotic species with remarkable genomic plasticity and gut-adaptive potential, Lactiplantibacillus plantarum stood out in our dataset for its enriched functional profile and was particularly abundant in the Chinese population. Moreover, compared with non-Chinese genomes, our isolates of key species displayed less metabolic complementarity and stronger competition with potentially pathogenic keystone species in the gut, thereby linking strain origin to enhanced probiotic potential and ecological fitness to benefit human gut health.

microbiology↗

bioRxiv2026

Single cell eQTL mapping reveals convergent glial-neuronal risk architecture in Parkinson's disease

Synucleinopathies affect [~]15 million people and are classically divided into neuronal (Parkinsons disease (PD), dementia with Lewy bodies) and glial (multiple system atrophy) disorders. Here we challenge this dichotomy. We functionally fine-map 90 PD GWAS signals across nine cell types in cortex and substantia nigra using disease-context, population-scale single-nucleus eQTL meta-analysis (N = 1,197), bulk brain eQTL analysis (N = 1,182), and Mendelian randomization. A stringent causal framework integrates single-nucleus allelic imbalance (snASE) with orthogonal validation. We identify 125 functional risk genes for 50 loci--nearly doubling supported genes--and assign genes and cell types to over half of GWAS signals. Unexpectedly, 51% of risk genes are regulated in glia, particularly oligodendrocytes and their precursors. Across cell types, risk converges on a shared glial-neuronal vesiculopathy network. These findings uncover a convergent glial-neuronal risk architecture and establish a single-cell atlas for context-aware gene discovery and precision therapeutics for PD.

genetics↗

bioRxiv2026

A Divergent Class of Arylamine N-Acetyltransferases Catalyzes Convergent Amidative Condensation of Polyketides in Manumycins Biosynthesis

Polyketides are prized for their structural complexity and therapeutic potential, yet the incorporation of amide bonds into their frameworks typically relies on linear, nonribosomal peptide synthetase (NRPS)-dependent assembly. The direct, convergent coupling of distinct polyketide chains via amide bond formation--an ideal strategy for combinatorial biosynthesis--has remained largely elusive. Here, we report the discovery of a novel family of arylamine N-acetyltransferases (NATs) from manumycin-type biosynthetic pathways that catalyze an unprecedented intermolecular amidative chain transfer/condensation between an acyl carrier protein (ACP)-tethered polyketide donor and a free polyketide acceptor. Biochemical, structural, and molecular dynamics studies reveal that the representative enzyme, ColC2, possesses a distinctive substrate-binding pocket that diverges from canonical arylamine NATs, conferring exceptional promiscuity toward diverse acyl donors and acceptors. We demonstrate the utility of this biocatalyst by coupling arylamines with either synthetic acyl-thioesters or polyketide synthase (PKS) machinery to generate a library of non-natural polyketide amides and manumycin derivatives. These findings establish a new paradigm for amide bond formation in polyketide biosynthesis and position arylamine NATs as powerful tools for the development of novel therapeutics through combinatorial synthesis.

synthetic biology↗

bioRxiv2026

A Haplotype-resolved Telomere-to-Telomere Pig Genome

Haplotype-resolved telomere-to-telomere (T2T) pig genomes have not been reported, but may be essential for xenotransplantation and interspecies chimerism. Here we describe fully phased paternal and maternal T2T assemblies of an Erhualian pig (Ssc_EHL), enabling chromosome-scale reconstruction at base resolution. We uncover 2,498 (paternal haplotype) and 2,577 (maternal haplotype) protein-coding loci previously unresolved in Sscrofa11.1, while maintaining high concordance for anchored gene models between haplotypes. Applying this haplotype-resolved T2T annotation to publicly available pig-to-human kidney xenograft transcriptomes further allows the resolution of xenograft cell states and reveals newly resolved, cell-type-enriched genes. Cross-species synteny and orthology analyses against human identified a subset of high-confidence pig-specific genes with limited human counterparts, thus, refining the genomic basis of interspecies divergence. By integrating these orthology features with organ transcriptomes, we further defined an Interspecies Chimerism Compatibility score to prioritize organ-enriched, highly conserved loci with minimal redundancy imbalance, providing haplotype consistent targets for engineering organ-deficient pigs. Together, this haplotype-resolved T2T pig genome provides a foundational resource for mechanistic studies and rational genome engineering in xenotransplantation and interspecies chimerism.

genomics↗

bioRxiv2026

Integrating Long-Read Structural Variant Analysis with single-nucleus RNA-seq to Elucidate Gene Expression Effects in Disease

Structural variants (SVs) are a major source of genetic diversity, yet how they impact cell types in complex brain diseases remains largely unexplored, partially due to limitations of short-read sequencing. Here, we addressed this fundamental question in Parkinsons disease (PD). generating long-read whole-genome sequencing (WGS) data for 100 post-mortem brain samples from a PD cohort, constructing a high-confidence catalog of 74,552 SVs. To resolve their functional impact, we integrated single-nucleus RNA-sequencing data from two brain regions from the same samples and focused functional analyses on SVs proximal to genes previously nominated as cis-regulated, potential causal targets of PD-associated GWAS loci. Using expression quantitative trait locus and allele-specific expression analyses, we uncovered SVs significantly associated with expression in specific cell types as well as effects shared across cell types. This study demonstrates the power of uniting long-read WGS with transcriptomics to uncover SVs underlying complex disease architecture with cell type resolution.

genomics↗

bioRxiv2026

Single-cell transcriptomic atlas of mouse oocyte development from growth to ovulation

Oocyte growth and maturation depend on tightly coordinated programs within oocytes and their surrounding granulosa cells, yet defining the transcriptional continuum of growing oocytes has been challenging due to their large size and the limitations of current droplet-based and spatial transcriptomic platforms. Here, we optimized a high-density array-based platform called Stereo-cell for high-throughput dual-modality profiling of large mouse oocytes, allowing for both the preservation of morphology and transcript capture. By integrating unsupervised transcriptomic clustering with cell morphological features, we delineated successive temporal windows from growing oocytes to metaphase II and uncovered stage-linked shifts from early programs toward later programs. We also profiled the ovarian somatic fraction, reconstructed granulosa-cell subtype relationships, and placed ovarian cell states in tissue context using single-cell-resolution spatial data.

developmental biology↗

bioRxiv2026

Chemical Proteomic Profiling of the Histaminylation Proteome in Cancer Cells Unveils Uncharted Epigenetic Marks on Core Histones

Histamine is a key signaling molecule in pathophysiology that can exhibit significant regulatory roles in diverse health and disease status. Besides the well-studied noncovalent interactions between histamine and its receptors, protein histaminylation is a recently discovered mechanism of action, through which histamine regulates cellular signaling pathways in a covalent modification manner. Histaminylation is an emerging protein post-translational modification, where an isopeptide bond is formed between the histamine primary amine and {gamma}-carboxyl group of glutamine through a transamidation reaction catalyzed by transglutaminase 2 (TGM2). However, due to the lack of efficient pan-specific antibodies targeting histaminylated glutamine, the histaminylation proteome in cells remains poorly explored. Here, we report the design and development of a novel N{tau}-propargylated histamine (N{tau}-PH) probe as well as its successful application in chemical proteomic profiling of the histaminylation proteome in cancer cells. Notably, new TGM2-catalyzed epigenetic marks on core histones, e.g., H2AX-Q84 and Q104 histaminylation, have been identified from cancer cells and verified. Lastly, the crosstalk between H2AX histaminylation and {gamma}H2AX formation was discovered in this study, suggesting that TGM2-mediated histaminylation plays a critical role in DNA damage responses.

biochemistry↗

bioRxiv2026

Several plant self-incompatibility systems may be controlled by atypical receptor-ligand interactions

Self-incompatibility (SI) is the single most important mechanism utilized by flowering plants to avoid self-pollination, thus preventing inbreeding and promoting outcrossing. Many plant SI systems are genetically controlled by a multi-allelic S-locus, containing two tightly linked genes that encode the female and male S-determinants. When pollen lands on a "self" pistil, interaction between cognate female and male S-determinants induces an SI signalling response, resulting in the failure of self-fertilization. Here, we review currently known SI systems that utilize receptor-ligand interactions to control pollen rejection on the stigma surface. Although detailed molecular and cellular information is only known for the SI systems in the Brassicaceae and Papaveraceae, it is apparent that the S-determinants of other SI systems (e.g. in the Poaceae and the Convolvulaceae) are likely to also utilize receptor-ligand interactions to prevent self-fertilization. Strikingly, although most of these systems all appear to utilize cysteine rich proteins (CRPs) as ligands to induce an SI response, only one of these receptors is a receptor-like kinase (RLK); the other "receptors" identified to date are proteins of unknown function, which we propose to be atypical receptors (ATRs). Although many of these receptors were identified some time ago, their atypical nature raises many questions, including how they function mechanistically, how they evolved and whether they are found in other plant cell-cell communication systems. Significance StatementSelf-incompatibility involves the precise recognition and rejection of incompatible pollen, often using a receptor-ligand type of interaction between male and female S-determinants. In this review we compare several S-determinants that appear to function as novel, atypical "receptors" (ATRs), with no kinase- or other distinct domains. We propose that the discovery of these novel "receptors" suggests that further, as yet, unidentified ATRs could be more widely utilized in angiosperms than currently appreciated.

plant biology↗

bioRxiv2026

AbNovoBench: a resource and benchmarking platform for monoclonal antibody de novo sequencing

Monoclonal antibodies (mAbs) are critical in disease diagnostics and therapeutics, yet the performance of mass spectrometry (MS)-based de novo sequencing remains incompletely characterized due to limited antibody-specific datasets and the absence of a standardized benchmark framework. Here we present AbNovoBench, a comprehensive framework for evaluating data analysis strategies for mAb de novo sequencing. It features the largest high-quality dataset to date, generated in-house, comprising 1,638,248 peptide-spectrum matches from 131 mAbs across six species and 11 proteases, supplemented by eight mAbs with known full-length sequence for end-to-end reconstruction assessment. Employing a unified training dataset, we systematically benchmarked 13 deep learning-based de novo peptide sequencing algorithms and three assembly strategies across peptide sequencing metrics (accuracy, robustness, efficiency, error types) and assembly metrics (coverage depth, assembly score). AbNovoBench (https://abnovobench.com) provides an online platform enriched with curated antibody MS resources and pre-trained models, enabling customizable antibody sequencing workflows, accelerating antibody-specific algorithms development, and improving reproducibility in proteomics.

systems biology↗

bioRxiv2026

Wing mechanosensory modulation of optic flow-sensitive descending neurons in butterflies

Visual motion processing in flying insects is strongly modulated by behavioural state, yet the mechanisms by which mechanosensory feedback contributes to this modulation remain poorly understood. Here we show that wing mechanosensation alone is sufficient to modulate a subset of optic flow-sensitive descending neurons (WFDNs) in butterflies. Airflow stimulation of the wings, mimicking flight conditions, increased baseline firing rates and reduced response latencies in WFDNs, without altering response gain or temporal frequency tuning. These effects indicate that mechanosensory modulation acts through mechanisms distinct from those governing other state-dependent changes in visual processing. Consistent with this interpretation, previous work has shown that baseline firing and response latency can be rapidly modulated, whereas gain changes arise through slower neuromodulatory pathways. Mechanosensory modulation was cell-type specific: the horizontally tuned WFDNL neuron was consistently affected across individuals, whereas other WFDN types were largely insensitive, likely reflecting the unilateral airflow stimuli used here. Interestingly, WFDNL modulation arose exclusively from mechanosensory input from the proximal area of the wing, not from distal wing deformation. This suggests that descending visual pathways require only coarse gain or excitability modulation rather than detailed information about wing shape or strain, leaving fast reflexive control of distal wing deformation to local ganglionic circuits. Together, our results demonstrate that wing mechanosensation selectively modulates visual descending pathways by altering excitability and timing rather than visual feature encoding, supporting the existence of multiple, parallel mechanisms for state-dependent visual modulation during flight.

neuroscience↗

bioRxiv2026

Uncovering the function of Wisp1 in whole-body glucose homeostasis: insights from Wisp1 knockout mice

WNT1-inducible signaling pathway protein 1 (Wisp1/CCN4) is a matricellular protein implicated in inflammation and metabolic dysfunction in obesity, yet its role in whole-body glucose metabolism remains unclear. In this study, Wisp1 knockout (KO) mice were analysed under physiological and high-fat (HF) diet conditions to define its impact on metabolic regulation. Neither physiological nor HF diet conditions revealed an effect of Wisp1 deficiency on whole-body glucose tolerance. However, male KO mice on a HF diet exhibited enhanced insulin sensitivity, lower insulin levels, and a marked reduction in adipose tissue inflammation, as evidenced by diminished macrophage infiltration and decreased pro-inflammatory cytokine expression in visceral fat. Additionally, beta cell mass expansion was attenuated in KO mice under HF diet, aligning with lower macrophage infiltration in islets. These findings suggest that improved insulin sensitivity in KO mice occurs independently of changes in glucose tolerance, likely due to mitigated adipose tissue inflammation. Thus, Wisp1 primarily modulates local adipose inflammatory responses, indirectly affecting islet adaptation to metabolic stress, rather than serving as a direct regulator of systemic glucose homeostasis.

physiology↗

bioRxiv2026

Rapid sensing and relaying of cellular hyperosmotic-stress signals via RAF-SnRK2 core condensates

Hyperosmolarity caused by drought, high salinity, or cold stress inhibits plant growth and crop productivity1,2. A conserved protein-kinase cascade of cytosolic B-RAFs and SnRK2s is rapidly activated upon osmotic stresses to initiate downstream adaptive responses, which represents one of the fastest known responses to osmotic stress in plants3-8. How the kinase cascade is activated by osmotic stress is unknown. Here, we show that Arabidopsis B4 subgroup RAFs have intrinsically disordered regions and directly sense both ionic and non-ionic hyperosmolarity by reversible condensation. B4-RAFs recruit and co-condense with subclass-I SnRK2s to phosphorylate and turn on SnRK2s, evading the non-condensable inhibitory A-clade PP2C phosphatases. This straightforward osmosensing and relaying module can be fully reconstituted in E. coli by co-expressing three components or in solution in a test tube using recombinant proteins. Our findings identify B-RAFs as the chief cellular osmosensors that detect low water potential by co-condensation, forming a signal hub with SnRK2s to orchestrate adaptive responses in plants, and represent an evolutionarily conserved osmosensing mechanism across kingdoms.

plant biology↗

bioRxiv2025

3'to 5'translation of linear mRNAs?

3[->]5 translation (termed "backward translation") mediated by eukaryotic circular RNAs has been reported recently. Whether linear mRNA can produce proteins through backward translation remained elusive. Here, we demonstrate that linear mRNAs can mediate backward translation in vitro. Backward translation was detected in human cells transfected with expression vectors used to produce linear mRNAs. Importantly, synthetic linear mRNAs could produce backward translation signal in multiple in vitro translation systems, with a level comparable to that of conventional 5 to 3 forward translation. Furthermore, we demonstrated that a single translation initiating sequence (TIS) was able to drive backward and forward translation in an in vitro experimental setup, with the efficiency of backward translation found to be significant lower than that of forward translation. In summary, this study further reinforces the notion of translation flexibility, demonstrates a broader applicability of backward translation and heralds a new strategy in synthetic biology.

cell biology↗

bioRxiv2025

Interleukin-17 directly triggers Epstein-Barr virus lytic reactivation in latently infected human B cells

Epstein-Barr virus (EBV) is a ubiquitous human gammaherpesvirus implicated in a wide spectrum of inflammatory and malignant diseases. Although EBV toggles between latent and lytic states, the host cues that control this switch remain incompletely defined. Interleukin-17A (IL-17A; hereafter IL-17), a signature Th17 cytokine, is abundant in EBV-associated tissues, and EBV products can augment IL-17 responses. Whether IL-17 directly modulates the EBV life cycle has remained unknown. Here we show that IL-17 alone is sufficient to induce EBV lytic reactivation in latently infected human B cells. Across RT-qPCR, immunoblotting, and RNA-seq, IL-17 increased the immediate-early regulator BZLF1 (Zta) and upregulated downstream early and late viral genes, consistent with activation of a transcriptome-wide lytic program. Culture supernatants from IL-17-treated cells contained elevated DNase-resistant extracellular EBV DNA, indicating productive replication with encapsidated genomes. Transcriptomic pathway analyses confirmed engagement of IL-17-linked signaling and highlighted inflammatory modules, including NF-{kappa}B and JAK-STAT. Gene Ontology analysis further enriched for regulation of B-cell receptor signaling and B-cell activation, situating IL-17 within B-cell inflammatory circuitry. Together, these findings identify IL-17 as a cytokine cue for EBV lytic entry and provide a mechanistic link between Th17-skewed inflammation and episodic EBV reactivation. This cytokine-driven pathway complements existing models centered on B-cell receptor signaling, hypoxia/HIF-1, COX-2/PGE2, and TGF-{beta} and motivates testing whether modulation of the IL-17/IL-17R axis can alter EBV reactivation in IL-17-rich settings. To our knowledge, this is the first demonstration that IL-17 alone directly triggers EBV lytic reactivation in human cells. IMPORTANCEEpstein-Barr virus (EBV) persists for life by maintaining latency with intermittent lytic reactivation, yet the physiological cues that initiate the latency-lytic switch remain poorly defined. Here we identify the Th17 cytokine interleukin-17A (IL-17) as a direct host trigger of EBV lytic reactivation in latently infected human B cells. IL-17 alone induced the immediate-early transactivator Zta, activated a transcriptome-wide lytic program, and promoted release of DNase-resistant extracellular EBV DNA consistent with encapsidated virions. Transcriptomic analyses confirmed engagement of IL-17-linked inflammatory modules and implicated convergence on signaling nodes shared with canonical B-cell receptor pathways. These findings establish a mechanistic link between Th17-skewed inflammation and EBV reactivation burden, providing a framework to interrogate how IL-17-rich microenvironments influence EBV dissemination and immunopathology and to evaluate whether targeting the IL-17/IL-17R axis can modulate EBV reactivation in disease settings.

microbiology↗