Biology subjects

Peng, Y.

Publications and source records attributed to Peng, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

CellMethMarker provides an integrated database of human cell- and tissue-type-specific DNA methylation markers

Cell- and tissue-type-specific DNA methylation markers provide epigenetic signatures of cellular identity and are widely used to infer cellular origin from bulk and single-cell methylomes. Existing resources mainly emphasize disease-associated biomarkers, methylome atlases, genomic annotations or RNA-based cell markers, leaving an unmet need for an integrated region-level resource dedicated to such markers. Here we present CellMethMarker (http://gu-zhanglab.hfcas.ac.cn/CellMethMarker), a curated database integrating 347,514 de novo markers derived from uniformly processed whole-genome and reduced-representation bisulfite sequencing datasets, 2,203,507 literature-derived marker records and harmonized metadata for 2,810 samples. CellMethMarker enables cell- and tissue-centered marker retrieval, coordinate-based search, genome-browser visualization, interactive methylation analysis and data download. In an independent single-cell methylome atlas, these markers recover the expected cell-type-associated methylation patterns, and a platform-matched reference built from them lowers the mean deconvolution error from 0.365 to 0.144. CellMethMarker therefore links region-level DNA methylation variation to cellular identity and supports methylome-based cell-type annotation and deconvolution.

bioinformatics↗

bioRxiv2026

Glioblastoma Hijacks Astrocyte Ribosomes to Feul Malignancy through Translatome Reprogramming

Cancer cells demand elevated protein synthesis, yet whether they directly requisition ribosomes from microenvironmental host cells remains unknown. Here, utilizing in vivo and in vitro ribosome tracing, we show that glioblastoma (GBM) cells hijack ribosomes from surrounding astrocytes via tunneling nanotube-like structures. This transfer supports GBM malignancy in both murine and patient derived models. Single cell RNA sequencing along with whole cell and cell source traceable ribosome profiling reveal that transferred ribosomes are translationally active and selectively reprogram the tumor translatome, prioritizing cell-cycle genes and driving interferon-response-mediated immune evasion. Through a genome wide CRISPR screen, we identify INTS12 as a critical mediator of ribosome transfer. Genetic inactivation or AAV-mediated knockdown of INTS12 impairs ribosome uptake, curbs translation and proliferation, remodels the immunosuppressive landscape, and extends survival in orthotopic models. Our study uncovers a parasitic translation-support mechanism in GBM, establishing INTS12 as a therapeutic vulnerability to disrupt ribosome transfer.

cancer biology↗

bioRxiv2026

Matrix stiffness shapes immunometabolic states and response to PD-1 blockade in gastric cancer

The extracellular matrix of solid tumors exhibits spatially heterogeneous stiffness, yet how matrix stiffness shapes antitumor immunity in gastric cancer (GC) remains unclear. Here, we integrated anti-PD-1 clinical cohorts, GC specimens, single-cell and spatial transcriptomic analyses, a syngeneic mouse model, and tunable-stiffness hydrogels to clarify the immunological consequences of matrix stiffness. High matrix stiffness was associated with collagen accumulation and immune exclusion, while higher stiffness-associated transcriptional scores were related to poorer response to PD-1 blockade. Matrix softening markedly reshaped the immune microenvironment and enhanced the efficacy of PD-1 blockade. Mechanistically, stiff matrices promoted F-actin remodeling and YAP nuclear enrichment, driving LDHA-dependent glycolytic reprogramming in GC cells that further impaired the effector function of CD8 T cells. Intriguingly, matrix softening was accompanied by enhanced IFN-{gamma}-responsive PD-L1 expression in GC cells, consistent with adaptive immune resistance that may contribute to the limited antitumor effects of matrix softening alone. These findings suggest that matrix remodeling alleviates spatial and metabolic constraints on antitumor immunity, providing a preclinical rationale for combining matrix softening with PD-1 blockade in GC.

cancer biology↗

bioRxiv2026

Pediatric brain charts reveal ADHD biotypes with distinct developmental, molecular, and therapeutic profiles

Attention-deficit/hyperactivity disorder (ADHD) exhibits profound clinical heterogeneity; however, its underlying neurobiological substrates remain unclear. Here, leveraging large - scale structural magnetic resonance imaging data from 12,663 typically developing children and 1,699 children with ADHD across Chinese and United States cohorts, we construct population specific pediatric brain charts via hierarchical Bayesian normative modeling to quantify individual deviations in cortical morphology. Data-driven clustering identifies two robust, cross - ethnically replicable ADHD biotypes: an infra - normal biotype characterized by widespread cortical thinning and a supra - normal biotype marked by cortical thickening. Multivariate analyses reveal distinct brain-behavior architectures: cortical deviations correlate preferentially with symptom severity in the infra-normal biotype but with both symptom severity and cognitive performance in the supranormal biotype. Clinically, the infra-normal biotype demonstrates a superior response to methylphenidate over atomoxetine, whereas the supra-normal biotype responds comparably to both. Transcriptomic analyses identify biotype-specific molecular signatures converging with ADHD genome-wide association study (GWAS) risk loci but exhibiting distinct expression patterns in the brain. These findings classify ADHD heterogeneity into neurobiologically distinct, clinically informed biotypes, providing a mechanistic framework for precision psychiatry in pediatric ADHD.

neuroscience↗

bioRxiv2026

ClonoDeconv: reference-based α - β paired recurrent clonotype proportion estimation from bulk-TCR sequencing

T cell receptor (TCR) sequencing is crucial when studying antigen-specific T cell responses and clonal dynamics. A key objective of TCR repertoire analysis is to identify recurring clonotypes across timepoints or different disease states, providing insight into the evolution of immune response. Bulk-TCR sequencing enables high-throughput profiling of TCR and {beta} sequences but lacks pairing information, while single cell TCR sequencing (scTCR-seq) retains pairing information but is limited by sensitivity, throughput, and costs. We present ClonoDeconv, a computational framework to deconvolute paired TCR {beta} ; clonotype frequency from bulk TCR sequencing experiments using a paired scTCR-seq reference. ClonoDeconv robustly estimated shared clonotype abundances from 5' RACE bulk-TCR datasets using a scTCR-seq reference from the same donor. Applied to longitudinal samples, ClonoDeonv successfully captured the expansion and contraction of rare virus-specific clones across timepoints. Taken together, ClonoDeconv provides a cost-effective and scalable approach for studying the longitudinal T-cell clonal dynamics.

bioinformatics↗

bioRxiv2026

Self-extending DNA recording with stochastic and programmed writing

Recording cellular histories requires new information to accumulate without erasing earlier records. Here we introduce Infinite Printer, a CRISPR recording architecture that couples self-extension to regeneration of a writable terminal context. A self-targeting prime-editing guide RNA (stpegRNA) directs repeat extension, while base editing generates diversity in situ without a separate insertion template for each character state. Earlier sequence remains upstream of the renewed terminus, linking substrate growth with record retention. Auxiliary pegRNAs specify payloads within a write-renew-write architecture. After three rounds of payload input, 4,436 distinct complete CCA-based records contained identities from all three pools. Longer AC/AT records retained shared upstream marks, and full-length sequence analysis resolved additional endpoint distinctions. Joint single-cell readout recovered 1,549 distinct records and 7,669 combinations across 12,302 transcriptome-linked cell labels from a single stpegRNA design. Spatial-transcriptomic readout recovered spacer records at 11,330 capture spots, linking record content to tissue coordinates and gene-expression profiles. Infinite Printer unites substrate renewal, sequence diversification and programmed writing with cell- and tissue-linked readout, providing a foundation for future lineage recording across large cell populations during mammalian development.

synthetic biology↗

bioRxiv2026

Role of Uridine Phosphorylase 1 (UPP1) in Pancreatic β-Cell Physiology and Its Dysregulation in Obesity and Type 2 Diabetes

Aims/hypothesis Fasting plasma uridine concentrations are elevated in obese mice and in individuals with type 2 diabetes (T2D), suggesting that uridine may function as a metabolic signal that adjusts insulin secretion to changes in metabolic demand. Here, we tested this hypothesis by determining whether uridine potentiates glucose-stimulated insulin secretion (GSIS) in mouse and human islets and by identifying uridine phosphorylase 1 (UPP1), the principal enzyme responsible for systemic uridine catabolism, as a key mediator of this effect. Methods Whole-body Upp1 knockout (KO) and {beta}-cell-specific Upp1 knockout (KO{beta}) mice were used to determine the requirement for UPP1 in uridine-potentiated glucose-stimulated insulin secretion (GSIS) and glucose-stimulated MAPK activation. Leptin-deficient and diet-induced obese mouse models were used to assess the impact of obesity on uridine responsiveness. UPP1 protein abundance and subcellular localization were examined in islets from obese mice and human donors spanning a range of glycemic control. Integrated single-nucleus RNA sequencing and ATAC sequencing were performed on wild-type and Upp1 KO mouse islets to characterize {beta}-cell molecular remodeling associated with UPP1 deficiency and altered responses to uridine. Results Uridine potentiated GSIS in islets from chow-fed and high-fat diet-fed mice, but not in leptin-deficient obese mice. Uridine also potentiated GSIS in human islets, although this effect progressively declined with worsening glycemic control. In mouse islets, uridine potentiation was accompanied by transient activation of the MAPK pathway. Both uridine-potentiated GSIS and uridine-enhanced glucose-stimulated MAPK activation were abolished in islets from Upp1 KO and KO{beta} mice. The requirement for a transient MAPK signaling was further supported by pharmacological inhibition of MEK and constitutive activation of MEK1. Leptin-deficient islets exhibited impaired glucose-induced MAPK activation together with increased UPP1 protein expression. In human islets, UPP1 protein abundance positively correlated with donor HbA1c and displayed heterogeneous subcellular localization. Integrated single-nucleus multiomic analysis identified UPP1 as an important regulator of {beta}-cell identity, function, and transcriptional responses to uridine. Conclusions These findings establish UPP1 as a key regulator linking pyrimidine metabolism to {beta}-cell function and identify impaired uridine responsiveness as a potential contributor to and/or consequence of {beta}-cell dysfunction during the progression of T2D.

molecular biology↗

bioRxiv2026

PlantRegMoD: An integrative and AI-driven multi-omics database for plant regeneration research

Plant regeneration underpins plant developmental plasticity, tissue culture, genetic transformation and crop improvement. Although numerous related omics datasets have been generated, specialized multi-omics databases for this field are still scarce. Here, we constructed PlantRegMoD, an AI-powered integrated database dedicated to plant regeneration. This platform hosts 20.54 TB standardized multi-omics data from 147 projects across 32 plant species and 2,593 samples. We established a unified hierarchical classification system covering five major categories and nine regeneration models, and curated 236 regeneration genes as well as their 28,190 homologs across 58 representative plant species. It contains extensive transcriptomic resources across all regeneration models, together with 196,423 single cells and over 8.81 million epigenetic peaks to dissect cellular heterogeneity and multi-layered epigenetic regulation. Equipped with nine online omics-related tools and a RAG-based intelligent Q&A system, PlantRegMoD greatly reduces bioinformatic barriers and serves as a robust resource for mechanistic, functional and evolutionary studies of plant regeneration.

plant biology↗

bioRxiv2026

A conserved transcriptional axis links cortical organization, developmental timing and autism-associated perturbations

Much of our mechanistic understanding of cortical development and neurodevelopmental disorders comes from studies in mice, yet translating these insights to humans rests on a fundamental assumption: that the cortex is organized according to conserved principles across species. Here, by independently decomposing human and mouse cortical transcriptomes, we test this assumption and identify a shared organizational axis extending from limbic anterior ventral (AV) to primary sensory posterior dorsal (PD) cortex. This axis aligns with conserved variation in cell-type composition, thalamocortical connectivity, myelination and excitation-inhibition balance. Its spatial topology emerges by mid-gestation and is progressively refined while remaining stable in orientation across subsequent development. What varies systematically along the axis is developmental timing: AV-enriched genes preferentially retained earlier cortical-construction features and progressively decline after birth, whereas PD-enriched genes preferentially reflected later maturation processes and progressively increased, with developmental rates graded along the axis. Across genetically distinct autism mouse models, developmental dysregulation converged on this axis, following a shared pattern that generally intensified toward the PD pole. The same axis also organized genotype-specific patterns of cortical volume alteration, while human autism risk genes showed corresponding enrichment along this transcriptional coordinate. Overall, we identify a conserved transcriptional axis that links cortical architecture to developmental timing and organizes the heterogeneous cortical effects of autism-associated mutations.

neuroscience↗

bioRxiv2026

A shared manifold for scalable temporal representations in self-paced timing

Adaptive behaviour often relies on tracking the passage of time, yet how distinct brain regions generate coherent temporal representations remains unclear. Using a self-paced interval timing task in mice, we show that heterogeneous single-neuron temporal firing profiles distributed across regions are organized within a shared ring manifold. Within this low-dimensional space, population activity evolves along a common trajectory across different intervals and encodes elapsed time in a relative reference frame. Different durations are not represented by separate neural states, but by modulation of traversal speed. These scalable dynamics arise from coordinated population-wide co-scaling of single-neuron activity and support trial-by-trial adjustments in timing behaviour. A cross-regional assembly of start neurons predicts, at interval onset, upcoming waiting duration and behavioural adjustments, linking initial population states to trajectory evolution. Together, these findings identify population traversal of a shared activity manifold as a mechanism for scalable temporal representation across brain regions.

neuroscience↗

bioRxiv2026

Real Science Is Harder Than Benchmarks: Evaluating Advanced AI Frameworks on Published Studies. II. Antibody Properties, Lipid-RNA Interactions

Artificial Intelligence (AI) frameworks for automating scientific research have shown strong performance on benchmarks, but their utility for real-world industrial research remains insufficiently characterized. Extending the analysis presented in the first paper of this series, we evaluated the same five advanced AI research frameworks (Kosmos, K-Dense, ToolUniverse, BioAgents from bio.xyz, and the AI Scientist-v2 from Sakana AI) on two more projects of high practical importance for biopharmaceutical development: predicting antibody developability properties with the use of pretrained protein language model embeddings, and modeling non-covalent lipid-RNA interactions in lipid nanoparticles with all-atom molecular dynamics (MD) simulations. The AI frameworks again showed genuine strengths, including unprompted identification of subtle methodological issues, successful use of pretrained protein embeddings, and consistent reporting of p-values and confidence intervals often absent from the original papers. However, no framework approached the scope of the original studies, and severe failures and hallucinations were observed. Our results confirm and extend the conclusion of the first paper that real published research from pharmaceutical companies that we tried to reproduce proved to be considerably harder for current AI frameworks than standard benchmarks suggest.

bioinformatics↗

bioRxiv2026

Mode of T cell priming durably shapes the TCR repertoire, effector function and α4β1 integrin expression of human virus-specific CD4+ T cells

The generation of an effective T cell response against an antigen depends on the recognition of the antigen by the T cell receptor (TCR), followed by T cell priming, initiating coordinated biophysical, biochemical and proliferative changes that drive differentiation into effector and memory clones. The immunological environments in which priming occurs, such as natural infection or vaccination, influences the quality and persistence of memory T cells, but the long-term impacts remain incompletely understood. Here, we investigate how the mode of priming shapes durable antigen-specific CD4+ T cell memory, utilising two cohorts 3-4 years after initial antigen encounter: individuals recovered from SARS-CoV-2 infection and infection-naive individuals who received a SARS-CoV-2 vaccination. Using ex vivo single-cell RNA sequencing, paired TCR sequencing and in vitro functional analyses, we characterise the transcriptional, clonal and functional profile of Spike-specific CD4+ T cells. Across both cohorts, CD4+ T cell responses against spike epitopes S166-180, S751-765 and S866-880, were immunodominant, with shared public TCR clonotypes indicating conserved antigen-recognition regardless of mode of priming. Despite this shared specificity, infection-primed individuals exhibited greater TCR repertoire diversity and lower CDR3{beta} sequence convergence. Transcriptionally, infection-primed cells exhibited a more cytotoxic and effector phenotype, while vaccine-primed cells preferentially adopted T follicular helper (Tfh)- and Th1-associated phenotypes. Infection-primed individuals also displayed enrichment of cell adhesion and integrin signalling pathways, with a greater proportion of spike-specific CD4+ T cells expressing 4{beta}1 integrin subunits, consistent with enhanced migratory and effector potential. Collectively, our findings demonstrate that the mode of antigen priming may influence the long-term CD4+ T cell memory states, influencing TCR repertoire diversity, functional differentiation and tissue-homing potential, years after the initial immune response.

immunology↗

bioRxiv2026

Myeloid-targeted RNA nanotherapeutics rewire cholesterol metabolism to unleash anti-tumor immunity in glioblastoma

Tumor-associated myeloid cells (TAMCs) dominate the glioblastoma (GBM) microenvironment and suppress anti-tumor immunity. Here, we identify cholesterol efflux via ABCA1 as a targetable metabolic checkpoint controlling TAMC immunosuppression in GBM. Reprogramming TAMC cholesterol metabolism using TAMC-targeting lipid nanoparticle encapsulating ABCA1 siRNA (ABCA1 LNP) converts TAMCs into potent antigen-presenting cells with enhanced pro-inflammatory activity and antigen-presenting capacity, thereby inducing T cell activation, expansion, and tumor infiltration. Mechanistically, ABCA1 blockade induces cholesterol accumulation in TAMC membranes, promoting lipid raft formation and enhancing MHC-I-mediated antigen presentation. In multiple preclinical GBM models, ABCA1 LNP treatment dramatically induces T cell priming, extends animal survival, and overcomes GBM resistance to radiotherapy and immune checkpoint therapy. This efficacy was well-maintained in stem-like and recurrent GBM models, GBM patient specimens, and a renal cell carcinoma model. Altogether, our work identifies cholesterol efflux as a targetable metabolic vulnerability in TAMCs to overcome therapy resistance in myeloid-rich, immunologically "cold" tumors.

immunology↗

bioRxiv2026

FXR-mediated recruitment of PPP1CB suppresses SMAD2/3 phosphorylation to mitigate pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal interstitial lung disease with limited treatment options and poorly understood molecular underpinnings. Dysregulated TGF-{beta}/SMAD signaling is a key driver of fibrotic remodeling, promoting persistent myofibroblast activation and excessive extracellular matrix deposition. Here we identify the Farnesoid X receptor (FXR), a bile acid activated nuclear receptor, as a previously unrecognized suppressor of pulmonary fibrosis. FXR expression is significantly reduced in lung tissues from patients with PF and in myofibroblasts derived from BLM-induced mouse models, correlating inversely with fibrosis severity. Genetic ablation of FXR exacerbates BLM-induced pulmonary fibrosis by promoting fibroblast hyperactivation and dysregulation of the TGF-{beta}/SMAD signaling pathway. Mechanistically, we identify PPP1CB as a previously unrecognized FXR-interacting protein in primary myofibroblasts derived from IPF patients. We further show that FXR both increases chromatin accessibility at the PPP1CB locus and assembles a functional complex with PPP1CB, which in turn promotes SMAD2/3 dephosphorylation and suppresses their nuclear translocation. Notably, the clinical-stage FXR agonist TERN101 exhibits potent therapeutic efficacy in a BLM-induced mouse pulmonary fibrosis model. These findings establish FXR as a critical antifibrotic regulator in lung tissue and suggest that pharmacological activation of FXR may offer a promising therapeutic strategy for IPF.

cell biology↗

bioRxiv2026

An allosteric pocket in KV1.3 defines a distinct chemical space for immunomodulator design

KV1.3 is a validated autoimmune drug target, yet all disclosed inhibitors converge on a narrow set of conserved binding sites, suffering from poor selectivity or clinical failure. Whether KV1.3 harbors a distinctive, druggable pocket amenable to selective targeting has remained unknown. Here we report MPiN, a highly selective, state-dependent KV1.3 inhibitor with in vivo efficacy in a mouse psoriasis model, which engages a previously uncharacterized extracellular allosteric pocket framed by the PP1-PP2 turret loops, the pore helix and the outer S5/S6 helices, acting through a bidirectional pore-to-sensor coupling that simultaneously constricts the selectivity filter and facilitates the voltage sensor toward activation. Unexpectedly, despite the extensive structural conservation of this pocket across KV1 paralogs, subtype selectivity is dictated by the peripheral residues G427 and H451, which define pocket geometry without directly contacting the ligand, thereby establishing a geometry-driven "non-contact selectivity" mechanism. By opening an unrecognized, structurally distinct chemical space on KV1.3 and redefining how selectivity is achieved within a conserved channel family, this work lays the structural and conceptual foundation for rational, structure-guided design of next-generation KV1.3 immunomodulators.

biochemistry↗

bioRxiv2026

Human CD8-iTreg are potent GVHD suppressors and tumoricidal effectors by release of Granzyme-K+ Supramolecular Attack Particles

Regulatory CD8+ T-cells (CD8+ Treg) are a distinct yet understudied T-cell subset capable of simultaneous immunosuppression and cytolysis. Here, we characterized induced human CD8+ Treg (CD8-iTreg) generated from peripheral blood CD8+CD25- T-cells using anti-CD3e mAb-loaded artificial antigen presenting cells, IL-2, TGF{beta}, and Rapamycin. These CD8-iTreg differentiated into a stable, highly proliferative bifunctional population with suppressive activity comparable to CD4-iTreg while retaining cytolytic capacity similar to conventional CD8 cytotoxic T lymphocytes (CTL). Multi-parameter spectral flow cytometry and single-cell RNA-seq revealed a distinct immunoregulatory signature: a predominantly Treg-like profile marked by tissue-residency marker CD103 with increased canonical Treg markers (FoxP3, HELIOS, CD25, CD39, CTLA-4, CCR4, and IL-10) and reduced pro-inflammatory cytokines. A unique cytotoxic program was marked by elevated Granzyme-K (GzmK) and Thrombospondin-4 (Tsp-4), a thrombospondin family extracellular matrix glycoprotein upregulated in activated CD8+ T-cells. Cytolysis was primarily mediated by Perforin (Prf) and multiple Granzymes packaged into Tsp-4 supramolecular attack particles (SMAPs), with GzmK contributing to both cytotoxic and suppressive functions. After anti-CD19scFv CAR (CAR19) transduction, CAR19+ CD8-iTreg showed superior in vivo anti-tumor efficacy compared with CAR19-CTLs, significantly reducing tumor burden and prolonging survival in a CD19+ Nalm-6 human leukemia xenograft model while maintaining low pro-inflammatory cytokine production. In a xenogeneic graft-versus-host disease (GVHD) model with residual human leukemia, CAR19 CD8-iTreg inhibited GVHD lethality and controlled tumor growth without increasing systemic inflammation. Together, these findings support CD8-iTreg-based CAR therapies as a strategy to retain potent anti-leukemic activity while limiting inflammatory toxicities of conventional CAR T-cells, properties particularly beneficial in treating auto- and allo-immune diseases. One sentence summaryCD8-iTreg drive parallel tumoricidal and immunoregulatory functions mediated by releasing Tsp-4+ SMAPs containing granzyme K.

immunology↗

bioRxiv2026

Persistent Post-Inflammatory Matrix Stiffening Defines a Premalignant Mechanical Niche in Ulcerative Colitis-Associated Neoplasia

Patients with long-standing ulcerative colitis (UC) remain at risk for colorectal neoplasia even after overt inflammatory activity improves, suggesting that repaired mucosa may retain residual tissue-level abnormalities. Whether extracellular matrix remodeling leaves a persistent mechanical cue that contributes to early neoplastic remodeling is unknown. Here we identify post-inflammatory matrix stiffening as a premalignant mechanical niche in UC-associated neoplasia. In human colonic biopsies, collagen remodeling and atomic-force-microscopy-based mucosal stiffness increased from non-UC controls to UC and UC-associated dysplasia. A stiffness-associated transcriptional program was also enriched in histologically non-dysplastic mucosa from patients with UC-associated neoplasia. In mouse models, colonic stiffness increased along the colitis-to-tumorigenesis axis and remained elevated during apparent recovery, when epithelial permeability, junctional protein loss, crypt proliferation and nuclear {beta}-catenin accumulation persisted despite reduced disease activity. Stiffness-controlled intestinal epithelial cultures showed that stiff substrates were sufficient to disrupt ZO-1 organization and enhance {beta}-catenin redistribution, particularly under TNF- stimulation. Pharmacological matrix normalization with {beta}-aminopropionitrile partially restored barrier organization and attenuated early epithelial remodeling in vivo. Single-cell profiling identified a stiffness-associated MMP7-positive/YAP-active epithelial state that was enriched in collagen-rich regions and reduced after matrix softening. Inhibition of YAP or MMP7 attenuated stiffness-associated junctional disruption and {beta}-catenin redistribution. These findings suggest that inflammatory recovery and mechanical recovery can be uncoupled, and that persistent mucosal stiffening provides a tissue-level mechanism by which chronically injured UC mucosa may remain biologically vulnerable to premalignant epithelial remodeling.

Cancer Biology↗

bioRxiv2026

Virus-human protein-protein interactions predict viral phenotypes

Viral phenotypes such as host and tissue tropism are critical determinants of viral infection and transmission. Inferring viral phenotypes presents unique challenges compared to cellular organisms, as viruses rely entirely on host machinery for replication and survival. Current methods for predicting viral phenotypes mainly rely on viral genomic data, often overlooking host-related information. Here, we evaluated the utility of predicted virus-human protein-protein interactions (PPIs) in inferring diverse viral phenotypes using machine-learning algorithms. For predicting human infectivity, a PPI-based machine learning model outperformed both virus genomic and protein sequence-based models that used large language model embeddings. It also surpassed previous methods that incorporated both viral and host genomic data. The human proteins identified by the model were significantly enriched in functions related to viral infection and immune response. In predicting various phenotypes of human RNA viruses, PPI-based models performed better than virus sequence-based models in forecasting virulence, human transmissibility and transmission routes, while showing comparable performance to genomic sequence-based models in predicting tissue tropism. Finally, we demonstrated that a PPI-based model could distinguish high-risk HPV genotypes from low-risk ones. Proteins associated with high-risk HPV were involved in apoptosis and immune regulation, whereas those linked to low-risk HPV were enriched in telomere maintenance and DNA repair. Collectively, this study is the first to demonstrate the value of predicted virus-human PPIs in inferring viral phenotypes, thereby enhancing our understanding of the molecular mechanisms underlying these phenotypes. It also provides effective tools for risk assessment of emerging viruses, contributing to improved pandemic preparedness.

bioinformatics↗