Biology subjects

Xu, Y.

Publications and source records attributed to Xu, Y..

At least 181 records · Page 10Linked to original sources

bioRxiv2025

Demonstrating and engineering the de novo synthesis of two aromatic chemicals estragole and anethole in Escherichia coli

Estragole and anethole are the major flavoring and aroma components of the essential oils extracted from basil (Ocimum basilicum L.), anise (Pimpinella anisum), star anise (Illicium verum), and fennel (Foeniculum vulgare). Besides, they also exhibit bioactivities, such as antioxidation, antimicrobial, immunomodulation, inti-inflammation, and anti-diabetes. These properties make them being faced with substantial applications in the industries of food, cosmetics, pharmaceutics, and agriculture. Commercial estragole and anethole are currently obtained from extraction from their original plants, which suffers from unstable quality and resources. Microbial synthesis is a promising alternative approach to sustainably obtain estragole and anethole, but has not been achieved. In this study, we modularly redesigned the synthetic pathways based on the Escherichia coli chassis. Firstly, a p-coumaryl alcohol over-accumulator (436.28 mg/L) was engineered to facilitate the validation of the undemonstrated downstream module. De novo biosynthesis of estragole and anethole was achieved by stepwise analysis and BioBricks assembly. The intracellular availability of S-adenosyl-L-methionine (SAM) was revealed to be the key limiting factor, and was enhanced by deregulating the synthesis. Finally, the productions of estragole and anethole were improved by 246.88% and 202.44% compared with the initial strains. This study represents the first synthesis of estragole and anethole in microbial chassis, and the demonstration of microbial synthesis of propenyl phenols. Besides, it provided an alternative sustainable approach to obtain flavoring and aroma chemicals.

synthetic biology↗

bioRxiv2025

Reciprocal Homoeologous Replacement of MYB Factors Drives the Evolutionary Trade-off between Yield and Fiber Quality in Cotton

The long-standing phenotypic trade-off between Upland cotton (Gossypium hirsutum, high yield) and Sea Island cotton (G. barbadense, high quality) represents a major bottleneck in cotton breeding and industrialization. Despite rapid advances in genomics, the genomic structural variations driving the divergence of these two domestication strategies, and their subsequent impact on downstream transcriptional networks, remain unclear. This study integrates multi-tissue transcriptomic atlases spanning the full growth period with pan-genomic analyses of both Upland and Sea Island cotton, proposing a "Reciprocal Selective Retention (RSR)" strategy adopted by the two species during evolution. Transcriptomic analysis revealed that while the transcriptional chassis of the two species is highly conserved, a drastic "phase inversion" occurs during fiber development. Sea Island cotton appears to trade off for quality by specifically activating a "delayed elongation" module (at 20 DPA), whereas Upland cotton initiates a "precocious filling" program to pursue yield. Further Weighted Gene Co-expression Network Analysis (WGCNA), combined with genomic Presence/Absence Variation (PAV) analysis, identified a set of key transcription factors exhibiting a "3-vs-3" reciprocal loss pattern. Upland cotton specifically retained CRF10, WIND1, and MYB93, constructing a genetic foundation of "robust root system and strong regeneration" to support high yield. Conversely, Sea Island cotton specifically retained MYB111 and ERF105/017 to maintain long-staple characteristics and environmental buffering. Whole-genome structural variation and microsynteny analyses confirmed that these differences stem from asymmetric physical deletions (e.g., a 5 kb deletion in MYB111) or fragment sequence collapse (e.g., a 15.9 kb sequence divergence in MYB93) on homologous chromosomes. The RSR model proposed in this study not only offers a novel insight into the genetic roots of the negative correlation between yield and quality but also provides clear genomic targets for precision improvement using gene-editing technologies such as CRISPR.

genomics↗

bioRxiv2025

Functional modules predict cancer-relevant genetic interactions in mammalian cells

Genetic interactions can reveal gene function and identify disease-relevant synthetic lethals, but resource-intensive screening in human cells constrains experimental scope and limits our understanding of how generalizable sparse hits are. Here, we leverage principles from yeast genetic networks to identify human gene modules involved in receptor tyrosine kinase signaling and DNA damage response that are predicted to be enriched for genetic interactions, then use our enCas12a-based In4mer combinatorial knockout platform to efficiently screen these modules across diverse cancer cell lines. We identify hundreds of unreported synthetic lethals, including a dense network within the protein N-linked glycosylation machinery that shows both evolutionary conservation and network rewiring, and we confirm that interactions discovered in 2D cell culture are maintained in more physiologically relevant models. Critically, a meta-analysis within and between screens highlights sources of variation in published results, reveals the potential for false positives in screens with many essential genes, and demonstrates the need to move beyond DDR for actionable synthetic lethalities.

systems biology↗

bioRxiv2025

An obligatory role for AgRP neurons in maintaining body temperature during time-restricted feeding

Homeotherms maintain a steady body temperature through thermoregulation, a process critical for survival during fasting, in which the brain has to defend energy-costly body temperature while reducing energy expenditure to conserve energy reserve; however, the neural basis for defending body temperature remains unclear. Here, we demonstrated that AgRP neuron lesion led to lethality during time-restricted feeding but no obvious impact on HFD-induced obesity or obesity-reducing responses to glucagon-like peptide-1 receptor agonism. The lesion disrupted adaptive feeding behaviors during time-restricted feeding and reduced motivational feeding. Notably, the lethality was caused by hypothermia instead of reduced food intake. The lesion also caused failure in body temperature maintenance during acute fasting in cold. Fasting-induced activation in AgRP neurons was abrogated when mice were placed in a warm environment. Our results identify the physiological role for AgRP neurons in defending body temperature during restricted feeding but dispensable for body weight regulation with food ad libitum.

neuroscience↗

bioRxiv2025

TUPAD: A Tn5-Mediated, Pre-amplification/Adapter-Dimer-Free Platform for Ultra-Uniform, One-Step PGT Profiling with High Stability and Broad Compatibility

High-throughput sequencing stands as a cornerstone of clinical molecular diagnostics, particularly in preimplantation genetic testing (PGT)--a key application where the selection of chromosomally normal embryos is critical to enhancing in vitro fertilization (IVF) success rates. A fundamental challenge inherent to PGT, however, lies in the ultra-low gDNA input (typically <100 pg) from embryo biopsies. To mitigate this limitation, traditional workflows rely on whole genome amplification (WGA) technologies, such as MDA, PicoPlex, and MALBAC. Yet these WGA-based protocols inherently entail pre-amplification of gDNA prior to standard library construction---a step that introduces significant coverage bias and compromised uniformity. These are intrinsic flaws irreparable by downstream library preparation or bioinformatics analysis, ultimately leading to clinical uncertainty in the interpretation of copy number variations (CNVs). In this study, we developed TUPAD (Tn5-Mediated, Uniform Pre-amplification-free and Adapter-Dimer-Free Library preparation), a transformative technology that bypasses the limitations of traditional WGA. By engineering a novel adapter-dimer-free transposon system, TUPAD enables high-efficiency library construction from as little as 1 picogram (pg) of gDNA. This breakthrough allows for a pre-amplification-free workflow, effectively eliminating the primary source of amplification bias. Compared to existing WGA standards, these advantages are fully retained in embryo biopsy and positive sample testing, TUPAD consistently generates highly uniform library data, significantly enhancing the detection limit and accuracy of CNVs and other genomic variants. Beyond these performance advantages, TUPAD also cuts wet-lab processing time by 50%. Practical validation confirms TUPAD results are stable, reliable, with proven practical utility in PGT testing.

molecular biology↗

bioRxiv2025

Synchronized Latency Reversal and Immune Clearance by a Multifunctional Fusion Protein Enables HIV-1 Reservoir Reduction

Strategies that concurrently reactivate latent reservoirs and enhance immune-mediated clearance hold significant promise for achieving an HIV cure. Here, we developed hyperIL-15xsCD4-Fc (15xsCD4-Fc), a fusion protein that integrates latency reactivation, targeted immune engagement, and effector-mediated killing into a single molecule. This agent not only potently reverses HIV-1 latency in CD4+ T cells from people living with HIV-1 (PLWH) through coordinated IL-15 receptor signaling and sCD4-mediated HIV-1 envelope (Env) engagement, but also enhances antigen-specific CD8+ T cell response in PBMCs derived from PLWH. Furthermore, 15xsCD4-Fc enables Env-specific elimination of reactivated latently infected cells by NK cells while preventing off-target cytotoxicity. In PBMCs from PLWH, 15xsCD4-Fc reduced replication-competent HIV-1 DNA by 93.8%. In antiretroviral treated HIV-1-infected humanized mice, the molecule demonstrated both safety and efficacy in diminishing viral reservoir in lymphoid organs. This spatiotemporally coupled approach to reservoir exposure and immune recognition establishes a clinically viable strategy for clearing the HIV-1 reservoir. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=195 SRC="FIGDIR/small/693434v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@8f8f0org.highwire.dtl.DTLVardef@10f63f7org.highwire.dtl.DTLVardef@16c1de2org.highwire.dtl.DTLVardef@11e1787_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2025

A haplotype-resolved T2T genome assembly of Indigofera pseudotinctoria reveals the genetic basis of flavonoid biosynthesis in Chinese Indigo

Indigofera pseudotinctoria, commonly known as Chinese Indigo, is a multifunctional leguminous shrub widely distributed in East Asia, valued for its medicinal, ecological, and forage importance, and naturally adapted to drought and nutrient-poor soils. However, the absence of genomic resources has hindered insights into the genetic basis of its bioactive metabolites and adaptive traits. Here, we present a haplotype-resolved, telomere-to-telomere (T2T) reference genome of I. pseudotinctoria, which represents the first complete genome within the genus Indigofera. By integrating PacBio HiFi sequencing, Oxford Nanopore ultra-long reads, and Hi-C chromatin conformation sequencing technologies, we successfully constructed two gap-free haplotypes assemblies (647.38 Mb and 657.52 Mb), characterized by high BUSCO completeness and QV scores, and fully captured all telomeric sequences. Comparative analysis between haplotypes revealed extensive synteny but notable structural heterozygosity but notable structural heterozygosity. Approximately 46% of structural variations overlap with genic or regulatory regions, leading to allele-specific expression divergence. Between the two haplotypes, we identified 2,607 and 2,331 haplotype-specific genes, reflecting a complementary functional specialization in defense and repair versus metabolism and growth. Integrative transcriptomic and metabolomic profiling across six tissues reconstructed the flavonoid biosynthetic network and identified MYB, bHLH, NAC, WRKY, and ERF transcription factors regulating five key pharmacologically active flavonoids (Calycosin, Butein, Sulfuretin, Chrysoeriol, and Genistin). These results collectively uncover the haplotype-specific regulatory and structural basis of Indigofera pseudotinctoria and establish a high-quality genomic framework for evolutionary, medicinal, and metabolic engineering studies in leguminous plants, and provide a framework for molecular breeding and bioactive compound discovery in medicinal legumes.

genomics↗

bioRxiv2025

Reliable delineation of Clostridioides difficile and related members of the family Peptostreptococcaceae using phylogenomics and spore coat protein-specific molecular markers

Traditional bacterial classification relies on phenotypic traits (e.g., morphology, metabolic profiles), but these methods lack resolution for closely related taxa and are biased by culture conditions. While 16S rRNA gene sequencing is a widely used molecular complement, it fails to resolve closely related Peptostreptococcaceae species, including Clostridioides difficile. These limitations have caused family-level taxonomic confusion and ambiguous Clostridioides genus boundaries, hindering clinical identification of pathogenic strains and posing public health risks. To address these limitations, we developed an integrated approach combining multi-scale phylogenomic and protein-based molecular evidence, adopting a hierarchical workflow: first, constructing a 16S rRNA phylogeny of 151 Firmicutes strains to demonstrate traditional marker inadequacies; second, generating a whole-genome protein phylogeny of 51 representative Peptostreptococcaceae genomes and defining taxonomic boundaries via Average Amino Acid Identity (AAI); third, analyzing spore-associated protein patterns across C. difficile isolates and related genomes. Results revealed high conservation of C. difficile spore coat/exosporium proteins and clear genus-level phylogenetic distinctiveness of these proteins. Combined with AAI-validated whole-genome data, our findings support key Peptostreptococcaceae taxonomic revisions: redefining polyphyletic Romboutsia, reassigning Eubacterium tenue to Paeniclostridium, and elevating Alkalithermobacter to genus status. This study establishes spore coat proteins as core taxonomic markers for spore-forming bacteria, with our integrated strategy overcoming traditional limitations to improve classification accuracy and C. difficile surveillance. ImportanceConventional classification struggles to resolve closely related Peptostreptococcaceae species (e.g., C. difficile). We developed an integrated framework combining 16S rRNA sequencing, whole-genome protein analysis, and spore trait assessment, with a key innovation: identifying spore coat/exosporium proteins as robust, conserved taxonomic markers. This approach enabled three pivotal Peptostreptococcaceae revisions--redefining Romboutsia, reassigning Eubacterium tenue to Paeniclostridium, and elevating Alkalithermobacter to genus rank. The findings resolve a longstanding microbial systematics bottleneck for spore-forming bacteria, provide critical taxonomic context for C. difficiles precise monitoring and prevention, and expand taxonomic markers beyond nucleic acid-based methods. This advances classification precision, critical for microbial ecology, pathogenesis, and industrial microbiology research.

genomics↗

bioRxiv2025

RamanOmics Decodes Spatial Vibrational-Molecular Architecture and Rewiring in Aging and Repair

Aging and tissue repair involve multilayered and spatially heterogeneous remodeling across transcriptional, biochemical, and cellular dimensions, yet prevailing definitions rely on isolated molecular markers that obscure how biochemical and transcriptional states co-evolve in tissues. Here we present RamanOmics, a multimodal framework that integrates single-nucleus RNA sequencing (snRNA-seq), spatial transcriptomics, and label-free Raman imaging to map the spatial vibrational-biochemical and molecular architecture of aging and senescence directly in intact tissues. Applied to mouse lung and skin, RamanOmics generates spatially resolved biochemical-molecular maps revealing tissue-specific programs: lung senescent cells are enriched for extracellular matrix (ECM) remodeling and TGF-{beta} signaling (Serpine1, Dab2, Igfbp7), whereas skin senescence is dominated by keratinization and barrier homeostasis modules (Krt10, Lor, Sbsn). Across tissues, we identify a conserved branched-chain fatty-acid-linked biochemical profile and Raman signature (1131-1135 cm-{superscript 1}) that robustly marks p21 senescent cells. To unify these layers, we develop a machine learning derived "multimodal barcode" that quantitatively integrates biochemical and transcriptional features, enabling non-destructive identification of senescence in situ. In a wound-healing model, RamanOmics further reveals coordinated reactivation of barrier-repair programs in senescent cells, marked by upregulation of Krt10, Lor, Sbsn, Sfn, and Dmkn together with matching increases in lipid-associated Raman signatures, confirming biological generalizability beyond steady-state aging. By directly integrating gene programs to spatial vibrational-biochemical states, RamanOmics provides a general framework and resource for scalable, multimodal profiling of cellular states.

systems biology↗

bioRxiv2025

In vitro study of the growth, reproduction and pathogenicity responses of Fusarium oxysporum f. sp. zingiberi to autotoxins from ginger

Long-term monoculture of ginger triggers Fusarium wilt, a disease caused by Fusarium oxysporum f. sp. niveum (Foz). However, the role of autotoxins in promoting pathogen growth remains unclear. Four representative autotoxins, syringic acid, coumarin, ferulic acid and 7-Hydrooxycoumarin were selected to investigate their allelopathic effects on the growth, reproduction, and virulence-associated traits of Foz. The responses of Foz to these compounds exhibited notable variations, which may be attributed to the structural differences among the autotoxins. The autotoxic compounds differentially enhanced the key pathogenic traits of Foz. Syringic acid was the most effective stimulant of mycelial growth and cell wall-degrading enzymes activity, concurrently boosting mycotoxin production via upregulating FUB3 gene expression. Ferulic acid was the most potent promoter of sporulation and biomass accumulation, whereas 7-Hydroxycoumarin most effectively stimulated conidial germination. Notably, coumarin suppressed mycelial growth but strongly induced mycotoxin synthesis in Foz. These results provide mechanistic insights into how autotoxins in ginger monoculture systems promote Fusarium wilt.

microbiology↗

bioRxiv2025

Closed-loop heart rate regulation based on medulla stimulation

Cardiovasular diseases are often accompanied with the dysfunctions of autonomic nervous system. Cardiac neuromodulation including vagus nerve stimulation have emerged as alternative therapies by restoring sympatho-vagal balance. In this work, a medulla stimulation strategy was developed to precisely regulate the heart rate. The stimulation parameters effecting on cardiac function were assessed in open-loop experiments. The cardiac effects of rostral and caudal medulla stimulation were enhanced with increased stimulus frequency. We further investigated whether medulla stimulation can temporarily regulate the heart rate at predetermined levels using on-off closed-loop control. Additionally, we tested the capacity of medullary stimulation to rebalance autonomic function under peripheral imbalance conditions caused by dobutamine and neostigmine administration. The performance of heart rate regulation was quantified by the control degree and root mean squared error. The results demonstrate the feasibility of medulla stimulation for regulating sympathetic activity, emphasizing its potential therapeutic use in cardiac disorders.

physiology↗

bioRxiv2025

multiVIB: A unified probabilistic contrastive learning framework for atlas-scale integration of single-cell multi-omics data

Comprehensive brain cell atlases are essential for understanding neural function and advancing translational research. As single-cell technologies proliferate across platforms, species, and modalities, atlas construction increasingly depends on integration frameworks that are capable of aligning heterogeneous datasets without obscuring biological variations. However, existing methods are typically limited to narrow use cases, often requiring ad hoc workflows that may introduce artifacts. Here, we introduce multiVIB, a unified probabilistic contrastive learning framework for diverse scenarios of data integration. We demonstrate that multiVIB achieves state-of-the-art performance while minimizing spurious alignments. Applied to atlas-scale datasets generated by the BRAIN Initiative, multiVIB supports robust and scalable integration across data modalities and preserves species-specific variation in cross-species analyses. These results position multiVIB as a scalable, biologically faithful framework for the construction of next-generation brain cell atlases.

bioinformatics↗

bioRxiv2025

Mut-BPE: A Modified BPE Strategy Improves Variant Effect Prediction

Byte Pair Encoding (BPE) is widely used in genome foundation models for its ability to compress long DNA sequences into fewer tokens. However, its variable-length tokens often span multiple nucleotides, limiting the models sensitivity to single-nucleotide variations--an essential requirement for accurate Variant Effect Prediction (VEP). We introduce Mut-BPE, a training-free, plug-and-play tokenization strategy that augments BPE with explicit single-nucleotide resolution at variant sites. Mut-BPE preserves the efficiency of BPE while enhancing its ability to represent subtle genomic alterations. To evaluate its effectiveness, we applied Mut-BPE to DNABERT-2 and conducted extensive experiments across six diverse datasets spanning gene expression, pathogenicity, and trait-associated variants, under zero-shot and fine-tuning settings. Mut-BPE consistently outperformed conventional BPE tokenization, yielding significant improvements in both AUROC and AUPRC, particularly in imbalanced datasets. These results highlight Mut-BPE as a practical enhancement for genomic foundation models in VEP tasks. Code availability: https://anonymous.4open.science/r/Mut-BPE-1182

bioinformatics↗

bioRxiv2025

LorMe: a streamlined and interoperable R framework for end-to-end microbiome analysis

Microbiome research is rapidly evolving accompanied by increasingly diverse analytical strategies and visualization formats. However, existing R-based tools remain fragmented, differ in data structures, and often require extensive package-specific pre-processing. This increases command-line complexity and limits both interoperability and reproducibility across packages. Here, we present LorMe (Lightweight One-line Resolving Microbial Ecology), an R package that provides a unified, interoperable, and user-friendly framework for microbiome data analysis. LorMe incorporates a standardized S4 object system with fully bidirectional compatibility with phyloseq and microeco, which enables seamless data exchange across major microbial analysis packages. A global configuration system ensures consistent parameter control and visualization standards, and a modular architecture supports both complete end-to-end workflows and flexible execution of individual analytical components. Based on these, LorMe further offers an one-command pipeline that conducts the full spectrum of microbial community analyses, including alpha and beta diversity, differential abundance testing, co-occurrence network inference, and meta-network construction, while archiving all intermediate objects and source data to ensure complete reproducibility. Demonstrations using sample datasets show that LorMe performs comprehensive analyses within minute, produces publication-ready outputs, and maintains methodological transparency. Application to a real rhizosphere dataset revealed biologically coherent patterns across diversity metrics, differential taxa, and network modules, highlighting the capacity of LorMe to support robust ecological interpretation. Collectively, LorMe provides a lightweight, extensible, and flexible solution that reduces technical barriers and enhances reproducibility in microbiome research. LorMe package is freely accessible from both CRAN (https://cran.r-project.org/web/packages/LorMe) and github (https://github.com/wangnq111/LorMe)

bioinformatics↗

bioRxiv2025

Ferrapoptosis: Discovery of a Hybrid Programmed Cell Death

Traditional taxonomies classify ferroptosis and apoptosis as distinct forms of regulated cell death. Here, we challenge this view by defining and validating a previously unrecognized neuronal death entity in traumatic brain injury (TBI), which we term "Ferrapoptosis". This hybrid mode of death is characterized by the coexistence of ferroptotic and apoptotic molecular and ultrastructural features within the same neuron-- ultrastructural alterations that cannot be fully characterized by any known cell death modalities. By integrating single-cell transcriptomics with multi-layered functional assays, we show that Ferrapoptosis dominates in severe injury and the acute phase, and is critically driven by mitochondrial oxidative stress. Over time, its predominance is gradually replaced by death modes in which either ferroptosis or apoptosis alone becomes the major pathway. Genome-wide CRISPR screening further identifies Smg7 as a key regulator that synchronously activates both death programs to drive the hybrid phenotype, whereas genetic or viral inhibition of Smg7 reduces Ferrapoptosis and promotes neurological recovery after TBI in mice. Our work systematically delineates a previously unrecognized form of cell death and its pathogenetic mechanisms, providing experimental evidence to refine cell death classification, and suggesting a conceptual strategy for treating complex diseases such as TBI by targeting shared regulatory nodes. HIGHLIGHTSO_LIDefined and validated a previously unrecognized cell death modality, termed "Ferrapoptosis". C_LIO_LIElucidated the ordered pattern of Ferrapoptosis across key stages of TBI pathogenesis. C_LIO_LIRevealed mitochondrial oxidative stress as the pivotal hub integrating ferroptosis and apoptosis. C_LIO_LIIdentify Smg7 as a core driver of Ferrapoptosis and a promising neuroprotective target. C_LI

cell biology↗

bioRxiv2025

General features of cognition gene polymorphism patterns in marine fish

A growing body of evidence suggests that the cognitive abilities of fish are far more advanced than traditionally believed. They are not mere "automata" driven by instinct, but complex organisms capable of learning, remembering, solving simple problems, engaging in social interactions, and even deception. This situation has prompted us to explore genes related to cognitive functions in the fish genome, examining the pattern status of a set of SNVs (single nucleotide variations) in their cognitive genes relative to the human genome sequence. This study investigates the locus status of 1,824 SNVs from 33 human cognitive genes across the whole genomes of 90 fish species. Based on this, preliminary findings indicate that fish exhibit approximately four patterns of cognitive gene polymorphism. One of these patterns includes at least two coelacanth/lungfish samples, which directly point to the evolutionary direction of the ancient human sd1 sample (an ancient human hair sample from Sudan, Africa).

molecular biology↗

bioRxiv2025

Nuclear factor kappa B subunits and IkappaB family are modulated in the ovine endometrium during early pregnancy

Pregnancy modulates the endometrial immune responses to establish maternal immune tolerance, and nuclear factor kappa B (NF-{kappa}B) subunits and I{kappa}B family are involved in the maternal innate and adaptive immune responses. It, nevertheless, is unclear if early pregnancy regulates the expression of NF-{kappa}B subunits and inhibitor of NF-{kappa}B (I{kappa}B) family in the ovine endometrium. In this study, ovine endometria were sampled at day 16 of the estrous cycle (N16), and at days 13, 16, and 25 of pregnancy (P13, P16, and P25), and mRNA and protein expression of NF-{kappa}B subunits and I{kappa}B family was analyzed by RT-qPCR, western blot, and immunohistochemistry. The results revealed that the expression of all NF-{kappa}B subunits was decreased at P25 compared with N16 both in mRNA and protein expression, but the expression of B cell leukemia-3, I{kappa}B, I{kappa}B kinase {gamma}, and I{kappa}B{delta} was increased at P25 compared with N16 both in mRNA and protein expression. I{kappa}B{beta}, however, was downregulated during early pregnancy, and the expression of I{kappa}B{varepsilon} and I{kappa}B{zeta} was decreased at P13 and P16 compared with N16 and P25 both in mRNA and protein expression. In summary, early pregnancy changed the expression of NF-{kappa}B subunits and I{kappa}B family in the ovine endometrium both in mRNA and protein expression, which may be essential for maternal immune tolerance and embryo implantation.

immunology↗

bioRxiv2025

RoBep: A Region-Oriented Deep Learning Model for B-Cell Epitope Prediction

MotivationAccurate in silico identification of B-cell epitope residues is crucial for antibody design and structure-guided vaccine development. Although recent protein language models and structure-aware methods can capture spatial information of tertiary structure when generating residue embeddings, most existing epitope predictors use these embeddings to perform classification for individual residues one by one, without enforcing spatial continuity for reported epitope residues. Such methods often result in biologically implausible predictions because B-cell epitope residues always cluster together on the antigen surface. ResultsWe present RoBep, a region-oriented B-cell epitope predictor that explicitly models the spatial clustering of epitope residues. RoBep introduces a novel region constraint mechanism and combines the advanced protein language model ESM-Cambrian with an equivariant graph neural network. Our method outperforms existing structure-based methods on the benchmark dataset, demonstrating improvements of 26%, 45%, 13%, and 43% in F1, MCC, AUPR, and AUROC0.1, respectively. In addition to residue-level predictions, RoBep can also provide antibody-antigen binding regions. Importantly, the predicted epitope residues are ensured to be spatially compact, enhancing biological plausibility and practical relevance for immunotherapeutic design. AvailabilityA user-friendly website for using RoBep is provided at https://huggingface.co/spaces/NielTT/RoBep. All datasets, source code used in this work, and implementation instructions of the website are publicly available at https://github.com/YitaoXU/RoBep.

bioinformatics↗