Biology subjects

Xu, J.

Publications and source records attributed to Xu, J..

At least 91 records · Page 5Linked to original sources

bioRxiv2026

A CandiChrome toolkit for multicolor labeling of Candida cells

Here, we develop CandiChrome, a multiplex labeling toolkit for Candida albicans, through combined in vitro and in vivo characterization of fluorescent proteins in a standard strain background. To this end, we screened 13 candidate fluorophores across the visible spectrum and assessed their practical performance based on brightness, stability, and usability. This analysis identified a seven-fluorophore set that achieved the most effective balance of signal strength, robustness, and compatibility. We used this optimized panel to build a modular multicolor platform that enables strain labeling, mixed-population imaging, and competition assays in C. albicans. This platform could resolve up to 21 distinct populations by flow cytometry and microscopy. Importantly, CandiChrome supported the resolution of differentially labeled populations both in vitro and in the murine host, supporting the simultaneous tracking of multiple strains in complex settings. Together, these results establish CandiChrome as a flexible platform for multiplex fungal imaging in a pathogenic species where multicolor tools remain underdeveloped.

microbiology↗

bioRxiv2026

Histone modifications analysis reveals enhancers reprogramming during maternal-to-zygotic transition

Enhancers are important epigenetic regulatory components that coordinate spatiotemporal gene expression and play a crucial role in mammalian development, gene regulation, and illness. During early mammalian embryogenesis, histone modifications including H3K4me1, a canonical enhancer mark, and H3K27ac, which identifies active enhancers, are still poorly understood. This study profiles the genome-wide H3K4me1 and H3K27ac patterns in mouse oocytes and pre-implantation embryos using low-input CUT&RUN (cleavage under targets and release using nuclease) with input as low as 50 cells. Both markers are enriched in distal regions and exhibit distinct sequence preferences and reprogramming dynamics in pre-implantation embryos. H3K27ac, a mark of active enhancers, is reprogrammed at the 2-cell stage, whereas H3K4me1 is remodeled at the 4-cell stage and overlaps with H3K27ac, coinciding with accessible chromatin regions. Interestingly, H3K4me1 and H3K27ac are co-localized in promoter regions, where they are mutually exclusive to H3K4me3. Enhancers are dynamically remodeled during maternal-to-zygotic transition (MZT). there are three enhancer types: active enhancers (H3K4me1/H3K27ac), primed enhancers (H3K4me1), and poised enhancers (H3K4me1/H3K27me3). Active enhancers increase significantly after zygotic genome activation. Further, super-enhancers are present across the genome and are mainly enriched in promoters. The specific motifs enriched by super-enhancers may be associated with the variations of gene expressions at different stages.

developmental biology↗

bioRxiv2026

The Structural Code of Breast Cancer Proteoform: Alternative Splicing-driven Protein Isoform Variation and Functional Diversification

Alternative splicing generates extensive transcript diversity, but the extent to which this diversity contributes to the translated proteome and reshapes protein function remains unclear. Here, we develop 3DisoGalaxy, an atlas integrating transcript reconstruction, ribosome profiling, structural modelling and regulatory annotation in breast cancer. We find that 58,292 of 90,929 transcripts are linked to translation-supported ORFs, 71.9% of which arise from non-canonical transcript structures. These products are broadly accommodated within established protein fold space, indicating that alternative isoforms frequently preserve recognizable protein architectures despite substantial sequence variation. Functional divergence is instead concentrated in domains, intrinsically disordered regions, localization determinants and regulatory motifs. Motif remodelling is biased towards gains and is more extensive in cancer-driver genes than in other genes, linking isoform-associated regulatory variation to cancer-relevant proteins. As an example of domain remodelling, we identify an AKT1-{Delta}PH isoform that lacks the N-terminal PH domain while retaining the kinase core, with immunoblotting revealing a lower-molecular-weight AKT1 species consistent with this isoform. Together, our results show that alternative transcript diversity extensively enters translation-supported proteoform space and establish a systematic link between transcript variation and protein functional diversification.

cancer biology↗

bioRxiv2026

Extra-lineage tissue programs define the transcription states of human pancreatic cancer

Cancers acquire alternate transcriptional states as they evolve, but the origins, timing and determinants of this plasticity are poorly understood in many tumours. We investigated the transcriptional states of pancreatic cancer by integrating [~]1000 tumour-enriched genomes and transcriptomes from 464 patients combined with scRNA-seq, multiome profiling, and spatial proteomics. Four epithelial states covering the spectrum of lineage plasticity were identified (Classical-1, Classical-2, Basal-1, Basal-2). Comparing these states to normal and pan-cancer human single cell atlases showed each state reflects distinct tissue programs found in other malignancies. Single cell analysis uncovered that the main transcription state of this disease (Classical-1) emerges before KRAS mutations. Spatial proteomics from patients and cancer-free donors showed that the Classical-1 program emerges during acinar-to-ductal metaplasia, and also unexpectedly, in normal ducts without disrupting their morphology. Overall, these findings link the extensive lineage plasticity potential of this organ to the origins of the transcriptional states.

cancer biology↗

bioRxiv2026

LNGCN: A Distance-Aware Dynamics Network for Protein-Protein Interaction Prediction

High-throughput PPI screening requires not only interaction discrimination but also stable, calibrated scores for candidate prioritization and efficient experimental allocation. Conventional graph neural networks may over-smooth deep residue representations, reducing score separation among high-confidence candidates. We therefore developed LNGCN, a distance-aware continuous-time graph framework for experimental PPI prioritization. LNGCN integrates residue-level structural graphs with liquid neural dynamics, uses radial distance to drive continuous graph evolution, and applies hierarchical calibration to convert raw outputs into prioritization scores. It performed robustly on balanced human, 1:10 imbalanced, and cross-species yeast bench-marks. On the imbalanced dataset, the top 5% of candidates achieved 85.1% precision. LNGCN also preserved residue-level representation diversity better than conventional GCN variants. In FGF23-FGFR1c--Klotho, SHP2 signaling, Tdk1 oligomer-dependent binding, and a TPR study, it enriched known partners near the ranking top, and experimentally supported novel interactions. Overall, LNGCN enables sustained enrichment of experimentally relevant PPI candidates.

bioinformatics↗

bioRxiv2026

A High-Fidelity 3D Fluid-Structure Interaction Framework for Predictive Microfluidic Design

The commercial maturation of microfluidics remains bottlenecked by empirical prototyping and an absence of predictive digital design capabilities. Because optimizing advanced technologies such as passive particle separation fundamentally hinges on the precise coupling of fluid dynamics and particle mechanics, conventional two-dimensional or decoupled fluid simulations inherently fail to capture authentic multiscale behaviors. To bridge this gap, we establish a high-fidelity three-dimensional fluid-structure interaction framework combining a high-order Arbitrary Lagrangian-Eulerian mapping-based finite element method with a localized hierarchical dynamic mesh strategy. Engineered to accurately resolve complex multiscale hydrodynamics, this architecture utilizes deterministic lateral displacement structures as a stringent test case. Validated against experimental data for rigid microspheres and tumor cells, the framework predicts transport trajectories and critical separation diameters with sub-micron precision. Crucially, the simulation explicitly resolves the M-shaped spatial fluctuation of local size thresholds alongside the dynamic vertical migration of particles. Unveiling these hidden physical mechanisms provides a deterministic explanation for highly debated phenomena such as mixed-mode transport. By enabling the rigorous in silico evaluation of complex non-periodic architectures, this framework serves as a powerful instrument for predictive structural optimization. Such capabilities establish the essential infrastructure for microfluidic digital design, accelerating the transition from empirical trial-and-error to precision simulation-driven engineering.

bioengineering↗

bioRxiv2026

Protein structure-informed deep learning enables species-specific codon optimization

Codon usage bias is highly species-specific, posing a major challenge for heterologous protein expression. Existing deep learning approaches to codon optimization rely primarily on DNA or protein sequence information and largely neglect constraints imposed by protein structure and folding. Here, we present Protein structure-Informed Species-specific Codon Optimization (PISCO), a Geometric Vector Perceptron (GVP)-based model that integrates protein sequence, three-dimensional protein structure, and host codon usage statistics to generate optimal, host-specific codon sequences. Compared with protein-structure-agnostic models, PISCO improves codon recovery by 6% and substantially increases similarity to natural coding sequences, reducing divergence by at least 42% in Codon Similarity Index (CSI), 50% in Codon Frequency Distribution (CFD), and 14% in Dynamic Time Warping (DTW) metrics. Ablation analyses demonstrate that incorporating protein folding kinetics and host-specific information is critical to these gains. Moreover, by leveraging host codon usage statistics, PISCO generalizes to optimize codon sequences for species absent from the training data. An autoregressive variant of PISCO further enhances concordance with natural codon usage patterns, at the cost of a modest reduction in codon recovery rate. Wet-lab validation confirms that PISCO-optimized sequences significantly enhance protein solubility and functional expression. Together, these results establish protein structure as a key determinant of species-specific codon optimization and provide a transferable framework for structure-aware gene design.

molecular biology↗

bioRxiv2026

OneGenomeRice (OGR): A Genomic Foundation Model for Rice

The transition of genomics to a predictive intelligence discipline is driven by the advent of genomic foundation models. While substantial progress has been observed in all-life and human-centric models, plant species, particularly for the staple crops, remains hindered by a lack of models. Here we introduce OneGenome-Rice (OGR), a rice (Oryza sativa) genomic foundation model pre-trained on a genomic dataset comprising 422 high-quality genomes of cultivated and wild rice. OGR is engineered upon a Mixture of Experts (MoE) transformer architecture with 1.25-billion parameters and supports an ultra-long context window of up to 1 million base (Mb) pairs at single-nucleotide resolution. A comprehensive benchmark demonstrated that OGR significantly outperforms existing state-of-the-art multi-plant or all-life genome models in 11 categories (e.g. motif identification, sweep detection, etc). We further demonstrated the utility of OGR in several downstream applications, such as indica-japonica subspecies introgression analysis, identification of agronomy trait-associated functional loci and prediction of gene expression from DNA sequences. These results establish OGR as a promising foundational computational infrastructure for rice functional genomics and precision breeding. The OGR and its fine-tuned models, including pretrained weights, training code and the rice genomic benchmark suit, have been fully opened.

genomics↗

bioRxiv2026

An Observational Study of the Impact of Systemic B-cell Depletion on Cervicovaginal Mucosal Environment

ImportanceEmerging data show that B-cell depleting chemotherapies, which are increasingly used to treat autoimmune disorders and multiple sclerosis, can be associated with mucosal side effects such as inflammatory vaginitis. ObjectiveEvaluate the impact of rituximab treatment on vaginal mucosal immune markers, endocervical immune cell populations and vaginal microbiome. DesignCross-sectional observational study conducted between 2022 - 2024. SettingAcademic medical center, Boston Massachusetts. ParticipantsWe enrolled women aged >18 years who were either 1) receiving rituximab for autoimmune renal disease or were 2) healthy controls ExposureTreatment with rituximab, an anti CD20 monoclonal antibody. Main outcome and measureWe compared endocervical immune cell populations, vaginal fluid immune markers, vaginal fluid immunoglobulins and vaginal microbiome composition between individuals being treated with rituximab and healthy controls. ResultsWe enrolled 26 women treated with rituximab for autoimmune renal disease and 26 healthy controls. Median circulating and endocervical B-cell and plasma cell proportions were significantly lower in treated participants compared to controls. Median vaginal fluid IgA concentrations were significantly lower in participants treated with rituximab, while ILE, IgM, IgG1, IgG2, IgG3 and IgG4 were not different between groups. Total T cell frequencies were similar between groups, but the proportion of activated T cells (CD4+CD38+HLADR+) was significantly lower in people treated with rituximab. Concentrations of IL10, IL13, IL17, IL21, IL23, IL4, ITAC and TNFa were elevated in vaginal fluid from the rituximab group, while IL-8 was lower. A CST-IV-C, low-Lactobacillus pattern of vaginal microbiota was more common in the rituximab group. Conclusions and RelevanceSystemic B-cell depletion is associated with reduced vaginal fluid IgA, a more diverse microbiome composition, and increases in many vaginal fluid immune markers compared to healthy controls. The reduction in vaginal fluid IgA may provide opportunities for vaginal bacteria to induce inflammation. Key pointsO_ST_ABSQuestionC_ST_ABSHow does circulating B-cell depletion impact the vaginal microenvironment? FindingsIn this cross-sectional study of 52 women, B cell and plasma cell proportions were significantly lower in both blood and vaginal mucosa among rituximab-treated participants compared to healthy controls. Vaginal IgA concentrations, but not other immunoglobulins, were significantly lower in rituximab treated participants. In treated participants, vaginal cytokine concentrations were elevated, and microbiome composition shifted toward non-Lactobacillus-dominant communities. In six people with inflammatory vaginitis, both circulating and endocervical B cells were lowest in people with the most severe symptoms. MeaningSystemic B cell depletion is associated with alterations in vaginal mucosal immune markers and microbiome composition which increase local inflammation.

immunology↗

bioRxiv2026

A simplified High-Pressure Freezing Workflow in Autogrids

Cryo-electron tomography (cryo-ET) is a powerful method for studying biological structures in near-native states, yet vitrification of thick and complex specimens remains a major limitation. High-pressure freezing (HPF) allows vitrification of up to [~]200 {micro}m thick samples, but its seamless integration into cryo-electron microscopy (cryo-EM) workflows is hindered by planchettes that are not optimized for EM grids, resulting in extensive handling, reliance on user experience, and frequent grid damage. Here, we present a streamlined HPF workflow based on newly designed planchettes that directly accommodate clipped EM Autogrids. Combined with interchangeable lids for controlling sample thickness, this system enables robust vitrification of diverse specimens, including single-celled eukaryotes and tissue biopsies, while minimizing post-freezing handling. Integration with plasma-focused ion beam milling supports both on-grid lamella preparation and lift-out approaches. We demonstrate reliable preservation of cellular ultrastructure and macromolecular integrity by cryo-ET and subtomogram averaging. This resource provides a practical and scalable solution for integrating HPF into modern cryo-ET pipelines, expanding access to structurally complex biological systems and supporting future clinical applications.

cell biology↗

bioRxiv2026

Sex stratified analyses enable new genetic insights into brain imaging phenotypes

Sex differences are commonly observed in neuroimaging phenotypes and in the risk of brain diseases, yet the underlying genetic mechanisms remain poorly understood. We investigated sex differences in the genetic architecture of 805 neuroimaging phenotypes in 22,950 males and 22,950 females matched for sample size and covariates, and systematically compared sex-stratified with sex-combined genetic analyses. We found eight variant-trait associations with significant sex differences, 235 fine-mapped sex-dominant causal associations, 457 sex-dominant colocalizations with sex hormones, and 96 sex-dominant colocalizations with schizophrenia. Compared with sex-combined analysis, sex-stratified analysis identified 47 new genetic associations, 170 new fine-mapped causal associations, 1,019 new colocalizations with sex hormones, and 191 new colocalizations with schizophrenia. Additionally, sex-stratified analysis improved global heritability and genetic-correlation estimates and enhanced polygenic prediction for certain phenotypes. This work highlights the need to routinely perform sex-stratified genetic association analyses to elucidate sex-specific and sex-shared genetic control of neuroimaging phenotypes and related disorders.

genetics↗

bioRxiv2026

Modification-aware AI enables terminal chemical modifications for peptide design and discovers potent antimicrobials

Antimicrobial resistance (AMR) is an escalating global health threat, intensifying the urgent need for novel antibiotics. Here, we introduce Termini, a generative machine learning (ML) framework that integrates peptide generation, classification, and regression modules to systematically identify potent antimicrobial peptides (AMPs). A key feature of this pipeline is its explicit design of both N- and C-terminal modifications, combined with predictive modeling across 15 bacterial species. We experimentally validated the framework against 11 pathogenic species, representing the broadest spectrum of testing reported to date in such a study. We synthesized and tested 120 peptides (including 60 unique amino acid sequences) with and without terminal modifications. Remarkably, 111 of these peptides (92.5%) demonstrated antimicrobial activity in vitro. Comparative analyses demonstrated that terminal modifications substantially enhanced antimicrobial potency. Furthermore, the lead candidates identified through in vitro screening exhibited robust anti-infective efficacy in subsequent in vivo experiments, confirming their therapeutic potential. Collectively, these results highlight the high hit rate, biological relevance, and translational promise of this integrative, modification-aware AI framework for next-generation antimicrobial peptide development.

microbiology↗

bioRxiv2026

Loss of hand control expressiveness revealed by task- and individual-specificity in spatiotemporal finger coordination

Stroke impairs dexterous hand use in daily activities, with prior studies of endpoint postures demonstrating reduced coordination complexity and diminished task-appropriate and individually-distinctive (termed expressiveness) coordination required by these daily activities. However, how spatiotemporal coordination reveals individual differences in post-stroke coordination remains unclear. Here, we characterized spatiotemporal coordination in able-bodied and post-stroke hands during finger individuation. We quantified coordination complexity and expressiveness (task-, individual-, and group-specificity) using principal component analysis (PCA) and linear discriminant analysis of 3D isometric forces from all five fingers. Paretic fingers showed reduced complexity and expressiveness, which was associated with greater intrusion of flexor bias in the paretic hand. Higher-variance PCs were characteristic of tasks and groups, while both higher- and lower-variance PCs were characteristic of individual-specific coordination. These findings suggest that stroke reduces spatiotemporal finger coordination complexity and expressiveness, limiting the coordination patterns available for daily hand use.

neuroscience↗

bioRxiv2026

Inhibitory-modulatory coupling generates persistent activity during working memory

Working memory requires the stable maintenance of neural representations across temporal gaps, yet the circuit mechanisms that generate and stabilize persistent activity remain unsolved. Prevailing models emphasize recurrent excitation as the principal substrate of persistence, but how inhibitory and modulatory interactions shape the stability of temporal dynamics is unclear. Here, using trace conditioning in Drosophila, a working memory-dependent form of associative learning, we identify reciprocal inhibition as a circuit mechanism for sustaining persistent activity. In trace conditioning, a "trace" interval separates the conditioned and unconditioned stimuli, requiring maintenance of a neural representation across the trace interval, to support learning. Combining virtual-reality behavior, targeted neurogenetic perturbations, in vivo two-photon calcium imaging, and real-time neurotransmitter measurements, we uncover a reciprocal inhibitory microcircuit within the ellipsoid body that is selectively engaged during trace, but not delay (overlapping CS-US), conditioning. During the trace interval, ER2/4m neurons exhibit sustained activity, while reciprocally connected ER3/4d neurons show progressively strengthened suppression, forming a dynamically stabilized inhibitory loop. Disrupting GABA synthesis or reception within this circuit abolishes persistent activity and impairs trace learning, demonstrating the causal requirement for reciprocal inhibition in working memory maintenance. We further show that glutamatergic and nitric oxide signaling enhance inhibitory efficacy during the trace interval. In vivo neurotransmitter imaging reveals temporally structured dynamics in which glutamatergic signaling precedes and amplifies sustained GABAergic inhibition, consistent with modulatory stabilization of circuit persistence. Together, these findings identify reciprocal inhibition, reinforced by modulatory signaling, as a core circuit mechanism for dynamically stabilizing persistent neural representations. Our results challenge excitation-centric models of working memory and establish inhibitory-modulatory loops as a fundamental substrate for maintaining memory traces across time.

neuroscience↗

bioRxiv2026

A single-cell and spatial atlas of prostate cancer reveals the combinatorial nature of gene modules underlying lineage plasticity and metastasis

Prostate cancer encompasses a spectrum of disease states driven by complex cellular heterogeneity. To delineate the transcriptional programs underlying lineage plasticity and metastasis, we constructed a comprehensive single-cell atlas of 128 patients, spanning localized, castration-resistant, and metastatic disease. Lineage plasticity was prevalent in localized disease, with subsets of tumor cells adopting distinct basal-like and club-like states. Luminal-like cancer cells also displayed extensive lineage infidelity, defined not by a binary loss of identity but by the combinatorial erosion of luminal gene modules associated with higher grade and stage. In the metastatic setting, gene program association analysis (GPAS) identified a broad induction of cell-cycle gene modules across organ sites as well as an induction of organ-specific gene modules, including osteomimetic signaling in bone, neuro-migratory genes in brain, and erythroid-like transitions in liver. Neuroendocrine prostate cancers (NEPCs) were not monolithic but defined by combinations of NE-associated gene modules including a novel HES6 program. Notably, these modules were detected at intermediate levels in localized samples, suggesting molecular plasticity precedes histological transformation. We also developed a refined NE signature that could distinguish NEPC tumors more accurately than previously published signatures. Within the tumor microenvironment (TME), we observed an elevation of pro-inflammatory Th17 T-cells in African American patients and identified a rare Schwann cell population. Finally, we present PCformer, a transformer-based foundation model trained on >500,000 cells to automate cell-state classification. Together, this comprehensive atlas demonstrates the complex nature of gene modules underlying lineage infidelity and plasticity in cancer cells and highlights distinct immune and stromal populations within the tumor ecosystem.

genomics↗

bioRxiv2026

An interferon independent innate immune response to double stranded RNA in embryonic stem cells

In vertebrate early embryos and embryonic stem cells, the interferon (IFN)-centered double-stranded RNA (dsRNA) sensing and signaling pathway is markedly suppressed, implying the existence of an alternative repertoire of dsRNA sensors in these stages. We recently reported that dsRNA treatment triggers translation inhibition using Prkra as a sensor in zebrafish and mouse early embryos. Independently, here we show that dsRNA stimulates the expression of a subset of interferon-stimulated genes (ISGs) in the absence of IFN production, establishing a defensive state in mouse embryonic stem cells (mESCs). Upon dsRNA stimulation, the multifunctional DExD/H-box RNA helicase Dhx9 is recruited into dsRNA-induced condensates, where it promotes the recruitment and functional suppression of the Mdm2/Cul4A ubiquitin ligase machinery by excluding their substrate adaptor Ddb1, thereby stabilizing p53 and Stat1. Dhx9, p53 and Stat1 then cooperate to stimulate an ISG response. This signaling is important for the defense against ZIKV infection in mESCs as well as other dsRNA stresses. Such a cascade is conserved in human ESCs, while in zebrafish embryos, p53 but not Stat1 is required for the transcriptional response. Our findings define an immediate, cell-autonomous innate immune pathway operating in ESCs and vertebrate embryos.

immunology↗

bioRxiv2026

Complete genome-derived metabolic interactions reveal impact of gut ecology on human health

Metabolic interactions govern gut microbiome assembly, yet functional rules remain obscured by genomic incompleteness and fragmentation. Here, we leverage 1,150 complete genomes to construct genome-scale metabolic models, demonstrating that draft genomes introduce systemic artifacts missing critical transport functions. We observe that metabolic interactions are intrinsically driven by genomic traits and niche specialization rather than random association. We stratifies strains into four ecological groups, including active players, resource predators, utilizers, and contributors, each of which exhibits distinct metabolite exchange/competition signatures. This functional architecture is strongly coupled to secondary metabolism. Applying this framework to inflammatory bowel disease revealed distinct temporal dynamics of ecological groups across disease subtypes, where group-specific dysbiosis predicted clinical phenotypes better than whole community profiles. Furthermore, integrating metabolic and co-occurrence networks to identify keystone for classifiers as features significantly improved disease diagnosis. Our study provides novel insights into gut metabolic interaction landscape, bridging the gap between genomic potential and clinical utility for precision microbiome therapeutics.

microbiology↗

bioRxiv2026

A Dynamic Oligomerization Network Coordinates Hemagglutinin-Mediated Membrane Fusion on Influenza Virions

Influenza A virus (IAV) entry is mediated by the trimeric glycoprotein hemagglutinin (HA), which undergoes low-pH-triggered conformational rearrangements to drive membrane fusion. Although biochemical and biophysical studies have long suggested that HA trimers function cooperatively, the structural basis for this cooperativity on intact virions has remained unclear. Here, using cryo-electron tomography (cryo-ET) and subtomogram averaging (STA), we determine the in situ structure of prefusion HA on native virions at 3.58 [A] resolution, enabling atomic modeling of membrane-anchored HA. We show that neighbouring HA trimers engage in lateral interactions mediated by HA1 subunits, assembling into flexible dimeric, pentameric, and hexameric organizations that form locally ordered lattices on the viral surface. A 6.0 [A] reconstruction of the HA-dimer reveals the molecular interfaces underlying these assemblies. Disruption of the dominant HA1-HA1 interaction markedly impairs viral entry and slows membrane fusion kinetics. Together, these findings define a virion-level mechanism for coordinated HA activation and establish a structural framework for understanding cooperative membrane fusion by class-I viral fusion proteins.

biophysics↗