Biology subjects

Xu, M.

Publications and source records attributed to Xu, M..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Integration of early-stage cryopreservation and cell cycle modulation into a flexible kidney organoid differentiation system

Kidney organoids derived from human pluripotent stem cells (hPSCs) represent a promising platform for modeling nephrogenesis and renal diseases. However, conventional differentiation protocols are continuous and time-sensitive, limiting their scalability and reproducibility. Here, we developed a method to pause and resume organoid formation through cryopreservation at an early differentiation stage using a chemically defined formulation that maintains high post-thaw viability and differentiation potential. We further found that synchronizing hPSCs in the G1 phase with PD-0332991 enhanced post-thaw organoid formation and transcriptional fidelity, while G2 phase enrichment with Ro-3306 promoted the development of SLC12A3-positive distal convoluted tubules. The post-thaw organoids exhibited well-organized nephron architecture and function comparable to uninterrupted cultured controls. This platform proved effective for modeling BK polyomavirus (BKV) infection, drug-induced nephrotoxicity, and renal fibrosis. Together, our cryopreservation and cell cycle synchronization strategy provides a flexible, practical framework to advance organoid-based research and translation.

developmental biology↗

bioRxiv2026

Functional characterization of a multi-cancer risk locus on chromosome band 2q33.1 near CASP8

Genome-wide association studies (GWAS) of melanoma have identified numerous susceptibility loci. However, causal genes and variants underlying risk have yet to be established for most. It is becoming apparent that many functional variants underlying complex traits act via cis-regulation that may be context-specific, dependent on availability of specific transcription factors/complexes in specific cell types and cell-states. To characterize a risk locus on chromosome band 2q33.1 associated with melanoma, breast cancer, and keratinocyte cancers, we integrated fine-mapping, cell-type specific expression quantitative trait locus (eQTL) analysis, a massively parallel reporter assay, individual luciferase assays, and SNP-based proteomics. Integrated analysis implicates the presence of multiple functional variants lying primarily within a promoter for CASP8. A haplotype containing rs3769823 appeared have the largest effect on expression. Strikingly, both tumor/normal context and this risk-associated haplotype play critical roles in mediating allelic cis-regulatory activity. Quantitative mass spectrometry for rs3769823 identified both E4F1, a transcriptional repressor, and IRF2, a transcriptional activator, as binding preferentially to risk-associated rs3969823-A. The binding of these transcription factors was validated via EMSA, supershift, and chromatin immunoprecipitation (ChIP) assays. The relative levels of E4F1 and IRF2 differ by cell-type and play a role in mediating transcriptional activity in a cell-type specific manner. Our results indicate that the top credible causal set variant rs3769823 likely influences expression of CASP8 and FLACC1 in a cell-type specific manner and may be a relevant functional variant for multiple cancers associated with this locus.

genetics↗

bioRxiv2025

Rhythmicity Revisited: Evidence from Robust Behavioral Oscillations

Rhythmic fluctuations in neuronal excitability, called neural oscillations, pervade brain activity. If these oscillations have a functional role in behavior, they should also be expressed in a behavioral signature. However, identifying such a behavioral signature has remained controversial: evidence for behavioral oscillations is not yet firmly established, and aperiodic components can be misidentified as rhythmic. To test their existence while controlling for aperiodic dynamics, we applied a state-of-the-art autoregressive (AR) approach on two datasets: one published dataset, and a new dataset collected with a revised dense-sampling design. In both datasets, AR modeling recovered reliable behavioral oscillations in the theta band. Reanalyses of the published dataset also reproduced the reported theta shift with task demands, with more difficult tasks showing slower theta. In contrast, despite clear rhythmicity, the new dataset showed no consistent frequency shift across conditions. Overall, this study establishes rigorous and robust detection of behavioral oscillations. It also suggests that the frequency modulation of behavioral oscillations by task difficulty requires further study.

neuroscience↗

bioRxiv2025

A Hybridization-Based Novel DNA Storage Technology with Rapid Read Performance

The development of traditional silicon-based microelectronic storage media has increasingly lagged behind the rapidly growing demands of contemporary data storage. DNA storage, with its ultra-high information density and long-term preservation advantages, has rapidly become a research hotspot for next-generation storage technologies. However, current mainstream DNA storage methods based on synthesis and sequencing suffer from slow read/write speeds, hindering practical applications. To address this limitation, we propose an innovative hybridization-based DNA storage scheme. Through principle validation experiments, short-text read/write and error-correction tests, and high-density multi-format file storage experiments, we verify the feasibility of this approach. The proposed method exhibits high parallelism, rapid read speeds, and robust encryption capabilities, demonstrating promising application prospects in scenarios such as confidential data storage.

synthetic biology↗

bioRxiv2025

A human multilineage gut organoid model for Parkinson disease

Emerging evidence links gut dysfunction to Parkinson disease (PD) pathogenesis, yet human models to study gut-related mechanisms are lacking. We developed a human intestinal organoid model incorporating PD-relevant cell types. Using control and PD patient-derived pluripotent stem cells, we generated intestinal epithelial organoids and vagal neural crest cells, then co-cultured them into assembloids. The resultant structures featured lumen-forming polarized epithelial monolayers with enteroendocrine cells, contractile subepithelial myofibroblast-like layers, and neuroglial networks containing dopaminergic and cholinergic enteric neurons. Notably, assembloids from a PD patient carrying the GBA1-E326K variant exhibited progressive -synuclein accumulation in non-enteroendocrine epithelial cells. This model recapitulates key gut architecture and PD-associated phenotypes, offering a physiologically relevant platform for mechanistic studies and therapeutic discovery targeting gut-brain pathways in PD.

cell biology↗

bioRxiv2025

Confinement prevents postmenopausal osteoporosis and obesity via nuclear mechanical remodeling

Postmenopausal osteoporosis (PMOP), affecting about half of postmenopausal women, is a major global health burden characterized by fragile bones and frequent comorbidity with obesity. Bone marrow mesenchymal stem cells (BMSCs) differentiation imbalance underpins PMOP pathogenesis and represents an attractive therapeutic target. Here, we demonstrate mechanically confining BMSCs to soft substrates mimicking physiological bone marrow stiffness completely suppresses adipogenic differentiation while inducing osteogenic differentiation. Mechanistically, confinement-induced elevation of nuclear envelope tension upregulates Lamin A/C expression, which in turn modulates Runx2 nuclear localization by activating histone acetylation via KAT2B, thereby directing BMSCs osteogenesis. Remarkably, FDA-approved deacetylation inhibitor Chidamide significantly enhances bone regeneration while concurrently suppressing obesity in a PMOP animal model, highlighting the significant therapeutic potential of nuclear mechanotransduction as a target for PMOP and obesity treatment. This work not only provides new insights into the mechanical regulation of bone homeostasis but also opens new avenues for the treatment of osteoporosis-related disorders.

biophysics↗

bioRxiv2025

SynPROTAC: synthesizable PROTACs design through synthesis constrained generative model and reinforcement learning

Protein hydrolysis targeting chimeric (PROTAC) has emerged as a promising technology in degrading disease-related proteins for drug design. Recent deep generative models can accelerate PROTAC design, but the generated molecules are often difficult to synthesize. Here we develop SynPROTAC model, which employs Graphormer encoded warhead or E3 ligand as input, and autoregressively samples reaction templates and building blocks through transformer based decoder for PROTAC construction. The model is also fine-tuned via reinforcement learning for generating PROTACs with favorable binding properties. The comprehensive evaluations indicated that SynPROTAC is capable of generating novel PROTACs with feasible synthetic routes, reasonable physico-chemical and binding related properties.

bioinformatics↗

bioRxiv2025

Functional characterization of the 9q34.13 locus identifies RAPGEF1 as modulating risk for melanoma and nevi via RAS activation

Genome-wide association studies identified a melanoma- and nevus count-associated locus on chromosome band 9q34.13. Fine-mapping and melanocyte expression data collectively suggest two potential causal genes with opposite association with risk: higher levels of Rap guanine nucleotide exchange factor 1 (RAPGEF1) and lower levels of uridine-cytidine kinase 1 (UCK1). Colocalization analyses and conditional TWAS suggest multiple causal cis-regulatory sequence variants in partial linkage disequilibrium (LD) to each other. Melanocyte capture-HiC and CRISPR-inhibition demonstrated regulatory interactions between fine-mapped variants and the RAPGEF1 and UCK1 promoters. Focusing on RAPGEF1, we demonstrate RAPGEF1 expression promotes melanocyte growth and drives malignant transformation of human immortalized melanocytes. Following treatment with human EGF, RAPGEF1 overexpression activated both RAP1 and RAS. Further, we show RAPGEF1 expression is significantly enriched in melanomas lacking strongly activating RAS-MAPK mutations, suggesting that RAPGEF1 may promote oncogenic RAS-MAPK signaling in melanomas. Furthermore, in these tumors, we provide preliminary evidence to support the prognostic relevance of RAPGEF1 expression in patients lacking RAS or BRAF mutations. Together with other recent studies, these data suggest that germline variation influencing RAS activation may play a key role in nevus development and melanoma risk.

genetics↗

bioRxiv2025

Exploring multi-level microbial interactions from individual 3D genomes to community networks

Microbial communities interact with their hosts through complex genomic networks that influence ecosystem stability and disease progression. Here, we present FindMeta3D, a computational framework that simultaneously identifies microbial three-dimensional (3D) genome structures and cross-domain interaction networks. Applying this approach to 528 Hi-C samples, we resolved 3D genome structures of 344 microbial species, revealing five evolutionarily conserved chromatin folding patterns linked to intrinsic sequence features. Further analyses demonstrated distinct microbial-host interaction preferences and identified functional interaction hotspots that are critical for infection. Experimental deletion of such hotspots in the EBV genome resulted in significant infection defects, demonstrating their essential role in viral infectivity. Additionally, we constructed the first Cross-domain Microbial Interaction Network (CMIN), which uncovered pathogen-specific subnetworks and demonstrate dramatic restructuring of gut microbial communities in neutropenic patients, including enhanced Klebsiella-phage interactions. Subnetwork analysis identified potential phage therapy targets, such as Klebsiella phage ST16-OXA48phi5.4. These findings provide fundamental insights into microbial 3D genomics and establish FindMeta3D as a powerful platform for studying microbial genome structure and communities and developing antimicrobial strategies.

microbiology↗

bioRxiv2025

Sensorineural regulation of skull healing implicates FGF1 signaling in non-healing bone

Bone injuries demonstrate rapid peripheral nerve ingrowth followed by nerve pruning as healing ensues. However, in non-healing bone injuries, peripheral innervation remains elevated, the implications of which remain unknown. Therefore, we investigated the neuroskeletal microenvironment in subcritical-and critical-sized calvarial defects using quantitative 3D fluorescence imaging. We identified elevated densities of peripheral nerves and Osterix positive (Osx+) osteoprogenitors in critical-sized defects, while osteogenic differentiation markers were severely diminished. Moreover, Osx+ osteoprogenitors in critical-sized defects exhibited enhanced proximity to peripheral nerves, which in turn was associated with increased osteoprogenitor cell proliferation. Using retrograde tracing in conjunction with single cell RNA-sequencing of sensory nerves from the innervating trigeminal ganglia, genes encoding for nerve-secreted proliferative and anti-differentiation factors were identified. Specifically, FGF-1/FGFR-1 signaling was identified as a significant neuroskeletal interaction with critical-sized defects demonstrating higher FGF-1 expression in fluorescence imaging. Presence of FGF-1 in neurons innervating the calvarial was confirmed, and neural conditioned media depleted for FGF1 showed enhanced induction of osteogenesis when placed on parietal bone cells. Collectively, we identify a sensorineural-skeletal signaling interaction elevated in critical-sized defects that can be leveraged as a potential therapeutic target for enhancing bone healing.

bioengineering↗

bioRxiv2025

Multimodal AI Decodes Extreme Environment Functional Dark Matter Beyond Homology

Functional annotation of proteins from extreme environments represents a major bottleneck for bioresource discovery, as a vast reservoir of functional dark matter defies existing homology-based methods. We demonstrate that environmental pressures impart conserved physicochemical energy signatures that co-determine protein function with sequence and structure. Here we developed ACCESS, a multimodal graph neural network employing hierarchical contrastive learning with a tailored label-sample co-embedding to fuse energy, sequence, and structural information and overcome homology scarcity. ACCESS surpasses state-of-the-art methods including BLASTp and CLEAN in annotating low-identity enzymes. Applied to extreme environmental metagenomics, we constructed a function map of extremophile enzymes to expand the biocatalyst library, pinpointed functionally critical residues to guide rational design, and enabled large-scale, function-based macro-evolutionary analyses. This paradigm transcends the limitations of homology, illuminating protein dark matter and accelerating the exploration of the biospheres functional diversity for applications in biotechnology and therapeutic development.

bioinformatics↗

bioRxiv2025

High-Concordance Validation of Droplet Digital PCR and Next-Generation Sequencing for EGFR Mutation Detection Across Diverse Biospecimens in a Large-scale NSCLC Cohort Study

BackgroundsNext-generation sequencing (NGS) and droplet digital PCR (ddPCR) are both established methods for detecting EGFR mutations in non-small cell lung cancer (NSCLC). However, comprehensive validation of their concordance in mutation detection and variant allele frequency (VAF) quantification across heterogeneous sample types remains limited. Inconsistent results from different sample types (e.g., cfDNA, FFPE) pose a significant challenge to clinical decisions. This is particularly critical for advanced NSCLC patients, who often rely on liquid biopsy, yet the concordance between liquid and tissue-based testing lacks validation in large-scale studies. Another issue in clinical practice is that many tumor samples are limited in quantity, making it difficult to meet testing requirements. Therefore, it is worth exploring whether pre-capture NGS libraries can serve as substitutes for original DNA. MethodsIn this study, we first developed three assays to detect EGFR L858R, exon 19 deletions (Ex19del) and T790M, respectively using ddPCR platform. Their Limit of Detection (LOD) could reach 0.01% at 100 ng of input DNA. Subsequently, we conducted a large retrospective clinical study to systematically compare the detection performance of ddPCR and NGS across three mutation types using approximately 1,000 EGFR-positive samples, including cell-free DNA (cfDNA), pre-capture NGS libraries of cfDNA (cfDNA-prePCR), FFPE-derived DNA (ffpeDNA), pre-capture NGS libraries of FFPE-derived DNA (ffpeDNA-prePCR), fresh tumor tissue DNA (ttDNA), pre-capture NGS libraries of ttDNA (ttDNA-prePCR), pleural effusion supernatants DNA (peDNA), and pre-capture NGS libraries of peDNA (peDNA-prePCR). They were analyzed for detection concordance and VAF correlation. Especially, we made comparisons of the tumor DNA, including ctDNA and tumor tissue DNA, with their paired pre-capture NGS library. ResultsKey findings demonstrated excellent overall agreement between NGS and ddPCR. The mutation detection concordance rates were 98.72% (overall), with subtype-specific rates of 98.93% (L858R), 99.23% (Ex19del), and 97.14% (T790M). VAF measurements between ddPCR and NGS showed exceptional correlation (Pearsons r = 0.975, P<0.001). Notably, pre-capture NGS libraries showed remarkable VAF concordance with their source materials (0.993 for cfDNA libraries vs cfDNA; 0.998 for tumor tissue libraries vs tumor DNA with EGFR L858R; 0.991 for tumor tissue libraries vs tumor DNA with EGFR Ex19del). ConclusionsNGS and ddPCR demonstrate high concordance in EGFR mutation detection and VAF quantification, supporting their complementary roles in clinical testing. Using pre-capture libraries as an alternative to source samples can avoid repeat biopsies and enables subsequent testing for patients with inadequate FFPE sample quantity. These findings establish an evidence base for integrated diagnostic paradigms leveraging NGSs multiplexing power and ddPCRs sensitivity.

cancer biology↗

bioRxiv2025

Unraveling Streptococcus pyogenes Carriage: Genomic and Transcriptomic Insights from Acute and Post-Treatment Phases

The carrier state of Streptococcus pyogenes (Group A Streptococcus, GAS), is defined by the presence of the organism without symptoms or an immune response. Carriage poses challenges for clinical management and contributes to transmission in the community. Prior studies suggest genetic and phenotypic differences between isolates from symptomatic (acute) infections and those from carriers, yet comprehensive genomic and transcriptomic analyses of naturally acquired human GAS carriage have been lacking. In this study, we collected longitudinal samples from individuals before and after antibiotic treatment for acute pharyngitis, performing whole genome sequencing and RNA-seq on selected isolates. This is the first report of transcriptional profiling of GAS directly from human derived oropharyngeal swabs. Genomic analysis revealed no consistent carrier-specific genotypes, and in vitro assays showed no major differences in biofilm formation or antibiotic susceptibility between carrier and acute isolates. Transcriptional profiling from oropharyngeal swabs identified distinct gene expression patterns when comparing the acute infection and post-treatment carriage phases, although early acute expression profiles did not predict treatment failure. These findings suggest that GAS carriage is likely influenced by conserved bacterial traits as well as host factors, advancing our understanding of GAS persistence and transmission. SummaryLongitudinal samples were collected from individuals before and after treatment for acute Group A Streptococcal pharyngitis. Whole genome sequencing and RNA-seq was performed on selected isolates. This is the first report of transcriptional profiling of GAS directly from human oropharyngeal swabs. Distinct gene expression patterns were observed when comparing the acute infection and post-treatment carriage.

microbiology↗

bioRxiv2025

Automatic Classification of Circulating Blood Cell Clusters based on Multi-channel Flow Cytometry Imaging

Circulating blood cell clusters (CCCs) containing red blood cells (RBCs), white blood cells (WBCs), and platelets are significant biomarkers linked to conditions like thrombosis, infection, and inflammation. Flow cytometry, paired with fluorescence staining, is commonly used to analyze these cell clusters, revealing cell morphology and protein profiles. While computational approaches based on machine learning have advanced the automatic analysis of single-cell flow cytometry images, there is a lack of effort to build tools to automatically analyze images containing CCCs. Unlike single cells, cell clusters often exhibit irregular shapes and sizes. In addition, these cell clusters often consist of heterogeneous cell types, which require multi-channel staining to identify the specific cell types within the clusters. This study introduces a new computational framework for analyzing CCC images and identifying cell types within clusters. Our framework uses a two-step analysis strategy. First, it categorizes images into cell cluster and non-cluster groups by fine-tuning the You Only Look Once(YOLOv11) model, which outperforms traditional convolutional neural networks (CNNs), Vision Transformers (ViT). Then, it identifies cell types by overlaying cluster contours with regions from multi-channel fluorescence stains, enhancing accuracy despite cell debris and staining artifacts. This approach achieved over 95% accuracy in both cluster classification and phenotype identification. In summary, our automated framework effectively analyzes CCC images from flow cytometry, leveraging both bright-field and fluorescence data. Initially tested on blood cells, it holds potential for broader applications, such as analyzing immune and tumor cell clusters, supporting cellular research across various diseases.

bioinformatics↗

bioRxiv2025

RNA viruses in water shape the viromes of shrimp and fish in aquaculture systems

Aquatic environments host immense RNA viral diversity, yet the extent to which waterborne viruses influence the virome of aquatic animals remains unclear. Here, we conducted a comprehensive longitudinal metatranscriptomic analysis of water, shrimp, and fish across multiple culture stages in aquaculture systems. We identified 3,211 RNA viruses spanning 21 viral supergroups, with 97.4% representing novel species. Water exhibited the greatest viral diversity (3,093 species), followed by shrimp (1,280) and fish (398), with most viruses detected in shrimp and fish also detected in water. Diversity analyses revealed increasing richness and significant compositional shifts in 92 high-abundance viruses (>1,000 RPM) across culture stages. Viral abundance in aquatic animals was strongly correlated with that in water, and the temporal trajectories of the 16 most abundant viruses were closely synchronized between water and shrimp. Furthermore, 337 virus species were shared among shrimp and two fish species, of which 309 were present in water. These findings demonstrated that RNA viruses in water shape the composition and dynamics of aquatic animal viromes, underscoring the importance of water virome surveillance and management for disease prevention in shrimp aquaculture.

microbiology↗

bioRxiv2025

Molecular and cellular dynamics of measurable residual disease progression in myelodysplastic syndromes

Cancer relapse after treatment invariably proceeds from the persistence and progression of measurable residual disease (MRD), an ultrasmall malignant population. Despite the poor prognostic impact established by increasingly sensitive MRD detection methods, the molecular pathways defining MRD remain unknown. To identify the unique features of MRD and the molecular forces shaping its progression, we performed single-cell multi-omic profiling on DNA, RNA and protein layers for a longitudinal patient cohort with relapsed myelodysplastic syndromes (MDS) after stem cell transplantation (SCT), the only curative modality for MDS. We provide a comprehensive molecular portrait of MRD cells with novel markers, shared across genetically heterogeneous patients. MDS relapse after SCT manifested universally with marked phenotypic evolution. Genotype and phenotype analyses revealed MRD progression as a dynamic, evolutionary process rather than a static expansionary one, driven by both subclonal sweeping and cell state transitions. Malignant cells adapted to infiltrating T cells by rewiring IFN-{gamma} responses to activate a key immunoevasive pathway. Our study demonstrates the power of longitudinal, single-cell multi-omic analysis for identifying, tracking, and understanding MRD cells, opening new avenues to target MRD persistence and progression.

cancer biology↗

bioRxiv2025

Deep Disentangled Representation Learning Reveals Neuron Subtype-Specific Nuclear Morphologies Across Aging in Mice and Humans

We present a computational pipeline that links nuclear morphology to mRNA expression-based cell phenotypes under diverse biological conditions, including aging, disease progression, and drug response, using RNAscope imaging. The pipeline consists of three components: nuclear segmentation from RNAscope images, nuclear morphology identification, and downstream statistical analysis. Central to our approach is a novel unsupervised method, based on deep disentangled representation learning, which effectively captures diverse nuclear morphologies in large-scale datasets, as validated on synthetic benchmarks. We applied the full pipeline to RNAscope data targeting dopaminergic and glutamatergic neuron populations in the midbrains of mice and humans. Our analyses uncovered distinct nuclear morphology differences between dopaminergic and non-dopaminergic, as well as glutamatergic and non-glutamatergic neurons, in both species. Moreover, we identified a significant interaction between neurotransmitter identity and healthy aging in mice, reflected in systematic changes in nuclear morphology. These findings position nuclear morphology as a scalable and informative imaging-based readout of cell identity and physiological state.

bioinformatics↗

bioRxiv2025

A newly identified Duck orbivirus as the etiological agent of egg-production decline in Chinese breeder ducks

The genus Orbivirus comprises double-stranded RNA viruses, many of which are transmitted by arthropods and cause febrile, hemorrhagic, or reproductive diseases in animals. In recent years, unexplained outbreaks characterized by marked egg-production decline have occurred in breeder duck flocks in China. To identify the causative agent, samples were collected from affected farms in multiple regions across China between 2022 and 2025. Representative samples were analyzed by high-throughput sequencing, followed by phylogenetic analysis, transmission electron microscopy, host cell infection assays, and animal challenge experiments. A previously unreported Orbivirus, designated Duck orbivirus (DORV), was identified. Epidemiological investigation indicated that outbreaks mainly affected breeder ducks during the peak laying period (21-55 weeks of age), with higher incidence in summer and autumn. The DORV genome contains ten double-stranded RNA segments encoding seven structural and five nonstructural proteins. Phylogenetic analysis showed that DORV is closely related to Parrys Lagoon virus (PLV) and Corriparta virus (CORV). Electron microscopy revealed icosahedral particles 30-40 nm in diameter. DORV replicated efficiently in DEF, DEL and C6/36 cells but not in MDCK and LMH cells, suggesting a restricted host range with potential arthropod-borne features. Infection of breeder ducks with DORV-SD01 reduced egg production by 30-40% and caused lesions in the ovary, liver, and spleen. This study describes a novel duck-origin Orbivirus linked to egg-production decline, offering new etiological insights and extending the host spectrum of Orbivirus. The results provide a foundation for future surveillance and prevention of emerging waterfowl diseases.

microbiology↗