Biology subjects

Xia, Y.

Publications and source records attributed to Xia, Y..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Membrane proteomics of the Drosophila circadian neural network

Circadian behaviors are controlled by dedicated brain pacemaker neurons, whose activity oscillate during the day and the night. The Drosophila brain contains ca. 240 such neurons. Their molecular clock is synchronized, but the phase of their rhythmic neural activity differs dramatically between functional groups. This explains how specific circadian neurons can for example promote morning or evening locomotor activity. To understand in depth how the circadian network functions, we surveyed its membrane proteome in the morning and evening, using in situ protein labeling and mass spectrometry. In addition to detecting known regulators of circadian behavior, we identified novel membrane or membrane-associated proteins present in circadian neurons. Through genetic screens, we found that many of these proteins regulate circadian behavior. In particular, Piezo regulates morning activity specifically under short photoperiod, and its loss compromises the structural plasticity of the clock neurons controlling locomotion at dawn. Our work thus illustrates the power of proteome-guided genetic screens to understand the mechanisms underlying circadian behavior.

neuroscience↗

bioRxiv2026

The CK2 and DBT kinases promote temperature compensation of the Drosophila circadian clock via distinct pathways

Circadian ([~]24 h) rhythms are essential for the survival of most organisms, as they optimize physiology and behavior with the time of day. They are defined by three fundamental properties: they are driven by a self-sustained molecular oscillator, entrained by environmental cues such as light and temperature, and temperature-compensated, whereby circadian period remains close to 24 h over a physiological range of temperatures. The molecular basis of temperature compensation remains incompletely understood. Here, we build on previous studies supporting a conserved and important role for phosphorylation-dependent mechanisms in the control of temperature compensation. We found that reducing the activity of two highly conserved circadian kinases, DBT (casein kinase [CK] 1) and CK2, disrupts temperature compensation in Drosophila. Genetic analyses indicate that DBT and CK2 act through distinct pathways that have additive effects on temperature compensation. DBT acts through the perShort phosphorylation cluster and the S47 phosphodegron of the core clock protein PER, both of which are required for normal thermal compensation. In contrast, CK2 acts through a phosphocluster in TIM as well as PER S45 residue. Interestingly, simultaneous disruption of both pathways causes accumulation of hyperphosphorylated PER, which is inefficiently cleared from the nucleus of circadian pacemaker neurons. Combined with previous work, our findings support a central and unifying role for nuclear PER phosphorylation dynamics in buffering circadian period against environmental temperature fluctuations.

neuroscience↗

bioRxiv2026

Integrated RNA-seq analysis identifies ABC transporters mediating taxane export in Taxus species

RNA-seq datasets from medicinal yews are crucial for studying paclitaxel biosynthesis. However, cross-study data analyses are hindered by pronounced batch effects. Here, we compiled 45 RNA-seq samples from three studies across four tissues (bark, leaf, root, stem) and assessed 35 preprocessing pipelines combining six normalization strategies with five batch-effect correction approaches. Unsupervised clustering (HCA, k-means, Grade-of-Membership), evaluated using Jaccard and Adjusted Rand indices, revealed significant variability in batch effect removal. Supervised classification of tissue and project labels (Random Forest and linear/radial SVM) demonstrated improved accuracy in tissue type prediction, highlighting the effectiveness of correction methods. The processed data facilitated the identification of 189 putative ABC transporters across samples, six of which showing a strong correlation to the gene encoding 10-deacetylbaccatin-III-10{beta}-O-acetyltransferase, a key biosynthetic enzyme in the taxol pathway. High expression levels in leaf and bark further support their role in taxane intermediates trafficking in taxol biosynthesis. Structural analysis and molecular docking further supported the selection of these candidates, and the agreement between transcriptomic ranking and docking-based prioritization suggests that these transporters may participate in taxane intermediate recognition, trafficking, or export. These findings demonstrate the importance of normalization and batch effect correction in RNA-seq analysis to advance gene discovery in Taxus species and, more broadly, in plant research. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=152 SRC="FIGDIR/small/723993v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@1469162org.highwire.dtl.DTLVardef@1f2c4deorg.highwire.dtl.DTLVardef@15ad821org.highwire.dtl.DTLVardef@123676d_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2026

In vivo programming of stem-like CAR T cells by lymphatic-selective lipid nanoparticle enables durable anti-tumour efficacy in orthotopic model

Chimeric antigen receptor (CAR) T-cell therapy has shown remarkable efficacy in hematological malignancies, yet its efficacy in solid tumours remains limited by poor persistence and progressive exhaustion within the tumour microenvironment. These barriers may be particularly pronounced in emerging in vivo CAR-T therapies, in which transient transgene expression and insufficient control over T-cell differentiation restrict the generation of durable antitumour immunity. Here, we report a primary lymphoid tissue-targeting lipid nanoparticle (pLNP), that directs in vivo CAR-T programming to the thymus and lymphoid tissues, thereby increasing the proportion of stem-like CAR-T cells and promoting durable, exhaustion-resistant antitumour responses. After antibody conjugation, pLNP enabled in vivo CAR expression in developing T cells, generating CAR-T cells enriched in naive and stem cell-like memory phenotypes with prolonged persistence. To reinforce this, we co-administered interleukin-7 (IL-7) mRNA, which increased stem-like CAR-T populations, favoured progenitor exhausted T (Tpex) cells over terminally exhausted states, and enhanced cytotoxic function without overt inflammatory amplification. This stemness-promoting strategy also improved responsiveness to immune checkpoint blockade, producing synergistic antitumour effects with anti-PD-1 therapy, reducing LNP dose requirements, and inducing durable tumour regression with prolonged survival in both subcutaneous and orthotopic DLL3-positive small-cell lung cancer models. Similar enhancement of in vivo CAR-T efficacy was also observed in aged mice with thymic involution. Together, these findings illustrated that primary lymphoid tissue-directed in vivo CAR-T programming is a potential strategy to overcome insufficient persistence and progressive exhaustion in solid tumours.

bioengineering↗

bioRxiv2026

Knowledge Inclusive Machine Learning for Disease Gene Prioritisation

The predictive performance of machine learning models depends on the context available to them. In disease gene prioritisation, this context comprises two forms: specific context from sample-level experimental data, such as gene expression and protein-protein interaction networks, and general context from accumulated and curated biological knowledge capturing established relationships among genes, diseases, and pathways. Neither is sufficient alone: experimental data are sensitive to dataset-specific noise and lack broader biological grounding, while curated knowledge lacks the resolution required for gene-level discrimination. Consequently, most machine learning approaches relying solely on experimental data risk learning spurious correlations rather than underlying biology. Here we introduce Knowledge Inclusive Machine Learning (KIML), a paradigm that integrates both context types within a unified analytical pipeline. KIML combines experimental data with two types of general context: literature-derived representations from PubMed and structured biomedical knowledge graphs. We evaluate the approach on Developmental and Epileptic Encephalopathy and benchmark it against recent methods using publicly available datasets. Performance is assessed using temporal-split evaluation and biological evaluations, including ontology enrichment analysis. KIML consistently outperforms existing approaches, providing improved predictive accuracy and biologically meaningful insights. Furthermore, the framework generates interpretable explanations of gene prioritisation and demonstrates strong generalisability across six additional diseases.

genetics↗

bioRxiv2026

Mutation-induced biophysical destabilization as a key contributor to cancer-driving potential in the human structural protein interactome

A systems-level investigation of mutation-induced perturbations in the human structural protein interactome, the network of structurally resolved protein-protein interactions in human cells, provides mechanistic insight into the complexity underlying oncogenesis. Mutations can destabilize protein folding or specific protein-protein interactions, resulting in loss-of-function effects within the interactome. Although such network-level loss-of-function consequences may contribute to oncogenesis, previous studies have largely examined either folding or binding destabilization in isolation. Here, we performed structural and free-energy calculations to assess the impact of interactome-wide cancer-associated missense mutations on protein-folding stability and protein-binding stability. We assessed the cancer-driving potential of destabilizing mutations using a "fold difference" metric, defined as the ratio between the fractions of destabilizing mutations in datasets of cancer-associated and non-pathogenic mutations. We observed a strong positive correlation between biophysical destabilization and cancer-driving potential, with folding-destabilizing ("quasi-null") and binding-destabilizing ("edgetic") mutations within cancer-driving genes causing stronger structural and functional effects than those across the entire cancer genome. Our findings align with the expectation that cancer-driving genes are enriched in driver mutations and suggest that biophysical destabilization is a key contributor to cancer-driving potential. Overall, our study provides a biophysical perspective on the loss-of-function implications of destabilizing mutations across the interactome, enhancing comprehension of the intricate processes driving oncogenesis.

bioinformatics↗

bioRxiv2026

Antiviral reverse transcriptase-primase synthesizes protein-templated DNA

Defense-associated reverse transcriptases (DRTs) are widespread in bacteria1,2, but how multi-domain DRTs containing RT and additional catalytic activities coordinate antiviral defense remains unclear. Here we show that DRT7, which contains both reverse transcriptase (RT) and primase-polymerase (PP) domains, provides broad-spectrum anti-phage immunity through abortive infection and can be activated by a phage-encoded putative transcriptional regulator. Upon activation, DRT7 synthesizes long, protein-primed, palindromic poly(A)/poly(T)-rich duplex-like DNA. Cryo-electron microscopy structures reveal that RT initiates protein-primed, protein-templated, sequence-specific poly(T) synthesis through an arginine-rich recognition pocket without requiring a complementary nucleic acid template, thereby converting DRT7 from an inactive closed dimer to an active open dimer. The RT-produced poly(T) then serves as both primer and template for PP-mediated poly(A) extension, with iterative handoff between RT and PP generating palindromic, alternating poly(A)/poly(T) ssDNA tracts that assemble into fold-back duplex-like DNA. These findings uncover an unexpected antiviral strategy based on protein self-templating, sequence-specific duplex-like DNA synthesis and reveal how coupling RTs with additional catalytic activities expands the functional scope of nucleic acid synthesis pathways.

microbiology↗

bioRxiv2026

Biomolecular condensates provide a unique environment for redox-mediated protein crosslinking

Biomolecular condensates, often formed through liquid-liquid phase separation, are dynamic cellular compartments. Here, we demonstrate that a wide range of fluorescently tagged proteins undergo inadvertent, condensate-mediated crosslinking, resulting in rapid solidification of condensates under common fluorescence imaging conditions. The process is driven by excitation-induced, short-lived reactive oxygen species (ROS), whose otherwise limited crosslinking potential becomes uniquely enabled in the dense phase. In live cells, excitation-induced ROS potently trigger stress granule formation, while the ROS-driven solidification of condensates is modulated by compartment-dependent antioxidant buffering. Our findings demonstrate that condensates create a distinct environment that enables ROS chemistry unlikely to occur in the bulk cytosol. Furthermore, the cellular redox level can be a general regulator of condensate rheology. Beyond biological insights, our findings underscore the need for scrutiny when examining fluorophore-labeled condensates.

biophysics↗

bioRxiv2026

Divergent landscapes of positive and negative selection signatures across residue-resolved human-virus protein-protein interaction interfaces

Virus-targeted host proteins evolve under dual selective pressures. Negative selection preserves within-host interactions, while positive selection promotes adaptive changes to evade viral engagement. Viral and endogenous within-host partners can compete for binding, bringing distinct pressures together on the same interaction interface. Yet, the spatial organization of distinct selective pressures across virus-targeted host proteins, and how such pressures manifest across diverse interaction contexts, remains largely unknown. Here, we integrate an evolutionarily annotated map of human-virus protein-protein interactions (PPIs) with intra-protein residue-residue contact maps to probe the spatial organization of residue-level selective pressures across PPI interfaces of virus-targeted host proteins. Across all PPI interfaces collectively, we find that residues under positive selection are spatially clustered, whereas those under negative selection are broadly dispersed, with additional spatial segregation between positive and strongly negatively selected sites. Moreover, while positive selection is unevenly distributed across interfaces bound exclusively by viral proteins (exogenous-specific), they are more uniformly distributed across interfaces shared between viral and within-host partners (mimic-targeted), suggesting that adaptive pressure from viral targeting acts on the entire mimic-targeted interface, whereas it acts on only a subset of the exogenous-specific interface. Strikingly, clustering of positively selected residues is more pronounced between mimic-targeted and other interface types than within exogenous-or endogenous-specific interfaces alone, suggesting that mimic-targeted interfaces may serve as focal points of adaptive evolution. Overall, our multiscale framework of PPI interfaces and residue-level contacts reveals heterogeneous, context-dependent landscapes of selective pressures across virus-targeted host proteins, providing a high-resolution view of how adaptation and constraint are intricately balanced and coordinated within the host.

bioinformatics↗

bioRxiv2026

A confined gene drive for population modification in the malaria vector Anopheles stephensi

Gene drives are genetic elements that bias their own inheritance to spread desired traits in target populations, enabling population modification or suppression. Although homing-based drives can propagate efficiently, their potential for uncontrolled spread may present a challenge for field deployment. Thus, confined drive systems are needed. Here, we developed a confined modification drive, called Toxin-Antidote Recessive Embryo (TARE) drive, in the globally important malaria vector Anopheles stephensi. This drive works by cleaving and disrupting wild-type alleles in the germline or early embryo from maternally deposited Cas9. Disrupted alleles are recessive lethal, thus increasing the drive in a frequency-dependent manner. Inheritance bias was moderate in crosses between drive heterozygote mosquitoes, possibly due to low gRNA activity and thus moderate germline cleavage rates. Single-release cage trials confirmed the TARE drives ability to spread, although the drive ultimately declined due to fitness costs and resistance alleles associated with repetitive elements. Nonetheless our modelling analysis indicate that this TARE system could achieve population spread if the resistance issue is addressed. These findings demonstrate a functional prototype TARE drive in Anopheles stephensi and highlight key parameters governing its performance. Minor design optimizations could substantially improve efficiency and integrity, enabling rapid but confined population modification.

genetics↗

bioRxiv2026

Accurate detection of mosaic mutations at short tandem repeats from bulk sequencing data

Short tandem repeats (STRs) are among the most mutable regions of the human genome, yet their somatic mosaicism remains poorly characterized due to the technical challenges of distinguishing genuine mutations from high intrinsic polymorphism and sequencing noise. Here, we introduce BulkMonSTR, a computational framework that combines STR-specific error modelling with machine-learning classification to enable accurate detection of mosaic STR mutations from bulk next-generation sequencing data. BulkMonSTR identifies nucleotide-resolution mutations--including insertions, deletions, and single-nucleotide variants (SNVs)--and supports both control-independent and case-control study designs. Leveraging a comprehensive training dataset derived from pedigree-based validation and in silico spike-in simulations, our random forest classifier effectively discriminates true mosaic events from germline variants and technical artifacts. Benchmarking on simulated and real datasets demonstrates that BulkMonSTR achieves substantially improved precision and F1 scores across diverse coverages and variant allele frequencies. In normal samples, cancer samples and controlled in silico mixing experiments, BulkMonSTR consistently outperforms existing methods, capturing a broader spectrum of STR mutations--including those arising on non-reference alleles--while achieving high validation rates. By enabling systematic, genome-wide interrogation of STR mosaicism, BulkMonSTR provides a scalable foundation for investigating the contributions of somatic STR mutations to aging and disease.

bioinformatics↗

bioRxiv2026

Clarified an rDNA Gene Unit Pattern with (CTTT)n and (CT)n Microsatellites Aggregation Ahead of and Behind the Gene in Human Genome

BackgroundConventional models of human ribosomal DNA (rDNA) array organization have historically depended on transcription-centric boundaries, partitioning the unit into a [~]13 kb rDNA transcription region and a monolithic [~]31 kb intergenic spacer (IGS). While our previous identification of Duplication Segment Units (DSUs) mapped these arrays based on an intuitive analysis of the microsatellite density landscape of the complete reference human genome, our present deep mining of this landscape has revealed a more accurate rDNA Gene Unit Pattern. Methods & ResultsIn this study, we conducted a deep mining analysis of our previously established microsatellite density landscape of the T2T-CHM13 assembly, focusing specifically on nucleolar organizing regions (NORs). We suggest a more accurate rDNA Gene Unit Pattern containing a (CTTT)n microsatellite aggregation ahead of the rDNA gene and a (CT)n microsatellite aggregation behind the gene, rather than a pattern featuring an IGS region inserted between two rDNA genes. ConclusionsA correct rDNA gene pattern of the human genome probably includes a (CTTT)n microsatellite aggregation ahead of the gene and a (CT)n microsatellite aggregation behind it, which possibly constitute cis- and trans-regulating regions; the (CTTT)n and (CT)n microsatellite aggregations may provide two different local stable DNA structures for regulatory protein binding.

genetics↗

bioRxiv2026

Digital Twin Brain simulation and manipulation of a functional brain network underlying mental illness

Linking synaptic-level perturbations to distributed brain-network dynamics remains a central challenge for understanding and treating mental illness. Although recent whole-brain models can reproduce individual brain activity patterns, they largely function as descriptive simulators rather than mechanistic, intervention-capable systems. Here we present an intervention-capable digital twin of the human brain, integrating individual neuroanatomy and task-evoked dynamics within a neuronal-scale framework. Individualised digital twin brains recapitulate a participant-specific compact cortico-subcortical network phenotype that captures transdiagnostic psychopathology across population and clinical cohorts. In silico modulation of excitatory and inhibitory synaptic conductance produces bidirectional, heterogeneous network responses across individuals. Population-scale simulations stratify individuals and predict longitudinal symptom trajectories from DTB-derived response profiles. Independent pharmacological functional MRI data further validate the predicted baseline-dependent network responses in vivo. Together, these findings establish digital brain models as experimental platforms for mechanistic perturbation, behavioural prediction and stratification, providing a foundation for precision neuroscience and psychiatry.

neuroscience↗

bioRxiv2026

Hypoxia-activated scleraxis a mediates epicardial progenitor differentiation into a unique cardiac perivascular cell type

The epicardium is a crucial source of progenitor cells and paracrine signals that support heart development and regeneration. However, the molecular mechanisms that guide epicardial cell fate decisions remain incompletely understood. Here, we identify the transcription factor Scleraxis a (encoded by scxa) as a key regulator of epicardial progenitor differentiation in zebrafish. Through single-cell transcriptomics, genetic lineage tracing, and cardiac injury models, we show that scxa is transiently induced in activated epicardial progenitor cells (aEPCs) during both heart regeneration and developmental coronary angiogenesis. scxa+ epicardial cells primarily give rise to a previously uncharacterized cardiac population of perivascular cells marked by col18a1a, molecularly distinct from classical pericytes and vascular smooth muscle cells. We refer to this population as epicardial-derived perivascular mesenchymal cells (Epi-PMCs). These Epi-PMCs closely associate with coronary vessels and may contribute to vascular stabilization and remodeling, potentially through the anti-angiogenic but vessel-stabilizing activity of endostatin derived from collagen XVIII. Loss of scxa increases coronary vessel density. Mechanistically, we identify hypoxia and Hif1a signaling as upstream regulators of scxa, with systemic hypoxia or Hif factor stabilization robustly inducing scxa expression in the epicardium. Together, these findings uncover a hypoxia-responsive Scxa-Col18a1a axis that drives epicardial differentiation toward a vascular-supportive fate, offering new insight into the regulation of coronary vessel development and the regenerative potential of the epicardium.

developmental biology↗

bioRxiv2026

Functional activation reveals a repressor-gated fourth type VI secretion system in clinical Pseudomonas aeruginosa

Pseudomonas aeruginosa is a major opportunistic pathogen in which the type VI secretion system (T6SS) contributes to interbacterial competition and virulence. While most strains encode three T6SSs, we here functionally characterize a fourth system (H4-T6SS) in a clinical P. aeruginosa isolate. The H4-T6SS gene cluster is transcriptionally silent under laboratory conditions. By promoter rewiring, we demonstrate that the H4-T6SS assembles a contractile machine and mediates effector secretion and robust inter- and intraspecific antagonism. We identify a dominant pore-forming effector and its secretion pathway and a silent yet conserved nuclease effector. Genetic and biochemical analyses show that H4-T6SS expression is activated by an H4-encoded transcriptional regulator and repressed by H-NS family proteins. Analysis of over 1,200 clinical isolates reveals that the H4-T6SS is distributed across lineages and geographic regions. Finally, we observe functional crosstalk between H4- and H2-T6SSs. Together, these findings establish H4-T6SS as a functional and repressor-gated secretion system that expands the competitive arsenal of clinical P. aeruginosa.

microbiology↗

bioRxiv2026

MAMBAxBrain: A Multi-task Neural Framework Linking Brain Functional Dynamics to Individual Fingerprints, Cognitive and Disease States

Functional magnetic resonance imaging (fMRI) contains rich individual, cognitive, and pathological information, yet no universal model exists for multi-task modeling of these dimensions. Here, we introduce MAMBAxBrain, a multi-task neural framework that integrates Mamba architecture with functional connectivity analysis to jointly model the temporal dynamics and spatial coordination of neural activity. MAMBAxBrain achieves high accuracy across four distinct fMRI objectives--brain fingerprinting, cognitive task decoding, reaction time prediction, and schizophrenia classification--consistently outperforming state-of-the-art methods with robust crosssession generalization. Interpretability analyses show that each task engages distinct, biologically plausible circuitry--from higher-order association cortex for identity to subcortical-motor loops for reaction time and disrupted control-sensory connectivity for schizophrenia. These findings inform a longstanding debate: rather than operating through wholly separate or entirely shared systems, the brain preferentially recruits task-specific circuits while retaining common representational structure across functions.

neuroscience↗

bioRxiv2026

Early developmental placental defects and pregnancy loss in lupus mice expressing human TLR8

Anti-phospholipid (APL) autoantibodies confer a high risk for adverse pregnancy outcomes, especially in Systemic Lupus Erythematosus (SLE). While human TLR8 (huTLR8) has been implicated in APL antibody-mediated placental injury in vitro, its in vivo role in pregnancy is unexplored. We report a novel mouse model of pregnancy loss in SLE-prone mice expressing huTLR8. Placental analysis revealed early developmental defects starting post-implantation, including a thin junctional zone, impaired vascularization, infarcts, and inflammation. Profound immune dysregulation was evident at E8.5 including increased myeloid cells and CD8 T cells and decreased uterine natural killer (uNK) cells. RNA sequencing revealed downregulated pregnancy-specific glycoproteins, reduced uNK cell-associated genes, and an upregulated myeloid cell signature. Bone marrow chimera studies demonstrated preferential activation of huTLR8-expressing placental Ly6C+ monocytes. Spatial transcriptomics at E9.5 confirmed uNK cell loss, decreased IL15 expression by both stromal and myeloid cells, and discrete inflammatory aggregates in the maternal layers containing myeloid cells and IFN{gamma}-expressing CD8 T cells. We propose that huTLR8, likely through myeloid cell activation and cytolytic T cell recruitment, drives placental injury in the context of SLE and APL autoantibodies. This model provides a valuable platform to dissect early pathogenic events in APL-associated pregnancy loss and identify new therapeutic targets.

immunology↗

bioRxiv2026

Detection of Somatic Point Mutations Directly from Spatial Transcriptomics Enables in vivo Spatiotemporal Lineage Tracing

Spatial transcriptomics reveals tissue organization but lacks in vivo lineage-tracing methods applicable to humans. We introduce SpaceTracer, a computational framework that accurately detects somatic single-nucleotide variants (SNVs) directly from spatial transcriptomics data. By leveraging naturally occurring somatic SNVs, SpaceTracer reconstructs cellular phylogenies within native tissue architecture, enabling the mapping of lineage spread, migration, lineage-coupled expression changes and lineage-aware local interactions. Applied to human cutaneous squamous cell carcinoma, it traced tumor initiation and progressions, uncovered widespread pre-invasive migration of dedifferentiated epithelial cells and characterized mutant B cells migrating from tertiary lymphoid structures (TLS) into the tumor boundary. The framework also reconstructed developmental lineages across multiple tissues and identified tissue-resident mutant immune cells. SpaceTracer thus provides a perturbation-free platform for high-resolution spatiotemporal lineage tracing, offering a transformative tool for elucidating complex biological systems--especially tumor-immune ecosystems--with direct implications for advancing cancer immunotherapy.

bioinformatics↗