Biology subjects

Zhao, X.

Publications and source records attributed to Zhao, X..

At least 73 records · Page 4Linked to original sources

bioRxiv2026

PanVariants: Best Practice for Pangenome-based Variant Calling Pipeline and Framework

BackgroundAlthough pangenome references offer richer population diversity compared to linear references, current mainstream pangenome-based variant callers are limited to detecting only known variants stored in the graph. To address this limitation, we developed PanVariants, a novel pipeline designed to improve the detection of both known and novel variants accurately. We systematically evaluated its performance against the traditional linear alignment solution (BWA+GATK/Manta) and the existing pangenome-aware solution (DRAGEN/PanGenie) in three contexts: small variants (SNVs/indels) and structural variants (SVs) accuracy in Genome in a Bottle samples, clinical detection on positive samples, and application in cohort-based joint calling. ResultsBy integrating k-mer-based and mapping-based methods, PanVariants significantly reduced variant errors (FPs + FNs), achieving a 73% reduction compared to BWA+GATK and a 45% reduction compared to DRAGEN for SNVs. Retraining the DeepVariant model with high-quality DNBSEQ data further decreased errors by 15%. For SVs detection, PanVariants attained an F1-score of 89.39%, markedly outperforming DRAGEN (68.18%) and BWA+Manta (58.33%), approaching long-read sequencing performance (95.22%). In validation using clinical positive samples, PanVariants successfully detected all expected pathogenic variants while PanGenie failed. In the cohort joint-calling analysis, PanVariants detected more variants, made fewer Mendelian inheritance errors, and gave better per-sample accuracy than GATK. ConclusionsPanVariants establishes a robust framework and best-practice pipeline for pangenome-based variant detection, achieving both sensitive novel variant discovery and high accuracy for SNVs, indels and SVs. Our systematic evaluation of optional processing steps and input variables offers practical guidance for users. Validated across diagnostic and population-based applications, our findings strongly support the transition from linear to pangenome references in future genomics.

bioinformatics↗

bioRxiv2026

Cardiac oxidative stress monitoring enabled by hierarchical mechanical adaptation

Soft bioelectronics have advanced cardiac monitoring through electrophysiological tracking, yet this alone cannot resolve the metabolic pathology essential to surgical decision-making. However, real-time molecular sensing on beating hearts remains unresolved due to deformation-induced sensor failure and stress-induced metabolite artifacts. This challenge is exemplified by ischemia-reperfusion injury (IRI), a major cardiac surgery complication characterized by reactive oxidative species (ROS) bursts, where true pathological ROS signals being confounded by mechanotransduction-induced ROS artifacts. Herein, we propose an enzymatic cardiac oxidative stress biosensor (E-cardiac) with hierarchical mechanical adaptation: macro-scale biofluid-mediated contact, micro-scale fiber reorganization, and nano-scale enzymatic confinement within gold nanoarches dissipate interfacial stress. This produces ultrathin ([~]460 nm), soft (0.79 kPa) E-cardiac with robust electrochemical stability (100% strain), low detection limit (380 nM), rapid adhesion (<3 s), stable biosensing on beating heart, as well as minimal invasive deployment capability. Mechanical analysis and cellular studies confirm mitigated stress-induced ROS and absent PIEZO channel activation. Validated across cardiomyocytes, ex vivo tissues, multi-species ischemia models (mouse, rat, rabbit, pig), rat ischemia-reperfusion injury, and Langendorff hearts simulating graded perfusion deficits, E-cardiac quantitatively differentiates IRI severity (sham < ischemia < reperfusion) as well as detecting the "ECG blind window". The E-cardiac platform provides real-time metabolic feedback for surgical guidance during cardiac procedures, enabling timely intervention before irreversible damage.

bioengineering↗

bioRxiv2026

Pan-cancer circular genomics identifies intratumoral Staphylococcus lugdunensis as a metabolic driver in bladder cancer

Intratumoral microbiota play key roles in cancer but are challenging to profile due to low biomass. We developed CIRCMIP, an enzymatic pipeline that eliminates linear DNA to enrich bacterial genomes, achieving 100-fold higher sensitivity than standard metagenomics. Applied to 312 pan-cancer specimens, CIRCMIP identified Staphylococcus lugdunensis as a signature bacterium enriched in early-stage bladder cancer (BLCA), where its presence predicts poor survival. Integrated modeling and lipidomics revealed that Staphylococcus lugdunensis colonization drives aberrant lipid metabolism with secretion of LPC14:0. Both Staphylococcus lugdunensis and LPC14:0 drive BLCA progression by promoting fatty acid uptake and {beta}-oxidation. Mechanistically, chemical proteomics revealed LPC14:0 as a direct PPAR{delta} ligand, binding via hydrogen bonds with Thr292/Thr289. This activation upregulates fatty acid transporters (CD36, FABP4) and metabolic enzymes (ACOX2), fueling malignant proliferation. Furthermore, CIRCMIP-derived biomarkers show robust diagnostic accuracy, establishing a new research paradigm and revealing the Staphylococcus lugdunensis-LPC14:0-PPAR{delta} axis as a therapeutic target in bladder cancer. HIGHLIGHTO_LICIRCMIP leverages DNA circularity to achieve 100-fold sensitivity in pan-cancer bacteriome profiling. C_LIO_LIStaphylococcus lugdunensis is a bacterial signature in early-stage bladder cancer that predicts poor patient survival. C_LIO_LIBacteria-derived LPC14:0 acts as a direct ligand for PPAR{delta} to drive host malignant metabolic reprogramming. C_LIO_LITargeting the Staphylococcus lugdunensis-LPC14:0-PPAR{delta} axis abrogates malignant progression in bladder cancer. C_LI

cancer biology↗

bioRxiv2026

Adaptation of the freshwater anaerobic methanotroph 'Ca. Methanoperedens vercellensis' to low pH levels reveals membrane lipid remodelling

Anaerobic methanotrophic archaea are key members of the biological methane filter, thereby preventing emissions of this strong greenhouse gas into the atmosphere. Previous studies on freshwater anaerobic methanotrophs targeted the activity of these microorganisms at circumneutral pH whereas molecular ecology studies identified this phylotype also in acidic environments such as peatlands; it is currently unknown whether they can adapt to low pH and remain effective in the biological methane filter in low pH environments. Here we show that a granular enrichment culture of the freshwater methanotroph Ca. M. vercellensis loses activity when experiencing pH stress but remains metabolically active down to pH 5.65 with appropriate adaptation time, indicating that adaptive changes are necessary to accommodate anaerobic methane oxidation at lower pH. Analyses of archaeal lipids revealed an increase in zwitterionic intact polar lipids over anionic lipids as an adaptation. This coincided with a change in granule structure while methane oxidation rate and enrichment state of Ca. M. vercellensis remained stable. We show that Ca. M. vercellensis remains metabolically active at lower pH values, despite increased maintenance energy demands and the need for cytoplasmic pH homeostasis. Our study demonstrates that adaptations to stress by slow-growing microorganisms may require long-term observation and is thereby instrumental for a better understanding of methane cycling in acidic ecosystems.

microbiology↗

bioRxiv2026

Sex-specific plasticity mechanisms mediating fear extinction

Strong evidence suggests synaptic plasticity is the critical cellular mechanism underlying learning and memory. Although the forms of synaptic plasticity used by different circuits vary, a widespread presumption is that the male and female brain has evolved to use the same form of plasticity within the same circuits during learning. We used complimentary approaches to determine how synaptic plasticity within the mouse frontal cortex supports extinction of associative memories. Here, we show that both male and female mice have similar ensemble dynamics in excitatory infralimbic cortical neurons during learning. However, activity in amygdala-projecting neurons was required for extinction memories only in male mice. Likewise, only male mice showed evidence for structural synaptic remodeling and clustering of dendritic spines on infralimbic-amygdala projection neurons. Projection-specific deletion of the glutamate receptor subunit GRIN2B blocked synaptic plasticity and impaired extinction memory in male but not female mice. These distinct mechanisms could be leveraged for precise therapies for mental health conditions relative to the present one-size-fits-all approach.

neuroscience↗

bioRxiv2026

Curvature-mediated prewetting organize mitochondrial nucleoid

The emergence of spatiotemporal order in diffusive cellular environments requires physical mechanisms to overcome the entropic drive toward disorder. While the organizing role of chemical signaling is well characterized, how complex membrane curvature regulate soluble molecular organization remains a fundamental open question. Here, we establish membrane curvature as a thermodynamic control parameter for the condensation of soluble proteins through prewetting. Using the mitochondrial transcription factor TFAM, we demonstrate that intrinsic membrane curvature locally drives a prewetting transitiona surface-mediated phase separation distinct from bulk condensation. By combining in vitro reconstitution, live-cell super-resolution imaging, cryo-electron tomography, and thermodynamic theory, we show that negatively high-curvature regions lower the nucleation energy barrier of Tfam, driving localized protein condensation at physiological concentrations. These results reveal that membrane curvature does not merely scaffold cellular machinery but manipulates the local free energy landscape, establishing a geometric principle for the spatial control of biological processes.

biophysics↗

bioRxiv2026

End-to-end bimodal anti-counterfeiting by informational DNA nanoparticles

The superior stealth properties and high information density make DNA a sought-after candidate in the field of molecular steganography. Here, we developed the InfinMark end-to-end DNA steganography framework for anti-counterfeiting applications by combining the characteristics of both the Internet of Things (IoT) and DNA-of-Things (DoT). InfinMark includes five modules: Information Transcoding, Fingerprint Writing, Nano-encapsulation, Invisible Marking, and Multi-level Rapid Authentication. It ensures precise anti-counterfeiting information reading and writing through a dynamic DNA-compatible transcoding algorithm, achieves seamless embedding by developing scalable nanoparticle manufacture methods, and supports cross-scenario on-site verification, ultimately granting it comprehensive anti-counterfeiting capabilities spanning from source labeling to terminal tracing. By addressing the bottlenecks in IoT and DoT integration, lifecycle tracking, as well on-site product authentication, this research constructs a full-chain bimodal anti-counterfeiting system, thereby showcasing the practical application of informational DNA nanoparticles in various aspects of production and daily life.

synthetic biology↗

bioRxiv2026

Structural Mechanism of TRPC3 Channel Activation by the Moonwalker Mutation

TRPC3 is a calcium-permeable, non-selective cation channel that is activated by DAG. It is expressed in several tissues, especially in the cerebellum, and has been implicated in various human diseases. Despite recent progress in understanding the structural mechanism of TRPC3, how the channel opens remains elusive. Here, we present structures of hTRPC3 in an agonist-free resting state, determined using a DAG-binding site mutant. We also present the structure of hTRPC3 in a DAG-bound open state, determined using a constitutively active "moonwalker" (T561A) mutant. These structures, together with electrophysiological results, reveal that the T561A mutation activates hTRPC3 by disrupting a polar interaction with N652. A newly formed {pi}-bulge in S6 leads to rotation and outward tilting of the lower half of S6, resulting in dilation of the pore and thus channel opening. Agonist DAG stabilizes hTRPC3 in the open conformation. BTDM exerts its inhibitory effect by pushing S5 and S6 back to the center to close the pore, while preserving the {pi}-bulge. These results shed light on the opening mechanism of hTRPC3.

biophysics↗

bioRxiv2026

Symmetric Self-play Online Preference Optimization for Protein Inverse Folding

Multi-objective reinforcement learning based on predicted structure feedback has been introduced into protein inverse folding. However, existing methods typically rely on a single model to optimize multiple structural objectives via a scalarized reward, which can bias the optimization toward dominant objectives and limit the exploration of diverse solutions. Here, we propose a online Symmetric Self-play Preference Optimization (SSP) framework that decouples the optimization of multiple structural objectives by training separate preference models with distinct reward signals, while enabling interaction through a shared sampling pool. This design allows the models to explore diverse optimization trajectories without enforcing a single dominant direction. Extensive experiments on both natural and de novo binder backbone inverse folding tasks demonstrate that SSP consistently improves sequence design self-consistency compared to single-model and existing baselines. Further analysis shows that different structural objectives are only partially aligned and induce distinct optimization directions, as evidenced by metric correlation and white-box analyses. This supports the effectiveness of decoupling objectives to enable higher design quality in protein design.

bioinformatics↗

bioRxiv2026

The Glucose Transporter GLUT3 Controls Regulatory T Cell Function

Regulatory T (Treg) cells are central mediators of immune tolerance and are generally considered to rely predominantly on mitochondrial metabolism rather than glucose-driven glycolysis. To define the role of glucose metabolism in Treg cells, we investigated the contribution of the hexose transporters GLUT1 and GLUT3. Genetic ablation of GLUT1 in T cells or selectively in Treg cells had minimal impact on Treg cell numbers, phenotype or immune homeostasis, indicating that GLUT1 is largely dispensable in this lineage. By contrast, deletion of GLUT3 in T cells resulted in a marked reduction in Treg cell numbers. However, it remained unclear whether this reduction reflected diminished IL-2 production by GLUT3-deficient conventional T cells or a cell-intrinsic requirement for GLUT3 in Treg cells. To investigate this, we generated mice with Treg cell-specific deletion of GLUT3. These animals developed severe systemic inflammation accompanied by lethal cellular and humoral autoimmunity. Mechanistically, GLUT3-deficient Treg cells exhibited reduced glycolytic activity and mitochondrial respiration, leading to impaired suppressive function and defective effector and follicular Treg cell differentiation. Collectively, our findings demonstrate a non-redundant requirement for GLUT3 in Treg cell metabolic fitness and immune regulation, refining the prevailing view that Treg cells operate largely independently of glucose metabolism. Our data further suggest that therapeutic strategies targeting glucose uptake and glycolysis in autoimmune and inflammatory diseases should account for potential adverse effects on Treg cell-mediated immune tolerance.

immunology↗

bioRxiv2026

Copper Import via CTR1 Supports the β3-Adrenergic Thermogenic Program

Adaptive thermogenesis requires coordinated activation of mitochondrial oxidation and metabolic remodeling, yet the signals driving this coordination are incompletely understood. Here, we show that cold exposure and {beta}3-adrenergic receptor ({beta}3-AR) stimulation upregulate the high-affinity copper (Cu) importer CTR1 and promote Cu accumulation in thermogenic adipose tissues. Adipocyte-specific Ctr1 knockout (ACKO) mice exhibit markedly reduced energy expenditure and develop severe hypothermia during acute cold challenge. Proteomic analysis of brown adipose tissue (BAT) from ACKO mice reveals coordinated suppression of oxidative phosphorylation and thermogenic metabolic programs, accompanied by attenuation of lipolytic pathways. Cu deficiency also impairs cold- and {beta}3-AR-induced lipolytic activation, including reduced HSL phosphorylation and lipid clearance in both BAT and inguinal white adipose tissue (iWAT). Although BAT-specific Ctr1 deletion (BCKO) leaves acute {beta}3-adrenergic responses largely intact, these mice still exhibit cold intolerance, indicating that BAT Cu homeostasis is indispensable for sustaining thermogenic capacity during cold challenge. Treatment with the Cu ionophore elesclomol partially restores mitochondrial oxidative capacity and improves cold tolerance in ACKO mice. Together, these findings identify CTR1-dependent Cu import as a dynamically regulated component of the {beta}3-adrenergic thermogenic program and establish intracellular Cu availability as a key determinant of thermogenic capacity during adaptive thermogenesis.

molecular biology↗

bioRxiv2026

Coronavirus envelope protein drives iron sensing disorder by hijacking the TAp73-FDXR axis

Iron overload is increasingly recognized as a critical contributor to coronavirus pathogenesis1, yet the underlying induction mechanisms remain unclear. Here, we uncover a fundamental pathway by which coronavirus drives IRP1 RNA-binding activity to induce iron accumulation2 via targeting the TAp73-FDXR axis. Specifically, coronavirus infection represses transcription of FDXR (encoding the key rate-limiting enzyme in host iron-sulfur cluster synthesis3), thereby impairing host iron-sulfur cluster generation to trigger the functional conversion of the cytosolic aconitase 1 (ACO1) into iron-regulatory protein 1 (IRP1)4, ultimately leading to the hosts persistently false perception of iron deficiency. We identify TAp73 as the primary transcription factor governing FDXR expression, and demonstrate that the coronavirus envelope protein (CoV-E) orchestrates TAp73 nuclear export. Subsequently, CoV-E binds TAp73 through a critical valine residue within its C-terminal PBM domain, inducing the K48-linked ubiquitination and proteasomal degradation of TAp73. Furthermore, we developed a CoV-E-targeting molecule, DPTP-FC, which blocks CoV-E-TAp73 interaction via forming steric hindrance and effectively alleviates iron accumulation and tissue damage caused by PEDV, PDCoV, and SARS-CoV-2 infection. Our study reveals the central role of the TAp73-FDXR axis in CoV-induced iron accumulation, highlighting CoV-E as an attractive antiviral target and DPTP-FC as a promising therapeutic candidate.

microbiology↗

bioRxiv2026

Hyperactive STAT1 Promotes T Follicular Helper Type 1 Cell Differentiation to Trigger Autoimmunity

ABSTRACTSHeterozygous gain-of-function (GOF) mutations in signal transducer and activator of transcription 1 (STAT1) cause an inborn error of immunity characterized by immune dysregulation, recurrent infections and various autoimmune manifestations. However, the precise pathogenic mechanism by which STAT1 GOF contributes to autoimmunity remains elusive. In our cohort, STAT1-GOF patients exhibit biased circulating follicular helper T (cTfh) populations with CXCR3+ Tfh1-like features. Using a Stat1 GOF mouse model that spontaneously developed autoimmunity, we found that overactivated STAT1 promotes Tfh differentiation and disrupted T cell-dependent humoral responses with skewed immunoglobulin class switching towards IgG2. Furthermore, STAT1 GOF directly targets to Tfh and Th1 cell signature genes and thereby drives the development of Tfh1 cells with excessive IFN-{gamma} production, which implicated in autoantibody production and the development of autoimmunity. Notably, IFN-{gamma} neutralization significantly alleviated autoimmune cellular responses and autoantibody levels in mutant mice, highlighting IFN-{gamma} blockade as a promising targeted therapy for the STAT1-GOF patients with autoimmunity. Our findings suggest that proper regulation of STAT1 activity within a reasonable magnitude is crucial for ensuring optimal host-protective humoral immunity. One-sentence summaryOveractivated STAT1 promotes Tfh1 differentiation to drive autoimmunity.

immunology↗

bioRxiv2026

The enhanced multi-tissue atlas of regulatory effects in cattle

Cattle are integral to global food security, yet the molecular architecture of their complex traits remains poorly understood. Here, we present the Cattle Genotype-Tissue Expression (CattleGTEx) Phase 1 resource (https://cattlegtex.farmgtex.org/), a substantial expansion of the pilot study. By leveraging 12,422 RNA-seq profiles across 43 tissues and 82 breeds, we characterized 433,972 primary and 161,428 non-primary regulatory effects spanning seven molecular phenotypes. This high-resolution atlas resolves 75% of GWAS signals for 44 complex traits, significantly addressing the "missing regulation" in livestock. We propose a genetic regulatory model demonstrating how variants across multiple biological layers interact with specific biological contexts to shape phenotypic variation. Furthermore, CattleGTEx elucidates mechanisms underlying adaptive evolution between Bos taurus and Bos indicus, as well as artificial selection in dairy and beef breeds. Finally, by mapping evolutionary constraints on these regulatory effects, we demonstrate the translational value of this resource for prioritizing causal variants in human complex diseases. Together, Phase 1 of CattleGTEx provides a transformative framework for functional genomics, precision breeding, and comparative genetics.

genetics↗

bioRxiv2026

Decomap-seq enables efficient and reliable retrieval of spatial transcripts

Spatial transcriptomics (ST) has emerged as a transformative tool for resolving the molecular heterogeneity of complex tissues within their native anatomical context. However, next-generation sequencing (NGS)-based ST platforms frequently encounter sensitivity bottlenecks arising from sub-optimal probe architectures on solid substrates. Conventional single-stranded DNA coupling methods often lead to disordered interfacial molecular conformations due to non-specific nucleobase-mediated surface tethering, which creates steric hindrance and inhibits the enzymatic efficiency of in situ library preparation. Here, we present Decomap (double-strand protected combinatorial barcoding microarray chip), a high-performance ST platform utilizing a triple-segment (dsZ-X-Y) fabrication strategy to achieve superior transcript capture efficiency. This structural optimization significantly enhances DNA ligation kinetics and subsequent polymerase-mediated extension, overcoming the fundamental limitations of traditional single-stranded coupling strategies. Decomap-seq achieved a median detection of 7,200 genes and 29,097 UMIs per 50 m-spot at a sequencing saturation of 50.1%. These results validate Decomap as a highly sensitive and robust tool for spatial transcriptomics, offering a powerful platform for advancing research in histopathology, developmental biology, and neuroscience.

biochemistry↗

bioRxiv2026

Unbiased Single-Cell Transcriptome-Proteome Co-Profiling Reveals Malignant Dormancy and Post-Transcriptional Buffering of CTCs

Leptomeningeal metastasis is driven by rare cerebrospinal fluid circulating tumor cells (CSF-CTCs). However, the mechanisms underlying their adaptation to chemotherapeutic stress remain elusive, primarily because transcriptomics alone poorly predicts functional protein states. Here, we present scMAPS, a single-cell multi-omics method that employs magnetic-assisted partitioning cell lysates to enable unbiased transcriptome-proteome co-profiling without loss-prone physical splitting and precision device. By coupling scMAPS with our custom CLEAP (CTC Label-free Enrichment and Accurate Picking) system, we performed the first deep multi-omics profiling of rare clinical CSF-CTCs before and after localized chemotherapy, detecting an average of 2,547 proteins and 7,821 genes per cell. The integrated CLEAP-scMAPS pipeline reveals a coordinated prioritizing survival over proliferation malignant dormancy phenotype and identified post-transcriptional buffering as the primary driver of treatment resistance. Our platform enables the comprehensive molecular phenotyping of rare clinical specimens, providing a highly versatile framework for decoding complex post-transcriptional regulatory networks.

cell biology↗

bioRxiv2026

Sex-specific Genetic Regulatory Effects in Chickens

Sexual dimorphism is a defining vertebrate feature, yet its sex-specific molecular architecture remains poorly understood. Here we established a sex-balanced, uniformly reared chicken cohort to map this landscape, integrating individual whole-genome sequencing with 7,969 bulk and 779,380 single nucleus transcriptomes across 32 tissues from 280 birds. We identified 495,098 independent expression quantitative trait loci for 20,194 genes, including 10,937 loci modulated by cell-type composition. Notably, 340 genes were regulated by 449 loci in a sex-dependent manner, significantly enrichment in endocrine tissues like adipose and the adrenal gland. Furthermore, we fine-mapped 1,219 structural variants, demonstrating their unique roles to tissue- and sex-specific expression beyond SNPs. Ultimately, we showed the utility of these regulatory effects in elucidating the molecular basis of metabolism and complex traits in both chickens and humans. This comprehensive atlas of regulatory effects provides profound insights into the genomic and molecular basis of sexual dimorphism in vertebrates.

genomics↗

bioRxiv2026

Learning heritable multimodal brain representation via contrastive learning

Magnetic resonance imaging (MRI)-derived phenotypes (IDP) has enabled the discovery of numerous genomic loci associated with brain structure and function. However, most existing IDPs and learned representations are derived from a single imaging modality, missing complementary information across modalities and potentially limiting the scope of genetic discovery. Here, we introduce a multimodal contrastive learning framework to derive heritable representations from paired T1- and T2-weighted MRIs. Unlike single-modality reconstruction-based models, we designed a momentum-based contrastive learning framework. As a result, our approach offers improved prediction of traditional IDPs, age, and brain disorders. Notably, genome-wide association studies (GWAS) of the learned representations reveal a substantially higher overlap of genetic loci across modalities, indicating improved alignment of their underlying genetic architecture. Analysis of the GWAS loci identified shared protein and drug targets, yielding meaningful biological insights. Overall, our framework learns shared representations across brain imaging modalities that exhibit anatomical and genetic coherence.

bioinformatics↗