Biology subjects

Xiao, X.

Publications and source records attributed to Xiao, X..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Genetic variation shapes human mRNA translation and disease risk

Genetic variation can influence protein abundance through translation, yet this regulatory layer remains poorly defined. We developed a deep learning approach to systematically map the effects of single-nucleotide variant (SNV) on translation efficiency (TE) across the human genome. In lymphoblastoid cells, >90,000 variants substantially altered TE, with strong positional and sequence-context biases. Importantly, the missense variants, traditionally considered only for their effect on protein recoding, were also found to reshape translation efficiency, with proline substitutions consistently reducing TE in a length-dependent manner. Extending our analysis to eight additional cell types revealed a two-layer architecture of translational regulation: 5UTR variants produced highly concordant effects across cell types, whereas synonymous and missense variants in coding region exhibited cell type-specific outcomes, suggesting context-dependent translation regulation. TE-altering variants were enriched among GWAS loci and linked to cancer, immune, cardiometabolic, and neurological traits, positioning translation as a key mediator of genetic effects on disease.

genetics↗

bioRxiv2026

The genetic repertoire of the deep sea: from sequence to structure and function

The deep sea as the largest and maybe most hostile environment on Earth is still underexplored especially regarding its genetic repertoire. Yet, previous work has revealed significant habitat-specific deep-sea biodiversity. Here, we present an integrated deep-sea genetic dataset comprising 502 million nonredundant genes from 2,138 samples and 2.4 million predicted structures, and used it to link specific protein structures with genetic variants associated with life in the deep sea and to assess their biotechnology potential. Combining global sequence analysis with biophysical and biochemical measurements revealed unprecedented sequence diversity, yet substantial structural conservation of proteins. Especially proteins involved in replication, recombination, and repair were identified to be under rapid evolution and with specialized properties. Among these, a structurally divergent helicase exhibited advantages in controlling nanopore sequencing speed. Thus, our work positions the deep sea as a unique evolutionary engine that generates and hosts genetic diversity and bridges genetic knowledge with biotechnology.

bioinformatics↗

bioRxiv2026

Identification of clofibric acid as a SYVN1 ligand for PROTAC development

Targeted protein degradation (TPD) is an emerging therapeutic modality for numerous diseases. PROteolysis-TArgeting Chimeras (PROTACs) represent a potentially generalizable strategy to achieve TPD. A PROTAC is composed of a ligand for a protein of interest, a linker and a ligand for E3 ligase. As such, PROTACs can bring the E3 ligase into the close proximity of a protein target leading to polyubiquitination followed by target protein degradation. While the human genome encodes over 600 E3 ligases, only a handful of them have been harnessed for developing PROTACs. In order to expand the repertoire of E3 ligases for PROTAC development, we developed clickable photoaffinity probes based on clinically used drugs and metabolites to identify potential E3 ligases as the targets. In this paper, we report the discovery of clofibric acid with a molecular weight of only 214 Daltons as a ligand for synoviolin (SYVN1). We demonstrate its utility by developing clofibric acid-based BRD4 PROTACs. The linker length and architecture play a critical role in target degradation efficiency. The clofibric acid-derived BRD4 PROTACs achieve selective BRD4 degradation in a SYVN1-dependent manner. Our findings establish clofibric acid as a robust addition to the TPD toolbox, offering a novel E3 ligase recruitment strategy for the development of next-generation degraders. TOC Graphics O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=90 SRC="FIGDIR/small/701774v1_ufig1.gif" ALT="Figure 1"> View larger version (15K): org.highwire.dtl.DTLVardef@776850org.highwire.dtl.DTLVardef@1616bd0org.highwire.dtl.DTLVardef@ed3e03org.highwire.dtl.DTLVardef@18271e7_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2026

Myeloid CD209 impairs T-cell activation by inducing ICAM-2-ERM-dependent cortical stiffening

Resistance to PD-1-based immunotherapy remains a major challenge in cancer treatment, especially in immunologically "cold" tumors characterized by T-cell exclusion and impaired effector function. Tumor-associated myeloid cells are important mediators of this resistance, but whether they directly suppress T-cell immunity through mechanical regulation remains unclear. Here, we identify DC-SIGN (CD209), a myeloid-expressed C-type lectin receptor, as a mechanosuppressive regulator of antitumor T-cell immunity. DC-SIGN is selectively enriched in tumor-infiltrating M2-like macrophages and monocytes, and its expression is associated with poor clinical response to PD-1 blockade and elevated TIDE scores across multiple cancer types. Mechanistically, DC-SIGN directly engages ICAM-2 on T cells and activates ROCK1-ERM signaling. This interaction increases T-cell cortical stiffness, destabilizes T cell-antigen-presenting cell interactions, and attenuates T-cell receptor signaling. Blocking the DC-SIGN-ICAM-2-ERM pathway restores T-cell activation and promotes CD8+ T-cell infiltration and effector function in mouse, humanized, and ex vivo human tumor systems. Importantly, DC-SIGN blockade overcomes resistance to PD-1-based immunotherapy in refractory and immunologically "cold" tumor models, and further enhances the response to PD-1 inhibition. Together, our findings define a myeloid-derived mechanical immune checkpoint and reveal T-cell mechanosuppression as a targetable mechanism of tumor immune evasion and immunotherapy resistance.

immunology↗

bioRxiv2026

Time Cells in the Human Brain Support Working Memory Maintenance

Working memory (WM), the active retention of information over short periods, is a fundamental cognitive function, yet its underlying neural mechanisms remain unclear. In rodents, cue-selective "time cells" fire at specific timepoints after a WM memory cue, collectively forming sequences that encode cue-memory and elapsed time, providing a temporal code for maintaining information across time intervals. Whether similar dynamics support WM in the human brain is unknown. Here, we analyzed intracranial single-neuron recordings from medial frontal and medial temporal regions of patients performing a WM task. We found time cells with temporally tuned activation during WM maintenance, collectively forming robust sequences that tiled a delay period. Time-cell coordination in the hippocampus predicted successful WM maintenance, whereas in the pre-supplementary motor area it reflected memory load. Furthermore, we identified distributed cue-selective time cells that encoded both the identity of a memorandum and elapsed maintenance time, providing a temporally structured mnemonic code that complements persistent firing of concept cells. Together, these findings establish time-cell sequences as a conserved neural mechanism supporting human working memory.

neuroscience↗

bioRxiv2026

3D reconstruction of spatial transcriptomics with spatial pattern enhanced graph convolutional neural network

Spatially resolved transcriptomics (SRT) is a promising new technology that enables simultaneous analysis of gene expression and spatial information for biomedical research. However, the existing statistical and deep learning algorithms used for analyzing SRT data rely solely on two-dimensional (2D) spatial coordinates, which limits their ability to accurately identify spatial domains, spatially variable genes, cell-to-cell communications, and developmental trajectories in a three-dimensional (3D) spatial manner. To address these limitations, we introduced Spa3D, which utilized the anti-leakage Fourier transform and graph convolutional neural network model to reconstruct 3D-based spatial structures from multiple 2D SRT slices. We demonstrate that Spa3D is appliable to analyze data from various SRT technology platforms and outperforms state-of-art methods by: (I) improving spatial domain identification through 3D reconstruction, (II) elucidating cell-cell communication landscape in the 3D cellular organization, (III) modeling of organ-level tempo-spatial development patterns in a 3D fashion, and (IV) annotating 3D spatial trajectory that are not captured by 2D spatial coordinates. Key pointsO_LIMost existing spatial omics analysis methods rely on 2D data, limiting their ability to capture full spatial and developmental tissue complexity C_LIO_LISpa3D incorporates physical z-axis distances, enabling accurate 3D modeling even when adjacent slices vary in tissue structure and composition C_LIO_LISpa3D reconstructs true 3D spatial structures from 2D SRT slices using graph convolutional networks and anti-leakage Fourier transforms C_LIO_LISpa3D enhances spatial domain detection, revealing detailed cell-cell communication and organ-level development patterns across multiple spatial omics platforms C_LIO_LISpa3D enables novel biological discoveries by revealing spatial features and trajectories not detectable using traditional 2D transcriptomic analysis approaches C_LI

bioinformatics↗

bioRxiv2026

Identification of specific gut bacteria and metabolomic signatures related to Myocardial Insulin Resistance in Type 2 Diabetes

BackgroundIn myocardial insulin resistance (mIR), insulin fails to appropriately stimulate myocardial glucose uptake, which can contribute to the development of heart disease. This reversible metabolic abnormality occurs in only a fraction of patients with type 2 diabetes mellitus (T2DM) and may be present even before clinical symptoms or the onset of diabetes. Identifying biomarkers of early-stage mIR is crucial to halt its progression with appropriate treatment and lifestyle interventions. In this context, we explore, for the first time, specific gut bacteria and fecal and plasma metabolic signatures associated with mIR. MethodsForty-two T2DM patients were divided into two groups, mIR patients patients with myocardial insulin sensitivity (mIS), depending on their myocardial glucose uptake measured with 18F-FDG PET during the hyperglycemic clamp. For each group, fecal microbiota was quantified by Illumina sequencing, and metabolomic profiles in feces and plasma were determined by NMR spectroscopy. ResultsThe Faiths phylogenetic diversity index was reduced significantly in mIR patients, compared with mIS patients. Linear discriminant analysis effect size (LEfSe) analysis revealed 25 bacterial taxa differing between mIS and mIR groups, and 6 bacteria (Thermicanus, Lachnobacterium, Desulfovibrio, Desulfuromusa, Desulfosporosinus and Coprobacillus cateniformis) were significantly decreased in mIR patients at the genus and species levels. Multivariate metabolomic analysis determined that six fecal metabolites (arabinose, {beta}-galactose and ribose, aspartate, histidine and lactate) and six plasma metabolites (creatinine, myo-inositol, threonine, {beta}-galactose, glycerol and choline) were reduced in mIR patients while plasmatic levels of VLDL(CH3) were elevated significantly. Myocardial IR correlated positively with plasmatic VLDL(CH3) and was negatively associated with two bacteria (Desulfosporosinus and Coprobacillus cateniformis), five fecal metabolites (arabinose, {beta}-galactose, ribose, aspartate, and histidine) and two plasma metabolites (choline and {beta}-galactose). ConclusionsOur pilot study proved that the gut microbiome and the metabolic plasma profile is altered in T2DM patients with mIR. Regression analysis and predictive modelling identified the bacteria Desulfosporosinus and the metabolite galactose as key biomarkers, which could aid in the identification of T2DM patients at risk for myocardial IR and in the design of novel therapeutic strategies to prevent it.

microbiology↗

bioRxiv2025

AlphaFold 3-powered discovery of phage proteins that inhibit bacterial transcription

Phages are the most abundant biological entities on Earth and play central roles in bacterial evolution and the emergence of new pathogens. Many phages encode proteins that specifically inhibit host RNA polymerase activity, thereby sabotaging and, in some cases, hijacking the host transcription machinery to serve their needs. Identification and characterization of these transcription inhibitors not only provide insights into the logic of transcription regulation but also inspire the design of antibiotics targeting bacterial transcription. Traditional methods for identifying new phage proteins that inhibit bacterial transcription are labor-intensive and require access to live phages. To overcome these limitations, we developed a highly efficient pipeline for AlphaFold 3-guided discovery of phage proteins that inhibit bacterial transcription. Using this pipeline, three phage proteins were identified and characterized. Structural and biochemical analyses demonstrated that these phage proteins bind to distinct sites on RNA polymerase and inhibit transcription via unprecedented mechanisms. This study showcases the power of AlphaFold 3 in discovering novel binders of large protein complexes, and the pipeline developed here could be readily adapted to screen modulators of other large targets, such as the ribosome, proteasome, and CRISPR-Cas systems.

molecular biology↗

bioRxiv2025

Rapid ecosystem collapse and biofilter formation following seabed methane leakage

Globally, vast amounts of methane are trapped within subseafloor gas hydrates. Recent evidence suggests that climate- and human-induced perturbations can destabilize gas hydrates and trigger methane release, yet the response of deep-sea ecosystems to these changes remains poorly understood. Here we show multi-year in situ monitoring of seabed ecosystem following methane leakage induced by hydrate exploration activities. Within just two years, benthic microbial and eukaryotic diversity in the affected areas declined significantly, while microbial and macrofaunal abundance increased. Integrated geochemical and omics analyses reveal the rapid successional shift of seabed ecosystem to a novel chemosynthetic system. Aerobic methanotrophs (Methyloprofundus) co-established with unexpectedly fast growing anaerobic methanotrophic archaea (ANME-3), accompanied by a rapid recruitment of opportunistic polychaetes that bioirrigated the seabed to >50 cm depths. The active animal-microbe interactions sustained exceptionally high rates of methane oxidation that utilized diverse electron acceptors. We demonstrate that methane hydrate destabilization can trigger rapid collapse of native seabed ecosystem while driving the formation of an effective methane biofilter consuming this potent greenhouse gas much faster than previously estimated. Understanding seabed ecosystem response and feedback is critical for predicting benthic methane cycling under ongoing global change and for developing sustainable strategies for methane hydrate resource management.

ecology↗

bioRxiv2025

NSUN2-dependent 5-methylcytosine Modification Regulates Influenza A virus Gene Expression and Genomic Packaging

Emerging evidence indicates that methyltransferase NSUN2 catalyzes 5-methylcytosine (m5C) modifications on various viral RNAs and plays important roles in viral biology. However, the regulatory roles of NSUN2 in influenza A virus (IAV) replication have not been elucidated. Here, we revealed that NSUN2 negatively regulated the viral RNA transcription and protein production by knocking out and over-expressing NSUN2. By m5C MeRIP-seq and RNA-BisSeq, NSUN2-dependent m5C sites were identified on both the plus and minus viral RNA strands. In NSUN2-KO cells, the m5C modification on vRNAs was reduced, resulting in the production of a large number of deficient interfering particles (DIPs) which had lower vRNA content, imbalanced genome fragments, abnormal morphology and reduced pathogenicity. Mutation of m5C sites at the 5 and 3 ends of PB2 vRNA interfered with the selective packaging of the 8 vRNA segments into virus particles, resulting in the formation of a variety of abnormally packaged virus particles. PB2-vRNA mutants also had reduced replication ability and pathogenicity in mice. Overall, these data demonstrate that the m5C residues catalyzed by NSUN2 are required on vRNAs for the proper assembly of infectious viral particles, suggesting the depletion of m5C modification as a potential strategy that can be utilized to attenuate IAV strains. Significance StatementInfluenza A virus (IAV) infections pose a significant threat to global public health by causing substantial morbidity and mortality. The segmented nature of the IAV genome requires precise regulation of the genomic assembly to produce infectious progeny virus particles. In this study, we demonstrate that m5C modification is crucial for the proper assembly of infectious viral particles. The lowered level of m5C modifications on vRNAs leads to the generation of defective interfering particles with reduced replication capacity and pathogenicity. Our data shed new light on the selective packaging mechanism of IAV segmented genome and highlight a potential new strategy for attenuating IAV strains by targeting the m5C modification machinery.

microbiology↗

bioRxiv2025

Cell-Type-Resolved Isoform Atlas of Human Tissues Reveals Age and Alzheimer's Disease-Associated Splicing Changes

Alternative splicing is a key mechanism for transcriptomic diversity, but how isoforms map to specific cell types in bulk tissues remains unclear. We present Sciege, a multimodal method that integrates bulk short-read RNA-seq with single-cell and long-read data to estimate cell type-specific isoform distributions. Through simulations, we demonstrate that Sciege accurately estimates isoform abundances and identifies differentially abundant transcripts through statistical tests. Applied to seven tissues in GTEx and brain tissue in ROSMAP datasets, Sciege generates a first-to-date multi-tissue isoform atlas and reveals isoform changes linked to cell types, aging, and Alzheimers disease. Validation with external cohorts and experimental data confirms our findings. Notably, we identify upregulation of the MAPT-010 isoform in AD inhibitory neurons, consistent with known methylation signatures. Our approach demonstrates the value of integrating RNA-seq data to study cell type-specific splicing and provides a foundation for further genetic and functional studies of alternative splicing across biological contexts.

bioinformatics↗

bioRxiv2025

REST elevation-dependent chromatin remodeling and alternative Grk6 transcript synthesis hyperactivates Cxcr4-Sdf1 signaling in cerebellar granule cell progenitors

RE1 Silencing Transcription Factor (REST) is a repressor of transcriptional initiation of genes involved in neurogenesis. Here, we show that conditional REST elevation in cerebellar granule cell progenitors (CGNPs) of RESTTG mice perturbed foliation, increased cell migration, and sustained C-X-C motif receptor 4 (Cxcr4) signaling, a pathway key to postnatal CGNP migration. Mechanistic studies uncovered a novel role for REST in controlling transcript diversity and exon skipping in CGNPs. Alternative transcript expression was detected in known Cxcr4 signaling regulator, G-protein-coupled receptor kinase-6 (Grk6). Further analysis of Grk6s isoform expression revealed an upregulation of a transcript lacking exon 10a (Grk6-207) in RESTTG CGNPs. Grk6-207 expression in wildtype CGNPs hyperactivated Cxcr4 signaling and increased chemotaxis. Structural modeling of Grk6-207 predicted changes in active site conformation and interactions with Cxcr4 and {beta}-Arrestin-1, supporting impairment of Cxcr4 signaling desensitization. Interestingly, REST elevation promoted increased chromatin accessibility at the exon10a-10b junction and exon 10a exclusion. Integrated multiomic analyses identified the enhancer of zeste (Ezh2) as a potential mediator of alternative transcript generation which demonstrated increased occupancy at the exon10a-10b locus in RESTTG CGNPs. Pharmacological inhibition of Ezh2 downregulated Grk6-207, confirming a role for Ezh2 in Grk6 exon10a exclusion and the increased migration in RESTTG CGNPs. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=67 SRC="FIGDIR/small/682654v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@166db32org.highwire.dtl.DTLVardef@1c0c5e0org.highwire.dtl.DTLVardef@ff2d6borg.highwire.dtl.DTLVardef@fed170_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2025

Mechanical stretch disrupts calcium dynamics and redistributes Piezo1 in human astrocytes

Astrocytes regulate the activity of nearby neurons so disruption of astrocyte calcium dynamics by traumatic brain injury (TBI) could have profound consequences for neural network activity in the brain. In this study, human induced pluripotent stem cell (hiPSC)-derived astrocytes were used in a two-dimensional (2D) in vitro stretch injury model to evaluate the effect of trauma on calcium dynamics, mitochondrial function, and the mechanosensitive ion channel Piezo1. Outcomes were assessed using live imaging, immunostaining, and RNA sequencing. Cell viability, mitochondrial membrane potential, and spontaneous calcium transients declined as injury severity increased. At moderate injury severity, the decreases in mitochondrial membrane potential and calcium dynamics were temporary. The spatial distribution of Piezo1 also changed temporarily after injury. RNA sequencing identified 196 genes that changed expression after injury, including downregulation of mitochondrial and oxidative metabolic processes and upregulation of cortical thinning pathways. These findings establish this model as a platform for investigating the cellular mechanisms of TBI and its influence on neurodegeneration.

neuroscience↗

bioRxiv2025

Bone Resists Fatigue Through Crack Deceleration at the Fibril Scale

Bone endures millions of cycles throughout its lifetime by accumulating damage at a rate slow enough to allow for cell-mediated repair, but the mechanisms that delay this fatigue failure remain poorly understood. While prior studies have focused on the fatigue response of macroscale architecture of bone, the role of its nanoscale structure in resisting fatigue has been experimentally inaccessible. Here, we combine in-situ fatigue loading with synchrotron X-ray tomography and radiography to directly observe crack propagation in human bone with [~] 21 nm spatial and 100 ms temporal resolution. We find that mineralized collagen fibrils decelerate crack growth through branching along the fibril axes, while orthogonal cracks are intermittently decelerated by nanoscale interfibrillar interfaces. These mechanisms suppress damage accumulation under physiological loads by an order of magnitude. Our findings uncover a previously unobserved toughening strategy at the nanoscale, providing insight as to how the hierarchical structure of bone bridges the timescale gap between mechanical damage and biological repair.

bioengineering↗

bioRxiv2025

Spatial Transcriptomics Reveal Developmental Dynamics of the Human Cerebral Cortex and Striatum

The human fetal brain undergoes morphological changes that contribute to the development of regional functionalities. However, the features of structural development, the underlying molecular and cellular signatures in the fetal brain remain unclear. With spatial transcriptomics and snRNA-seq, we identified 25 forebrain regions and characterized the dynamic changes in the cortex and striatum during the late first and early second trimesters. In particular, we discovered that temporal lobe enriched NPY-expressing L2/3 EX neuron potentially interacted with L4 EX neurons during cortical expansion and arealization. Additionally, the gyrus and sulcus were developmental asynchronous, in which HOPX and SPARC genes were potentially involved. Further investigation on the striatum showed specific genes and cell types that enriched in patch and matrix compartments, and SST-positive interneurons potentially involved in the development of these structures. Together, our results give insights into the understanding of early fetal brain development.

bioinformatics↗

bioRxiv2025

Maturation of Dorsal Association Tracts during Preadolescence Links to Concurrent and Future Cognitive Performance and Transdiagnostic Psychopathology

Many psychiatric disorders begin during adolescence, coinciding with the rapid development of brain white matter (WM). However, it remains unclear whether deviations from normal WM maturation during this age period contribute to the development of psychopathology. In this study, we developed and validated normative models of brain age based on specific WM tracts using three large-scale developmental datasets (a total of [~]10,000 subjects). We found that tract-specific deviations in WM development of association and limbic/subcortical systems were linked to concurrent cognition and psychopathology. The spatial pattern of the association system aligned closely with distributions of high-order brain networks, and with mitochondrial content and respiratory capacity. The maturation of the association system contributed significantly to better cognitive performance assessed two or three years later. Importantly, delayed WM development especially in dorsal association tracts predicted psychiatric disorders across diagnoses and disorder onset over a 2-year follow-up. By identifying tract-specific WM development during preadolescence as a predictor of cognitive capacity and psychiatric disorder risks, this study provides a valuable framework for tracking individualized brain maturation and understanding the neurobiological underpinnings of cognitive performance and transdiagnostic psychopathology.

neuroscience↗

bioRxiv2025

Spatiotemporal dynamics of questing activity by four tick species in the central Great Plains

In this study, we explore a suite of new ecological niche modeling approaches to illuminate the distributional potential and distributional dynamics of questing individuals of four tick species in the central Great Plains region. Specifically, we improve on typical approaches in distributional ecology by (1) assigning time-specific environmental values to sampling events so that repeated sampling at the same points yields additional information, (2) using both positive and negative records of the species as inputs in model development, and (3) constraining model response shapes in models to resemble the shapes of fundamental ecological niches. Model outcomes demonstrate both seasonal dynamics and differences between species in terms of the geographic potential of questing behavior by Great Plains tick species. These improved approaches in distributional ecology have considerable potential to enrich distributional understanding of vector species distributions.

ecology↗

bioRxiv2025

Temporal foundation model unveils ancient HepatitisB virus evolution

Since ancient hepatitis B virus (HBV) sequencing data are scarce and incomplete, the evolutionary dynamics of HBV have long remained enigmatic. This data gap hinders a comprehensive understanding of HBV genetic variations, evolutionary trajectories, and host interactions in different historical periods, preventing insight into its long-standing co-evolutionary relationship with humans. In this study, we developed a sequence-based generative foundational model, ViraChron (Viral Chronology Foundation Model), that integrates multi-scale temporal information to compensate for the lack of ancient HBV data. We confirmed the robustness of our model through sequence identity, phylogenetic, and recombination analyses. ViraChron enabled the identification of fixed mutations specific to HBV genotype A, demonstrating that HBV acquires survival advantages through mutations that are ultimately fixed by natural selection. Our model outperforms the original baseline in terms of sequence completion, achieving significantly higher accuracy. The model significantly reduced data acquisition time from 80 hours to 5.4 minutes per HBV genome, providing reliable, high-quality data for 7 new HBV genomes from specific archeological sites. ViraChron overcomes previous limitations, obtaining high-quality genomic data from samples over ten thousand years old, thereby facilitating a systematic understanding of viral evolution and its biological characteristics.

paleontology↗