Biology subjects

Sun, H.

Publications and source records attributed to Sun, H..

At least 73 records · Page 4Linked to original sources

bioRxiv2026

Energetic cross-talk of filter gate and lower helices drives polymodal regulation and disease in TREK K2P channels

The TREK subfamily of two-pore domain potassium (K2P) channels are essential regulators of membrane excitability, and their activity is modulated by a wide range of physiological stimuli, including phosphorylation and membrane stretch. Single-site mutations in this subfamily have been identified in patients with FHEIG symptom (facial dysmorphism, hypertrichosis, epilepsy, intellectual disability/developmental delay, and gingival overgrowth), where they cause pathological channel hyperactivation. Using OneOPES framework, which unifies multiple enhanced-sampling molecular dynamics strategies, we provide a detailed energetic characterization of the TREK-2 conformational landscape. Our simulations uncover a unifying mechanism in which coupling between the lower transmembrane helices, the proximal C-terminal domain, and selectivity filter stability governs channel gating under different physiological stimuli, as well as disease-mimicking conditions. The predicted conformational effects of an FHEIG syndrome-associated mutation were further validated by electrophysiological measurements using a conformation-sensitive TREK-2 inhibitor. Together, these results establish an energetic framework for TREK-2 regulation and dysfunction and provide a foundation for structure-based drug discovery targeting the K2P TREK channel family.

biophysics↗

bioRxiv2026

Single Plaque Proteomics Reveals the Composition and Dynamics of the Amyloid Microenvironment in Alzheimer's Disease

Alzheimers disease (AD) is characterized by amyloid plaques that form complex microenvironments in the brain. However, the molecular composition of these plaques and their temporal regulation are not well defined. Here, we developed a sensitive workflow for quantitative proteomic profiling of single plaques using refined laser capture microdissection and data-independent acquisition mass spectrometry (LCM-DIA-MS). From >200 plaques and control regions in AD mouse models (5xFAD and APP-KI) and human brains, we quantified >7,000 proteins, revealing stage-dependent, cell-type-related remodeling of the amyloid proteome (amyloidome). Temporal profiling uncovered early immune and lysosomal activation followed by engagement of RNA processing and synaptic pathways. Cross-model and cross-species analyses determined a conserved amyloidome including APOE, MDK, PTN, and HTRA1, validated by co-localization in imaging analysis. Network analysis highlighted modules in lipid transport, vesicle organization, and autophagy. These findings establish amyloid plaques as conserved, dynamic multicellular hubs that link amyloid accumulation to downstream cellular events.

neuroscience↗

bioRxiv2026

Cell type-resolved proteomics reveals intra- and intercellular signalingin Alzheimers disease

Alzheimers disease (AD) arises from pathological interactions among diverse brain cell types, but cell-specific proteomic changes remain underexplored. Here, we present deep proteomic profiling of sorted or proximity-labeled brain cells from AD mouse models (5xFAD and AppNL-G-F) at multiple ages, quantifying 13,411 proteins in microglia (three subtypes), astrocytes, oligodendrocyte precursor cells, and neurons. We identified 3,028 differentially abundant proteins across these cell types, the majority of which were not detected in bulk proteomic datasets, and constructed cell type-specific networks to define functional modules and hub proteins. Comparison with transcriptomic data revealed that [~]30% of proteomic changes are RNA-independent. Further analyses uncovered cross-cell type signaling proteins conserved in human AD brains, such as pleiotrophin (Ptn), which is transcriptionally enriched in astrocytes but accumulates in microglia. Importantly, recombinant PTN directly activates induced microglia-like (iMG) human cells. Thus, these findings provide a comprehensive cell type-resolved proteomic atlas of AD models, highlighting novel intra- and intercellular signaling events. HighlightsO_LIA high-resolution cell type-resolved proteomic atlas of Alzheimers disease mouse models C_LIO_LI[~]3,000 cell type-specific protein alterations identified beyond bulk tissue analyses C_LIO_LIProteomic profiling of microglial subtypes reveals subtype-specific changes in Alzheimers disease C_LIO_LIAstrocyte-microglia signaling is highlighted and validated through PTN-mediated interactions C_LI

neuroscience↗

bioRxiv2026

Ultra-flexible PINE arrays for month-long, continuous intracellular ion flux monitoring in plants with nanomolar accuracy

High-precision in vivo monitoring of ion fluxes is essential yet challenging studying plant electrophysiology such as growth regulation, signal transduction and stress responses. Existing methods for probing ion dynamics are limited by low sensitivity, high invasiveness that interferes physiological processes, and the inability to accurately resolve ion homeostasis with required spatial and temporal resolution. Here, we introduce ultraflexible, plant implantable nanoelectrode (PINE) arrays manufactured on 1.2-m-thick polymer substrates, which enable ultrasensitive and selective measurement of ionic current for month-long via scalable nanofabrication techniques. The fabricated PINE arrays have a smaller dimension than typical plant cells as well as less stiffness, facilitating minimally invasive integration with living plant cells. This subcellular-scale plant-electronic interface allows for reliable, selective detection of K+ flux with a detection limit of [~]10- M, and thus allows continuous, stable monitoring of tomato stem cells over six weeks, capturing dynamic potassium fluctuations during all key growth stages. More importantly, the method permits long-term, real-time tracking of ion-specific dynamics without disrupting plant cellular structure or altering endogenous ion concentrations. Therefore, PINE provides unprecedented access to ion homeostasis and signaling networks, making it an excellent platform for precision agriculture and a foundational tool for future digital plant engineering.

plant biology↗

bioRxiv2026

A general and extensible algorithmic framework to biological sequence alignment across scales and applications

Sequence alignment underpins nearly every facet of modern genomics, from genetic testing and cancer profiling to functional genome annotation. Yet, despite decades of algorithmic innovation, most existing aligners remain narrowly optimized for specific tasks, fragmenting analytical workflows and limiting reproducibility. Here we introduce the Versatile Alignment Toolkit (VAT), a unified algorithmic framework that generalizes existing seeding and genome-indexing strategies within a single, transparent architecture. VAT employs a novel multi-view indexing scheme that integrates multiple seeding strategies and supports run-time seed-length parameterization without reindexing. A radix clustering algorithm based on hardware-efficient in-register bitonic sort accelerates multi-view table construction, ensuring scalability across large datasets. VAT delivers consistently high performance across diverse alignment tasks, including short- and long-read mapping, homology search, and whole-genome alignment, while maintaining algorithmic simplicity and adaptability. By bridging previously isolated alignment paradigms, VAT substantially reduces workflow complexity, enhances computational efficiency, and establishes an extensible foundation for future sequencing technologies. We anticipate this unification will set a new standard for flexible and reproducible sequence alignment in biomedical research and clinical genomics.

bioinformatics↗

bioRxiv2026

Sex without crossovers mimics clonal reproduction in the holocentric plant Rhynchospora tenuis

Meiotic recombination ensures accurate chromosome segregation and promotes genetic diversity by generating crossovers between homologous chromosomes1. While essential in most sexually reproducing organisms, recombination is variably regulated and can be absent in some lineages, a condition known as achiasmy2. However, obligate achiasmy in both sexes of a sexual species has not been previously documented. Here, we investigate the beak-sedge Rhynchospora tenuis, a holocentric plant with the lowest known chromosome number among flowering plants (n = 2) and inverted meiosis3. Using chromosome-scale genome assemblies from nine accessions, molecular cytogenetics, immunocytochemistry, high-throughput single-gamete sequencing and whole-genome sequencing of controlled crosses, we show that R. tenuis undergoes obligate, genome-wide achiasmy in both male and female meiosis. Despite normal early meiotic axis formation, synapsis fails, crossovers are not detected cytologically or genetically, and univalents persist at metaphase I. Extensive haplotype-specific accumulation of transposable elements (TEs) generates segregation distortion (e.g. meiotic drive), favouring the transmission of larger, TE-rich chromosomes. Remarkably, sexual reproduction is retained with fertilisation producing viable seeds only when translocation-compatible gametes meet, indicating strong post-meiotic selection that eliminates incompatible homozygous combinations. As a result, all surviving offspring are genetically identical to the maternal genotype, effectively restoring heterozygosity each generation and mimicking clonal reproduction. We propose that the combined effects of recombination loss, low chromosome number, holocentricity, inverted meiosis, and selective transmission of longer chromosomes enable faithful segregation and clonal-like inheritance despite sexual reproduction. These findings challenge the boundary between sex and clonality, revealing a unique evolutionary strategy linking genome architecture, recombination loss, and transmission bias.

evolutionary biology↗

bioRxiv2026

caRBP-Pred: Deep Learning-based Prediction of Chromatin-Associated RNA-Binding Proteins Using Short Peptide Sequences

RNA-binding proteins (RBPs) are pivotal in cellular processes ranging from RNA metabolism to 3D genome organization. A distinct subset, chromatin-associated RBPs (caRBPs), binds directly to chromatin to function as transcriptional regulators. However, identifying caRBPs via traditional methods like Chromatin Immunoprecipitation Sequencing (ChIP-seq) and Mass Spectrometry (MS) is labor-intensive and costly. While computational tools for DNA- and RNA-binding protein (DRBP) prediction exist, they often rely on outdated Gene Ontology annotations and fail to capture the unique characteristics of chromatin association. Here, we introduce caRBP-Pred, a novel deep learning approach combining Convolutional Neural Networks (CNN) and Bidirectional Long Short-Term Memory networks (BiLSTM). Unlike previous methods utilizing full-length sequences, our model is trained on chromatin-contact peptides derived from mouse embryonic stem cells (mESCs). caRBP-Pred achieves a superior Area Under the Curve (AUC) of 0.81 using peptide sequence information alone, significantly outperforming existing DRBP predictors which exhibit low recall for caRBPs. We further predicted 52 potential caRBPs in mice. Notably, validation against human homologs confirmed that our model accurately predicts candidates with experimentally verified chromatin-binding capabilities. Collectively, caRBP-Pred is the first tool specifically designed to predict caRBPs based on chromatin-contact peptides, offering a valuable resource for investigating regulatory roles of caRBPs on transcription.

bioinformatics↗

bioRxiv2026

Active Site-Directed Probes for targeting Bacterial Phosphoarginine Phosphatases

Canonical protein phosphorylation patterns are a thoroughly studied post-translational modification (PTM) driving distinct regulatory mechanisms in both prokaryotes, and eukaryotes. In contrast, the identification and investigation of essential components that regulate non-canonical phosphorylation has received considerably less attention, although these PTMs are associated with important functions. One notable example is arginine phosphorylation which modulates processes such as protein degradation, transcriptional regulation and spore germination in bacteria. Herein we introduce the first in class covalent activity-based probes to study phosphoarginine-phosphatases. We identify unsaturated phosphonamidic acids as bespoke electrophilic phosphoarginine (pArg) mimics, which allowed to uncover a series of unprecedented pArg-phosphatases, which in part had been previously annotated as low molecular weight tyrosine-phosphatases across phylogenetically distinct microbial species. This work, which serves as the first example of proteome-wide activity-based profiling of pArg phosphatases will help inform the development of new therapeutic modalities and expand our understanding of bacterial signal transduction.

microbiology↗

bioRxiv2026

Spatial transcriptomic analysis of myositis muscles reveals novel molecular insights of MDA5+ dermatomyositis

Idiopathic inflammatory myopathies (IIM), also known as myositis, are a rare and heterogeneous group of autoimmune disorders characterized by chronic inflammation of skeletal muscle. Other organs are also frequently affected, such as skin, joints, and lungs, leading to morbidity and even mortality. Anti-MDA5 autoantibody-positive dermatomyositis (MDA5+ DM) is a unique subtype with a high mortality rate but the underlying molecular mechanisms remain incompletely understood. In this study, we profiled the spatial transcriptome of a cohort of healthy controls, MDA5+, and MDA5- muscles and found a distinct transcriptomic profile of the MDA5+ muscles with a low percentage of stressed myofibers but increased immune cell infiltration. Niche analysis revealed a distinct microenvironment in the MDA5+ muscles with the endothelial cell (EC) niche showing increased inflammation, dampened oxygen transport function, and a unique enrichment of the Type 1 interferon response. Cell-cell communication and pathway activity analysis uncovered that hypoxia, TGF-{beta}, NF-{kappa}B, and TNF- signaling were enriched in the MDA5+ EC niche. Altogether, our results support a vasculopathy model whereby blood vessels exhibit a strong inflammatory response and impaired oxygen transport function, leading to vasculopathy and perivascular immune cell infiltration in MDA5+ muscles.

immunology↗

bioRxiv2025

DNA replication errors drive genome-wide small inverted triplication dynamics

Structural variants (SVs) have a profound impact on phenotype and diversity and are associated with human diseases. To explore the origination of SVs, we have analyzed 1,340 cancer genomes with annotation of 4,608 novel small inverted triplication (SIT) events and found that FEN1 is strongly associated with SIT incidence. Then, we performed long-read sequencing and developed PacBioR to annotate SITs in yeast FEN1 mutant cells. We found that SIT structures mimic classic inverted triplications but with a smaller DUP/IN/DUP structure of 184/160/184 bp on average, with a spacer sequence of 30 bp and breakpoint junction of 6 bp. We further showed that breakpoints of SITs preferentially occurred at nucleosome midpoints, aligned with Okazaki fragment termini, and those harbored in plasmids were precisely eliminated via DNA polymerase slippage over SIT-derived hairpin structures. This study provides mechanistic insight into SIT origination and offers practical tools for future studies on genome rearrangements.

genetics↗

bioRxiv2025

MicroGenomer: A Foundation Model for Transferable Microbial Genome Representations Enabling Multi-scale Genomic Understanding and Ecophysiological Trait Prediction

Microorganisms underpin global biogeochemical cycles and represent a vast, underexplored reservoir for sustainable biotechnology and human health. Their diversity, arising from the interplay of numerous genes within holistic genomic contexts, dictates complex ecophysiological traits across varied environments. To bridge the gap between complex genomic sequences and associated biological functions and phenotypic outcomes, we present MicroGenomer, a foundation model for transferable microbial genome representations enabling multi-scale genomic understanding and ecophysiological trait prediction. MicroGenomer leverages a hierarchical training strategy comprising pre-training on large-scale genomic sequences (234.5 billion base pairs), domain-specific mid-training using the GTDB-curated marker gene set, and task-specific post-training. Despite a streamlined architecture of 470 million parameters, MicroGenomer achieves performance on key tasks competitive with models nearly 85 times its size. Advancing beyond established gene-scale encoders, MicroGenomer generates robust embeddings at the genome scale for downstream modeling. Extensive evaluations demonstrate that MicroGenomer effectively captures phylogenetic structures in species space, excelling in geneand genome-scale understanding as well as ecophysiological trait prediction. The practical utility of these capabilities is further demonstrated by targeted wet-lab validation on newly isolated strains, indicating that MicroGenomers predictions provide reliable guidance for biological experiments. Collectively, MicroGenomer offers a high-performance, resource-efficient framework that transforms raw sequence data into actionable biological insights, providing a powerful foundation for microbiome research and biotechnology.

bioinformatics↗

bioRxiv2025

IGHV3-53 antibody abundance drives divergent SARS-CoV-2 immune imprinting

The mechanisms driving divergent SARS-CoV-2 immune imprinting in populations with distinct SARS-CoV-2 exposure histories remain unclear. However, conventional wild-type mouse models fail to recapitulate severe imprinting, even after potent ancestral-strain mRNA immunization, hindering imprinting-related mechanistic investigation and vaccine evaluation. Here, we surprisingly found that V(D)J-humanized mice could faithfully recapitulate human severe imprinting phenotypes. Comprehensive antibody repertoire analysis and deep mutational scanning-based epitope mapping of 583 monoclonal antibodies from these models revealed that the pre-existing IGHV3-53/66 antibody abundance determine imprinting severity through antibody-mediated masking of Omicron-specific epitopes. Both passive IGHV3-53/66 antibody transfer and IGHV3-53 knock-in were sufficient to induce severe imprinting in wild-type mice. Together, these findings demonstrate that the V(D)J germline repertoire--even a single germline-encoded antibody response--can profoundly shape humoral imprinting severity. Accordingly, we established an IGHV3-53 knock-in mouse model that accurately recapitulates the human antibody landscape, providing a valuable tool for guiding future COVID-19 vaccine updates.

immunology↗

bioRxiv2025

Computer-assisted dissection of the DNA mismatch recognition mechanism of the MutS protein

By sensing local conformational strains in DNA, TaqMutS utilizes a push-pull mechanism via the synergy of residues S57 and D472 to modulate {pi}-stacking interactions between the key recognition residue F39 and DNA, thereby achieving specific mismatch-site recognition. Meanwhile, residues K61 and R473 fine-tune non-specific binding of TaqMutS through electrostatic synergy.

synthetic biology↗

bioRxiv2025

DeepDOX1: A Dual-Drive Framework Integrating Deep Learning and First-Principles Physics for Drug-Protein Affinity Prediction

In this work, we present DeepDOX1, a dual-drive drug-protein affinity (DPA) prediction tool features the tight integration of a concise AI architecture and a quantum mechanics based representation. The first-principle physics generated features incorporating the interactions between the drug and the protein pocket allows a relatively simple CNN model trained on a relatively small training set to exhibit exceptional generalization capabilities across extensive testing. Notably, DeepDOX1 outperforms popular AI models in the tests simulating real-world drug design scenario and a highly challenging test set featuring covalent ligands, halogenated ligands and metalloproteins. In addition, we designed a series of novel covalent inhibitors targeting the diabetes target hu-FBPase using DeepDOX1. Subsequent experimental validation including enzyme-level bioactivity assays and crystal structure determination confirmed the DeepDOX1s effectiveness in real-world drug design applications. It is conceivable that the combination of AI and first-principle QM might be one of the next breakthrough points of DPA prediction.

bioinformatics↗

bioRxiv2025

Epitope and functional classification of human neutralizing antibodies against SFTSV Gn

Severe fever with thrombocytopenia syndrome virus (SFTSV) is a lethal bunyavirus lacking approved countermeasures. From SFTS survivors, we isolate 84 human monoclonal antibodies (mAbs) against the viral glycoproteins Gn and Gc. Gn-specific mAbs demonstrate superior neutralization breadth and potency compared to the restricted neutralizing activity observed with Gc. Using a high-throughput yeast display deep mutational scanning (DMS) platform, we classify Gn-head mAbs into eight epitope groups, among which four groups (IA, ID, IIIA, IIIB) conferring neutralization. Notably, mAbs BD70-4003 (group IA) and BD70-4017 (group IIIA) exhibit broad neutralization and provide 100% protection in a lethal mouse model. Cryo-EM structural analysis of these mAbs in complex with the Gn-head reveal their binding interfaces, directly validating the epitope residues identified by DMS. Our study delineates the antigenic landscape of SFTSV Gn, identifies potent therapeutic candidates, and establishes DMS coupled with structural validation as a powerful framework for antibody discovery against bunyavirus.

immunology↗

bioRxiv2025

Spectral tuning and signaling of diverse and most red sensitive visual rhodopsins that drive high colour discrimination in Mantis Shrimp eyes

Stomatopod crustaceans (mantis shrimps) possess extraordinary eyes with unmatched visual opsin diversity, but their potential for broad colour detection remains unclear. Here, we report that seventeen opsins, mostly from the midband eye region, are involved in colour sensing and signaling via Gq/Gi-coupling and describe the underlying mechanisms of spectral tuning. Two mid-wavelength opsins preferentially absorb blue light and a majority of long-wavelength opsins absorb in the green range, but three absorb light beyond 600 nm, representing exquisite far-red-sensitive animal opsins. Several blue and red opsins exhibit photoreversibility with opposite spectral shifts explained by retinal binding interactions, revealing unrecognised photochemical flexibility in stomatopod photoreception. Row-specific spectral sensitivity results from combining carotenoid filters with multiple individually-tuned rhodopsins, altogether extending broad vision to the far-red spectrum.

biophysics↗

bioRxiv2025

Life history and infection susceptibility parameters of Drosophila species reared on a common diet

The fruit fly Drosophila is a powerful model organism for many biological questions. While Drosophila melanogaster has been the most widely used species owing to its versatile genetic tools, comparative studies also take advantage of the rich evolutionary, ecological, and behavioural diversity of Drosophilidae. This model system has only benefitted from the sequencing of hundreds of genomes assembled to chromosome level, and rich array of publicly-available datasets. However, labs that typically use just D. melanogaster can have difficulties adopting other species into their experiments due to unique dietary needs and care regimens. While dedicated research groups can rear dozens of fly species, this often requires preparing a variety of food media, which can be logistically taxing. In this study, we report an agar food recipe that we have used to rear >70 species of Drosophilidae (Prop recipe). This list includes ecological specialists such as D. sechellia, major pest species including D. suzukii, cactophiles, slime flux feeders, detritivores, and even mushroom-feeding species of the Quinaria and Testacea groups. This food recipe uses only standard powdered ingredients and molasses, and is already in use by one commercial transgenic injection provider. We provide life history parameters for dozens of species reared on this recipe, including comparisons in a subset of species across a variety of diets, finding fly fitness to be comparable or better on the Prop recipe among tested species. We further provide comparative data for 42 species after systemic infection by Acetobacter bacteria. However, unexpectedly, we found a striking interaction of diet and the microbiota that impacts susceptibility to infection in species-specific fashion. Our results suggest certain experiment types may be impacted by diet due to the microbiome that the diet itself supports. By providing rearing advice, life history parameters, and this infection dataset and experience, we hope to enable researchers to take advantage of the diversity of Drosophila as a model system for evolutionary research.

evolutionary biology↗

bioRxiv2025

Gut metabolite IPA alleviates white matter injury post-ICH by enhancing myelin debris phagocytosis via Stap1 inhibition

BackgroundIntracerebral hemorrhage (ICH) causes neurological dysfunction and white matter injury (WMI) characterized by myelin loss, axonal injury and myelin debris accumulation. Microglia-mediated debris clearance is critical for WMI repair. The microbiota-gut-brain axis plays an essential role in the central nervous system diseases, one of the ways in which gut microbiota affects brain is via producing metabolites. Indole-3-proprionic acid (IPA), a tryptophan-derived metabolite that mainly produced by Clostridium sporogenes, exhibits anti-inflammatory and neuroprotective properties. However, its effect on ICH remains unclear. This study aims to investigate the IPA level after ICH and the therapeutic effects of IPA on neurological deficits and WMI, as well as the potential mechanisms underlying IPA-mediated neuroprotection. MethodsAn ICH model was established using C57BL/6 mice, which then received intragastric IPA (20 mg/kg/day). Fecal abundance of IPA-related genes and IPA levels in feces and plasma were measured by qPCR and UPLC-MS/MS. Behavioral tests, qPCR, and immunofluorescence staining were used to assess neurological function, myelin integrity, and axonal injury. In vitro, BV2 microglia, with or without Stap1 knockdown, were co-cultured with myelin debris to assess IPAs effects on phagocytosis. Additionally, targeted plasma IPA profiling was performed in 30 ICH patients and 30 matched healthy controls. ResultsThe relative abundance of IPA production-related genes and IPA levels in feces and plasma were significantly decreased after ICH and remained low into the chronical phase. After IPA administration, the neurological deficits, myelin loss and axonal injury of mice with ICH were significantly improved. In vitro, IPA increased BV2 microglia myelin debris phagocytosis by inhibiting Stap1 expression. IPA levels were significantly reduced in ICH patients, consistent with ICH mouse model. ConclusionsOur findings demonstrated that the gut microbiota-derived metabolite IPA could facilitate neurological deficits recovery and alleviate WMI, which could be a promising therapeutic strategy to improve ICH prognosis.

neuroscience↗