Biology subjects

Yang, Y.

Publications and source records attributed to Yang, Y..

At least 181 records · Page 10Linked to original sources

bioRxiv2026

The inner nuclear membrane protein SUN1 regulates cullin-3 neddylation to maintain insulin signaling

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent chronic liver disease and strongly linked to obesity and insulin resistance. We previously reported that the common nuclear envelope variant rs6461378 (g.842031C>T; SUN1 H118Y) associated with MASLD and related traits including insulin resistance. To gain insight into how wild-type (WT) and H118Y SUN1 might differentially impact insulin signaling, we performed affinity purification-mass spectrometry (AP-MS) in human liver-derived cells stably expressing WT or H118Y SUN1. Unbiased AP-MS revealed a novel SUN1-CUL3 interaction, with comparative analysis showing that WT SUN1 interacted robustly with CUL3, while CUL3 interaction was markedly diminished with H118Y SUN1. Cells in which SUN1 was silenced via siRNA, or in which H118Y SUN1 was ectopically expressed, showed increased CUL3 neddylation, which is required for cullin RING ligase (CRL)-mediated ubiquitination of insulin receptor substrate (IRS) proteins. Inhibition of neddylation restored IRS-1 levels and insulin signaling in H118Y SUN1-expressing cells. Together, our findings provide a potential mechanism of H118Y SUN1-driven insulin resistance and a viable therapeutic approach for its reversal.

physiology↗

bioRxiv2026

The BraALA3 Homologs Mediate Propiconazole-Modulated Plant Growth in flowering Chinese cabbage

In agriculture, propiconazole (PCZ) controls excessive growth in flowering Chinese cabbage but poses dietary safety risks due to residue accumulation. Therefore, identifying novel PCZ targets and breeding PCZ-free cultivars is critical for the safe production of flowering Chinese cabbage. Here, we identified three P4-ATPase flippase homologs aminophospholipid ATPase 3 (BraALA3a/b/c) in flowering Chinese cabbage that function as sensitive targets for PCZ. These proteins exhibit high binding affinity for PCZ, which directly inhibits their ATPase activity. Overexpression of the BraALA3 homologs enhanced plant growth and increased sensitivity to PCZ, whereas knockdown led to dwarfism and reduced sensitivity. Based on these findings, we identified editable active sites via protoplast-based screening. Genetic transformation of one such site yielded BraALA3a/braala3aK200T mutant lines, which displayed a dwarf and compact architecture. These findings provide a precise molecular target for developing PCZ-free germplasm in flowering Chinese cabbage through gene editing.

plant biology↗

bioRxiv2026

Vascularized Human Cardiac Organoids Reveal Endothelial-Cardiomyocyte Crosstalk and Mechanisms of Carfilzomib-Induced Cardiotoxicity

Human cardiac organoids (hCOs) provide a powerful platform for modeling heart development and disease, yet their lack of vasculature limits physiological relevance. Here, we generate vascularized human cardiac organoids (vhCOs) by assembling hCOs with blood vessel organoids, enabling the self-organized formation of unified tissues with extensive vascular networks and substantially enhanced cardiomyocyte (CM) maturation. Single-nucleus multiomic profiling reveals CM state resembling the 17-week human fetal heart, while endothelial cells (ECs) acquire cardiac-specific and arterial-like identities. Integrative cell-cell communication analyses and experimental validation identify CM-derived Laminin-2 as a driver of arterial EC specification, while reciprocal EFNB2 signaling from arterial ECs promotes CM maturation, uncovering bidirectional cardiac-vascular crosstalk. Modeling carfilzomib-induced cardiotoxicity in vhCOs reveals ATF4-dependent endoplasmic reticulum (ER) stress and IL8-mediated inflammatory responses that are blunted in non-vascularized hCOs. Pharmacological attenuation of ER stress alleviates carfilzomib-induced cardiotoxicity. Altogether, vhCOs provide a developmentally advanced and physiologically faithful human cardiac model.

cell biology↗

bioRxiv2026

GPI lipid remodeling regulates lipophagy by forming lipid domains in response to glucose deprivation

Lipophagy is an important microautophagic process that degrades lipid droplets (LDs) to mobilize stored lipids as an energy source during nutrient starvation. However, the molecular mechanisms regulating lipophagy in response to nutrient starvation remain poorly understood. We found that budding yeast mutants defective in glycosylphosphatidylinositol (GPI) lipid remodeling exhibited aberrant accumulation of lipid droplets (LDs) and neutral lipids under glucose starvation. Our data suggest that the accumulation results from a failure of vacuolar liquid-ordered (Lo) domain-mediated lipophagy. Furthermore, we demonstrated that glycosylphosphatidylinositol-anchored proteins (GPI-APs) localize to vacuoles in response to glucose depletion and that a mutant defective in endocytosis has defects in both vacuolar Lo domain formation and lipophagy. These results imply that GPI lipid remodeling is required for Lo domain-mediated lipophagy upon glucose starvation. We propose that endocytosis functions to supply the lipid portion of GPI-APs, remodeled to C26 diacylglycerol, to the vacuolar membrane for Lo domain formation. Summary StatementOur data suggest that the endocytic transport of GPI-APs remodeled with C26 diacylglycerol to the vacuole is required for vacuolar Lo domain formation and subsequent lipophagy in response to glucose deprivation. This reveals the essential role of GPI lipid remodeling in ensuring lipophagy to adapt to changes in nutrient availability.

cell biology↗

bioRxiv2026

Spikes meet Spins: Quantum-Native Neural Decoding for Ultra_Low-Latency Brain-Computer Interfaces

Brain - computer interfaces (BCIs) require rapid and accurate decoding of neural activity, yet conventional computing architectures face growing latency as neural recording scales. We demonstrate a quantum computing - enabled neural decoding approach using a physical 1000-qubit coherent photonic Ising machine, in which inference is performed through hardware energy relaxation rather than numerical computation. By mapping sparse neural spike patterns onto Ising Hamiltonians, our hardware-native Quantum Semi-Restricted Boltzmann Machine achieves up to 96.2% accuracy across public in vivo datasets spanning multiple species and modalities. We report hardware-verified median latencies of 0.075 ms-- a tenfold speedup over GPUs--with complexity-invariant scaling. These results establish quantum computing as a viable pathway toward ultra-low-latency neural decoding for future BCI systems.

neuroscience↗

bioRxiv2026

Dormant Bacteria's Fatal Attraction to RNA Bacteriophages

Phages are the most abundant biological entities on Earth, yet RNA phages are strikingly scarce compared to their DNA counterparts--a long-standing mystery in phage biology. Here, we use dsRNA phage phiYY as a model to demonstrate that while RNA phages efficiently infect growing bacteria, they are gradually eliminated inside dormant bacteria through weak and time-dependent ROS-mediated damage. The RNA phages decline over days rather than through immediate clearance inside dormant bacteria. Accordingly, scavenging ROS with mannitol or overexpressing ROS degradation enzymes AhpB/TrxB2 rescues RNA phages from elimination. Crucially, because the underlying ROS-mediated RNA damage is minimal, RNA phage survival hinges on genomic redundancy. In single-phage infections, the lone RNA genome is highly vulnerable to cumulative damage and is eventually inactivated. In contrast, during co-infection by multiple RNA phages, the presence of multiple genome copies provides functional redundancy, thereby allowing a fraction of RNA phages to survive inside dormant bacteria. Given that most environmental bacteria are dormant and subject to heterogeneous phage infection, this copy number-dependent vulnerability offers a possible explanation for the scarcity, but not perish, of RNA phages in nature.

microbiology↗

bioRxiv2026

REST-AKT-SOX2 axis controls neuronal lineage state and Midkine-mediated communication in SHH-medulloblastoma.

Stem/progenitor-like cells are known drivers of tumor progression, chemoresistance, and relapse in Sonic-Hedgehog medulloblastoma (SHH-MB), yet the regulatory mechanisms that sustain these resilient cellular states remain incompletely defined. Here, we identify the RE1-silencing transcription factor (REST) as a key transcriptional regulator that preserves the progenitor compartment in SHH-MB through stabilization of the stemness factor SOX2. Mechanistically, REST activates AKT signaling, which in turn enhances SOX2 protein stability, revealing a REST-AKT-SOX2 axis that supports stem/progenitor identity and ongoing tumor maintenance. Beyond maintaining intrinsic stem-like programs, REST also orchestrates the extrinsic communication network of SHH-MB tumors. Single cell transcriptomic profiling and ligand-receptor interaction mapping highlight Midkine (MDK)-mediated signaling as one of the most upregulated intercellular communication routes in MB. We demonstrate that REST drives this signaling cascade through its control of SOX2. Perturbation of REST or SOX2 results in reduced MDK and its receptor, SDC2 expression, and chromatin immunoprecipitation assays show that SOX2 directly binds and regulates MDK/SDC2 expression, establishing and reinforcing a REST/SOX2 centered transcriptional mechanism that coordinates both progenitor maintenance and cell-cell communication in the malignant compartment. Together, these findings position REST as an integrator of intrinsic progenitor cell programs and extrinsic MDK-mediated signaling in SHH-MB. By linking stemness, communication and potential for therapeutic resistance, the REST-AKT-SOX2-MDK signaling axis emerges as a targetable vulnerability to suppress stem/progenitor driven tumor program in REST-driven SHH-MBs.

cancer biology↗

bioRxiv2026

Dimerisation and twist reversal of the Lewy fold in α-synuclein mutants with Parkinson's disease and dementia

Dominantly inherited missense and gene dosage mutations in SNCA, the -synuclein gene, cause familial forms of Parkinsons disease and dementia. Here we report the structures of -synuclein filaments from the brains of such individuals. Pathogenic mutations A53T and G51D in SNCA give rise to singlets and doublets of the Lewy fold with a left-handed helical twist in the absence of a peptide-like density for island A. By contrast, filaments from the non-pathogenic variant H50Q consist of singlets of the right-handed Lewy fold with a density for island A, like filaments of wild-type -synuclein. The structures of filaments from homozygous mice transgenic for human mutant A53T -synuclein (line M83) are unlike those from human brains. They are more similar to the multiple system atrophy folds than to the Lewy fold of Parkinsons disease, Parkinsons disease dementia and dementia with Lewy bodies

biophysics↗

bioRxiv2026

Geometry-enhanced protein language modeling enables discovery of novel antibiotic resistance genes

The global antibiotic resistome remains largely unexplored, not because antibiotic resistance genes (ARGs) are rare in the environment, but because many are evolutionarily distant from known ARGs. Current computational approaches primarily rely on sequence homology, and thus miss distant homologues. We develop GeoARG, a geometry-enhanced framework that integrates structural features with protein language models through knowledge distillation, enabling efficient large-scale screening using sequence input alone. Across multiple benchmarks, GeoARG substantially improves the detection of remotely homologous ARGs, particularly under low sequence identity and fragmented conditions. Large-scale metagenomic analysis uncovers 1,485 high-confidence ARG candidates that are highly divergent from known ARGs, expanding the phylogenetic and functional landscape of the resistome. Structural analyses further show that these candidates preserve active-site geometry and maintain stable ligand-binding configurations consistent with known resistance mechanisms. These results demonstrate that geometric constraints enable systematic expansion of the resistome and facilitate the discovery of evolutionarily distant yet functionally conserved genes. A public web server is available at https://ycclab.cuhk.edu.cn/GeoARG/.

bioinformatics↗

bioRxiv2026

Photo-downregulation of SIRT4 mitigates aging in mice by enhancing H3K9ac via fatty acid metabolism

As organisms age, mitochondrial metabolic activity declines, and disrupted gene expression regulation mediated by histone acetylation induces the emergence of senescent physiological phenotypes in tissues. In this study, we found that periodic exposure to red light significantly increased histone H3 Lys9 acetylation (H3K9ac) levels in the tissues and organs of aged mice. Following red light exposure, silent information regulation factor 4 (SIRT4) protein levels in keratinocytes were notably reduced, whereas glycolysis, fatty acid metabolism, and the tricarboxylic acid (TCA) cycle were significantly activated in keratinocytes. The reduction in mitochondrial SIRT4 levels enhances the acetylation of mitochondrial metabolic proteins, particularly malonyl-CoA decarboxylase (MCD), a potent inhibitor of the key rate-limiting enzyme carnitine palmitoyltransferase 1A (CPT1A) in fatty acid oxidation. This process promotes mitochondrial fatty acid oxidation and TCA cycle. Additionally, the decrease in SIRT4 activates SIRT1 through feedback mechanisms, thereby alleviating its inhibition on PPAR- in senescent keratinocytes and comprehensively activating the expression of genes related to lipid metabolism. This lipid metabolism activation ultimately facilitates the accumulation of acetyl-CoA within keratinocytes, increases H3K9ac levels, and reshapes the expression patterns of senescence-related genes. Eventually, cellular aging is effectively mitigated by the synergistic regulation of metabolism, inflammation, and gene expression. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/717004v2_ufig1.gif" ALT="Figure 1"> View larger version (82K): org.highwire.dtl.DTLVardef@ba3865org.highwire.dtl.DTLVardef@1cc9a58org.highwire.dtl.DTLVardef@1a90e7borg.highwire.dtl.DTLVardef@1f5e88f_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical AbstractMechanism of anti-aging action of red light: Red light can reduce SIRT4 signalling in keratinocytes, thereby reactivating lipid metabolism and increasing levels of acetyl-CoA. This promotes histone acetylation, which in turn remodels the expression of age-related inflammatory factors and genes.

cell biology↗

bioRxiv2026

STDrug enables spatially informed personalized drug repurposing from spatial transcriptomics

Drug repurposing offers a scalable route to accelerate therapeutic discovery, yet existing approaches based on single-cell RNA sequencing (scRNA-seq) often overlook spatial tissue context, limiting their ability to capture microenvironment-dependent drug responses. Here we present STDrug, a spatially informed computational framework that integrates spatial transcriptomics, graph-based modeling, and multimodal learning to enable patient-specific therapeutic prioritization. STDrug identifies and aligns disease and control spatial domains using graph convolutional networks and coherent point drift, and prioritizes candidate drugs through an integrative scoring scheme combining tumor-reversible gene signatures, perturbation-based reversal scores, and knowledge-guided gene weighting within a machine learning framework. By modeling spatial domain interactions alongside predicted drug efficacy and toxicity, STDrug generates robust patient-level drug scores. Across hepatocellular carcinoma and prostate cancer datasets, STDrug outperforms existing single-cell and spatial transcriptomics-based drug repurposing methods, achieving signficantly improved predictive accuracy (AUCs=0.81-0.82) across patients. Validation using large-scale electronic health records and in vitro assays further supports the translational relevance of top-ranked candidates. Taking together, STDrug establishes a generalizable framework for incorporating spatial omics into therapeutic discovery, advancing spatially informed and personalized drug repurposing.

bioinformatics↗

bioRxiv2026

PRISM: A High-Throughput Simulation Infrastructure for CADD Agents

Despite rapid progress in AI agents for computer-aided drug design (CADD), protein-ligand simulation workflows remain fragmented across disparate tools, creating a major bottleneck for scalable candidate evaluation. Here, we present PRISM (Protein-Receptor Interaction Simulation Modeler), a Python platform built on GROMACS that unifies ligand parameterization across multiple force fields, automated system construction, enhanced sampling, multi-tier binding free energy estimation, and trajectory analysis within a single workflow. Through the Model Context Protocol (MCP), PRISM further serves as the computational infrastructure for CADD-Agent, an expert-workflow-driven AI agent designed to orchestrate hierarchical drug screening pipelines. As a pilot application, we applied PRISM to riboflavin synthase and demonstrated end-to-end automation from candidate library assembly to binding pocket characterization, identifying a potential allosteric inhibition site at the oligomerization interface. Together, these results establish PRISM as a high-throughput simulation infrastructure for agent-enabled CADD.

biophysics↗

bioRxiv2026

Gut Microbiome Alterations in Canine Idiopathic Epilepsy: A Pairwise Case-Control Study

BackgroundIdiopathic epilepsy (IE) is the most common chronic nervous system disorder of dogs, and its cause is poorly understood. Emerging evidence suggests that microbiome alterations can occur with IE via the microbiota-gut-brain axis. Therefore, we analyzed the fecal microbiomes of 98 dogs (49 IE, 49 control) in a pairwise case-control observational study using 16S rRNA gene sequencing. ResultsAlthough the microbial community was mostly similar between groups, IE was associated with a modest but significant shift in Weighted-Unifrac distance (P = 0.042). We used six differential abundance (DA) methods to identify differentially abundant amplicon sequencing variants (ASVs) between IE and control groups. Notably, one Collinsella ASV was found to be significantly more abundant in IE dogs by all six methods. The gut microbial compositions varied drastically across households (accounting for about 69% of the total variation), but did not have significant differences between sex, age, or breed. Phenobarbital administration in IE dogs had a significant effect on seizure control, and was not associated with changes in the microbiome. ConclusionOur findings suggest a relationship between gut microbiomes and IE. However, the specific mechanism needs to be further investigated.

microbiology↗

bioRxiv2026

Structural Basis of M1 Muscarinic and H3 Histamine Receptor Inhibition in OPC Differentiation

Muscarinic and histamine receptors are neurotransmitter-binding proteins within the large family of G protein-coupled receptors (GPCRs) and are relevant to human health and disease, including multiple sclerosis (MS), a chronic immune-mediated inflammatory demyelinating disease of the central nervous system (CNS) with neurodegenerative components. MS affects approximately 1 in 333 people, and women are affected at roughly threefold higher rates than men. A major pathological feature of MS is demyelination with incomplete remyelination of axons in the CNS. Because oligodendrocyte progenitor cells (OPCs) can differentiate into mature oligodendrocytes that restore myelin, small molecules that promote OPC differentiation represent a potential therapeutic strategy. High-throughput screening identified 18 hit compounds with EC50 values below 0.2 M, including the lead compound CN045, which showed an EC50 of 40 nM in vitro. Cheminformatic and experimental target-identification studies implicated the M1 muscarinic receptor and the H3 histamine receptor as candidate targets. To interpret these findings, we performed docking, molecular dynamics simulations, and binding free-energy analyses on complexes involving CN045 and clemastine, a known antihistamine with antimuscarinic activity. The simulations support weaker and less stable binding of CN045 to H3 than to M1 and identify residue-level interactions that contribute to stability within the M1 binding pocket. Comparisons between CN045 and clemastine at M1 further suggest that the two ligands sample different local conformational ensembles, including differences in conserved microswitch behavior associated with active-like versus inactive-like receptor states. Together, these results provide a structural framework for understanding ligand-specific M1 engagement and may help guide future optimization of remyelination-promoting compounds.

biophysics↗

bioRxiv2026

Striatal Social Reward Sensitivity Predicts Trust-Related Brain Responses Depending on Closeness and Depression

BackgroundDepression is associated with social dysfunction, but the mechanisms linking affective symptoms to disrupted close relationships remain poorly understood. One possibility is that depression alters how people experience rewards shared with close others and how they interpret partners actions. It remains unclear whether neural sensitivity to shared reward predicts social valuation during more complex interactions such as reciprocated trust. MethodsIn this preregistered fMRI study, participants completed a reward-sharing task and a Trust Game with a close friend, a stranger, and a computer. We measured striatal shared reward sensitivity (SRS; friend > computer) and tested whether it related to subsequent investment behavior and brain responses to trust reciprocation. Depressive symptoms and perceived closeness were assessed via self-report. ResultsIn a final sample of n = 123, participants reporting more depressive symptoms invested more in their friend than in the computer. Striatal SRS predicted temporoparietal junction responses to reciprocated trust, but this association depended jointly on social closeness and depression -- with depression reversing the expected pattern among individuals reporting closer relationships. Striatal SRS was also inversely associated with connectivity between the default mode network and cerebellum during reciprocity. ConclusionsThese findings suggest that closeness calibrates the striatal SRS link to regional activity and network-level responses during social exchange, while depression alters how striatal SRS relates to regional activity, potentially disrupting how individuals interpret and respond to close others.

neuroscience↗

bioRxiv2026

eSIG-Net: Accurate prediction of single-mutation induced perturbations on protein interactions using a language model

Most proteins exert their functions in complex with other interactors. Single mutations can exhibit a profound impact on perturbing protein interactions, leading to human disease. However, predicting the effect of single mutations on protein interactions remains a major computational challenge. Deep learning, particularly protein language models or transformers, has become an effective tool in bioinformatics for protein structure prediction. However, the functional divergence of mutations makes it difficult to predict their interaction perturbation profiles. To address this fundamental challenge, we present eSIG-Net (edgetic mutation Sequence-based Interaction Grammar Network), a novel sequence-based "Interaction Language Model" for predicting protein interaction alterations caused by single mutations. eSIG-Net combines various protein sequence embeddings, introduces a mutation-encoding module with syntax and evolutionary insights, and employs contrastive learning to evaluate mutation-induced interaction changes. eSIG-Net significantly outperforms current state-of-the-art sequence-based and structure-based prediction methods at predicting mutational impact on protein interactions. We highlight examples where eSIG-Net nominates causal variants with high confidence and elucidates their functional role under relevant biological contexts. Together, eSIG-Net is a first-in-kind "interaction language model" that can accurately predict interaction-specific rewiring by single mutations with only sequence information, and exhibits generalizability across biological contexts.

bioinformatics↗

bioRxiv2026

Multidimensional MRI reveals cellular-scale microstructural phenotypes in human brain aging

Brain aging is accompanied by profound cellular and microstructural changes that precede overt tissue loss, yet in vivo MRI studies largely emphasize macroscopic measures or isolated diffusion and relaxation metrics, providing limited insight into how cellular-scale tissue architecture is altered across the adult lifespan. Here, we apply multidimensional diffusion-relaxation MRI (MD-MRI) to map voxel-wise microstructural phenotypes in cognitively unimpaired adults spanning early adulthood to late life (23-77 years). Rather than relying on predefined compartment models, MD-MRI resolves continuous voxel-wise distributions in a joint diffusion-relaxation space, enabling an integrated, model-free description of how cellular shape, size, restriction, and chemical environment vary with age. Using this approach, we reveal age-related multilateral shifts within a complex microstructural landscape, marked by increasing heterogeneity and disorder across brain tissue. With age, cellular-scale features showed a systematic transition from small to larger length-scale structures accompanied by reduced microscopic restriction, indicating a loss of fine cellular barriers and expansion of extracellular space. In parallel, we show tissue-dependent alterations in fast-relaxing properties aligned with known gray- and white-matter aging processes, including iron accumulation and myelin loss. Together, these findings indicate that normative brain aging involves progressive reorganization of structure and composition at the cellular level, rather than uniform shifts in bulk tissue properties. By decoupling cellular-scale shape, size, restriction, and chemical environment in vivo, MD-MRI identifies increasing cellular heterogeneity and breakdown of microscopic restriction as central features of human brain aging and provides a biologically interpretable framework for linking microstructural reorganization to age-related functional decline.

neuroscience↗

bioRxiv2026

Generalizable Finger Movement Decoding from Intracranial Recordings Across Static and Dynamic Actions

Reliable decoding of finger movements requires brain-computer interfaces (BCIs) that generalize across the diverse static and dynamic actions performed in daily life. Static postures and dynamic movement sequences rely on partially distinct neural representations, and the balance between these components varies widely across tasks. Yet most BCI decoding pipelines are optimized for a narrow task domain, limiting their ability to transfer to new scenarios. Here we show that standard intracranial decoding approaches show notable performance drops when applied to previously unseen finger tasks with different static-dynamic compositions, and that generalization critically depends on multiple elements of the decoding pipeline. High gamma features and short temporal windows yield the most robust cross task transfer. Although nonlinear models perform best when examples of all tasks are represented during training, linear decoders generalize better to novel, particularly dynamic, actions. We identify a consistent static-dynamic structure across tasks that may provide a useful basis for improving generalization. Finally, we show that anatomical heterogeneity between tasks also constrains generalization. Together, these results establish design principles for BCIs that generalize reliably across the rich repertoire of human finger movements.

neuroscience↗