Biology subjects

Peng, H.

Publications and source records attributed to Peng, H..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Prophylactic Lipoxin A4 Attenuates Clostridioides difficile Infection by Augmenting Epithelial Barrier and Resolving Inflammation

Clostridioides difficile infection (CDI) is a leading healthcare-associated diarrhea with high recurrence rates, partially due to antibiotic-induced dysbiosis and dysregulated host inflammation. Specialized pro-resolving mediators (SPMs), such as Lipoxin A4 (LXA4), offer promise in controlling excessive inflammation and promoting tissue repair, yet their role in CDI remains unexplored. Here, we developed a compact, gas-tight gut-on-a-chip (GOC) system that reconciles the anaerobic requirements of C. difficile with the oxic needs of human intestinal epithelium, enabling physiologically relevant co-culture within a standard incubator. A CDI in vitro model was established based on this GOC system. Using the model, we demonstrated that prophylactic administration of LXA4 significantly preserved epithelial barrier integrity, attenuated pro-inflammatory cytokine secretion (IL-8 and IFN-{gamma}), and reduced bacterial colonization. Transcriptomic analysis revealed that LXA4 pretreatment upregulated genes involved in cell junction organization while downregulated immune activation pathways. These protective effects were validated in a murine CDI model, where LXA4 pretreatment reduced weight loss, pathological damage, and fecal bacterial burden. Furthermore, prophylactic administration of LXA4 synergized with vancomycin treatment further enhanced antibiotic efficacy while allowing a 50% dose reduction without compromising therapeutic outcomes. Our study establishes a robust approach for CDI research and highlights the prophylactic and adjuvant potential of inflammation-resolving strategies, offering a novel approach to mitigate CDI incidence and improve treatment outcomes.

bioengineering↗

bioRxiv2026

Brain-wide Organization of Post-Synaptic Sites: Three Principles

Synapses are fundamental units of neural computation and structural plasticity in the brain, yet their brain-wide spatial organization in mammals remains largely unknown. Building on our previous mapping and modeling of dendritic spines and axonal boutons, we developed a statistical approach to generate over 17.99 million predicted post-synaptic sites based on the potential arbor contacts (PPSSPAC) across the dendritic arbors of 155,743 neurons spanning the entire mouse brain. By analyzing the topological features of these sites, we identified three key organizational principles. First, PPSSPAC exhibits a distinct region-specific spatial pattern at the dendritic branch level, preferentially enriching near the distal ends of dendritic segments, in contrast to the valley-like distribution of pre-synaptic sites along axonal branches. Cross-species validation against independent electron microscopy datasets from mouse and human brains, revealed a conserved and previously unquantified pattern of synaptic organization. Second, the spatial distribution of PPSSPAC effectively captures variations across cell types in the hippocampus, enabling neuron classification based on synaptic architecture. This serves as a complementary mesoscale descriptor to existing classifications based on global neuronal connectivity (source-target relationships) or local dendritic microenvironments. Third, the spatial distribution of PPSSPAC, rather than synapse density, shows remarkable correlation with independent whole-brain electrophysiological activity. The spatial organization of PPSSPAC also correlates with several gene expression datasets. These results suggest the post-synaptic pattern could be mediator linking molecular signatures, neural dynamics, and connectivity types of cells. Our study reveals, for the first time, a structural substrate for hierarchical information processing in the brain, providing new insights into neural computation and a foundation for brain digital twin models to support next-generation AI infrastructure.

neuroscience↗

bioRxiv2025

Multimodal Data Fusion Reveals Morpho-Genetic Variations in Human Cortical Neurons Associated with Tumor Infiltration

We introduce LetsACT (Light-Electron-Transcriptome synergistic ACTomography), a multimodal integration platform that overcomes the limitations of single-modality data acquisition and analysis of human brain cells while synergistically leveraging the strengths of each modality. Our approach enables the rapid sample preparation, cell injection, imaging, and multimodal integration of large-scale human neuronal datasets at single-cell resolution. By generating initial laser-scanning-microscopy based optical reconstruction of neuron morphologies followed by refining them using electron-microscopy derived morphological priors, we have assembled one of the largest human cortical morphology datasets to date: 8,398 neurons from 58 donors, with high cortical coverage. This platform is then applied to studying morphological impact of tumor infiltration. Pyramidal neurons in glioma-infiltrated tissues display clear volume shrinkage in somas and branches, tapering from the soma to nearby dendritic compartments. By integrating these morphological variations with spatial and bulk transcriptomic profiles, we find that glioblastoma tissues exhibit dysregulation of 15.29% of genes, including overexpression of TERT, whereas infiltrated tissues show 7.74% gene dysregulation, characterized by overexpression of tumor suppressors such as CDKN2A and TP53. Our analysis implies that pyramidal neurons observed in these infiltrated tissues may involve an active defense instead of undergoing passive apoptosis. Our finding also indicates that LetsACT establishes a valuable resource for the large-scale, comprehensive morpho-genetic analysis of human tissues.

neuroscience↗

bioRxiv2025

Identification and Characterization of a Small Molecule Ligand for the Huntingtin-HAP40 Complex

Huntingtons disease (HD) is caused by a CAG repeat expansion mutation, giving rise to a polyglutamine expansion in the huntingtin (HTT). However, the explicit molecular functions of HTT and opportunities for direct pharmacological modulation remain incompletely understood. Here, we report the discovery of a small molecule ligand for the full-length HTT protein in complex with its partner, HAP40. Using affinity selection mass spectrometry (AS-MS), we identified a stereoselective binder, whose binding was characterized by surface plasmon resonance, hydrogen-deuterium exchange mass spectrometry, and cryo-electron microscopy at 2.3 [A] resolution. The ligand binds HTT-HAP40 in vitro with single-digit micromolar affinity and one-to-one stoichiometry at a druggable interface previously predicted computationally. In silico studies predicted and experimental analyses confirmed the (R)-enantiomer as the eutomer and initial structure activity relationship was established experimentally. This work details a structurally-validated chemical scaffold and highlights a ligandable pocket which could enable development of chemical probes for probing HTT biology, as well as therapeutics such as degraders and imaging agents for HD.

pharmacology and toxicology↗

bioRxiv2025

Multimodal AI Decodes Extreme Environment Functional Dark Matter Beyond Homology

Functional annotation of proteins from extreme environments represents a major bottleneck for bioresource discovery, as a vast reservoir of functional dark matter defies existing homology-based methods. We demonstrate that environmental pressures impart conserved physicochemical energy signatures that co-determine protein function with sequence and structure. Here we developed ACCESS, a multimodal graph neural network employing hierarchical contrastive learning with a tailored label-sample co-embedding to fuse energy, sequence, and structural information and overcome homology scarcity. ACCESS surpasses state-of-the-art methods including BLASTp and CLEAN in annotating low-identity enzymes. Applied to extreme environmental metagenomics, we constructed a function map of extremophile enzymes to expand the biocatalyst library, pinpointed functionally critical residues to guide rational design, and enabled large-scale, function-based macro-evolutionary analyses. This paradigm transcends the limitations of homology, illuminating protein dark matter and accelerating the exploration of the biospheres functional diversity for applications in biotechnology and therapeutic development.

bioinformatics↗

bioRxiv2025

Igniting full-length isoform analysis in single-cell and spatial RNA-seq data with FLAMESv2

Long-read single-cell RNA-sequencing enables the profiling of RNA isoform expression and alternative splicing at single cell resolution. However, diverse single-cell technologies and sparse isoform data demand flexible and accurate analysis tools. We introduce FLAMESv2, a highly modular and protocol-agnostic R/Bioconductor package for long-read single-cell RNA-seq data analysis. FLAMESv2 supports a wide range of single-cell and spatial protocols, is highly configurable, scales to allow multi-sample analysis and provides versatile visualisation and analysis outputs. We demonstrate its compatibility with both droplet-based and combinatorial barcoding single-cell methods, as well as spatial transcriptomics workflows. Benchmarking confirms FLAMESv2 achieves field-leading performance across key analysis tasks. Applying FLAMESv2 to in vitro differentiation of stem cells into neurons, we identify cell-types, differentiation trajectories, expression of annotated and novel isoforms and isoform expression diversity and heterogeneity within individual cells. FLAMESv2 provides a comprehensive, flexible approach to analysing long-read single-cell RNA-sequencing, unlocking this powerful methodology for RNA isoform characterisation.

bioinformatics↗

bioRxiv2025

Understanding Fertility Intention Through the Lens of Family Functioning, Fertility Anxiety and Marriage-Fertility Views: A TPB-Based SEM Approach

ABSRTACTO_ST_ABSBackgroundC_ST_ABSGlobal fertility rates are declining, and despite Chinas three-child policy, the number of women of childbearing age continues to shrink. Fertility intention, a key predictor of fertility behavior, is shaped by factors such as socioeconomic stress, family functioning, and psychological traits. ObjectiveGrounded in the Theory of Planned Behavior, this study investigates how family functioning, marriage and fertility values, and fertility anxiety influence the fertility intentions of newlywed, childless young couples. MethodsA cross-sectional survey of 1,292 newlywed, childless couples in Yinchuan, Ningxia (2024) assessed demographics, family functioning (FAD), marriage and fertility values (MFV), and fertility anxiety (FA). Multiple logistic regression and structural equation modeling (SEM) were used. ResultsFamily functioning promoted intentions to have two or more children indirectly via positive communication and mediated by traditional MFV (44.4% of the total effect). Fertility anxiety showed no significant effect. Men preferred more children than women, and fertility intentions increased with age ConclusionsImproving family communication and reinforcing traditional values may help boost fertility intentions. Findings offer insight into the family-psychological mechanisms shaping fertility decisions.

animal behavior and cognition↗

bioRxiv2025

Bidirectional translocation of actomyosin drives epithelial invagination in ascidian siphon tube morphogenesis

How epithelia perform a spatiotemporal heterogeneous force generating program to drive a sequential tissue morphogenesis remains unclear, particularly the underlying precise mechanical mechanisms. This study investigated dynamic actomyosin reorganization between apical and lateral membrane cortex regions during two sequentially invaginated stages during ascidian atrial siphon tube morphogenesis. At the initial invagination stage, the originally lateral-located actomyosin redistributed to the apical domains, while those actomyosin redistributed back to lateral domains at the accelerated invagination stage. Using genetic mutants to modulate myosin activities, the initial invagination was strengthened or abolished, indicating invagination is apical constriction dependent. Optogenetic inhibition of myosin activities in lateral domains after initial invagination stage blocked the further processes, suggesting lateral constriction of actomyosin is required for the accelerated invagination. Vertex model simulations uncovered a coupled mechanism underlying epithelial invagination driven by apicobasal tension imbalance and lateral contraction. We thus propose an actomyosin redistribution mechanical model: lateral actomyosin first redistributes apically to drive apical constriction and shape the initial invagination, then apical actomyosin redistributes laterally to promote lateral contractility and accelerate invagination. Our findings reveal a bidirectional reorganization of actomyosin network as a central mechanism driving epithelial invagination, providing insights on epithelial invagination and the organ morphogenesis during development.

developmental biology↗

bioRxiv2025

Identification and quantification of alternative polyadenylation sites in single cell RNA-seq data using scPAISO

AbstractsAlternative polyadenylation (APA) is a critical posttranscriptional mechanism that generates transcriptomic diversity through the production of mRNA isoforms with distinct 3 UTRs or coding sequences. Current APA analysis based on single-cell RNA sequencing (scRNA-seq) for establishing cell type-specific APA landscapes primarily rely on Read2 data, which lacks precise cleavage site (CS) information. This limitation restricts their ability to achieve precise de novo mapping of polyadenylation sites (PASs). Here, we present single-cell PolyAdenylation ISOform quantification (scPAISO), a computational pipeline designed for de novo identification of PAS and quantification of PAS isoforms in scRNA-seq data, by leveraging the often-discarded Read1 from 3 tag-based scRNA-seq protocols. Unlike existing tools, scPAISO directly captures mRNA 3 end cleavage sites, enabling superior performance in motif enrichment (stronger AAUAAA signal) and peak precision (sharper PAS peaks). Moreover, the smaller peak widths enhance the spatial resolution, enabling more accurate detection of closely spaced PASs in the genome. By integrating Read1 and Read2 data, scPAISO achieves isoform-level quantification with an assignment accuracy exceeding 95%. We demonstrate the robustness of scPAISO in identifying PASs and quantifying APA events across diverse biological contexts, including hematopoiesis, systemic sclerosis (SSc), and mouse tissues. We identified stage-specific 3 UTR lengthening in hematopoietic progenitors, global 3 UTR remodeling in SSc and tissue-specific polyadenylation (PA) preference along with RNA-binding proteins in mice. Overall, scPAISO represents a significant advancement in the analysis of APA at single-cell resolution and provides a powerful tool for exploring the regulatory landscape of APA, offering new insights into transcriptome complexity and gene regulation in both health and disease.

bioinformatics↗

bioRxiv2025

Modeling 3D Mesoscaled Neuronal Complexity through Learning-based Dynamic Morphometric Convolution

Accurate reconstruction of neuronal morphology from three-dimensional (3D) light microscopy is fundamental to neuroscience. Nevertheless, neuronal arbors intrinsically exhibit slender, tortuous geometries with high orientation variability, posing significant challenges for standard 3D convolutions whose static, axis-aligned receptive fields lack adaptability to such complex morphology. To address this, we propose the Dynamic Morph-Aware Convolution (DMAC) framework, which incorporates inherent geometric priors into convolution by jointly adapting both the shape and orientation of the kernel. This enables morphology-aware feature extraction tailored to arborized and variably oriented neuronal trajectories. Specifically, we first apply dynamic tubular convolutions to bridge the structural mismatch between isotropic convolution kernels and the slender morphology of neurons. To sufficiently accommodate the 3D orientation variability of neuronal branches, we further introduce a rotation mechanism that dynamically reorients the tubular kernel via two learnable angles (elevation and azimuth), enabling precise alignment with local neuronal directions. We validate our method through extensive experiments on four mesoscaled neuronal imaging datasets, including two from the BigNeuron project (Drosophila and Mouse) and two additional benchmarks (NeuroFly and CWMBS). Our approach consistently outperforms state-of-the-art methods, achieving average improvements of 5.4% in Entire Structure Average (ESA), 6.9% in Different Structure Average (DSA), and 7.5% in Percentage of Different Structure (PDS). These results demonstrate the effectiveness of our proposed DMAC in capturing complex morphological variations and enhancing structural fidelity across diverse mesoscaled neuronal morphologies.

neuroscience↗

bioRxiv2025

A disease-causing Isoleucyl-tRNA synthetase variant leads to altered protein complex formation and cellular stress response

Aminoacyl-tRNA synthetases are key enzymes in protein synthesis, as they catalyze the attachment of amino acids to their designated, cognate tRNAs. As such, mutations in aminoacyl-tRNA synthetases are associated with severe diseases, such as neurodevelopmental disorders. Many of these mutations occur in the catalytically active site or tRNA binding domains, however, others can affect domains associated with multisynthetase complex formation. Here, we investigate a disease-causing mutation in the UNE-L domain of Isoleucyl-tRNA synthetase (IARS1, IleRS), which mediates IleRS interactions within the multisynthetase complex. Interestingly, levels of the resulting protein were severely reduced in comparison to wildtype IleRS. While bulk protein synthesis and cell proliferation were not affected, the integrated stress response signaling pathway was altered. This change was exacerbated in low glucose medium, suggesting that mutant cells could respond differently to cellular stress. Our study hints at a possible underlying disease mechanism, where catalytic activity might not be affected but instead complex formation and protein stability.

molecular biology↗

bioRxiv2025

Neuron-Microenvironments Associated with Specific Long-Range Connectivity Reveal Functional Modules in the Adult Drosophila Brain

Advances in electron microscopy (EM) and computational neuroscience enable large-scale neuronal reconstruction, yet existing methods often overlook surrounding neurons influence. Using a whole-brain EM dataset of Drosophila, we analyzed 50 million synapses and derived microenvironmental (MicroEnv) features for over 130,000 neurons categorized by polarity. This refined 78 brain regions into 482 subregions, forming a high-resolution MicroEnv-atlas. MicroEnv features improved spatial coherence by 68% compared to single-neuron morphological features and correlated with long-range projections in the Mushroom Body. Integration with scRNA-seq data revealed associations with transmembrane transport and metabolism, suggesting roles in intercellular communication. Clustering based on distal projections identified submodules aligned with functional hierarchies, including feeding and multisensory processing. Our framework highlights the value of microenvironmental context in mapping brain organization.

neuroscience↗

bioRxiv2025

Effect of the S2' site cleavage on SARS-CoV-2 spike

SARS-CoV-2 initiates infection of host cells by fusing its envelope lipid bilayer with the cell membrane. To overcome kinetic barriers for membrane fusion, the virus-encoded spike (S) protein refolds from a metastable prefusion state to a lower energy, stable postfusion conformation. The protein is first split into S1 and S2 fragments at a proteolytic site after synthesis, and presumably further cleaved at a second site, known as the S2 site, before membrane fusion can occur. We report here a cryo-EM structure of S2 fragment after the S2 cleavage, possibly representing a late fusion intermediate conformation, in which the fusion peptide and transmembrane segment have yet to pack together, distinct from the final, postfusion state. Functional assays demonstrate that the S2 cleavage accelerates membrane fusion, probably by stabilizing fusion intermediates. These results advance our understanding of SARS-CoV-2 entry and may guide intervention strategies against pathogenetic coronaviruses.

biochemistry↗

bioRxiv2025

High-throughput protein target mapping enables accelerated bioactivity discovery for ToxCast and PFAS compounds

Chemical pollution is a global threat to human health, yet the toxicity mechanism of most contaminants remains unknown. Here, we applied an ultrahigh-throughput affinity-selection mass spectrometry (AS-MS) platform to systematically identify protein targets of prioritized chemical contaminants. After benchmarking the platform, we screened 50 human proteins against 481 prioritized chemicals, including 446 ToxCast chemicals and 35 per-and polyfluoroalkyl substances (PFAS). Among 24,050 interactions assessed, we discovered 35 novel interactions involving 14 proteins, with fatty acid-binding proteins (FABPs) emerging as the most ligandable protein family. Given this, we selected FABPs for further validation, which revealed a distinct PFAS binding pattern: legacy PFAS selectively bound to FABP1, whereas replacement compounds, PFECAs, unexpectedly interacted with all FABPs. X-ray crystallography further revealed that the ether group enhances molecular flexibility of alternative PFAS, to accommodate the binding pockets of FABPs. Our findings demonstrate that AS-MS is a robust platform for the discovery of novel protein targets beyond the scope of the ToxCast program and highlight the broader protein-binding spectrum of alternative PFAS as potential regrettable substitutes.

pharmacology and toxicology↗

bioRxiv2025

Identification of Rapaglutin E as An Isoform-specific Inhibitor of Glucose Transporter 1

Natural products rapamycin and FK506 are macrocyclic compounds with therapeutic benefits whose unique scaffold inspired the generation and exploration of the hybrid macrocycle rapafucins. From this library, a potent inhibitor of the facilitative glucose transporter (GLUT), rapaglutin A (RgA) was previously identified. RgA is a pan-GLUT inhibitor of Class I isoforms GLUT1, GLUT3, and GLUT4. Herein, we report the discovery of rapaglutin E (RgE). Unlike RgA, RgE is highly specific for GLUT1. Further characterization revealed that RgE and RgA likely bound to distinct sites on GLUT1 despite their shared FKBP-binding domain, suggesting that the distinct effector domains of RgE and RgA play key roles in recognition of GLUTs. TOC GRAPHIC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=168 SRC="FIGDIR/small/641094v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@d69b12org.highwire.dtl.DTLVardef@15ee120org.highwire.dtl.DTLVardef@e2495org.highwire.dtl.DTLVardef@83e270_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2025

Rapaprotin is Activated by an Endopeptidase to Disassemble 26S Proteasome

The 19S regulatory particle (RP) associates with the 20S core particle (CP) to form the 26S proteasome, an evolutionarily conserved holoenzyme that plays key roles in both physiological and pathological processes. Proteasome inhibitors that target the catalytic subunits within the 20S have proven to be valuable research tools and therapeutics for various cancers. Herein we report the discovery of rapaprotin, a 26S proteasome assembly inhibitor from our natural product-inspired hybrid macrocycle rapafucin library. Rapaprotin induces apoptosis in both myeloma and leukemia cell lines. Genome-wide CRISPR-Cas9 screen identified a cytosolic enzyme, prolyl endopeptidase (PREP) that is required for the pro-apoptotic activity of rapaprotin. Further mechanistic studies revealed that rapaprotin acts as a molecular transformer, changing from an inactive cyclic form into an active linear form, rapaprotin-L, upon PREP cleavage, to block 26S proteasome activity. Time-resolved cryogenic electron microscopy (cryo-EM) revealed that rapaprotin-L induces dissociation of the 19S RP from the 26S holoenzyme, which was verified in cells. Furthermore, rapaprotin exhibits a marked synergistic effect with FDA-approved proteasome inhibitors and resensitizes drug-resistant multiple myeloma cells from patients to bortezomib. Taken together, these results suggest that rapaprotin is a new chemical tool to probe the dynamics of the 26S proteasome assembly and a promising anticancer drug lead.

pharmacology and toxicology↗

bioRxiv2025

Enantioselective Protein Affinity Selection Mass Spectrometry (EAS-MS)

We report an enantioselective protein affinity selection mass spectrometry screening approach (E-ASMS) that enables the detection of weak binders, informs on selectivity, and generates orthogonal confirmation of binding. After method development with control proteins, we screened 31 human proteins against a designed library of 8,210 chiral compounds. 16 binders to 12 targets, including many proteins predicted to be "challenging to ligand", were discovered and confirmed in orthogonal biophysical assays. 7 binders to 6 targets bound in an enantioselective manner, with KD values ranging from 3 to 20 {micro}M. Binders for four targets (DDB1, WDR91, WDR55, and HAT1) were selected for in-depth characterization using X-ray crystallography. In all four cases, the mechanism for enantioselectivity was readily explained. We conclude E-ASMS can be used to identify and characterize selective and weakly-binding ligands for novel protein targets with unprecedented throughput and sensitivity.

pharmacology and toxicology↗

bioRxiv2024

Bridging the Dimensional Gap from Planar Spatial Transcriptomics to 3D Cell Atlases

Spatial transcriptomics (ST) has revolutionized our understanding of tissue architecture, yet constructing comprehensive three-dimensional (3D) cell atlases remains challenging due to technical limitations and high cost. Current approaches typically capture only sparsely sampled two-dimensional sections, leaving substantial gaps that limit our understanding of continuous organ organization. Here, we present SpatialZ, a computational framework that bridges these gaps by generating virtual slices between experimentally measured sections, enabling the construction of dense 3D cell atlases from planar ST data. SpatialZ is designed to operate at single-cell resolution and function independently of gene coverage limitations inherent to specific spatial technologies. Comprehensive validation using real 3D ST and independent serial sectioning datasets demonstrates that SpatialZ accurately reconstructs virtual slices while preserving cell identities, gene expression patterns, and spatial relationships. Leveraging the BRAIN Initiative Cell Census Network data, we constructed a 3D hemisphere atlas comprising over 38 million cells, a scale not feasible experimentally. This dense atlas enables unprecedented capabilities, including in silico sectioning at arbitrary angles, explorations of gene expression across both 3D volumes and surfaces, and 3D mapping of query tissue sections. While currently validated for spatial transcriptomics, the underlying principles of SpatialZ could potentially be adapted for spatial proteomics, spatial metabolomics, and even spatial multi-omics. Validated through internal and external testing, our computationally generated atlas maintains biological accuracy, providing unprecedented resolution of spatial molecular landscapes and demonstrating the potential of computational approaches in advancing 3D ST.

bioinformatics↗