Biology subjects

Zhu, Y.

Publications and source records attributed to Zhu, Y..

At least 91 records · Page 5Linked to original sources

bioRxiv2026

Nature-inspired Nanoparticle Adiposomes Enable Targeted Delivery of Hydrophobic Drug for Anti-Cancer Treatment

The predominance of hydrophobic molecules in drug pipelines poses a fundamental delivery challenge in the aqueous physiological environment. Inspired by the endogenous lipid-transport machinery of lipid droplets and lipoproteins, adiposome was developed as a biocompatible platform for hydrophobic drug delivery. Here, docetaxel (DTX) was selected as a model hydrophobic chemotherapeutic agent to evaluate the therapeutic versatility of adiposome. Non-targeted DTX-loaded adiposomes (DTX-Ad) reduced systemic toxicity by avoiding the allergenic excipients Tween 80 and ethanol used in commercial DTX formulations. The cytotoxic mechanism and intracellular responses of DTX-Ad were comprehensively characterized. To boost antitumor efficacy, three tumor-targeting DTX-Ad formulations were subsequently engineered. Lung-targeting DTX-adiposomes (Lung@DTX-Ad), mediated by AAM-B1-28-CRGDK fusion peptide/NRP1 axis, enhanced antitumor efficacy in a lung metastasis model. BCMA-targeting DTX-adiposomes (BCMA@DTX-Ad), conferred by biotin-avidin-mediated antibody conjugation, achieved sustained suppression in a multiple myeloma model. Liver-targeting DTX-adiposomes (Liver@DTX-Ad), enabled by the ApoE/LDLR axis, outperformed both commercial DTX injection and sorafenib in hepatocellular carcinoma models. Taken together, these results demonstrate adiposome as a promising and broadly applicable drug delivery platform, with considerable potential for clinical translation across diverse malignancies.

cancer biology↗

bioRxiv2026

De novo design of binder proteins targeting Helicobacter pylori adhesin BabA

Helicobacter pylori has been classified as a Group 1 carcinogen by the International Agency for Research on Cancer of the World Health Organization and is one of the most well-established risk factors for gastric cancer. Long-term colonization by H. pylori depends on adhesin-mediated attachment to the gastric mucosa, among which the blood group antigen-binding adhesin BabA is a key surface factor involved in host recognition, tissue tropism, and persistent infection. In this study, we established a structure-guided computational design pipeline to develop compact protein binders targeting functionally relevant epitopes of BabA. First, using experimentally resolved BabA-antibody and BabA-nanobody complex structures as templates, we extracted structural contact residues on BabA through heavy-atom contact analysis, thereby defining antibody-recognition epitopes supported by complex-structure evidence. In addition, sequence-based, structure-based, and evolutionary conservation analyses were integrated to identify candidate functional epitope residues with high antigenicity, strong conservation, and surface-exposed features. On this basis, constrained de novo backbone generation was performed around the prioritized epitope regions, followed by amino acid sequence design and structural back-validation of the candidate binders. Candidate BabA-binder complexes were further evaluated using molecular docking, molecular dynamics simulations, and residue-level interface perturbation analysis to assess interface stability, epitope occupancy, and potential binding hotspots. This workflow enables systematic screening of BabA-targeting binders that may compete with antibody-recognized functional surfaces. Although these candidates still require experimental validation, this study provides a transferable computational framework for designing compact protein binders against pathogen adhesins by integrating experimentally resolved complex-structure resources with computational epitope prioritization based on sequence, conformation, and evolutionary conservation, and establishes a preliminary library of BabA candidate binders for subsequent validation and optimization.

bioengineering↗

bioRxiv2026

DOC Release and Physiological Response of Zostera marina Under Light and Nutrient Gradients

The seagrass bed, known as an important blue carbon ecosystem, not only has robust carbon sequestration capacity, but also releases the fixed organic carbon into the water column in the form of dissolved organic carbon (DOC). Zostera marina is the main constructive species of the seagrass meadows of northern China, but the regulatory mechanism of its DOC release in response to environmental changes still remains unclear. Adult Z. marina was used as the experimental material in this research to investigate the effects of light intensity and nutrient concentration on its DOC release, and to observe its physiological responses. By using a total organic carbon (TOC) analyzer, dissolved oxygen monitoring, transmission electron microscopy (TEM), and transcriptome analysis, we explored how light and nutrients affect DOC release and the underlying physiological mechanisms in Z. marina. The results showed that both elevated light intensity and short-term nutrient enrichment promoted organic carbon release from Z. marina to the environment. Increased light enhanced the net primary productivity (NPP) of Z. marina, while the magnitude of DOC release increased more than NPP itself. Nutrient enrichment reduced NPP while raising the proportion of DOC released by Z. marina. Transcriptome analysis showed that nutrient enrichment significantly affected pathways, including flavonoid biosynthesis and fatty acid degradation. This study demonstrated that changes in light and nutrients can significantly influence DOC release and carbon allocation patterns in Z. marina, providing a theoretical basis for blue carbon accounting and ecological restoration evaluation in seagrass beds.

plant biology↗

bioRxiv2026

A unified ensemble-allosteric framework reconciles gain- and loss-of-function disease mutations in the IP3 receptor

Missense mutations in multidomain signalling proteins often produce divergent functional phenotypes despite preserved structural integrity, posing a fundamental challenge for interpreting human genetic variation. This problem is exemplified by the type 1 inositol 1,4,5-trisphosphate receptor, IP3R1, the principal neuronal IP3-gated Ca2+ release channel and a recurrent locus of pathogenic variation in ITPR1-associated ataxias and neurodevelopmental disorders. Although disease mutations cluster within the N-terminal suppression domain (SD) and IP3-binding core (IBC), how neighbouring substitutions can drive either gain- or loss-of-function remains unresolved. Here, we establish a unified ensemble-allosteric framework for IP3R1 channelopathy by integrating mutational constraint analysis, ensemble structural modelling, adaptive molecular dynamics, Markov state modelling and dynamical network analysis. We show that pathogenic variants preferentially occupy a stability-preserving regime, perturbing local sequence-structure compatibility without inducing global structural collapse. Thus, disease arises not from loss of fold, but from corruption of the conformational and allosteric logic that links ligand recognition to channel gating. The IP3-binding pocket forms a discrete multistate ensemble whose populations, physicochemical properties and kinetic connectivity are selectively remodelled by mutation. The loss-of-function variant R269W disrupts a cationic IP3-coordinating site, enriches non-permissive binding-pocket states and diverts conformational exchange through indirect kinetic routes. By contrast, the gain-of-function variant R36C preserves local pocket competence but weakens suppressor-domain restraint by rerouting long-range communication through extended, less efficient allosteric pathways. These findings reconcile opposing disease phenotypes within a single mechanistic model, showing that pathogenic variation can be encoded in altered ensemble probabilities and information flow rather than in static structural lesions.

biophysics↗

bioRxiv2026

Analysis of multi-way chromatin interactions at sub-nucleosome resolution identifies synergistic nano-scale interactions within super-enhancers

In-depth understanding of the 3D organization of the genome and its role in the regulation of gene expression requires techniques to measure complex chromosome conformations at single alleles at high resolution. Here, we present multi-way Micro-Capture-C (mwMCC), a method to detect concurrent interactions between multiple chromatin regions at single alleles at sub-nucleosome resolution. mwMCC resolves the internal 3D structure of super-enhancers and identifies synergistic multi-way interactions between their constituent elements and gene promoters, providing a structural basis for cooperation within super-enhancers in nano-scale chromatin hubs. The dynamic formation and dissolution of these hubs during cellular differentiation correlates with up- and down-regulation of gene expression. Although large-scale chromatin hubs are dependent on the architectural protein CTCF, nano-scale hubs are robust to CTCF depletion. Instead, integration of footprinting analysis and protein occupancy data indicates a role for transcription factors and the co-activator Mediator in the formation of synergistic enhancer-promoter interactions within nano-scale chromatin hubs.

genomics↗

bioRxiv2026

The Vagus Nerve conducts viable translocation of gut flora to the lungs that impacts interstitial lung disease severity in mice

Communication between gut microbiota and extraintestinal organs is increasingly recognized, yet elucidation of relevant translocation mechanism(s) remains enigmatic. Vagus neuroanatomy and reports of vagal protein transfer to extraintestinal organs suggest that this "superhighway" could translocate bacteria. Here we explore whether the vagus superhighway can translocate bacteria to extraintestinal organs. Gavage of green fluorescent protein-expressing Escherichia coli (GFP-E. coli) into germ-free (GF) or specific-pathogen free (SPF) C57BL/6 mice yielded high bacillary loads in the stomach and lungs, followed by the heart, stool and peripheral muscles, despite negative blood cultures. Notably, confocal microscopy and culture revealed GFP-E. coli within the vagus nerve within five minutes of gavage suggesting rapid translocation. Metagenomic analysis of stool, lung, heart, vagus nerve, and muscle from non-gavaged SPF mice demonstrated significant microbial overlap, supporting that bacterial translocation occurs despite the presence of endogenous microflora. Remarkably, subdiaphragmatic vagotomy performed prior to GFP-E. coli gavage resulted in marked reductions of bacterial transduction in the lungs and other extraintestinal organs, except muscle. Furthermore, vagotomy significantly reduced lung fibrosis in SPF mice following intranasal bleomycin administration. In lung cancer patients undergoing lobectomy, vagotomy inhibited postsurgical reductions in forced vital capacity. These findings identify the vagus nerve as a literal gut-lung axis, facilitating viable bacterial translocation and influencing lung severity.

microbiology↗

bioRxiv2026

A weak-interaction model defines the cell-autonomous function of DNA methylation in gastrulation

DNA methylation is essential for mammalian embryonic development, yet its functional implications remain debated. Here, we introduce a quantitative model that reconciles conflicting perspectives on the roles of methylation in genome regulation and cell specification. Using single-cell multiome analysis in chimeric and whole embryo mutants during mouse gastrulation and organogenesis, we separate cell-autonomous from indirect effects of methylation and demethylation machinery. We show that while the transcriptional and chromatin programs defining basic lineages can be established independently of methylation, the fidelity of differentiated states is severely impaired in its absence. Specifically, we identify hundreds of genes and thousands of cis-regulatory elements (CREs) dependent on methylation for precise regulation. CRE accessibility alterations in methylation mutants are linked with CpG dinucleotide content, and correlate with multiple transcription factor binding motifs. Our data support a weak-interaction model in which DNA methylation moderates, but does not block or instruct the potency of trans-acting regulatory machineries genome-wide.

genomics↗

bioRxiv2026

ParSeek: Accurate cryo-EM particle picking with a deep learning model trained on synthetic data

Accurate particle picking from noisy cryo-EM micrographs is essential for high-resolution reconstruction. Current deep learning methods rely on manually annotated data, which is labor-intensive, subjective, and limits particle recall under low signal-to-noise ratio (SNR). Here we introduce ParSeek, an automated picker trained entirely on synthetic data without human annotation. Synthetic micrographs are generated by projecting known 3D structures into realistic background patches that reproduce experimental noise. On seven public cryo-EM datasets, ParSeek outperformed Topaz and CryoSegNet on four datasets, achieving the highest F1-score (up to 0.82) and reaching 0.63 on a challenging membrane protein dataset. Density maps from ParSeek-picked particles showed cross-correlation coefficients up to 0.995 with the reference and a minimal resolution difference of 0.1 [A]. ParSeek also overcame severe orientation bias on an influenza dataset, yielding a reasonable reconstruction. Applied to three experimental datasets (an antibody-antigen complex and two GPCRs), ParSeek enabled reconstructions at 5.0 [A], 4.0 [A], and 2.8 [A], respectively. The 2.8 [A] map resolved side-chain densities and ligand flexibility. This study establishes a fully synthetic-data-driven strategy that eliminates manual annotation for training cryo-EM deep-learning models, paving the way for automated, unbiased particle picking.

molecular biology↗

bioRxiv2026

Dynamic dorsal body morphology encodes engineering design principles of fish propulsion and hydrodynamics

Understanding how biological shape and movement interact with surrounding fluids represents a fundamental challenge at the intersection of biology, physics, and engineering. Fish locomotion exemplifies this challenge: body morphology and swimming kinematics together determine the hydrodynamic forces and flow structures that enable efficient propulsion and maneuverability. Whereas biologists have long sought to connect morphological variation to swimming performance, traditional morphometric approaches provide limited insight into the fluid mechanical consequences of shape differences. Similarly, although computational fluid dynamics can reveal detailed flow physics, simulating hydrodynamics across diverse and dynamic morphologies remains prohibitively expensive for systematic investigation. To bridge this gap, we introduce a data-driven framework that connects fish body shape dynamics to hydro-dynamic performance through compact morphospace parameterization and reduced-order modeling. Using CFD simulations of 15 fish species from the Digital Life Project database (www.digitallife3d.org/3d-model), we generate hydrodynamic datasets capturing the shape-flow relationship. Principal Component Analysis (PCA) extracts four dominant shape parameters from dorsal body profiles, which are then integrated into an Inverse-Design with Dynamic Mode Decomposition (ID-DMD) framework to model the resulting fluid dynamics. The resulting modal analysis suggests that locomotion strategies emerge from specific shape-flow interactions. We further demonstrate the frameworks utility through single- and multi-objective shape optimization, showing how it enables efficient exploration of the morphology-hydrodynamics relationship. This approach offers a novel analysis and design tool for understanding how biological form and motion interact with fluid mechanics, with applications ranging from bio-inspired vehicle development to evolutionary biomechanics.

biophysics↗

bioRxiv2026

Neuromodulation of Foxp2+ hypothalamic neurons induces therapeutic hypothermia

The inability to selectively trigger therapeutic hypothermia independent of environmental cooling has hindered causal analysis of its broader physiological benefits. Here, we employed P57, a natural product that pharmacologically induces therapeutic hypothermia circumventing external cold stress, to identify the neuronal substrates underlying hypothermia-induced antitumor effects. Integrating functional ultrasound imaging, activity-dependent neuronal labeling, and single-nucleus RNA sequencing, we identify a previously unrecognized population of Foxp2 neurons in the medial preoptic area (MPA) that are selectively activated by P57. Inhibition of MPA Foxp2+ neurons abolishes P57-induced hypothermia, whereas the paraventricular hypothalamus (PVH) serves as a critical downstream node. Importantly, targeted activation of MPA Foxp2 neurons is sufficient to induce sustained hypothermia, suppress systemic metabolism, and inhibit tumor growth, providing causal evidence that neuronally driven reductions in core body temperature can exert antitumor effects. Together, these findings establish MPA Foxp2 neurons as a controllable node for therapeutic hypothermia induction and demonstrate that neuromodulation of defined neuronal populations can achieve therapeutic benefit by directly controlling physiological states.

neuroscience↗

bioRxiv2026

Identification of functional non-coding variants affecting Alzheimer's disease risk by Massively Parallel Reporter Assay

The majority of genetic risk variants for late-onset Alzheimers disease (LOAD) reside within non-coding genomic regions, suggesting they exert pathogenic effects by disrupting transcriptional regulatory programs. To systematically identify functional variants, we performed an unbiased, high-throughput Massively Parallel Reporter Assay (MPRA) in the THP-1 human monocytic cell line, screening 2,231 SNPs across 24 LOAD GWAS loci. We identified 62 variants exhibiting significant allele-specific transcriptional regulatory output, including rs636317 in the MS4A locus. The risk allele of rs636317 disrupts a CTCF binding motif, altering fine-scale chromatin looping. To validate these findings, we employed CRISPR/Cas9 to generate an allele-specific deletion of the rs636317 T allele in H9 human embryonic stem cells. Monocytes differentiated from these edited cells displayed increased expression of MS4A4E, MS4A6A, and TREM2, along with highly elevated levels of soluble TREM2 (sTREM2). These results provide a mechanistic link between a non-coding genetic variant, transcriptional regulation of the MS4A family, and TREM2-mediated immune responses in Alzheimers disease pathogenesis.

genetics↗

bioRxiv2026

Structure-guided, physics-aware reconstruction expands scan-limited multiphoton imaging

Multiphoton microscopy is increasingly pushed toward deep, large-scale and fast functional imaging, where acquisition speed has become a bottleneck. Here we present SPARC, a structure-guided, physics-aware reconstruction framework for scan-limited multiphoton imaging. Rather than treating undersampled recovery as generic super-resolution, SPARC formulates it as a constrained reconstruction problem tailored to point-scanning microscopy by incorporating a sample-matched structural reference from the same field of view and the anisotropic acquisition physics of scan-limited imaging. SPARC jointly integrates denoising and deep upsampling, enabling stable recovery from noisy sparse measurements. In simulated calcium imaging with ground truth, SPARC improved spatial reconstruction fidelity and temporal signal recovery relative to existing methods. In vivo, SPARC improved temporal readout in three-photon and mesoscale two-photon calcium imaging, and enabled a more temporally informative 400-Hz voltage readout on a standard resonant-galvo two-photon microscope. These results suggest SPARC expands the functional operating range of existing multiphoton microscopes under scan-limited conditions.

neuroscience↗

bioRxiv2026

A Context-Aware Target Engagement and Pharmacodynamic Biomarker Resource to Accelerate Drug Discovery and Development

Confirming target engagement in tumor experimental models remains a major challenge in oncology drug development. Pharmacodynamic biomarkers can help address this, but few systematic resources link drug targets to candidate biomarkers. We developed TargetTrace, a comprehensive resource to identify and prioritize pharmacodynamic biomarkers across nine key target classes, including transcription factors/cofactors, kinases, phosphatases, ubiquitin ligases, deubiquitinases, acetyltransferases, deacetylases, methyltransferases, and demethylases. Biomarker candidates were gathered from curated molecular interaction resources and refined using external annotations to improve accuracy. For enzyme targets with measurable substrate changes, we applied a two-agent large language model workflow, followed by manual review, to harmonize antibody information from the antibody resources and ensure that the selected biomarkers are measurable with existing laboratory tests. From more than 92,000 input interactions and over 2,300 targets, we compiled 71,323 target-biomarker relationships involving 2,270 potential drug targets, encompassing both transcription factor/cofactor-target gene and enzyme-substrate interactions. Commercial antibodies were available for over 1,400 biomarkers, supporting laboratory validation. This resource provides a structured and reusable resource for systematic identification and prioritization of pharmacodynamic biomarkers in oncology.

bioinformatics↗

bioRxiv2026

Foundation cell segmentation models performance on live microscopy and spatial-omics data

Accurate cell segmentation is an essential step for quantitative analysis of biological imaging data. Recent advances in deep learning have led to the development of generalist segmentation models that perform robustly across multiple imaging modalities, including label-free phase contrast, fluorescence cell culture, and multiplexed fluorescence tissue imaging. However, systematic comparisons of these models at the level of downstream biological analysis remain limited. To address this gap, we evaluated several recent segmentation models, including Cellpose cyto3, Cellpose-SAM, {micro}SAM, and CellSAM, on phase contrast and fluorescence cell culture images. In addition, Mesmer and InstanSeg were included for benchmarking on multiplexed fluorescence tissue images generated using CO-Detection by IndEXing (CODEX). We found that Cellpose-SAM achieved strong performance on phase contrast images, while SAM-based models consistently performed well on fluorescence cell culture data. In contrast, no single model consistently outperformed others on CODEX datasets. Instead, each model exhibited distinct strengths and limitations, which led to differences in downstream analyses, including clustering and cell type identification. Together, our study emphasizes the importance of selecting segmentation models based on dataset characteristics and analytical goals, rather than relying on a single universal approach.

bioinformatics↗

bioRxiv2026

cryoAgent: An agentic workflow for robust and adaptive end-to-end cryo-EM image processing

Cryo-electron microscopy (cryo-EM) is the mainstream method for structure determination, yet current automated workflows remain rigid and require expert intervention for failure recovery, heterogeneity analysis, and optimization. We present cryoAgent, an agentic workflow for autonomous cryo-EM image processing with adaptive tool use to address these challenges. cryoAgent improves reconstruction quality across diverse datasets, identifies a previously unreported structural state, and outperforms state-of-the-art automated workflows, advancing scalable and discovery-oriented structural biology.

biophysics↗

bioRxiv2026

Active Surveillance Reveals a Systemic Pro-Resolving Th2 Immune Program Linked to 1 Desmoid Tumor Regression

Desmoid fibromatosis (DF) is a rare mesenchymal neoplasm with an unpredictable clinical course, where spontaneous regression or progression occurs in a significant subset of patients through largely undefined mechanisms. The use of active surveillance (AS) offers the opportunity to investigate whether tumor- or host-driven systemic and local immune features may explain these divergent outcomes, improving patient management. A prospective observational study enrolled 55 patients with primary sporadic DF managed with AS. Clinical evolution was categorized as progression, regression, or stable disease according to RECIST 1.1. Immunomonitoring with multicolor flow cytometry identified distinct systemic T-helper polarization states stratifying clinical trajectories: regressors showed a Th2-skewed profile, while progressors displayed activated T-helper cells and Th1/Th9/Th17 subsets. Higher baseline Th2 levels associated with regression and longer progression-free survival. Plasma proteomic and whole-blood transcriptomic analyses confirmed coordinated IL-4/IL-13-linked pro-resolving programs in regressors and inflammatory, early T-cell activation signatures in progressors. Tumor transcriptomics revealed adaptive, antigen-presentation and restrained immune programs in regressing lesions versus innate inflammatory, interferon and TGF-{beta}-driven fibrotic pathways in progressing tumors. These findings identify systemic T-helper polarization as a biomarker of DF behavior and highlight coordinated systemic-tumoral immune programs underlying clinical outcomes, supporting more precise clinical management.

immunology↗

bioRxiv2026

A NOVEL MITOCHONDRIAL PEPTIDE ESSENTIAL FOR RESPIRATORY CAPACITY PROMOTES GROWTH, YIELD AND ABIOTIC STRESS TOLERANCE IN PLANTS

Efforts to boost crop productivity have focused on improving photosynthesis. However, plant respiration consumes over 90% of fixed carbon, fueling growth, stress responses, and resource acquisition. Despite its metabolic centrality, respiratory regulation remains underexplored as a yield target. Here, we identify AtMLSP1 (At4g17085), a 57-amino-acid mitochondrial inner membrane peptide in Arabidopsis thaliana. Loss-of-function atmlsp1 mutants show impaired growth, while AtMLSP1 overexpression boosts biomass, seed yield, and high light tolerance. No induction of alternative oxidase protein abundance or activity was observed in atmlsp1 plants, a response normally triggered by respiratory perturbation. Mitochondria isolated from atmlsp1 lines had an approximately 90% reduction in the amount of the intermembrane space protein Cytochrome c and a 30% reduction in all subunits of complex III, while other respiratory complexes remain unaffected. As expected, loss-of-function plants atmlsp1 reveal a significant decrease in total respiratory capacity and membrane potential, but mitochondrial integrity, and abundance of complex I, II and complex IV were unchanged. Overexpression of the orthologues of this gene in Oryza sativa (rice) and Glycine max (soybean) results in a significant increases in yield (seed number and size) under field conditions across different locations.

plant biology↗

bioRxiv2026

iCNG99: a validated genome-scale metabolic model of Cryptococcus neoformans strain H99

Cryptococcus neoformans is a ubiquitous environmental fungus that can also cause life-threatening infections in immunocompromised individuals. As a competent pathogen, Cryptococcus needs to reprogram its metabolism to adapt to the drastic differences between environmental niches and host niches. A well-curated genome-scale metabolic model (GEM) is a powerful tool to facilitate the investigation of the metabolic resilience of an organism. Here we reconstructed and validated iCNG99, a GEM for C. neoformans reference strain H99, and evaluated its predictive performance across 43 growth conditions and gene essentiality benchmarks. The model achieved high confidence essential gene prediction (precision = 0.77) and recapitulated pathways targeted by clinically available antifungals. Integration with transcriptomic and metabolomic data enabled iCNG99 to capture condition-specific metabolic adaptations and to identify candidate vulnerabilities in drug tolerance, revealing metabolic adaptations associated with survival within host conditions and drug susceptibility. Together, iCNG99 provides a systems-level computational platform for investigating C. neoformans metabolism and for prioritizing antifungal vulnerabilities.

systems biology↗