Biology subjects

Han, D.

Publications and source records attributed to Han, D..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Differential transcriptomics and metabolomics analyses of the skin of coarse and fine Liaoning cashmere goats

Secondary follicles in cashmere goats determine cashmere yield and quality. The present study investigated the relationship between the regulatory factors and cashmere fiber diameter through transcriptomics and metabolomics methods. Diameters of the fibers of 400 (18 months old) female Liaoning cashmere goats were measured and categorized into coarse and fine hair types (200 goats per category). Six goats were selected as representatives of each group for further analysis. Fiber diameters were significantly different between groups (P < 0.05). Transcriptomic analysis revealed 211 differentially expressed genes between groups, including FGF18, KRT36, KRT79, AWAT2, and MOGAT1, which were enriched in the PPAR and glycerol-lipid metabolism signaling pathways that regulate hair follicle growth and sebum secretion. Metabolomics analysis revealed 50 differentially expressed metabolites in the skin, which regulate cellular ion channels and participate in neurological channels by enriching ABC transporter protein pathways, amino acid biosynthesis and metabolism, and arachidonic acid metabolism. The findings of the present study could facilitate improvement of cashmere quality in cashmere goats.

genetics↗

bioRxiv2025

Light-up nanostructures with allosteric DNA mimics of GFP

In this study, we present a systematic approach for the rational design of synthetic allosteric DNA aptamers. This methodology enables precise control over the allosteric ON-OFF transition in fluorescent DNA aptamers, allowing for the engineering of aptamers with highly tunable fluorescent properties. When combined with toehold-mediated strand displacement, we have developed a series of allosteric aptamers in which the target sequence functions as a specific allosteric modulator. Furthermore, these aptamers have been applied in synthetic DNA computing and in the construction of responsive nanostructures that light up upon activation.

synthetic biology↗

bioRxiv2025

Regularized Deep Neural Networks for Combining Heterogeneous Features of Peptides in Data Independent Acquisition Mass Spectrometry

AbstractData-independent acquisition (DIA) has gained much attention in mass spectrometry (MS)-based proteomics for its improved reproducibility and unbiased data acquisition. In DIA-MS, the spectral library is crucial in peptide identification. However, this method is limited to peptides previously identified via data-dependent acquisition (DDA) MS experiments. This study proposes a deep learning approach for generating spectral libraries, even for previously unseen peptides. While most deep learning-based methods rely on one-hot encoding representation for peptides, the proposed method incorporates physicochemical features, including atomic composition, hydrophobicity, flexibility, fractional surface probability, and aromaticity. We introduce sparsity regu-larized neural network layers to facilitate the selection and combination of important high-dimensional physicochemical features and improve prediction performance. Fur-thermore, we suggest a transfer learning strategy for training the proposed deep neural networks having multiple heterogeneous input channels. Numerical experiments using benchmark DDA-MS data demonstrated that the proposed deep learning model out-performed existing benchmark models, such as Prosit and DeepDIA, particularly in predicting retention times. And it was demonstrated that the proposed models with sparsity regularization identified more peptides from HeLa cell DIA data compared to the other deep learning models.

bioinformatics↗

bioRxiv2025

ReCellTy: Domain-specific knowledge graph retrieval-augmented LLMs workflow for single-cell annotation

To enable precise and fully automated cell type annotation with large language models (LLMs), we developed a graph-structured feature-marker database to retrieve entities linked to differential genes for cell reconstruction. We further designed a multi-task workflow to optimize the annotation process. Compared to general-purpose LLMs, our method improves human evaluation scores by up to 0.21 and semantic similarity by 6.1% across 11 tissue types, while more closely aligning with the cognitive logic of manual annotation.

bioinformatics↗

bioRxiv2025

Enzyme Co-Scientist: Harnessing Large Language Models for Enzyme Kinetic Data Extraction from Literature

The extraction of molecular annotations from scientific literature is critical for advancing data-driven research. However, traditional methods, which primarily rely on human curation, are labor-intensive and error-prone. Here, we present an LLM-based agentic workflow that enables automatic and efficient data extraction from literature with high accuracy. As a demonstration, our workflow successfully delivers a dataset containing over 91,000 enzyme kinetics entries from around 3,500 papers. It achieves an average F1 score above 0.9 on expert-annotated subsets of protein enzymes and can be extended to the ribozyme domain in fewer than 3 days at less than $90. This method opens up new avenues for accelerating the pace of scientific research.

biochemistry↗

bioRxiv2025

Oral dosing of the nucleoside analog obeldesivir is efficacious against RSV infection in African green monkeys

Respiratory syncytial virus (RSV) is a significant cause of morbidity and mortality in high-risk populations. Although prophylactic options are available, there are no effective oral therapeutics for RSV infection. Obeldesivir (ODV) is an orally bioavailable prodrug of the nucleoside analog GS-441524, which is converted intracellularly to its active nucleoside triphosphate and inhibits the RSV RNA polymerase. Here we report the potent antiviral activity of ODV against geographically and temporally diverse RSV A and B clinical isolates (EC50: 0.20-0.66 M). Resistance selection studies with ODV and GS-441524 against RSV identified a single amino acid substitution, I777L, in the L polymerase with reduced susceptibility (3.3-3.8-fold) to ODV and GS-441524, indicating a high barrier for resistance development. In an African green monkey RSV infection model, once-daily oral ODV doses of 30 or 90 mg/kg initiated [~]24 hours post-infection significantly reduced log10 viral RNA copies/mLxday area under the curve by 69-92% in the upper and lower respiratory tracts. Together, these preclinical data support the clinical evaluation of ODV for the treatment of RSV infection.

microbiology↗

bioRxiv2025

Mechanical impact on neural stem cell lineage decisions in human brain organoids

During neurodevelopment neural stem cells give rise to a spatially patterned tissue in which a regionally differentially regulated balance between proliferation and differentiation produces the fine-tuned number of neurons and macroglia necessary for a functional central nervous system. The cells driving these highly intricated developmental processes of patterning, growth and differentiation are constantly exposed to a mechanical environment that is however variable between different brain regions and along differentiation trajectories. Here we demonstrate that both, acute mechanical manipulations as well as a persistent change in the mechanical environment provided to human brain organoids, instruct neural stem cell lineage decisions. Furthermore, we dissect the underlying changes in the molecular program of organoid-resident cells by bulk- and single cell RNA-sequencing and reveal that mechanical manipulations impact on molecular programs governing early patterning events as well as cell-type specifically alter cellular metabolism. Thus, our results unravel a regulatory network linking mechanics and neural stem cell lineage decisions.

neuroscience↗

bioRxiv2024

Increased cerebrospinal fluid and plasma apoE glycosylation is associated with reduced levels of Alzheimer's disease biomarkers

The apolipoprotein E (APOE) {varepsilon}4 allele is the strongest genetic risk factor for Alzheimers disease (AD). ApoE is glycosylated with an O-linked Core-1 sialylated glycan at several sites, yet the impact and function of this glycosylation on AD biomarkers remains unclear. We examined apoE glycosylation in a cohort of cerebrospinal fluid (CSF, n=181) and plasma (n= 178) samples from the Alzheimers Disease Neuroimaging Initiative (ADNI) stratified into 4 groups: cognitively normal (CN), Mild Cognitive Impairment (MCI), progressors and non-progressors based on delayed word recall performance over 4 years. We observed decreasing glycosylation from apoE2 > apoE3 > apoE4 in CSF, and in plasma (apoE3 > apoE4). ApoE glycosylation was reduced in the MCI compared with CN groups, and in progressors compared to non-progressors. In CSF, higher apoE glycosylation associated cross-sectionally with lower total tau (t-tau), p-tau181, and with higher A{beta}1-42. Similar associations of apoE glycosylation with higher A{beta}1-42 were observed in plasma. In CSF, greater apoE4 glycosylation was associated with lower t-tau and p-tau181. Over a 6-year period, higher baseline levels of CSF apoE glycosylation predicted lower rates of increase in CSF t-tau and p-tau181 and lower rates of decrease in CSF A{beta}1-42. These results indicate strong associations of apoE glycosylation with biomarkers of AD pathology independent of apoE genotype, warranting a deeper understanding of the functional role of apoE glycosylation on AD tau pathology.

neuroscience↗

bioRxiv2024

Magnetically induced magnetosome chain (MAGiC):A biogenic magnetic-particle-imaging tracer with high performance and navigability

Magnetic particle imaging (MPI) enables real-time, sensitive and quantitative visualization of magnetic tracers spatial distribution, augmenting the capability of in vivo imaging technologies. Previous tracer studies in MPI have primarily focused on superparamagnetic nanoparticles; however, their non-ideal sigmoidal magnetization response limits the spatial resolution. Here we demonstrate the utilization of magnetically induced magnetosome chain (MAGiC) as a novel superferromagnetic MPI tracer, exhibiting a 25-fold improvement in resolution and a 91-fold enhancement in signal intensity compared to the commercial tracer VivoTrax+. The spatial resolution of MPI was pushed to an unprecedented 80 m under a 4 T/m gradient field. Additionally, MAGiC can be precisely controlled using magnetic fields, enabling it to function as a MPI trackable microrobot. We provided a theoretical model elucidating MAGiCs unique properties, and validated its imaging and actuation performance through phantom studies and in vivo experiments. As a high-performance MPI tracer and magnetic microrobot with exceptional capabilities, MAGiC holds tremendous potential for diverse applications including cell tracking, targeted drug delivery as well as therapeutic interventions.

bioengineering↗

bioRxiv2024

Long-term Immunity of a Microneedle Array Patch of SARS-CoV-2 S1 Protein Subunit Vaccine Irradiated by Gamma Rays in Mice

COVID-19 vaccines effectively prevent symptomatic infection and severe disease, including hospitalization and death. However, unequal vaccine distribution during the pandemic, especially in low- and middle-income countries, has led to the emergence of vaccine-resistant strains. This underscores the need for alternative, safe, and thermostable vaccine platforms, such as dissolved microneedle array patches (MAP) delivering a subunit vaccine, which eliminate the need for cold chain and trained healthcare personnel. This study demonstrates that the SARS-CoV-2 S1 monomer with RS09, a TLR-4 agonist peptide, serves as an optimal protein subunit immunogen. This combination stimulates a stronger S1-specific immune response, resulting in binding to the membrane-bound spike on the cell surface and ACE2-binding inhibition, compared to the monomer S1 alone or trimer S1, regardless of RS09. MAP delivery of the rS1RS09 subunit vaccine elicited higher and longer-lasting immunity compared to conventional intramuscular injection. S1-specific IgG levels remained significantly elevated for up to 70 weeks post-administration. Additionally, different doses of 5, 15, and 45 g of MAP vaccines induced robust and sustained Th2-prevalent immune responses, suggesting a dose-sparing effect and inducing significantly high neutralizing antibodies against the Wuhan, Delta, and Omicron variants at 15 and 45 g dose. Moreover, gamma irradiation as a terminal sterilization method did not significantly affect immunogenicity, with irradiated vaccines maintaining comparable efficacy to non-irradiated ones. The stability of MAP vaccines was evaluated after long-term storage at room temperature and refrigeration for 19 months, showing minimal protein degradation. Further, after an additional one-month of storage at elevated temperature (42{degrees}C), rS1RS09 in both non-irradiated and irradiated MAP degraded less than 3%, while the liquid subunit vaccine degraded over 23%. Overall, these results indicate that gamma irradiation sterilized MAP-rS1RS09 vaccines maintain stability during extended storage without refrigeration, supporting their potential for mass production and widespread use in global vaccination efforts.

microbiology↗

bioRxiv2024

Voluntary Exercise Attenuates Tumor Growth in a Preclinical Model of Castration-Resistant Prostate Cancer

PurposeTo examine the effects of voluntary exercise training on tumor growth and explore the underlying intratumoral molecular pathways and processes responsible for the beneficial effects of VWR on tumor initiation and progression in a mouse model of Castration-Resistant Prostate Cancer (CRPC). MethodsMale immunodeficient mice (SCID) were castrated and subcutaneously inoculated with human CWR-22RV1 cancer cells to construct CRPC xenograft model before randomly assigned to either voluntary wheel running (VWR) or sedentary (SED) group (n=6/group). After three weeks, tumor tissues were collected. Tumor size was measured and calculated. mRNA expression of markers of DNA replication, Androgen Receptor (AR) signaling, and mitochondrial dynamics was determined by RT-PCR. Protein expression of mitochondrial content and dynamics was determined by western blotting. Finally, RNA-sequencing analysis was performed in the tumor tissues. ResultsVoluntary wheel running resulted in smaller tumor volume at the initial stage and attenuated tumor progression throughout the time course (P < 0.05). The reduction of tumor volume in VWR group was coincided with lower mRNA expression of DNA replication markers (MCM2, MCM6, and MCM7), AR signaling (ELOVL5 and FKBP5) and regulatory proteins of mitochondrial fission (Drp1 and Fis1) and fusion (MFN1 and OPA1) when compared to the SED group (P<0.05). More importantly, RNA sequencing data further revealed that pathways related to pathways related to angiogenesis, extracellular matrix formation and endothelial cell proliferation were downregulated. ConclusionsThree weeks of VWR was effective in delaying tumor initiation and progression, which coincided with reduced transcription of DNA replication, AR signaling targets and mitochondrial dynamics. We further identified reduced molecular pathways/processes related to angiogenesis that may be responsible for the delayed tumor initiation and progression by VWR.

cancer biology↗

bioRxiv2024

An explainable map of human gastruloid morphospace reveals gastrulation failure modes and predicts teratogens

Human gastrulation is a critical stage of development where many pregnancies fail due to poorly understood mechanisms. Using the 2D gastruloid, a stem cell model of human gastrulation, we combined high-throughput drug perturbations and mathematical modelling to create an explainable map of gastruloid morphospace. This map outlines patterning outcomes in response to diverse perturbations and identifies variations in canonical patterning and failure modes. We modeled morphogen dynamics to embed simulated gastruloids into experimentally-determined morphospace to explain how developmental parameters drive patterning. Our model predicted and validated the two greatest sources of patterning variance: cell density-based modulations in Wnt signaling and SOX2 stability. Assigning these parameters as axes of morphospace imparted interpretability. To demonstrate its utility, we predicted novel teratogens that we validated in zebrafish. Overall, we show how stem cell models of development can be used to build a comprehensive and interpretable understanding of the set of developmental outcomes.

developmental biology↗

bioRxiv2024

Wheat TaNADPO promotes spot blotch resistance

Bipolaris sorokiniana is a common soil-borne fungal pathogen that can infect various organs of wheat (Triticum aestivum L.), causing diseases such as spot blotch, common root rot, head blight, and black point. The genetic basis of wheat resistance to B. sorokiniana is not yet fully understood. In this study, a natural population of 1,302 global common wheat germplasms was established and inoculated with B. sorokiniana at the seedling stage in a greenhouse. Resistance to spot blotch was assessed, revealing that only about 3.8% of the germplasms exhibited moderate or higher resistance levels. A genome-wide association study (GWAS) using high-density 660K single nucleotide polymorphism (SNP) data identified a region on chromosome 1BL (621.2-674.0 Mb) with 9 SNPs significantly associated (p < 10e-4) with spot blotch resistance, designated as Qsb.hebau-1BL. RNA sequencing and qRT-PCR assays showed that the gene TraesCS1B02G410300, encoding nicotinamide-adenine dinucleotide phosphate-binding oxidoreductase (TaNADPO), was significantly induced by B. sorokiniana. Five SNP variations were found in the promoter region of TaNADPO in wheat lines with or without Qsb.hebau-1BL. Transient expression of TaNADPO in Nicotiana benthamiana leaves showed a cytoplasmic subcellular localization of the fusion protein with a green fluorescent protein (GFP) tag. Wheat transgenic lines overexpressing TaNADPO exhibited significantly enhanced resistance to spot blotch compared to wildtype plants, with higher accumulation of reactive oxygen species (ROS). The knockout EMS mutant of Triticum turgidum NADPO (tdnadpo-K2561, Gln125*) showed significantly reduced resistance to spot blotch and lower ROS accumulation compared to wildtype plants. In summary, TaNADPO has been identified as a crucial gene for resistance to B. sorokiniana, providing valuable insights for developing spot blotch-resistant wheat varieties through molecular breeding techniques.

genetics↗

bioRxiv2024

Ultra-resolution Deconvolution of Spatial Transcriptomics Unveils Spatiotemporal Cellular Dynamics in Complex Microenvironments

Immune cells infiltrate tissues in response to exogenous pathogens or spontaneous tumors, generating protective immunity to safeguard tissues. Despite advancements in spatial transcriptomics (ST), the precise spatial distribution and functional specialization of immune cells within tissue microenvironments remain elusive. Here, we introduce an ultra-precision ST deconvolution algorithm (UCASpatial) that enhances the mapping of cell subpopulations to spatial locations by leveraging the contribution of genes indicative of cell identity through entropy-based weighting. Using both in silico and real ST datasets, we demonstrate that UCASpatial improves the robustness and accuracy in identifying low-abundant cell subpopulations and distinguishing transcriptionally heterogeneous cell subpopulations. Applying UCASpatial to human colorectal cancer (CRC), we link genomic alterations in individual cancer clones to multi-cellular characteristics of the tumor immune microenvironment (TIME) and reveal the co-evolution of tumor cells and TIME at a clonal resolution. We show that the copy number gain on chromosome 20q (chr20q-gain) in tumor cells orchestrates a T cell-excluded TIME, indicative of resistance to immunotherapy in CRC, and is associated with tumor-intrinsic human endogenous retrovirus subfamily H (HERV-H) silencing and impaired type I interferon response. In murine wound healing models, we illuminate the spatiotemporal dynamics of individual cell subsets across various stages of the healing process. We discovered that the scarring-healing mice (C57BL/6) exhibited a replacement of Prg4+ chondrogenic progenitors to Igfbp5+ chondrocytes in the wound bed at the regeneration stage, a change not observed in the regenerative strain (MRL/MpJ). The Igfbp5+ chondrocyte, spatially coordinating with Cd36+ Gpnmb+ Il1b- macrophage and Fmod+ fibroblast, forms a pro-fibrotic community associated with regeneration failure. The cell-cell interactions within this three-cell cluster, mediated by the IL11-IL11RA axis, drive the pro-fibrotic community formation and limit regeneration in C57BL/6 mice. Our findings present UCASpatial as a versatile tool for deciphering fine-grained cellular landscapes in ST and exploring intercellular mechanisms in complex and dynamic microenvironments.

bioinformatics↗

bioRxiv2024

siRNADesign: A Graph Neural Network for siRNA Efficacy Prediction via Deep RNA Sequence Analysis

The clinical adoption of small interfering RNAs (siRNAs) has prompted the development of various computational strategies for siRNA design, from traditional data analysis to advanced machine learning techniques. However, previous studies have inadequately considered the full complexity of the siRNA silencing mechanism, neglecting critical elements such as siRNA positioning on mRNA, RNA base-pairing probabilities, and RNA-AGO2 interactions, thereby limiting the insight and accuracy of existing models. Here, we introduce siRNADesign, a Graph Neural Network (GNN) framework that leverages both non-empirical and empirical rules-based features of siRNA and mRNA to effectively capture the complex dynamics of gene silencing. In multiple internal datasets, siRNADesign achieves state-of-the-art performance. Significantly, siRNADesign also outperforms existing methodologies in in vitro wet lab experiments and an externally validated dataset. Additionally, we develop a new data-splitting methodology that addresses the data leakage issue, a frequently overlooked issue in previous studies, ensuring the robustness and stability of our model under various experimental settings. Through rigorous testing, siRNADesign has demonstrated remarkable predictive accuracy and robustness, making significant contributions to the field of gene silencing. Furthermore, our approach in redefining data-splitting standards aims to set new benchmarks for future research in the domain of predictive biological modeling for siRNA.

bioinformatics↗

bioRxiv2024

Telomere-to-telomere genome assembly of a male goat reveals novel variants associated with cashmere traits

A complete goat (Capra hircus) reference genome enhances analyses of genetic variation, thus providing novel insights into domestication and selection in goats and related species. Here, we assembled a telomere-to-telomere (T2T) gap-free genome (2.86 Gb) from a cashmere goat (T2T-goat1.0), which included a Y chromosome of 20.9 Mb. With a base accuracy of >99.999%, T2T-goat1.0 corrected numerous genome-wide structural and base errors in previous assemblies and added 288.5 Mb of previously unresolved regions (PURs) and 446 newly assembled genes to the reference genome. We sequenced the genomes of five representative goat breeds for PacBio reads, and used T2T-goat1.0 as a reference to identify a total of 63,417 structural variations (SVs) with up to 4711 SVs (7.41%) in the PURs and 507 overlapping genes significantly enriched (Padj. < 0.05) in the keratin filament pathway. T2T-goat1.0 was applied in population analyses of global wild and domestic goats, which revealed 32,419 SVs and 25,397,794 SNPs, including 870 SVs and 545,026 SNPs in the PURs. Also, our analyses revealed a set of novel selective variants and genes associated with domestication (e.g., NKG2D and ABCC4) and cashmere traits (e.g., ABCC4 and ASIP).

genomics↗

bioRxiv2023

Fourth dose of Microneedle Array Patch of SARS-CoV-2 S1 Protein Subunit Vaccine Elicits Robust Long-lasting Humoral Responses in mice

The COVID-19 pandemic has underscored the pressing need for safe and effective booster vaccines, particularly in considering the emergence of new SARS-CoV-2 variants and addressing vaccine distribution inequalities. Dissolving microneedle array patches (MAP) offer a promising delivery method, enhancing immunogenicity and improving accessibility through the skins immune potential. In this study, we evaluated a microneedle array patch-based S1 subunit protein COVID-19 vaccine candidate, which comprised a bivalent formulation targeting the Wuhan and Beta variant alongside a monovalent Delta variant spike proteins in a murine model. Notably, the second boost of homologous bivalent MAP-S1(WU+Beta) induced a 15.7-fold increase in IgG endpoint titer, while the third boost of heterologous MAP-S1RS09Delta yielded a more modest 1.6-fold increase. Importantly, this study demonstrated that the administration of four doses of the MAP vaccine induced robust and long-lasting immune responses, persisting for at least 80 weeks. These immune responses encompassed various IgG isotypes and remained statistically significant for one year. Furthermore, neutralizing antibodies against multiple SARS-CoV-2 variants were generated, with comparable responses observed against the Omicron variant. Overall, these findings emphasize the potential of MAP-based vaccines as a promising strategy to combat the evolving landscape of COVID-19 and to deliver a safe and effective booster vaccine worldwide.

immunology↗

bioRxiv2023

Generalizing deep variant callers via domain adaptation and semi-supervised learning

Deep learning-based variant callers (DVCs) offer state-of-the-art perfor-mance in small variant detection from DNA sequencing data. However, their reliance on supervised learning and the subsequent need for exten-sive labeled data pose a potential hurdle to their generalizability across diverse sequencing methods with varying error profiles. Indeed, even minor discrepancies in error profiles can compromise the robustness of DVCs and impair the variant calling accuracy in the target sequencing method. To mitigate these challenges, we propose RUN-DVC, the first semi-supervised training approach for DVCs that presents two complemen-tary training techniques to the conventional supervised training approach. RUN-DVC leverages semi-supervised learning techniques to learn error profiles from unlabeled datasets of the target sequencing method as well as a domain adaptation technique to aid semi-supervised learning by reducing the domain discrepancy due to different error profiles. We ana-lyze and contrast RUN-DVC against the supervised training approach under various generalization scenarios using nine sequencing methods from Illumina, BGI, PacBio, and Oxford Nanopore sequencing platforms. Remarkably, RUN-DVC significantly improves the variant calling accu-racy of DVC in the target sequencing method even with purely unlabeled datasets in the target domain and enables label-efficient generalization when partially labeled datasets are available. Our results suggest RUN-DVC is a promising semi-supervised training method for DVCs with the potential to broaden the use of DVC across diverse sequencing methods.

bioinformatics↗