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Xu, Y.

Publications and source records attributed to Xu, Y..

At least 343 records · Page 19Linked to original sources
bioRxiv2024

Unveiling Cell Wall Structure and Echinocandin Response in Candida auris and Candida albicans via Solid-State NMR

Invasive candidiasis affects 1.6 million people annually, implicating high mortality and morbidity in immunocompromised and hospitalized patients. Echinocandins, inhibitors of {beta}-1,3-glucan synthesis, are used as a first-line treatment; however, their efficacy is increasingly compromised by resistance and tolerance. To understand how echinocandins remodel Candida cell wall structures, thereby reducing drug effectiveness, this study compares the effects of echinocandin exposure on the cell walls of the prevalent pathogen Candida albicans and the recently emerged multidrug-resistant superbug Candida auris. High-resolution solid-state NMR analysis revealed a conserved cell wall structure in both species, with a rigid inner layer composed of closely associated chitin microfibrils and {beta}-1,3-glucans, supported by a flexible network of {beta}-1,6-glucans and additional {beta}-1,3-glucans. Despite the presence of N-mannan fibrils in the outer layer, mannan components are mobile and rely on -1,2-linked mannoside sidechains to maintain contact with chitin and {beta}-1,3-glucans. Caspofungin treatment rigidifies certain mannan sidechains and {beta}-1, 6-glucans to reinforce the cell wall in response to the depletion of most {beta}-1,3-glucans. While caspofungin treatment reduced water permeability in both species, only C. albicans responded by inducing cell wall thickening and changes in chitin and {beta}-1,3-glucan dynamics. Furthermore, the deletion of KRE6 genes encoding {beta}-1,6-glucan synthase reduced the echinocandin susceptibility of C. auris, and the impaired {beta}-1,6-glucan biosynthesis were offset by compensatory upregulation of this wall component due to caspofungin treatment. The profound alterations induced by caspofungin in Candida cell wall architecture suggest that cell wall structural contribute substantially to drug resistance and tolerance.

microbiology↗
bioRxiv2024

Deep Learning Unravels Potential Antibiotic-Resistance Drugs against Klebsiella Pneumoniae

BackgroundKlebsiella pneumoniae (KP) is a critical pathogen recognized by the World Health Organization due to its high mortality rates and resistance to antibiotics. Developing effective treatments for KP is essential to mitigate the growing threat of multidrug-resistant infections. This study leverages deep learning techniques to identify and validate potential drug candidates against KP, accelerating the drug discovery process and reducing associated risks. ResultsA comprehensive dataset was constructed, comprising 3,475 drugs selected from the DrugBank database, filtered for their potential efficacy and safety. Using convolutional neural networks (CNNs) for drug-drug interaction analysis, a prediction accuracy of 72% was achieved. Evolutionary Scale Modeling (ESM) was employed to calculate molecular similarities between drugs and KP strains, identifying five promising candidates with structural similarities exceeding 85% to known KP targets. A drug repurposing knowledge graph (DRKG) further validated these findings, with the PairRE model outperforming other approaches in ranking potential drug candidates. ConclusionsThis study presents a scalable and efficient framework for identifying and validating drug candidates to combat antibiotic-resistant KP. By integrating deep learning models, molecular similarity analysis, and knowledge graph techniques, this approach shortens the drug discovery timeline from years to months. The identified candidates hold significant promise for preclinical and clinical testing, offering a pathway to effective therapies against KP and other multidrug-resistant pathogens.

bioinformatics↗
bioRxiv2024

Multi-modal refinement of the human heart atlas during the first gestational trimester

1.Forty first-trimester human hearts were studied to lay groundwork for further studies of principles underlying congenital heart defects. We first sampled 49,227 cardiac nuclei from three fetuses at 8.6, 9.0, and 10.7 post-conceptional weeks (pcw) for single-nucleus RNA sequencing, enabling distinction of six classes comprising 21 cell types. Improved resolution led to identification of novel cardiomyocytes and minority autonomic and lymphatic endothelial transcriptomes, among others. After integration with 5-7 pcw heart single-cell RNAseq, we identified a human cardiomyofibroblast progenitor preceding diversification of cardiomyocyte and stromal lineages. Analysis of six Visium sections from two additional hearts was aided by deconvolution, and key spatial markers validated on sectioned and whole hearts in two- and three-dimensional space and over time. Altogether, anatomical-positional features including innervation, conduction and subdomains of the atrioventricular septum translate latent molecular identity into specialized cardiac functions. This atlas adds unprecedented spatial and temporal resolution to the characterization of human-specific aspects of early heart formation.

developmental biology↗
bioRxiv2024

Canonical Notch2 Signaling Regulates the Development of Iron-recycling Macrophages and Iron Homeostasis

Red pulp macrophages (RPM) and bone marrow macrophages (BMM) are iron-recycling cells involved in iron homeostasis and erythropoiesis. Here, we show, using conditional deletion strategies of Notch signaling components, that the development of RPM and BMM is regulated by canonical Notch2 signaling. Loss of functional Notch2, or its nuclear mediator Rbpj, causes impairment in RPM and BMM and iron overload in the spleen and bone marrow, while prototypic RPM genes required for iron handling are downregulated. This was accompanied by splenic extramedullary hematopoiesis and changes in splenic microarchitecture. Furthermore, early postnatal transfer of bone marrow and fetal liver progenitors rescued the defects in RPM and BMM and iron overload in a Notch2-dependent manner, demonstrating the potential to restore defective tissue resident macrophage niches by Notch-competent progenitors. Thus, canonical Notch2 is required for development and function of iron-recycling macrophages.

immunology↗
bioRxiv2024

Immune Evasion, Cell-Cell Fusion, and Spike Stability of the SARS-CoV-2 XEC Variant: Role of Glycosylation Mutations at the N-terminal Domain

SARS-CoV-2 continues to evolve, producing new variants that drive global COVID-19 surges. XEC, a recombinant of KS.1.1 and KP.3.3, contains T22N and F59S mutations in the spike proteins N-terminal domain (NTD). The T22N mutation, similar to the DelS31 mutation in KP.3.1.1, introduces a potential N-linked glycosylation site in XEC. In this study, we examined the neutralizing antibody (nAb) response and mutation effects in sera from bivalent-vaccinated healthcare workers, BA.2.86/JN.1 wave-infected patients, and XBB.1.5 monovalent-vaccinated hamsters, assessing responses to XEC alongside D614G, JN.1, KP.3, and KP.3.1.1. XEC demonstrated significantly reduced neutralization titers across all cohorts, largely due to the F59S mutation. Notably, removal of glycosylation sites in XEC and KP.3.1.1 substantially restored nAb titers. Antigenic cartography analysis revealed XEC to be more antigenically distinct from its common ancestral BA.2.86/JN.1 compared to KP.3.1.1, with the F59S mutation as a determining factor. Similar to KP.3.1.1, XEC showed reduced cell-cell fusion relative to its parental KP.3, a change attributed to the T22N glycosylation. We also observed reduced S1 shedding for XEC and KP.3.1.1, which was reversed by ablation of T22N and DelS31 glycosylation mutations, respectively. Molecular modeling suggests that T22N and F59S mutations of XEC alters hydrophobic interactions with adjacent spike protein residues, impacting both conformational stability and neutralization. Overall, our findings underscore the pivotal role of NTD mutations in shaping SARS-CoV-2 spike biology and immune escape mechanisms.

molecular biology↗
bioRxiv2024

Deep Learning with Evolutionary Scale Modeling to discover Antibiotic-Resistance Drug against Klebsiella Pneumoniae

The development of effective antibiotics is crucial in combating antibiotic-resistant pathogens such as Klebsiella pneumoniae (KP). This study utilizes deep learning, specifically Evolutionary Scale Modeling (ESM), to identify potential drug candidates. By analyzing molecular similarities between known drugs and KP strains, we aim to accelerate the discovery of new treatments and reduce the risks associated with clinical trials. This approach may shed new lights in the field of drug repositioning.

bioinformatics↗
bioRxiv2024

Neural Representation of Time across Complementary Reference Frames

Humans conceptualize time in terms of space, allowing flexible time construals from various perspectives. We can travel internally through a timeline to remember the past and imagine the future (i.e., mental time travel) or watch from an external standpoint to have a panoramic view of history (i.e., mental time watching). However, the neural mechanisms that support these flexible temporal construals remain unclear. To investigate this, we asked participants to learn a fictional religious ritual of 15 events. During fMRI scanning, they were guided to consider the event series from either an internal or external perspective in different tasks. Behavioral results confirmed the success of our manipulation, showing the expected symbolic distance effect in the internal-perspective task and the reverse effect in the external-perspective task. We found that the activation level in the posterior parietal cortex correlated positively with sequential distance in the external-perspective task but negatively in the internal-perspective task. In contrast, the activation level in the anterior hippocampus positively correlated with sequential distance regardless of the observers perspectives. These results suggest that the hippocampus stores the memory of the event sequences allocentrically in a perspective-agnostic manner. Conversely, the posterior parietal cortex retrieves event sequences egocentrically from the optimal perspective for the current task context. Such complementary allocentric and egocentric representations support both the stability of memory storage and the flexibility of time construals.

neuroscience↗
bioRxiv2024

Substrate utilization and cross-feeding synergistically determine microbiome resistance to pathogen invasion

Understanding how microbiomes resist pathogen invasion remains a key challenge in natural ecosystems. Here, we combined genome-scale metabolic models with synthetic community experiments to unravel the mechanisms driving pathogen suppression. We developed curated genome-scale models for each strain, incorporating 48 common resource utilization profiles to fully capture their metabolic capacities. Trophic interactions inferred from models accurately predicted pathogen invasion outcomes, achieving an F1 score of 96% across 620 invasion tests involving diverse microbial communities and nutrient environments. Importantly, considering both substrate and metabolite features provided a more holistic understanding of pathogen suppression. In particular, cross-feeding metabolites within the native community emerged as crucial yet often overlooked predictors of community resistance, disproportionally favoring native species over invaders. This study lays the foundation for designing disease-resistant microbiomes, with broad implications for mitigating pathogen exposure in diverse environments.

ecology↗
bioRxiv2024

Distribution of haploid chromosomes into separate nuclei in two pathogenic fungi

The presence of nuclei defines eukaryotes, enabling compartmentalization of macromolecules and cellular regulation. Inside the nucleus, chromosome numbers vary greatly across organisms, both in terms of ploidy status and haploid chromosome number. For cells harboring multiple nuclei as in many fungal mycelia and animal muscle cells, each healthy nucleus is traditionally believed to carry at least one haploid set of chromosomes. Abnormal chromosome numbers in nuclei are often associated with aging, diseases such as cancer, developmental disorders or lethality. Here we report a surprising discovery that chromosomes in haploid cells of the fungal species Sclerotinia sclerotiorum and Botrytis cinerea are segregated into separate nuclei, with each nucleus containing only a fraction of the chromosomes. This is the first report of eukaryotic cells that partition chromosome subsets into distinct nuclei, bringing new questions and opening fresh avenues for chromosome biology.

microbiology↗
bioRxiv2024

Structure of the microtubule anchoring factor NEDD1 bound to the γ-tubulin ring complex

The {gamma}-tubulin ring complex ({gamma}-TuRC) is an essential multiprotein assembly, in which {gamma}-tubulin, GCP2-6, actin, MZT1 and MZT2 form an asymmetric cone-shaped structure that provides a template for microtubule nucleation. The {gamma}-TuRC is recruited to microtubule organizing centers (MTOCs), such as centrosomes and pre-existing mitotic spindle microtubules, via the evolutionarily-conserved attachment factor NEDD1. NEDD1 contains an N-terminal WD40 domain that binds to microtubules, and a C-terminal domain that associates with the {gamma}-TuRC. However, the structural basis of the NEDD1-{gamma}-TuRC interaction is not known. Here, we report cryo-electron microscopy (cryo-EM) structures of NEDD1 bound to the human {gamma}-TuRC in the absence or presence of the activating factor CDK5RAP2, which interacts with GCP2 to induce conformational changes in the {gamma}-TuRC and promote its microtubule nucleating function. We found that the C-terminus of NEDD1 forms a tetrameric -helical assembly that contacts the lumen of the {gamma}-TuRC cone, is anchored to GCP4, 5 and 6 via protein modules consisting of MZT1 & GCP3 subcomplexes, and orients its microtubule-binding WD40 domains away from the complex. We biochemically tested our structural models by identifying NEDD1 mutants unable to pull-down{gamma} -tubulin from cultured cells. The structure of the {gamma}-TuRC simultaneously bound to NEDD1 and CDK5RAP2 reveals that both factors can associate with the "open" conformation of the complex. Our results show that NEDD1 does not induce conformational changes in the {gamma}-TuRC, but suggest that anchoring of {gamma}-TuRC-capped microtubules by NEDD1 would be structurally compatible with the significant conformational changes experienced by the {gamma}-TuRC during microtubule nucleation.

biochemistry↗
bioRxiv2024

Multiomics reveals age-dependent metabolic reprogramming of macrophages by wound bed niche secreted signals

The cellular metabolism of macrophages depends on tissue niches and can control macrophage inflammatory or resolving phenotypes. Yet, the identity of signals within tissue niches that control macrophage metabolism is not well understood. Here, using single-cell RNA sequencing of macrophages in early mouse wounds, we find that, rather than gene expression of canonical inflammatory or resolving polarization markers, metabolic gene expression defines distinct populations of early wound macrophages. Single-cell secretomics and transcriptomics identify inflammatory and resolving cytokines expressed by early wound macrophages, and we show that these signals drive metabolic inputs and mitochondrial metabolism in an age-dependent manner. We show that aging alters the metabolome of early wound macrophages and rewires their metabolism from mitochondria to glycolysis. We further show that macrophage-derived Chi3l3 and IGF-1 can induce metabolic inputs and mitochondrial mass/metabolism in aged and bone marrow-derived macrophages. Together, these findings reveal that macrophage-derived signals drive the mitochondrial metabolism of macrophages within early wounds in an age-dependent manner and have implications for inflammatory diseases, chronic injuries, and age-related inflammatory diseases. In BriefThis study reveals that macrophage subsets in early inflammatory stages of skin wound healing are defined by their metabolic profiles rather than polarization phenotype. Using single-cell secretomics, we establish key macrophage cytokines that comprise the in vivo wound niche and drive mitochondrial-based metabolism. Aging significantly alters macrophage heterogeneity and increases glycolytic metabolism, which can be restored to OxPHOS-based metabolism with young niche cytokines. These findings highlight the importance of the tissue niche in driving macrophage phenotypes, with implications for aging-related impairments in wound healing. HighlightsO_LISingle cell transcriptional analysis reveals that reveals that metabolic gene expression identifies distinct macrophage populations in early skin wounds. C_LIO_LISingle-cell secretomic data show that young macrophages contribute to the wound bed niche by secreting molecules such as IGF-1 and Chi3l3. C_LIO_LIOld wound macrophages display altered metabolomics, elevated glycolytic metabolism and glucose uptake, and reduced lipid uptake and mitochondrial mass/metabolism. C_LIO_LIChi3l3 but not IGF-1 secretion is altered in macrophages in an age dependent manner. C_LIO_LIChi3l3 can restore mitochondrial mass/metabolism in aged macrophages. C_LI

cell biology↗
bioRxiv2024

Isoprene deters insect herbivory by priming plant hormone responses

Isoprene, emitted by some plants, enhances plant abiotic resilience but its role in biotic stress resilience remains elusive. We used tobacco plants engineered to emit isoprene (IE) and the corresponding azygous non-emitting control (NE) to investigate isoprene emission and biotic stress resilience. IE plants were more resistant to insect herbivory than NE plants. Worms preferred to feed on NE rather than IE leaves. IE plants showed less decline in photosynthesis during worm feeding. Insect feeding increased jasmonate levels in IE leaves, suggesting isoprene-mediated priming of the jasmonic acid response. Wound-induced increase in isoprene emission corresponded with elevation of methyl-D-erythritol-4-phosphate pathway and Calvin-Benson cycle metabolites. The results highlight interactive functions of isoprene and jasmonic acid and advance our understanding of how isoprene emission enhances plant resilience.

plant biology↗
bioRxiv2024

Deep generative design of neutralizing nanobodies againstSARS-CoV-2 variants

In recent years, single-domain heavy chain antibodies (nanobodies), with only one-tenth the molecular weight of conventional antibodies, have emerged as important therapeutic proteins in the fight against SARS-CoV-2. However, the rapid mutation of the virus often renders existing nanobodies ineffective, underscoring the need to develop nanobodies that specifically target new variants. Traditional methods for discovering nanobodies are time-consuming and complex, making it difficult to efficiently identify nanobodies that bind to specific epitopes. To address this, we propose a de novo nanobody design method based on a Generative Adversarial Network (GAN). We developed a deep generative model, AiCDR, which consists of three discriminators and one generator. By determining the contribution of these three discriminators to the entire network, we can enhance the discrimination of generated sequences and reduce the similarity of the generated CDR3 sequences with natural peptides and random sequences, thereby ensuring their nature-like properties. These generated CDR3 sequences were then grafted onto humanized nanobody scaffolds, resulting in a structural library of approximately 104 nanobodies with natural-like properties. Using computational methods, we screened this library against the Spike (S) protein of the SARS-CoV-2 Omicron variant and identified 10 candidate nanobodies. Functional assays confirmed that two of these nanobodies exhibited neutralizing activity against the S protein. Our study demonstrates the potential of deep learning in nanobody design and offers a novel approach for developing nanobodies that target rapidly evolving viral variants.

bioinformatics↗
bioRxiv2024

LEGEND: Identifying Co-expressed Genes in Multimodal Transcriptomic Sequencing Data

Identifying co-expressed genes across tissue domains and cell types is essential for revealing co-functional genes involved in biological or pathological processes. While both single-cell RNA-sequencing (scRNA-seq) and spatially-resolved transcriptomic (SRT) data offer insights into gene co-expression patterns, current methods typically utilize either data type alone, potentially diluting the co-functionality signals within co-expressed gene groups. To bridge this gap, we introduce LEGEND, a novel computational method that integrates scRNA-seq and SRT data for identifying groups of co-expressed genes at both cell type and tissue domain levels. LEGEND employs an innovative hierarchical clustering algorithm designed to maximize intra-cluster redundancy and inter-cluster complementarity, effectively capturing more nuanced patterns of gene co-expression and spatial coherence. Enrichment and cofunction analyses further showcase the biological relevance of these gene clusters, and their utilities in exploring context-specific novel gene functions. Notably, LEGEND can reveal shifts in gene-gene interactions under different conditions, furnishing insights for disease-associated gene crosstalk. Moreover, LEGEND can be utilized to enhance the annotation accuracy of both spatial spots in SRT and single-cells in scRNA-seq, and pioneers in identifying genes with designated spatial expression patterns. LEGEND is available at https://github.com/ToryDeng/LEGEND.

genomics↗
bioRxiv2024

NSD2 promotes cell durotaxis and drives the transition from PKD to tubulocystic renal cell carcinoma through integrin/FAK/AKT signaling

Renal cell carcinoma (RCC) is one of the most common malignancies in the urinary system. NSD2 is an H3K36-specific di-methyltransferase which has been reported to participate in diverse biological processes and human tumors. However, its role in RCC remains unclear. Here, we found that NSD2 is highly expressed in RCC, which is associated with poor survival in RCC patients. NSD2 facilitates the transition from Myc-induced polycystic kidney disease to tubulocystic renal cell carcinoma (TCRCC), which is a rare RCC subtype with distinctive clinicopathologic and genetic characterizations. The mice with kidney-specific overexpression of MYC and NSD2 (KMN) display severe cyst burden at only 6 weeks of age, and develop into TCRCC at 12 weeks of age. Mechanistically, NSD2 transcriptionally upregulates the expressions of integrins (Itga4 and Itga11), to further activate the FAK/AKT pathway. In addition, we found that NSD2 enhances the cell proliferation on the stiff matrix of PEGDA hydrogel. Moreover, inhibition of FAK signaling relieves the symptoms of KMN mice, and significantly rescues the enhanced cell proliferation caused by NSD2 overexpression in vitro. Together, our findings highlight an epigenetic mechanism by which NSD2 regulates TCRCC tumorigenesis through the integrin/FAK/AKT pathway. This study may also pave the way for the development of targeted, patient-tailored therapies for TCRCC patients with NSD2 amplification or high expression.

cancer biology↗
bioRxiv2024

Connectomic Organization of the Suprachiasmatic Nucleus

The suprachiasmatic nucleus (SCN), the mammalian master clock, is a special structure dedicated to the time computation. However, a connectomic understanding of the nucleus as a whole is lacking. Using serial section electron microscopy, we reconstructed multiscale and multimodal SCN communication networks. Intra-SCN synaptic network consists of 9,566 morphologically similar neurons and 4.3 million synapses, organized into multiscale circuitries that interact with SCN-traversing axon fascicles. Strikingly, SCN neurons engage in unique soma-soma ephaptic interaction, forming 2,038 electrotonic integrative units with the largest overlapping the light-responsive area (LRA). SCNs paracrine modality contains 47,396 m3 dense core vesicles, with notable scarcity in the LRA, suggesting cross-modal coordination and functional integration. These distinct network features provide comprehensive insights into the system architecture of the mammalian circadian clock.

neuroscience↗
bioRxiv2024

Decipher Fundamental Atomic Interactions to Unify Generative Molecular Docking and Design

Understanding molecular interactions is essential to structural biology and drug discovery. Despite the progress of AI models in revealing and exploiting the interaction mechanisms for various applications, they are predominantly tailored to specific tasks without fully exploiting the underlying transferability across molecular data and tasks. Here, we present PocketXMol, an atom-level generative foundation model to decipher fundamental atomic interactions for general protein-pocket-interacting molecular tasks. It adopts a novel unified generative framework with an innovative task prompt mechanism and an exclusive atom-level representation, making it applicable to diverse tasks covering structure prediction and design of small molecules and peptides, without requiring fine-tuning. PocketXMol was compared to 55 baseline models across 13 typical tasks, achieving state-of-the-art performance in 11 tasks and remaining competitive in the others. We successfully utilized PocketXMol to design novel small molecules that inhibit caspase-9 with efficacy comparable to that of commercial pan-caspase inhibitors. Furthermore, we employed PocketXMol to design PD-L1-binding peptides, demonstrating a success rate substantially higher than random library screening. Three representative peptides underwent further experiments, which validated the cellular specificity and confirmed their potential for molecular probing and therapeutics. PocketXMol presents a powerful and versatile tool with promising prospects for future applications and will have a profound impact on AI-aided drug discovery.

bioinformatics↗