Biology subjects

Xu, Q.

Publications and source records attributed to Xu, Q..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Single-cell Transcriptomic Profiling of Pancreatic Ductal Adenocarcinoma: Epithelial Reprogramming and Systemic Immune Exhaustion

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal human malignancies, with a five-year survival rate below 10%, underscoring the urgent need to unravel its complex pathophysiology. In this study, we employ an integrative single-cell RNA sequencing (scRNA-seq) approach to comprehensively characterize both the pancreatic tumor microenvironment and peripheral blood mononuclear cells (PBMCs) from PDAC patients and healthy controls. Using Harmony for batch correction and Azimuth for automated cell-type annotation, we identify cell-type-specific transcriptional alterations through differential expression and functional enrichment analyses. Our results reveal a system-wide disruption involving both epithelial and immune compartments. Epithelial cells exhibit a "de-skilling" phenotype, losing digestive enzyme expression while activating metabolic and ribosomal programs that sustain malignant proliferation. The local immune microenvironment displays chronic inflammation and remodeling, whereas systemic immune exhaustion is evident in cytotoxic T, NK, and myeloid populations, marked by impaired effector activity and metabolic imbalance. Collectively, these findings depict PDAC as a coordinated multi-compartmental failure encompassing epithelial reprogramming, local immune dysregulation, and systemic immune collapse, providing a holistic single-cell view of PDAC pathogenesis and offering mechanistic insights that may guide biomarker discovery and the development of targeted therapeutic strategies.

bioinformatics↗

bioRxiv2025

Missense Mutation ADNP p.C687R Disrupts Chromatin Regulation and GABAergic Differentiation in HVDAS

Activity-dependent neuroprotective protein (ADNP) is a key regulator of neurodevelopment and a high-risk gene for autism spectrum disorder (ASD). Most pathogenic variants cause loss-of-function in Helsmoortel-Van der Aa syndrome (HVDAS), yet the impact of missense mutations remains unclear. Here, we characterized a ADNP missense mutation (p.C687R) identified from a HVDAS patient, predicted to disrupt its ninth zinc finger domain. Overexpression of p.C687R altered subnuclear localization and affected wild-type ADNP distribution. In utero electroporation revealed impaired neuronal migration and cortical branching. CUT&Tag profiling showed mutant- specific chromatin binding, preferentially targeting histone modification genes through both direct and distal interactions. Patient-derived iPSCs carrying p.C687R exhibited upregulated bivalent histone marks (H3K4me3 and H3K27me3) on neurodevelopmental genes, including regulators of GABAergic differentiation, which became transcriptionally activated in neural progenitors. These findings reveal a gain-of-function mechanism by which ADNP p.C687R perturbs chromatin regulation and disrupts GABAergic lineage specification, expanding the molecular framework of ADNP pathogenesis. The Paper Explained ProblemMutations in the gene ADNP cause Helsmoortel-Van der Aa syndrome (HVDAS), a severe neurodevelopmental disorder, and also increase the risk for autism spectrum disorder (ASD). While most known ADNP mutations lead to loss of protein function, many missense mutations that alter a single amino acid remain poorly understood regarding their effects on brain development and disease contribution. ResultsWe characterized a specific missense mutation, ADNP p.C687R, from a patient diagnosed with HVDAS, and found that it does not simply inactivate the protein but instead confers a disruptive new function. Across multiple models, from cells to mice, the p.C687R mutant exhibits abnormal chromatin binding, altered subnuclear localization, and impaired neuronal migration and differentiation. Importantly, in patient-derived iPSCs, it marks distinct neurodevelopmental genes with bivalent histone modifications, which become aberrantly activated during differentiation into GABAergic neural progenitor cells. ImpactThese findings confirm the pathogenicity of the missense mutation ADNP p.C687R in HVDAS, reveal a gain-of-function mechanism whereby the mutant disrupts chromatin regulation and GABAergic lineage specification, and advance our understanding of ADNP-related neurodevelopmental disorders.

neuroscience↗

bioRxiv2025

Host EV derived lipids promote malaria parasite development via mosquito fatty acid oxidation

Malaria parasites must transition between mammals and mosquitoes, but how they adapt to such distinct environments is unclear. We show that blood from infected mammals buffers this environmental shift by packaging parasite-induced signals into extracellular vesicles (EVs). EVs internalized by mosquito midgut increases expression of VLCAD and raises levels of a 22-carbon fatty acid, driving fatty acid breakdown and acetyl-CoA production. The parasite exploits this metabolic shift to synthesize its own lipids during oocyst growth. Stable isotope tracing confirmed that13C4-labelled behenic acid is degraded and incorporated into parasite fatty acids. Lipidomic profiling further revealed that ceramides enriched in the EVs are key mediators. These findings identify a mechanism by which host bood-derived EVs reprogram mosquito lipid metabolism to promote parasite transmission.

microbiology↗

bioRxiv2025

Community coalescence reveals strong selection and coexistence within species in complex microbial communities

Complex microbial ecosystems harbor extensive intra-species diversity, but the fitness consequences of this genetic variation are poorly understood in community settings. Here we address this question by competing in vitro gut communities derived from different human donors, revealing the emergent fitness differences between conspecific strains as they competed within larger communities. Most pairs of strains experienced strong and context-dependent selection, even when their parent communities were originally selected in the same nutrient environment. However, these fitness differences typically attenuated over time due to biotic interactions within the community, leading to extended coexistence within many species, and competitive exclusion in others. These results support the view that conspecific strains can fulfill distinct ecological roles when competing within a diverse community, even when their genomic diversity exhibits the hallmarks of a single biological species.

evolutionary biology↗

bioRxiv2025

Integrated cell atlas and tumoroids chart pancreatic cancer therapeutic targets

Pancreatic ductal adenocarcinoma (PDAC) is characterized by dense, fibroblast-rich stroma that actively shapes the tumor microenvironment. Most PDAC cases arise from conserved genetic transformations initiated by oncogenic KRAS mutations, developing into metastatic disease with high mortality rates. To chart universal PDAC cell states and identify therapeutic inroads, we integrated published single-cell transcriptomes from 200 patient samples, and used the atlas to define prevalent cancer cell and cancer-associated fibroblast (CAF) states, gene expression programs, and ligand-receptor interactions. We established modular tumoroids incorporating patient-derived cancer cells and CAFs that recapitulate aspects of ductal architecture and desmoplastic stroma. Single-cell and spatial transcriptomic profiling confirmed preservation of key cellular states and signaling networks in vitro. We identified Syndecan-1 (SDC1) as a CAF-responsive cancer cell receptor correlating with poor patient survival. Functional SDC1 blockade disrupted cancer growth in tumoroids, highlighting therapeutic relevance. This study provides a framework for dissecting cancer-stroma dynamics and identifying actionable targets using patient-derived tumoroid models.

cancer biology↗

bioRxiv2025

CryoDataBot: a pipeline to curate cryoEM datasets for AI-driven structural biology

Cryogenic electron microscopy (cryoEM) has revolutionized structural biology by enabling atomic-resolution visualization of biomacromolecules. To automate atomic model building from cryoEM maps, artificial intelligence (AI) methods have emerged as powerful tools. Although high-quality, task-specific datasets play a critical role in AI-based modeling, assembling such resources often requires considerable effort and domain expertise. We present CryoDataBot, an automated pipeline that addresses this gap. It streamlines data retrieval, preprocessing, and labeling, with fine-grained quality control and flexible customization, enabling efficient generation of robust datasets. CryoDataBots effectiveness is demonstrated through improved training efficiency in U-Net models and rapid, effective retraining of CryoREAD, a widely used RNA modeling tool. By simplifying the workflow and offering customizable quality control, CryoDataBot enables researchers to easily tailor dataset construction to the specific objectives of their models, while ensuring high data quality and reducing manual workload. This flexibility supports a wide range of applications in AI-driven structural biology.

molecular biology↗

bioRxiv2025

The Darwin-Godel Drug Discovery Machine (DGDM): A Self-Improving AI Framework

Despite advances such as AlphaFold and modern generative AI models, current drug discovery pipelines lack mechanisms to refine both molecules and the pipelines themselves, limiting their ability to achieve autonomous and reliable self-improvement. To address this, we present the Darwin-Godel Drug Discovery Machine (DGDM), a self-improving artificial intelligence framework that integrates generative molecular design and evolution with adaptive meta-learning. DGDM employs a dual-loop architecture: an inner loop frames molecular optimization as a Darwinian evolutionary process guided by reinforcement learning signals, where candidate molecules generated by generative AI are evolved through search and feedback; an outer loop adaptively modifies the discovery pipeline itself. Unlike the original Godel machine, which demands formal proofs of improvement--rarely attainable in practice--DGDM uses statistical validation to bound risk and ensure reliable progress. The framework is fully compatible with modern structural biology tools, including AlphaFold, and supports evaluation through docking, binding affinity prediction, and ADMET profiling. In a proof-of-concept study, DGDM improved the median binding affinity of candidate ligands from -4.457 to -5.422 kcal/mol while maintaining 100% drug-likeness and novelty. These results suggest that bounded-risk, self-improving AI can accelerate drug discovery by continuously refining both molecular design and discovery processes, extending the Godel machine principle of self-improvement into biomedical research. All code is open-sourced at https://github.com/deep-geo/DGDM.

bioinformatics↗

bioRxiv2025

Nitric Oxide-Releasing Thixotropic Hydrogels as Antibacterial and Hemocompatible Catheter Locks

Catheters are indispensable medical tools for accessing blood vessels, hollow organs, and body cavities to facilitate medication delivery and fluid drainage. However, they also serve as major entry points for bacterial contamination and trigger foreign body responses, necessitating locking strategies that are both bactericidal and biocompatible. This study introduces the first gel-based catheter lock, in contrast to conventional liquid locks. The gel is a poloxamer-based hydrogel formulated with 2-hydroxypropyl -cyclodextrin (HP-CD). HP-CD forms supramolecular complexes with the poloxamer to enhance gelation, and with the nitric oxide (NO) donor to modulate NO release kinetics. This thixotropic gel can be injected into the catheter lumen when the catheter is not in use and withdrawn when vascular access is needed. The gel matrix provides a physical barrier that slows bacterial migration and minimizes drug loss. Simultaneously, the released NO functions as a broad-spectrum antimicrobial agent, effectively preventing biofilm formation on both the internal and external surfaces of the catheter. The NO-releasing hydrogel also demonstrates excellent hemocompatibility and reduces clot adhesion. Together, the gel-based lock offers a promising strategy for more effective catheter maintenance and represents a new application of hydrogels.

bioengineering↗

bioRxiv2025

gCoSRNA: Generalizable Coaxial-Stacking Prediction for RNA Junctions Using Secondary Structure

Coaxial stacking between adjacent stems is a key tertiary interaction that defines the spatial organization of RNA junctions, which are core structural motifs in folded RNAs. Accurate prediction of coaxial stacking is critical for RNA 3D structure modeling, yet existing computational tools remain limited, especially for junctions with variable numbers of branches or complex topologies. Here, we present gCoSRNA, a generalizable computational framework for predicting coaxial stacking configurations using RNA sequence and secondary structure as input. Instead of developing separate models for each junction type, gCoSRNA decomposes multi-way junctions into all possible adjacent stem pairs, termed pseudo two-way junctions, and uses a unified random forest classifier to evaluate stacking probabilities. Global stacking configurations are inferred by integrating these pairwise predictions, eliminating the need for explicit junction-type classification. Benchmarking on two independent test sets, including CASP15/16 and RNA-Puzzles targets, shows that gCoSRNA achieves consistently high accuracy (mean [~]0.87) across junctions with two to seven branches, outperforming existing junction-specific methods. These results highlight the models ability to capture higher-order structural features and its potential utility in RNA tertiary structure prediction pipelines. The source code is freely available at https://github.com/RNA-folding-lab/gCoSRNA.

bioinformatics↗

bioRxiv2025

The Role of Primate-Specific Genes and Network Dynamics in Cancer Evolution

The atavistic evolutionary theory of cancer evolution highlights the role of ancient and unicell-originated genes, and comprehensive research demonstrated the evolutionary inference. Comparably, very few reports linked young genes with cancer development and maintenance. Here, we found that in cancer cell lines a higher proportion of core essential genes was present among primate-specific genes (PSG) than early metazoan-originated genes (Wilcoxon rank-sum test, p-value = 4.67e-12) and mammal-originated genes (Wilcoxon rank-sum test, p-value = 1.22e-16). Additionally, we found that the loss of many co-expression gene pairs in pan-cancer leads to their network becoming looser compared with normal tissue. However, PSGs particularly those being essential, exhibit a dynamic increase in co-expression, explaining their enhanced role in maintaining cancers. Furthermore, clustering of the gene co-expressions brings a cancer-exclusive module, which contains a large number of PSG connections. We also demonstrate the divergence between essential genes in healthy individuals and those in cancer cells. Our findings complement the atavistic theory in elucidating the evolutionary process of cancer.

evolutionary biology↗

bioRxiv2025

Dual Inhibition of CDK4/6 and mTORC1 Establishes a Preclinical Strategy for Translocation Renal Cell Carcinoma

PurposeTranslocation renal cell carcinoma (tRCC) is a rare and aggressive subtype of kidney cancer driven by an oncogenic fusion involving a transcription factor in the MiT/TFE gene family, most commonly TFE3. Treatment of tRCC currently lacks a clear standard of care, underscoring the pressing need to nominate new therapeutic targets with mechanistic rationale in this cancer. Experimental DesignIn this study, we applied integrative genomic approaches to identify activation of the cyclin-dependent kinase 4/6 (CDK4/6) and mammalian target of rapamycin complex 1 (mTORC1) pathways in tRCC. We tested the activity of CDK4/6 inhibitors (CDK4/6i), alone or in combination with mTORC1-selective inhibition, using in vitro and in vivo models of tRCC. ResultstRCC tumors displayed multiple genomic and transcriptional features associated with activation of the CDK4/6 and mTORC1 signaling pathways. Genetic or pharmacologic inhibition of CDK4/6 suppressed tRCC cell growth and induced cell cycle arrest in vitro but was not cytotoxic, with rapid cell regrowth observed after drug withdrawal. The mTORC1-selective inhibitor, RMC-5552, potently reduced translation of Cyclin D1, which complexes with CDK4/6 proteins to regulate G1-S cell cycle progression. Combined treatment with the CDK4/6 inhibitor, palbociclib, and RMC-5552 resulted in synergistic suppression of tRCC cell viability and increased markers of apoptosis in vitro. The combination of palbociclib and RMC-5552 in a tRCC xenograft model showed greater eOicacy than either single agent while also being well-tolerated. ConclusionsOur study indicates the therapeutic potential of combined CDK4/6 and mTORC1 inhibition in tRCC, providing the rationale for further clinical evaluation of this strategy. Translational RelevanceTranslocation renal cell carcinoma (tRCC) is a rare and aggressive form of kidney cancer that accounts for 2-5% of all RCCs in adults and around 50% of RCCs in children. tRCC lacks effective therapies and represents a significant unmet clinical need. Therapies approved for clear cell RCC (ccRCC), including VEGF/multikinase inhibitors and immune checkpoint blockade, typically show decreased efficacy in tRCC. Via an integrative genomic analysis, we nominate combined inhibition of the cyclin-dependent kinase 4/6 (CDK4/6) and mammalian target of rapamycin complex 1 (mTORC1) pathways in tRCC. We demonstrate that combining the CDK4/6 inhibitor palbociclib with the mTORC1-selective inhibitor RMC-5552 synergistically inhibits the growth of tRCC cells in vitro and of tRCC xenografts in vivo, where the combination is well-tolerated. This proof-of-concept study provides preclinical evidence supporting CDK4/6 inhibitor-based combination regimens tailored to tRCC biology, offering a foundation for future clinical studies in tRCC, which currently has no clear standard of care.

cancer biology↗

bioRxiv2025

Advancing Inter-brain Synchrony Measurement: A Comparative Hyperscanning Study of High-Density Diffuse Optical Tomography and Functional Near-infrared Spectroscopy

Inter-brain synchrony (IBS), measured by hyperscanning, refers to the synchronization of multiple individuals brain activities during social interactions. Traditional fNIRS-based hyperscanning suffers shortcomings like low spatial resolution and high susceptibility to superficial interference, causing imprecise estimation of IBS in complex social tasks. This study aims to fill the knowledge gap by comprehensively assessing how high-density diffuse optical tomography (HD-DOT), an enhanced alternative to fNIRS, can benefit hyperscanning studies of complex social interactions. Sixteen dyads were engaged in both collaborative and individual tangram puzzle tasks, and their brain activities were recorded simultaneously using HD-DOT and fNIRS. We found that HD-DOT demonstrated significantly stronger IBS and identified more brain regions with significant IBS compared to fNIRS during the collaborative task. Specifically, while fNIRS detected IBS only in the dorsolateral prefrontal cortex (DLPFC) and supramarginal gyrus (SMG), HD-DOT revealed additional IBS in the superior temporal gyrus (STG). Additionally, compared to the individual task, the collaborative task showed increased IBS in HD-DOT, not only in the DLPFC but also in the SMG, frontal eye fields (FEF), and inferior frontal gyrus (IFG). By highlighting the superior spatial resolution and sensitivity of HD-DOT in capturing detailed and extensive neural activity during complex social interactions, our findings for the first time clarified the potential strengths of HD-DOT in measuring IBS over traditional fNIRS. These advances provide a stronger empirical foundation for investigating the neural basis of social interaction, paving the way for future research on real-world, dynamic group behaviors. HighlightsO_LIFirst application of HD-DOT for inter-brain synchrony measurement. C_LIO_LIFirst demonstration of HD-DOTs superiority over fNIRS in IBS measurement. C_LIO_LIHD-DOT detects stronger IBS and more brain regions than fNIRS. C_LI

neuroscience↗

bioRxiv2025

Medial preoptic area FoxO1 controls metabolic adaptation in a sexually dimorphic manner

The medial preoptic area (MPOA) of the hypothalamus is essential for metabolic adaptation to environmental challenges, though the molecular mechanisms underlying this process remain poorly understood. Here, we investigate the role of Forkhead transcription factor O1 (FoxO1), a key mediator of stress adaptation, in MPOA-dependent metabolic responses to temperature and nutritional changes. Our findings reveal sex-specific responses to both nutritional and temperature challenges. In female mice, but not males, a high-fat diet (HFD) challenge decreased FoxO1 expression in the MPOA. Specific deletion of FoxO1 in MPOA neurons (FoxO1-KOMPOA) had no effect on body weight under normal chow-fed conditions but protected females from HFD-induced obesity (DIO). These protected females exhibited increased lean mass, decreased fat mass, enhanced thermogenesis, increased energy expenditure, and reduced food intake under HFD conditions. They also showed enhanced cold-induced heat production at 6{degrees}C, though this effect vanished at thermoneutrality (30{degrees}C). The protection against DIO was abolished by ovariectomy (OVX) and was not restored by 17{beta}-estradiol supplementation, suggesting an estrogen-independent mechanism. Conversely, constitutive activation of FoxO1 in MPOA neurons (FoxO1-CAMPOA) increased DIO susceptibility in both sexes. Together, these findings demonstrate that FoxO1MPOA plays a crucial role in coordinating metabolic adaptation to nutritional and temperature challenges specifically in female mice.

physiology↗

bioRxiv2025

Modular Inter-brain Synchrony Network Associated with Social Difficulty in Autism Spectrum Disorder: a Graph Neural Network-Driven Hyperscanning Study

Understanding social difficulties in Autism Spectrum Disorder (ASD) remains challenging due to its neurobiological heterogeneity and the limited ecological validity of conventional neuroimaging methods in capturing dynamic social interactions. Hyperscanning analysis based on functional near-infrared spectroscopy (fNIRS), which measures inter-brain synchrony (IBS) during dyadic interaction, offers a novel avenue to address these challenges. However, prior studies on ASD have reported inconsistent findings, primarily focusing on intra-regional synchronization while overlooking cross-regional network dynamics. To bridge this gap, we proposed an interpretable graph neural network (GNN) model to systematically identify ASD-specific IBS modular network between child-caregiver dyads during naturalistic cooperative puzzle-solving and free-talking tasks. We identified distinctive key IBS sub-networks for the cooperative puzzle-solving task and free-talking task, with the frontal eye field (FEF) of caregivers, the dorsal lateral prefrontal cortex (DLPFC) and the motor region of children highlighted. Furthermore, the key IBS sub-networks were found to be able to predict multiple domains of the core ASD symptoms. By integrating hyperscanning with GNN-driven analysis, this work uncovers task-dependent inter-brain neural mechanisms underlying social difficulties in ASD. These findings advance the field by proposing a data-driven framework to identify IBS biomarkers tied to clinical profiles, paving the way for personalized interventions that integrate computational neuroscience with clinical practice.

neuroscience↗

bioRxiv2025

A synergistic generative-ranking framework for tailored design of therapeutic single-domain antibodies

Single-domain antibodies (sdAbs) have emerged as powerful therapeutic agents due to their small size, high stability, and superior tissue penetration. However, unlike conventional monoclonal antibodies (mAbs), sdAbs lack an Fc domain, limiting their functional versatility and manufacturability. To address this challenge, we developed TFDesign-sdAb, a deep learning-based generative-ranking framework that enables rational engineering of sdAbs with tailored functionalities. Our framework integrates a structure-aware diffusion model (IgGM) for large-scale candidate generation and a fine-tuned sorter (A2binder) that evaluates and prioritizes them based on predicted functionality. Unlike traditional CDR-focused approaches, TFDesign-sdAb optimizes both complementarity-determining regions (CDRs) and framework regions (FRs), allowing sdAbs to acquire new functional properties while maintaining antigen specificity. We validated our approach by conferring Protein A binding to human VHs and nanobodies that originally lacked this feature, achieving high expression rates, strong binding affinities, and successful purification via industry-standard Protein A affinity chromatography. High-resolution structural characterization (1.49 [A] and 2.0 [A]) of the redesigned sdAb-Protein A complexes revealed conserved FR-mediated binding motifs that recapitulate natural Fc-Protein A interactions, validating the accuracy of our model. Furthermore, our pipeline streamlined the antibody engineering process, achieving a 100% success rate in generating Protein A-binding sdAbs while maintaining their original antigen-binding affinity. This work demonstrates the power of AI-driven design in overcoming long-standing limitations in antibody engineering and presents a scalable, generalizable solution for enhancing sdAb functionality.

bioinformatics↗

bioRxiv2025

β-Glucan Modulates Monocyte Plasticity and Differentiation Capacity to Mitigate DSS-Induced Colitis

Trained immunity involves the reprogramming of innate immune cells after an initial exposure, resulting in heightened inflammatory responses to subsequent stimuli and enhanced bactericidal capacity during infection. However, this proinflammatory state could also exacerbate chronic conditions like inflammatory bowel disease (IBD), which is characterized by persistent inflammation and microbial imbalance. It remains unclear how trained immunity influences IBD pathogenesis and whether it can be harnessed therapeutically. In our study, pretreatment with {beta}-glucan reprogrammed bone marrow hematopoietic progenitors and peripheral monocytes, inducing a profound shift in monocyte plasticity and significantly reducing the severity of dextran sulfate sodium (DSS)-induced colitis. Adoptive transfer of bone marrow or peripheral monocytes from {beta}-glucan-trained mice into naive mice conferred robust protection against colitis, demonstrating that this protective effect is transferable. Trained mice also displayed improved clearance of intestinal bacterial infections. Single-cell RNA sequencing revealed an expansion of reparative Cx3cr1 macrophages derived from Ly6Chi monocytes, correlating with accelerated colonic epithelial regeneration. Collectively, these findings reveal how {beta}-glucan-induced trained immunity modulates monocyte differentiation to ameliorate experimental colitis, highlighting the potential of harnessing trained immunity as a therapeutic strategy to recalibrate innate immune responses and restore gut homeostasis in IBD, shedding light for future clinical applications. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=189 SRC="FIGDIR/small/653036v2_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@1b969c2org.highwire.dtl.DTLVardef@1ce603dorg.highwire.dtl.DTLVardef@10582forg.highwire.dtl.DTLVardef@10d7de6_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2025

SLICK: A Sandwich-LIke Culturing Kit for in situ Cryo-ET Sample Preparation

In situ cryo-electron tomography (cryo-ET) has recently been widely used in observing subcellular structures and macromolecules in their native states at high resolution. One of the reasons that it has not been more widely adopted by cell biologists and structural biologists is the difficulties in sample preparation. Here we present the Sandwich-LIke Culturing Kit (SLICK), simplifying the procedure and increasing the throughput for sample preparation for in situ cryo-ET (69 words).

biophysics↗

bioRxiv2025

Functional dynamics reveal the response of the crabapple (Malus sp.) phyllosphere microbiome to Gymnosporangium yamadae infection

The plant microbiome is crucial for maintaining plant health under disease stress. While considerable research has focused on belowground systems, the phyllosphere microbiome remains underexplored, particularly regarding its functional responses to pathogen infection. In this study, we investigated the phyllosphere microbiome dynamics of crabapple (Malus Kelsey) infected by Gymnosporangium yamadae using metatranscriptomic sequencing across six stages of rust disease progression. Our analysis revealed a general increase in the diversity of fungi, bacteria and viruses in infected leaves. Notably, fungal diversity negatively correlated with bacterial diversity, reflecting competitive interactions during disease development. Microbial taxa in diseased leaves exhibited heightened expression activity compared to healthy leaves, with fungi progressively dominating the microbial community. Functional co-occurrence networks of the phyllosphere microbiome in infected leaves were more complex than in healthy leaves, suggesting adaptive reorganization in response to pathogen invasion. Differentially expressed genes at each stage were significantly enriched in carbohydrate metabolism pathways and gene regulation-related functions, enabling functional adaptations to rust diseases. Random forest modeling identified key microbial transcripts associated with pathogen abundance, including beneficial microbes like Saitozyma podzolica, which secretes glucan-degrading enzymes, and Mortierella elongata, involved in sterol biosynthesis and plant resistance. Conversely, Alternaria alternata emerged as a major pathobiome contributor, secreting enzymes that degrade plant cell wall components (e.g., pectin, cellulose, lignin, and xylan), and engaging in MAPK signaling pathways critical for pathogenesis. Our findings underscore the vital role of the phyllosphere microbiome in mediating plant-pathogen interactions and shaping disease progression, providing a foundation for microbiome-based strategies to enhance plant resilience. ImportanceOur findings reveal the dynamic shifts in the expression patterns and adaptive functional strategies of crabapple phyllosphere microbiome in response to the Gymnosporangium yamadae infection. We identified several key microbes that may play vital roles in pathogenesis and speculated on their roles and functions in plant-pathogen interactions. In conclusion, our study highlights the potential of the phyllosphere microbiome in regulating plant health.

microbiology↗