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Biology subjects

Gu, Y.

Publications and source records attributed to Gu, Y..

At least 19 recordsLinked to original sources

FXR2 Promotes Autophagic Clearance of Sindbis Virus Capsid and Protects Against Viral Encephalitis

Autophagy protects neurons from viral infection by removing toxic viral components, but the host factors that recognize viral proteins and direct their clearance remain incompletely defined. Here, we identify fragile X mental retardation syndrome-related protein 2 (FXR2) as a mediator of protective autophagy during Sindbis virus (SINV) infection. Quantitative proteomic analysis of host proteins associated with SINV capsid identified FXR2, an RNA-binding protein linked to stress granules and protein homeostasis. Co-immunoprecipitation and immunofluorescence confirmed that FXR2 associates and colocalizes with viral capsid in infected cells. Loss of FXR2 increased capsid accumulation, reduced LC3 lipidation and autophagosome formation, and impaired p62 degradation following infection. Reconstitution of FXR2-deficient cells restored autophagy and promoted capsid clearance. Although FXR2 deficiency did not significantly increase viral replication, it enhanced virus-induced cell death, suggesting that FXR2 protects infected cells by limiting viral protein toxicity rather than by directly restricting virus production. Consistent with this model, both Fxr2-null and heterozygous mice exhibited increased mortality following neurotropic SINV challenge, and Fxr2-null mice developed greater neuronal degeneration, inflammation, and cell death despite viral titers comparable to those in wild-type animals. Together, these findings identify FXR2 as a previously unrecognized component of the antiviral autophagy pathway that promotes viral capsid clearance and protects neural tissue from infection-associated damage.

microbiology↗

Prior visual context accelerates the emergence of object representations

Our knowledge about how the world is structured allows for predictions about what objects we might see next. Visual context is known to impact the perception of subsequent objects, but we do not know what context does to the mental representation of those objects. Using MEG, we tested how a scene context changes the neural representation of visual objects, and whether the context simply enhances expected object representations, or if it acts to reorganise the temporal trajectory of object information in the brain. Using temporal generalisation decoding, we show that multiple dimensions of semantic information are shifted up to 200 ms earlier when the object and the prior context are congruent, and this temporally-shifted decoding was related to behavioural object recognition speed. This suggests that prior context can warp the temporal trajectory through which object representations are accessed and accelerate the emergence of semantic object representations in the mind.

neuroscience↗

Hypomagnetic field inhibits seed germination via ROS signaling and reprogramming transcriptome in Arabidopsis thaliana

The geomagnetic field (GMF) is a ubiquitous yet poorly understood environmental factor that affects plant growth and development. It has been suggested that the blue-light photoreceptor cryptochrome (CRY) functions as a critical magnetic-field sensor in birds and insects through the radical-pair mechanism (RPM). However, whether CRY acts as a bona fide transducer of GMF signals and what are the downstream cascades remain largely elusive in plants. To address these key issues, we generated hypomagnetic field (HMF) via Helmholtz coils and passive magnetic shielding to investigate the GMF deprivation effects in Arabidopsis thaliana. HMF significantly delays the germination speed without altering the final germination rate, suggesting that HMF specifically modulates germination kinetics rather than seed viability. Time-resolved transcriptomic profiling revealed a coordinated transcriptional shift characterized by downregulation of growth-promoting genes and concurrent upregulation of defense-related genes under HMF. This biphasic transcriptional reprogramming coincides with a significant increase of reactive oxygen species (ROS), linking redox perturbation to the germination delay. Consistently, supplementation with ROS-scavenging antioxidants (e.g., reduced glutathione and ascorbic acid) rescues both germination speed and the misregulated expression of a subset of HMF-responsive genes, suggesting the central role of ROS in mediating HMF bioeffects. Genetic analysis using cry1 cry2 double mutants further indicated that HMF-induced germination delay operates through both CRY-dependent and -independent signaling pathways, suggesting the involvement of additional magnetosensitive modules beyond the canonical CRY-based RPM. These findings suggest that the GMF acts as a positive environmental cue that fine tunes the growth-defense trade-off through a redox-dependent signaling.

plant biology↗

Spatiotemporal atlas resolves the mesenchymal-epithelial stem cell axis governing human hair follicle aging and pathology

How adult stem cell populations coordinate tissue regeneration across physiological and pathological states remains unclear. Hair follicles contain epithelial and mesenchymal stem cells that codetermine hair regeneration. Here, we integrate a multimodal spatiotemporal atlas with functional validation to define the mesenchymal-epithelial stem cell dynamics governing human hair follicle homeostasis, aging, and androgenetic alopecia. Aging is characterized by passive depletion of hDSC-derived regenerative cues, whereas AGA involves a shift of hDSC toward an inhibitory signaling hub that promotes HFSC dysfunction. We further pinpoint hDSC-secreted PTN as a key regenerative factor that promotes hair growth and counteracts androgen-induced growth suppression. This study provides a holistic framework of adult stem cell crosstalk across physiological and pathological states, offering a mechanistic roadmap to reinstate tissue regeneration.

cell biology↗

Spatial transcriptomics reveals selective vulnerability of cardiac neural crest-derived glial cells in human myocardial infarction

Cardiac neural crest-derived glial cells (CNGs) are recently identified glial cells that support cardiac autonomic innervation and maintain sympathetic-parasympathetic balance. Their fate in myocardial infarction (MI) is unknown. Here, we analyzed 16 human cardiac spatial transcriptomes spanning normal myocardium (n=4), infarct zone (n=5), border zone (inner, n=1; outer, n=3), and remote zone (n=3). CNGs (S100B+/GFAP+, CD68- spots) were selectively lost along a spatial gradient from healthy tissue to the infarct core (Spearman rho = -0.92, p = 4.5 x 10-7). Tissue-area-corrected analysis confirmed that CNG loss (26% retained in infarct zone vs. normal; p = 0.016) vastly exceeded overall tissue loss, indicating selective vulnerability rather than bulk tissue destruction. Mechanistically, oxidative phosphorylation (OXPHOS) activity in CNG-positive spots correlated positively with CNG survival (partial rho = 0.65, p = 0.009 after controlling for spot composition), consistent with a high metabolic demand underlying their ischemic sensitivity. Pyroptosis - but not ferroptosis or apoptosis - signatures correlated with CNG loss (partial rho = -0.67, p = 0.006). These findings identify CNGs as selectively vulnerable cellular components of the cardiac autonomic system in MI and nominate metabolic failure and pyroptosis as candidate mechanisms, providing a spatially resolved foundation for future mechanistic and interventional studies.

bioinformatics↗

Polygenic hierarchies of macroscale brain structural organisation

Different Magnetic Resonance Imaging-derived cortical, subcortical, and white matter measures are presumed to reflect different developmental and cellular processes, but how their genetic architecture is organised and the underlying cellular and developmental processes is unclear. We conducted genome-wide association studies of 2,326 imaging-derived phenotypes (IDPs) spanning twelve structural measures across the cortex, subcortex, ventricles, and white matter tracts in the UK Biobank (Nmax = 53,751), replicated in ABCD (Nmax = 5,119), identifying 14,176 experiment-wide significant loci and prioritizing 848 genes. We found that IDPs primarily cluster by measure into six families: brain size, cortical thickness, curvature, microstructural coherence, microstructural diffusivity, and orientation dispersion. This structure was preserved across prioritized genes, cell types, and developmental timing; brain size implicates first-trimester radial glia programs, while white matter coherence implicates adolescent astrocyte and oligodendrocyte lineages. Within individual measures, genetic effects were further organised along broad spatial gradients, with a principal gradient reflecting allometric scaling for most measures and secondary gradients showing correspondence with the sensory-association topographic axis across several measures. We identified 79 genes with spatially restricted effects along the cortex, with many aligning with these dominant gradients while a substantial subset showed additional spatial patterns. Together, these findings reveal a hierarchical organisation of the genetic architecture of macroscale human brain structure, spanning phenotype families, broad spatial gradients, and regionally restricted developmental programmes.

genomics↗

BCIJelly: An integrated ecosystem for brain-computer interface research

Brain-computer interface (BCI) research relies on multistage computational pipelines, but progress has been slowed by fragmented data formats, heterogeneous decoder implementations and hardware-specific deployment toolchains. Here, we introduce BCIJelly, a unified ecosystem that standardizes 18 BCI datasets into AI-ready inputs and integrates 15 benchmark decoders, 80 reusable modules, automated architecture search (AAS) and hardware-aware neuromorphic deployment. Our AAS constructs task-specific decoders without manual design and extends into a large language model (LLM)-driven closed-loop mode supporting single-task, multitask and cross-species decoder design. A single-command pipeline compiles trained decoders for neuromorphic hardware, reducing power consumption by 30 to 50 times while preserving decoding performance. An interactive visualization software enables code-free exploration of neural recordings and decoding outputs. BCIJelly is validated across five BCI paradigms (motor, visual, speech, emotion and auditory) in humans, macaques and mice, providing an extensible ecosystem connecting data standardization, decoder development, systematic evaluation and hardware-aware deployment for BCI research.

neuroscience↗

TRACER navigates rearrangement-driven sesterterpene chemical space via multimodal enzyme-product representation learning

Skeletal rearrangement drives the immense structural complexity of terpene, yet predicting it remains a formidable challenge due to sequence-function decoupling in terpene synthases. Here, we established TRACER (terpene rearrangement annotation via co-attentive enzyme-product representation), a multimodal framework mapping the latent associations between sequence-derived enzyme representations and product chemotypes. Retrospective validation proved TRACERs exceptional precision in predicting compound classes and discriminating skeletal rearrangement (SR) from non-skeletal rearrangement (NSR) pathways. TRACER-guided genome mining characterized two bifunctional synthases, FsPS and AcPS, uncovering four unprecedented carbon skeletons. Density functional theory calculations deciphered these cyclization cascades, pinpointing a critical 5/6/11 tricyclic intermediate as the key branching node for scaffold diversification. Mutagenesis and molecular dynamics simulations suggested that E305 in FsPS enables rearrangement by maintaining active-site water exclusion, whereas its alanine mutation causes premature carbocation quenching. Collectively, this work establishes a predictive paradigm for the rational discovery and mechanistic elucidation of complex terpene architectures.

synthetic biology↗

RADIX: a deep learning framework that maps root barriers across species and reveals genetic and environmental contributions

Root anatomical barriers, including the suberized and lignified walls of the endodermis and exodermis, and cortical aerenchyma, regulate water and nutrient transport, gas exchange, and rhizosphere interaction. Their adaptive function places them as an important target for breeding environmentally resilient plant species. Quantifying these structures at high resolution is a manual bottleneck that limits experimental scale. We present RADIX (Root Anatomy Deep- learning Image segmentation across species and platforms), a framework that adapts a large self-supervised vision-transformer foundation encoder (DINOv3), pre-trained on billions of natural images, to root anatomy by fine-tuning its encoder with a dense-prediction-transformer decoder. Transferring these general-purpose vision encoders to a specialized biological domain with a high-quality annotated dataset is what allows RADIX to generalize across species and imaging platforms. We train and evaluate it on the first expert-annotated benchmark of root anatomical structures at scale, comprising 1,695 high-quality fluorescence images spanning 17 monocot and dicot species, six anatomical structures, and three imaging platforms. RADIX segments all six structures at inter-annotator-level accuracy and generalizes to unseen species, genotypes, growth conditions, and an imaging platform from an independent laboratory. A single unified model surpasses monocot- and dicot-specialist models without sacrificing in-group accuracy. Predicted masks yield aerenchyma and suberin/lignin measurements matching expert annotation at [~]1.2 s per image with a single GPU, reducing weeks of manual analysis to minutes. Applying RADIX across genotypes, microbial treatments, and growth systems, we show that these cell type features form a coordinated, multidimensional, and context-dependent system shaped by genetic and environmental factors.

plant biology↗

Continuous target-specific mutagenesis and rapid gene evolution by diversity-generating retroelements in Escherichia coli

Sequence-programmable directed evolution systems have great potential to accelerate bioengineering. Diversity-generating retroelements (DGRs) are natural hypermutation systems widely distributed in prokaryotes and bacteriophages with the capacity to introduce diverse mutations at template-specified sites of target genes. Here, we show that DGRs can be installed in E. coli and reprogrammed for the continuous, iterative mutagenesis of user-defined target genes. We show that the DGR template RNA can be reprogrammed for gene- and residue- specific mutagenesis, leaving untargeted, adjacent residues unchanged. Furthermore, we establish continuous DGR-enabled mutagenesis with F-plasmid-mediated horizontal gene transfer of target genes (HGT-DGR) into a new host for the progressive accumulation of target- specific mutations. Iterative HGT-DGR mutagenesis over seven cycles yielded an average mutation load of approximately 6% across adenine positions in the target segment, generating a diverse library of variants comprising 40% mutant sequences, with a median pairwise Hamming distance of 4 among mutant variants. HGT-DGR enables iterative diversification of either the same or different user-specified segments of the target gene, as demonstrated with the directed evolution of the M. mazei pyrrolysyl-tRNA synthetase for non-canonical amino acid incorporation. HGT-DGR provides a simple, low-cost, sequence-programmable system that enables iterative, position-specific and tunable in vivo mutagenesis of any target sequence for applications in biotechnology and medicine.

synthetic biology↗

From Hodgkin-Huxley to Pretrained Neural Inference AI

High-density probes record from thousands of neurons simultaneously, yet resolving single-neuron identity remains an illposed inverse problem. While detailed simulations precisely characterize the biophysical forward process, their utility for interpreting brain signal remains unclear. Here we show that biophysical simulations of population neuronal electrical signals serve as an effective bridge between theory and experiment. By pre-training artificial neural networks exclusively on large-scale synthetic data, we demonstrate robust zero-shot generalization across diverse brain regions, experimental paradigms and species, enabling the accurate inference of single-unit activities and cell-type properties without exposure to real data. Further-more, uncovering a substantial population of functionally competent but weakly active neurons systematically obscured by conventional heuristics, our framework resolves a long-standing discrepancy regarding ocular dominance in mouse primary visual cortex. These findings establish biophysical simulations as a reference standard, bridging the gap between theoretical understanding and experimental observation through data-driven inference.

neuroscience↗

Partial epithelial-to-mesenchymal transition mediates profound gap closure through growth and fluidization

Epithelial gap closure is essential for maintaining tissue integrity during development and wound healing. Previous studies have shown that closure of small gaps is driven by actomyosin purse-string contraction and traction forces generated at the gap edge. Here, we show that millimeter-scale circular gap closure in mouse epicardial (MEC1) monolayers is driven primarily by growth-mediated compressive stresses. Compared with MDCK monolayers, MEC1 cells close gaps more rapidly with reduced undulation near gap edge through coordinated tissue-wide extension-contraction. The collective closing dynamics can be modulated by partial epithelial-mesenchymal transition induction and Rho kinase inhibition. By integrating tissue and cell kinematic analyses, traction-force mapping, and a continuum framework that decomposes tissue strain rates into growth-, elastic-, and fluidity-related contributions, we reveal that growth-generated compression drives inward tissue flow, while elastic cell elongation and fluid-like tissue remodeling through cell-cell intercalation act synergistically to accommodate deformation and promote robust collective gap closure.

biophysics↗

Engineered probiotic Escherichia coli-mediated intestinal nicotine clearance alleviates nonalcoholic steatohepatitis in mice

Nicotine accumulates in the gut and drives non-alcoholic steatohepatitis (NASH) via the gut-liver axis, yet no effective clinical intervention is currently available. To address this challenge, the probiotic Escherichia coli Nissle 1917 (EcN) was engineered for in situ nicotine clearance in the gut. Mutational screening of nicotine oxidoreductase 2 (PpNicA2) identified a highly active variant, PpNicA2A107R. Its incorporation into EcN together with an electron transfer protein (CycN) and a newly identified transporter (T3/T7) yielded 80% nicotine-degrading activity. Chromosomal integration of this module generated a stable strain, EcN-N12, which in NASH mouse models depleted intestinal nicotine, rescued hepatic lipid metabolism, alleviated tissue damage, and intercepted the nicotine-mediated gut-liver axis pathological progression. This work thus offers an effective and clinically translatable approach for nicotine-associated diseases.

synthetic biology↗

SOX8-USP7-PGC-1α axis enhances thermogenesis in brown adipocytes

Obesity is one of the most prevalent diseases worldwide. Increasing thermogenesis to enhance energy expenditure has emerged as a promising therapeutic strategy. In an effort to identify new regulatory targets in thermogenic adipocytes, we found that SOX8 is correlated with obesity and serves as a novel marker of classical brown adipocytes in both humans and mice, upregulating during acute cold exposure. Functional studies further demonstrated that adipocyte-specific knockdown of SOX8 leads to obesity and metabolic dysfunction in mice. Mechanistically, SOX8 directly interacts with USP7 and stabilizes PGC-1 by reducing its K48-linked polyubiquitination. AAV-Rec2-mediated SOX8 overexpression initially enhanced energy expenditure, improved insulin sensitivity, and alleviated metabolic dysfunction in HFD-fed mice. However, prolonged SOX8 overexpression induced compensatory metabolic maladaptation, characterized by reduced energy expenditure, impaired glucose homeostasis, and mitochondrial structural disruption. These findings reveal a novel SOX8-USP7-PGC-1 regulatory axis in brown adipocytes, and reveal a previously unrecognized time-dependent effect of sustained thermogenic activation, highlighting SOX8 as a promising therapeutic target for obesity and metabolic syndrome.

cell biology↗

Decoding Immune Reconstitution Failure in People Living with HIV through Single-cell Genomics

Immune non-responders (INRs), a subset of people living with HIV (PLWH), fail to achieve full immune reconstitution and remain at increased risk of morbidity, mortality, and non-AIDS-related illnesses. As the mechanisms underlying this impaired immune recovery remain poorly understood, we performed single-cell multi-omics profiling on peripheral blood mononuclear cells from 43 INRs, 47 immune responders and 53 healthy donors. Our dataset comprises 2,744,009 transcriptomes and 1,226,658 chromatin-accessibility profiles across 58 identified immune cell types. INRs exhibited markedly elevated inflammatory signaling, increased apoptotic activity, and dysregulation of immune-activating ligand-receptor interactions. Additionally, we identified 2,996 interaction cis-eGenes and 5,938 cis-caPeaks, and validated key cell type-specific cis-xQTL effects associated with immune reconstitution failure. Furthermore, we identified 3,551 sc-eQTLs and 872 cell-state interaction eQTLs (ieQTLs) in CD4+ T cells. A genotype-specific upregulation of OAS3 in INRs, likely regulated by STAT1, was identified based on these results. We developed scPRISM (single cell Predictive Reconstitution Immune Status Model), a multi-modal framework that integrates scRNA-seq and scATAC-seq data to perform the dual tasks of differentiating disease states and predicting gene expression from chromatin accessibility, thereby deciphering the cell type-specific cis-regulatory basis of the disease. Our study delineates the transcriptional and epigenomic landscape of immune dysregulation in INRs and provides new genetic insights into HIV-associated immune reconstitution failure. These findings offer a foundation for developing biomarkers and precision therapies to restore immune function in PLWH.

genetics↗

Comprehensive Complete-Genome Analysis of Lactobacillaceae and Bifidobacteriaceae Reveals Strain-Specific Metabolic Interactions in Chinese Gut Microbiota

Bifidobacteriaceae and Lactobacillaceae are key probiotic families and widely used in food production, yet a comprehensive understanding of strain functions and their gut microbial interactions based on complete genomes remain understudied. Here we constructed a complete-genome dataset of 3,300 strains from these two families, including 1,151 newly isolated from China. Compared with draft assemblies, complete genomes substantially recovered a gene functional landscape encompassing stress tolerance, surface exopolysaccharide synthesis, nutrient utilization, and mobile genetic elements. Major species from both families exhibited a prevalence >60% in the Chinese population, far higher than that in US/Dutch cohorts. Notably, as a core probiotic species with remarkable genomic plasticity and gut-adaptive potential, Lactiplantibacillus plantarum stood out in our dataset for its enriched functional profile and was particularly abundant in the Chinese population. Moreover, compared with non-Chinese genomes, our isolates of key species displayed less metabolic complementarity and stronger competition with potentially pathogenic keystone species in the gut, thereby linking strain origin to enhanced probiotic potential and ecological fitness to benefit human gut health.

microbiology↗

Microbial network rewiring mediates the function-biosafety trade-off in transboundary Pamir lakes

The Pamir Plateau is a transboundary water tower whose source lakes serve as critical biogeochemical hubs with implications for downstream freshwater security. However, it remains unclear how environmental shifts in these high-altitude lakes reshape the microbial communities that drive ecosystem functioning and water safety. Here, we conducted a multi-omics survey across 20 lakes spanning Chinese and Tajikistani Pamir. Our results revealed that prokaryotes exhibited lower diversity but higher among-lake connectivity in China, while eukaryotes showed higher diversity but stronger dispersal limitation. These contrasting biogeographic responses triggered profound rewiring of microbial associations. Under intensified anthropogenic pressures, Chinese cross-kingdom networks decoupled from environmental constraints and became more centralized and complex. Conversely, Tajikistani lakes maintained more modular networks governed by hydrochemical filtering. Critically, this rewiring mediated a trade-off between multifunctionality and potential biosafety risk, with higher element cycling abundances in Chinese lakes, whereas Tajikistani lakes harbored larger biosafety burden dominated by virulence, pathogen, and toxic-algae potential. Incorporating network topology also substantially improved the prediction of these ecological consequences. These findings highlight the importance of network-informed monitoring and management strategies to safeguard ecosystem sustainability in transboundary Pamir lakes under global change.

microbiology↗

H2O: A Foundation Model Bridging Histopathology to Spatial Multi-Omics Profiling

Spatial omics technologies have revolutionized the molecular profiling of tissues but remain constrained by high costs and limited scalability. While hematoxylin and eosin (H&E) staining is ubiquitous, it lacks molecular specificity. Here, we present H2O (Histopathology to Omics), a generalist AI framework that bridges the modality gap between histopathology and spatial multi-omics, enabling the direct inference of spatial transcriptomics (ST) and proteomics (SP) landscapes from routine H&E images. H2O integrates Vision Transformers (ViT) with Large Language Models (LLM) via contrastive learning to align histological morphology with semantic molecular knowledge. This cross-modal approach allows the model to incorporate spatial expression profiles into histological pattern recognition, effectively decoding the molecular heterogeneity underlying tissue morphology. Trained on a pan-tissue dataset of 1.3 million paired H&E-spatial patches across 25 organs and cancer types, H2O predicts spatial omics expression from histology with high concordance to sequenced measurements and consistently outperforms state-of-the-art models across three cancer benchmarks. Notably, H2O recovers the MIF-CD74/CD44 signaling axis directly from H&E images, highlighting its capacity to infer biologically meaningful cell-cell communication without molecular profiling. Applying on three additional public cohorts covering fetal and paediatric thymus tissues, human metastatic lymph node, and breast cancer, encompassing human development, 3D spatial frameworks, and integrative multi-omics, H2O yields biologically concordant insights, demonstrating superior accuracy, robustness, and generalizability across real-world applications in diverse scenarios. H2O converts routine histopathology into a portal for spatially resolved multi-omics profiling by computationally generating transcriptomic and proteomic landscapes, thereby enhancing tissue phenotyping and enabling scalable, integrative tissue-atlas construction.

bioinformatics↗