Biology subjects

Yi, C.

Publications and source records attributed to Yi, C..

At least 19 recordsLinked to original sources

bioRxiv2026

Impaired astrocytic Cx43 syncytial network in lateral habenula affects synaptic connectivity and drives adolescent stress-induced depression

Adolescent depression is a major neuropsychiatric disorder induced by early life stress; the underlying cellular mechanisms instigating pathological circuit malformation remain unclear, and, consequently, effective therapeutic strategy is limited. Here, we analysed the contribution of astrocytes to early life stress-induced adolescent depression using a mouse model of parental separation. We identified a previously unrecognised regional specialisation of lateral habenula (LHb) astrocytes, characterised by compact cellular domains, abundant leaflets, and enhanced Cx43 gap junctional coupling. Parental separation selectively reduced astrocytic Cx43 expression and gap junctional communication in the LHb, which was accompanied by profound astrocytic atrophy and loss of leaflets. Single-cell sequencing further revealed that parental separation induces a broad reorganisation of LHb astrocyte transcriptional states, including metabolic, stress-response, and inflammatory programs; moreover, it specifically reduces astrocyte-neuron communication. Consistent with this, we found that structural remodelling of LHb astrocytes affected tripartite synapse geometry, resulting in impaired excitatory and inhibitory synaptic transmission, and neuronal Ca2+ hyperexcitability, all ultimately associated with depressive-like behaviours. Selective knockdown of astrocytic Cx43 in the LHb recapitulated these pathological changes and translated into depressive-like behaviours. Mechanistically, we found that impaired Cx43 gap junctional communication is associated with excessive astrocytic Ca2+ dynamics, resulting in Rac1-GTPase activation and decreased p-Ezrin levels. In vivo inhibition of LHb astrocytic Ca2+ signalling rescued astrocytic atrophy and depressive-like behaviours following parental separation. Together, our findings establish a Cx43-Ca2+-Rac1-p-Ezrin pathway that links gap junction malfunction to structural remodelling of astrocytes and disruption of neuron-astrocyte interactions in the developing LHb. Our study reveals astrocytic Ca2+ dysregulation as an active downstream effector of Cx43 dysfunction and identifies a regionally specialised astrocytic mechanism through which early-life stress disrupts synaptic transmission and neuronal function during adolescence, providing a potential cellular target for intervention in adolescent depression.

neuroscience↗

bioRxiv2026

Long-form hibernation-promoting factor coordinates 100S assembly and translational repression

Ribosome hibernation mediated by long-form hibernation-promoting factor (HPF) requires coordination of ribosome dimerization and translational repression, but how these functions are integrated remains unclear. Here, we present cryo-EM structures of native 100S from a deep-sea Bacillus isolate, revealing a conformationally heterogeneous 100S population. Beyond the established roles of the HPF N-terminal domain (NTD) in decoding-center occlusion and the C-terminal domain (CTD) in dimerization, our analyses reveal additional contributions from the Linker and a charged CTD surface near the 16S rRNA 3' terminus containing the anti-Shine-Dalgarno (aSD) sequence. Linker substitutions differentially affect translational repression while retaining 100S formation, with distinct effects of the two Linker segments. Mutation of the charged CTD surface enhances translational repression while retaining robust 100S formation, suggesting an additional role beyond CTD-mediated ribosome dimerization. Functional analyses in an E. coli cell-free translation system further show that the inhibitory activity of individual HPF regions varies with translational context. Together, these findings support a modular model in which the NTD, Linker, and CTD make distinct but interconnected contributions to 100S assembly and translational repression.

biochemistry↗

bioRxiv2026

A brain-tumour axis links chronic stress to gastric cancer progression through NPY signalling

Chronic stress promotes gastric tumour growth, but the central neural pathways remain largely enigmatic. Here, we identify a brain-tumour axis, implicating the central amygdala (CeA) activity in promoting gastric cancer growth through sympathetic neuropeptide Y (NPY) signalling occurring within the tumour. Using clinical datasets, patient samples, pathway tracing, electrophysiology and chemogenetic manipulation, we demonstrate that stress selectively increases NPY Y1 receptor (NPY1R) synthesis in the patients gastric cancer tissue; moreover, the NPY1R density correlates with advanced cancer stage and poor prognosis. In mice, daily constraint chronic stress enhances CeA excitability and promotes sympathetic neurotransmitter norepinephrine release within the tumour microenvironment. Norepinephrine, in turn, increases tumour endogenous NPY/NPY1R production and the activation of downstream MAPK/Erk1/2 signalling pathway, which drives cancer cell proliferation and invasion. Manipulating CeA neuronal activity alone can regulate tumour growth, whereas selectively blocking tumour NPY1R prevents stress-induced tumour progression in vivo and cancer cell migration in vitro. This study identifies a central-to-peripheral circuit linking chronic stress to gastric cancer growth, and highlights NPY1R as a potential therapeutic target.

Cancer Biology↗

bioRxiv2026

Metabolic compensation via gluconeogenesis explains the non-essentiality of glycogen phosphorylase as an insecticidal target in Plutella xylostella

Glycogen phosphorylase (GP) catalyzes the rate-limiting step of glycogenolysis and occupies a central position in insect carbohydrate metabolism, supplying precursors for chitin biosynthesis. Acyl urea compounds structurally related to benzoylphenylurea (BPU) insecticides are potent inhibitors of mammalian GP, raising the question of whether insect GP could serve as an independent insecticidal target. Here, we systematically evaluate this possibility in the diamondback moth Plutella xylostella. We show that a mammalian GP inhibitor (GPI) potently inhibits recombinant PxGP (IC50 = 2.96 nM), while the BPU insecticide diflubenzuron (DFB) does not. Molecular docking and MM/GBSA analysis predict that this selectivity reflects differential side-chain engagement: GPI is predicted to occupy the allosteric site at the dimer interface via contacts with seven residues spanning both subunits ({Delta}G = -34.63 kcal/mol), whereas DFB's difluorobenzoyl moiety is predicted to remain solvent exposed without productive protein contacts ({Delta}G = -29.29 kcal/mol). Despite potent in vitro inhibition, GPI exhibits no insecticidal activity, and RNAi-mediated knockdown of PxGP (confirmed by enzyme activity measurements showing ~29% reduction in per-larva GP-a activity) does not impair development or survival. We provide evidence that insects compensate through a multi-layered metabolic response: upregulation of gluconeogenic enzymes (PEPCK, G-6-Pase), selective upregulation of glycogen branching enzyme (GBE) but not -amylase, and changes in protein content suggestive of catabolic substrate mobilization. Fitness assessment reveals transient larval weight loss (24-48 h) with complete recovery of pupal weight, adult wing morphology, and female fecundity, indicating that the metabolic compensation response is ultimately effective in sustaining development. These findings suggest that GP is functionally non-essential under these conditions, likely through a combination of gluconeogenic compensation and the availability of alternative carbon sources, and highlight the importance of considering metabolic network redundancy in target-based insecticide design.

biochemistry↗

bioRxiv2026

A dual-factor complex governs archaeal ribosome hibernation by sensing energy status

Efficient coupling of cellular energy status to ribosome regulation is fundamental for cellular survival. Here, we identify the Archaeal Ribosome regulatory Complex (ARC)--a previously uncharacterized dual-factor complex comprising ARC-P and ARC-A. Cryo-EM reveals that ARC anchors to the small ribosomal subunit, establishing a stringent blockade of the tRNA and mRNA paths via an electrostatic wedge mechanism. This hibernation state is modulated by energy status: the complex remains stably associated under low-energy conditions, whereas ATP binding triggers rapid mobilization. Genetic analyses demonstrate that ARC acts as a translational brake essential for preserving ribosomal structural integrity, with ARC-A serving as the primary inhibitory factor. Notably, while the loss of ARC accelerates growth, it impairs recovery in proportion to stress severity. Phylogenomic analysis identifies ARC as an evolutionarily novel and widely distributed dual-factor system, revealing a conserved regulatory strategy for metabolic-translational coupling across diverse archaea. Our findings define a fundamental strategy where modular complexes integrate metabolic sensing with mechanical sequestration to balance growth and persistence.

biochemistry↗

bioRxiv2026

TSTScope Unifies Single-Cell Multi-Omics to Identify Functional T Cell States Predictive of Immunotherapy Response

Immune checkpoint blockade (ICB) can produce durable responses in cancer, but reliable predictors of benefit are still lacking. CD8 tumor-specific T cells are essential for ICB efficacy, yet it remains unclear which functional states of these cells determine therapeutic success. To address this, we developed TSTScope, an interpretable deep learning framework that integrates single-cell transcriptomic and T-cell receptor sequencing data to generate unified representations of CD8 T-cell identity. By applying TSTScope to non-small cell lung cancer (NSCLC) datasets, we characterized the gene programs defining tumor specificity and computationally inferred a population of potential TSTs. Crucially, we demonstrate that clinical response is not a product of TST abundance, but is instead governed by their functional state. We derived the MPR score, a metric capturing this functional potential, which proved to be a robust predictor of treatment outcomes. In an independent validation cohort, the MPR score significantly outperformed established biomarkers. Collectively, TSTScope identifies a distinct functional state of tumor-specific T cells as a primary determinant of ICB efficacy, providing both a mechanistic framework and a potent tool for precision immunotherapy.

bioinformatics↗

bioRxiv2026

A comprehensive analysis of flagellar mutations in Vibrio cholerae: Trade-off mechanisms between motility loss and host adaptability

IntroductionCholera, caused by Vibrio cholerae, is a severe diarrheal disease threatening global health. The flagellum of V. cholerae functions not only for motility but also as an environmental sensor regulating virulence. The trade-off mechanism between motility loss and enhanced host adaptation remains unclear. ObjectiveThis study aimed to elucidate how flagellar mutations, which lead to a loss of motility, affect host adaptability in V. cholerae and to uncover the underlying molecular basis. MethodsWe analyzed 3,135 cholera-related samples to identify mutation hotspots in flagellar genes. A relevant flagellar mutant library was constructed and assessed for host adaptability. Multiple approaches, including molecular, genetic, transcriptomic, and proteomic analyses, were applied to dissect the FlgM-mediated pathway, with key findings revalidated in an adult mouse model using a specifically constructed 6N-labeled mutant pool. ResultsBig data analysis reveals those flagellar mutations in V. cholerae cluster in key structural and regulatory genes, including flhB, fliA, fliF, fliD, and fliM. Flagellar mutations led to a scenario where the secretion level of the regulator FlgM was negatively correlated with host adaptability. Intracellular FlgM inactivates either the {sigma}28 factor FliA directly or acts through the VarS/VarA-CsrA/BCD system, ultimately leading to the derepression of the quorum-sensing master regulator named hapR. HapR can directly bind to the promoters of genes involving in methionine transportation to regulate adaptability of V. cholerae. The 6N-labeled mutants pool experiment reconfirmed that motility loss promotes host adaptability via the FlgM-FliA-HapR-methionine axis. ConclusionOur findings demonstrate that secretion levels of the flagellar regulator FlgM drive an adaptive shift in V. cholerae from motility to host adaptability, mediated through quorum sensing and methionine metabolic reprogramming. This reveals a novel mechanism underlying bacterial evolution and pathogenicity.

microbiology↗

bioRxiv2025

MAGNET: an all-in-one foundation model for cross-modal and cross-dimensional microscopic image restoration

The application of emerging Foundation models in current microscopy has remained limited due to task-specific model designs, strong modality dependence and insufficient robustness under complex degradations. Here, we introduce MAGNET (Microscopic All-in-one General fouNdation model for imagE resToration), the first end-to-end All-in-One foundation model designed for universal microscopic image restoration. MAGNET integrates multi-task, cross-modal and cross-dimensional (2D + 3D) image restoration capabilities within a single unified architecture, and it is specifically designed to handle composite degradations in practical imaging systems. The framework comprises three components: (i) a task-aware, prompt-guided feature enhancement module for adaptive learning across diverse degradations; (ii) an LIIF-based reconstruction module enabling continuous, resolution-adaptive restoration; and (iii) a dimension-compatible triple-plane projection module supporting both 2D and 3D data. Trained on large-scale datasets spanning 5 major microscopy modalities (structured illumination, confocal, light-sheet, wide-field and two-photon) and 8 representative restoration tasks, MAGNET achieves state-of-the-art performance across super-resolution, denoising, deblurring, background suppression, isotropic reconstruction, aberration correction, de-scattering and virtual staining. Beyond supervised training, MAGNET supports direct inference on unseen systems, efficient few-shot fine-tuning and self-supervised test-time optimization, enabling robust performance across diverse data and imaging conditions. MAGNET serves as a unified, generalizable, and scalable computational framework for microscopy, enabling more efficient and reliable downstream analyses in cell biology, neuroscience, and pathology.

cell biology↗

bioRxiv2025

DINOcell: Learning Generalizable Perturbation Effects through Self-Distillation

AO_SCPLOWBSTRACTC_SCPLOWPredicting cellular responses to therapeutics is a promising approach for novel target discovery. However, state-of-the-art computational models designed to predict perturbation effects struggle to generalize and outperform simple baselines. We present DINOcell, a weakly supervised framework that adapts self-distillation to single-cell transcriptomics for predicting perturbation effects. We demonstrate that DINOcell outperforms baselines in predicting the effects of single gene perturbations. Furthermore, DINOcell accurately predicts non-additive effects of combination perturbations, indicating its capacity to model complex genetic interactions. Finally, we show that DINOcell learns representations that capture biological signals and is a promising, generalizable approach for in silico perturbation modeling, providing a valuable tool for accelerating therapeutic target discovery.

bioinformatics↗

bioRxiv2025

A high-quality bread wheat genome unravels adaptive evolution of wheat end-use quality

Understanding the genetics of superior dough performance is essential for improving wheat end-use quality. Here, we presented a de novo assembly of the genome of JM44, a Chinese wheat cultivar known for its exceptional end-use quality. The JM44 genome achieved reference-level quality (QV = 66.74), depicting a complete picture of complex regions containing gluten genes. Our microsynteny analysis across the Triticum-Aegilops complex showed that high-molecular-weight glutenin subunits (HMW-GSs) loci are highly conserved, while low-molecular-weight glutenin subunits (LMW-GSs) and -/{beta}-gliadins exhibited greater structural variation. These variable loci appear to have been preferentially selected by humans and contributed substantially to the evolution of wheat quality traits. Moreover, we observed that epistatic interactions between gluten genes are strong in modern cultivars, but markedly weaker in landraces, indicating the importance of epistatic selection during modern breeding. Our findings shed light on the genomics and evolution of wheat quality traits, providing valuable guidance for future breeding efforts.

genomics↗

bioRxiv2025

Integrated landscape genomics reveals biogeography and climate-driven local adaptation in high-altitudes

High-elevation environments harbor unique species adapted to altitudinal and environmental extremes. However, due to logistical challenges of sampling such species throughout their distribution across steep and varied terrains, studies often lack comprehensive evidence to understand patterns of population divergence, local adaptation, and how current adaptations may influence future vulnerability. In this study, we utilized Tibetan Partridge (Perdix hodgsoniae), a high-altitude endemic bird found between 2800-5000 meters across the arid western and humid northeastern regions of the Sino-Himalayan landscape. This regions complex topography-characterized by tall mountains, deep valleys, and contrasting climatic conditions provided opportunities for investigating population divergence, local adaptation, and climate-related vulnerability. We integrated population-scale whole-genome sequencing with ecological, climatic, landscape, and morphological data to examine current patterns of local adaptation and forecast future risks. Our findings show that both biogeographic barriers and climatic variation drive rapid population divergence in P. hodgsoniae, reflected in distinct morphological traits and population genetic structure. Western populations, inhabiting dry and fragmented landscapes, exhibit adaptations to temperature extremes with low genetic diversity, reduced habitat suitability, limited gene flow, and weak connectivity--factors that increase their vulnerability to future environmental changes. In contrast, northeastern populations, living in more humid regions, show genetic adaptations linked to precipitation, maintain high genetic diversity and habitat connectivity, and may serve as evolutionary refugia under future climate scenarios. This study underscores the value of integrating genomic, ecological, and landscape data to reveal mechanisms of divergence and adaptation, and to develop robust predictions for conservation planning under rapidly changing environmental conditions.

evolutionary biology↗

bioRxiv2025

A single-cell fixed RNA profiling of liver fibrosis progression and regression reveals SEMA4D and LMCD1 as key mediators of fibrogenesis

Liver fibrosis progression and regression are dynamic processes involving diverse hepatic and immune cell populations. Here, we utilize single-cell fixed RNA profiling (FLEX) of a TAA-induced mouse liver cirrhosis model, with and without a recovery phase, to depict the cellular landscape and molecular mechanisms of fibrosis resolution. The regression phase was characterized by the emergence of pericentral hepatocytes enriched in detoxification and antioxidant genes (e.g., Cyp2e1, Txn1), which secreted Rarres2 to modulate hepatic stellate cell (HSC) function. This was accompanied by the upregulation of scar-resolving genes (Mmp14, Ctsl), restoration of fenestrae in liver sinusoidal endothelial cells, anti-inflammatory phenotypes of Kupffer cells, a decrease in fibrogenic cholangiocyte subsets, and recovery-associated signatures in NK/T cells, B cells, and neutrophils. In contrast, SEMA4D secreted by monocyte-derived macrophages during fibrosis progression activated Plxnb2 HSCs, and its blockade attenuated fibrosis in vivo. Furthermore, LMCD1 was identified as a novel marker for HSC activation and regulation. This single-cell atlas reveals key transcriptional programs and intercellular signaling pathways dependent on the fibrotic condition, offering new therapeutic targets for liver cirrhosis.

cell biology↗

bioRxiv2025

Phased ERK function on muscle stem cell plasticity in axolotl

The precise regulation of muscle stem cell (MuSC) plasticity remains poorly understood. While studies have suggested that Pax7+ MuSCs in vertebrate limbs are committed solely to myogenic lineages during regeneration, we previously observed during axolotl tail regeneration, Pax7+ MuSCs contribute to the fibroblast and chondrocyte mesodermal lineages. However, the underlying mechanism is unclear. Here, we show that the duration of ERK signaling plays an important role in MuSCs cell fate. We observed that ERK exhibits sustained activation after tail amputation that is followed by subsequent inhibition. We found that ERK activation initiates MuSCs plasticity switch toward a trunk fibroblast fate by repressing PAX7 expression. However, subsequent inhibition of ERK activity is essential for the transition of trunk fibroblast to fin fibroblast. In addition, we found that the TGF-{beta}/SMAD2 cascade as a downstream mediator of ERK-driven regulation of MuSC plasticity towards fibroblast and chondrocyte during tail regeneration. Together, we uncovered a new phased stem cell regulatory mechanism linking injury-induced ERK signaling to stem cell plasticity regulation, offering new insights with potential implications for regenerative medicine.

developmental biology↗

bioRxiv2025

Fast in vivo deep-tissue 3D imaging with selective-illumination NIR-II light-field microscopy and aberration-corrected implicit neural representation

Near-infrared II (NIR-II) microscopy, which enables in vivo deep-tissue visualization of vasculature and cell activities, has been a promising tool for understanding physiological mechanisms. However, the volumetric image speed of the NIR-II microscopy is hindered by scanning strategy, causing limitations for observing instantaneous biological dynamics in 3D space. Here, we developed a NIR-II light-field microscopy (LFM) based on selective-illumination and self-supervised implicit neural representation (INR)-reconstruction, which allows ultra-fast 3D in vivo imaging (100 volumes/s). Through integrating INR with view-wise aberration correction, we could conquer the artifacts induced by the angular subsampling and refractive index variation, achieving single-cell resolution at a volume of 550 m diameter and 200 m thickness. The volumetric selective-illumination overcomes the influence of out-of-focus background, together with the low scattering advantage of NIR-II wavelength, extending the imaging depth to 600 m. The developed aberration-corrected implicit neural representation reconstruction (AIR) NIR-II LFM showcases its capability by monitoring hemodynamics of mouse brain under norepinephrine and flow redistribution of ischemic stroke in 3D vasoganglion, as well as noninvasively tracking immune cell activities inside subcutaneous solid tumor through intact skin. This approach represents a significant advancement in 3D in vivo imaging, holding great potential in biomedical research and preclinical studies.

neuroscience↗

bioRxiv2025

Divergent stem cell mechanisms governing the primary body axis and appendage regeneration in the axolotl

Exploring the fundamental mechanisms of organ regeneration is crucial for advancing regenerative medicine. The axolotl tail represents a unique opportunity to study regeneration of the primary axis including segmented muscle, vertebrae and skin. During tail development, muscle stem cells (MuSCs) displayed expected specificity to the muscle lineage. Tail amputation, however, induced expansion of MuSC potential yielding clonal contribution to muscle, connective tissue including cartilage, pericytes, and fibroblasts. This expanded potential was not observed during limb regeneration, and cross-transplantation showed these differences in potential are intrinsic. ScRNA-Seq profiling revealed that tail MuSCs revert to an embryonic mesoderm-like state. Through genetic manipulation involving the over-expression of constitutively active TGF-{beta} receptors or Smad7 (antagonist of TGF-{beta} signaling) in MuSCs, we demonstrated that the levels of TGF-{beta} signal determine the fate outcome of MuSCs to connective tissue lineage or muscle respectively. Our findings illustrate a fundamental difference between regeneration of primary axis versus limb and offers a novel stem cell source for regeneration of axial skeletal tissues.

developmental biology↗

bioRxiv2025

m3C is a mitochondrial mRNA modification which promotes tumor progression

Mitochondrial mRNA modifications are suggested to play a role in fine-tuning mitochondrial gene expression and function. However, the epitranscriptomic landscape of mitochondrial mRNA (mt-mRNA) remains poorly explored. Here, we uncover N3-methylcytosine (m3C) as a novel mt-mRNA that is catalyzed by METTL8, an enzyme previously known to modify mt-tRNA. Transcriptome-wide mapping reveals that METTL8-dependent m3C is enriched in mt-mRNAs encoding complex I subunits of the respiratory chain. Additionally, METTL8 is highly expressed in various cancers, notably in cervical cancer. METTL8 depletion impairs cell migration in vitro and reduces tumor growth in mouse xenografts. Finally, transcriptomic analyses further link METTL8 expression to oncogenic pathways, mitochondrial functions and complex I activity. Together, our results reveal a novel mitochondrial mRNA modification that promotes cancer progression.

cell biology↗

bioRxiv2024

MethylQUEEN: A Methylation Encoded DNA Foundation Model

DNA 5-methylcytosine (5mC) modification plays a pivotal role in many biological processes, yet 5mC information and pattern hidden behind remains to be explored. Here, we develop Methylation Language Model based on Quintuple Bidirectional Transformer (MethylQUEEN), a novel pre-trained DNA methylation foundation model capable of sensing methylation states and covering the genome-wide methylation landscape. Through tailored methylation-prone pre-training, MethylQUEEN effectively captured epigenetics information hidden within the DNA sequences: it accurately traces DNAs tissue-of-origin, and successfully recovers the expression profile through methylation states. Integrative analysis on MethylQUEENs attention scores also enables us to reveal the unique methylation status of a tissue for precise disease detection, and identifying key regulatory 5mC sites for disease intervention. As a result, MethylQUEEN signifies a new paradigm in methylation analysis for various biological problems. Besides, our study demonstrates the effectiveness of directly integrating methylation information into pre-training, offering new perspectives and methodologies for a range of methylation-related biological processes. It serves as an initial exploration for the development of more comprehensive epigenomic models.

genomics↗

bioRxiv2024

Benchmarking deep learning methods for biologically conserved single-cell integration

Advancements in single-cell RNA sequencing (scRNA-seq) have enabled the analysis of millions of cells, but integrating such data across samples and methods while mitigating batch effects remains challenging. Deep learning approaches address this by learning biologically conserved gene expression representations, yet systematic benchmarking of loss functions and integration performance is lacking. This study evaluated 16 integration methods using a unified variational autoencoder framework, incorporating batch and cell-type information. Results revealed limitations in the single-cell integration benchmarking index (scIB) for preserving intra-cell-type information. To address this, we introduced a correlation-based loss function and enhanced benchmarking metrics to better capture biological conservation. Using annotations from the Human Lung Cell Atlas and Human Fetal Lung Cell Atlas, our approach improved biological signal preservation. This work highlights the need for biologically informed metrics in scRNA-seq integration and offers guidance for future deep learning developments.

bioinformatics↗