Biology subjects

Cui, Q.

Publications and source records attributed to Cui, Q..

At least 19 recordsLinked to original sources

bioRxiv2026

ASTRA enables zero-shot super-resolution of spatial transcriptomics across capture geometries

Spatial transcriptomic super-resolution recovers tissue organization obscured by coarse sampling, but fitting a model to each section greatly increases computational cost and reduces practicality. We introduce ASTRA, a cross-platform pretrained model that reconstructs expression from histology and measured RNA by zero-shot inference. Training with arbitrarily shaped count-bearing regions, termed parents, enables one frozen model to accommodate dense bins and separated spots. Across six held-out Visium HD sections, ASTRA achieved higher correlations under dense-bin and pseudo-Visium sampling, lower dense-bin errors and substantially shorter processing times than existing methods. It improved colorectal tissue segmentation and tumor-boundary recovery. In real colorectal Visium, reconstruction spatially resolved a stromal transcriptional state supported by measured RNA. The same checkpoint supported regional and nucleus-associated analyses across 43 invasive lobular carcinoma sections and within-spot interpretation across 92 triple-negative breast cancer sections. ASTRA establishes a reusable framework for practical, cohort-scale spatial transcriptomic super-resolution across platforms.

bioinformatics↗

bioRxiv2026

Counterions, Polarization and Pore Hydration Relay Drive Ion Permeation through Hydrophobic Pore Formed by the MERS Coronavirus E Protein

Hydrophobic pores are generally expected to exclude ions because the large desolvation penalty associated with ion transfer cannot be compensated within a nonpolar environment. The envelope (E) protein of Middle East Respiratory Syndrome coronavirus (MERS-CoV) presents a striking exception, conducting cations with high efficiency despite forming a predominantly hydrophobic pore. To resolve this apparent paradox, we combine finite-temperature string simulations with additive and polarizable force fields to determine the minimum free-energy pathways for ion permeation through the MERS E channel. The simulations reveal a cooperative permeation mechanism in which transient counterion association, localized pore hydration, and electronic polarization jointly reduce the desolvation penalty. Rather than acting as passive spectators, counterions transiently chaperone the permeating cation before dissociating within the channel, thereby lowering the energetic cost of charge desolvation while preserving net ionic conductance. Explicit electronic polarization further reshapes the pore hydration landscape and cation-{pi} interactions, leading to substantially reduced free-energy barriers and a permeation mechanism in substantially better agreement with experiment. These results suggest that efficient ion transport through hydrophobic pores arises from the cooperative interplay between electrostatics, polarization and hydration rather than complete pore wetting, providing both a mechanistic framework for MERS E protein function and a general physical principle for ion transport through biological and synthetic hydrophobic nanopores.

biophysics↗

bioRxiv2026

Proteome Profiling of Human Tear Fluid Following Acute Exercise

Acute exercise induces systemic molecular perturbations that are not fully reflected by individual biomarkers. Tear fluid is amenable to non-invasive and repeated collection and contains a diverse array of bioactive molecules, thereby constituting a practical biological specimen for evaluating exercise-related physiological responses. However, the immediate proteome-wide alterations in tear fluid following acute exercise have not been characterized. In this study, we performed quantitative proteomic profiling of paired tear samples obtained from healthy female participants before and immediately after a single exercise session, using data-independent acquisition liquid chromatography-tandem mass spectrometry (DIA-LC- MS/MS). Among the 3,173 identified proteins, 744were significantly altered post-exercise, of which 484 exhibited up-regulation and 260 exhibited down-regulation. Functional enrichment analysis demonstrated that the up-regulated proteins were predominantly associated with translation and ribosome biogenesis, whereas down-regulated proteins were primarily involved in glycan metabolism, lysosomal processing, and extracellular matrix organization. Collectively, these observations indicate that acute exercise elicits a rapid and coordinated reconfiguration of the tear proteome. To our knowledge, this investigation provides the first proteomic evidence of the immediate tear response to physical activity, offering a molecular basis for understanding exercise-mediated modulation of tear composition and ocular surface homeostasis.

physiology↗

bioRxiv2026

Bridging Gene Expression and Morphology: A Cell Size Score and Its Applications Across Multiple Diseases and Physiological Contexts

Cell size is a critical morphological parameter determining cellular functional homeostasis, yet existing large-scale transcriptomic databases lack direct cell size measurement data. By integrating high-resolution immunofluorescence images with transcriptomics, we identified 457 genes significantly correlated with cell area. Based on these findings, we developed an algorithm, Cell Size Score (CSS), to predict cell size from gene expression profiles. Validation across multiple independent datasets, including human cell lines, mouse models, and single-cell spatial transcriptomics, confirmed that CSS accurately predicts cell size. Furthermore, we observed a significant positive correlation between CSS and broad-spectrum chemotherapy drug resistance, suggesting that increased cell volume confers survival advantages to cancer cells. Moreover, CSS analysis of aging revealed sex-dependent, tissue-specific patterns of change, wherein male adipose and cardiac tissues exhibited progressive hypertrophy with age, while female reproductive organs showed significant atrophy. Additionally, CSS significantly increased in skeletal muscle after exercise, indicating that this metric can capture dynamic physiological adaptation processes. This study establishes a bridge between transcriptomics and cell morphology, providing novel insights into retrospectively analyzing the role of cell size in pathological and physiological processes such as cancer and aging using existing omics data, as well as understanding the molecular mechanisms underlying cell size regulation.

bioinformatics↗

bioRxiv2026

Exercise-induced sweat suppresses depression-like behaviors in mice

Depression represents a major global public health challenge. Current antidepressant therapies are often limited by significant side effects, delayed onset of action, and suboptimal efficacy, creating an urgent need for the development of novel interventions. In this study, using a transcriptome-based bioinformatics pipeline, we found that the gene signature of depression is significantly anti-correlated with that of exercise-induced sweat (EIS), suggesting that EIS may have the potential to treat depression. To validate this prediction, we first established a lipopolysaccharide-induced mouse model of depression and then evaluated the therapeutic effects of EIS in comparison with the positive control fluoxetine. Our results show that EIS treatment significantly suppresses depressive and anxiety-like behaviors, as evidenced by increased sucrose preference in the sucrose preference test, reduced immobility in the tail suspension test, and enhanced exploratory activity in the elevated plus maze. Notably, high-dose EIS intervention achieved therapeutic efficacy comparable to, or even better than, that of fluoxetine. This study identifies EIS as a novel bioactive intervention and an innovative strategy for treating depression, and opens a new avenue in sports medicine by investigating the potential beneficial effects of EIS.

neuroscience↗

bioRxiv2026

Microglial sTREM2 limits dyskinesia and acts on TrkB to support circuit plasticity

Microglia continuously survey the brain and shape neuronal activity, but their contribution to experience-dependent synaptic plasticity is unclear. Levodopa-induced dyskinesia (LID) is a disabling complication of late-stage Parkinsons disease (PD) that is linked to maladaptive striatal remodeling and is often assumed to reflect detrimental neuroinflammation. Here we identify a dyskinesia-associated microglial gene program in the striatum of PD patients and show that microglia instead act as a protective brake on LID. In a mouse model, microglial depletion exacerbated dyskinesia, whereas microglial repopulation mitigated it. Delivery of AAV expressing soluble TREM2 (sTREM2) similarly reduced LID without impairing the therapeutic benefit of levodopa. Single-nucleus transcriptomics revealed that microglial loss drives extensive remodeling of both direct and indirect spiny projection neurons (SPNs), while repopulation or sTREM2 reverses a large fraction of LID-associated transcriptional changes. Mechanistically, sTREM2 directly engages TrkB and potentiates BDNF-dependent TrkB-ERK signaling, consistent with positive allosteric modulation. Functionally, sTREM2 enhances BDNF-TrkB-dependent hippocampal synaptic plasticity and acutely rebalances striatal dendritic excitability in a compartment- and cell type-specific manner. These findings reveal an unexpected neuroimmune pathway in which microglia restrain maladaptive plasticity via sTREM2-TrkB signaling, with therapeutic implications.

neuroscience↗

bioRxiv2026

Exercise-induced Sweat Promotes Wound Healing in Diabetic Foot Ulcers

Persistent hyperglycemia impairs wound healing in diabetic patients, and severe cases may even lead to disability or death. Glycemic control alone cannot effectively prevent the occurrence of diabetic foot ulcers, a serious complication of diabetes. However, safe, efficient, and cost-effective therapies remain unavailable and are urgently needed. Using a novel sports medicine paradigm, we predicted, based on reverse-transcriptomics, that exercise-induced sweat has the potential to promote would healing in diabetic foot ulcers. Subsequent animal experiments demonstrated that sweat can indeed promote re-epithelialization and collagen deposition, upregulate the expression of the proliferation marker Ki-67, the angiogenesis marker CD31, and -SMA, and significantly accelerate wound healing in a mouse model of diabetic foot ulcers. This study provides a new direction for sports medicine and offers a novel therapeutic strategy for patients with diabetic foot ulcers.

zoology↗

bioRxiv2026

Exercise-conditioned tear fluid suppresses myopia progression

Myopia represents a major global public health challenge with rapidly rising prevalence. It is thus important to explore novel therapeutics for the treatment of myopia. Here we predicted tear fluid after (TA) but not before (TB) moderate-intensity aerobic exercise might protect against myopia using reverse transcriptomic analysis. To experimentally validate this hypothesis, TA or TB was administered by periocular injection in a guinea pig model of form-deprivation myopia. As a result, TA treatment significantly attenuated myopic refractive shifts and suppressed vitreous chamber depth and axial length elongation, whereas TB showed no protective effects. This study proposes a novel therapeutic avenue for myopia intervention and also suggests a previously unrecognized tear fluid-mediated mechanism linking exercise to myopia.

bioinformatics↗

bioRxiv2026

Disease diagnosis via sperm motility variations induced by body fluids in bioassay

Precise diagnosis of high-risk conditions such as cardiovascular and cerebrovascular diseases still remains a challenge. We previously developed a microfluidic chip for sperm selection and observed that sperm motility is highly sensitive to environmental changes. Building on this finding, we hypothesized that motility traits of sperm could be differentially modulated by body fluids from healthy versus diseased individuals, thereby serving as potential biomarkers for disease diagnosis. To test this hypothesis, we designed a diagnostic system in which mouse sperm were co-incubated with serum samples from patients with myocardial infarction, cerebral infarction, and pancreatitis, along with matched healthy controls. Key kinematic parameters--including motility rate (MR), curvilinear velocity (VCL), straight-line velocity (VSL), linearity (LIN), and amplitude of lateral head displacement (ALH)--were analyzed using a multiparameter sperm quality analysis system. The results revealed that disease-specific serum induced distinct and reproducible changes in sperm motility patterns, enabling accurate discrimination between healthy and pathological conditions. Evaluation of these motility parameters demonstrated high diagnostic performance, with area under the receiver operating characteristic curve (AUC) values ranging from 0.719 to 0.888. This sperm-based bioassay offers a non-invasive, rapid, and cost-effective platform for disease detection and personalized health assessment, with the potential to complement existing diagnostic approaches.

bioengineering↗

bioRxiv2025

Unlocking biological insight from single-cell data with an interpretable dual-stream foundation model

Deep learning foundation models are revolutionizing single-cell biology, yet learning holistic and discriminative representations from complex, high-dimensional data remains a central challenge. Although Transformer-based single-cell language models have shown significant progress, they typically rely on a single input-encoding scheme, a practice that results in the loss of critical gene expression information and hinders the effective learning of global cellular representations. To address these challenges, we introduce scDMC, an innovative single-cell Dual-stream Masked Contrastive pre-training framework designed to synergistically optimize information fidelity at both the gene and cellular levels. Pre-trained on only 2 million cells far fewer than the datasets used by mainstream models, scDMC sets a new state-of-the-art in multiple benchmark tasks, including cell annotation, clustering, and data integration. More importantly, we demonstrate that scDMC can uncover functional gene modules, infer cell-type-specific regulatory networks in a data-driven manner, and exhibits a high degree of biological interpretability.

bioinformatics↗

bioRxiv2025

Integrated Genomic and Methylome Profiling Reveals Promoter Repression and Age-Linked CpGs in the California Mussel

While most knowledge of animal DNA methylation comes from vertebrates, this epigenetic mark remains poorly understood in invertebrates, which comprise the majority of animal diversity. For instance, how promoter and gene body methylation contribute to gene regulation, and how methylation relates to aging, are still relatively unknown in most invertebrates. Focusing on the California mussel (Mytilus californianus), we paired whole-genome resequencing and whole-genome bisulfite sequencing from the same individuals and evaluated relationships among promoter methylation, gene body methylation, gene expression, and age. Using seven individuals spanning a range of body sizes from the Santa Barbara Channel, California, we found standing genetic variation levels similar to related species and a relatively small effective population size. CpG methylation was enriched in gene bodies, and gene body methylation was positively associated with expression. Promoter methylation was less frequent but showed a strong negative association with expression and remained the best predictor of repression after accounting for gene body methylation, aligning with patterns widely documented in vertebrates and adding to the limited evidence in invertebrates that promoter methylation can be regulatory. We identified thousands of age-associated differentially methylated loci with directional changes across age classes, providing candidate sites for epigenetic clocks that could enable assessment of biological age, health, and stress resilience in wild and cultured populations.

evolutionary biology↗

bioRxiv2025

Systematic Evaluation of Somatic Contamination in Germline Genomes

Large-scale genomic initiatives like the UK Biobank (UKB) have revolutionized our understanding of human disease. These studies typically assume that blood-derived DNA faithfully reflects an individuals germline genome. However, this assumption is challenged by somatic mutations arising from processes like clonal hematopoiesis. Although standard bioinformatics pipelines employ variant allele frequency (VAF)-based filtering to mitigate such contamination, the efficacy of these approaches requires systematic evaluation. By systematically analyzing whole-exome sequencing (WES) and whole-genome sequencing (WGS) data from large cohorts, including the UK Biobank, The Cancer Genome Atlas (TCGA), and the 1000 Genomes Project, we revealed critical limitations in current filtering methodologies. We found that the mutational spectrum of rare "germline" variants is highly similar to that of somatic mutations. Furthermore, we uncovered these variants show significant associations with phenotypes such as age, sex, and smoking status, established drivers of somatic mutagenesis. This persistent somatic contamination introduces substantial confounder effects, potentially generating spurious associations and reverse causality in genetic studies. Our work underscores the urgent reconsideration of two fundamental aspects of genomic research: (1) refinement of variant filtering strategies to better distinguish true germline variants from somatic contaminants, and (2) incorporation of somatic mutagenesis factors as essential covariates in study design. Our findings provide a basic framework for improving the accuracy and interpretability of large-scale genomic studies.

genomics↗

bioRxiv2025

Mass explosions and extinctions may be influenced by the dynamical Coupling between Earth's magnetic field strength and atmospheric oxygen level

A recent study has revealed that Earths magnetic field strength and atmospheric oxygen level exhibit strongly correlated, linearly increasing trends (M-O relationship) over the past 540 million years. This discovery sheds new lights on the long-standing debate regarding whether a strong magnetic field is an essential prerequisite for origin and the evolution of complex life. Here, we demonstrate that the M-O relationship is not static but highly dynamic across geological timescales using dynamic correlation and variable parameter regression analysis. Intriguingly, periods of weakened M-O coupling coincide precisely with the "Big Five" mass extinctions, while the strongest M-O correlation aligns with the Cambrian explosion. Further analysis indicates that shifts in M-O linkage are driven primarily by changes in the magnetic fields trend rather than oxygen fluctuations, with the "Big Five" extinctions closely matching inflection points in Earths magnetic field strength curve. Additionally, human gene age analysis unveils that de novo gene birth rate correlates strongly with mass explosion/extinction and M-O relationship strength, enabling the prediction of such events predating 540 million years ago (Mya) and potentially in the future. Our findings suggest that the stability of Earths magnetic field trend--or its coupling strength with oxygen--rather than absolute magnetic strength or oxygen level, plays a pivotal role in shaping the rise and fall of life.

evolutionary biology↗

bioRxiv2025

A large-scale foundation model for bulk transcriptomes

Large language models (LLMs) have emerged as powerful foundation models leading to breakthroughs in transcriptome analysis. However, current RNA-seq foundation models are exclusively pretrained on sparse single-cell RNA-seq (scRNA-seq) data, which typically detects only [~]3000 genes per cell. This thus creates a critical gap in models specifically designed for bulk transcriptomes, a fundamentally different modality capable of profiling [~]16,000 genes per sample. Here we propose BulkFormer, a large-scale foundation model for bulk transcriptome analysis. With 150 million parameters covering about 20,000 protein-coding genes, BulkFormer is pretrained on over 500,000 human bulk transcriptomic profiles. BulkFormer incorporates a hybrid encoder architecture, combining a graph neural network to capture explicit gene-gene interactions and a performer module to model global expression dependencies. As a result, despite incurring much lower training costs than scRNA-seq foundation models, BulkFormer consistently outperforms them in all six downstream tasks: transcriptome imputation, disease annotation, prognosis modeling, drug response prediction, compound perturbation simulation, and gene essentiality scoring. Notably, BulkFormer not only enhances the discovery of novel clinical biomarkers but also uncovers latent disease mechanisms by imputing biologically meaningful gene expression. Collectively, these results demonstrate BulkFormers power as a versatile and robust framework for bulk transcriptome modeling and biomedical discovery, bridging a critical gap in the current foundation model landscape.

bioinformatics↗

bioRxiv2025

Phosphorylation-inducing chimera rewires oncogenic kinase to trigger apoptosis

The active sites electric field is integral to enzymatic catalysis (e.g., substrate recognition) and nature employs charge-altering post-translational modifications (e.g., phosphorylation) to perturb this electric field and regulate enzymes. A chromosomal translocation converts Abelson kinase (ABL) to BCR-ABL, whose hyperactivity drives several cancers. Here, we developed a small molecule, BRD8833, that induces BCR-ABL phosphorylation, which perturbs its active sites electric field with loss of hyperactivity. Unlike "occupancy-driven" inhibitors that require stoichiometric concentrations, BRD8833 operates through an event-driven, substoichiometric mechanism by inducing proximity between two BCR-ABL molecules to trigger the inhibitory phosphorylation and selective apoptosis of BCR-ABL-dependent cancer cells. Furthermore, BRD8833 is effective against other oncogenic ABL fusions or clinically observed resistance mutations, including those to occupancy-driven drugs with the same binding site as BRD8833, suggesting differences in their resistance mechanisms. These studies lay the foundation for electric-field and "event-driven" modalities to control hyperactive enzymes with orthogonal resistance mechanisms to occupancy-driven drugs. GRAPHICAL ABSTRACT (TOC) O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=197 SRC="FIGDIR/small/659082v2_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@1607a40org.highwire.dtl.DTLVardef@fa10deorg.highwire.dtl.DTLVardef@1698232org.highwire.dtl.DTLVardef@1e2e0f1_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2025

Integrating experiments and simulations to unravel coacervate-membrane interactions: Insights into de-mixing and morphology modulation

Intrinsically disordered proteins and polypeptides can undergo liquid-liquid phase separation (LLPS) to form condensates/coacervates, which play numerous regulatory roles in the cell. Recently, the relevance of such LLPS occurring in the vicinity of membranes has been brought to light by several experimental studies. Membrane-adsorbed condensates are crucial for biomolecular localization, and in some cases, phase separation of proteins at the membrane surface induces significant changes in membrane morphology. A detailed microscopic understanding of the mechanisms behind these observations remains incomplete. Here we combine experiments and molecular simulations to unravel structural and dynamic features of the coacervate/membrane interface across scales. We study poly-Lysine/poly-Aspartate (K10/D10) coacervates as a prototype of phase-separated condensates with different unilamellar liposomes. Using a multiscale characterization approach that combines confocal microscopy, hyperspectral imaging, fluorescence recovery after photobleaching, and two complementary coarse-grained approaches, we show that the membrane-condensate affinity can be tuned by the anionic lipid content and quantified through the intrinsic contact angle - a material property derived from system geometry - both in vitro and in silico. We find that the membrane region in contact with the condensate displays a nearly two-fold reduced fluidity compared to the bare membrane. This is attributed to orientational ordering of lipid tails, resulting in decreased area per lipid. Moreover, we observed local lipid de-mixing induced by the coacervate adsorption. This study provides an effective framework for integrating experiment and computation to characterize the properties of coacervate/membrane interfaces that are critical to the functional impacts of these interactions.

biophysics↗

bioRxiv2025

Comprehensive profiling of N6-methyladnosine (m6A) readouts reveals novel m6A readers that regulate human embryonic stem cell differentiation

N6-methyladenosine (m6A) methylation has emerged as a prevalent RNA modification that extensively impacts various physiological and pathological processes via various post-transcriptional readout effects in mammals. High-throughput methylome profiling has outlined the landscape of m6A modification sites, but their downstream readouts require comprehensive investigation. To this end, we systematically assessed the effects of m6A on mRNA half-life, translation efficiency, and alternative splicing across five cell lines (A549, HEK293T, HUVEC, JURKAT, and human embryonic stem cells (hESCs)) using actinomycin D-disrupted temporal transcriptome sequencing, ribosome sequencing, and ultra-high-depth transcriptome sequencing, respectively. Our analysis, coupled with the integration of public and re-profiled m6A methylome data, revealed high cell type specificity in m6A readouts where m6A level alone is insufficient to predict m6A readouts. Machine learning models focused on the RNA binding protein (RBP) binding context of m6A sites demonstrated substantial predictive ability of m6A readouts while prioritizing putative m6A readers from their informative RBP features. Four novel m6A readers (DDX6, FUBP3, FXR2, and L1TD1) were identified and validated through m6A RNA pull-down assays and transcriptome-wide RBP binding site mapping. Notably, FUBP3, FXR2 and L1TD1 were found to regulate hESC differentiation without impairing self-renewal, underscoring their critical roles in stem cell biology. Together, this study bridges the gap in understanding m6A functional readouts and lays the groundwork for future research on m6A-mediated stem cell fate decisions.

genomics↗

bioRxiv2025

CHIEF: An Attention-based Ensemble Learning Framework for Functional Protein Design

Protein de novo design is a longstanding challenge in biological field due to the multifaceted physicochemical properties and complexities of proteins. Several deep learning models have emerged for protein de novo design. However, each model exhibits distinct strengths and limitations because of the differences in training strategies or neural network architectures. Therefore, improving the effectiveness of protein design, particularly for functional protein, requires further improvement. To tackle this challenge, we developed CHIEF (Chimera Ensemble Inverse Folding), an attention-based ensemble framework that integrates five pretrained base models (ProteinMPNN-vanilla, ProteinMPNN-soluble, ESM-IF, Frame2seq and PiFold) to leverage their complementary strengths and mitigate limitations. Compared with the base models, CHIEF significantly improved the sequence recovery rate by 16.6-28.0%, while reducing the prediction perplexity by 22.7-34.6%. CHIEF also exhibited superior protein-designing capacity in variable sequence- and structure-based metrics and in large and complex proteins. CHIEF dynamically captured the semantic information from base models in a context-dependent manner and was minimally affected by the ablation of each base model. More importantly, CHIEF demonstrates real-world applicability to design functional malate dehydrogenase (MDH), achieving a 100% success rate. In summary, our study develops an ensemble deep learning model that improves the efficacy of protein sequence design, and will be a valuable platform for protein engineering and drug development.

bioengineering↗