Biology subjects

Chen, Q.

Publications and source records attributed to Chen, Q..

At least 109 records · Page 6Linked to original sources

bioRxiv2025

Temporal Dynamics of Flexible Cognitive Control

In dynamic environments, flexible cognitive control adaptively adjusts processing through proactive mechanisms deployed in advance and reactive mechanisms engaged upon conflict. Previous studies have primarily focused on identifying neural networks supporting specific control components, while less is known about how multiple components interact over time to support adaptive control. To characterize these temporal dynamics, we combined EEG recordings with a face-word Stroop paradigm under changing conflict environment. A hierarchical Bayesian model was used to estimate trial-wise learning rate, predicted conflict level, and prediction error, providing computational indices of cognitive control flexibility. Neural correlation analysis revealed that these variables correlated with Theta, Alpha, and Beta oscillations in distinct brain regions. Connectivity analysis among these regions indicated enhanced cross-frequency directional interactions triggered by stimuli. Furthermore, connections reflecting updates to predicted conflict level prior to stimulus onset indexed individual strength in proactive control, while connections reflecting learning rate updates after stimulus onset indexed reactive control. These findings highlight how oscillatory dynamics coordinate multiple control components and provide new insight into how proactive and reactive control emerge as distinct modes within this interconnected neural architecture of flexible cognitive control.

neuroscience↗

bioRxiv2025

Distinct cell wall molecular architecture of dimorphic Talaromyces marneffei cells revealed by solid-state NMR spectroscopy

Talaromyces marneffei, causing systemic infections in immunocompromised patients ranging from HIV/AIDS individuals to cancer and transplant recipients, is an increasingly urgent global pathogen. However, the fungus remains underrecognized despite the systemic infection disease talaromycosis caused by this pathogen is associated with high mortality rates. Its pathogenicity depends on a temperature-triggered shift from saprophytic mold (25 {degrees}C) to pathogenic yeast (37 {degrees}C), and the two growth forms display distinct sensitivity to antifungal drugs, which processes involve extensive cell wall structure and components remodeling. To dissect these processes, we use solid-state nuclear magnetic resonance (ssNMR) and other techniques to show that T. marneffei yeast and hyphal cells have distinct cell wall thickness and hydrophobicity, and different assembly of mobile and rigid polymers within the T. marneffei cell wall. The yeast wall was 2.3 times thicker and more hydrated. ssNMR revealed a rigid core of {beta}-1,3-glucans, chitin and chitosan, with {beta}-1,3-glucan rising from 57% in mold to 72% in yeast. Both forms showed tight polysaccharide packing, but only mold exhibited lysine-containing protein interactions with chitin and chitosan. These insights not only map the structural basis of host temperature adaptation and also inform targeted antifungal design in future.

bioinformatics↗

bioRxiv2025

Augmented prediction of multi-species protein--RNA interactions using evolutionary conservation of RNA-binding proteins

AbstractRNA-binding proteins (RBPs) play critical roles in gene expression regulation. Recent studies have begun to detail the RNA recognition mechanisms of diverse RBPs. However, given the array of RBPs studied so far, it is implausible to experimentally profile RBP-binding peaks for hundreds of RBPs in multiple non-model organisms. Here, we introduce MuSIC (Multi-Species RBP-RNA Interactions using Conservation), a deep learning-based framework for predicting cross-species RBP-RNA interactions by leveraging label smoothing and evolutionary conservation of RBPs across 11 diverse species ranging from human to yeast. MuSIC outperforms state-of-the-art computational methods, and provides predicted RBP-binding peaks across species with high accuracy. The prediction confidence is higher in the closely related species, partially due to the RBP conservation patterns. Finally, the effects of homologous genetic variants on RBP binding can be computationally quantified across species, followed by experimental validations. The target transcripts with disrupted binding events are enriched with the ubiquitination-associated pathways. To summarize, MuSIC provides a useful computational framework for predicting RBP-RNA interactions cross-species and quantifying the effects of genetic variants on RBP binding, offering novel insights into the RBP-mediated regulatory mechanisms implicated in human diseases. HighlightsO_LIMuSIC integrates RBP-binding peaks with conservation-weighted label smoothing to predict RBP-RNA interactions across eleven species C_LIO_LIMuSIC outperforms state-of-the-art computational methods in predicting cross-species RBP-RNA interactions C_LIO_LICross-species prediction accuracy of RBP-binding peaks correlates with the conservation of RBPs C_LIO_LIMuSIC quantifies the effects of homologous SNVs on RBP binding with experimental validation in mouse C_LI

bioinformatics↗

bioRxiv2025

A phenotypic screen identified KEAP1-kelch domain blockade as a mechanism to restore cardiac function in the setting of chronic severe hemodynamic stress

A bespoke gene expression (GE) based small molecule screen in human induced pluripotent stem cell derived cardiomyocytes (iPSC-CM) was conducted with the aim of identifying drug targets and pathways with the potential to reverse heart failure (HF) pathologic GE and the resultant decompensated HF phenotype. The screen utilized a composite human-murine HF gene expression signature, a target annotated compound set, and a HF gene expression reversal scoring algorithm to identify small molecules and their associated targets as potential modulators of HF pathologic GE. Following hit triage, a lead optimization program, and compound characterization in preclinical rodent models of HF and human iPSC-CM contractility assays, KEAP1 kelch domain blockers were identified as potent efficacious agents in the restoration of contractile function in the setting of oxidant stress and pressure overload induced cardiac dysfunction.

molecular biology↗

bioRxiv2025

System-Level Computations Underlie Visual Field Heterogeneity

Human visual perception for basic dimensions varies with eccentricity and polar angle, influencing daily activities such as reading, searching and scene perception. We investigated whether and how system-level computations that transform visual input into perception underlie these heterogeneities. Using the equivalent noise method and perceptual template model, we estimated gain, internal noise, and nonlinearity for orientation discrimination across eccentricity (fovea, parafovea and perifovea) and around polar angle. Participants discriminated the orientation of Gabors embedded in dynamic white noise and showed the expected variations across eccentricity and around polar angle. Importantly, visual performance declined with eccentricity due to decreased gain and nonlinearity and increased internal noise. Observers with stronger eccentricity effects showed greater gain decrease. Only gain varied with polar angle--higher along the horizontal than vertical meridian, and lower than upper vertical meridian--paralleling performance asymmetries. This dissociation aligns with known variations in neuronal count and tuning, suggesting that neural correlations and neural noise contribute to these system-level computations. By revealing distinct system-level computations underlying the eccentricity effect and polar angle asymmetries, our findings link perceptual heterogeneity across the visual field and neural architecture and provide insights into how the human brain encodes information under neural constraints. Significance StatementHuman visual performance varies across eccentricity-distance from gaze-and around polar angle -circular dimension. Retinal factors and cortical surface area account for eccentricity, but only partially for polar angle variations. Here, we show that system-level computations--how signal are amplified and how noisy the system is--distinctly underlie these perceptual variations. Decline across eccentricity stems from both reduced gain and nonlinearity and elevated internal noise, whereas variation around polar angle arises solely from gain difference. This dissociation implies fundamental differences in information processing along two axes of the visual field. Our results provide a computational link between behavior and its neural bases and highlight the importance of considering both eccentricity and polar angle in modeling and understanding human perception.

neuroscience↗

bioRxiv2025

CSRefiner: A lightweight framework for fine-tuning cell segmentation models with small datasets

AO_SCPLOWBSTRACTC_SCPLOWRecent advances in spatial omics technologies have enabled transcriptome profiling at subcellular resolution. By performing cell segmentation on nuclear or membrane staining images, researchers can acquire single cell level spatial gene expression data, which in turn enables subsequent biological interpretation. Although deep learning-based segmentation models achieve high overall accuracy, their performance remains suboptimal for whole-tissue analysis, particularly in ensuring consistent segmentation accuracy across diverse cell populations. Existing fine-tuning approaches often require extensive retraining or are tailored to specific model architectures, limiting their adaptability and scalability in practical settings. To address these challenges, we present CSRefiner, a lightweight and efficient fine-tuning framework for precise whole-tissue single-cell spatial expression analysis. Our approach incorporates support for fine-tuning widely uaed segmentation models in the field of spatial omics, including recent published model Cellpose-SAM, while achieving high accuracy with very limited annotated data. This study demonstrates CSRefiners superior performance across various staining types and its compatibility with multiple mainstream models. Combining operational simplicity with robust accuracy, our framework offers a practical solution for real-world spatial transcriptomics applications.

bioinformatics↗

bioRxiv2025

A ratio-based framework using Quartet reference materials for integrating long- and short-read RNA-seq

Long-read RNA sequencing (lrRNA-seq) enables full-length transcript profiling but is confounded by technical batch effects that compromise quantification and prevent data integration across platforms, protocols, and laboratories. The lack of a transcriptome-wide biological ground truth has hindered objective benchmarking. To address these dual challenges, we leveraged certified Quartet reference materials to generate one of the largest multi-center lrRNA-seq resources to date: over one billion long reads from 144 libraries across four PacBio and Nanopore protocols in four independent laboratories. We first establish that ratio-based quantification against built-in reference samples effectively removes technical noise, revealing underlying biological signals. We then constructed the first ratio-based reference datasets for full-length transcripts-- comprising 10,218 isoforms and 6,032 alternative splicing (AS) events--and orthogonally validated them with RT-qPCR. Finally, a comprehensive benchmark using these ground truths reveals that a hybrid strategy integrating long- and short-read data (hybrid-seq) achieves the highest quantification accuracy for both isoforms and AS events. Our work provides a foundational framework and resource for evaluating lrRNA-seq technologies and accelerating the standardization of full-length transcriptomics for research and clinical applications.

genomics↗

bioRxiv2025

PATTY corrects open chromatin bias for improved bulk and single-cell CUT&Tag profiling

Precise profiling of epigenomes is essential for better understanding chromatin biology and gene regulation. Cleavage Under Targets & Tagmentation (CUT&Tag) is an efficient epigenomic profiling technique that can be performed on a low number of cells and at the single-cell level. With its growing adoption, CUT&Tag datasets spanning diverse biological systems are rapidly accumulating in the field. CUT&Tag assays use the hyperactive transposase Tn5 for DNA tagmentation. Tn5s preference toward accessible chromatin alters CUT&Tag sequence read distributions in the genome and introduces open-chromatin bias that can confound downstream analysis, an issue more substantial in sparse single-cell data. We show that open-chromatin bias extensively exists in published CUT&Tag datasets, including those generated with recently optimized high-salt protocols. To address this challenge, we present PATTY (Propensity Analyzer for Tn5 Transposase Yielded bias), a comprehensive computational method that corrects open-chromatin bias in CUT&Tag data by leveraging accompanying ATAC-seq. By integrating transcriptomic and epigenomic data using machine learning and integrative modeling, we demonstrate that PATTY enables accurate and robust detection of occupancy sites for both active and repressive histone modifications, including H3K27ac, H3K27me3, and H3K9me3, with experimental validation. We further develop a single-cell CUT&Tag analysis framework built on PATTY and show improved cell clustering when using bias-corrected single-cell CUT&Tag data compared to using uncorrected data. Beyond CUT&Tag, PATTY sets a foundation for further development of bias correction methods for improving data analysis for all Tn5-based high-throughput assays.

bioinformatics↗

bioRxiv2025

A Novel 3D Visualization Method in Mice Identifies the Periportal Lamellar Complex (PLC) as a Key Regulator of Hepatic Ductal and Neuronal Branching Morphogenesis

The liver is a complex organ responsible for multiple functions, including metabolism, energy storage, detoxification, bile secretion, and immune regulation. Its highly organized vascular system plays a crucial role in maintaining functional zonation and tissue homeostasis. Within the liver, the hepatic artery, portal vein, hepatic vein, bile duct, and nerve networks intertwine to form an intricate three-dimensional architecture; however, traditional two-dimensional imaging fails to reveal their true spatial relationships, and current three-dimensional imaging methods remain insufficient to capture fine structural details. To achieve comprehensive visualization of these multi-ductal systems, we established a high-resolution three-dimensional imaging platform that combines multicolor perfusion of metallic compound nanoparticles (MCNPs) with an optimized tissue-clearing protocol (Liver-CUBIC), enabling simultaneous 3D reconstruction of the portal vein, hepatic artery, bile duct, and hepatic vein in mouse livers. Based on these data, we identified and defined a previously unrecognized structure located in the outer layer of the portal vein, termed the Periportal Lamellar Complex (PLC). The PLC encircles the portal vein between the vascular endothelium and the perisinusoidal region, exhibits low-permeability barrier characteristics, and contains a distinctive population of CD34Sca-1 endothelial cells. During liver fibrosis, the PLC extends from the portal vein toward the hepatic lobule, forming a structural scaffold that guides bile duct and nerve migration.

developmental biology↗

bioRxiv2025

The Disruption and Normalization of Cortical Language Network Dynamics After Post-Stroke White Matter Disconnection

The human language network undergoes reorganization across different spatiotemporal scales, limited by its fixed structural neurobiological foundations. Although stroke often damages white matter, its effect on temporary language network reorganization is not fully understood. This study examined longitudinal behavioral and resting-state fMRI data from post-stroke patients with exclusive subcortical lesions at three time points: two weeks (n = 38), three months (n = 29), and one year (n = 27). Patients showed mild to moderate language impairments during the acute phase, which improved within three months. The extent of disconnection in several left-hemispheric white matter tracts was negatively associated with language deficits. Healthy controls (HC, n = 25) exhibited domain-segregation dynamics in the cortical language network, limited by the underlying white matter pathways. In patients, severe, state- and track-specific network disruptions were observed in the acute phase, characterized by hypo- and hyper-connectivity and abnormal topological features. As language recovery progressed, connectivity patterns began to return to normal, resembling those of HC, and the domain-segregation dynamics reappeared. These results deepen our understanding of structure-function coupling and indicate significant post-lesional plasticity within the cortical language network.

neuroscience↗

bioRxiv2025

A simple liquid 3D cell culture paradigm models oxidative mitochondrial metabolism of epithelial breast cancer cells with relevance for lung metastases.

Three-dimensional (3D) cell culture systems have emerged as powerful tools for modeling tumor biology in ex vivo settings. However, the diverse array of available 3D culture methods presents challenges in selecting the most appropriate model for specific research questions. This study provides a comparative analysis of breast cancer cells (SUM149, IBC-3, and MDA-MB-468) in the mammosphere culture (SphC) model or an "emboli" culture (EmC) model, which enrich for cancer stem cells and epithelial features, respectively. The EmC model, designed originally for inflammatory breast cancer, is characterized by media viscosity and mechanical rocking of the culture vessel. Notably, cells in EmC showed a distinct and durable reduction in cell proliferation ex vivo while demonstrating increased capacity to establish experimental lung metastases in vivo. Ultrastructural quantitative analysis of electron microscopy images suggested that cells in EmC acquire nuclear and mitochondrial features that resemble those of tumor tissue. Proteomics, single-cell transcriptomics, and metabolic flux analyses showed that cells in EmC and SphC favor mitochondrial oxidative metabolism (OXPHOS) and glycolysis, respectively. EmC rendered cells hypersensitive to OXPHOS inhibition, but more resistant to oxidative stress. Several genes associated with lung metastasis, including ID1, were specifically enriched in EmC. Given the emerging role of OXPHOS in cancer cell survival during dissemination and as established metastases, we propose that the EmC paradigm is a suitable ex vivo model to study signaling pathways relevant for tumor tissue and to assess drug sensitivities and resistance mechanisms of metastatic breast cancer cells ex vivo. SIGNIFICANCEThis study provides an in-depth characterization of a resource-efficient yet powerful 3D culture paradigm to improve the physiological relevance of ex vivo approaches. Applicable to epithelial cancers, this model offers a platform to accelerate the discovery of physiologically relevant signaling pathways and specific cancer cell vulnerabilities.

cancer biology↗

bioRxiv2025

Core gastric microbiota linked to pathogenesis and preserved across age stratified cohorts

Mounting evidences reveal a complex microbial niche in gastric environment. Nevertheless, the phylogenetic stability of gastric microbiota remains undetermined. Here, using full-length 16S rRNA and ITS amplicon sequencing applied to gastric brushes from a pediatric endoscopic cohort (n=243), we identified a core microbiota comprising 11 genera, which clustered into two antagonistic communities (CST1A and CST1B). CST1A was enriched in healthy subjects, while CST1B correlated with gastroduodenal disease. Notably, this bipartite architecture arose through bacterial interactions, with fungal taxa demonstrating minimal integration. Further stratified analyses revealed that H. pylori infection preferentially depleted CST1A taxa. The subclusters exhibited divergent metabolic profiles, with CST1A specializing in motility processes and CST1B in nucleotide/peptidoglycan synthesis. Cross-cohort validation of six datasets (n=1,183) confirmed the persistent relevance of the CST1A-CST1B structure across disease stages. Collectively, our findings define a core gastric microbiota established in early life, linked to gastric disease risk, and persisting into adulthood. HighlightsO_LIIdentification of a gastric bacterial network established in early life. C_LIO_LIDysbiosis in two subclusters within the core microbiota is associated with pediatric peptic ulcers. C_LIO_LIHelicobacter pylori infection reduces the abundance of the core microbiota, with a particularly greater inhibitory effect on CST1A. C_LIO_LIThe core microbiota is preserved across age stratified cohorts and is associated with gastric cancer. C_LI

microbiology↗

bioRxiv2025

C9orf72/SMCR8 complex maintains microglial homeostasis via RAB8A-ESCRT-mediated lysosomal repair

Microglia are critical regulators of neuroinflammation and neurodegeneration. Haploinsufficiency of C9orf72, the most common genetic cause of ALS and FTD, has been mainly linked to autophagy-lysosomal pathway defects, but its precise role in microglial lysosomal function remains unclear. Here we identify the C9orf72/SMCR8 complex as a key regulator of microglial homeostasis through lysosomal repair. Loss of C9orf72 and SMCR8 in mice causes age-dependent neuroinflammation and microgliosis, with microglia adopting a disease-associated state. In aged CNS tissue, microglia display lysosomal damage, marked by galectin-3 upregulation and its accumulation on lysosomes. To model this process, we applied the lysosomotropic agent LLOMe to microglia, which recapitulated lysosomal damage and revealed defective recruitment of phosphorylated RAB8A and the ESCRT machinery in C9orf72/SMCR8-deficient cells. Notably, mutant microglia accumulate GTP-bound RAB8A, which becomes aberrantly hyperphosphorylated and mislocalized to non-lysosomal vesicles. We further show that the GAP activity of the C9orf72/SMCR8 complex is essential for lysosomal repair. These findings uncover a previously unrecognized role for the C9orf72/SMCR8 complex in coordinating RAB8A-ESCRT-mediated lysosomal repair, thereby safeguarding microglial homeostasis and limiting neuroinflammation.

cell biology↗

bioRxiv2025

Manganese mediates antiviral effects by driving an ATM -TBK1 phosphorylation signaling pathway

We previously reported that manganese (Mn) enhances innate immune responses to viral infection by inducing phosphorylation of TANK-binding kinase 1 (TBK1) in an Ataxia-telangiectasia mutated (ATM)-dependent manner. However, the underlying mechanism by which how Mn induces TBK1 phosphorylation remained unclear. Here, we show that Mn dose-dependently induced TBK1 phosphorylation in the presence of ATM across multiple cell lines, as well as in primary human macrophages and T cells. This phosphorylation was abolished in ATM-deficient cells, and we identified cytoplasmic ATM as a key mediator. Immunoprecipitation assays revealed that Mn promoted ATM phosphorylation at Ser1893, Ser1981, and Ser2996. TBK1 interacted with phosphorylated ATM at early stages, but upon phosphorylation, TBK1 dissociated from the ATM-TBK1 complex. This dissociation coincided with enhanced antiviral cytokine production. Furthermore, Mn dose-dependently suppressed HIV replication by inducing multiple antiviral host factors and cytokines. Together, these findings identify a cytoplasmic ATM-TBK1 phosphorylation cycle as a critical regulator of antiviral innate immunity and suggest Mn supplementation as a potential therapeutic approach against HIV and other viral infections. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/671272v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1c72f62org.highwire.dtl.DTLVardef@1f7e789org.highwire.dtl.DTLVardef@820fe0org.highwire.dtl.DTLVardef@e06fb3_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical Abstract:C_FLOATNO Mn-dependent activation of the ATM-TBK1 phosphorylation signaling pathway. At early time points, Mn phosphorylated ATM at multiple site. And then TBK1 bound to p-ATM and became phosphorylated. Phosphorylated TBK1 then dissociated from the complex at later stages (right panel). P-TBK1 participated in activating downstream TBK1-IRF signaling, thereby enhancing antiviral cytokines induction to DNA or RNA virus infection (left panel). C_FIG

immunology↗

bioRxiv2025

Ginkgolic acid attenuates e chinococcus granulosus infection-induced hepatic fibrosis by inhibiting Smad4 SUMOylation

BackgroundThe SUMOylation modification is closely linked to the progression of fibrotic diseases, yet its role in hepatic fibrosis associated with cystic echinococcosis (CE) remains unclear. This study aimed to investigate the function of SUMOylation in CE-related hepatic fibrosis and evaluate the anti-fibrotic effects and mechanisms of ginkgolic acid (GA) via regulation of the SUMOylation pathway. MethodologyPeri-lesional (PL) and adjacent normal (AN) liver tissues from CE patients were collected to examine histopathology and SUMO pathway proteins. A CE-infected mouse model was established and treated with GA to assess cyst burden, serum TGF-{beta}1 levels, hepatic fibrosis markers, and SUMO-related proteins. In vitro, macrophages and hepatic stellate cells (HSCs, LX-2 line) were stimulated with Echinococcus granulosus cyst fluid (EgCF) or TGF-{beta}1 to evaluate GAs effects on macrophage polarization (CD206/CD86), HSC activation (-SMA/PCNA), Smad4 SUMOylation, and nuclear translocation. Macrophage-HSC crosstalk was investigated via conditioned medium co-culture assays. ResultFibrosis was exacerbated in peri-lesional liver tissues of CE patients, accompanied by SUMO pathway activation. GA significantly alleviated hepatic fibrosis in CE mice and reversed SUMO pathway dysregulation. Mechanistically, GA inhibited EgCF-induced pro-fibrotic M2 macrophage polarization and blocked Smad4 SUMOylation and nuclear translocation by modulating SUMOylation. Furthermore, GA directly suppressed HSC activation and bidirectionally disrupted the pro-fibrotic crosstalk between macrophages and HSCs under EgCF stimulation, ultimately alleviating fibrosis. ConclusionThis study reveals the critical role of SUMOylation modification in CE-associated hepatic fibrosis and elucidates a novel anti-fibrotic mechanism whereby GA targets the SUMOylation-Smad4 axis to regulate the immune microenvironment. Author summaryThis study demonstrates aberrant activation of the SUMOylation pathway during hepatic fibrosis progression in cystic echinococcosis (CE), characterized by upregulated SUMO1/Ubc9 expression and downregulated SENP1 in peri-cystic liver tissue. Ginkgolic acid (GA) intervention significantly attenuated CE-associated liver fibrosis in mice, evidenced by reduced cyst volume, decreased TGF-{beta}1 levels, and suppressed expression of fibrotic markers (-SMA/COL1A1). GA concurrently reversed dysregulated SUMO pathway protein expression. Mechanistically, GA upregulates the deSUMOylating enzyme SENP1, thereby inhibiting Echinococcus granulosus cyst fluid (EgCF)-induced SUMOylation and nuclear translocation of Smad4. This blockade impedes macrophage polarization toward the pro-fibrotic M2 phenotype (CD206{downarrow}) and suppresses hepatic stellate cell (HSC) activation (-SMA/PCNA{downarrow}). Furthermore, GA disrupts the pro-fibrotic bidirectional crosstalk between HSCs and macrophages. Collectively, these findings indicate that GA ameliorates CE-induced hepatic fibrosis by targeting the SUMO-Smad4 axis to modulate the immune microenvironment, providing a novel therapeutic strategy.

molecular biology↗

bioRxiv2025

Comparative Temporal Transcriptomic Analysis of SOD1 Mutations in iPSC-Motor Neurons

Mutations in the SOD1 gene are among the most significant genetic contributors to amyotrophic lateral sclerosis (ALS), with different variants linked to varying disease severity. To investigate the molecular mechanisms driving this variability, we conducted RNA sequencing on spinal motor neurons (MNs) differentiated from isogenic human induced pluripotent stem cell (iPSC) lines engineered via CRISPR/Cas9. These lines carried two representative SOD1 heterogenous mutations, D91A and G94A, and were analyzed at Days 10 and 20 of neuronal maturation stage to capture the temporal changes of gene expression. We aim to explore how these mutations affect MN function, identify distinct molecular pathways that may explain the variable severity of ALS, and investigate the role of translation and metabolic dysregulation in disease progression.

bioinformatics↗

bioRxiv2025

Metabolomics-Guided Machine Learning Reveals Diagnostic and Mechanistic Biomarkers in CHB with MASLD

BackgroundMetabolic dysfunction-associated steatotic liver disease (MASLD) often coexists with chronic hepatitis B (CHB), yet early diagnosis remains challenging, particularly in non-obese patients or those with subclinical features. This study aimed to identify metabolic signatures of CHB-related MASLD and construct a predictive model using untargeted metabolomics integrated with machine learning. MethodsSerum metabolomics was performed on 160 subjects (80 CHB + MASLD and 80 healthy controls). Differential metabolites were identified and analyzed using KEGG enrichment and 4 machine learning algorithms (Random Forest, XGBoost, SVM, and LASSO). Metabolite-clinical correlations and diagnostic model performance were evaluated. ResultsA total of 924 differential metabolites were identified, with significant enrichment in pathways related to the TCA cycle, sphingolipid metabolism, and amino acid turnover. Machine learning prioritized six robust and biologically relevant metabolites: L-aspartic acid, succinic acid, caproic acid, sebacic acid, monomenthyl succinate, and glycolaldehyde, which consistently distinguished CHB + MASLD patients from controls (AUC > 0.75). These metabolites reflect key disruptions in mitochondrial function, lipid oxidation, and redox homeostasis. Integrated models combining metabolomics with clinical indices achieved perfect classification (AUC = 1.000). ConclusionCHB-associated MASLD is driven by systemic metabolic remodeling centered on mitochondrial overload, oxidative stress, and impaired amino acid metabolism. The identified metabolites provide mechanistic insights and hold promise for non-invasive MASLD screening in CHB patients. This study underscores the potential of multi-algorithmic metabolomics in advancing early diagnosis and personalized management of complex liver comorbidities.

bioinformatics↗

bioRxiv2025

Decoding cancer metabolism: A pan-cancer proteomics perspective

Metabolic reprogramming fuels cancer progression, but whether common metabolic patterns exist across tumor types remains elusive. To address this, we developed parseMetab, an R package that integrates large-scale proteomic, transcriptomic, and spatial transcriptomic datasets from 24 human cancers and 3,226 samples to map pan-cancer metabolic dysregulation. Strikingly, glycan biosynthesis pathways - especially those driving fucosylation and sialylation - were consistently upregulated, while early sugar nucleotide precursors were suppressed. Nucleotide metabolism was broadly enhanced, uncovering conserved metabolic programs that enable tumor growth, adaptation, and immune evasion. Our results highlight universal metabolic vulnerabilities that may be therapeutically exploited across diverse cancer contexts. Significance statementWhile metabolic reprogramming is a known hallmark of cancer, identifying universal patterns across diverse tumor types remains a major challenge. We developed parseMetab, a computational framework to integrate large-scale proteomic and transcriptomic data from over 3,200 samples across 24 human cancers. Our analysis reveals a striking, conserved "glyco-switch": tumors consistently prioritize the production of complex, immune-evading surface sugars (fucosylation and sialylation) while depleting their own internal sugar precursor pools. Furthermore, we demonstrate that nucleotide metabolism is broadly hyperactivated across nearly all studied malignancies. By defining these ubiquitous metabolic signatures, this study uncovers conserved vulnerabilities that transcend specific cancer types, providing a map for developing broad-spectrum metabolic therapies to combat tumor growth and immune evasion.

cancer biology↗