Biology subjects

Yang, J.

Publications and source records attributed to Yang, J..

At least 199 records · Page 11Linked to original sources

bioRxiv2025

Screening of Oyster Peptides for Anti-Muscle Atrophy Based on Machine Learning and Computer Simulation: Guided by Antioxidant Pathways

Muscle atrophy poses a serious threat to human health, with its primary pathogenic mechanisms closely linked to oxidative stress. This study focuses on the potential of oyster peptides in alleviating dexamethasone (DEX)-induced skeletal muscle atrophy and their underlying antioxidant mechanisms. Utilizing efficient integrated machine learning and computer simulation methods, a systematic screening of active peptides and mechanistic research was conducted. The results revealed that oyster peptides at concentrations of 25-50 g/mL significantly improved the decline in cell viability and myotube atrophy induced by DEX, while downregulating the expression of muscle atrophy markers Atrogin-1 and MuRF1. Through LC-MS/MS, 220 high-activity peptide sequences were identified. Following the replication and extension of the iAnOxPep integrated learning model, 15 potential antioxidant peptides were selected. Among them, the short peptide AWPGPQ demonstrated the strongest binding affinity with Keap1 and PPAR{gamma} targets. Molecular dynamics simulations confirmed its stability, suggesting that AWPGPQ may exert its dual effects--antioxidant and anti-muscle atrophy--by modulating the Keap1-Nrf2 and PPAR{gamma} signaling pathways. This study established a systematic and efficient strategy for screening natural active peptides, providing theoretical support and technical pathways for the discovery of multifunctional short peptide candidates, with significant theoretical value and application prospects.

molecular biology↗

bioRxiv2025

HGS+ enlarged vesicular compartment serves as site for coronavirus assembly at later infection stage

The precise site of coronavirus assembly remains poorly characterized. In this study, we observed that coronavirus infection induces the host factor hepatocyte growth factor-regulated tyrosine kinase substrate (HGS) to form distinct HGS enlarged vesicular compartments at later infection stage. Confocal and live-cell super-resolution microscopy showed that viral structural proteins colocalize with these HGS enlarged vesicular compartments. Correspondingly, APEX2-based electron microscopy (APEX2-EM) and immuno-EM analyses confirmed the presence of assembled virions within these unique HGS compartments, identifying them as sites of virion assembly. This was further supported by cryogenic correlated light and electron microscopy (cryo-CLEM), which captured ongoing virion formation occurring within HGS enlarged vesicles. Crucially, whole cell volume EM revealed that HGS deficiency abolishes these vesicular compartments and markedly reduces assembled virions. Lastly, we demonstrated that HGS vesicular compartments are rearranged from Golgi and endosome/lysosome by coronavirus infection. Together, these findings establish that coronavirus-induced HGS vesicular compartments function as essential platforms for virion assembly at later infection stage.

microbiology↗

bioRxiv2025

NyxBind: enhancing DNN representations via contrastive learning for TFBS prediction

While pretrained genomic language models effectively capture general DNA sequence patterns through masked language modeling, they often struggle to discriminate subtle yet biologically critical differences among transcription factor binding site (TFBS) motifs. Recent studies suggest that contrastive learning can enhance the discriminative power of embeddings by explicitly modeling inter-instance similarities and differences. Building on this insight, we introduce NyxBind, the first TFBS prediction model that applies contrastive learning across multiple TFBS types to enhance regulatory sequence representations. NyxBind better captures discriminative sequence features, enabling more accurate and biologically meaningful TFBS prediction. Extensive evaluations show that NyxBind consistently outperforms alternative models across multiple TFBS classification benchmarks, demonstrating strong robustness and generalizability. Moreover, NyxBind supports both full-parameter and parameter-efficient fine-tuning while maintaining high performance, and supports accurate motif visualization, aligning closely with experimentally validated transcription factor binding profiles. The code are available at https://github.com/ai4nucleome/NyxBind.

bioinformatics↗

bioRxiv2025

Systematic review of biodiversity monitoring shows gradual rise of scaleable and automated methods and inherent spatial and taxonomic biases

1Global policy efforts to reverse biodiversity declines are hindered by a lack of clarity over how to measure biodiversity. The debate over the best ways to define biodiversity and which metrics to use has taken place in the absence of a clear, holistic view of how biodiversity has been, and is currently, measured. This gap has hindered us moving from discussion to action on conserving biodiversity. Here we track trends in biodiversity measurement, using a dataset of >2400 papers across the last 22 years, identifying trends, biases, and gaps in the assessment of nine major taxonomic groups (Invertebrate, fish, aquatic mammal, terrestrial mammal, bird, herpetofauna, fungi, microbe and plant). We found proportional declines in invertebrate, but increases in fish, surveys over time, and fewer assessments of biodiversity in Africa and Oceania. Although we do find an increase in the use of high-throughput, scaleable methods such as eDNA and camera-traps, their uptake is more modest than might be expected and shows signs of having already plateaued. We argue that emerging technologies can, but remain underutilised in addressing the systematic biases in our understanding of biodiversity, and so in helping guide and track our progress towards restoring and saving biodiversity.

ecology↗

bioRxiv2025

Song complexity in suboscine birds: evolutionary drivers and ecological constraints

Acoustic signal complexity varies widely in the animal kingdom for reasons that remain unclear. In birds, it is widely proposed that vocal complexity evolves as an honest signal of individual quality driven by sexual selection. Other hypotheses related to social interactions include competition for ecological resources (social selection) and intra-group communication in group- living animals, both of which may favour signal complexity. However, these hypotheses are rarely explored at macroevolutionary scales, particularly in the context of constraints on sound production, transmission and detection, leading to ongoing uncertainty about the evolutionary origins of complex vocal signals. Using Bayesian phylogenetic models, we test whether different forms of social communication and ecological constraints predict the temporal and spectral complexity of songs in 1,288 species of suboscine passerine birds. We found that song complexity was reduced by sexual selection, along with other limiting factors including large body size and dense vegetation. Conversely, territoriality boosted the temporal complexity of songs. These findings challenge the common assumption that sexual selection is the main driver of increased signal complexity, and instead highlight the role of social selection as a key component of multiple inter-related drivers and constraints.

evolutionary biology↗

bioRxiv2025

DEEPReditor-CMG: A deep-learning-based predictive RNA editor for crop mitochondria genomes

C-to-U RNA editing is a pervasive phenomenon in crop mitochondria, playing a pivotal role in the processing of functional proteins encoded by mitochondrial genes and serving as a crucial regulatory mechanism for nuclear control over mitochondrial gene expression. However, identifying editing sites across the mitochondrial genome with high precision remains a formidable challenge. To address this challenge and uncover the potential regulatory patterns of C-to-U RNA editing, this study compiled a comprehensive dataset of mitochondrial genome sequences from 13 crops, including Arabidopsis thaliana, Lactuca sativa var. Capitata, Oryza sativa Japonica, and Zea mays, among others, annotated with editing sites from NCBI. Utilizing TensorFlow 2.0, we constructed a rigorous hyperparameter optimization framework, which facilitated the development of the DEEPReditor-CMG model, demonstrating superior predictive capabilities. Based on the DEEPReditor-CMG model and three interspecies relationship indices, we discovered that species with closer phylogenetic relationships exhibit more similar C-to-U RNA editing mechanisms, providing valuable insights into the evolutionary conservation of RNA editing mechanisms. We further developed executable programs for predicting C-to-U RNA editing sites in crop mitochondrial genomes, leveraging the conserved nature of the crop RNA editing machinery to maximize prediction reliability and uncover new editing sites with great potential. This research not only deepens our understanding of C-to-U RNA editing and post-transcriptional regulatory mechanisms in crop mitochondria but also paves a novel avenue for investigating RNA editing mechanisms. Experimental data, computational code, and applications are publicly accessible at https://github.com/Qinsidong/DEEPReditor-CMG. HighlightsHigh-precision prediction model for C-to-U RNA editing in crops--DEEPReditor-CMG Three interspecies relationship indices describing C to U RNA editing Prediction tools based on the conservation of crop RNA editing mechanisms Open-sourced experimental data, computational code, and applications

bioinformatics↗

bioRxiv2025

Machine learning-based definition of cellular senescence reveals pro-senescence potential implication in lung adenocarcinoma

Despite growing evidence implicating cellular senescence in tumor progression, methodological challenges in objectively quantifying senescent cell burden across cancer types continue to limit mechanistic studies and clinical translation. To address this, we developed the Predictive Cellular Senescence Model (PreCSenM), a machine learning-based tool that assigns a CS score by integrating senescence-associated features across 888 samples. Benchmarking analyses confirmed that PreCSenM markedly outperforms existing methodologies in reliably predicting senescent states within both normal and cancerous transcriptomic datasets. In lung adenocarcinoma (LUAD), PreCSenM identified the CS score as a robust predictor of clinical outcomes. Multi-omics analyses further revealed that lower CS levels correlate with decreased genomic stability and enhanced immune responses, aligning with clinical observations. Notably, drug discovery using PreCSenM identified histone deacetylase inhibitors (HDACis) as potent inducers of CS in LUAD. Transcriptional and epigenetic profiling of HDACi-treated cells pinpointed FOSB as a core transcription factor driving CS, and FOSB knockdown blocked HDACi-induced senescence. Overall, our study establishes PreCSenM as a multidimensional senescence quantification tool, bridging computational prediction with clinical relevance and mechanistic validation to enable senescence-directed therapies in precision oncology.

bioinformatics↗

bioRxiv2025

Type 2 Diabetes and Obesity Alter Exercise Training-Induced Transcriptional Adaptations to Subcutaneous White Adipose Tissue

White adipose tissue (WAT) dysfunction contributes to obesity-associated metabolic disease and type 2 diabetes (T2D). Rodent studies have demonstrated that exercise training improves WAT function, but molecular studies investigating exercise training effects on WAT in humans have been limited, particularly in the context of metabolic disease. Here, we defined the subcutaneous WAT (scWAT) transcriptome in middle-aged adults (10 male, 19 female) that were classified by lower BMI (<27 kg/m2), higher BMI ([≥]27 kg/m2), and T2D status before and after a 10-week endurance exercise regimen. At baseline, 624 genes were significantly upregulated and 112 genes downregulated in the scWAT from higher BMI participants compared to lower BMI. There was a spectrum of pathway dysregulation in scWAT in higher BMI individuals, ranging from increased markers of extracellular matrix (ECM) deposition and inflammation to decreased circadian rhythm gene expression. In people with T2D, there were additional transcriptomic differences such as translation-related pathways, selenoamino acid metabolism, and proteoglycans. Exercise training had robust effects on the transcriptome regardless of metabolic status, and notably, for the high BMI and T2D groups, training reversed several of the detrimental gene expression patterns in a cell-type-specific manner. These beneficial exercise-induced transcriptomic adaptations significantly correlated with lower levels of free fatty acids and blood pressure, particularly in participants with higher BMI and T2D. By integrating our exercise training-modulated genes with GWAS meta-analysis of physical activity, genes influenced by exercise training in the higher BMI group showed a significant enrichment in genetic associations of exercise traits in the population. A circadian rhythm-related transcription factor NR1D1 was enriched in enhancers linked with both the exercise differentially expressed genes (DEGs) and GWAS signals, suggesting a link between the circadian rhythm and training-induced adaptations. These findings demonstrate that obesity and T2D result in marked, progressive alterations in cell-type specific gene transcription in scWAT, while endurance exercise training reverses many of the metabolic disease-associated adaptations. Identification of novel molecular pathways regulated by exercise training can lead to therapeutic targets for obesity and metabolic disease.

molecular biology↗

bioRxiv2025

Castl: Robust Identification of Spatially Variable Genes in Spatial Transcriptomics via an Ensemble-based Framework

Spatially variable genes (SVGs) are essential for elucidating tissue organization within spatially resolved transcriptomics. While a number of computational methods have been developed for SVG identification, their reliance on algorithm-specific assumptions, such as predefined kernel functions or spatial neighborhood graphs, often results in substantial variability in sensitivity and inflated false discovery rates (FDRs) across heterogeneous datasets. To address this challenge, we here develop Castl, an ensemble-based framework for SVG identification that integrates multiple detection methods through statistically designed aggregation modules. Comprehensive evaluations on both simulated and real-world data demonstrate that Castl consistently identifies biologically meaningful spatial expression patterns, mitigates method-specific biases and effectively controls FDRs across various biological contexts, resolutions, and spatial technologies. This flexible, assumption-free framework offers a robust and standardized foundation for spatially informed feature discovery in complex biological systems.

bioinformatics↗

bioRxiv2025

TRPM2 is a direct pain transducer

Chronic pain results from maladaptive interaction between the immune and nervous systems. TRPM2 channels in immune cells (immune TRPM2) are believed to facilitate chronic pain by indirectly promoting immune-inflammatory responses. Whereas TRPM2 in sensory neurons (neuronal TRPM2) acts as a warmth sensor critical to sense innocuous warm temperatures. However, neuronal TRPM2 mediates the warmth sensitivity of less than 3.5% of sensory neurons. The functions of the vast majority (42%) of TRPM2+ neurons are unknown. Here we show that neuronal TRPM2 functions as a pain sensor responsible for directly transducing acute and chronic pain independently of immune TRPM2. Both chronic arthritis pain and neuropathic pain were markedly reduced in TRPM2-knockout mice, and the pain deficit was recapitulated by sole deletion of neuronal TRPM2. However, immune and inflammatory responses were largely similar between wild-type and neuronal TRPM2-deficient mice. Moreover, antagonizing joint TRPM2 rapidly reversed chronic arthritis pain without affecting joint inflammation. Mechanistically, TRPM2 is activated by PGE2 and IgG immune complex (IgG-IC) through GoA and Fc{gamma}RI coupling, respectively, independently of conventional signalling messengers. Consistently, acute pain induced by PGE2 and IgG-IC was abolished in TRPM2 mutant mice. We conclude that neuronal TRPM2 is a convergent direct pain transducer independently of inflammation, representing an appealing target for alleviating chronic pain.

neuroscience↗

bioRxiv2025

CSCN: Inference of Cell-Specific Causal Networks Using Single-Cell RNA-Seq Data

Understanding gene regulation is fundamental to deciphering the coordinated activity of genes within cells. Although single-cell RNA sequencing (scRNA-seq) enables gene expression profiling at cellular resolution, most gene network inference methods operate at the tissue or population level, thereby overlooking regulatory heterogeneity across individual cells. Recent approaches, such as Cell-Specific Network (CSN) and its extension c-CSN, attempt to construct gene networks at single-cell resolution, providing a more detailed view of the regulatory logic underlying individual cellular states. However, these methods remain limited by high false positive rates due to indirect associations and lack of directionality or causal interpretability. To address these issues, we propose the Cell-Specific Causal Network (CSCN) framework, which infers directed, cell-specific gene regulatory relationships by explicitly modeling causality. CSCN combines causal discovery techniques with efficient computation using kd-trees and bitmap indexing to perform conditional independence testing, yielding sparse and interpretable causal graphs for each cell that effectively suppress indirect and spurious associations. We demonstrate through simulations that CSCN significantly reduces false positives compared to existing methods. Furthermore, we evaluate the quality of the inferred causal networks via clustering on the Causal Katz Matrix (CKM), and CSCN outperforms CSN and c-CSN in distinguishing cellular states.

bioinformatics↗

bioRxiv2025

Chronic Ethanol Drinking Alters Medial Prefrontal Cortex and Nucleus Accumbens Astrocyte Translatome and Extracellular Matrix Glycosaminoglycans

Alcohol Use Disorder is a leading preventable cause of morbidity and mortality, yet knowledge of mechanisms driving ethanol-related neuroplasticity remains incomplete. While research has traditionally focused on neuronal signaling, emerging evidence implicates astrocytes in addiction-related adaptations. Here, we investigated the astrocyte-specific molecular consequences of chronic ethanol consumption in the prefrontal cortex and nucleus accumbens, two brain regions critical for executive control and reward processing. Using Translating Ribosome Affinity Purification RNA-seq and bulk RNA-seq in Aldh1l1-EGFP/Rpl10a mice, expressing an EGFP tag on astrocyte ribosomes, we identified hundreds of differentially translated astrocytic genes following chronic continuous two-bottle choice ethanol drinking. Sex-specific analyses revealed greater astrocytic changes in the female PFC and male NAc. Pathway enrichment highlighted extracellular matrix remodeling, synaptic signaling, mitochondrial function, and immune-related pathways. Analyses of individual drinking levels further demonstrated distinct correlations between ethanol intake and astrocytic translation. The major components of the brain extracellular matrix are chondroitin sulfate proteoglycans, produced primarily by astrocytes and covalently bound to chondroitin sulfate glycosaminoglycan chains. Complementary mass spectrometry/liquid chromatography analyses of chondroitin sulfate, heparan sulfate, and hyaluronic acid glycosaminoglycan disaccharides revealed ethanol-induced alterations in chondroitin sulfate glycosaminoglycan sulfation patterns, with additional baseline differences identified between selectively bred high- and low-ethanol preference lines. Together, these findings indicate that astrocytes undergo profound sex- and region-specific adaptations to chronic ethanol, implicating extracellular matrix and glycosaminoglycan remodeling as key risk-factors for and mediators of chronic ethanol-related neuroplasticity.

neuroscience↗

bioRxiv2025

Dynamic Meta-Networking Identifies Distinct Network Correlates of Positive and Negative Formal Thought Disorder in Schizophrenia

Formal thought disorder (FTD) is a core symptom of schizophrenia, yet the neural network mechanisms underlying this phenotype remain poorly understood. In this study, we applied a dynamic meta-networking framework, which captures temporally recurring functional network states, to investigate alterations in the language and executive control networks and their associations with positive and negative FTD. Resting-state fMRI data were collected from three independent cohorts: a discovery cohort comprising 150 first-episode, drug-naive patients with schizophrenia and 175 healthy controls (HCs); a replication cohort including 183 first-episode, drug-naive patients and 109 HCs; and a third cohort consisting of 71 patients who had received two weeks of antipsychotic treatment and 71 HCs. Meta-networking analysis identified four distinct resting-state meta-states within both the language and executive control networks. Connectivity-behavior correlation analyses and machine-learning regression models revealed that positive FTD was associated with aberrant connectivity across specific meta-states in both networks. In contrast, negative FTD was linked exclusively to dysfunction within two meta-states of the executive control network. Notably, these polarity-specific, multi-state connectivity disruptions normalized following short-term antipsychotic treatment, highlighting their potential as clinically relevant neuroimaging biomarkers.

neuroscience↗

bioRxiv2025

The Drosophila PDGF/VEGF signaling pathway regulates host immunometabolism in response to parasitoid infection

Mounting an immune response requires energy, but how that energy is reallocated at the organismal level remains poorly understood. In Drosophila melanogaster, infection by a parasitoid wasp triggers a systemic metabolic switch known as immunometabolism which is characterized by a shift in metabolic activity and the redistribution of resources away from organismal development and toward the production of a cellular immune response. We identify the PDGF/VEGF (PVF) signaling pathway as a key initiator of this immunometabolic switch. Genetic manipulation of PVF signaling alters infection outcomes, modulates systemic metabolite profiles, and reveals a direct trade-off between immune function and development. Our findings establish the Drosophila-parasitoid wasp system as a genetically tractable model for understanding the molecular basis of immunometabolism.

biochemistry↗

bioRxiv2025

Rare centenarian SIRT6 coding variants elevate SIRT6 protein levels and resist cellular senescence

Centenarians provide valuable insights into the biological mechanisms underlying human longevity and potential gerotherapeutic targets. We previously identified two linked missense variants in SIRT6 that are enriched in Ashkenazi Jewish centenarians. To investigate their functional impact in physiologically relevant cellular contexts, we generated human embryonic stem cells carrying these variants through precise genomic knock-in and differentiated them into somatic lineages. Functional characterization revealed that the centenarian variants endogenously elevated SIRT6 protein levels through weakened interaction with vimentin, and altered SIRT6 enzymatic activities including enhanced mono-ADP-ribosyl transferase activity and reduced deacetylase activity. These variants delayed replicative and progerin-induced cellular senescence, preserving genome stability through maintenance of DNA repair pathways and suppression of transposable element derepression. Moreover, pharmacologically mimicking the centenarian variants using SIRT6 activator Fucoidan-FV partially ameliorated premature aging-associated molecular defects in progeria fibroblasts. Together, our findings demonstrate that rare centenarian variants exert multifaceted effects on SIRT6 and enhance cellular resilience, providing insights for developing geroprotective therapies informed by genetic discoveries in exceptionally long-lived individuals.

cell biology↗

bioRxiv2025

Epigenetic CRISPR Screening of 9p21.3 Non-Coding Regions identifies Cis-Regulatory Elements of P16INK4a and P15INK4b Controlling Cellular Senescence

Cellular senescence is a hallmark of aging and a promising target for extending human healthspan. Senescence is often accompanied by upregulation of the key senescence marker gene CDKN2A, yet the mechanism underlying its transcriptional activation remains unclear due to complex cis-regulations within the 9p21.3 locus. Here, we performed complementary CRISPR activation and interference screens in human mesenchymal stromal cells (MSCs) to systematically map non-coding cis-regulatory elements (CREs) at this locus that epigenetically regulate senescence. This approach revealed senescence-regulating CREs (SenReg-CREs) that bidirectionally modulate senescence through P16INK4a and P15INK4b. Notably, we identified a primate-specific short interspersed nuclear element (SINE) MIR3 embedded within the most potent distal SenReg-CRE. Deletion of this SINE:MIR3 accelerated senescence, revealing its potential insulator function in restraining CDKN2A/CDKN2B activation. Collectively, these findings reveal novel mechanisms underlying senescence-associated transcriptional activation of CDKN2A/CDKN2B and demonstrate that senescence is malleable through manipulation of regulatory element activity, highlighting the potential of epigenetically targeting these SenReg-CREs for senomorphic interventions.

genomics↗

bioRxiv2025

Osmotic stress triggers fast and reversible PMF collapse in Escherichia coli

Environmental stressors routinely impact bacteria and affect their physiology. Among the most important physiological parameters is the proton motive force (PMF), that powers vital cellular processes and molecular machines. Measuring how PMF responds to environmental stress in real time requires tools that capture rapid physiological changes with high temporal resolution. Here, we use the bacterial flagella motor as an in vivo voltmeter to probe PMF dynamics during hyperosmotic shock. Because motor rotation frequency scales linearly with PMF, this approach enables single-cell electrophysiology with high temporal resolution. We find that hyperosmotic stress causes a rapid and reversible loss of PMF in Escherichia coli, independent of the osmolyte used or the presence of potassium ions. We corroborate these findings by using the Nernstian dye, tetramethyl rhodamine methyl ester (TMRM), showing that hyperosmotic shock leads to membrane depolarization. Together, our results highlight the efficacy of the flagellar motor as powerful tool for probing bacterial electrophysiology and reveal that hyperosmotic stress directly disrupts cellular energetics in addition to its mechanical effects.

biophysics↗

bioRxiv2025

Atlas of Lysosomal Aging Reveals a Molecular Clock of Storage Disorder-Associated Metabolites

Lysosomal dysfunction is a well-recognized feature of aging, yet its systematic molecular investigation remains limited. Here, we employ a suite of tools for rapid lysosomal isolation to construct a multi-tissue atlas of the metabolite changes that murine lysosomes undergo during aging. Aged lysosomes in brain, heart, muscle and adipose accumulate glycerophosphodiesters and cystine, metabolites that are causally linked to juvenile lysosomal storage disorders like Batten disease. Levels of these metabolites increase linearly with age, preceding organismal decline. Caloric restriction, a lifespan-extending intervention, mitigates these changes in the heart but not the brain. Our findings link lysosomal storage disorders to aging-related dysfunction, uncover a metabolic lysosomal "aging clock," and open avenues for the mechanistic investigation of how lysosomal functions deteriorate during aging and in age-associated diseases. One-Sentence SummaryAging in mice is tracked by a lysosomal "clock", where glycerophosphodiesters and cystine - metabolites causally linked to juvenile lysosomal storage disorders - gradually accumulate in lysosomes of the brain, heart, skeletal muscle and adipose tissue.

cell biology↗