Biology subjects

Yue, Z.

Publications and source records attributed to Yue, Z..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Contractile peri-nuclear actomyosin network PANEM repositions chromosomes from unfavorable locations to facilitate their interaction with the mitotic spindle

Chromosomes must efficiently and properly interact with the mitotic spindle during prometaphase for correct segregation in anaphase. Chromosomes at the nuclear periphery or behind the spindle poles interact less efficiently with the mitotic spindle, increasing the risk of missegregation. The mechanisms that mitigate such risks in unperturbed cells are unknown. An actomyosin network (PANEM) forms around the nucleus during prophase. While the myosin-II-dependent PANEM contraction immediately after nuclear envelope breakdown (NEBD) facilitates chromosome interaction with the mitotic spindle, the mechanism by which it does so remains unclear. Here, using human cell lines, we show that immediately after NEBD, PANEM contraction directly pushes chromosomes at the nuclear periphery or behind spindle poles toward the center of cells. Detailed tracking of kinetochore movements following light-induced activation of a myosin-II inhibitor reveals that this inward movement of chromosomes facilitates kinetochores initial interaction with spindle microtubules. It also promotes the onset of kinetochores congression towards the spindle mid-plane, but not congression itself once it starts. Thus, PANEM contraction ensures high-fidelity chromosome segregation by relocating chromosomes from unfavorable locations. Since some chromosomally unstable cancer cells fail to establish PANEM during early mitosis, the absence of PANEM may contribute to numerical chromosomal instability in these cells. Impact statementAn actomyocin network (PANEM) forms around the nucleus in prophase, and its contraction repositions peripheral and polar chromosomes to facilitate their interaction with the mitotic spindle, ensuring their correct segregation.

cell biology↗

bioRxiv2025

Cortical tension as a mechanical barrier to safeguard against premature differentiation during neurogenesis

Neuronal differentiation requires coordinated gene reprogramming and morphodynamic remodeling. How mechanical forces integrate with nuclear gene programs during neurogenesis remains unresolved. Here, we identify cortical tension as a mechanical barrier that safeguards against premature neuronal differentiation. Deletion of Plexin-B2, a guidance receptor controlling actomyosin contractility, lowers this barrier, enabling neurite outgrowth and accelerating neuronal lineage commitment. We show that coupling of extrinsic differentiation cues with intrinsic morphodynamics is essential for stabilizing neuronal fate and that cortical barrier and epigenetic barrier act in concert to regulate developmental timing. In cerebral organoids, Plexin-B2 ablation triggered premature cell-cycle exit and differentiation, resulting in progenitor pool depletion and neuroepithelial disorganization, phenotypes echoing intellectual disability in patients with rare pathogenic PLXNB2 variants. Our studies demonstrate that cortical tension functions as mechano-checkpoint that regulates the onset of neurogenesis. Lowering this barrier may provide a strategy to accelerate induced neuron generation and maturation for CNS disease modeling.

neuroscience↗

bioRxiv2025

Neutral lipid processing in glia is sexually dimorphic and promotes sleep through diacylglycerol catabolism

Sleep is thought to have a protective role in clearing toxic waste from the brain, which may include processing of damaged lipids. We recently showed that blocking endocytosis in glia increases sleep and report here that this block is associated with an increase in peroxidized lipids and glial lipid droplet accumulation, raising the possibility that accumulation of these lipids increases the need to sleep. Sleep gain induced by blocking glial transport is exaggerated by knockout of the lipid droplet coat protein, Lipid Storage Droplet 2 (Lsd2), suggesting that sleep-promoting lipids are not contained in lipid droplets. To identify lipids regulated by sleep state, we performed global, targeted lipidomics analysis on Drosophila neurons and glia, screening nearly 3,000 lipids across 11 major classes. This revealed that sex influences lipid composition in both cell types and lipid homeostasis following extended wakefulness. Female neurons and glia are enriched in ultra-long chain fatty acids, triacylglycerols, and diacylglycerols, with glial diacylglycerol enrichment correlating with elevated sleep need. Based on manipulations of neutral lipid metabolic pathways, we propose that monoacylglycerols, products of glial diacylglycerol catabolism, promote sleep.

neuroscience↗

bioRxiv2025

A PAM-CNN recognition approach to Muscle Fatigue of Special Operators by sEMG signals

Fatigue operation was the primary accident causes of large special equipment which could lead to serious economic loss and personnel injury or death, so the establishment of early fatigue warning methods was of great significance to reduce the accident rate. In view of the working environment and biomechanics properties of operators of special equipment, theoretical and experimental method was presented to analyze the fatigue mechanism and accumulate data samples, and then a new approach was proposed to recognize muscle fatigue by classifying these datasets. Firstly, in order to deduce fatigue mechanism, hidden Markov chain was adopted to build five-element theoretical model for studying interaction between machines and operators muscles during operation process, so that influence factors and tested points of muscles were approached; Surface electromyographic (sEMG) sensors were introduced to acquire muscle signals which were taken as sample data, and wavelet packet was adopted to extract features of these data. Subsequently, a convolutional neural network (CNN) classification model based on partial attention mechanism (PAM) was proposed to execute triple fatigue classification, moreover cross entropy-Adam algorithm was applied to train and optimize this model. Finally, large crane operators were taken as case studies to verify the proposed model. By comparison results indicated when the number of extracted features was 3 and the size of patch was [5,5], PAM-CNN model could approach the optimum solution of fatigue recognition, and the average accuracy could achieve 95.6% in test datasets, which showed a good potential in practical application.

bioengineering↗

bioRxiv2025

Central nervous system atlas of larval zebrafish constructed using the morphology of single excitatory and inhibitory neurons

Single-neuron morphology mapping is fundamental for deciphering brain architecture and function, yet in vertebrates it remains limited in spatial coverage and cell-type information. Here we present a nervous system-wide single-neuron morphology atlas of larval zebrafish with annotated excitatory/inhibitory identity and dendrite-axon polarity. The atlas comprises >20,000 reconstructed neurons from >13,400 animals, spanning the central and peripheral nervous system and representing [~]24.5% of the total excitatory and inhibitory neurons in the brain, all integrated into a common physical space with neuroanatomical parcellations. We define >500 excitatory and inhibitory neuronal morphotypes and construct putative inter-cell-type and interregional connectomes. Projection and morphotype analyses reveal distinct laterality and directionality biases and modular innervation patterns in excitatory and inhibitory neurons, while network analyses uncover fundamental connectivity motifs, hubs, and sensorimotor pathways. Accessible through custom-built interactive platform ZExplorer, this atlas provides a foundational resource for multimodal data integration, circuit analysis, computational modeling, and hypothesis-driven research.

neuroscience↗

bioRxiv2025

GOALS: Gene Ontology Analysis with Layered Shells for Enhanced Functional Insight and Visualization

Gene Ontologies (GOs) are standardized descriptions of gene functions in terms of biological processes, molecular functions, and cellular components, capturing their Parent-Child relationships in a structured framework and advancing cancer biological modeling to provide consistent and meaningful insights into functional genomics analysis. The conventional GO hierarchical structure is defined by human curation experts, with levels determined by the shortest path to the root term. However, grouping GOs poses challenges due to the uneven distribution of gene members within GO terms and inconsistencies in the level of detail across terms at the same GO level. In this work, we introduce Gene Ontology Analysis using Layered Shells (GOALS), a novel tool that discretizes GOAs into optimal layers. GOALS creates scalable GO layers while maintaining a balanced number of genes across GOs in each layer. Unlike existing tools, the GOALS framework organizes GO terms using a bottom-up approach based on their co-membership network, discretizing GOs to achieve an exponential fit with GOs gene member size. Meanwhile, GOALS reveals clusters or supersets reflecting biological relevance by unsupervised clustering of GOs latent projections. In a case study on mouse natural killer (NK) cell development, GOALS identified distinct GO functional clusters with multi-GO layers to reveal multiple levels of detail from specific to abstract contexts to maximize signal discovery and uncover those signals associations with trajectory divergence. More importantly, GOALS enhances enrichment analysis by introducing additional GO stratification and latent GO map that enables more accurate classification of functional differences. GOALS offers a robust and innovative framework for exploring disordered GO clusters, mining GO activities, and analyzing potential GO-GO interplays. By addressing critical challenges in functional genomics, GOALS provides a powerful tool for advancing our understanding of cell heterogeneity and potentially uncovering actionable insights for therapeutic development.

bioinformatics↗

bioRxiv2025

MF-PENS: An Efficient and Versatile Nuclear Extraction Method for Plant Single-Cell Sequencing

The widespread adoption of single-cell transcriptomics in plants remains constrained by the challenges of isolating high-quality nuclei from tissues with rigid cell walls and complex metabolomes. Here, we present methanol fixation and Percoll-enriched nuclei sorting (MF-PENS), a robust strategy designed to tackle these limitations. Distinct from conventional protocols, MF-PENS circumvents the need for fluorescence activated cell sorting (FACS) and effectively reduce RNA leakage, consistently yielding high-quality single-nucleus RNA sequencing (snRNA-seq) data. MF-PENS has been validated across various plant tissues, including fresh and frozen rice roots and leaves, as well as recalcitrant samples such as soybean root nodules, soybean seeds, and tomato fruits. Benchmarking results demonstrate that MF-PENS significantly enhances gene capture efficiency, cell clustering performance, and cell type annotation accuracy. With its broad applicability and superior performance, MF-PENS represents a robust and versatile tool for plant single-cell research, facilitating deeper insights into plant development and biology processes.

plant biology↗

bioRxiv2025

Enzyme Co-Scientist: Harnessing Large Language Models for Enzyme Kinetic Data Extraction from Literature

The extraction of molecular annotations from scientific literature is critical for advancing data-driven research. However, traditional methods, which primarily rely on human curation, are labor-intensive and error-prone. Here, we present an LLM-based agentic workflow that enables automatic and efficient data extraction from literature with high accuracy. As a demonstration, our workflow successfully delivers a dataset containing over 91,000 enzyme kinetics entries from around 3,500 papers. It achieves an average F1 score above 0.9 on expert-annotated subsets of protein enzymes and can be extended to the ribozyme domain in fewer than 3 days at less than $90. This method opens up new avenues for accelerating the pace of scientific research.

biochemistry↗

bioRxiv2024

Bipolar and schizophrenia risk gene AKAP11 encodes an autophagy receptor coupling the regulation of PKA kinase network homeostasis to synaptic transmission

Human genomic studies have identified protein-truncating variants in AKAP11 associated with both bipolar disorder (BD) and schizophrenia (SCZ), implicating a shared disease mechanism driven by loss-of-function. AKAP11, a protein kinase A (PKA) adaptor, plays a key role in degrading the PKA-RI complex through selective autophagy. However, the neuronal functions of AKAP11 and the impact of its loss-of-function remains largely uncharacterized. Through multi-omics approaches, cell biology, and electrophysiology analysis in mouse models and human induced neurons, we delineated a central role of AKAP11 in coupling PKA kinase network regulation to synaptic transmission. Loss of AKAP11 distorted compartment-specific PKA and GSK3/{beta} activities and impaired cellular functions that significantly overlap with pathways associated with BD and SCZ. Moreover, we identified interactions between AKAP11, the PKA-RI adaptor SPHKAP, and the ER-resident autophagy-related proteins VAPA/B, which co-adapt and mediate PKA-RI complex degradation in neurons. Notably, AKAP11 deficiency impaired neurotransmission, providing key insights into the mechanism underlying AKAP11-associated psychiatric diseases.

neuroscience↗

bioRxiv2024

Structure-Based Design of Covalent Nanobody Binders for a Thermostable Green Fluorescence Protein

Green fluorescence protein (GFP) lights up almost every aspects of life sciences. An ultra thermostable GFP (TGP), engineered from a coral GFP, offers potential advantages over traditional jellyfish-derived GFP due to its high stability. However, owing to its later discovery, TGP lacks the extensive toolsets available for GFP, such as heavy chain-only antibody binders known as nanobodies. In this study, we have structurally characterized TGP in complex with Sb92, a synthetic nanobody identified from a previous in vitro screening, revealing its precise three-dimensional epitope. This structural insight, alongside the previously characterized Sb44-TGP complex, have allowed us to rationally design disulfide bonds between antigen and antibody for tighter interactions. Using biochemical analyses, we identify two bridged complexes (TGP A18C-Sb44 V100C, TGP E118C-Sb92 S57C), with the TGP-Sb92 disulfide pair showing high resistance to reducing agents. Our study expands the toolkit available for TGP and should encourage its wider applications.

biochemistry↗

bioRxiv2024

Toden-E: Topology-Based and Density-Based Ensembled Clustering for the Development of Super-PAG in Functional Genomics using PAG Network and LLM

The integrative analysis of gene sets, networks, and pathways is pivotal for deciphering omics data in translational biomedical research. To significantly increase gene coverage and enhance the utility of pathways, annotated gene lists, and gene signatures from diverse sources, we introduced pathways, annotated gene lists, and gene signatures (PAGs) enriched with metadata to represent biological functions. Furthermore, we established PAG-PAG networks by leveraging gene member similarity and gene regulations. However, in practice, high similarity in functional descriptions or gene membership often leads to redundant PAGs, hindering the interpretation from a fuzzy enriched PAG list. In this study, we developed todenE (topology-based and density-based ensemble) clustering, pioneering in integrating topology-based and density-based clustering methods to detect PAG communities leveraging the PAG network and Large Language Models (LLM). In computational genomics annotation, the genes can be grouped/clustered through the gene relationships and gene functions via guilt by association. Similarly, PAGs can be grouped into higher-level clusters, forming concise functional representations called Super-PAGs. TodenE captures PAG-PAG similarity and encapsulates functional information through LLM, in characterizing network-based functional Super-PAGs. In synthetic data, we introduced a metric called the Disparity Index (DI), measuring the connectivity of gene neighbors to gauge clusterability. We compared multiple clustering algorithms to identify the best method for generating performance-driven clusters. In non-simulated data (Gene Ontology), by leveraging transfer learning and LLM, we formed a language-based similarity embedding. TodenE utilizes this embedding together with the topology-based embedding to generate putative Super-PAGs with superior performance in semantic and gene member inclusiveness.

bioinformatics↗

bioRxiv2024

Targeting Specific Kinase Substrates Rescues Increased Colitis Severity Induced by the Crohn's Disease-Linked LRRK2-N2081D Variant

LRRK2 contains a kinase domain where both the N2081D Crohns disease (CD) risk and the G2019S Parkinsons disease (PD)-pathogenic variants are located. The mechanisms by which the N2081D variant increase CD risk, and how these adjacent mutations result in distinct diseases, remain unclear. To investigate the pathophysiology of the CD-linked LRRK2 N2081D variant, we generated a knock-in (KI) mouse model and compared its effects to those of the LRRK2-G2019S mutation. We find that Lrrk2N2081D KI mice demonstrate heightened sensitivity to induced colitis, resulting in more severe inflammation and intestinal damage than Lrrk2G2019SKI and wild-type mice. Analysis of Colon tissue revealed distinct mutation-dependent LRRK2 RAB substrate phosphorylation, with significantly elevated phosphorylated RAB10 levels in Lrrk2N2081D mice. In cells, we demonstrate that the N2081D mutation activates LRRK2 through a mechanism distinct from that of LRRK2-G2019S. We further find that proinflammatory stimulation enhances LRRK2 kinase activity, leading to mutation-dependent differences in RAB phosphorylation and inflammatory responses in dendritic cells. Finally, we show that genetic knockout of Rab12, but not pharmacological LRRK2 kinase inhibition, significantly reduced colitis severity in Lrrk2N2081D mice. Our study characterizes the pathogenic mechanisms of LRRK2-linked CD, highlights important structural and functional differences between disease-associated LRRK2 variants, and suggests RAB proteins as promising therapeutic targets for modulating LRRK2 activity in CD treatment.

molecular biology↗

bioRxiv2024

Activation of the influenza B M2 proton channel (BM2)

Influenza B viruses have co-circulated during most seasonal flu epidemics and can cause significant human morbidity and mortality due to their rapid mutation, emerging drug resistance, and severe impact on vulnerable populations. The influenza B M2 proton channel (BM2) plays an essential role in viral replication, but the mechanisms behind its symmetric proton conductance and the involvement of a second histidine (His27) cluster remain unclear. Here we perform the membrane-enabled continuous constant-pH molecular dynamics simulations on wildtype BM2 and a key H27A mutant to explore its pH-dependent conformational switch. Simulations capture the activation as the first histidine (His19) protonates and reveal the transition at lower pH values compared to AM2 is a result of electrostatic repulsions between His19 and pre-protonated His27. Crucially, we provide an atomic-level understanding of the symmetric proton conduction by identifying pre-activating channel hydration in the C-terminal portion. This research advances our understanding of the function of BM2 function and lays the groundwork for further chemically reactive modeling of the explicit proton transport process as well as possible anti-flu drug design efforts.

biophysics↗

bioRxiv2024

RAB12-LRRK2 Complex Suppresses Primary Ciliogenesis and Regulates Centrosome Homeostasis in Astrocytes

Leucine-rich repeat kinase 2 (LRRK2) phosphorylates a subset of RAB GTPases, and the phosphorylation levels are elevated by Parkinsons disease (PD)-linked mutations of LRRK2. However, the precise function of the specific RAB GTPase targeted by LRRK2 signaling in the brain remains to be elucidated. Here, we identify RAB12 as a robust LRRK2 substrate in the mouse brains through phosphoproteomics profiling and solve the structure of RAB12-LRRK2 protein complex through Cryo-EM analysis. Mechanistically, RAB12 cooperates with LRRK2 to inhibit primary ciliogenesis and regulate centrosome homeostasis in astrocytes through enhancing the phosphorylation of RAB10 and recruiting Rab interacting lysosomal protein like 1 (RILPL1), while the functions of RAB12 require a direct interaction with LRRK2 and LRRK2 kinase activity. Furthermore, the ciliary deficits and centrosome alteration caused by the PD-linked LRRK2-G2019S mutation are prevented by the deletion of Rab12 in astrocytes. Thus, our study reveals a physiological function of the RAB12-LRRK2 complex in regulating ciliogenesis and centrosome homeostasis. The RAB12-LRRK2 structure offers a guidance in the therapeutic development of PD by targeting the RAB12-LRRK2 interaction.

neuroscience↗

bioRxiv2024

Exclusion of condensin I from the nucleus during prophase coordinates mitotic chromosome reorganization to complete sister chromatid resolution

AbstractDuring early mitosis, chromosomes are reorganized from their relatively decompacted interphase state into characteristic mitotic rod-shaped structures. This process is important to allow correct segregation of newly replicated sister chromatids to the opposite spindle poles during anaphase. To facilitate mitotic chromosome organization, two protein complexes named condensin I and condensin II play crucial roles. Condensin II is particularly important for achieving sister chromatid separation (resolution) whilst condensin I is required for chromosome condensation (compaction). Although sister chromatid resolution occurs 15-20 min earlier before chromosome compaction, it is not yet clear how these events are temporally coordinated or whether this temporal coordination is important to ensure chromosome segregation later in mitosis. One hypothesis is that the temporal coordination is achieved through different subcellular localisation of two condensin complexes; whilst condensin II localizes in the nucleus, condensin I is restricted to the cytoplasm, during interphase and prophase. In this study we tested this hypothesis by engineering the localization of condensin I to the nucleus. We monitored sister chromatid resolution and chromosome compaction by real-time imaging that visualized selected neighboring chromosome loci. We found that localization of condensin I to the nucleus led to precocious chromosome compaction during prophase with a similar timing to sister chromatid resolution. We also monitored later stages of mitosis and found that cells expressing nuclear condensin I subsequently exhibited frequent chromosome mis-segregation in anaphase. Therein, the majority of mis-segregated chromosomes consisted of lagging chromosomes involving both sister chromatids. This suggests that the temporal control of mitotic chromosome reorganization is crucial for high-fidelity chromosome segregation. In conclusion, the exclusion of condensin I from the nucleus during prophase delays chromosome compaction and allows condensin II to complete sister chromatid resolution, which ensures correct chromosome segregation later in mitosis.

cell biology↗

bioRxiv2024

Explorative Discovery of Gene Signatures and Clinotypes in Glioblastoma Cancer Through GeneTerrain Knowledge Map Representation

This study introduces the GeneTerrain Knowledge Map Representation (GTKM), a novel method for visualizing gene expression data in cancer research. GTKM leverages protein-protein interactions to graphically display differentially expressed genes (DEGs) on a 2-dimensional contour plot, offering a more nuanced understanding of gene interactions and expression patterns compared to traditional heatmap methods. The research demonstrates GTKMs utility through four case studies on glioblastoma (GBM) datasets, focusing on survival analysis, subtype identification, IDH1 mutation analysis, and drug sensitivities of different tumor cell lines. Additionally, a prototype website has been developed to showcase these findings, indicating the methods adaptability for various cancer types. The study reveals that GTKM effectively identifies gene patterns associated with different clinical outcomes in GBM, and its profiles enable the identification of sub-gene signature patterns crucial for predicting survival. The methodology promises significant advancements in precision medicine, providing a powerful tool for understanding complex gene interactions and identifying potential therapeutic targets in cancer treatment.

bioinformatics↗

bioRxiv2024

Transcranial Photobiomodulation on the Left Prefrontal Cortex Enhances Mandarin Chinese L1 and L2 Complex Sentence Processing Performances

This study investigated the causal effect of transcranial photobiomodulation (tPBM) over the left prefrontal cortex (LPFC) on syntactically complex Mandarin Chinese first language (L1) and second language (L2) sentence processing performances. Two (L1 and L2) groups of participants (thirty per group) were recruited to receive the double-blind, sham-controlled tPBM intervention, followed by the sentence processing, the verbal working memory (WM), and the visual WM tasks. Results revealed a consistent pattern for both groups: (a) tPBM enhanced sentence processing performance but not verbal WM and visual WM performance; (b) Participants with lower sentence processing performances under sham tPBM benefited more from active tPBM. Taken together, the current study substantiated that tPBM enhanced L1 and L2 sentence processing ability directly without verbal WM interference, and would serve as a promising and cost-effective noninvasive brain stimulation (NIBS) tool for future applications on upregulating the human language faculty. HighlightsO_LIThe first study that applies tPBM to (complex) sentence processing. C_LIO_LItPBM enhances sentence processing performances in both Mandarin L1 & L2 speakers. C_LIO_LItPBM directly enhances sentence processing without the interference of verbal WM. C_LIO_LIA causal role of LPFC for sentence processing through active tPBM. C_LIO_LIOpening up the promising application prospect for tPBM on sentence processing. C_LI

neuroscience↗

bioRxiv2023

Identification of functional genes underlining growth in large yellow croaker

Large yellow croaker (Larimichthys crocea) is the largest cultured marine fish in China, although its economic benefits are significant, its growth cycle is long and it takes 2 years to market. Identification of genomic variations and genes affecting the growth of L. crocea is of great significance for breeding fast-growing strains by molecular means. We utilized whole genome resequencing to identify a highly effective GWAS locus on chromosome 6 of the genome, and identified some candidate genes that affect growth. This study provides a theoretical basis for analyzing the genetic mechanism of growth traits of L. crocea and cultivating fast-growing varieties.

genetics↗