Biology subjects

Zhu, Z.

Publications and source records attributed to Zhu, Z..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

Reprogramming the Immune Suppressive Tumor Microenvironment in Glioma Enhances the Efficacy of Immune-Mediated Gene Therapy

Gliomas account for ~80% of primary malignant brain tumors. Many CNS WHO grade 2-3 and some grade 4 gliomas harbor mutant isocitrate dehydrogenase 1 (mIDH1), which causes a gain of function mutation (IDH1 R132H) leading to the production of 2-hydroxyglutarate (2HG). Mutant IDH1-induced 2HG, through epigenetic reprogramming elicits an immune-permissive tumor microenvironment (TME). An immunosuppressive mechanism in the glioma TME involves adenosine production via the ectoenzyme CD73. This study investigates mIDH1s influence on CD73 expression and adenosine levels. We demonstrate that mIDH1 glioma cells exhibit reduced CD73 expression, driven by DNA hypermethylation, leading to reduced adenosine levels. Since wtIDH1 gliomas have high CD73 expression, we evaluated CD73 blockade as an immunotherapy target. We show that CD73 inhibition used as monotherapy, did not improve survival in wtIDH1 glioma-bearing mice. However, when combined with immune-stimulatory Ad-TK (adenoviral vectors encoding herpes simplex virus thymidine kinase) and Ad-Flt3L (adenoviral vectors encoding FMS-like tyrosine kinase 3 ligand) gene therapy, CD73 blockade significantly enhanced therapeutic efficacy and increased anti-glioma effector T cell activity. These findings reveal that CD73 inhibition used in combination with immune stimulatory Ad-TK/Ad-Flt3L gene therapy may be an effective treatment for wtIDH1 gliomas, which could be readily translated to the clinical arena.

cancer biology↗

bioRxiv2025

Cross-task, explainable, and real-time decoding of human emotion states by integrating grey and white matter intracranial neural activity

Decoding human emotion states from intracranial neural activity is key in developing brain-computer interfaces and new therapies for affective disorders. However, real-world application of decoding requires high performance that integrates neural activity from both grey and white matter, stable generalization across different contexts, sufficient neural encoding explainability, and robust real-time implementation, all of which remain elusive. Here, we simultaneously recorded intracranial electroencephalogram (iEEG) and abundant self-rated valence and arousal scores across two emotion-eliciting tasks in eighteen subjects, forming the largest intracranial neural dataset for emotion decoding. We then developed personalized decoding models within a hybrid deep learning framework involving both self-supervised and supervised components. The models achieved high-performance decoding of continuous valence/arousal states, doubling the R-squared performance of prior EEG/iEEG decoding. Critically, the models significantly improved performance by integrating grey and white matter signals and demonstrated cross-task generalization. The models further revealed shared and preferred mesolimbic-thalamo-cortical subnetworks encoding valence and arousal, showing neurophysiological explainability. Finally, the models realized robust real-time decoding in four new subjects. Our results have implications for advancing emotion decoding neurotechnology toward deployable affective brain-computer interfaces and closed-loop therapeutic systems for affective disorders.

neuroscience↗

bioRxiv2025

NADH dehydrogenase reverses dietary and clock metabolic syndrome

Circadian clocks are internal timing systems that enable organisms to anticipate and adapt to daily environmental changes. These rhythms arise from a transcription-translation feedback loop in which CLOCK/BMAL1 regulate the expression of thousands of genes, including their repressors PER/CRY1. Disruption of circadian rhythms contributes to obesity, metabolic disease, and cancer2-4, yet how the clock maintains metabolic homeostasis remains limited. Here we report that the clock regulates oxidative metabolism through diurnal respiration of mitochondrial respiratory chain complex I. Genetic loss of the clock and high fat diet feeding in male mice led to reduced complex I respiration within adipocytes, leading to suppression of PPAR and insulin signaling pathways. In contrast, preserving complex I function maintained adipogenic and metabolic gene networks and protected against diet- and circadian-induced metabolic dysfunction independently of weight gain. These findings reveal that circadian disruption impairs metabolic health through mitochondrial complex I dysfunction, establishing clock control of complex I as a key regulator of transcriptional and metabolic homeostasis.

cell biology↗

bioRxiv2025

Population density triggers wing dimorphism via NlNompC-mediated insulin signaling in Nilaparvata lugens

The Nilaparvata lugens employs wing dimorphism as a key adaptive strategy to environmental heterogeneity. While hormonal pathways and transcription factors governing nutrient-induced wing plasticity are known, how population density triggers developmental divergence remains unresolved. Here, we mechanistically dissect density-dependent wing morph determination, revealing tactile inter-individual contact as the primary signal. High-density conditions amplify gentle-touch frequency, which is detected by mechanosensitive ion channels NlNompC and NlNMDARs. Genetic silencing or pharmacological inhibition of these channels abolished density-induced long-winged morphogenesis. The conserved role of NlNompC in gentle-touch sensation was validated by rescuing tactile perception deficits in Drosophila nompC mutants. Crucially, NlNompC integrates tactile cues into insulin/insulin-like growth factor signaling (IIS): crowding-driven mechanical stimuli upregulate NlIlp3, while suppressing NlInR2, to activate wing elongation programs. Epistasis experiments confirmed IIS as the key downstream pathway, with co-silencing NlInR2 or NlFoxO rescuing the short-winged phenotype induced by NlNompC knockdown or low population density, silencing NlIlp3 or NlInR1 rescuing the long-winged phenotype induced by high population density. Our work uncovers a mechano-endocrine axis linking tactile perception to developmental plasticity, bridging ecological cues with molecular pathways. These findings redefine density sensing beyond chemical modalities and offer actionable targets for disrupting pest dispersal strategies, advancing sustainable agriculture.

molecular biology↗

bioRxiv2025

Tracking seasonal variation in modal properties of an open-grown green ash (Fraxinus pennsylvanica)

Despite longstanding interest and varied applications, the vibration behavior of trees remains poorly understood, largely due to methodological limitations. To more effectively identify and partition sources of natural variation in the modal properties of trees, there is a need for more reliable estimates derived from long-term observations. Using improved Bayesian methods, the modal properties of one green ash tree were identified over an entire growing season with simultaneous measurements of nearby weather conditions and phenological observations. The analysis confirmed many features of tree vibration observed in an earlier related study, including two prevalent close, nearly orthogonal modes and amplitude dependence for modal properties, but the more extensive and detailed measurements also revealed new characteristics, including changes in the arrangement of partial mode shapes and sizeable variation in modal properties over multiple time scales. For the leafless tree, the two modes were consistently oriented in directions aligned with the planting layout of surrounding trees, but their orientation varied erratically over time, while remaining roughly perpendicular to one another, during periods with leaves. Though some of the modal property variation closely paralleled other measurements, including weather conditions and vegetative phenophases, in physically reasonable ways, the reasons for other changes were not clear. Using a detailed assessment of the governing factors for estimate uncertainty, the cause of low-quality estimates was attributed to very close or nearly identical modes, and the causes and implications of close modes for tree vibration monitoring should be a main priority for future studies.

biophysics↗

bioRxiv2025

Directed evolution of a compact TranC11a system for efficient genome editing

The recently discovered TranC systems represent programmable RNA-guided DNA endonucleases of transposon origin with compact protein sizes ideal for therapeutic delivery. However, their editing efficiency in human and plant cells is limited. Here, we evolved TranC11a and engineered its sgRNA to enhance overall editing efficiencies. TranC11a systems exhibit up to 9.2-fold higher editing activity than its parent and achieves efficiency comparable to SpCas9 across multiple human genome endogenous sites, significantly outperforming compact editors NovaIscB and enTnpB1c. TranC11a enables efficient editing of disease-relevant genes in human cells and breeding traits in maize. With its high editing activity and compact size (574 aa), TranC11a demonstrates strong potential for future in vivo genome editing and crop engineering.

synthetic biology↗

bioRxiv2025

Discrete interneuron subsets participate in GluN1/GluN3A excitatory glycine receptor (eGlyR)-mediated regulation of hippocampal network activity throughout development and evolution.

Decades of studies implicating GluN3A N-methyl-D-aspartate receptor (NMDAR) subunits in physiological and pathological function have largely been interpreted through direct regulation of conventional glutamatergic NMDARs. However, emerging evidence indicates that GluN3A frequently assembles with GluN1 forming unconventional glutamate-insensitive NMDARs that operate as native excitatory glycine receptors (eGlyRs). Here we demonstrate that hippocampal somatostatin and neurogliaform interneurons (Sst-INs and NGFCs) express functional eGlyRs from early postnatal through adult ages. In the developing hippocampus eGlyR-mediated excitation of NGFCs with ambient glycine dramatically increases GABAergic tone, with consequences for the generation of giant depolarizing potentials (GDPs). In the mature hippocampus, eGlyR- mediated excitation of Sst-INs regulates sharp wave ripples (SWRs). Finally, we reveal evolutionary conservation of hippocampal Sst-IN eGlyRs and eGlyR- mediated SWR regulation in non-human primates confirming functional eGlyR availability for therapeutic potential in higher species. Our findings underscore that eGlyR mediated regulation of cell and circuit excitability through both cell autonomous and cell non-autonomous mechanisms must be considered to understand GluN3A roles in brain development, plasticity, and disease.

neuroscience↗

bioRxiv2025

YeastSAM: A Deep Learning Model for Accurate Segmentation of Budding Yeast Cells

An essential step for quantitative image analysis is cell segmentation, which is the process of defining the outline of individual cells in microscopy images. Segmentation of budding yeast is challenging due to their asymmetric cell division and mother-bud morphology. As a result, a dividing cell is frequently misidentified as two separate cells, causing errors in downstream analysis. Here, we overcame this challenge by developing YeastSAM, a deep learning-based segmentation framework derived from {micro}SAM and optimized for budding yeast. YeastSAM achieves more than threefold higher accuracy in segmenting dividing cells compared to existing methods. When combined with single-molecule RNA imaging and organelle imaging, YeastSAM facilitates quantitative analysis of the spatial regulation of gene expression. This study offers an accessible, high-accuracy model for yeast cell segmentation, empowering researchers with minimal programming experience to perform quantitative image analysis.

cell biology↗

bioRxiv2025

Evolutionary remodeling of non-canonical ORF translation in mammals

Non-canonical open reading frames (ncORFs) are pervasive within transcripts annotated as "non-coding" or "untranslated regions" of mRNAs, yet their landscape under normal physiological conditions remains to be fully resolved, particularly outside humans. Here we applied a stringent and standardized pipeline to hundreds of high-quality ribosome profiling libraries from normal mammalian tissues and cell types, identifying 11,623 human and 16,485 mouse ncORFs. Evolutionary analyses revealed that thousands of ncORFs are subject to coding constraint and exhibit lineage-specific conservation, underscoring their functional potential. Ancient ncORFs are preferentially highly translated, broadly expressed, and enriched for lineage-specific conservation. Co-expression patterns further indicate that many ncORFs, especially ancient ones, are cotranslated with canonical coding sequences, consistent with functions mediated through protein-protein interactions. Together, these findings establish a comprehensive atlas of mammalian ncORFs and provide fundamental insights into their evolutionary dynamics and functional integration within the proteome.

genomics↗

bioRxiv2025

Dual-LLM Adversarial Framework for Information Extraction from Research Literature

Information Extraction (IE) is a fundamental task in Natural Language Processing (NLP) that aims to automatically identify relevant information from unstructured or semi-structured data. Information extraction from lengthy research literature, particularly in multi-omics studies, faces significant challenges due to their complex narratives and extensive context. To address this, we present a novel dual-LLM adversarial framework in which one large language model (LLM) performs the extraction and another provides iterative feedback to refine the results. This process systematically reduces errors, enhances consistency across heterogeneous data sources, and converges toward more accurate outputs. We evaluated our approach against manual and single-LLM extraction, using LLMs as evaluators. Experimental results show that our adversarial framework outperforms these baselines, highlighting its effectiveness for extracting structured information from lengthy scientific texts.

bioinformatics↗

bioRxiv2025

PepCCD: A Contrastive Conditioned Diffusion Framework for Target-Specific Peptide Generation

Peptide-based drug design targeting "undruggable" proteins remains one of the most critical challenges in modern drug discovery. Conventional peptide-discovery pipelines rely on low-throughput experimental screening, which is both time-consuming and prohibitively expensive. Moreover, existing computational approaches for designing peptides against target proteins typically depend on the availability of high-quality structural information. Although recent structure-prediction tools such as AlphaFold3 have achieved break-throughs in protein modeling, their accuracy for functional interfaces remains limited. The acquisition of high-resolution structures is often expensive, time-intensive, and particularly challenging for targets with dynamic conformations, further restricting the efficient development of peptide therapeutics. Additionally, current sequence-based generative methods follow a paradigm that relies on known templates, which limits the exploration of sequence space and results in generated peptides lacking diversity and novelty. To address these limitations, we propose a contrastive conditioned diffusion framework for target-specific peptide generation, referred to as PepCCD. It employs a contrastive learning strategy between proteins and peptides to extract sequence-based conditioning representations of target proteins, which serve as precise conditions to guide a pre-trained diffusion model to generate peptide sequences with the desired target specificity. Extensive experiments on multiple benchmark target proteins demonstrate that the peptides designed by PepCCD exhibit strong binding affinity and outperform state-of-the-art methods in terms of diversity and generation efficiency.

bioinformatics↗

bioRxiv2025

Human mammary 3D spheroid models uncover the role of filopodia in breaching the basement membrane to facilitate invasion

Basement membranes (BM) are thin, nanoporous sheets of specialized extracellular matrix (ECM) that line epithelial tissues. They are dynamic structures that serve multiple key functions, as evidenced by numerous diseases, including cancer progression, that are associated with their alterations. Our understanding of the BM and its communication with adjoining epithelial cells remains highly fragmented due to the BMs complex molecular architecture, the lack of molecular tools, limitations in utilizing high-resolution imaging techniques to BMs assembled on tissues, and the difficulty of assessing their functional contributions in vivo. Here, by combining multiple -omics analyses and advanced microscopy methodologies, we characterized the BM from two normal human mammary epithelial cell lines, MCF10 and HMLE, grown as spheroids in 3D matrices. Our findings indicate that the spheroids autonomously assemble a BM exhibiting all the molecular, structural, and biophysical characteristics of physiological BM. Using these minimalist model systems, we show for the first time that the laminins, perlecan, and the hemidesmosomes are all arranged along a shared porous lattice defined by the collagen IV molecular network. Next, we demonstrate that the invasion-promoting PSD4/EFA6B knockout, found in patients with breast cancer, decreases the expression of BM components and their assembly on the spheroid surface. We then show that invasive spheroids develop enlarged pores in the BM via filopodia-like plasma membrane extensions, which further expand in a protease-dependent manner, thereby facilitating the passage of invasive cells. Significance StatementThe basement membrane (BM) directs epithelial tissue architecture and behavior. How tumor cells breach this barrier during invasion remains poorly understood. Using minimalist 3D spheroid models mimicking physiological BM assembly, we reveal a novel infiltration mechanism. Filopodia-like protrusions perforate and widen BM pores. This facilitates cell dissemination through sequential protease-independent and -dependent steps.

cell biology↗

bioRxiv2025

BACH2 dosage establishes the hierarchy of stemness and finetunes antitumor immunity in CAR T cells

Self-renewing stem-like T cells promote the efficacy of cancer immunotherapy and are a heterogeneous population with sub-lineages demonstrating different degrees of stemness. At the apex of this hierarchy is long-term (LT) stem-like T cells with the highest capacity of persistence, repopulation and response to immune checkpoint inhibitors (ICI). However, the pathway that establishes the hierarchy of stemness in chimeric antigen receptor (CAR) T cells and its role in antitumor efficacy of CAR T cells are unclear. Here, we demonstrate that LT stem-like differentiation and antitumor immunity of CAR T cells are dose-dependently regulated by BACH2. Pre-infusion LT stem-like CAR T cells showed epigenetic activation of BACH2 and superior antitumor response in mice and humans. After clearing tumor in vivo, LT stem-like T cells emerged as a CAR subset that transcriptionally and epigenetically upregulated BACH2 and downregulated TOX. Loss-of-function experiments revealed an essential role of BACH2 in the antitumor response of CAR T cells and the transcriptional program of LT stem-like CAR T cells. In exhaustion-prone GD2 CAR T cells with high tonic signaling, we showed that quantitative control of BACH2 protein level by a small molecule drug finetuned the degree of stemness and exhaustion in CAR T cells. Chemically inducing temporal BACH2 activation during manufacture of GD2 CAR T cells imprinted greater antitumor immunity against solid tumor after infusion. Together, we show that BACH2 dosage establishes the hierarchy of stem-like CAR T cells and can be temporally and tunably controlled in CAR T cells to optimize differentiation and antitumor immunity.

cancer biology↗

bioRxiv2025

Mathematical Foundations of Beta Diversity: Why Common Metrics Fail in Microbiome Analysis

BackgroundIn microbiome studies, beta diversity quantifies dissimilarity between samples and is often visualized using ordination techniques. It enables researchers to characterize ecological structure, compare microbial communities, assess environmental or host-driven heterogeneity, and track longitudinal shifts over time. Although many diversity indices were originally developed with practical goals in mind, they lack a unified framework to ensure theoretical rigor and validity. This gap makes it challenging for researchers to evaluate and select appropriate beta diversity measures for microbiome analyses, potentially leading to biased analyses and invalid conclusions. ResultsTo bridge the persistent knowledge gaps, we systematically evaluate the commonly used beta diversity measures according to key mathematical properties, including whether they are true metrics, conform to Euclidean geometry, and satisfy conditional negative definiteness. We show that their violations can compromise downstream analyses such as PCoA, PERMANOVA, and kernel-based tests. In addition, drawing on mathematical consensus, we introduce a novel four-category classification of beta diversity measures: scale difference, difference scale, Hamming difference, and distribution difference. Complementing this framework, we build diagnostic tools for assessing Euclidean validity and develop remedial strategies that correct problematic dissimilarity matrices while preserving ordination structures. We demonstrate the effectiveness of these solutions using real-world microbiome datasets. ConclusionsThese results establish a unified framework for evaluating beta diversity in microbiome research, supported by an R package, interactive Shiny app, and step-by-step tutorials. The framework provides a clear roadmap for selecting and refining dissimilarity metrics, paving the way for future methodological advances.

bioinformatics↗

bioRxiv2025

Human single-cell atlas analysis reveals heterogeneous endothelial signaling

Endothelial cells (ECs) play complex roles across tissues and vessel types. Yet, systematic investigations of EC heterogeneity in the combined context of vessel type and tissue microenvironment are still largely lacking. We integrated over three million single cells of scRNA-seq datasets in 15 human tissues and found that ECs in some tissues (e.g., heart and kidney) exhibited greater tissue specificity, while others displayed more substantial vessel specificity. We developed a computational pipeline to analyze cell-cell communications (CCC) mediated by metabolites or proteins to explore microenvironmental regulation. Interestingly, our results showed that CCC events involving ECs varied vastly across tissues, highlighting tissue-specific EC interactions. Using topic modeling, we identified CCC patterns, termed CCC topics, representing metabolite- and protein-mediated interactions between ECs and other tissue-resident cells. Most CCC topics exhibited high tissue specificity, potentially explaining microenvironmental regulations for EC heterogeneity. The work systematically investigates EC heterogeneity and provides insights into how EC heterogeneity was regulated across diverse tissue microenvironments.

bioinformatics↗

bioRxiv2025

Helicobacter pylori genome aggregation database reveals complex evolutionary forces shaping its genomic landscape and clinical impact in East Asia

We assembled HPgnomAD, a comprehensive global genome aggregation database of Helicobacter pylori (H. pylori) featuring 7,544 high-quality genomes from 278 populations, along with the first species-wide haplotype reference panel for genotype imputation. The panel provides high accuracy across diverse H. pylori populations, including those from low-coverage data, and is openly accessible with integrated analysis tools (https://www.hpgnomad.top/). Variant discovery revealed 1.82 million SNPs and 0.65 million InDels, with African strains exhibiting the most tremendous diversity and East Asian strains showing unexpectedly high novel variation. Fine-scale analysis of the hpEAsia lineage revealed six new sublineages shaped by altitude-, latitude-related divergence and region-specific admixture. Phylogenomic dating revealed two divergence waves in East Asia, paralleling Upper Paleolithic settlement and Neolithic human expansions, with highland-lowland separation at [~]18.8 kya, followed by the formation of complex geography-related population substructures. Genome-wide scans revealed adaptive loci related to metal acquisition, nitrogen metabolism, surface adhesion, and membrane transport, including altitude-associated highly differentiated variants linked to antibiotic resistance and gastric disease. By integrating genomic, evolutionary, environmental, and clinical data, HPgnomAD offers a framework for understanding H. pylori evolution, host-pathogen adaptation, and precision medicine worldwide.

evolutionary biology↗

bioRxiv2025

Angiogenic CD8 T cells from PWH induce Granzymes-dependent PAR1 activation promoting endothelial inflammation

In people with HIV (PWH), T cell immune activation and endothelial inflammation are contributors of the increased cardiovascular risk, however the mechanisms remain poorly understood. PAR1 connects the coagulation cascade, endothelial cells and CD8 T cells at the site of endothelial inflammation and we hypothesized that HIV driven CD8 T cell immune activation alters endothelial repair mechanisms. Endothelial repair is partially mediated by angiogenic T (Tang) cells that facilitate proliferation of endothelial cells, and differentiation of endothelial progenitor cells at site of vascular injury. During LCMV infection, we identified a subset of CD31highCD8 T cells that exhibited a long-lived memory precursor phenotype (CD127+KLRG1-) and secreted the proangiogenic cytokine vascular endothelial growth factor (VEGF) after viral control. Furthermore, in PWH, the frequencies of CD8 Tang cells were reduced and showed an activated phenotype and expression of granzymes. GZMA+GZMB+CD8 Tang cells correlated with atherosclerotic cardiovascular disease (ASCVD) risk. In vitro, granzyme dependent PAR1 activation led to calcium mobilization and secretion of proinflammatory cytokines IL-6, IL-8 and angiopoietin-2 by primary human endothelial cells. Altogether, these findings suggest that CD8 T cells are involved in immunity against viruses and endothelial homeostasis and HIV driven immune activation alters these functions.

immunology↗

bioRxiv2025

StCEL-based platform enables detection and sequencing of native sialoglycoRNA

Glycosylated RNAs (glycoRNAs) are an emerging class of biomolecules characterized by glycans attached to RNA molecules. Currently, glycoRNA detection remains largely confined to cellular models, substantially impeding its functional characterization and clinical translation. Here, we developed sialyltransferase-mediated chemical enzymatic labeling (StCEL), in which azido-modified sialic acid was transferred to the natural sialic acid on sialoglycoRNA, enabling the detection of native sialoglycoRNA across diverse biological samples with high specificity and sensitivity. Using StCEL, we found that sialoglycoRNA was significantly upregulated in multiple cancer types. StCEL combined with a microplate reader was applied to detect sialoglycoRNA in large-scale samples, revealing that elevated sialoglycoRNA levels correlate positively with tumor malignancy and poor patient prognosis. Furthermore, StCEL-based sialoglycoRNA enrichment and sequencing identified dysregulated sialoglycoRNAs in tumor tissues. Collectively, StCEL establishes a multifunctional platform that enables sensitive and specific detection of sialoglycoRNA, alongside sequencing analysis, demonstrating significant potential for clinical translation.

molecular biology↗