Biology subjects

Zhang, M.

Publications and source records attributed to Zhang, M..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

USP20 Stabilizes FABP5 to Drive Macrophage Foam Cell Formation and Atherosclerosis

Background: Macrophage foam cell formation is a central event in atherosclerosis. Although protein ubiquitination is increasingly recognized as a regulator of macrophage lipid handling, whether deubiquitinating enzymes directly control lipid uptake and metabolic remodeling during atherogenesis remains unclear. Methods and Results: Here, transcriptomic profiling identified ubiquitin-specific protease 20 (USP20) as a previously unrecognized regulator of macrophage foam cell formation. Genetic and pharmacological studies demonstrated that USP20 promoted macrophage lipid accumulation and foam cell formation, whereas macrophage-specific Usp20 deficiency markedly attenuated atherosclerotic lesion formation, lipid deposition, and macrophage accumulation in mice. To elucidate the underlying mechanism, integrative analysis of USP20-interacting proteins and proteomic alterations in Usp20-deficient macrophages identified fatty acid-binding protein 5 (FABP5) as a substrate of USP20. Mechanistically, USP20 interacted with FABP5 and stabilized its protein abundance by preventing ubiquitin-dependent proteasomal degradation. Consequently, USP20-mediated stabilization of FABP5 enhanced PPAR{gamma} occupancy at the Cd36 promoter, thereby increasing Cd36 transcription, ox-LDL uptake, and foam cell formation. Accordingly, Fabp5 knockdown abolished USP20-induced CD36 expression, ox-LDL uptake, and foam cell formation, whereas pharmacological activation of PPAR{gamma} restored CD36 expression in Fabp5-deficient macrophages. Finally, macrophage-targeted delivery of the USP20 inhibitor GSK2643943A markedly reduced atherosclerotic burden without evident systemic toxicity, supporting the therapeutic potential of targeting USP20 in atherosclerosis. Conclusions: USP20 promotes macrophage foam cell formation by stabilizing FABP5 and enhancing PPAR{gamma}-dependent Cd36 transcription. Targeting the USP20-FABP5-PPAR{gamma}-CD36 axis may represent a therapeutic strategy to limit macrophage lipid accumulation, metabolic dysfunction, and atherosclerosis progression.

cell biology↗

bioRxiv2026

An atlas of eukaryotic centromere architecture reveals recurrent evolutionary dynamics

Centromeres evolved at the root of eukaryotes to segregate chromosomes during cell division. Despite their ancient origin, centromeric DNA sequences evolve rapidly and adopt diverse architectures, including point centromeres, satellite arrays, transposon clusters, and holocentrics. To analyse centromere evolution at a broad scale, we characterised architectures across 325 diverse Darwin Tree of Life genome assemblies. Centromere architecture is evolutionarily labile, and similar configurations arise independently across divergent lineages. In plants and animals, we modelled centromere evolution as a recurrent cycle, in which satellite- and transposon-based architectures interconvert, with independent origins of holocentricity. We curated >23 million satellite repeats comprising 263 families from 165 species. Despite sequence divergence between satellite families, higher order repeats are prevalent, indicating constraint on repeat architecture rather than primary sequence. Satellite arrays are heavily invaded by diverse transposon families, consistent with convergent adaptation to the centromeric niche. In 89 species, transposons themselves constitute the primary centromere structure. We observed centrophilic transposons forming tandem arrays, suggesting mechanisms for satellite regeneration. Our sample includes five independent origins of holocentricity in plants and animals, which vary in association with periodic satellite arrays. We propose that genetic instability, centrophilic transposition, and transmission distortion promote recurrent centromere architectural interconversions during evolution.

genomics↗

bioRxiv2026

The HBV basal core promoter mutation confers a replicative advantage and transcriptionally reprograms hepatocytes toward HCC subtypes

Background: Hepatitis B virus (HBV) basal core promoter (BCP) and precore (PC) mutations occur during chronic HBV infection with the BCP-mutant being associated with increased hepatocellular carcinoma (HCC) risk. Objectives: The effects of these mutants on viral replication, hepatocyte biology, and carcinogenesis remain poorly defined. To address this, we characterized BCP- and PC-mutants using human hepatocyte chimeric mice and asked whether the resulting infection-induced transcriptomes correspond to subsets of human HBV-related hepatocellular carcinomas (HBV-HCCs). Design: Isogenic wild-type (WT), BCP- and PC-mutants of HBV genotypes A, C, and D (HBV-A, -C, -D) were generated from recombinant covalently-closed circular DNA to infect chimeric mice. HBV-HCC transcriptomic datasets from The Cancer Genome Atlas (TCGA) were used to stratify association of HBV variants with HCC subtypes. Results: WT, BCP-mutant, and PC-mutant HBV sequences remained genetically stable. The BCP mutation, but not the PC mutation, accelerated the rise in serum viremia in HBV-D- and HBV-A-infected chimeras; in HBV-C, acceleration required both (PC+BCP) mutations. Further comparisons of HBV-D variants revealed that the BCP-mutant increased intrahepatic viral DNA, viral protein expression, and upregulated cancer-related pathways, including transcripts associated with a subset of HBV-HCCs. Analysis of HBV-HCC samples from the TCGA revealed that tumors often harbor a mixture of WT and mutant transcripts, and that WT- and BCP-mutant-associated HCCs exhibit distinct transcriptional profiles. Conclusions: The HBV BCP-mutant directly perturbs hepatocyte homeostasis via virus-intrinsic mechanisms, selectively activating cancer-related pathways and defining a molecularly distinct subset of HBV-HCC. These findings suggest that HBV variants form distinct subcategories of HBV-HCCs.

molecular biology↗

bioRxiv2026

CA1 reinstatement and novelty response independently support recognition memory

One of the central tensions in memory research is whether consistency or differentiation across events is beneficial for remembering. While theoretical models posit that the hippocampal subfield CA1 subserves both types of computations, it remains unclear how it can simultaneously express both in service of recognition memory. Here, we contrasted the two prominent functions of CA1: reinstatement (consistency) and novelty processing (differentiation) to address this gap. To this end, we analysed the Natural Scenes Dataset featuring eight participants who completed a continuous recognition memory task spanning 41 separate days with 213,000 trials in total. We calculated reinstatement and novelty indices for each image and then examined the degree to which these reflected successful memory encoding. We found that CA1 showed evidence for encoding-related reinstatement as well as for novelty processing even after controlling for each other. Reinstatement was specific to retrieving the initial representation during the first retrieval attempt and did not extend to other forms of reinstatement. Exploratory analyses additionally identified reinstatement in CA3, which exhibited different response profiles compared to CA1. Our work thus highlights that computations of consistency as well as differentiation can be orthogonal signals contributing independently to memory success and can simultaneously co-exist within the same region of the hippocampus.

neuroscience↗

bioRxiv2026

Seasonal influenza vaccine strain selection by quantifying viral fitness

The long-standing challenge of seasonal influenza vaccines providing poor protection is attributed to the rapid and continuous evolution of the virus. In theory, the recommendation of vaccine strain is to predict the dominant strain with best fitness in the upcoming season. Here, we develop FutureFlu, a biologically-grounded framework that quantifies the fitness score of influenza variants in upcoming seasons, by integrating metrics on three levels: molecular genetic divergence, individual immune escape, and population-scale transmission dynamics. The fitness scores of influenza variants present strong positive correlation with their actual observed frequencies in the next seasons. Validation across 24 seasons of three influenza subtypes shows FutureFlu recommends antigenically matched vaccine strains more frequently than annual recommendations, particularly for challenging subtypes: 83.3% versus 45.8% seasons for A/H3N2, and 75.0% versus 33.3% seasons for B/Victoria. Furthermore, FutureFlu significantly outperforms the currently used methods in vaccine strain selection whether or not there is available antigenic data from hemagglutination inhibition (HI) assay, which provides a valuable supplement for WHO vaccine recommendation. To support global public health implementation, an open online platform (futureflu.com.cn) has been established to offer real-time viral fitness predictions and vaccine recommendations.

evolutionary biology↗

bioRxiv2026

Multimodal profiling establishes ovarian fibrosis as a measurable and targetable hallmark of human reproductive aging

ABSTRACT Ovarian aging underpins infertility, systemic morbidity, and mortality in women. Stromal fibrosis is implicated in ovarian aging but has not been defined in the human ovary in situ. We integrated shear wave elastography (SWE), extracellular matrix (ECM) neoepitope fingerprinting, and singlecell RNA sequencing of follicular fluid aspirates within the same individual to comprehensively profile ovarian fibrosis. In an age-stratified cohort (<33 and >37 years; N=32), age predicted ovarian stiffness, while mean stiffness was independently associated with reduced oocyte yield and follicular efficiency. ECM profiling revealed a dynamic fibrotic index favoring formation over degradation products. Single-cell transcriptomics demonstrated an age-associated fibroinflammatory stromal program enriched in pro-fibrotic pathways with stromal-immune crosstalk. In a larger validation cohort (25-45 years; N=100), age was similarly associated with ovarian stiffness. Thus, ovarian fibrosis is a quantifiable hallmark of human reproductive aging and represents a robust potential non-invasive biomarker and target for therapeutic intervention.

cell biology↗

bioRxiv2026

PromptBio: An Agentic Platform for End-to-End Computational Biomedical Research

Modern biomedical research increasingly depends on complex computational analyses, yet translating a scientific question into a reliable workflow still requires substantial technical expertise and manual coordination. PromptBio is a multi-agent AI platform available through a web portal at https://promptbio.ai that addresses this challenge. Through natural-language interaction, its agent harness, PromptGenie, translates a research objective into an inspectable plan, executes the required research and analysis, and adapts subsequent steps as evidence and results emerge. PromptBio integrates reasoning with managed execution while preserving human oversight and a traceable record of the research process. It can apply validated methods, construct custom analyses, and incorporate external workflows, enabling researchers to move beyond fixed pipelines while supporting reproducibility. We evaluate the platform through benchmarks of end-to-end bioinformatics analysis and biomedical deep research, validation of representative omics and machine-learning skills, and a hypothesis-driven regulatory-genomics case study. PromptGenie achieved higher analytical accuracy and stronger evidence retrieval and synthesis than the comparison agents, while the evaluated domain skills produced results consistent with established methods. The case study further demonstrates how PromptBio can integrate human-specific genomic and epigenomic features to investigate cortical development. Together, these findings show that PromptBio can coordinate complex biomedical analyses under researcher oversight, offering an accessible approach for accelerating scientific iteration and transforming research questions into transparent, reusable computational workflows.

bioinformatics↗

bioRxiv2026

Neural signatures of spontaneous transitions between internal and external thought

The human mind constantly shifts between internal representations and the external environment, yet the neural mechanisms underlying such spontaneous transitions remain underexplored. Here, we analyzed a think-aloud functional magnetic resonance imaging dataset, in which participants continuously verbalized their thoughts, to identify neural activity predicting transitions between internally and externally oriented thought. Internal-to-external transitions were preceded by increased activation in the salience/ventral attention network, with the strongest effect observed in the right temporoparietal junction. The spatial pattern of this pre-transition activation was positively associated with acetylcholine receptor density, suggesting a role for cholinergic signaling in cognitive reorientation. Pre-transition activation was itself preceded by a large-scale brain state proposed to serve as a flexible hub between functionally specialized states, indicating that spontaneous transitions are more likely when the brain occupies this intermediate configuration. Together, these findings suggest that multilevel neural mechanisms support flexible reorientation along the internal-external dimension of spontaneous cognition.

neuroscience↗

bioRxiv2026

Active control modulates memory-related activity during encoding and encoding-retrieval similarity

Self-directed learning allows learners to actively control their learning experience and has been shown to enhance memory compared with matched yoked learning. However, it remains unclear when and how active control modulates memory-related neural activity during learning and retrieval. We recorded electroencephalography (EEG) while participants encoded objects under active and yoked learning conditions and again during a delayed recognition test approximately 24 h later. We examined event-related potential (ERP) activity across earlier processing windows, including pre-stimulus slow potentials and early N2 activity, and later processing windows, including P300, late slow-wave, and post-stimulus slow-potential activity. We also examined encoding-retrieval similarity (ERS) between neural patterns during encoding and retrieval. Behaviorally, active control improved delayed recognition, with the advantage selectively expressed in detailed recognition. In the ERP analyses, earlier processing windows showed memory-related effects, with pre-stimulus slow-potential and N2 activity differentiating subsequently remembered from forgotten items, but were not modulated by active control. By contrast, active control modulated later memory-related ERP activity, with remembered-forgotten differences expressed during late stimulus-related and immediate post-stimulus processing only in the active condition. ERS showed a similar active-control modulation: memory-related encoding-retrieval pattern similarity was evident under active learning, but not under yoked learning, with this effect involving relatively late encoding and retrieval windows. Together, these findings support a constructive-processing account, suggesting that memory formation under active control depends more strongly on rich, detailed encoding representations that can be reinstated during retrieval.

neuroscience↗

bioRxiv2026

Universally conserved isoasparylation sustains ribosome biogenesis and function

All living beings use ribosomes to synthesize proteins from -amino acids. Inherited from our common ancestor, a few universally conserved ribosome biogenesis steps, introducing essential ribosomal RNA modifications, have survived to our days. However, it was unknown whether similar primordial core mechanisms could also target ribosomal proteins. Here we show that the assembly and the function of ribosomes depend on the installation of an unusual {beta}-amino acid, isoaspartate, within the ribosomal protein uS11. In bacteria, mitochondria, and plastids, this modification is catalyzed by the metzincin-like hydrolase YbeY, whereas in archaea and eukaryotes, it is introduced by the atypical kinase Fap7. The formation of this strategically positioned isoaspartate enables correct maturation of the small ribosomal subunit to support protein synthesis and normal cell physiology.

biochemistry↗

bioRxiv2026

Kinesin-1 holoenzyme assembly coordinates cargo-adaptor recognition with heavy-chain autoinhibition

Kinesin-1 is a major microtubule-based molecular motor that transports diverse cellular cargoes, yet how assembly of its subunits is coupled to cargo recognition and motor regulation remains poorly understood. Mammalian kinesin-1 functions as a heterotetrameric holoenzyme composed of kinesin heavy chains (KIF5s) and kinesin light chains (KLCs), but the structural principles linking holoenzyme assembly to motor regulation remain unclear. Here, using KIF5C as a model system, we define the molecular mechanisms underlying kinesin-1 holoenzyme assembly and cargo-adaptor regulation. We identify a conserved coiled-coil interface between KIF5C and KLC1 that mediates their 2:2 assembly, with quantitative mutagenesis revealing key hydrophobic determinants of complex formation. We further demonstrate that the mitochondrial adaptor TRAK2 directly engages the KIF5C CC4 cargo-binding platform through a defined 2:2 interaction required for mitochondrial recruitment of KIF5C. Although KLC1 and TRAK2 bind distinct regions of KIF5C, KLC1 modulates TRAK2 association through steric and conformational effects, revealing how holoenzyme composition influences cargo-adaptor accessibility. Mechanistically, we identify a previously unrecognized intramolecular interaction between the KIF5C CC1 and CC4 domains that forms a stalk-mediated autoinhibitory latch. TRAK2 and KLC1 release this inhibitory interaction through distinct mechanisms. Together, our study establishes a molecular framework in which kinesin-1 holoenzyme assembly regulates cargo-adaptor recognition and autoinhibitory remodeling, providing mechanistic insight into how molecular motors coordinate cargo engagement with activation.

biochemistry↗

bioRxiv2026

MultiFlow: coupled flow matching for predicting single-cell multiomic perturbation responses in unseen cellular contexts

Predicting cellular responses to perturbation requires resolving coordinated changes across molecular layers, yet most single-cell perturbation models focus on transcriptional responses alone. Here we present MultiFlow, a coupled flow-matching framework that unifies generation and perturbation prediction of paired gene expression and chromatin accessibility. By learning coupled RNA-ATAC flows conditioned on perturbation and control-derived cellular-state representation, MultiFlow enables prediction of coordinated multiomic responses in unseen cellular contexts. Across multiomic generation benchmarks, MultiFlow accurately reproduced paired RNA-ATAC states and their population distributions. In multiomic perturbation benchmarks, MultiFlow achieved the strongest overall performance in predicting both gene-expression and chromatin-accessibility responses, outperforming competing modality-specific perturbation-prediction methods. Joint multiomic modeling further preserved perturbation-induced RNA-ATAC coordination, including concordant peak-gene effects and cross-modal cellular neighborhood structure. These results establish coupled flow matching as a unified generative framework for modeling paired multiomic states and predicting coordinated perturbation responses across cellular contexts. Code and tutorial for MultiFlow are available at https://github.com/liuq-lab/MultiFlow.

bioinformatics↗

bioRxiv2026

Autonomous Spatial Transcriptomics Analysis (ASTA): Demonstrating Performance Improvements through Clustering, Biological Annotation, and AI-Driven Discovery

Spatial transcriptomics keeps measurement of gene expression while preserving spatial context, yet traditional analysis methods face challenges in computational efficiency, biological interpretability, and autonomous discovery. This project presents a framework solving these issues through three parts: (1) an ensemble clustering system achieving 66.7% improvement over baseline average and 23.9% over best single method with silhouette score of 0.540 and statistical significance (p = 0.0032, Cohens d = 1.82); (2) a knowledge-based clustering framework that annotates 88.6% of cells across 8 ovarian cell types using 428 marker genes; and (3) a GPT-4o-mini-powered autonomous agent that generated 3 biological hypotheses with validations.

bioinformatics↗

bioRxiv2026

Defining the genetic landscape of acid and oxidative stress tolerance in Streptococcus mutans by pooled CRISPR interference screening

Bacterial stress tolerance is a fundamental ecological adaptation that enables survival, competitive fitness, and persistent colonization under fluctuating environmental conditions. Dental caries remains a major global health burden. As an etiologic agent in caries, Streptococcus mutans (S. mutans) has the ability to adapt to sudden and substantial acid and oxidative stress. Nevertheless, the genome-wide genetic programs that support these stress tolerances remain incompletely defined. Herein, we established a xylose-inducible, genome-wide pooled CRISPR interference (CRISPRi) platform in S. mutans and performed parallel functional screens under acidic conditions (pH 5.0) and low-dose hydrogen peroxide (H{square}O{square}) stress. Using predefined screening thresholds, we identified 422 genes whose repression reduced fitness during acid challenge and 337 genes whose repression reduced fitness during H{square}O{square} exposure. Functional and network analyses revealed that stress tolerance is strongly constrained by core physiological processes, including RNA (particularly transfer RNA) metabolism, macromolecule maintenance, and damage repair. Comparative analyses further indicated that growth-associated pathways displayed opposite trends between the two stresses, consistent with a stress-dependent allocation trade-off. These two complementary findings redefine the dual-stress adaptation paradigm of S. mutans: stress resistance is not determined merely by canonical stress signaling, but requires intact core physiological modules, and bacteria tune resource allocation dynamically to adapt to divergent stress microenvironments. Collectively, the present study provides a comparative, genome-scale functional map of acid- and oxidative-stress tolerance in a key oral pathogen and identifies genetic determinants for mechanistic studies and anti-caries interventions.

microbiology↗

bioRxiv2026

HER2 mutation-derived neoantigens in NSCLC as actionable targets for TCR therapy

HER2 mutations are oncogenic drivers in 1-6% of non-small cell lung cancers (NSCLC), but therapeutic resistance limits the durability of current HER2-targeted treatments. Here, we identify T-cell receptors (TCRs) targeting recurrent HER2 hotspot mutations as a potential immunotherapeutic strategy for HER2-mutant NSCLC. Using neoepitope prediction and antigen-specific T-cell enrichment, we isolated HLA-A*02:01restricted TCRs recognizing HER2 A775insYVMA, S310F, and G776delinsVC mutations, collectively covering approximately 60% of HER2-mutant NSCLC. These TCRs selectively recognized mutant HER2 epitopes without detectable wild-type reactivity and some displayed cross-recognition of related hotspot variants, expanding the spectrum of targetable tumors. The G776delinsVC-specific TCR also exhibited co-receptorindependent activity showcased by its ability to activate CD4+ T cells. Importantly, timelapse single-cell flow cytometry analyses demonstrated that TCR-engineered T cells repeatedly reacquired activated polyfunctional states following serial antigen stimulation, while serial tumor rechallenge assays confirmed sustained cytotoxic activity across multiple rounds of tumor killing. These findings identify recurrent HER2 mutations as shared immunotherapeutic targets and provide a foundation for the development of TCR-based therapies for HER2-mutant NSCLC.

immunology↗

bioRxiv2026

Reconstructing whole-organism cell phylogenies with resolved ancestral transcriptional states

Combining cell lineage tracing with single-cell RNA sequencing can reconstruct a phylogenetic tree to integrate single-cell transcriptomic atlas. However, the internal nodes of this tree - representing ancestral cells - remain transcriptionally silent, preventing along-lineage longitudinal tracing of cell state dynamics. Here, we overcome this by reconstructing high-resolution zygote-to-larva developmental cell phylogenies for 15 zebrafish larvae, with directly measured transcriptomes of the terminal nodes (i.e., sampled cells). Leveraging a set of lineage-committed upregulated genes (LUGs), we developed LUG-encoded ancestral projection (LEAP), a novel phylogeny-based computational framework, and successfully imputed the transcriptional states of internal nodes of the phylogenies. This enabled, for the first time in a non-nematode organism, lineage-informed longitudinal analysis of cell state dynamics throughout development. Our analysis revealed a major, previously unappreciated wave of fate specializations associated with hatching, distinct from the well-characterized events of gastrulation. Furthermore, we uncovered abundant incipient cell states that are already fate-determined but exhibit minimal transcriptional differentiation, revealing a hidden layer of developmental fate specializations. In sum, by resolving ancestral transcriptional states of a reconstructed cell phylogeny, this work paves the way for constructing lineage-resolved cell atlases in complex organisms to characterize comprehensive cell state dynamics.

developmental biology↗

bioRxiv2026

Pervasive historical introgression across oak phylogeny shapes gene expression

Oaks were once described as the "worst-case scenario" for the biological species concept because of the presumed pervasive hybridization and introgression among species. However, we still lack a full picture of genome-wide introgression across the eight sections of the Quercus phylogeny. Furthermore, we still do not have a complete characterization of what is introgressed and how it functionally influences the recipient species. Firstly, we used 168 whole genomes from 67 Quercus species belonging to the eight sections of the Quercus phylogeny and a super pan-genome to generate a phylogeny and test for ILS and introgression. Introgression was widespread: ancient introgression occurred between ancestors of the eight sections and more recent introgression took place within sections. Secondly, using genome-wide transcriptome, methylome, and chromatin accessibility data from a subset of 19 species sampled from four sections we demonstrated that introgressed genes are more highly and uniformly expressed than non-introgressed ones. This difference in expression level between introgressed and non-introgressed genes mostly results from cis-regulation, and is most likely due to DNA methylation decay in promoter ACRs. In summary, introgression has been a major evolutionary force during the whole evolutionary history of Quercus and had a significant impact on fundamental processes such as gene regulation and expression.

evolutionary biology↗

bioRxiv2026

Learning to read a second language establishes a parallel L2 representation alongside the native one in the VWFA

Learning to read a second language requires the brain to incorporate a new writing system into an already established native-language reading network, yet how this process reshapes the Visual Word Form Area (VWFA) remains poorly understood. Using fMRI with a passive viewing paradigm, we systematically investigated how VWFA responses to Chinese (L1) and English (L2) words evolved across three groups of native Mandarin-speaking children at distinct stages of L2 literacy acquisition: L2 pre-readers, L2 beginning readers, and L2 advanced readers. We combined univariate activation analyses, representational similarity analysis, and supervised machine learning classification to investigate two theoretical accounts of VWFA reorganization: the Overlay Model, which predicts stable L1 responses as L2 responses emerge, and the Competing Model, which predicts competitive reallocation of neural resources from L1 to L2. We found that although the VWFA already exhibited robust selective responses to L1 words, L2-word selectivity was absent in L2 pre-readers but emerged robustly in beginning readers, with L1-word selectivity remaining stable throughout. Representational similarity analysis further revealed that robust L2 word representations within the VWFA emerged only after children began learning to read L2, while L1 word representations remained stable across all three groups. Finally, supervised machine learning analyses successfully discriminated among the three L2 literacy groups on the basis of L2 but not L1 activation patterns, indicating that VWFA responses to L2 alone were sufficient to capture childrens stages of L2 literacy acquisition, whereas responses to L1 were insensitive to L2 learning experience, providing no support for the Competing Models prediction of competitive neural reallocation away from L1. Together, these findings support the Overlay Model, demonstrating that the VWFA incorporates a new writing system within its existing cortical resources without compromising L1 print processing.

neuroscience↗