Biology subjects

Zhou, Y.

Publications and source records attributed to Zhou, Y..

At least 181 records · Page 10Linked to original sources

bioRxiv2025

Normative modeling of brain morphology reveals neuroanatomical heterogeneity and biological subtypes in major depressive disorder

BACKGROUNDMajor Depressive Disorder (MDD) is characterized by high neurobiological heterogeneity, which hinders precise diagnosis and treatment. Traditional group-level neuroimaging analyses fail to capture individual differences, while normative modeling offer a promising approach to quantify individual deviations from healthy brain structure patterns, facilitating the identification of biological subtypes and offering a data-driven framework to dissect this heterogeneity. METHODSUsing 1,190 healthy controls, we constructed normative developmental trajectories of gray matter volume (GMV) across 246 Brainnetome-defined regions using Bayesian linear regression. Deviation maps were derived for 398 MDD patients. k-means clustering was employed to identify GMV-based biotypes. Then, the clinical characteristics and anatomical differences among these subtypes were explored, along with the post-treatment clinical features and treatment responses of participants who completed the 8-week antidepressant treatment within each subtype. RESULTSPatients with MDD exhibited widespread yet individually variable GMV deviations. Clustering analysis revealed two subtypes: Subtype 1 displayed predominantly negative deviations in sensorimotor and occipital cortices, whereas Subtype 2 showed widespread positive deviations in temporal and posterior cingulate regions. Subtype 1 had higher extraversion and symptom-linked deviation patterns; in Subtype 2, deviation burden correlated with generalized anxiety. Longitudinally, Subtype 1s GMV deviation changes predicted symptom improvement, while Subtype 2s deviations correlated with baseline severity. CONCLUSIONSNormative modeling of GMV reveals marked neuroanatomical heterogeneity in MDD and identifies subtypes with distinct clinical and treatment-related characteristics, laying a foundation for precision psychiatry and individualized interventions.

neuroscience↗

bioRxiv2025

De Novo Computational Design of VHH Nanobodies Against LGR5

VHH discovery traditionally relies on animal immunization or large-scale library screening, methods that are slow, costly, and often ineffective for challenging targets such as GPCRs. We present a fully de novo computational pipeline for epitope-directed VHH design, integrating generative backbone modeling, deep learning-based sequence optimization, and iterative experimental feedback. Using LGR5 as a model, we progressed from in silico design to functional binders without structural templates. Across three design-test-learn cycles, millions of candidates were reduced to epitope-specific binders with nanomolar affinity and high thermal stability (melting temperature [Tm] > 65 {degrees}C). Cryogenic electron microscopy (cryo-EM) confirmed atomic-level agreement (RMSD {approx} 2.2 [A]). This structure-validated approach accelerates timelines, reduces cost, and is broadly applicable to GPCRs and other membrane proteins, enabling "on-demand" therapeutic antibody generation.

bioengineering↗

bioRxiv2025

Molecular basis of high-torque transmission of the Vibrio polar flagellar motor

The bacterial flagellar motors are huge protein nanomachines that drive rotation of the flagellum for bacterial motility, and have considerable diversity in structure among bacterial species, which enables the transmission of different torques to the flagellar filaments to propel bacteria and renders various swimming abilities. Relative to the bacterial peritrichous flagellar motors, the polar flagellar motors are the faster rotational machines and transmit high torque to drive bacterial high-speed motility in liquid and empower swimming in viscous environments. However, the structural basis of high-torque transmission of the polar flagellar motors is still unclear. Here we present an atomic-resolution cryo-electron microscope structure of the polar flagellar motor in complex with the hook from Vibrio alginolyticus, comprising 295 subunits from 18 proteins. Extensive inter-subunit interactions and additional phospholipids generate the higher rigidity of the rod. The LP ring utilizes more electrostatic charges on the inner surface and less physical contacts to facility the higher-speed rotation of the rod. The additional HT ring tightly binds to the outer surface of the LP ring to enhance the LP-ring stability. A previously function-unknown component FlrP enhances the interactions of 15 FliF peptides of the MS ring with the rod and stabilizes the LPHT and MS rings. The hook has two different states, L- and R-state, which provides structural flexibility of the hook to drive the unique forward-reverse-flick motility of the bacteria in the flicking process. This study provides unprecedented molecular insights into evolution and structural adaptions of the bacterial polar flagellar motors for high-torque transmission.

microbiology↗

bioRxiv2025

Beyond Correlation: An Ultra-Large Physics-Driven Vascularized Tumor Model to Bridge Feature Formation with Underlying Biology

Radiomics provides an appealing, non-invasive approach to probing tumor biology for potential diagnostic and prognostic applications. However, its clinical adoption is limited by challenges in interpretability, which in turn compromise its robustness. To uncover the underlying causation, we developed an ultra-large-scale (ULS) computational model that simulates heterogeneous, vascularized tumor growth under physical constraints to a scale that can be visualized in medical images. Our study revealed the pivotal role of tumor proliferation rate in driving necrosis and tissue heterogeneity and the dominant impact of oxygen consumption rate on vascularization level. Analysis of the resultant tumor Radiomics shows a causal relationship between tumor biophysical parameters and imaging features. Specifically, differences in proliferation and oxygen consumption rates result in distinct changes in radiomic image features, identifying suitable imaging modalities and quantitative imaging metrics for studying these biophysical parameters. This work thus reverse-engineers the building blocks of Radiomics as a means to understand their respective biological underpinnings.

bioinformatics↗

bioRxiv2025

Overexpression of TPM4 promotes cancer progression through EMT in anaplastic thyroid cancer

Anaplastic thyroid cancer (ATC) is an undifferentiated tumour originating from thyroid follicular epithelium and represents the most malignant subtype of thyroid cancer. However, the mechanisms underlying ATC development are not fully understood. This study aimed to investigate the mechanisms driving ATC invasion and metastasis to provide novel insights into its aggressive behavior. Through an integrated bioinformatics analysis of the GEO database, we identified Tropomyosin 4 (TPM4) as a differentially expressed gene in ATC. Bioinformatic correlation and pathway enrichment analyses suggested that TPM4 expression is potentially linked to tumor cell invasion and lymph node metastasis. We showed that TPM4 was highly expressed in both ATC tissues and cell lines, and its expression levels were positively correlated with enhanced cell migration and invasion. Mechanistic studies indicated that TPM4 likely enhances tumour cell migration and invasion by facilitating cytoskeletal remodeling and promoting the epithelial-mesenchymal transition (EMT). Our findings suggest that TPM4 represents a promising diagnostic and therapeutic biomarker for ATC.

cancer biology↗

bioRxiv2025

Creating an energy efficient central metabolism for boosting biosynthesis without compromising cell growth of yeast

Long-term natural evolution selects glycolysis as the major metabolic mode for rapid cell growth, which however lacks sufficient NADPH supply to dive the biosynthesis of reduced chemicals such as free fatty acids (FFAs). Engineering energy economical pathway for chemical overproduction always compromises cellular fitness due to the rigidity of cellular metabolism. Here, we successfully replaced glycolysis metabolism with an optimized pentose phosphate pathway (PPP) in an industrial yeast Ogataea polymorpha, for the first time, which enabled a higher energy generation efficiency than glycolysis and a balanced supply of ATP and NADPH. More importantly, we discovered a global carbon metabolism regulator CMR that drives metabolic flux toward glycolysis for energy generation, and its disruption relieved the tight regulation of metabolic flux distribution and significantly enhanced the efficiency of cellular energy generation, which significantly boosted the FFA production by 63% in a FFA overproducing chassis. The final engineered yeast produced FFAs at a titer of 41.7 g/L, the highest titer reported by microbial fermentation. Our work provides valuable insights into the metabolic regulation mechanisms and a feasible approach for constructing energy efficient metabolism for chemical overproduction.

synthetic biology↗

bioRxiv2025

Methanobacterium nebraskense sp. nov., a hydrogenotrophic methanogen isolated from saline wetland soil

A hydrogenotrophic methanogen, designated strain ACI-7T, was isolated from an alkaline, saline wetland located in eastern Nebraska, USA. Cells were identified as non-motile rods (0.9-4.2 m in length and 0.2-0.4 {micro}m in diameter) that occurred singly, in chains, and as long filaments and twisted aggregates. Strain ACI-7T utilized H2 + CO2 or formate as methanogenic substrates and required growth factors present in yeast extract for continuous cultivation. The strain grew at 20-45{degrees}C (optimum, 40{degrees}C), at pH 6.5-8.5 (optimum, pH 7.3) and with 0-2.5% NaCl (optimum, 0-1%). The genomic G+C content of ACI-7T was 31.79 mol%. Phylogenetic analysis of the 16S rRNA gene sequence indicated strain ACI-7T was affiliated with the genus Methanobacterium, most closely related to Methanobacterium oryzae FPiT (97.1% sequence similarity) and Methanobacterium veterum MK4T (96.9% sequence similarity). Overall genome relatedness indices for strain ACI-7T compared to other Methanobacterium species ranged from 68.45-78.17% for average nucleotide identity and 18.9-25.7% for digital DNA-DNA hybridization. Morphological, physiological, and genomic characteristics indicate that strain ACI-7T represents a novel species, for which the name Methanobacterium nebraskense sp. nov. is proposed. The type strain is ACI-7T (=DSM 118696T=ATCC TSD-487T).

microbiology↗

bioRxiv2025

The 9p21.3 Coronary Artery Disease Risk Locus Modulates Vascular Cell-State Transitions via Enhancer-Driven Regulation of MTAP

The 9p21.3 locus is the strongest genetic association with coronary artery disease (CAD), yet its causal mechanisms remain unresolved. We map the regulatory architecture of 9p21.3 in disease-relevant vascular cells, identifying 12 enhancers within the CAD risk haplotype that respond dynamically to inflammatory and metabolic stress in fibroblasts and smooth muscle cells. These activated states are enriched for CAD heritability, implicating stress-responsive vascular wall cells in disease pathophysiology. Dense CRISPRi tiling integrated with fine-mapping and genomic constraint across >500,000 individuals nominates MTAP as the effector gene, with rs1537371 as a likely causal variant. Perturbation and multi-modal analyses show that MTAP loss induces pro-fibrotic and angiogenic programs and sensitizes vascular cells to TGF-{beta}-driven pathological transitions. Our findings reveal a vascular-specific enhancer network through which noncoding variation at 9p21.3 modulates CAD risk via MTAP--a previously unrecognized regulator of vascular remodeling located 269 kb from the risk haplotype. HighlightsO_LI9p21.3 CAD risk locus harbors 12 functional enhancers active in vascular wall cell types C_LIO_LICAD heritability is enriched in stressed vascular fibroblasts and smooth muscle cells C_LIO_LIHigh-resolution CRISPRi-MAC-seq maps 9p21.3 enhancer-gene and SNP-gene interactions C_LIO_LIMTAP identified as a causal effector gene regulated by 9p21.3 fine-mapped and constrained variants C_LIO_LIMTAP modulates TGF-{beta}-driven pathological vascular cell transitions C_LI

genomics↗

bioRxiv2025

Probabilistic working memory representations in human cortex guide behavior

Models of working memory make fundamentally different commitments to the architecture of individual memories. Information-sparse models conceptualize individual memories single point estimates agnostic to meta-cognitive variables such a uncertainty. In contrast, information-rich models propose memories re encoded s probability distributions over feature space that embed memory uncertainty in the shape of the distribution To distinguish these accounts, constructed probability distributions of memory from participants iterative reports of motion direction each trial. Remarkably, the idiosyncratic shape of these distributions (e.g., asymmetry) single trials matched the shape of neural probability distributions decoded from fMRI patterns measured from occipital and parietal cortex. Consistent with information-rich models, the neural representation of n individual memory encodes mor than the memorized feature; its variance (i.e., width and asymmetry) encodes idiosyncrasies whose read-out predicts memory behavior.

neuroscience↗

bioRxiv2025

SCAPE: An AI-Driven Platform for Comprehensive Single-Cell Data Analysis

Single-cell RNA sequencing (scRNA-seq) has transformed the study of cellular heterogeneity, but downstream analysis remains fragmented and technically demanding. Current pipelines often lack analytical diversity, require programming expertise, and offer limited integration of advanced methods. To address these challenges, we developed SCAPE, an AI-driven automated and interactive platform that unifies multi-omics, multi-resource, and multi-modal single-cell data analysis. SCAPE provides platform-independent installation, customizable workflows, and integration of R- and Python-based tools. Beyond Seurat and Scanpy, it incorporates modules for transcription factor and pathway inference, pseudotime trajectory reconstruction, spatial transcriptomics deconvolution, and cell-cell communication analysis. To demonstrate SCAPE, we curated a unified atlas of lung cancer progression in human patients and mouse models, spanning primary tumors and metastatic sites. The platform enabled harmonized integration, regulatory program inference, and spatial mapping, revealing conserved epithelial programs that promote metastatic seeding and organ-specific adaptations driven by microenvironments. Collectively, SCAPE offers an accessible and comprehensive framework for single-cell analysis, providing new insights into cancer progression and broad utility across biological systems.

cancer biology↗

bioRxiv2025

Structural basis for constitutive activation of oncogenic gp130 mutants in human inflammatory hepatocellular adenomas

Inflammatory hepatocellular adenomas (IHCAs) are benign liver tumors primarily driven by somatic mutations in the gp130 receptor, resulting in its constitutive activation. To uncover the structural mechanisms underlying this activation, we employed cryo-electron microscopy and mutagenesis to study five representative IHCAs-associated gp130 mutants and two engineered mutants with ligand-independent activity. Most mutants formed "X"-shaped dimers through a 3D domain-swapping mechanism, characterized by large juxtamembrane separations and reliant on D1 domain-mediated "tip-to-tip" interactions for dimer clustering and activation. A rare mutant displayed a distinct "Y"-shaped dimer conformation, with closely aligned juxtamembrane domains enabling direct activation independent of dimer clustering. These findings highlight the diversity of gp130 mutant activation mechanisms and provide a foundation for developing therapeutic strategies targeting aberrant gp130 signaling in IHCAs.

biochemistry↗

bioRxiv2025

When Animals Turn Inside Out: The Eversion of Bloodworms

Bloodworms, Glycera dibranchiata, possess an eversible proboscis that normally remains concealed within their bodies but explosively everts if the worm attacks or burrows. How does the bloodworm evert quickly and reliably? In a series of experiments, we characterize bloodworm kinematics, pressure, and material properties to estimate the criteria for eversion safely without rupture of the proboscis. We predict the proboscis can withstand pressures 50 times higher and bending strains up to three times higher than the respective values observed. We also present a dimensional analysis of eversion, finding that everting animals, from frogs to snails to sharks, do not satisfy Froudes law for equivalence of velocities. Our findings may help inspire the development of pressure-driven soft robots with efficient retraction capabilities.

biophysics↗

bioRxiv2025

StrainOptimizer empowers rational cell factory design through multi-scale metabolic models with expression and proteome constraints

The rational design of microbial cell factories for high bioproduction remains a key challenge in metabolic engineering. While advanced modelling frameworks incorporating protein resource allocation, such as enzyme-constrained models (ecGEMs) and Expression and Thermodynamic Flux (ETFL), provide superior predictive power, their application is limited by a lack of user-friendly computational tools. Here, we present strainOptimizer, a comprehensive computational platform for rational strain design that systematically evaluates key resource allocation principles: the coupling of gene expression with metabolism, subcellular compartmentalization, and enzyme capacity limitations. Our benchmark analyses demonstrate that each principle offers distinct advantages: models coupling metabolism and expression (like ETFL) enable the identification of non-metabolic targets, organelle-level proteomic constraints improve precision for high-protein-cost products, and protein-usage-based objectives consistently outperformed traditional flux-based approaches. To demonstrate its practical utility, we applied strainOptimizer to an engineered sclareol-overproducing Saccharomyces cerevisiae strain. The platform identified novel targets, and experimental validation confirmed a 67% success rate, increasing the final sclareol titer by 14-26% and productivity by up to 45%. StrainOptimizer bridges the gap between resource allocation theory and applied engineering, providing a powerful, validated tool to accelerate the development of high-performance cell factories.

bioengineering↗

bioRxiv2025

Two routes to land: Genomic underpinnings of parallel aerial egg deposition in aquatic Old-World Pila and New-World Pomacea (Ampullariidae)

The parallel evolution of aerial oviposition in Old-World Pila and New-World Pomacea apple snails--diverged since the Gondwanan breakup yet convergently transitioning from aquatic to terrestrial egg deposition--offers a powerful model for probing genomic adaptations underpinning key evolutionary innovations. We generated chromosomal-level genomes of Pila celebensis and Pila pesmei, revealing a genus-specific doubling in genome size driven by transposable element expansions. Parallel chromosomal rearrangements linked to environmental sensing, stress responses, and metabolism were identified in both lineages. Gene family analyses uncovered parallel expansions in cellulases, immune genes, and environmental sensors, alongside convergent positive selection in aquaporins critical for aerial osmoregulation. Strikingly, proteomics of egg perivitelline fluid (PVF) highlighted parallel adaptations in the PV1 protein family, where increased hydrophobicity enhances desiccation resistance in aerially deposited eggs. Phylogenetic and structural evidence traced PV1s likely origin to horizontal gene transfer (HGT) from a virus in the Ampullariidae ancestor, with subsequent duplications enabling lineage-specific aerial adaptations. Despite distinct genomic trajectories, Pila and Pomacea demonstrate that parallel molecular evolution and HGT-driven innovation facilitated their convergent transition to terrestrial reproduction, providing unprecedented insights into the genomic architecture of adaptive convergence.

evolutionary biology↗

bioRxiv2025

A single-component optogenetic toolkit for programmable control of microtubule

Microtubules (MTs) form dynamic cytoskeletal scaffolds essential for intracellular transport, organelle positioning, and spatial organization of signaling. Their architecture and function are continuously remodeled through the concerted actions of microtubule-associated proteins (MAPs), post-translational modifications (PTMs), and molecular motors. To precisely interrogate these processes in living systems, we developed a genetically encoded optogenetic toolkit for spatiotemporal control of MT organization and dynamics. By replacing native multimerization motifs with a blue light-responsive oligoermization domain, we have engineered single-component probes, OptoMT and OptoTIP, that reversibly label MT polymers or track plus-ends with tunable kinetics from seconds to minutes. When coupled to enzymatic effectors, these modules enable localized tubulin acetylation or detyrosination, directly linking PTMs to MT stability. We further engineered OptoMotor, a light-activatable kinesin platform that reconstitutes tail-dependent cargo transport along MTs, and OptoSAW, a light-triggered severing actuator for controlled MT disassembly. Using these tools, we reveal how local MT integrity governs lysosomal trafficking and ER-associated signaling dynamics. Collectively, this versatile single-component toolkit bridges molecular design with cytoskeletal function, offering new avenues to illuminate how dynamic cytoskeletal architectures coordinate intracellular organization, transport, and signaling.

cell biology↗

bioRxiv2025

Clair-Mosaic: A deep-learning method for long-read mosaic small variant calling

Mosaic variants, defined as postzygotic mutations occurring during an organisms development from zygote to adult, play critical roles in developmental biology, aging, and diseases such as cancer and neurological disorders. However, their accurate detection remains challenging due to low abundance in the genome and low variant allelic fractions (VAF). While current mosaic variant callers are primarily designed for short-read sequencing, no method is available for long-read sequencing, which can generate tens of kilobase-long reads to cover complex genomic regions inaccessible to short reads. To fill the gap, we present Clair-Mosaic, a deep-learning-based method for detecting mosaic small variants from long-read data. Clair-Mosaic was trained on hundreds of millions synthetic variants encompassing diverse read coverages and allelic fractions, enabling it to detect low-VAF mosaic variants with high sensitivity in paired-sample and single-sample modes. In addition to neural network prediction, Clair-Mosaic distinguishes genuine mosaic variants from sequencing artifacts by leveraging their inherent haplotype relationship in phased long reads. Furthermore, a Bayesian mosaic-germline discriminator is introduced to distinguish mosaic variants from germline variants. It also employs multiple post-calling filters, including a mosaic variant database and multiple germline population resources, to tag common germline and mosaic variants. Comprehensive benchmarking on synthetic datasets and real samples demonstrated Clair-Mosaics outstanding performance in ONT and PacBio. Clair-Mosaic is also applicable to short-read data and outperforms methods like MosaicHunter, MosaicForecast, DeepMosaic, and DeepSomatic. Clair-Mosaic is open-source and available at https://github.com/HKU-BAL/Clair-Mosaic.

bioinformatics↗

bioRxiv2025

Modified self-amplifying RNAs mediate robust and prolonged gene expression in the mammalian brain

Facile, non-genomic integrating gene delivery technologies are lacking for rapid onset and prolonged protein expression in the brain. Here we report the protein expression and cell type tropism for an advanced messenger ribonucleic acid (mRNA) technology, modified 5-hydroxymethylcytidine (hm5C) self-amplifying ribonucleic acid (saRNA), when injected into the mouse brain or applied to ex vivo human cortical brain slices. saRNA, encoding fluorescent proteins, encapsulated in an LNP formulation comprising ALC-0315 (present in Comirnaty(R)) efficiently mediates long-lasting protein expression in mouse brain cells beyond five weeks, with detectable expression in some neurons at three months. hm5C saRNA substantially outperforms N1m{Psi} mRNA. In addition to transfecting astrocytes and neurons at the injection site, hm5C saRNA-LNPs label neurons retrogradely. Excitingly, hm5C saRNA-LNPs afford protein expression in human cortical brain slices, with expression emerging within 24 hours and lasting beyond 76 days. Modified saRNA provides new opportunities for mechanistic neuroscience research and therapeutic development.

neuroscience↗

bioRxiv2025

Microbial metabolism of mannitol as a tracer for the non-invasive measurement of oral-cecal transit

The timing of digestion after a meal reveals information essential for evaluating gastrointestinal function and overall digestive health. Alterations in transit time through the GI tract can reveal abnormalities such as delayed gastric emptying and provide critical insights into nutrient absorption dynamics. This information is particularly valuable for optimizing dietary interventions, managing metabolic conditions such as diabetes, and improving personalized nutrition strategies. Methods for measuring the oral to cecal transit time (OCTT) in murine models have significant limitations. We demonstrate a non-invasive approach in freely-moving non-anesthetized mice which quantifies the microbial digestion of the non-nutritive sweetener mannitol to CO2. We monitor cage air for the production of 13CO2 from 13C-enriched mannitol using Off-Axis Integrated Cavity Output Spectroscopy integrated with multiplexes indirect calorimetry. With this approach, we find mannitol oxidation is absent in mice following commensal depletion of the microbiota. In mice with conventional microbiota, the peak 13C-mannitol oxidation occurs proximal to the mouse cecum, allowing the quantitation of OCTT in mice. By tracking the output of 13CO2, this method provides highly granular, real-time data. We detect delayed OCTT with the use of pharmacological transit-altering compounds loperamide, a gut restricted opioid receptor agonist and also semaglutide, a GLP-1 receptor agonist. This approach may provide more physiologically relevant results in a range of genetic, environmental, and pharmacological research models.

physiology↗