Biology subjects

Meng, L.

Publications and source records attributed to Meng, L..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Radiosynthesis and Evaluation of Novel Cholesterol 24-Hydroxylase Positron Emission Tomography Tracers

Cholesterol 24-hydroxylase (CH24H or CYP46A1) is a pivotal enzyme in brain cholesterol metabolism and has emerged as a therapeutic and imaging target in neurodegenerative disorders. Although [18F]Cholestify ([18F]CHL-2205) has shown promise as a positron emission tomography (PET) tracer for imaging of CYP46A1, the impact of cyclopropyl moiety conformation on binding and imaging performance remains unexplored. Here, we report the rational design and preliminary evaluation of novel CYP46A1 PET tracers, in which the left-side cyclopropyl group was modified into bridged, spirocyclic, and fused bicyclic architectures to probe steric and conformational effects. All compounds 9-11 exhibited high CYP46A1 affinity (IC50 = 0.19-0.28 nM). Radiosynthesis of [18F]9-11 was achieved via copper-mediated [18F]fluorination, providing practical non-decay-corrected radiochemical yields of 10-34% with excellent radiochemical purity (>98%). In vitro autoradiography in rat brain sections demonstrated specific and regionally selective binding, comparable to that observed for [18F]CHL-2205. These cyclopropyl-derived scaffolds establish a scaffold-driven strategy for PET tracer development, providing a robust framework for further structure-activity relationship studies and the rational optimization of CYP46A1 PET tracers.

pharmacology and toxicology↗

bioRxiv2026

DeepKOALA: A Fast and Accurate Deep Learning Framework for KEGG Orthology Assignment

The KEGG Orthology (KO) system links DNA and protein sequences to biological functions and pathways, providing a curated, fundamental and consistent annotation framework across all domains of life. While accurate, traditional sequence alignment-based annotation methods are computationally expensive, which severely limits their application in large-scale datasets. To address this challenge, we introduce DeepKOALA, a deep learning approach based on Gated Recurrent Units (GRU), which frames KO annotation as an open-set recognition task. This design reduces false positives arising from out-of-scope sequences and, together with a lightweight GRU backbone, enables high-throughput annotation. The GRU-based model was benchmarked against four other deep learning architectures and showed the best balance between speed and accuracy. We further performed a cross-species evaluation of DeepKOALA in comparison with existing KO annotation tools, where it achieved an F1-score of 0.8653 and 37.5-fold acceleration compared with BlastKOALA. We also provide a specialized fragment model for handling incomplete sequences and an optional Multi-domain mode. Together, these features make DeepKOALA a scalable, efficient, and accurate solution for high-throughput function annotation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=61 SRC="FIGDIR/small/698072v1_ufig1.gif" ALT="Figure 1"> View larger version (15K): org.highwire.dtl.DTLVardef@8c3b53org.highwire.dtl.DTLVardef@8acfa8org.highwire.dtl.DTLVardef@147398borg.highwire.dtl.DTLVardef@112d762_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

Focused ultrasound programmed characteristic NIR-IIb lanthanide mechanoluminescence for high sensitivity bioimaging in vivo

Optical imaging techniques for biodetection are hindered by limited sensitivity and resolution in deep tissues, arising primarily from photon scattering and endogenous autofluorescence. Herein, we report a focused ultrasound (FUS) programmable NIR-IIb emissive mechanoluminescent nanoparticle for in vivo bioimaging. Specifically, CaZnOS nanoparticles co-doped with Mn2+ and Er3+ were engineered to exhibit mechanoluminescence (ML) emission peaked at 1550 nm. FUS stimulation elicits ML without the need for optical excitation, thereby enabling deep-tissue imaging devoid of background interference from excitation light. By modulating the excitation frequency of FUS, ML can be programmed as a characteristic signal. Integrated with a Fourier frequency-transform identification reconstruction (FFIR) algorithm, the specific ML signals can be detected with high sensitivity, reaching sub-millimeter spatial resolution and markedly enhanced signal-to-background ratios compared to conventional photoluminescence-based approaches. By macrophage internalization of the ML nanoparticles to yield functional macrophage-nanoparticle (FMNs), a ultralow detection limit of 10 cells can be achieved. In murine tumor models, the FMNs facilitated real-time monitoring of early-stage tumor progression, underscoring their biocompatibility and translational promise for high-precision diagnostics in deep-seated neoplasms.

bioengineering↗

bioRxiv2025

OPSTA: An Online Analysis Platform for Chinese Sports Science Thesis Data Based on the Shiny Framework

With the continuous expansion of postgraduate enrollment in sports science in China, problems related to research design and statistical analysis in masters theses have become increasingly prominent. Some postgraduate students have limited statistical training, which may lead to inappropriate research designs, improper selection of statistical methods, failure to check underlying assumptions, and insufficient reporting of effect sizes and confidence intervals, ultimately undermining the scientific rigor and credibility of research conclusions. To address these issues systematically, it is necessary to develop an easy-to-use data analysis tool tailored to the sports science domain and aligned with statistical reporting standards. Accordingly, this study developed the Online Platform for Sports Thesis Analysis (OPSTA). Built on the Shiny framework, OPSTA integrates statistical procedures commonly used in sports science research, including descriptive statistics, independent-samples and paired-samples t tests, one-way and multifactor analysis of variance (ANOVA), correlation analysis, regression analysis, and reliability and validity testing. Through an interactive and visualized interface, the platform guides users through data import, method selection, and result export. While lowering the barrier to statistical analysis, OPSTA emphasizes assumption checking and standardized result presentation, thereby reducing the misuse of statistical methods and improving reporting quality. The platform is available at: https://menglab.org.cn/opsta/.

bioinformatics↗

bioRxiv2025

Evolutionary Decoding of the Bacillus subtilis Secretome: Insights from Pan-Genomics and Deep Learning

Bacillus subtilis serves as a crucial host for industrial protein production, where the efficiency and regulation of its secretion system represent a central focus of applied research. Despite substantial genomic diversity among strains, current understanding of signal peptides, which are key elements in the secretion process, remains largely based on single model strains, lacking systematic investigation from a pan-genomic perspective. This study integrates pan-genomics and deep learning to construct a pan-secretome profile of 287 B. subtilis strains. Our analysis reveals an open repertoire of signal peptides in B. subtilis. Our results reveal an open pan-signal peptidome in B. subtilis. Core signal peptides exhibit high sequence conservation and primarily direct the localization of housekeeping proteins, whereas accessory signal peptides govern the extracellular secretion of environment-responsive proteins, forming a functional "housekeeping-adaptive" dichotomy. We demonstrated for the first time at a broad scale the widespread evolutionary decoupling between signal peptides and their corresponding mature peptides, uncovering a modular evolutionary mechanism in protein evolution. While the deep learning model achieved high accuracy (88.0%) in discriminating core and accessory gene-encoded full-length proteins, its performance was considerably limited when using signal peptide sequences alone (69.7% accuracy), reflecting the information constraints inherent to short sequences. This study provides a systematic portrayal of the signal peptide evolutionary landscape in B. subtilis at the pan-genome scale, advancing our understanding of the evolutionary principles governing bacterial secretion systems and establishing a theoretical foundation for optimizing industrial protein production through rational signal peptide design.

bioinformatics↗

bioRxiv2025

Two Small Proteins Enable N2O Reduction in Acidic Environments

Denitrifying bacteria are major contributors to nitrous oxide (N2O) emissions, which rise with global soil acidification, likely because low pH impairs maturation of the periplasmic enzyme N2O reductase (NosZ) in most bacteria. While some bacteria can reduce N2O under acidic conditions, the underlying mechanism remain unclear. Here, we isolated bacteria from acidic soils and identified strains that efficiently reduce N2O at low pH. They carry two novel proteins, NosP and NosQ, along with NosZ clade I. Functional analyses of deletion mutants demonstrated that NosP and NosQ are essential for the maturation of NosZ at low pH, but are not required at circumneutral pH. Cryo-EM analysis indicates that NosPQ forms a protective complex with NosZ, safeguarding its maturation under acidic conditions. Metagenomic analysis shows that nosPQ genes are widely distributed across diverse bacterial taxa and soil types. Our findings reveal a key molecular adaptation mechanism for N2O reduction in acidic environments and provide valuable insights for developing efficient N2O mitigation strategies.

biochemistry↗

bioRxiv2025

Vascular Basement Membrane Laminins Modulate Functional Zonation of Cerebral Microvessels

We investigated whether vascular basement membrane (BM) laminins influence vascular zonation by performing single-cell RNA sequencing on cerebral blood vessels from mice lacking the major vascular laminins in endothelial and smooth muscle BMs, laminin 4 (Lama4-/-) and laminin 5 (Tek-cre:Lama5-/-), and wild-type littermates. Our dataset expands existing cerebral vascular transcriptomic profiles and reveals that Lama4-/- endothelial cells exhibit increased arterial marker expression and reduced postcapillary venule identity. In vitro and in vivo studies indicate that compensatory upregulation of laminin 5 in Lama4-/-vessels enhances expression of junctional proteins (Ocln, Cldn5) and promotes vessel contractility via increased expression of contractile molecules in mural cells. Additionally, loss of Lama4 upregulates expression of large artery markers (Gja4, Dll4, Tgfb2) and results in elevated autotaxin (Enpp2) levels, a key enzyme in lysophosphatidic acid production implicated in stroke. Accordingly, Lama4-/- mice exhibit worsened stroke outcomes, driven not by immune infiltration or junctional defects, but by increased vascular permeability likely mediated by autotaxin and/or activation of resident myeloid cells. Our data suggest that laminin 4/5 ratios in vascular BMs regulate functional zonation between arterioles, capillaries and postcapillary venules by modulating metabolic pathways in endothelial and mural cells, and indirectly influencing resident myeloid cells.

cell biology↗

bioRxiv2025

Multimodal AI Decodes Extreme Environment Functional Dark Matter Beyond Homology

Functional annotation of proteins from extreme environments represents a major bottleneck for bioresource discovery, as a vast reservoir of functional dark matter defies existing homology-based methods. We demonstrate that environmental pressures impart conserved physicochemical energy signatures that co-determine protein function with sequence and structure. Here we developed ACCESS, a multimodal graph neural network employing hierarchical contrastive learning with a tailored label-sample co-embedding to fuse energy, sequence, and structural information and overcome homology scarcity. ACCESS surpasses state-of-the-art methods including BLASTp and CLEAN in annotating low-identity enzymes. Applied to extreme environmental metagenomics, we constructed a function map of extremophile enzymes to expand the biocatalyst library, pinpointed functionally critical residues to guide rational design, and enabled large-scale, function-based macro-evolutionary analyses. This paradigm transcends the limitations of homology, illuminating protein dark matter and accelerating the exploration of the biospheres functional diversity for applications in biotechnology and therapeutic development.

bioinformatics↗

bioRxiv2025

Environmental exosomes: Evidence of extracellular RNA release by aquatic organisms

Aquatic organisms continuously interact with surrounding water, yet whether they release extracellular vesicles remains unknown. We hypothesized that pearl oysters (Pinctada fucata) release exosomes/small extracellular vesicles (sEVs) into the aquatic environment. To this end, we collected exosomes/sEV-sized components by ultrafiltration from tank water and open-sea culture areas. Microscopy revealed abundant vesicles consistent with exosome/sEV size, and RNA sequencing identified oyster-specific piRNAs that matched sequences previously detected in hemolymph exosomes. These findings demonstrated that pearl oysters actively released exosomes containing species-specific nucleic acids into surrounding water. We propose referring to these vesicles as environmental exosomes/environmental sEVs (eExosomes/esEVs). This finding suggests that aquatic exosomes serve as carriers of RNA and may contribute to inter-organismal communication networks. Beyond their functional role, eExosomes/esEVs also hold promise as novel targets for environmental DNA/RNA (eDNA/eRNA) analysis, offering new opportunities for ecological monitoring and biodiversity research.

ecology↗

bioRxiv2025

Physically intelligent soft antennae enhance tactile perception by active touch

Soft robotic sensors today struggle to interpret complex tactile scenes without incurring significant computational costs. Inspired by insect antennae--compliant, distributed sensors that efficiently process tactile information through physical intelligence--we investigated whether mechanical design and active touch sensing strategies could enhance robotic tactile feature perception. We hypothesized that insect-inspired antenna dynamics, specifically flexural stiffness gradients and active touch speed, could simplify tactile classification. Using a sim-to-real framework that bridges bioinspired computational models with a multi-link soft robot antenna, we introduce the notion of tactile fields--spatiotemporal representations of tactile stimuli shaped by contact location, feature type, and active touch speed. Our analyses show that cockroach-inspired antenna mechanics jointly with active touch speeds improve feature classification accuracy compared to conventional sensors with uniform flexural stiffness gradient by increasing tactile data sparsity and dispersion. An exploration of stiffness and damping of antenna mechanics revealed design trade-offs that influence tactile discrimination and structural stability. Through sim-to-real transfer, stiffness gradients and structured active touch motions were demonstrated on a miniature distributed soft robotic antenna, validating their effectiveness in real-world robotic systems. Taken together, this work presents a biologically grounded framework for tactile sensor design that reduces computational load and enhances adaptability.

bioengineering↗

bioRxiv2025

Hollow condensates emerge from gelation-induced spinodal decomposition

Recent studies have identified diverse hollow biomolecular condensates, characterized by biomolecule-depleted interiors surrounded by biomolecule-rich shells. Although several formation mechanisms have been proposed, a general thermodynamic driving force remains elusive. Here, we investigate a well-defined system in which the human transcription factor p53 and non-specific double-stranded DNA (dsDNA) form biomolecule-rich condensates. Introduction of dsDNA containing p53-binding motifs induces a morphological transition to hollow structures, accompanied by a material state transition from liquid-like to gel-like. In vitro assays indicate that the formation of hollow condensates is driven by p21 DNA-induced localized gelation at the condensate periphery. Guided by these findings, we developed a three-component phase-field model that quantitatively recapitulates the formation of hollow condensates. Simulations show that peripheral gelation leads to gradual depletion of protein and Random DNA from the condensate core, triggering spinodal decomposition and lumen formation inside condensates. Together, these results offer mechanistic insights into multi-component hollow condensates.

biophysics↗

bioRxiv2025

Giant viruses specific to deep oceans show persistent presence and activity

Giant viruses (GVs) of the phyla Nucleocytoviricota and Mirusviricota are large double-stranded DNA viruses that infect diverse eukaryotic hosts and impact biogeochemical cycles. Their diversity and ecological roles have been well studied in the photic layer of the ocean, but less is known about their activity, population dynamics, and adaptive strategies in the aphotic layers. Here, we conducted eight seasonal time-series samplings of the surface and mesopelagic layers at a coastal site in Muroto, Japan, and integrated 18S metabarcoding, metagenomic, and metatranscriptomic data to investigate deep-sea GVs and their potential hosts. The analysis identified 48 GV genomes including six that were exclusively detected in the mesopelagic layer. Notably, these mesopelagic-specific GVs showed persistent activity across seasons. To investigate the global deep-sea-specific GV distribution, we compiled GV reference genomic data from the OceanDNA MAG project and other resources, and analyzed 1,890 marine metagenomes. This revealed 101 deep-sea-specific GVs, distributed across the GV phylogenetic tree, indicating that adaptation to deep-sea environments has occurred in multiple lineages. One clade enriched with deep-sea-specific GVs included one GV identified in our Muroto sampling, which displayed a wide geographic distribution. Seventy-six KEGG orthologs and 74 Pfam domains were specifically enriched in deep-sea-specific GVs, encompassing functions related to the ubiquitin system, energy metabolism, and nitrogen acquisition. These findings support the scenario that distinct GV lineages have adapted to hosts in aphotic marine environments by altering their gene repertoire to thrive in this unique habitat. IMPORTANCEGiant viruses are widespread in the ocean surface and are key in shaping marine ecosystems by infecting phytoplankton and other protists. However, little is known about their activity and adaptive strategies in deep-sea environments. In this study, we performed metagenomic and metatranscriptomic analyses of seawater samples collected from a coastal site in Japan and discovered giant virus genomes showing persistent transcriptional activity across seasons in the deep-sea water. Using a global marine dataset, we further uncovered the widespread existence of deep-sea-specific giant viruses and characterized their unique gene repertoire, which likely facilitates adaptation to the limited availability of light and organic compounds in the aphotic zone. These findings expand our understanding of giant virus ecology in the dark ocean.

genomics↗

bioRxiv2025

Oncogenic mutations disrupt lineage differentiation via epigenetic perturbations

Understanding lineage differentiation is an ongoing challenge in the field of stem cell research. We acquired eight gain-of-function (GOF) oncogenic mutations associated with DNA methylation alteration from the TCGA datasets. After introducing each oncogene into wild-type stem cells separately, we found that the mutant stem cells are difficult to reprogram to iPSCs and terminally differentiate to induced neuronal cells, and retain proliferation capacity in the process of differentiation. This findings suggests that oncogenic mutations impair the lineage differentiation. After analyzing the resulting DNA methylation profiles, we identified many novel lineage differentiation genes in mutant cells showing DNA methylation alteration compared with wild-type cells, which is consistent with their methylation states in low-grade gliomas (LGGs) compared with control brain. Collectively, our results indicate that oncogenic mutations in stem cells are associated with DNA methylation changes for genes related to multipotency maintenance, differentiation resistance, and tumorigenesis, therefore, displaying impairment in lineage commitment.

cell biology↗

bioRxiv2025

Exploring the double-stranded DNA viral landscape in eukaryotic genomes

Endogenous viral elements record past virus-host interactions, yet those derived from Baltimore class I double-stranded DNA viruses remain poorly explored in eukaryotes. Here, we identified 781,111 viral regions in 7,103 eukaryotic genome assemblies, revealing their broad but uneven distribution across both eukaryotic host lineages and viral taxa. Viral regions showed pronounced accumulation in several invertebrates, where they accounted for up to 16% of a single genome assembly. Taxonomic analyses of viral regions revealed 72 previously unrecognized endogenization-based associations between viral major taxa and eukaryotic lineages, including those involving invertebrates such as bivalves, starfish, sponges, flatworms, and ribbon worms, as well as diverse algae. In addition, we uncovered cases of iridoviral endogenization in ray-finned fishes. Overall, our study provides a baseline view of the landscape of the endogenous dsDNA virosphere across both eukaryotic and viral lineages.

microbiology↗

bioRxiv2025

Mechanical and morphological features of the cockroach antenna confer flexibility, reveal a kinematic chain system and predict strain information for proprioception

A broad class of animals rely on touch sensation for perception. Among insects, the American cockroach P. americana is a touch specialist that uses a pair of soft antennae with distributed sensors to touch its environment to guide decision making. During touch, forces on the antenna can activate thousands of mechanosensors. To understand the content of this sensory information, it is critical to understand how antenna mechanics shape the transmission of contact forces. Here, we investigate the mechanical behavior and morphology of the American cockroach antenna at the individual segment level through experiments, mathematical modeling, imaging with Micro-Computed Tomography (Micro-CT), 3D reconstruction of antenna morphology, and finite element modeling (FEM). Our experimental results and model predictions reveal that the antenna flagellum bends according to a kinematic chain model, with rigid segments connected by joints. Whereas the middle region of the antenna consistently fractured under cyclic bending, the tip region remained intact under large deformations, revealing mechanical specialization along the antenna. Micro-CT imaging revealed an invagination of the exocuticle at segment intersections of the tip. To test the hypothesis that this structure can enhance flexibility and robustness, we used FEM and confirmed that the invagination allows for larger bending without structural failure (buckling). Applying FEM to a morphologically accurate kinematic chain model of the flagellum revealed the relationship between the local strain at the location of marginal sensilla and intersegment angle, predicting the information available for antenna proprioception. Taken together, these findings reveal biomechanical adaptations of insect antennae and provide a critical step toward a mechanistic understanding of touch sensation in a touch specialist. SUMMARY STATEMENTBy combining experiments, imaging and modeling, we demonstrate distinct mechanical features in the cockroach antenna and provide a framework to model the neuromechanics of the antenna in an insect touch specialist.

biophysics↗

bioRxiv2025

Looking for the optimal pathway to stimulate hippocampus in human participants using transcranial ultrasound stimulation (TUS): a simulation study

At present, very limited methods can directly modulate the neural activities in deep brain structures in human participants. Low-intensity transcranial ultrasound stimulation (TUS), as an emerging and advanced modality of non-invasive brain stimulation (NIBS), has great potential for focally stimulating the subcortical structures that are related to sleep, emotion and the functions of motor of cognition. Due to the focality, the integration of various methods, including magnetic resonance imaging and possible pathways, is important to perform TUS intervention for precise targeting and dosing. Based on structural MRI scans, we constructed a simulation model of low-intensity TUS, with a particular focus on the optimal pathways of targeting hippocampus in human participants. Finally, we outlooked the future perspectives of TUS in clinical applications in neurological and psychiatric fields.

neuroscience↗

bioRxiv2024

CosinorTest: An R Shiny App for Cosinor-model-based circadian and differential analysis in transcriptomic applications

Summary CosinorTest application is an interactive R Shiny tool designed to facilitate circadian and differential circadian analysis with transcriptomic data using Cosinor-model-based methods. This novel application integrates multiple major statistical algorithms to identify circadian rhythmicity in gene expression data and enables the comparison of differential circadian patterns between two experimental conditions. Key features of the CosinorTest app include circadian rhythmicity detection, differential patterns assessment, circadian and differential analyses with repeated measurement, and interactive data visualization, all contributing to a comprehensive understanding of underlying biological mechanisms. As the application doing all comprehensive circadian analysis using the Cosinor model, the CosinorTest app fills a crucial gap in the field of circadian biology and transcriptomics, providing a powerful and user-friendly platform for researchers, especially those without profound programming skills to explore the circadian gene expression regulation, and further advance circadian research. Availability and implementationCosinorTest is freely available at https://circadiananalysis.shinyapps.io/circadianapp/. Contacthading@augusta.edu Supplementary informationSupplementary files are available at bioR{chi}iv online.

bioinformatics↗

bioRxiv2024

NOLC1 Suppresses Immuno-chemotherapy by Inhibiting p53-mediated Ferroptosis in Gastric Cancer

Gastric cancer (GC) is one of the most malignant cancers, and cisplatin (Cis)-based chemotherapy remains the main clinical treatment for GC. However, Cis resistance often occurs, largely limiting its therapeutic efficacy in tumors. Therefore, a better understanding of the drug resistance mechanism could reveal new approaches for improving GC treatment efficacy. Here, we define the integrative role of nucleolar and coiled-body phosphoprotein 1 (NOLC1), a molecular chaperone that is significantly upregulated in GC tissues and Cis-resistant GC cells. Knocking down NOLC1 increased GC sensitivity to Cis by regulating ferroptosis. Mechanistically, NOLC1 binds to the p53 DNA binding domain (DBD), decreasing p53 nuclear accumulation stimulated by Cis and suppressing p53 transcriptional functions. Then, the p53-mediated ferroptosis is suppressed. Furthermore, the silence of NOLC1 promoted ferroptosis-induced immunogenic cell death (ICD) and reprogrammed the immunosuppressive tumor microenvironment, thereby increasing sensitivity to anti-programmed cell death-1 (PD-1) therapy plus Cis. The combination of anti-PD-1 plus Cis effectively inhibited GC growth without significant side effects. In summary, our findings reveal that targeting NOLC1 may be a novel therapeutic strategy for GC and may increase the efficacy of chemotherapy combined with immune checkpoint inhibitor (ICI) therapy.

cancer biology↗