Biology subjects

Ma, L.

Publications and source records attributed to Ma, L..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Artificial Intelligence of Things-Enhanced Automated Surveillance System for Global Antimicrobial Resistance in Food Supply Chain

Antimicrobial resistance (AMR) threatens food safety across the farm-to-fork continuum. Real-time surveillance is crucial to mitigate its global escalation, yet conventional antimicrobial susceptibility testing (AST) remains slow, labor-intensive, and impractical for large-scale monitoring. We developed an Artificial Intelligence of Things (AIoT)-integrated multiplex microfluidic platform enabling automated AMR surveillance of pathogens in food supply chain. Each node combines a single-board AIoT controller (Orange Pi 5B), portable incubator, colorimetric microfluidic chips, and environmental sensors, reducing costs by 98% compared with standard AST. A lightweight YOLOv5 model embedded in the controller achieved >99% accuracy in identifying bacterial growth and inhibition under antibiotic pressure, showing 96% and 95% agreement with standard results for Salmonella and Campylobacter, respectively. Data are synchronized to a cloud server for real-time aggregation and early resistance warning. This fully automated and low-cost system minimizes human error and workload, providing a scalable sample-to-answer solution for AMR surveillance in global agri-food system.

microbiology↗

bioRxiv2026

Rapid Assessment of Immune Effector Cell-mediated Cytotoxicity using mRNA Lipid Nanoparticles

Cellular immunotherapy has revolutionized cancer treatment by enabling more targeted and personalized disease management. As the field progresses, there is an increasing need for high-throughput in vitro assays to efficiently assess the cytotoxicity of therapeutic cells. Conventional cytotoxicity assays pose various limitations in the workflow and scalability. Here, we present an mRNA lipid nanoparticle (mRNA-LNP) approach to efficiently and robustly deliver reporter genes to target cells for assessing immune effector cell-mediated cytotoxicity. This approach enables the rapid, homogenous reporter expression without compromising the viability of target cells. The cytotoxicity results obtained using mRNA-LNP-transfected cells are highly consistent and comparable to those obtained using cell lines with stable reporter gene expression. Finally, we highlight the mRNA-LNP approachs compatibility across a diverse range of tumor models, including primary tumor-derived models, enabling rapid and high-throughput assessment of the potency of various cytotoxic therapeutic cells.

immunology↗

bioRxiv2026

Evolutionary genomics of local adaptation, climate vulnerability, and linarin metabolism in Opisthopappus longilobus

Global climate change and human activities are posing substantial threats to biodiversity. The genus Opisthopappus (O. taihangensis and O. longilobus), endemic to Chinas Taihang Mountains, possesses great ecological, ornamental and medicinal value. However, it is confronted with the pressures of habitat fragmentation and climate change. Here, we present the first haplotype-resolved, chromosome-scale genome assembly of O. longilobus ([~]2.95 Gb) and re-sequence 115 individuals across its range. Comparative analyses show Opisthopappus is sister to Artemisia-Chrysanthemum, with Opisthopappus and Chrysanthemum diverging at 5.15-5.18 million years ago. A profound genetic divergence is evident between O. taihangensis and O. longilobus, resulting in two distinct lineages within each species, driven by geography and climate. Our analyses indicate restricted gene flow, low diversity, and recurrent demographic bottlenecks collectively contribute to their endangerment. By integrating population genomics and environmental variables, we identified 4,437 core adaptive genes linked to water deprivation, and metabolism. Genomic offset predicts higher maladaptation risk in populations under drastic climate change. Furthermore, diverged promoters of two O-methyltransferase genes, OMT250 and OMT310, likely underlie the differential acacetin/linarin accumulation between C. morifolium and O. longilobus. These findings advance understanding of Opisthopappus evolution and climate vulnerability, offering a model for genomics-guided biodiversity conservation.

plant biology↗

bioRxiv2025

A gastric microbial chromatin remodeler drives gastric cancer progression and immune evasion by reprogramming the host epigenome

Emerging evidence highlights the crucial role of microbial communities in modulating cancer development and progression. In gastric cancer (GC), we identify Streptococcus anginosus (SA) as a tumor-resident oncobacterium that drives both tumor progression and immune evasion. We define a novel mechanism in which SA secretes extracellular vesicles (saEVs) that translocate the bacterial chromatin remodeler saSNF2 into host cell. There, saSNF2 partners with host transcription factor TEAD1--through its ATPase activity and participation in BAF complex assembly--to coordinately activate oncogenic transcription. This transkingdom interaction upregulates the palmitoyltransferase ZDHHC11, which in turn stabilizes PD-L1 via palmitoylation to establish an immunosuppressive niche, while also amplifying other TEAD1 target genes to fuel tumor progression. Functionally, saEVs promote tumor growth and limit CD8+ T-cell infiltration in vivo. Strikingly, pharmacological inhibition of ZDHHC11 reverses immune evasion and synergizes with anti-PD-1 checkpoint blockade. Our results establish SA as a multifaceted driver of GC and reveal the saSNF2-ZDHHC11 axis as a promising target to potentiate immunotherapy.

cancer biology↗

bioRxiv2025

A multivalent mRNA-LNP therapeutic vaccine with broad cross-genotype immunogenicity elicits clearance of HBV infected hepatocytes

Chronic hepatitis B remains a major global health challenge, affecting over 254 million individuals and causing over 1 million deaths annually. Despite current antiviral therapies effectively suppressing viral replication, functional cure rates are low due to HBV-induced immune dysfunction and exhaustion. Therefore, new therapeutic approaches to achieve immune control of HBV infection are needed. Following the systematic evaluation of multiple HBV mRNA antigen designs, we developed mRNA-1965, a trivalent therapeutic mRNA vaccine encoding nanoparticle-displayed PreS1 and PreS2 domains of HBsAg to bypass the immune interference caused by HBV subviral particles, along with mutant forms of HBV Core and Polymerase. In HBV naive mice, mRNA-1965 immunization induced dose-dependent HBV-neutralizing antibodies and Th1-skewed CD4+ and IFN{gamma}+ CD8+ T cell responses to all three encoded HBV antigens. In non-human primates, mRNA-1965 elicited broad antibody and T cell responses across multiple HBV genotypes. Furthermore, vaccination with mRNA-1965 achieved a strong neutralizing antibody response and complete clearance of serum and liver HBV biomarkers in in an AAV-HBV mouse model with [~]100 IU/mL baseline HBsAg. Notably, combining mRNA-1965 with immune stimulatory co-modalities targeting PD-L1 and OX40 further enhanced therapeutic efficacy in mice with [~]1000 IU/mL baseline HBsAg. Clearance of HBV in AAV-HBV mice was associated with T cell response to mRNA-encoded antigens and with activation and differentiation of Core-specific CD8+ T cells. These findings support the potential of mRNA-1965 to promote a functional cure for chronic hepatitis B by overcoming immune dysfunction and subsequently enabling robust, functional immunity.

immunology↗

bioRxiv2025

Machine learning for integrative multi-omics clustering and feature gene identification

Multi-omics integrative analysis provides a powerful means for elucidating complex molecular mechanisms and biological processes, yet remains challenging in effectively representing the multi-dimensional relationships inherent to multi-omics data. Here we present MIA, a tensor-based representation learning framework that preserves the multi-dimensional structure of multi-omics data for accurate sample clustering and feature discovery. Unlike existing algorithms that primarily rely on two-dimensional representations, MIA models multi-omics data as a three-dimensional tensor and integrates tensor decomposition, fuzzy c-means, and an enhanced random forest model within a unified framework for clustering and feature discovery. Benchmarking on simulated and empirical datasets demonstrates that MIA consistently outperforms representative state-of-the-art algorithms in both clustering and feature identification. Application to multiple TCGA cancer types further shows its ability to stratify samples and identify molecular features associated with clinically relevant outcomes. Specifically, in glioblastoma, MIA reveals three previously uncharacterized subtypes with distinct prognostic profiles and uncovers feature genes strongly associated with subtype identity. These genes are further linked to therapeutic response and retain discriminative power across major glioblastoma cellular populations at single-cell resolution. Collectively, our results establish MIA as a generalizable computational framework for multi-omics integrative analysis, enabling systematic molecular stratification and interpretable feature discovery across diverse biological systems.

bioinformatics↗

bioRxiv2025

DECODING BRAIN DYNAMICS VIA CROSS-NETWORK NON-LINEAR TRAJECTORIES

Infant brain networks mature rapidly and nonlinearly, yet cross-network comparisons of developmental trajectories remain rare. We introduce cross-network non-linear trajectory characterization (CNTC), which fits cubic polynomials to age-related change in three spatial measures--network-averaged spatial similarity (NASS), network strength, and network size--derived from resting-state fMRI. Using 137 scans from 74 neurotypical infants spanning 0-6 months of age, we estimated networks via group ICA, modeled age trajectories within each network, and then contrasted coefficients across networks. Across seven canonical systems, trajectories showed robust age effects. Cross-network differences were dominated by linear terms, with selective quadratic effects and few cubic effects. Visual and cerebellar systems exhibited the steepest NASS slopes and pronounced increases in strength and size, whereas motor/attention changes were more gradual. CNTC provides a compact, coefficient-level summary of inter-network maturation and a basis for benchmarking atypical development in future work.

neuroscience↗

bioRxiv2025

Oxymatrine Induces Ferroptosis in MKN28 Gastric Cancer Cells

This study aimed to investigate the effect and potential mechanism of oxymatrine (OMT) on MKN28 gastric cancercells. Through a series of experiments including CCK8 cell viability assay, lipid peroxidation level detection, and Fe2+ concentration measurement, it was found that OMT significantly inhibited the viability of MKN28 cells in a dose- and time-dependent manner. OMT could induce an increase in intracellular lipid peroxidation level and iron ion concentration, while activating ferroptosis-related signaling pathways, indicating that OMT can induce ferroptosis in MKN28 cells. This study provides a new theoretical basis and potential target for the application of OMT in gastric cancer treatment.

cancer biology↗

bioRxiv2025

Epithelial FOXP3 Drives Pancreatic Fibrosis through O-glycosylated IL-6

BACKGROUND & AIMSThe transcription factor FOXP3, known for specifying regulatory T cell fate, is unexpectedly expressed in the epithelium of precancerous pancreatic lesions. Here we investigate its non-immune role in initiating pancreatic fibrosis, a process driving therapeutic resistance and organ failure in pancreatic ductal adenocarcinoma (PDAC) with unknown origins in early neoplasia. METHODSUsing human tissues and genetically engineered mouse models, we analysed FOXP3 expression in premalignant lesions. We employed epithelial-specific FOXP3 knockout and knock-in strategies to determine its functional impact on fibrogenesis and neoplasia progression. Mechanistic studies included chromatin immunoprecipitation, glycomic analyses, and signalling assays. RESULTSFOXP3 was consistently expressed in the epithelial compartment of human and murine precancerous pancreas. Epithelial-specific deletion of FOXP3 attenuated pancreatic fibrosis and delayed neoplasia, whereas its knock-in induced spontaneous stromal activation and accelerated PanIN progression. Mechanistically, epithelial FOXP3 directly transactivated the glycosyltransferase GALNT1. GALNT1, in turn, mediated O-glycosylation of interleukin (IL)-6, which was essential for its rapid secretion. CONCLUSIONSOur study establishes epithelial-derived FOXP3 as a master regulator of early pancreatic fibrocarcinogenesis. It drives a glycosylation-dependent amplification loop for IL-6 signalling, orchestrating sustained stromal activation. This pathway represents a promising target for intercepting pancreatic fibrosis and carcinogenesis at its origin.

cancer biology↗

bioRxiv2025

A human forebrain organoid model phenocopies dysregulated RNA and protein homeostasis in ALS/FTD-associated TDP-43 proteinopathies

TAR DNA-binding protein 43 (TDP-43) proteinopathy is a defining pathological feature of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), yet the downstream molecular events linking TDP-43 dysfunction to neurodegeneration remain incompletely understood. Here, we model TDP-43 proteinopathy by introducing the ALS/FTD-associated TARDBP K181E mutation into human induced pluripotent stem cells and differentiating them into three-dimensional forebrain organoids. Organoids carrying the K181E mutation exhibit spontaneous TDP-43 hyperphosphorylation, cytoplasmic p-TDP43 accumulation, RNA dysregulation, pro-inflammatory signaling, and activation of apoptotic pathways without TDP-43 overexpression or external stress. Single-cell transcriptomics and enhanced crosslinking immunoprecipitation reveal that the K181E mutation alters TDP-43 RNA-binding specificity, causing widespread RNA mis-splicing including cryptic exon inclusion. Among affected targets, we identify cryptic exon inclusion in the transcription factor PRDM2. PRDM2 cryptic exon-derived peptide immunoreactivity was detected in ALS spinal motor neurons and associated with p-TDP-43 pathology. These findings identify PRDM2 mis-splicing as a candidate downstream event linking TDP-43 dysfunction relevant to ALS and FTD. One sentence summaryHuman brain organoids reveal how mutant TDP-43 disrupts RNA processing and causes neuronal stress.

neuroscience↗

bioRxiv2025

Targeting the host factor HGS-viral membrane protein interaction in coronavirus infection

While current antivirals primarily target viral proteins, host-directed strategies remain underexplored. Here, we performed a genome-wide CRISPRi screening to identify the host protein, Hepatocyte Growth Factor-Regulated Tyrosine Kinase Substrate (HGS), as essential for the pan-coronaviruses infection both in vitro and in vivo. Mechanistically, HGS directly interacts with the viral membrane (M) protein, facilitating its trafficking to the ER-Golgi intermediate compartment (ERGIC) for virion assembly. Conversely, HGS deficiency caused M retention in the ER, blocking assembly. Leveraging this interaction, we designed M-derived peptides and screened over 5,000 FDA-approved drugs, identifying riboflavin tetrabutyrate (RTB). Both the peptides and RTB bind HGS and disrupt its interaction with the M protein, leading to M retention in the ER and subsequent blockade of virion assembly. These agents demonstrated broad anti-pan-coronavirus activity in vitro and in vivo. Collectively, our findings establish HGS as a druggable host target and identify RTB as a promising broad-spectrum antiviral candidate.

microbiology↗

bioRxiv2025

Machine learning-based definition of cellular senescence reveals pro-senescence potential implication in lung adenocarcinoma

Despite growing evidence implicating cellular senescence in tumor progression, methodological challenges in objectively quantifying senescent cell burden across cancer types continue to limit mechanistic studies and clinical translation. To address this, we developed the Predictive Cellular Senescence Model (PreCSenM), a machine learning-based tool that assigns a CS score by integrating senescence-associated features across 888 samples. Benchmarking analyses confirmed that PreCSenM markedly outperforms existing methodologies in reliably predicting senescent states within both normal and cancerous transcriptomic datasets. In lung adenocarcinoma (LUAD), PreCSenM identified the CS score as a robust predictor of clinical outcomes. Multi-omics analyses further revealed that lower CS levels correlate with decreased genomic stability and enhanced immune responses, aligning with clinical observations. Notably, drug discovery using PreCSenM identified histone deacetylase inhibitors (HDACis) as potent inducers of CS in LUAD. Transcriptional and epigenetic profiling of HDACi-treated cells pinpointed FOSB as a core transcription factor driving CS, and FOSB knockdown blocked HDACi-induced senescence. Overall, our study establishes PreCSenM as a multidimensional senescence quantification tool, bridging computational prediction with clinical relevance and mechanistic validation to enable senescence-directed therapies in precision oncology.

bioinformatics↗

bioRxiv2025

Ecological constraints foster both extreme viral-host lineage stability and mobile element diversity in a marine community

Phages are typically viewed as very rapidly evolving biological entities. Little is known, however, about whether and how phages can establish long-term genetic stability. We addressed this eco-evolutionary question in an open marine animal associated system, through two longitudinal samplings years apart in an oyster farm, obtaining >1,000 virulent phages and >600 Vibrio crassostreae strains. Surprisingly, lineages of phage and bacteria were very persistent, with some phages remaining strictly identical after four years. The phage-vibrio infection network remained modular with multiple lineages co-habitating within individual oysters for long periods of time. Seasonal restriction of V. crassostreae, overwintering in wild oysters, and limited viral decay may explain phage stability. Oysters also act as hotspots of activity of diverse mobile genetic element (MGE), hosting plasmids, prophages, phage-plasmids and entirely new classes of satellite-plasmids. Our findings demonstrate how nested ecological constraints can stabilize viral lineages: oysters house vibrio populations that escape host immunity, vibrios restrict phages via receptors and defenses, and satellites parasitize their cognate helper phages. We suggest that ecological context can favor the long-term maintenance of viral lineages and stabilize MGE persistence in the ocean, even amid ongoing mutation and antagonistic co-evolution.

microbiology↗

bioRxiv2025

The role of medicinal Cu2+ salts in expanding the multi-pathway application of tigecycline against drug-resistant bacteria

Tetracyclines are highly susceptible to photolysis, causing pollution in water, land and other ecosystems, as well as posing threats to human health. In this study, we found that only tigecycline and minocycline reduce the antibacterial activity in light, and this inferiority has severely hindered their scope of clinical use. By strategically regulating the photolysis pathway, we identified chalcanthite, which primarily contains Cu2+. By conducting antibiotic susceptibility test and electron microscopy analysis, Cu2+ salts (including copper sulfate, copper chloride, and copper gluconate) were confirmed to restore the antibacterial activity of tigecycline under light exposure against all tested bacterial strains. Spectroscopic characterization combined with quantum chemical calculations elucidated the molecular mechanism by which Cu2+ selectively modulates the photolytic degradation pathway of tigecycline and structural determinants (dimethylamino groups on the D ring). Multi-omics technologies revealed the mechanism underlying the Cu2+-mediated (non-antibacterial) inhibition of bacterial ferric citrate transporter. Animal infection models were developed using diverse drug-resistant pathogens to validate the in vivo therapeutic efficacy of copper gluconate-tigecycline combination therapy under photic conditions. These findings revealed effective adjuvants that facilitate the development of topical tigecycline formulations, and the establishment of a scientific foundation for synthesizing photostable tetracycline-based antibiotics through structural optimization.

biochemistry↗

bioRxiv2025

Diagnosis-Optimized Dynamic Feature Learning Reveals Altered Default Mode Network Connectivity in Schizophrenia

Schizophrenia (SZ) is characterized by widespread neural dysconnectivity, with particularly pronounced alterations in the default mode network (DMN)--a set of brain regions involved in self-referential thought and mind-wandering. We investigated dynamic functional connectivity within the DMN in SZ by analyzing resting-state fMRI data from two independent cohorts (FBIRN and COBRE). Using a novel iterative feature-removal clustering approach focusing on DMN independent components, we identified distinct recurring connectivity states while iteratively removing dominant connectivity features to reveal subtler network patterns. This approach iteratively refines the set of features considered, ensuring a more balanced representation and facilitating the identification of significant interactions that would otherwise be overlooked. Cluster centroids for the four connectivity states were highly similar across both datasets, reflecting stable shared DMN patterns. State occupancy was compared between participants with SZ and healthy controls, and associations with clinical symptom severity were examined. The SZ group exhibited significant alterations in DMN connectivity dynamics, spending more time than controls in certain connectivity states characterized by atypical DMN coupling and less time in a state reflecting a normative DMN configuration. A comparison between the FBIRN and COBRE datasets reveals both similarities and differences in occupancy rate (OCR) states. Overall, the pattern of group effects converged while state-specific divergences likely reflected protocol/sample differences rather than conflicting biology. Crucially, the explainability pipeline yielded a highly similar feature-removal order across datasets, indicating that the same DMN edges drive the diagnostic signal in both cohorts. Several OCR effects also tracked symptom ratings, linking abnormal DMN dynamics to clinical expression. Our findings suggest that SZ is characterized by reproducible disturbances in the temporal organization of DMN connectivity. These dynamic DMN features may serve as potential biomarkers for SZ, offering diagnostic and clinical utility by capturing network dysfunction that static connectivity measures could overlook.

neuroscience↗

bioRxiv2025

A targeted amplicon sequencing panel for cost-effective high-throughput genotyping of Aedes aegypti

The mosquito Aedes aegypti is the primary vector for several medically significant arboviruses, including dengue, Zika, chikungunya, and yellow fever. Studying the genetic diversity of Ae. aegypti is crucial for understanding its evolutionary history, population dynamics, and the effectiveness of vector control methods. Due to the large genome size of Ae. aegypti, whole-genome sequencing (WGS) is often cost-prohibitive for large-scale studies. Recent advances in reduced-representation methods, aiming to reduce costs by sequencing only a small portion of the genome, provide cost-effective alternatives. However, a standardized set of genome-wide markers specifically designed for population genetic studies of Ae. aegypti remains unavailable. Here, we present a targeted amplicon sequencing panel designed for cost-effective, high-throughput genotyping across 291 loci distributed throughout the Ae. aegypti genome. Our in silico analyses indicate that this amplicon panel effectively replicates population structure analyses typically derived from WGS data. We demonstrate that the amplicon panel accurately discriminates between diverse laboratory colonies of Ae. aegypti and consistently measures individual genetic admixture to a degree comparable with WGS. By enabling high-throughput genotyping at a reduced cost, we anticipate that our targeted amplicon sequencing panel will facilitate large-scale genotyping studies of Ae. aegypti for vector surveillance and population structure analyses, especially in resource-limited settings.

genomics↗

bioRxiv2025

NQO1 phase condensation promotes stress granule assembly to facilitate pancreatic carcinogenesis

G3BP1 promotes pancreatic ductal adenocarcinoma (PDAC) tumorigenesis driven by oncogenic KRAS mutations through liquid-liquid phase separation (LLPS)-mediated assembly of stress granules (SGs). However, the regulatory mechanisms remain elusive. We identify the antioxidant enzyme NAD(P)H quinone dehydrogenase 1 (NQO1) as a novel SG regulator that enhances SG assembly in pancreatic cancer cells independently of reactive oxygen species (ROS). Mechanistic studies reveal that NQO1 does not regulate the expression of G3BP1 or other SG-associated genes. Instead, NQO1 undergoes LLPS dependent on its RNA-binding K homology (KH) like domain. Further analysis demonstrates that residues 121-131 of NQO1 directly interact with G3BP1s RNA-binding domain (RBD), enhancing the multivalency of G3BP1 complexes to potentiate LLPS-driven SG assembly. This interaction accelerates cell proliferation, KRAS mutation-induced acinar-to-ductal metaplasia (ADM), and pancreatic carcinogenesis. Notably, the interaction between NQO1 residues 121-131 and G3BP1s RBD is essential for NQO1 phase condensation under stress condition. Integrative analysis of human PDAC transcriptomic datasets reveals a weak association between NQO1 and G3BP1 levels. Importantly, both NQO1 and G3BP1 formed biological condensates and co-localized in the lesions of human PDAC tissue sections. Our study uncovers a novel KRAS mutation-driven mechanism of pancreatic carcinogenesis through the lens of phase separation, transcending conventional gene expression regulation and offering new insights into non-canonical KRAS-NQO1-G3BP1-SG regulatory networks in PDAC initiation.

cancer biology↗

bioRxiv2025

Bayesian inference of lineage trees by joint analysis of single-cell multimodal lineage-tracing data with BiLinT

The advent of single-cell lineage-tracing technologies has enabled simultaneous measurement of gene expression and lineage barcodes. However, integrating these modalities for high-resolution lineage reconstruction has remained challenging due to limitations of methods that analyze modalities separately. In response, we present BiLinT, a Bayesian framework for reconstructing high-resolution cell lineage trees by jointly modeling single-cell multimodal lineage-tracing data. BiLinT integrates lineage barcode evolution (modeled via a continuous-time Markov chain) and gene expression dynamics (modeled via an Ornstein-Uhlenbeck process) within a unified probabilistic model. Applications to synthetic and real datasets demonstrate improved accuracy and reveal developmental fate biases.

bioinformatics↗