Biology subjects

Gao, M.

Publications and source records attributed to Gao, M..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Comprehensive characterization of V(D)J recombination from long-read transcriptomic data with VDJcraft

V(D)J recombination generates antigen receptor diversity in developing B and T cells. Long-read transcriptome technologies (e.g., PacBio Iso-Seq, Nanopore RNA/cDNA) capture full-length transcripts and thus resolve V(D)J events more accurately than short-read platforms. However, existing short-read tools are not applicable to or optimized for long-read data. We developed VDJcraft, the first integrated pipeline designed for V(D)J recombination analysis using long-read transcriptome sequencing data. The workflow uses a two-pass alignment strategy: global alignment to the GENCODE reference with minimap2, followed by local realignment and annotation using the international ImMunoGeneTics information system (IMGT). A customized module enhances D-gene detection sensitivity and positional precision. Sequencing errors are reduced through consensus-based correction toward the predominant subclass. Antigen-binding regions are annotated using IMGT-defined motifs to characterize CDRs and binding site composition. VDJcraft was validated on simulated and Human Genome Structural Variation Consortium (HGSVC) datasets and applied to disease datasets. It accurately recovered full-length V(D)J-C sequences and outperformed existing methods in gene detection and recombination accuracy. Long-read calls also showed significantly higher concordance with high-confidence short-read calls (Mann-Whitney U test, p = 1.55 x 10-4). Additionally, we identified 31 putative novel gene subclasses absent from the IMGT database from HGSVC datasets. Analyses of longitudinal blood samples from a COVID-19 patient revealed distinct V(D)J recombination patterns and segment enrichment, characterized by increased IGHV1-2 usage, enrichment of the IGHV3-7/IGHD6-9/IGHJ5_02 rearranged clonotype, and a transient peak in IgG2 levels at day 4 followed by a gradual return to baseline. In conclusion, VDJcraft provides a robust framework for long-read V(D)J characterization and enables the discovery of disease-associated immune signatures.

bioinformatics↗

bioRxiv2026

Transplanting ANXA1- CD8+ Naive T cells Delay Aging Through Senolysis

Immunosenescence is a hallmark of aging, yet strategies using defined immune subsets to counteract it are largely unexplored. We performed paired scRNA/TCR-seq on CD45 cells from human bone marrow (15 donors, 3-91 years). T cells were the most altered lineage, with CD8 naive T cell contraction and functional impairment. We identified an expanding ANXA1 CD8 naive subset with senescence signatures and impaired function. ANXA1-deficient CD8 T cells exhibited increased resting stemness and enhanced activation/cytotoxicity upon stimulation. ANXA1- cells showed senolytic activity in vitro and reduced senescence burden in vivo. Monthly transfer of syngeneic ANXA1- CD8 naive T cells into aged mice extended median lifespan by >30 weeks, improving cardiac function, bone density, motor coordination, and marrow immune microenvironment. Our study identifies ANXA1 as critical in CD8 naive T cell aging and establishes ANXA1- cell transfer as a strategy to counter immunosenescence and promote healthy aging.

immunology↗

bioRxiv2026

MATR3 is essential for oocyte growth and maturation quality through a dual molecular mechanism

The molecular mechanisms governing mRNA accumulation during oocyte growth, essential for developmental competence, remain poorly understood. This study investigates the role of Matrin-3 (MATR3), a highly expressed RNA-binding protein in growing oocytes (GOs), using oocyte-specific knockout mouse models and human oocyte maturation arrest (OMA) samples. The results showed that MATR3 was more abundant in GOs than fully-grown oocytes (FGOs), highly expressed in the nucleus of non-surrounded nucleolus (NSN) oocytes, and exited the nucleus during the NSN-to-surrounded nucleolus (SN) transition. In OMA patients, MATR3 nuclear localization was missed, with smaller oocytes than FGOs. Further, Matr3 deletion in mouse GOs caused restricted oocyte growth, global transcription disorders, follicle development failure, blocked GO-granulosa cell communication (via reduced Gdf9 and Radixin expression), and infertility. Mechanistically, MATR3 regulated transcription by recruiting H3K9me2-demethylating lysine-specific demethylase 3B or binding target gene promoters, like Radixin. These findings reveal a critical role of MATR3 in orchestrating transcription and paracrine signaling during oogenesis and suggest its potential as a diagnostic and therapeutic target for OMA.

physiology↗

bioRxiv2026

ChatDIA: A zero-shot large language model workflow for targeted analysis of data-independent acquisition mass spectrometry data

Data-independent acquisition (DIA) proteomics enables reproducible, large-scale protein identification and quantification but remains challenging to analyze due to highly complex MS/MS spectra and chromatographic interference, particularly in low signal-to-noise single-cell proteomics. Here, we introduce ChatDIA, a zero-shot large language model (LLM)-based workflow for targeted DIA analysis that operates through an explicit reasoning-based decision framework. ChatDIA performs automated peptide identification and supports natural-language interaction with DIA data. Unlike purpose-built DIA software that relies on domain-specific models, ChatDIA employs general-purpose LLMs in a zero-shot setting to reason directly over extracted ion chromatograms and generate human-interpretable rationales for each decision. On an expert-annotated Streptococcus pyogenes DIA benchmark dataset, ChatDIA achieved 96.9% accuracy, matching the domain-specific state-of-the-art software DIA-NN (95.5%). In a challenging single-cell HEK-293T DIA proteomics dataset, ChatDIA further demonstrated excellent performance, achieving a lower risk-coverage area under the curve than DIA-NN (0.06 vs. 0.12) and identifying 38.75% and 46.25% of library peptides at 1% and 5% false discovery rate, respectively, compared with 16.25% and 48% for DIA-NN. Together, these results demonstrate that zero-shot LLM reasoning can competitively automate core targeted DIA decision-making while providing transparent, inspectable rationales that enable conversational, interactive validation and data exploration in noisy proteomics applications. More broadly, ChatDIA illustrates how reasoning-based AI systems can move beyond prediction to generate evidence-based decisions, offering a foundation for more general and interpretable computational analysis in proteomics.

bioinformatics↗

bioRxiv2025

A metagenomics-based tool for surveillance of bacterial pathogens in environmental samples

Bacterial pathogens are responsible for millions of human deaths and significant losses in food production annually. Soil acts as a natural reservoir for many critical bacterial pathogens, however, the lack of accurate, high-throughput methods to identify the distribution of bacterial pathogens in soil and other environments greatly limits our ability to develop effective surveillance and disease management strategies and policies. Here, we present MetaPatho, an easy-to-use, rapid, robust, and shotgun metagenomics-based tool for identifying human and plant bacterial pathogens in environmental metagenomes. We first constructed high-quality pathogenic databases for the identification of human and plant bacterial pathogens. In-silico tests and soil spike-in experiments, including pathogen DNA spike-in and cell spike-in tests, were then employed to examine the accuracy and robustness of our tool. The in-silico tests suggested that the tool accurately identified pathogenic sequences, achieving an average accuracy of 97.4%, with a specificity of 98.1% and a sensitivity of 97.2%. Further analyses from soil spike-in experiments showed that the tool accurately detected bacterial pathogens at different concentrations, achieving an average accuracy of 96.3%. Overall, our tools can provide a high-throughput and accurate surveillance of bacterial pathogens in environmental metagenomes, contributing to an effective risk management associated with human and plant diseases.

microbiology↗

bioRxiv2025

Pervasive splicing in a plant DNA virus

RNA splicing is considered an oddity in plant viruses; here, unexpectedly, we find it to be prevalent in the geminivirus tomato yellow leaf curl virus. Transcriptome analysis revealed eight splicing events generating novel protein isoforms, six of which were validated and two shown to depend on the plant spliceosome. Splicing impairment reduced viral accumulation and symptom severity, demonstrating that splicing contributes to infectivity, potentially by expanding the viral proteome, and suggesting that plant virus transcriptomes need to be reassessed.

plant biology↗

bioRxiv2025

Programming Microbe-Computer Interaction for Customized Life-Nonlife and Cross-Life Communication

This extension of human-computer interaction (HCI) paradigm to the non-intelligent microbe-computer interaction (MCI) is attractive for building generalized life-nonlife communication. Main challenges lie in how to construct biohybrid interface within individual MCI unit and thereafter program cross-life communication based on these MCI units. Here, we propose the design and construction of opto-interfaced MCI unit composed of engineered microbes and computer terminals, for enabling quantifiable transduction between microbial signals and digital signals. These units were able to serve as biohybrid sensors, actuators and transceivers, supporting biomonitoring, bio-actuation and microbe-centric bidirectional operations. Based on these functional units, we established programmable cross-life communication architectures capable of unicast, multicast, and logic-gate-driven communication with temporal dynamic control. The architectures were validated in biomedical scenarios including tumor hypoxia biomarking, epidermal heavy metal detoxification, and colitis intervention, demonstrating robust performance in closed-loop diagnostic-therapeutic applications. Additionally, we integrated MCI with an unmanned surface vessel for environmental monitoring, highlighting its cross-domain potential. Collectively, we provide a scalable strategy for building customized life-nonlife and cross-life communication, which is expected as an important complement to internet of things (IoT).

synthetic biology↗

bioRxiv2025

Integrative Systems Biology Identifies the AHR Signaling Axis as a Mechanistic Basis for Xiaobi Plaster in Lumbar Disc Degeneration

BackgroundLumbar disc degeneration (LDD) is characterized by chronic inflammation, oxidative stress, and extracellular matrix (ECM) breakdown, yet current therapies provide only symptomatic relief. Xiaobi Plaster (XBG), a traditional Chinese transdermal herbal preparation, has shown clinical benefit, but its molecular mechanisms remain unclear. MethodsWe applied an integrative systems biology framework combining network pharmacology, machine learning, and transcriptomic validation to identify candidate targets of Xiaobi Plaster in LDD. Molecular docking, dynamics simulations, and immune infiltration analysis further elucidated the underlying mechanisms, which were experimentally validated in a rat puncture-induced degeneration model. ResultsThree key targets--AHR, PTPN2, and SOAT1--were identified, with AHR emerging as the central regulator. Differential expression and enrichment analyses highlighted inflammatory and ECM-remodeling pathways, which overlapped with AHR-specific GSEA, underscoring its hub role in integrating immune and redox signaling with matrix turnover. Molecular docking and 100-ns molecular dynamics confirmed rutaecarpine (MOL002662) as the most stable AHR ligand. Transcriptomic data further showed AHR expression correlates with degeneration severity and mast cell infiltration. In vivo qPCR and Western blotting validated upregulation of AHR and supporting roles of PTPN2 and SOAT1 in degenerative discs. ConclusionThis study elucidates the multi-target and multi-pathway mechanisms of XBG in LDD, highlighting AHR as a pivotal therapeutic target modulated by rutaecarpine, with PTPN2 and SOAT1 serving as auxiliary regulators. These findings provide mechanistic insights into the transdermal application of XBG and support the therapeutic relevance of targeting the AHR signaling axis in LDD.

bioinformatics↗

bioRxiv2025

Transcontinental Spread of HPAI H5N1 from South America to Antarctica via Avian Vectors

Our study has for the first time identified H5N1 strains (clade 2.3.4.4b, genotype B3.2) in brown skuas from the Fildes Peninsula, South Shetland Islands, Antarctica. These findings indicate that highly pathogenic avian influenza H5N1 viruses is now actively circulating in Antarctic ecosystems, representing a significant expansion of its geographic range.

genomics↗

bioRxiv2025

Neural signaling contributes to heart formation and growth in the invertebrate chordate, Ciona robusta.

Neurons contribute to the complex interplay of signals that mediate heart development and homeostasis. Although a limited set of studies suggest that neuronal peptides impact vertebrate heart growth, the specific contributions of these peptides to cardiomyocyte progenitor differentiation or proliferation have not been elucidated. Here we show that the neuropeptide tachykinin along with canonical Wnt signaling regulate cardiomyocyte progenitor proliferation in the chordate model Ciona robusta. In C. robusta, the heart continues to grow throughout adulthood and classic histological studies indicate that a line of undifferentiated cells may serve as a reserve progenitor lineage. We found that this line of cardiomyocyte progenitors consists of distinct distal and midline populations. Distal progenitors divide asymmetrically to produce distal and midline daughters. Midline progenitors divide asymmetrically to produce myocardial precursors. Through single cell RNA sequencing (scRNA-seq) of adult C. robusta hearts, we delineated the cardiomyocyte progenitor expression profile. Based on this data we investigated the role of Wnt signaling in cardiomyocyte progenitor proliferation and found that canonical Wnt signaling is required to suppress excessive progenitor proliferation. The scRNA-seq data also identified a number of presumptive cardiac neural-like cells. Strikingly, we found that a subset of these neuronal cells appears to innervate the distal cardiomyocyte progenitors. Based on the expression of the tachykinin receptor in these neuronal cells, we blocked tachykinin signaling using pharmacological inhibitors and found that this drove reduced proliferation in the distal progenitor pool. Through targeted CRISPR-Cas9 knockdown we then demonstrated that both extrinsic tachykinin and intrinsic, cardiac tachykinin receptors are required for formation of the myocardial heart tube. This work provides valuable insights into how organisms may deploy neural signals to regulate organ growth in response to environmental or homeostatic inputs.

developmental biology↗

bioRxiv2025

Neural correlates of appetitive extinction learning: An fMRI study with actively participating pigeons

AbstractExtinction learning is an important learning process that enables adaptive and flexible behavior. Human neuroimaging studies show that the neural basis of extinction learning consists of a neural network that includes the hippocampus, amygdala, and subcomponents of the prefrontal cortex, but also extends beyond them. The limitations of applying fMRI to actively participating animals have so far restricted the identification of the entire extinction network in non-human animals. Here, we present the first fMRI study of extinction in awake and actively participating pigeons, using a Go/NoGo operant paradigm with a water reward. Our study revealed an extensive and largely left hemispheric telencephalic network of sensory, limbic, executive, and motor areas that slowly ceased to be active during the process of extinction learning. We propose that the onset of extinction ignites a neuronal updating of the associated consequences of own actions within a large telencephalic neural network until a new association is established which inhibits the previously acquired operant response.

neuroscience↗

bioRxiv2025

Harnessing the Power of Single-Cell Large Language Models with Parameter Efficient Fine-Tuning using scPEFT

Single-cell large language models (scLLMs) capture essential biological insights from vast single-cell atlases but struggle in out-of-context applications, where zero-shot predictions can be unreliable. To address this, we introduce a single-cell parameter-efficient fine-tuning (scPEFT) framework that integrates learnable, low-dimensional adapters into scLLMs. By freezing the backbone model and updating only the adapter parameters, scPEFT efficiently adapts to specific tasks using limited custom data. This approach mitigates catastrophic forgetting, reduces parameter tuning by over 96%, and decreases GPU memory usage by more than half, significantly enhancing scLLMss accessibility for resource-constrained researchers. Validated across diverse datasets, scPEFT outperformed zero-shot models and traditional fine-tuning in disease-specific, cross-species, and under-characterized cell population tasks. Its attention-mechanism analysis identified COVID-related genes associated with specific cell states and uncovered unique blood cell subpopulations, demonstrating scPEFTs capacity for condition-specific interpretations. These findings position scPEFT as an efficient solution for improving scLLMs utilities in general single-cell analyses.

cell biology↗

bioRxiv2025

Metabolic reinvigoration of NK cells by IL-21 enhances immunotherapy against MHC-I deficient solid tumors

Natural killer (NK) cells, a type of potent cytotoxic lymphocytes, are particularly promising for the treatment of cancers that lose or downregulate major histocompatibility complex class I (MHC-I) expression to evade T cell-mediated immunotherapy. However, the hostile and immune suppressive tumor microenvironment (TME) greatly hinders the function of tumor-infiltrating NK cells limiting the therapeutic efficacy against solid tumors. Here, we show that a fusion protein of interleukin-21 (IL-21-Fc), as a direct in vivo intervention, can safely and effectively reprogram NK cell metabolism and enhance their effector function in the TME. Our research demonstrates that combining IL-21-Fc with IL-15 superagonist (IL-15SA) or NK cell transfer leads to the eradication of MHC-I-deficient tumors and confers durable protection in syngeneic and xenograft tumor models. Mechanistically, we uncover that IL-21-Fc enhances NK cell effector function by upregulating glycolysis in a lactate dehydrogenase A (LDHA)-dependent manner. These findings not only underscore the considerable potential of IL-21-Fc as an in vivo therapeutic intervention to bolster NK cell-based immunotherapy, but also unveil an innovative strategy of metabolic reprogramming for NK cell rejuvenation within tumors. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=183 SRC="FIGDIR/small/643961v2_ufig1.gif" ALT="Figure 1"> View larger version (57K): org.highwire.dtl.DTLVardef@daf24forg.highwire.dtl.DTLVardef@5a5029org.highwire.dtl.DTLVardef@144c978org.highwire.dtl.DTLVardef@106ed1c_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LINK cells display functional exhaustion in MHC-I deficient solid tumors C_LIO_LIIL-21-Fc as an in vivo-applicable and safe immunotherapy reinvigorates intratumoral NK cells for enhanced effector function C_LIO_LIIL-21-Fc enhances NK cell function by elevating glycolysis in a LDHA-dependent manner C_LIO_LICombining IL-21-Fc with low-dose IL-15SA or NK cell transfer eradicates syngeneic and xenografted solid tumors C_LI

cancer biology↗

bioRxiv2025

Mechanistic modeling suggests stroma-targeting antibody-drug conjugates as an alternative to cancer-targeting in cases of heterogeneous target expression

Antibody-drug conjugates (ADCs) are gaining increasing traction in the treatment of oncological diseases; however, many clinical failures have also been observed. One key factor limiting ADC effectiveness is the heterogeneous expression of their target antigen. While the vast majority of ADCs in clinical development target antigens on cancer cells (cancer-targeting), they can also target antigens expressed on non-cancerous stromal cells in the tumor microenvironment (stroma-targeting). It remains unclear whether targeting cancer cells or stromal cells is more effective in suppressing tumor growth. Here, we present three related mathematical models to evaluate: (1) cancer-targeting ADCs with homogeneous target antigen expression, (2) cancer-targeting ADCs with heterogeneous target antigen expression, and (3) stroma-targeting ADCs. Our simulations suggest that cancer-targeting ADCs can achieve high efficacy when their target antigen is homogenously expressed. However, in cases of heterogeneous antigen expression, cancer-targeting ADCs may lead to an initial reduction in tumor size, followed by regrowth due to the elimination of antigen-positive cells and expansion of antigen-negative cells. This limitation could potentially be overcome by stroma-targeting ADCs, as antigen-positive stromal cells may continue to be recruited into the tumor by the oncogenic factors produced by the remaining cancer cells. Furthermore, we demonstrate that ADCs with more permeable payloads and less stable linkers may offer improved efficacy in the context of heterogeneous target expression.

pharmacology and toxicology↗

bioRxiv2025

A fast numerical integration scheme for clonal expansion processes on graphs

Compound birth-death processes are widely used to model the age-incidence curves of many cancers [1]. There are efficient schemes for directly computing the relevant probability distributions in the context of linear multi-stage clonal expansion (MSCE) models [2]. However, these schemes have not been generalised to models on arbitrary graphs, forcing the use of either full stochastic simulations or mean-field approximations, which can become inaccurate at late times or old ages [3, 4]. Here, we present a numerical integration scheme for directly computing survival probabilities of a first-order birth-death process on an arbitrary directed graph, without the use of stochastic simulations. As a concrete application, we show that this new numerical method can be used to infer the parameters of an example graphical model from simulated data.

cancer biology↗

bioRxiv2025

ORP2 regulates free cholesterol accumulation in hepatocytes during MASH

BackgroundCholesterol crystals in hepatocytes are known to strongly associate with human Metabolic Dysfunction-Associated Steatohepatitis (MASH). However, it remains unclear which molecular pathway(s) regulates free cholesterol accumulation, and therefore the formation of cholesterol crystals in hepatocytes. In cultured cell lines, oxysterol-binding protein-related protein 2 (ORP2) functions to deliver cholesterol to the plasma membrane from internal organelles. MethodsHere, we generated liver-specific ORP2 knockout (ORP2-LKO) mice and characterized their metabolic phenotypes on chow and high fat diet. ResultsThe ORP2-LKO mice developed much more severe hepatic steatosis than wild type mice after high-fat diet feeding. They also demonstrated more severe liver inflammation and damage. Notably, free but not esterified cholesterol, as well as cholesterol crystals accumulated in ORP2-LKO liver. The expression of Cyp7a1 was significantly upregulated in ORP2-LKO liver, accompanied with accumulation of taurocholic acid. Our results thus unveil an important in vivo function of ORP2 in preventing free cholesterol from accumulating in mouse liver. Conclusionsour results suggest that impaired cholesterol trafficking may enhance the deposition of cholesterol crystals in hepatocytes, promoting the development of MASH.

cell biology↗

bioRxiv2024

The genetic diversity and populational specificity of the human gut virome at single nucleotide resolution

Large-scale characterization of gut viral genomes provides strain-resolved insights into host-microbe interactions. However, existing viral genomes are mainly derived from Western populations, limiting our understanding of global gut viral diversity and functional variations necessary for personalized medicine and addressing regional health disparities. Here, we introduce the Chinese Gut Viral Reference (CGVR) set, consisting of 120,568 viral genomes from 3,234 deeply sequenced fecal samples collected nationwide, covering 72,751 viral species-level clusters (VSCs), nearly 90% of which are absent from current databases. Analysis of single nucleotide variations (SNVs) in 233 globally prevalent VSCs revealed that 18.9% showed significant genetic stratification between Chinese and non-Chinese populations, potentially linked to bacterial infection susceptibility. The predicted bacterial hosts of population-stratified viruses exhibit distinct genetic components associated with health-related functions, including multidrug resistance. Additionally, viral strain diversity at the SNV level correlated with human phenotypic traits, such as age and gastrointestinal issues like constipation. Our analysis also indicates that the human gut bacteriome is specifically shaped by the virome, which mediates associations with human phenotypic traits. This foundational resource underscores the unique genetic makeup of the gut virome across populations and emphasizes the importance of recognizing gut viral genetic heterogeneity for deeper insights into regional health implications.

microbiology↗

bioRxiv2024

An Expanded Registry of Candidate cis-Regulatory Elements for Studying Transcriptional Regulation

Mammalian genomes contain millions of regulatory elements that control the complex patterns of gene expression. Previously, The ENCODE consortium mapped biochemical signals across many cell types and tissues and integrated these data to develop a Registry of 0.9 million human and 300 thousand mouse candidate cis-Regulatory Elements (cCREs) annotated with potential functions1. We have expanded the Registry to include 2.35 million human and 927 thousand mouse cCREs, leveraging new ENCODE datasets and enhanced computational methods. This expanded Registry covers hundreds of unique cell and tissue types, providing a comprehensive understanding of gene regulation. Functional characterization data from assays like STARR-seq, MPRA, CRISPR perturbation, and transgenic mouse assays now cover over 90% of human cCREs, revealing complex regulatory functions. We identified thousands of novel silencer cCREs and demonstrated their dual enhancer/silencer roles in different cellular contexts. Integrating the Registry with other ENCODE annotations facilitates genetic variation interpretation and trait-associated gene identification, exemplified by discovering KLF1 as a novel causal gene for red blood cell traits. This expanded Registry is a valuable resource for studying the regulatory genome and its impact on health and disease.

genomics↗