Biology subjects

Zhang, M.

Publications and source records attributed to Zhang, M..

At least 181 records · Page 10Linked to original sources

bioRxiv2025

N6-Methyladenine DNA modification regulates pathogen virulence in nematodes

Understanding the global regulatory mechanisms that control pathogen virulence gene expression is essential for elucidating the molecular basis of pathogenicity. N6-methyladenine (6mA) plays a crucial role in regulating gene expression in response to various environmental stresses; however, its role in pathogen virulence remains largely unexplored. Here, we report the widespread occurrence of 6mA across 17 nematode isolates and map its genomic landscape in six notorious agriculturally important pathogen root-knot nematodes (RKNs). We demonstrated that 6mA is characterized by a conserved GAG motif across nematodes, but exhibits species-specific distribution patterns and distinct effects on gene expression. In particular, its enrichment in transposable elements differs between polyploid and diploid nematodes, suggesting lineage-specific epigenetic regulation potentially associated with polyploidy. We further identified two functional 6mA demethylases, MiNMAD-1 and MiNMAD-2, and confirmed their catalytic activity and active sites. Host-induced gene silencing of minmad-1 significantly increased plant resistance to three polyploid RKN species. A detailed functional analysis revealed that minmad-1 knockdown disrupted virulence gene expression during the parasitic stage, thereby reducing nematode infectivity. Together, our findings suggest 6mA demethylase as a key epigenetic regulator of RKNs virulence, providing new insights into nematode biology and offering promising targets for the development of sustainable control strategies. Significance Statement6mA methyltransferase regulates the expression of virulence genes in certain pathogenic bacteria and plays a critical role in their infectivity. However, the regulation of virulence gene expression in eukaryotic pathogens, particularly plant pathogens, remains poorly understood. Most studies on pathogen virulence have focused on individual effectors, with little insight into global regulatory mechanisms. Here, we demonstrate that 6mA broadly shapes virulence gene expression patterns in polyploid RKNs. Moreover, transgenic tobacco, tomato, and rice plants expressing dsRNA against nematode demethylases showed significantly enhanced resistance to RKNs. These findings establish 6mA demethylase as a promising epigenetic target for controlling plant-parasitic nematodes.

molecular biology↗

bioRxiv2025

ACTL6A regulates the Warburg effect through coordinated activation of AP-1 signaling in head and neck squamous cell carcinoma

ACTL6a is an essential component of SWI/SNF and expressed on the chromosome 3q26 cytoband, which is amplified in head and neck squamous cell carcinomas (HNSCC). While ACTL6A is emerging as an oncogene, its role as a treatment target and mechanisms of transcription factor induction remain unknown. Here, we show that ACTL6A expression is a mediator of the Warburg effect, with ACTL6A knockdown inducing mitochondrial dependency and significantly decreasing levels of aerobic glycolysis. These effects lead to near complete attenuation of hypoxic cell growth by blunting induction of HIF1 and HIF2 protein expression. They also sensitize treatment resistant HNSCC cells to the tumor killing effects of the complex I inhibitor IACS-010759 in vivo. Using ATAC-seq, we identify ACTL6A as a mediator of chromatin accessibility of AP-1 transcription factor sites and find that it regulates upstream MAPK signaling through induction of Ras and Galectin-1. These effects sensitize ACTL6A over-expressing cells to inhibition of glycolysis by MEK inhibitors. Our results link SWI/SNF subunit amplification with potentiation of MAPK signaling in HNSCC and provide a novel mechanism by which cancer cells drive aerobic glycolysis and reduce mitochondrial dependency. We leverage these findings to propose treatment strategies for hypoxic tumors with SWI/SNF subunit amplifications.

cancer biology↗

bioRxiv2025

Structural insights and engineering of deep-sea halophilic PET hydrolytic enzymes

Pervasive use of polyethylene terephthalate (PET) poses tremendous challenges for global waste management and environmental sustainability, fueling growing interests in enzymatic degradation as an eco-friendly solution. While PET hydrolases hold significant promise, their industrial deployment is hindered by insufficient performance, particularly under high-salinity conditions raised from high substrate loads. Building on our previous discovery of three deep-sea PET hydrolases (dsPETase01, dsPETase05 and dsPETase06) with exceptional halophilicity and PET-degrading activity, we here present their three-dimensional structures and mechanistic characterization. Structural comparison, site-directed mutagenesis, and domain swapping reveal key structural features and the essential role of C-terminal acidic residues in salt tolerance. Integrating semi-rational protein design, Transformer-based modeling, and disulfide bond engineering, we synergistically enhance the thermostability and catalytic efficiency of dsPETase05. These findings elucidate the unique structural features and salt adaptation mechanisms of deep-sea halophilic PET hydrolases, and inform the future engineering of biocatalysts for application in harsh industrial environments.

molecular biology↗

bioRxiv2025

Cholesterol metabolism modulation facilitates CAR-T induced killing of ovarian cancer

Ovarian cancer is one of the most lethal gynecological cancers worldwide and has one of the highest recurrence rates. Recently developed Chimeric Antigen Receptor T (CAR-T) cell therapy has shown potent clinical efficacy against hematological malignancies. However, solid tumors, including ovarian cancer, possess several mechanisms that hinder T cell activity, and metabolic alteration of cancer cells has been shown to contribute to resistance to immune cell attack against solid tumors. Here, we explored the metabolic response of ovarian cancer cells to CAR-T cell attack using label-free high-content hyperspectral stimulated Raman scattering (h2SRS) imaging. Utilizing visible h2SRS imaging with much improved spatial resolution, we found an altered cholesterol metabolism, featured by increased storage of cholesteryl ester in lipid droplets and free cholesterol, in ovarian cancer cells that survived the CAR-T treatment. Administration of Avasimibe, an inhibitor of cholesteryl esterification, further enhanced CAR-T cytotoxicity. Our study shows the promise of implementing metabolic modulation to facilitate CAR-T cell treatment of solid tumors. Significance StatementOvarian cancer is a major global health challenge, mainly due to relapse driven by chemotherapy resistance development. Meanwhile, immunotherapies such as CAR-T have revolutionized treatment for blood cancers, but their application in solid tumors like ovarian cancer is hindered by limited efficacy. This study uses high-content stimulated Raman scattering (SRS) imaging to reveal metabolic adaptations that help ovarian cancer cells survive CAR-T-mediated cytotoxicity. Guided by these insights, we apply metabolic interventions that enhance CAR-T cytotoxicity efficacy. This approach reveals therapeutic vulnerabilities in ovarian cancer and demonstrates an investigative strategy applicable for overcoming resistance in solid tumors.

cell biology↗

bioRxiv2025

Patient-derived organoids reveal hypoxia-driven plasticity and therapeutic vulnerabilities in pheochromocytomas and paragangliomas

Pheochromocytomas and paragangliomas (PPGLs) are rare chromaffin cell-derived neuroendocrine tumors of sympathetic (catecholamine-producing) or parasympathetic (nonsecretory) origin, frequently driven by dysregulation of hypoxia-inducible factor (HIF) signaling, particularly HIF-2. Although often benign, PPGLs can metastasize unpredictably, with limited therapeutic options once disseminated. Progress has been hindered by the lack of robust preclinical models, especially those that capture their molecular complexity and microenvironmental influences. To address this gap, we established patient-derived tumor organoids (PDOs) from 35 PPGLs, encompassing a broad spectrum of clinical and molecular phenotypes. The organoids retained key immunohistochemical, genomic, transcriptomic, and catecholamine-secretory features of their parental tumors. PPGL organoids cultured under hypoxic conditions generally exhibited enhanced viability, supporting hypoxia as a driver of cell survival. Hypoxia activated HIF-1 and expanded ASCL1+ cell populations, suggesting a lineage shift toward an immature chromaffin state. In contrast, long-term normoxic cultures activated hypoxia inducible factor 2 (HIF-2) and acquired a hybrid sympathoblast-mesenchymal identity in subpopulations with upregulation of extracellular matrix and cell cycle markers, independent of genotype. These features resemble high-risk neuroblastoma subtypes and establish a molecular parallel suggestive of shared lineage plasticity and pathogenic programs, detectable in primary PPGLs. Drug screening across a library of up to 51 drugs and combinations revealed both shared and unique vulnerabilities, with response rates to approved therapies matching clinical observations. The CDK4/6 inhibitor abemaciclib, previously unexplored in PPGLs, elicited the strongest activity. Abemaciclib-responsive PDOs and their matched tumors, including a metastatic sample, exhibited epithelial mesenchyme transition enrichment, nominating potential biomarkers for patient stratification. Our results establish PDOs as a novel platform for modeling neuroendocrine tumor biology, reveal microenvironment-driven plasticity in PPGLs, with potential translational relevance, and identify actionable vulnerabilities in a disease with few effective systemic therapies. Main findingsO_LIPDOs can be successfully generated from PPGLs of various genetic backgrounds and reflect parental tumor properties C_LIO_LIPDO cultures grown in hypoxia retain main molecular features of parental tumors, have increased viability and a more immature developmental/biosynthetic profile C_LIO_LILong term PDOs grown for 4 weeks in normoxia activate HIF2, drift toward a hybrid sympathoblast-mesenchymal-like identity resembling relapsed/therapy resistant neuroblastomas, features that can be detected in primary tumors C_LIO_LIA subset of PDOs respond to Abemaciclib, a drug class not previously used therapeutically in PPGLs C_LI

cancer biology↗

bioRxiv2025

Temporal control of sgRNA library activation unlocks large-scale in vivo CRISPR screens

Functional genomics screens have illuminated genetic dependencies in cancer, but conventional in vitro approaches fail to capture vulnerabilities shaped by the tumor microenvironment. Here, we implement CRISPR-StAR (Stochastic Activation by Recombination), a next-generation inducible CRISPR screening platform for large-scale in vivo applications. The system uses a dual lox-based recombination system to enable guide-level normalization and clonal knockout phenotyping. To analyze the rich (barcode-embedded) sequencing output, we developed UMIBB, a superior Bayesian statistical framework for quantifying gene-level dropout and enrichment compared to conventional software packages. Screening a 30,000-sgRNA library in A549 xenografts, followed by clone representation and dropout correlation analyses, showed high fidelity and reproducibility with dropout phenotypes resolvable using as few as 30 tumors for this size library. Validation across multiple tumor models demonstrated that a single tumor can provide reliable, functional annotation for [~]1,000 genes leveraging intra-tumor library controls for normalization. Comparing in vivo and in vitro screens revealed that a substantial subset of tumor suppressor genes exerts strong phenotypic effects only observable in vivo. For example, single-gene knockout and transcriptomic profiling confirmed that KMT2C and KMT2D have contrasting impacts on tumor growth - an insight that would have been overlooked in standard cell culture. Looking ahead, CRISPR-StAR screening, combined with our user-friendly analysis pipeline available on GitHub (R-package), offer an integrated framework for creating in vivo dependency maps that can complement existing vitro datasets like DepMap and Achilles. Critically, our approach reduces animal use by up to 7-fold compared to conventional in vivo dropout screens. This represents a significant ethical and methodological advancement - achieving genome-scale resolution with far fewer animals and greater reproducibility.

genomics↗

bioRxiv2025

Dehydration promotes intracellular lipid synthesis and accumulation

Lipids can be considered a water reservoir used to offset dehydration stress as their oxidation by the mitochondria generates water. However, whether dehydration and the ensuing hypertonic stress directly regulate lipid synthesis is unknown. We found that hypertonic stress decreases cellular oxygen consumption, increases intracellular lipid synthesis, and favors glutamine oxidation as a carbon precursor for lipid synthesis via remodeling mitochondrial metabolism. These findings provide a mechanism whereby cellular dehydration leads to intracellular lipid accumulation, functionally linking water availability to lipid storage.

physiology↗

bioRxiv2025

Advancing Target Discovery Through Disease-Specific Integration of Multi-Modal Target Identification Models and Comprehensive Target Benchmarking System

Target identification is crucial for drug development. AI-driven approaches leveraging multi-omics and computational modeling can accelerate this process. However, integrating multi-modal data for disease-specific target identification and predicting translational potential remains challenging. Moreover, the absence of a systematic evaluation framework for model performance limits confidence in target reliability. We present a unified platform combining machine learning-based target identification with comprehensive benchmarking. As a testbed, we developed Target Identification Pro (TargetPro), a disease-specific model spanning 38 diseases across oncology, metabolic, immune, fibrotic, and neurological categories. TargetPro shows strong predictive performance for clinical-stage targets and reveals disease-specific patterns, underscoring the need for tailored target detection models. We next created Target Identification Benchmark (TargetBench 1.0) to rigorously assess target identification systems, including large language models, based on their ability to recover established targets and find high-quality novel candidates. This integrated approach offers a streamlined strategy to evaluate target discovery models, ultimately improving drug development efficiency.

bioinformatics↗

bioRxiv2025

An evolutionary leap in plant reproduction: From archegonia and motile sperm to embryo sacs and pollen tubes

The transition of plants from water to land marks a pivotal step in their evolutionary history, with the change in reproductive mode being the most fundamental. This change freed plant reproduction from aquatic dependence, fostering terrestrial lifes prosperity. Key to the shift from archegonial to embryo sac reproduction are pollen tube emergence and female gametophyte changes, though their evolutionary trajectories and mechanisms remain unclear. Ginkgo, a basal gymnosperm, occupies a pivotal position in this transition, retaining motile sperm, simplified archegonia, and primitive pollen tubes, making it an ideal model. To study how the transition between these two reproductive modes occurred, we collected transcriptome data from the reproductive organs of Ginkgo and evolutionarily representative species. Our findings reveal the MYB98-CRP-ECS module- critical for angiosperm pollen tube guidance--in Ginkgos mature archegonia, with pollen tubes containing guidance components. While egg cells are transcriptionally and functionally conserved across land plants, changes in the cell fate of other female gametophyte component cells drove the shift from archegonia to embryo sacs. Pollen tubes may originate from fern male gametophyte internalization and modification. These findings clarify the evolutionary path and molecular basis of this major reproductive transition.

plant biology↗

bioRxiv2025

Integrating 12 Spatial and Single Cell Technologies to Characterise Tumour Neighbourhoods and Cellular Interactions in three Skin Cancer Types

Cutaneous squamous cell carcinoma (cSCC), basal cell carcinoma (BCC), and melanoma - the three major skin cancers - collectively comprise over 70% of all cancer cases. Despite their prevalence, much understanding of cellular interactions in the skin cancer microenvironment is needed, both in the outer skin layer where the cancer originates and at the deeper junctional and dermal layers into which it progresses. To address this gap, we integrated 12 complementary spatial and single-cell technologies to generate orthogonally-validated cell signatures, spatial maps, and interactomes for cSCC, BCC, and melanoma. Through comprehensive comparisons and integrating these spatial methods, we provided practical benchmarking guidelines for experimental design and analysis. By identifying keratinocyte cancer cells and melanomas, we found distinct signatures of these cells compared to non-cancer keratinocytes and melanocytes. Spatial integration of transcriptomics, proteomics and glycomics uncovered cancer niches enriched for cancer initiating cells (melanocytes or keratinocytes) and fibroblast and T-cell (MKFT) clusters, with altered tyrosine and pyrimidine metabolism. Ligand-receptor analysis across >700 cell-type combinations and >1.5 million interactions highlighted key roles for CD44, integrins, and collagens, with CD44-FGF2 emerging as a potential therapeutic target. Consistently, melanoma showed strong MFT interactions, validated by Opal Polaris, RNAScope, Proximal Ligation Assay and two additional single-cell spatial platforms (making a total of 14 technologies). For population-scale generalisation, genetic associations from >500,000 individuals were mapped onto spatial skin tissues, identifying SNPs enriched in domains containing melanocytes and T cells and their ligand-receptor pairs, shedding light on functional mechanisms linking genetic heritability to cells within cancer tissue. We built an interactive multiomics resource for exploring spatially-resolved molecular signatures and cellular crosstalk in skin cancer, available at https://skincanceratlas.com.

cancer biology↗

bioRxiv2025

Three-Dimensional Mechanical Cooperativity Optimises Epithelial Wound Healing

Epithelial tissues serve as critical physical barriers that protect organs, making efficient repair essential upon damage. To achieve this, tissues must quickly react, forcing cells to rearrange and accommodate. Therefore, cells must cope with forces that will deform their shape to achieve these sudden but necessary changes. In the Drosophila wing disc, we showed how tissue fluidisation accelerated wound healing in 2D. However, the 3D aspect of tissue repair remains poorly understood. Here, we uncover a new mechanism aiding the tissue in repairing itself by changing cell height. We find actomyosin contractile cables at the wound edge connecting the apical and basal cell surface, which indent the apical side of the tissue and deform the basement membrane (BM), respectively. To understand the role of the different repair mechanisms, we developed a 3D vertex model allowing apico-basal intercalations. The model predicts that lateral cables play a role in regulating cell-cell intercalations, confirmed by Drosophila mutations affecting cell deformations. Our results demonstrate that lateral cables cooperate with the apical purse string to drive 3D cell shape changes and intercalations to promote more efficient wound repair.

developmental biology↗

bioRxiv2025

Construction of a genome-wide pooled CRISPRi library as a resource for exploring the acid tolerance mechanism in Streptococcus mutans

Streptococcus mutans is recognized as the primary etiological agent of dental caries, one of the most prevalent infectious diseases globally. Its remarkable acid tolerance enables survival and proliferation in the low-pH biofilm microenvironment, establishing S. mutans as the dominant species in dental plaque and a key contributor to cariogenesis. Although numerous studies have identified genes linked to acid tolerance mechanisms, the full set of essential acid tolerance genes within its genome remains incompletely characterized, largely due to the lack of systematic, genome-scale investigations. To address this knowledge gap, we constructed a genome-wide pooled CRISPR interference (CRISPRi) library targeting 95% of the predicted S. mutans genes and employed next-generation sequencing to identify acid tolerance determinants systematically. Our screen revealed 95 acid tolerance-associated genes, a subset of which were functionally validated through gene knockout studies. Functional enrichment analysis demonstrated significant associations with metabolic pathways (including cofactor biosynthesis and amino/nucleotide sugar metabolism), tRNA modification, and transcriptional regulation. Protein-protein interaction (PPI) network analysis identified critical interactors (ComYC, SMU_1979c, DeoC, AcpP, NadD, and SMU_1988c) and two functionally cohesive modules. These findings provide novel mechanistic insights into the acid adaptation strategies of S. mutans and highlight potential therapeutic targets for caries prevention.

microbiology↗

bioRxiv2025

Host Microenvironment Reprogramming by Saccharides Overcomes Lung Barriers for mRNA Therapeutics

AbstractOvercoming biological barriers remains the paramount challenge for pulmonary mRNA therapeutics. Conventional approaches focus exclusively on passively optimizing formulation quality without controlling dynamic host barriers. Here, we pioneer a host-centric strategy by leveraging sugar that actively reprograms the airway microenvironment to boost IVT-mRNA transfection. Utilizing machine learning-accelerated screening of a chemically diverse saccharide library, we identify D-glucose as the best-performing candidate. Glucose assisted-delivery within lipid nanoparticles (Glu-LNP) achieves robust, lung-specific protein expression (up to 131.21-fold increase) across diverse preclinical models with reduced inflammation. In lung carcinoma models, Glu-LNP-encapsulated IL-12 mRNA reduced tumor burden by approximately 59.12% and improved survival by 2.5-fold compared to the LNP group. Mechanistically, glucose orchestrates a dual-pathway cascade: metabolic reprogramming via the Warburg effect elevates ATP, fueling endocytosis and translation; ATP further activates the P2Y2-IP3 signaling axis that triggers Ca2+ release and subsequent CLCA1/TMEM16A-dependent chloride/bicarbonate efflux, which remodels mucus barriers and enhances nanoparticle penetration. This bioenergetic and mucolytic host intervention strategy presents a broadly applicable paradigm to transcend delivery limitations for respiratory mRNA therapeutics.

bioengineering↗

bioRxiv2025

Granulin+ macrophages promote lineage plasticity in prostate cancer through paracrine signaling loops

The role of tumor-infiltrating immune cells in driving phenotype switching remains unclear, despite the well-established association between lineage transition and drug resistance in prostate cancer. This study employed an integrated analysis of single-cell multiomics to investigate the dynamics of immune infiltration, transcriptional programs, and cell-cell communication in prostate cancer. Our results demonstrated that granulin (GRN) positive macrophages facilitated the transition from adenocarcinoma to a multilineage state with mesenchymal and stem-like traits by activating intra-tumoral NF-{kappa}B signaling. Subsequently, the multilineage clones induced macrophages to highly express granulin through the secretion of CSF1, forming a positive feedback cell communication loop. Next, we validated the biological function of granulin in mediating epithelial-mesenchymal transition in vitro. Additionally, organoids drug resistance assay demonstrated that granulin drove resistance to androgen receptor (AR)-targeted drug (enzalutamide). Moreover, pharmacologic blockade of the CSF-1/CSF-1R axis in TRAMP mouse models reduced the expression of GRN in macrophages and suppressed the formation of multilineage subclones in prostate malignant cells. Furthermore, multiplex immunofluorescence staining of tumor samples from TRAMP mouse models revealed the VIM lineages were spatially in close contact with macrophages. Meanwhile, Cytometry by Time-Of-Flight (CyTOF) analysis validated our findings at single-cell protein level in patients with castration-resistant prostate cancer. Besides, three distinct tumor-infiltrating subsets associated with disease relapse were identified, including DCN+ endothelial cells, CCL7+ fibroblasts, and IFIT1+ neutrophils. These results offer potential therapeutic targets to address lineage plasticity-driven resistance to AR-targeted therapy.

cancer biology↗

bioRxiv2025

Pluripotent stem cell-derived siTNK cells attack tumors via a synthetic CD8-CD28 TCR complex

Tumor-associated antigen-specific T cell receptor (TCR)-engineered T cells offer a promising strategy for cancer therapy. Natural killer (NK) cells exhibit broad anti-tumor activity with low side effects but lack the capacity to recognize intracellular antigens. Here, we found that the human pluripotent stem cell (hPSC)-derived iNK cells, unlike tissue-isolated NK cells, expressed all four CD3 subunits at the transcriptome level. We introduced a synthetic gene-expressing complex (SCOTR), encoding a tumor antigen- specific TCR, CD8 coreceptor, and CD28 costimulatory molecule, into hPSCs to generate SCOTR-hPSCs. The SCOTR-hPSCs gave rise to abundant synthetic TCR complex-expressing iNK (siTNK) cells via an organoid induction method. These siTNK cells showed HLA-dependent, antigen-specific cytotoxicity against tumor cells and significantly suppressed tumor growth in tumor xenograft animal models, while also preserving universal non-specific tumor-killing activity. Collectively, siTNK cells, as hPSC-derived hybrid cells with dual features of adaptive T and inherent NK cells, offer an artificial cell source for human immunotherapies.

immunology↗

bioRxiv2025

GREmLN: A Cellular Regulatory Network-Aware Transcriptomics Foundation Model

AO_SCPLOWBSTRACTC_SCPLOWThe ever-increasing availability of large-scale single-cell profiles presents an opportunity to develop foundation models to capture cell properties and behavior. However, standard language models such as transformers benefits from sequentially structured data with well defined absolute or relative positional relationships, while single cell RNA data have orderless gene features. Molecular-interaction graphs, such as gene regulatory networks (GRN) or protein-protein interaction (PPI) networks, offer graph structure-based models that effectively encode both non-local gene token dependencies, as well as potential causal relationships. We introduce GREmLN (Gene Regulatory Embedding-based Large Neural model), a foundation model that leverages graph signal processing to embed gene token graph structure directly within its attention mechanism, producing biologically informed single cell specific gene embeddings. Our model faithfully captures transcriptomics landscapes and achieves superior performance relative to state-of-the-art baselines on cell type annotation, graph structure understanding, and fine-tuned reverse perturbation prediction tasks. It offers a unified and interpretable framework for learning high-capacity foundational representations that capture complex, long-range regulatory dependencies from high-dimensional single-cell transcriptomic data. Moreover, the incorporation of graph-structured inductive biases enables more parameter-efficient architectures and accelerates training convergence.

bioinformatics↗

bioRxiv2025

PromptBio: A Multi-Agent AI Platform for Bioinformatics Data Analysis

PromptBio is a modular AI platform for scalable, reproducible, and user-adaptable bioinformatics analysis, powered by generative AI and natural language interaction. It supports three complementary modes of analysis designed to meet diverse research needs. PromptGenie is a multi-agent system that enables stepwise, human-in-the-loop workflows using prevalidated domain-standard tools. Within PromptGenie, specialized agents--including DataAgent, OmicsAgent, AnalysisAgent, and QAgent--collaborate to manage tasks such as data ingestion, pipeline execution, statistical analysis, and interactive summarization. DiscoverFlow provides integrated, automated workflows for large-scale multi-omics analysis, offering end-to-end execution and streamlined orchestration. ToolsGenie complements these modes by dynamically generating executable bioinformatics code for custom, user-defined analyses, enabling flexibility beyond standardized workflows. PromptGenie and DiscoverFlow leverage a suite of domain-specific tools, including Omics Tools for standardized omics pipelines, Analysis Tools for downstream statistical interpretation, and MLGenie for machine learning and multi-omics modeling. We present the design, capabilities, and validation of these components, highlight their integration into automated and customizable workflows, and discuss extensibility, monitoring, and compliance. PromptBio aims to democratize high-throughput bioinformatics through a large language model-powered, natural language understanding, workflow generation and agent orchestration.

bioinformatics↗

bioRxiv2025

Endogenous glucocorticoids moderate the gastric inflammatory response to Helicobacter infection and protect from autoimmunity.

Background and AimsImmune responses to infection must balance pathogen clearance with minimizing tissue damage and autoimmunity. Chronic gastric inflammation caused by H. pylori damages the gastric mucosa and promotes carcinogenesis. Glucocorticoids are immunoregulatory hormones that limit immune activation in the stomach. This study aimed to determine how endogenous glucocorticoids regulate the gastric immune response to Helicobacter infection and their impact on preneoplastic lesion development. MethodsWe examined the role of endogenous glucocorticoids in shaping the gastric immune response to Helicobacter felis colonization. Gastric immune cell infiltration, atrophy, metaplasia, and preneoplastic lesion development were evaluated in adrenal-intact control mice and adrenalectomized (ADX) mice. Auto-reactive IgG antibodies were assessed using a mouse self-antigen array and by measuring their binding to healthy gastric tissue. ResultsLoss of endogenous glucocorticoids led to significantly increased H. felis-induced gastric T cell infiltration and proinflammatory cytokine expression compared to intact-infected controls. While all intact mice maintained chronic infection for up to 12 months, nearly all ADX mice eradicated H. felis within 2-3 weeks. Despite bacterial clearance, ADX mice continued to exhibit chronic gastric inflammation and developed dysplasia. Autoantibody profiling showed that both intact and ADX groups generated self-reactive IgG during active infection. However, only ADX mice sustained autoantibody production following bacterial eradication. ConclusionsEndogenous glucocorticoids attenuate gastric inflammation during Helicobacter infection, supporting bacterial persistence while maintaining immune tolerance. These findings suggest that heightened immune responses to H. pylori may trigger autoimmune gastritis (AIG) development, which can persist after H. pylori clearance and continue to drive gastric cancer risk.

immunology↗