Biology subjects

Ma, H.

Publications and source records attributed to Ma, H..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

Metagenomic Analysis Reveals Northwest Pacific Ocean as a Reservoir and Evolutionary Hub of Antibiotic Resistance Genes

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/659680v1_ufig1.gif" ALT="Figure 1"> View larger version (81K): org.highwire.dtl.DTLVardef@139e191org.highwire.dtl.DTLVardef@10834c4org.highwire.dtl.DTLVardef@1c0544aorg.highwire.dtl.DTLVardef@1ddfd8a_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO C_FIG Antibiotic resistance genes (ARGs) were identified as a novel type of environmental contaminants. Ocean is thought to be one of the ultimate environments where ARGs gathered. Marine ecosystems represent vast reservoirs of ARGs, yet their dynamics in open-ocean environments remain poorly characterized. Through large-scale metagenomic profiling of the Kuroshio Extension, a hydrographically dynamic region in the Northwest Pacific, we identified a striking enrichment of ARGs (1.81 x 10-3 ppm) at a frontal zone site (S30). The ARG abundance at this site exceeded coastal levels by 90-fold. Notably, multidrug resistance genes dominated this hotspot, with efflux pumps contributing 62% of the resistance mechanisms, a pattern distinct from the target-alteration strategies prevalent in other regions. The site exhibited unique microbial consortia, including pathogenic Acinetobacter (30.2% abundance) carrying clinically critical determinants (blaOXA-23, adeJ). Co-occurrence networks revealed horizontal transfer risks, linking pelagic Sphingobium to terrestrial-derived {beta}-lactamase variants. Crucially, we discovered three novel plasmid-borne resistance genes circulating in >15% of microbial populations, demonstrating open-ocean ARG diversification independent of direct anthropogenic inputs. These findings redefine oceanic frontiers as crucibles of resistance evolution, demanding urgent integration into global antimicrobial stewardship strategies.

microbiology↗

bioRxiv2025

ImmunoFusion: A Unified Platform for Investigating RNA-seq-Derived Gene Fusions in Cancer and Immunotherapy

BackgroundGene fusions play a critical role in cancer development by persistently activating kinases or inactivating tumor suppressor genes, leading to altered signal transduction and gene expression regulation. However, their impact on treatment responses remains poorly understood. Although existing cancer databases catalog numerous fusion events or immune checkpoint blockade (ICB) studies, no unified platform integrates gene fusion data across cancer types while linking them to the tumor microenvironment (TME) and patient outcomes. Such integration is essential for elucidating how fusions shape immune responses and for developing improved biomarkers for personalized cancer therapies. MethodsTo address this gap, we constructed the Fusion Immune Atlas (ImmunoFusion), a platform integrating data from TCGA, TARGET, CPTAC, and 29 ICB cohorts (including ICB treatments and other treatment modalities) across diverse cancer types. We identified fusion events from raw RNA-seq data using Arriba and STAR-Fusion, and standardized fusion calls by adapting MetaFusion to the GRCh38 reference genome. Additionally, we curated clinical data and estimated TME signatures and cell fractions using the Immuno-Oncology Biological Research (IOBR) approach. ImmunoFusion was developed using the high-quality Rhino framework for Shiny applications, built on R. ResultsImmunoFusion (https://shiny.zhoulab.ac.cn/ImmunoFusion) encompasses 21,014 clinical samples, serving as a comprehensive RNA-seq-derived gene fusion database and analytical tool. It offers functionalities to investigate fusion breakpoints, confidence scores, frequency patterns, and associations with clinical variables. The platform also enables TME evaluation and interactive exploration of fusions for analyzing tumor immunophenotypes in cancer and immunotherapy contexts. As an illustration, analysis of MTAP fusions in lung cancer cohorts revealed their association with a metabolically depleted, "cold" (immune-suppressive) tumor environment and poorer patient outcomes, pinpointing MTAP fusions as a novel biomarker for treatment selection. ConclusionsImmunoFusion represents a significant advancement, delivering a unified platform to explore the influence of gene fusions on cancer and immune responses. It offers particular value in understanding fusion-driven immunotherapy outcomes, paving the way for more effective therapeutic strategies.

bioinformatics↗

bioRxiv2025

Developmental constraints mediate the summer solstice reversal of climate effects on European beech bud set

Accurate projections of temperate tree growing seasons under climate change require representing developmental constraints that determine tree resource allocation. Recent work has identified a phenological "switch point" after the summer solstice (21 June), with pre-solstice warming advancing autumn phenology and post-solstice warming delaying it. Here, we propose this switch is flexible and occurs at the compensatory point between the antagonistic effects of early-season development and late-season temperature. We performed trans-solstice climate manipulation experiments on potted European beech (Fagus sylvatica) saplings to test (i) how spring leaf-out timing and June-August temperatures influence end-of-season timing (bud set and leaf senescence [50% loss of leaf chlorophyll content]), and (ii) whether daytime and nighttime temperatures before and after the solstice have different effects, given that trees primarily grow at night. Bud set and leaf senescence responses were tightly coupled (R2 = 0.49), with bud responses being generally stronger. Each day delay in spring leaf-out delayed bud set by 0.24 {+/-} 0.06 days and senescence by 0.22 {+/-} 0.08 days. Post-solstice full-day cooling in July delayed autumn phenology in late-leafing individuals (bud set +4.9 {+/-} 2.6 days; senescence +3.1 {+/-} 2.8 days) but had negligible impact on early-leafing trees (bud set +1.4 {+/-} 2.6 days; leaf senescence +2.2 {+/-} 2.8 days). Conversely, August full-day cooling advanced both stages. Daytime cooling before the solstice had no effect, while after the solstice it advanced autumn phenology. Nighttime cooling always delayed bud set. These findings support the Solstice-as-Phenology-Switch model and highlight the central role of developmental progression in constraining growing seasons. Faster early-season development -especially under nighttime warming- moves trees past the switch earlier, increasing sensitivity to late-season cooling and thereby triggering earlier autumn phenology. To improve growing season length projections, phenology models should account for these developmentally-mediated and diel-specific temperature responses.

ecology↗

bioRxiv2025

A synthetic biology toolkit for interrogating plasmid-dependent methylotrophy and enhancing methanol-based biosynthesis of Bacillus methanolicus

Bacillus methanolicus represents a thermophilic methylotroph whose methanol utilization depends on plasmid-encoded genes. It serves as a unique model for deciphering plasmid-dependent methylotrophy and an ideal chassis for low-carbon biomanufacturing using CO2-derived C1 substrates. Despite its evolutionary uniqueness and industrial potential, the lack of synthetic biology tools has hindered both mechanistic understanding and strain engineering. Here, we present a comprehensive synthetic biology platform comprising a high-efficiency electroporation protocol, a CRISPR method enabling robust and multiplex genome editing, diverse neutral loci for gene integration and overexpression, and a cloud-based genome-scale metabolic model iBM822 for user-friendly biodesign. Leveraging this toolkit, we systematically dissected plasmid-dependent methylotrophy, host restriction-modification systems, and functional significance of the chromosomal methylotrophic genes through targeted deletion. To address plasmid loss-induced strain degeneration, we integrated the large endogenous plasmid pBM19 into the chromosome for stable and intact methylotrophic growth. Finally, by integrating metabolic modeling with CRISPR editing, we engineered L-arginine feedback regulation to achieve the first L-arginine biosynthesis from methanol. This study establishes a synthetic biology framework for B. methanolicus, promoting mechanistic exploration of methylotrophy and low-carbon biomanufacturing.

synthetic biology↗

bioRxiv2025

Replication competition drives the selective mtDNA inheritance in Drosophila ovary

Purifying selection that limits the transmission of harmful mitochondrial DNA (mtDNA) mutations has been observed in both human and animal models. Yet the precise mechanism underlying this process remains undefined. Here, we present a highly specific and efficient in situ imaging method capable of visualizing mtDNA variants that differ by only a few nucleotides at single-molecule resolution in Drosophila ovaries. Using this method, we revealed that selection primarily occurs within a narrow developmental window during germline cysts differentiation. At this stage, the proportion of the deleterious mtDNA variant decreases without a reduction in its absolute copy number. Instead, the healthier mtDNA variant replicates more frequently, thereby outcompeting the co-existing deleterious variant. These findings provide direct evidence that mtDNA selection is driven by replication competition rather than active elimination processes, shedding light on a fundamental yet previously unresolved mechanism governing mitochondrial genome transmission.

genetics↗

bioRxiv2025

PIBE: Parallel ion beam etching of sections collected on wafer for ultra large-scale connectomics

We developed a parallel ion beam etching device that simultaneously thins hundreds of sections on a whole 4-inch wafer at 20 nm steps, enabling sub-centimeter volumetric imaging with high axial resolution. Compared with traditional volume electron microscopy, PIB preserves in-situ continuity within sections and simplifies inter-section registration. Its high axial resolution facilitates reliable neuron segmentation and tracing with reduced proofreading, providing an efficient route toward ultra-large-scale connectomics, such as whole-mouse-brain reconstruction.

neuroscience↗

bioRxiv2025

Single-Cell Pharmacogenomic Landscapes of Epigenetic Therapy in Gastric Cancer

Gene expression signatures ("molecular phenotypes") are extensively utilized in cancer research. To study how gastric cancer (GC) molecular phenotypes are shaped by cell-intrinsic genetic alterations interacting with cell-extrinsic therapeutic pressures, we performed direct capture Perturb-seq (dcPerturb-seq) to interrogate >200 GC-related genes across 4 distinct epigenetic drug classes in multiple gastric lines. We captured 17.7 million pharmocogenomic expression interactions in 625,866 cells representing baseline and post-therapeutic molecular phenotypes. This single-cell pharmacogenomic compendium confirmed previously known gene-driven molecular phenotypes, elucidated poorly characterized genes, and uncovered novel gene dosage-molecular phenotype relationships. Molecular phenotypes in post-therapeutic surviving cells revealed diverse gene perturbation-associated pathways causing convergent drug resistance (EMT plasticity, cell cycle alterations, metabolic reprogramming), highlighting combinatorial strategies for restoring sensitivity. Mapping of in vitro molecular phenotypes to primary human GCs imparted prognostic information and insights into spatial heterogeneity. Comparative analysis of gene perturbations across therapies and lines revealed both conserved and context-specific molecular alterations. Our results illustrate how Perturb-seq approaches can systematically map diverse cancer-associated molecular phenotypes across multiple gene/drug/cell line interactions, yielding translational insights.

cancer biology↗

bioRxiv2025

Single-Cell eQTL Mapping Reveals Cell Type-Specific Genetic Regulation in Lung Cancer

Genome-wide association studies (GWAS) have identified over 50 lung cancer risk loci; however, the precise cellular context of these genetic mechanisms remains unclear due to limitations in bulk tissue eQTL analyses. Here, we present the largest single-cell eQTL atlas of human lung tissue to date, profiling 222 donors using multiplexed scRNA-seq. We identified 16,785 eQTLs across 17 cell types, with over 90% of sc-eQTLs and 59% eGene being cell-type-specific, and fewer than 23% were detectable in paired bulk datasets. Integration with GWAS for non-small cell lung cancer highlighted epithelial and immune cells as key contributors to genetic susceptibility, identifying 28 candidate genes within known risk loci and 24 in novel regions. Notably, 47% of established NSCLC susceptibility loci exhibited cell-type-specific pleiotropic genetic regulation. This study provides a valuable resource of lung sc-eQTLs and illuminates how genetic variation modulates gene expression in a cell-type-specific fashion, contributing to lung cancer susceptibility.

genetics↗

bioRxiv2025

Expanding the chicken gut virome: Uncovering viral diversity, host interactions, and regional variations across the intestinal tract

Chicken gastrointestinal virome comprises a complex and diverse viral community with significant implications for host health and microbiome function. We analyzed 3,312 publicly available chicken gut metagenomic datasets to establish the chicken gastrointestinal virome collection (CGVD), which includes 39,380 non-redundant viral operational taxonomic units (vOTUs); notably, 84.90% (33,433/39,380) represent novel sequences absent from current databases. Over half of the CGVD vOTUs were classified as bacteriophages, predominantly from the order Caudovirales. The predicted hosts were mainly prokaryotes, particularly Bacillota and Bacteroidota, revealing a multifaceted landscape of virus-host interactions. Many vOTUs infected multiple bacterial phyla, indicating high adaptability and broad ecological impact. In addition, lifestyle prediction showed that 28.28% (11,137 /39,380) of the vOTUs in CGVD were identified as lytic phages. Functional annotation demonstrated that viral genes contribute to key metabolic processes, including nucleotide and amino acid metabolism, thereby facilitating viral replication and host adaptation. The detection of auxiliary metabolic genes and carbohydrate-active enzymes underscores the role of viruses in modulating the gut microbiome. Although antibiotic resistance genes and mobile genetic elements were present, their contribution to horizontal gene transfer appears limited. Additionally, marked regional differences in virome composition were observed between the small and large intestines, particularly in the abundance of families such as Siphoviridae and Myoviridae. CGVD not only highlights the key role of viruses in shaping the chicken gut microbiome and influencing microbial dynamics and metabolic pathways, but also provides new resources and insights for future research.

microbiology↗

bioRxiv2025

SynBioGPT: A Retrieval-Augmented Large Language Model Platform for AI-Guided Microbial Strain Development

Synthetic biology seeks to engineer microbial cell factories for sustainable bioproduction, yet the optimization of these systems is impeded by the complexity of metabolic engineering and the protracted timelines of iterative design-build-test-learn (DBTL) cycles. Traditional computational approaches, such as constraint-based modeling, provide valuable insights but demand extensive manual curation. Large language models (LLMs) hold promises for automating knowledge extraction and strain design, yet conventional models like GPT-4 suffer from outdated corpora and hallucination errors in domain-specific tasks. SynBioGPT v1.0, a Retrieval-Augmented Generation (RAG)-enhanced LLM, enhanced knowledge retrieval using vector search but often retrieved semantically similar yet contextually irrelevant documents. Here, we introduce SynBioGPT v2.0 (https://synbiogpt.biodesign.ac.cn), which mitigates these limitations by decomposing queries into sub-questions and employing keyword-based searches. Tested on a 100-question synthetic biology benchmark, SynBioGPT v2.0 achieved 98% accuracy with the Claude-3.7-sonnet backend, a 10% improvement over v1.0s 88% with Llama3-8B-Instruct. This advance highlight the efficacy of query decomposition and precise retrieval in enhancing LLM utility for synthetic biology.

synthetic biology↗

bioRxiv2025

A multi-modal whole-slide image processing pipeline for quantitative mapping of tissue architecture, histopathology, and tissue microenvironment

Multi-modal, multiscale imaging is crucial for quantitative high-content spatial profiling. We present an integrated image processing pipeline for comprehensive tissue analysis that combines quantitative phase microscopy for tissue architecture mapping, hyper-plex fluorescence imaging for immune microenvironment profiling, and whole-slide histopathology. This approach enables detailed morphological mapping of tissue architecture and cell morphology, while simultaneously linking them to the functional states of individual cells across the entire slide. By analyzing tissue biopsies from patients with ulcerative colitis, we demonstrate the potential of this pipeline for quantitative spatial analysis of molecular markers related to mucosal healing. Open-source and compatible with conventional microscopy systems, this pipeline provides a powerful tool for research and clinical applications through its comprehensive integration of quantitative, high-content, and histological imaging modalities.

bioinformatics↗

bioRxiv2025

A piece of evidence for pathogenesis of cerebral small vessel disease caused by blood-brain barrier dysfunction

BackgroundBlood-brain barrier (BBB) dysfunction caused by endothelial cell injury is one of the widely accepted pathogenesis of small cerebral vessel disease (CSVD). However, the early microcirculation studies were notably deficient in providing compelling imaging evidence, which has hampered a comprehensive understanding of the pathophysiological processes underlying BBB dysfunction in CSVD. The onset of CSVD is insidious and the clinical manifestations are diverse, diagnosis of CSVD relies primarily on neuroimaging information currently. These MRI imaging features mainly represent the end-stage brain parenchyma injury, rather than the vascular lesion itself. Therefore, clarifying the pathophysiological processes related to cerebral microcirculation in CSVD is of great significance for early treatment intervention of CSVD. MethodsTwenty rats were used to prepare CSVD animal model by ultrasound combined with ultrasonic microbubble contrast agent. MRI, functional ultrasound (fUS) imaging and ultrasound localization microscopy (ULM) were used to evaluate microcirculation changes in acute and chronic models. ResultsCurrently, our research has successfully validated that the imaging characteristics of this model align with the four established criteria outlined in the STRIVE-2 classification. FUS shows increased microflow velocity in the molding area, which can be used for initial evaluation of CSVD models in the acute phase. ULM has revealed a progressive reduction in the density of both the short cortical arteries and the long medullary arteries, along with their respective branches, over time. Concurrently, there has been a noted deviation in blood flow velocity. ConclusionThis model offers compelling evidence at the microvascular level, suggesting that blood-brain barrier (BBB) dysfunction is a central pathophysiological mechanism in the etiology of CSVD. Then it provides a straightforward, efficient, and widely applicable tool and continuous monitoring method for the further investigation of CSVD from the macroscopic to the microscopic circulation level, with significant long-term implications for CSVD diagnosis and treatment.

neuroscience↗

bioRxiv2025

LDL receptor-mediated endocytosis of Escherichia coli α-hemolysin mediates renal epithelial toxicity

Pore-forming toxins (PFTs) are secreted bacterial effector molecules that disrupt host cell membranes. The -hemolysin (HlyA) of uropathogenic Escherichia coli (UPEC) can exert damage to various mammalian cell types. While a candidate toxin receptor (CD11a/CD18 [LFA-1] integrin) exists on myeloid cells, the mechanism of HlyA cytotoxicity to epithelial cells remains undefined. We show that HlyA secretion by UPEC exacerbates renal tubular epithelial injury during ascending pyelonephritis in mice. A CRISPR-Cas9 loss-of-function screen in renal collecting duct cells identified clathrin-mediated endocytosis as required for HlyA cytotoxicity. HlyA internalization induces lysosomal permeabilization, facilitating protease release, cytoplasmic acidification, and mitochondrial dysfunction leading to rapid cell death. This mechanism contrasts with the described actions of other PFTs (plasma membrane poration and osmotic cytolysis). We also identify the low-density lipoprotein receptor (LDLR) as an epithelial receptor for HlyA; genetic or competitive inhibition of the HlyA-LDLR interaction prevented cytotoxicity. Our studies define a new mechanism of action for HlyA, in which its toxicity to epithelial cells requires LDLR-mediated, clathrin-dependent internalization. These results suggest therapeutic avenues for mitigating HlyA-induced damage during E. coli infections.

microbiology↗

bioRxiv2025

CellFateExplorer: An integrated platform for exploring cell fate

Cell fate prediction from single-cell omics data is a central task for reconstructing developmental dynamics and inferring lineage relationships, but existing tools remain fragmented and often tailored to specific trajectory structures. Here we present Cafe (CelluAr Fate Explorer), an integrated platform for cell fate analysis that unifies trajectory-aware data storage, heterogeneous inference methods, benchmarking, visualization, and downstream interpretation. Cafe standardizes diverse inputs into a common milestone-network representation, supports both native and Dynverse-compatible methods, and evaluates performance across representative benchmark criteria. Applied to representative case studies across atlas-scale and lineage-resolved datasets, Cafe recovers coherent developmental trajectories and provides benchmark-guided method selection across data types and biological contexts. A browser-based interface built on cellxgene enables interactive trajectory inspection. Cafe also supports downstream analyses, including driver-gene prioritization and gene-regulatory-network inference. As an open, community-driven platform, Cafe is designed to evolve continuously with contributions from developers and users, expanding method coverage and functionality for cell fate prediction.

cell biology↗

bioRxiv2025

Single-molecule mitochondrial DNA imaging reveals heteroplasmy dynamics shaped by developmental bottlenecks and selection in different organs in vivo

Mitochondrial DNA (mtDNA) occurs in many copies per cell, with cell-to-cell variability in mutation load, known as heteroplasmy. Developmental and age-related expansion of pathogenic mtDNA mutations contributes to mitochondrial and neurodegenerative disease pathogenesis. Here, we describe an approach for in situ sequence-specific detection of single mtDNA molecules (mtDNA-smFISH). We apply this method to visualize and measure in situ mtDNA and heteroplasmy levels at single-cell resolution in whole-mount Drosophila tissue and cultured human cells. In Drosophila, we identify a somatic mtDNA bottleneck during neurogenesis. This amplifies heteroplasmy variability between neurons, as predicted from a mathematical bottleneck model, predisposing individual neurons to a high mutation load and degeneration. However, both during neurogenesis and oogenesis, mtDNA segregation is accompanied by purifying selection, promoting wild-type over mutant mtDNA. mtDNA-smFISH thus elucidates novel mechanisms whereby developmental cell-fate transitions, accompanied by changes in cell morphology, behaviour and metabolism, will shape disease-relevant and tissue-specific transmission and selection of mtDNA mutations.

developmental biology↗

bioRxiv2024

GP-ML-DC: An Ensemble Machine Learning-Based Genomic Prediction Approach with Automated Two-Phase Dimensionality Reduction via Divide-and-Conquer Techniques

Traditional machine learning (ML) and deep learning (DL) methods for genome prediction often face challenges due to the imbalance between the limited number of samples (n) and the large number of single nucleotide polymorphisms (SNPs) (p), where n is much smaller than p. To address this, we propose GP-ML-DC, an innovative genome predictor that combines traditional ML and DL models with a unique two-phase, parameter-free dimensionality reduction technique. Initially, GP-ML-DC reduces feature dimensionality by characterizing genes as features. Building on big data methodologies, it employs a divide-and-conquer approach to segment gene regions into multiple haplotypes, further decreasing dimensionality. Each haplotype segment is processed by a sub-task based on traditional ML, followed by integration via a neural network that synthesizes the results of all sub-tasks. Our experiments, conducted on four cattle milk-related traits using ten-fold cross-validation and independent testing, show that GP-ML-DC significantly surpasses current state-of-the-art genome predictors in prediction performance.

bioinformatics↗

bioRxiv2024

A molecularly defined brain circuit module for regulating the panic-like defensive state

Panic is an episode of strong defensive state, characterized by intense fear and severe physical symptoms such as elevated cardiorespiratory activities. How the brain generates panic state remains poorly understood. Here, we developed a robot-based experimental paradigm to evoke panic-like defensive state in mice. When stimulated by the robot, the mice exhibited jumping escapes and elevated cardiorespiratory activities. With this paradigm, we identified Cbln2-expressing (Cbln2+) neurons in the posterior hypothalamic nucleus (PHN) as a key neuronal population essential for the induction of panic-like defensive state. Activation of Cbln2+ PHN neurons induced behavioral and physical symptoms of panic-like defensive state. These neurons were strongly activated by noxious mechanical stimuli and encode jumping escape vigor. They were synaptically innervated by anxiety-associated brain areas and provoked panic-like defensive state via their projection to the periaqueductal gray. Together, our results reveal a molecularly defined circuit module that regulates the panic-like defensive state in mice.

neuroscience↗

bioRxiv2024

Elovl1 inhibition reduced very long chain fatty acids in a mouse model of adrenoleukodystrophy

Adrenoleukodystrophy (ALD) is a rare neurometabolic disease caused by mutations in the ABCD1 gene, which encodes for the peroxisomal very long chain fatty acid (VLCFAs) transporter. It is a debilitating disorder, which has a spectrum of clinical presentations. The most severe form is a rapidly progressing demyelinating disease called cerebral ALD or CALD. Patients with cALD have a life expectancy of 2-4 years after onset and symptoms often manifest in childhood. The other forms are adrenomyeloneuropathy or AMN, which is a slower progressing degeneration of the spinal cord, and adrenal insufficiency (Addison disease). Since the accumulation of VLCFAs are a common factor in all ALD pathologies, we identified therapeutic approach that could correct this metabolic defect. We developed a substrate reduction therapy (SRT) for ALD in the form of an inhibitor of the lipid elongase principally responsible for the generation of VLCFAs, Elovl1. This small molecule was able to successfully reduce the accumulation of VLCFA in the brain and spinal cord of ABCD1-/y mice. We used single nuclei RNA seq to identify the pathways altered in the ABCD1-/y mouse and corrected with Elovl1 inhibition. Though many lipid metabolism genes and pathways were indeed corrected, treatment with the Elovl1 inhibitor unexpectedly led to profound transcriptional changes beyond correction of pathways altered by loss of ABCD1. These data suggest that Elovl1 inhibition may have broader consequences in ABCD1-/y mice than correction of lipid homeostasis.

pharmacology and toxicology↗