Biomedical subjects

Hao Wu

Publications and source records attributed to Hao Wu.

8 recordsLinked to original sources

PubMed2026

Loss of Ku70 promotes mononucleate conidiation and homologous recombination in Phanerochaete chrysosporium.

Lignin is a major constituent of lignocellulose and the most abundant aromatic biopolymer on earth. It provides plants with rigidity and protection, but its recalcitrant nature also presents a significant barrier to lignocellulose valorization. The white-rot fungus Phanerochaete chrysosporium is among nature's most efficient lignin degraders, and its ligninolytic capabilities have been subjected to intensive investigations. Genome editing with precision is crucial for elucidating the in vivo mechanisms of its ligninolytic actions, but genetic manipulations of P. chrysosporium are often plagued by imprecision. This technical nuisance is driven primarily by canonical non-homologous end joining (c-NHEJ), a DNA repair system that requires little homology and depends on the binding of the Ku70/Ku80 heterodimer to double-strand break (DSB) ends. Loss of Ku70 or Ku80 abolishes c-NHEJ and significantly improves genome editing precision in many filamentous fungi, but it has yet to be examined and exploited in P. chrysosporium. Here, we constructed a homozygous ku70Δ mutant in a meiotic homokaryon of clear genetic background. Loss of Ku70 minimally impacts growth but significantly increases homologous recombination frequency from ~2% to ~66%, with ~32% of the latter being homozygous. Unexpectedly, loss of Ku70 also promotes mononucleate conidiation, which may facilitate isolation of homozygous mutants. Taken together, our work provides a valuable genetic tool to understand and exploit P. chrysosporium's remarkable ligninolytic capabilities.IMPORTANCEGenome editing with precision is essential to unraveling the intricacies of P. chrysosporium's exceptional ligninolytic capabilities, but the available tools are generally imprecise due to the dominance of non-homologous recombination, a problem that is further exacerbated by the discontinuation of Novozyme 234. We tackle these challenges by reestablishing protoplast-based transformation with Lywallzyme as an alternative. Importantly, we demonstrate that inactivation of c-NHEJ by deleting ku70 significantly increases gene knockout efficiency and report the unexpected involvement of c-NHEJ in regulating the number of nuclei during conidiation. Our work paves the way for future ventures into understanding ligninolysis in P. chrysosporium and building superior chassis for industrial applications.

Ku70↗

PubMed2026

Functional chimeric mRNAs encode proteins in mammalian immunity.

Individual mammalian mRNAs and proteins are typically believed to originate from single genomic loci, with isoform diversity arising through cis-splicing of pre-mRNA. Whether mRNA from distant genes can undergo trans-splicing to generate functionally relevant chimeric transcripts has remained unclear. Here we develop a pipeline combining long-read direct RNA sequencing with non-targeted and targeted validation to identify chimeric transcripts in macrophages. Chromatin conformation capture studies reveal that inflammation induces interchromosomal DNA interactions, positioning parent genes proximally to facilitate the formation of chimeric mRNA. Notably, we identify a protein-coding chimeric mRNA representing a fusion between the pore-forming protein gasdermin D (GSDMD)1,2 and a C-terminal domain translated out of frame from Tmem106a (Gsdmd-Tmem106a) in mice. We show that inflammasome priming upregulates Gsdmd-Tmem106a, with the protein localizing to the plasma membrane. After activation of the inflammasome, GSDMD-TMEM106A directly interacts with canonical GSDMD N termini to accelerate and enhance pore formation and IL-1β release. Finally, we show that GSDMD-TMEM106A balances host defence and immunopathology in vivo: its loss protects against lethal sepsis but compromises antibacterial defence, whereas overexpression enhances host protection while increasing sepsis lethality. We establish that protein-coding chimeric mRNAs formed by regulated transcript fusion events are operative during inflammation and immunity.

Journal Article↗

PubMed2026

Spatial mapping of RNA turnover kinetics in the mouse brain.

Gene regulation requires coordinated control of RNA synthesis and degradation, yet measuring RNA turnover across intact tissues remains challenging. Here we present spatial NT-seq, a method that combines transgenesis-free metabolic RNA labeling with in situ chemical recoding on spatial transcriptomics platforms to co-map newly synthesized and pre-existing RNAs. Applying spatial NT-seq to the mouse brain reveals pronounced regional heterogeneity in RNA turnover and identifies the dentate gyrus as a spatial hotspot marked by coordinated upregulation of basal RNA synthesis and decay. Moreover, spatial NT-seq uncovers rapid, brain region-specific transcriptional and post-transcriptional responses to electroconvulsive stimulation, a clinically relevant treatment for refractory depression. Finally, we leverage computational modeling to identify sequence features and post-transcriptional regulators that shape transcriptome-wide mRNA stability across spatial and cellular contexts in the mouse brain. Together, this integrated 'in vivo timescope' framework provides a spatially resolved view of RNA turnover kinetics and reveals the regulatory architecture of RNA stability in vivo.

Journal Article↗

PubMed2026

Phytolacca acinosa Roxb. induces intestinal toxicity through the histamine-MLCK-tight junction axis: Integrated evidence from proteomics, metabolomics, intestinal organoids and epithelial barrier validation.

Phytolacca acinosa Roxb. (PR) is a saponin-rich medicinal plant associated with gastrointestinal toxicity, but the mechanisms underlying PR-induced intestinal barrier injury remain unclear. In this study, raw PR extract was analytically characterized by UPLC-ZenoTOF-MS/MS, confirming triterpenoid saponins as the predominant constituents. C57BL/6 J mice were orally exposed to characterized PR extract (1.20 or 12.0 g/kg for 5 h), and Caco-2 cells and mouse intestinal organoids were used to assess epithelial toxicity and barrier disruption. Histopathology, ELISA, FITC-dextran permeability assays, immunofluorescence, CCK-8, LDH release, western blotting, DIA-based proteomics and untargeted metabolomics were integrated to define toxicological mechanisms. PR induced dose-dependent intestinal inflammation and barrier dysfunction, with the ileum as the most sensitive target. PR increased serum DAO and D-lactate and intestinal TNF-α and IL-1β, disrupted organoid morphology, enhanced epithelial permeability, and reduced ZO-1 expression. Proteomics revealed changes in inflammatory, lipid-metabolic, cytoskeletal and tight-junction pathways, including upregulation of MLCK3 and phospholipase-related proteins and downregulation of ZO-1 and ZO-2. Metabolomics identified histidine metabolism disturbance and histamine accumulation. Integrated multi-omics and pharmacological validation indicated that histamine activated the PLC/IP₃/Ca²⁺/CaM/MLCK cascade, promoting MLC phosphorylation, tight-junction disassembly and epithelial leakiness. MLCK inhibition partially restored ZO-1/ZO-2 expression and attenuated PR-induced epithelial injury. These findings identify the histamine-MLCK-tight junction axis as a key mechanism of PR-induced intestinal toxicity and support hazard identification of saponin-rich PR exposure.

Animals↗

PubMed2026

Genomic analysis of regulatory mechanisms governing EPS66A biosynthesis in Streptomyces changanensis HL-66.

Streptomyces changanensis HL-66 produces the α-(1,4)/(1,6)-glucan exopolysaccharide EPS66A, a potent plant immune elicitor with promising applications in plant protection. However, its low native fermentation yield limits large-scale application. To investigate the biosynthetic potential and regulatory mechanisms underlying EPS66A production, the whole genome of HL-66 was sequenced and analyzed. The HL-66 genome is 6.82 Mb in size, with a GC content of 74%, and encodes 6081 predicted functional genes. Among these, 1390 genes were annotated to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, 4187 were assigned to Gene Ontology (GO) terms, and 143 were classified into Clusters of Orthologous Groups (COG) categories. antiSMASH analysis identified 22 secondary metabolite biosynthetic gene clusters, including multiple polyketide synthase (PKS) and nonribosomal peptide synthetase (NRPS) clusters. Functional analyses revealed that the glycosyltransferase gene (GTy) and the global regulatory gene (bldD) are involved in EPS66A biosynthesis. bldD is involved in morphological development and EPS66A production, whereas GTy specifically regulates EPS66A production without affecting growth or development. In both in vivo and potted-plant experiments, EPS66A (200 μg/mL) significantly reduced the severity of tobacco mosaic virus, apple anthracnose leaf spot, walnut bacterial leaf spot, and jujube anthracnose, achieving control efficacies of 90.21%, 87.95%, 77.41%, and 68.55%, respectively, and outperforming a commercial chitosan oligosaccharide control. These findings provide new insights into the genetic architecture and regulatory mechanisms of EPS66A biosynthesis and support its development as a polysaccharide-based green pesticide.

Streptomyces↗

PubMed2026

A genome-wide cross-trait analysis characterizes the shared genetic architecture between rheumatoid arthritis and psychiatric disorders.

OBJECTIVES: Patients with RA have a 2- to 3-fold elevated risk of psychiatric disorders, suggesting an underlying genetic link between these phenotypes. However, the shared genetic architectures and pathological mechanisms driving RA-psychiatric disorder comorbidity remain to be fully elucidated. Herein, we performed cross-trait analysis to investigate the shared genetic architecture between RA and psychiatric disorders. METHODS: Leveraging European-ancestry genome-wide association studies (GWASs) datasets of RA (n = 1 026 690) and 10 major psychiatric disorders (n = 14 307-1 222 882), we performed cross-trait pleiotropic analysis to identify the shared pleiotropic loci and genes between RA and psychiatric disorders, followed by functional annotation and Mendelian randomization analysis to explore the pathological mechanisms underlying RA-psychiatric disorder comorbidity. RESULTS: Our analysis revealed significant positive genetic correlations between RA and seven psychiatric disorders, such as major depressive disorder. From these correlations, we identified 61 pleiotropic loci jointly influencing RA and psychiatric disorder risk, along with 208 pleiotropic genes predominantly involved in immune and inflammatory response biological processes. Druggable target exploration identified 21 drug-gene interactions involving pleiotropic genes, with two genes (RHOA and TRAF3) classified in the clinically actionable category, representing potential therapeutic targets for both RA and psychiatric disorders. Mendelian randomization further demonstrated a bidirectional causal relationship between RA and schizophrenia, while supporting the causal roles of attention-deficit/hyperactivity disorder, major depressive disorder and post-traumatic stress disorder in increasing RA risk. CONCLUSION: Our findings elucidate the shared genetic architecture between RA and psychiatric disorders, providing novel insights into the pathological mechanisms underlying their comorbidity and laying the groundwork for improved comorbidity management.

Arthritis, Rheumatoid↗

PubMed2025

SIGEL: a context-aware genomic representation learning framework for spatial genomics analysis.

Spatial transcriptomics (ST) integrates spatial information into genomics, yet methods for generating spatially-informed gene representations are limited and computationally intensive. We present SIGEL, a cost-effective framework that derives gene manifolds from ST data by exploiting spatial genomic context. The resulting SIGEL-generated gene representations (SGRs) are context-aware, biologically meaningful, and robust across samples, making them highly effective for key downstream tasks, including imputing missing genes, detecting spatial expression patterns, identifying disease-related genes and interactions, and improving spatial clustering. Extensive experiments across diverse ST datasets validate SIGEL's effectiveness and highlight its potential in advancing spatial genomics research.

Genomics↗

PubMed2025

Accurate prediction of toxicity peptide and its function using multi-view tensor learning and latent semantic learning framework.

MOTIVATION: Therapeutic peptide is an important ingredient in the treatment of various diseases and drug discovery. The toxicity of peptides is one of the major challenges in peptide drug therapy. With the abundance of therapeutic peptides generated in the post-genomics era, it is a challenge to promptly identify toxicity peptides using computational methods. Although several efforts have been made, few algorithms are designed to identify whether a query peptide exhibits toxicity. Considering the varied levels of biological activities, the toxicity peptides should be further classified into multi-functional peptides. RESULTS: This study introduces a two-level predictor, ToxPre-2L, developed using the multi-view tensor learning and latent semantic learning framework. The proposed method utilized multi-label learning with feature induced labels to avoid the redundancy of information from each view. Then the multi-view tensor learning was employed to establish the latent semantic information among different views, while low-rank constraint learning was leveraged to exploit the correlation information among multi-labels. Finally, we constructed an updated toxicity peptide benchmark dataset to assess the effectiveness of the proposed method. Experimental results demonstrated that ToxPre-2L achieves a better performance than alternative computational methods in the prediction of toxicity peptides and their multi-functional types. AVAILABILITY AND IMPLEMENTATION: The source code and data of ToxPre-2L can be accessed at http://bliulab.net/ToxPre-2L.

Peptides↗