Genome Sequencing and Comparative Transcriptomic Analysis of Rice Brown Spot Pathogen Bipolaris oryzae Adaptation to Osmotic StressWang, Yang, Jibril
et alJ Fungi (Basel) (2025) 11 (3)
Abstract: Rice brown spot disease, caused by Bipolaris oryzae, is a significant fungal disease that poses a major threat to global rice production. Despite its widespread impact, genomic studies of B. oryzae remain limited, particularly those involving high-quality genomic data. In this study, we performed whole-genome sequencing of the B. oryzae strain RBD1, which was isolated from the demonstration field for upland rice cultivation in Haozhiba Village, Lancang County, Pu'er City, Yunnan Province, China, using a combination of second-generation Illumina sequencing and third-generation Single-Molecule Real-Time (SMRT) sequencing. The assembled genome was 37.5 Mb in size with a G + C content of 49.39%, containing 42 contigs with a contig N50 of 2.0 Mb. Genomic analysis identified genes related to carbon, nitrogen, and lipid metabolism, highlighting the strain's metabolic flexibility under diverse environmental conditions and host interactions. Additionally, we identified pathogenicity-related genes involved in MAPK signaling, G protein signaling, and oxidative stress responses. Under 1.2 M sorbitol-induced osmotic stress, we observed significant differences in growth responses between RBD1 and the rice blast fungus Magnaporthe oryzae H7. Transcriptomic analysis using Illumina sequencing revealed that RBD1 responds to osmotic stress by enhancing carbohydrate metabolism, fatty acid degradation, and amino acid synthesis, while H7 primarily relies on protein synthesis to enhance growth tolerance. This study provides a valuable foundation for understanding the pathogenic mechanisms of rice brown spot and future disease control strategies.
Fungal Stress Responses and the Importance of GPCRsLara-Martínez, Tristán-Flores, Cervantes-Montelongo
et alJ Fungi (Basel) (2025) 11 (3)
Abstract: G-protein-coupled receptors (GPCRs) play a crucial role in the gene regulation of processes related to the response to different types of stress in fungi. These receptors act as sensors of extracellular signals and transmit the information to the interior of the cell through G-proteins. In the presence of different and specific types of stresses, GPCRs activate signaling cascades that culminate in the activation of transcription factors, which regulate the expression of genes associated with the stress response, including those induced by changes in environmental pH. GPCR-mediated gene regulation allows fungi to adapt to adverse conditions such as osmotic, thermal, oxidative, or nutritional stress, as well as fluctuations in environmental pH. This review focuses on the understanding of how GPCRs modulate the stress response in fungi and their crucial role in advancing our knowledge of the physiology and adaptability of these microorganisms in their changing environment.
The Purification and Characterization of a Novel Neutral Protease from Volvariella volvacea Fruiting Bodies and the Enzymatic Digestion of Soybean IsolatesXu, Li, Guo
et alJ Fungi (Basel) (2025) 11 (3)
Abstract: A novel protease was isolated from the fruiting bodies of the straw mushroom Volvariella volvacea. The protease was purified 13.48-fold using a series of techniques, including ammonium sulfate precipitation, ultrafiltration, diethylaminoethyl fast-flow (DEAE FF) ion-exchange chromatography, and Superdex 75 gel filtration chromatography, resulting in a specific enzyme activity of 286.82 U/mg toward casein as a substrate. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis revealed that the purified protease had a molecular weight of 24 kDa. The enzyme exhibited optimal activity at pH 7 and 50 °C, showing sensitivity to alkaline conditions and instability at elevated temperatures. The presence of Ca2+ significantly enhanced enzyme activity, whereas Ni2+ and Cu2+ exerted strong inhibitory effects, with other metal ions showing weak inhibition. β-mercaptoethanol, Tween-80, and Triton X-100 had more pronounced inhibitory effects, whereas PMSF, EDTA, and CTAB had weaker inhibitory effects. The Michaelis constant (Km) and maximum velocity (Vm) of the protease were determined to be 1.34 g/L and 3.45 μg/(mL·min), respectively. The protease exhibited a greater degree of enzymatic degradation of soybean-isolate protein (7.58%) compared to trypsin (5.24%), with the enzyme product containing a high percentage of medicinal amino acids (73.54%), particularly phenylalanine (Phe) and arginine (Arg), suggesting their presence at the enzyme's active site. These findings suggest that the protease from V. volvacea holds promising potential for applications in the food industry, particularly in protein hydrolysate production and flavor enhancement.
Targeted Detection of 76 Carnitine Indicators Combined with a Machine Learning Algorithm Based on HPLC-MS/MS in the Diagnosis of Rheumatoid ArthritisZhang, Wang, Zhai
et alMetabolites (2025) 15 (3)
Abstract: Early diagnosis and treatment of rheumatoid arthritis (RA) are essential to reducing disability. However, the diagnostic criteria remain unclear, relying on clinical symptoms and blood markers.Using high-performance liquid chromatography-mass spectrometry (HPLC-MS/MS) targeted detection, we evaluated 76 carnitine indicators (55 carnitines and 21 corresponding ratios) in the serum of patients with RA to investigate the role of carnitine in RA. A total of 359 patients (207 patients with RA and 152 healthy controls) were included in the study. Screening involved three methods and integrated 76 carnitine indicators and 128 clinical indicators to identify candidate markers to establish a theoretical basis for RA diagnosis and new therapeutic targets. The diagnostic model derived from the screened markers was validated using three machine learning algorithms.The model was refined using eight candidate indicators (C0, C10:1, LYMPH, platelet distribution width, anti-keratin antibody, glucose, urobilinogen, and erythrocyte sedimentation rate (ESR)). The receiver operating characteristic curve, sensitivity, specificity, and accuracy of the V8 model obtained from the training set were >0.948, 79.46%, 92.99%, and 89.18%, whereas those of the test set were >0.925, 78.89%, 89.22%, and 85.87%, respectively. Twenty-four carnitines were identified as risk factors of RA, with three significantly correlating with ESR, four with anti-cyclic citrullinated peptide antibody activity, two with C-reactive protein, five with immunoglobulin-G, eight with immunoglobulin-A levels, and eleven with immunoglobulin-M levels.Carnitine is integral in the progression of RA. The diagnostic model developed shows excellent diagnostic capacity, improving early detection and enabling timely intervention to minimize disability associated with RA.
膜杰作
Star Staining
