Production of a high-efficiency cellulase complex via β-glucosidase engineering in Penicillium oxalicum

Additional file 6: Table S1. Primers used in this study

Antifungal effects and biocontrol potential of lipopeptide-producing Streptomyces against banana Fusarium wilt fungus Fusarium oxysporum f. sp. cubense

Fusarium wilt of banana (FWB), caused by Fusarium oxysporum f. sp. cubense (Foc), especially tropical race 4 (TR4), presents the foremost menace to the global banana production. Extensive efforts have been made to search for efficient biological control agents for disease management. Our previous study showed that Streptomyces sp. XY006 exhibited a strong inhibitory activity against several phytopathogenic fungi, including F. oxysporum. Here, the corresponding antifungal metabolites were purified and determined to be two cyclic lipopeptide homologs, lipopeptin A and lipopeptin B. Combined treatment with lipopeptin complex antagonized Foc TR4 by inhibiting mycelial growth and conidial sporulation, suppressing the synthesis of ergosterol and fatty acids and lowering the production of fusaric acid. Electron microscopy observation showed that lipopeptide treatment induced a severe disruption of the plasma membrane, leading to cell leakage. Lipopeptin A displayed a more pronounced antifungal activity against Foc TR4 than lipopeptin B. In pot experiments, strain XY006 successfully colonized banana plantlets and suppressed the incidence of FWB, with a biocontrol efficacy of up to 87.7%. Additionally, XY006 fermentation culture application improved plant growth parameters and induced peroxidase activity in treated plantlets, suggesting a possible role in induced resistance. Our findings highlight the potential of strain XY006 as a biological agent for FWB, and further research is needed to enhance its efficacy and mode of action in planta

A Homeodomain-Containing Transcriptional Factor PoHtf1 Regulated the Development and Cellulase Expression in Penicillium oxalicum

Homeodomain-containing transcription factors (Htfs) play important roles in animals, fungi, and plants during some developmental processes. Here, a homeodomain-containing transcription factor PoHtf1 was functionally characterized in the cellulase-producing fungi Penicillium oxalicum 114-2. PoHtf1 was shown to participate in colony growth and conidiation through regulating the expression of its downstream transcription factor BrlA, the key regulator of conidiation in P. oxalicum 114-2. Additionally, PoHtf1 inhibited the expression of the major cellulase genes by coordinated regulation of cellulolytic regulators CreA, AmyR, ClrB, and XlnR. Furthermore, transcriptome analysis showed that PoHtf1 participated in the secondary metabolism including the pathway synthesizing conidial yellow pigment. These data show that PoHtf1 mediates the complex transcriptional-regulatory network cascade between developmental processes and cellulolytic gene expression in P. oxalicum 114-2. Our results should assist the development of strategies for the metabolic engineering of mutants for applications in the enzymatic hydrolysis for biochemical production

Advantage of Combining OBIA and Classifier Ensemble Method for Very High-Resolution Satellite Imagery Classification

Accurate and timely collection of urban land use and land cover information is crucial for many aspects of urban development and environment protection. Very high-resolution (VHR) remote sensing images have made it possible to detect and distinguish detailed information on the ground. While abundant texture information and limited spectral channels of VHR images will lead to the increase of intraclass variance and the decrease of the interclass variance. Substantial studies on pixel-based classification algorithms revealed that there were some limitations on land cover information extraction with VHR remote sensing imagery when applying the conventional pixel-based classifiers. Aiming at evaluating the advantages of classifier ensemble strategies and object-based image analysis (OBIA) method for VHR satellite data classification under complex urban area, we present an approach-integrated multiscale segmentation OBIA and a mature classifier ensemble method named random forest. The framework was tested on Chinese GaoFen-1 (GF-1), and GF-2 VHR remotely sensed data over the central business district (CBD) of Zhengzhou metropolitan. Process flow of the proposed framework including data fusion, multiscale image segmentation, best optimal segmentation scale evaluation, multivariance texture feature extraction, random forest ensemble learning classifier construction, accuracy assessment, and time consumption. Advantages of the proposed framework were compared and discussed with several mature state-of-art machine learning algorithms such as the k-nearest neighbor (KNN), support vector machine (SVM), and decision tree classifier (DTC). Experimental results showed that the OA of the proposed method is up to 99.29% and 98.98% for the GF-1 dataset and GF-2 dataset, respectively. And the OA is increased by 26.89%, 11.79%, 11.89%, and 4.26% compared with the traditional machine learning algorithms such as the decision tree classifier (DTC), support vector machine (SVM), k-nearest neighbor (KNN), and random forest (RF) on the test of the GF-1 dataset; OA increased by 32.31%, 13.48%, 9.77%, and 7.72% for the GF-2 dataset. In terms of time consuming, by rough statistic, OBIA-RF spends 223.55 s, SVM spends 403.57 s, KNN spends 86.93 s, and DT spends 0.61 s on average of the GF-1 and GF-2 datasets. Taking the account classification accuracy and running time, the proposed method has good ability of generalization and robustness for complex urban surface classification with high-resolution remotely sensed data

Fe-MnO2 nanosheets loading dihydroartemisinin for ferroptosis and immunotherapy

Ferroptosis has emerged as a therapeutic tactic to trigger cancer cell death driven by abnormal accumulation of reactive oxygen species (ROS). However, a single ferroptosis treatment modality is often limited. In this work, a combination therapy of ferroptosis and immunotherapy for cancer was proposed. Specifically, a versatile nanodrug was designed for the multiple treatment of hepatocellular carcinoma (HCC) by loading dihydroartemisinin (DHA) on Fe3+-doped MnO2 nanosheets (Fe-MnO2/DHA). Firstly, Fe-MnO2/DHA was degraded by glutathione (GSH) in the tumor microenvironment (TME) to release Fe2+, Mn2+ and DHA, leading to aberrant ROS accumulation due to Fenton/Fenton-like reaction. Secondly, breakage of endoperoxide bridge from DHA was caused by Fe2+ to further induce oxidative stress. Thirdly, the depleted GSH promoted the inactivation of glutathione peroxidase 4 (GPX4), resulting in lipid peroxide (LPO) accumulation. The resulting LPO and ROS could induce ferroptosis and apoptosis of liver cancer cells. Furthermore, Fe-MnO2/DHA mediated three-pronged stimulation of oxidative stress, resulting in high levels of targeted immunogenic cell death (ICD). It could enhance the infiltration of CD4+ T and CD8+ T cells, and promote macrophage polarization. DHA also acted as an immunomodulator to inhibit regulatory T cells (Tregs) for systemic antitumor. Overall, Fe-MnO2/DHA presents a multi-modal therapy for HCC driven by ferroptosis, apoptosis and immune activation, significantly advancing synergistic cancer treatment

Transcriptome Analysis and Genome-Wide Gene Family Identification Enhance Insights into Bacterial Wilt Resistance in Tobacco

Bacterial wilt, caused by the Ralstonia solanacearum species complex, is one of the most damaging bacterial diseases in tobacco and other Solanaceae crops. In this study, we conducted an analysis and comparison of transcriptome landscape changes in seedling roots of three tobacco BC4F5 lines, C244, C010, and C035, with different resistance to bacterial wilt at 3, 9, 24, and 48 h after R. solanacearum infection. A number of biological processes were highlighted for their differential enrichment between C244, C010, and C035, especially those associated with cell wall development, protein quality control, and stress response. Hence, we performed a genome-wide identification of seven cell wall development-related gene families and six heat shock protein (Hsp) families and proposed that genes induced by R. solanacearum and showing distinct expression patterns in C244, C010, and C035 could serve as a potential gene resource for enhancing bacterial wilt resistance. Additionally, a comparative transcriptome analysis of R. solanacearum-inoculated root samples from C244 and C035, as well as C010 and C035, resulted in the identification of a further 33 candidate genes, of which Nitab4.5_0007488g0040, a member of the pathogenesis-related protein 1 (PR-1) family, was found to positively regulate bacterial wilt resistance, supported by real-time quantitative PCR (qRT-PCR) and virus-induced gene silencing (VIGS) assays. Our results contribute to a better understanding of molecular mechanisms underlying bacterial wilt resistance and provide novel alternative genes for resistance improvement