Sheng wu gong cheng xue bao = Chinese journal of biotechnology最新文献

Steroids, a group of diverse plant-derived natural products, exhibit not only essential physiological roles but also significant pharmacological activities, including anti-tumor, anti-viral, antibacterial, anti-inflammatory, blood glucose- and lipid-lowering, hepatoprotective, and immunomodulatory properties. The cytochrome P450 monooxygenase (CYP450) superfamily constitutes a class of heme-containing enzymes capable of catalyzing remarkably regiospecific and stereospecific oxidative reactions. CYP450s serve as pivotal catalysts for structural modifications of steroids in plants. This review comprehensively summarizes the functionally characterized CYP450 proteins that participate in plant steroid biosynthesis, which encompasses backbone formation (C-14 demethylation and side chain degradation) and structural modifications of both steroid skeleton and side chains. Focusing on distinct structural features of steroid skeletons and side chains, we highlight recent advances in CYP450-mediated biosynthetic pathways of Δ²²-sterols, brassinosteroids, cholesterol derivatives, and withanolides, with a particular emphasis on the impacts of oxidative modifications on the bioactivity and functionality of steroids. Furthermore, we discuss prospective research directions for CYP450s in plant steroid biosynthesis, aiming to provide a comprehensive and up-to-date overview of CYP450s involved in plant steroid metabolism. This review is intended to give novel insights for deciphering additional steroid biosynthetic pathways and advancing their biotechnological applications.

In recent years, potato scab caused by Streptomyces scabies is aggravating year by year, becoming an industrial problem urgently to be resolved. Screening antagonistic bacteria with good inhibitory effect and wide adaptability is the main measure to realize effective prevention and control of the disease. This study screened three strains of antagonistic bacteria DXT2-4, T2-1 and 21-14 with good inhibitory effect on S. scabies by using plate standoff test, and identified them as Bacillus altitudinis, Bacillus safensis and Bacillus pumilus, respectively, based on morphological characteristics, physiological and biochemical properties, and 16S rRNA gene sequences. DXT2-4, T2-1 and 21-14 showed the pot control efficacy of 68.83%, 48.57%, and 57.14%, respectively. The field control efficacy of the three strains was 59.48%, 34.58% and 51.75% in Hulun Buir, Inner Mongolia Autonomous Region and 55.14%, 36.05%, and 49.05% in Huizhou, Guangdong. The three strains could grow normally in the media with pH 1.0-13.0 and with 1%-11% NaCl, and they had inhibitory effects on Rhizoctonia solani, Verticillium dahliae, Alternaria solani, and Fusarium oxysporum. The indole-3-acetic acid yields of DXT2-4, T2-1, and 21-14 were 2.23, 1.11, and 1.67 mg/L, respectively. DXT2-4 and 21-14 demonstrated strong abilities to solubilize phosphorus. The optimal carbon source, nitrogen source, and inorganic salt for fermentation of strain DXT2-4 were 2% molasses+2% corn starch, 2% soybean meal, and 0.3% MgSO₄·7H₂O, respectively. These findings suggest the three strains of bacteria can efficiently inhibit the growth of S. scabies and have strong environmental adaptability. Particularly, DXT2-4 has the best effects of inhibiting the disease and promoting plant growth, showing a high development value and broad application prospects, this is of great significance for promoting sustainable potato production and ensuring the environmentally sound utilization of resources.

Agriculture, the strategic cornerstone of national long-term stability, is undergoing a fundamental shift from resource-dependent to technology-driven, driven by global food security and ecological conservation needs. Traditional agriculture can no longer sustain the growing food demand. Scientific and technological advancements are fundamental guarantees for ensuring food supply security and are the primary driver for future agricultural development. This special issue compiles the latest research advancements from diverse experts, covering fields such as microbe-driven green agriculture, pesticide technology innovation, intelligent agricultural machinery, smart manufacturing, and molecular design breeding fundamentals. It aims to inspire researchers to explore cutting-edge directions in future agriculture, promote interdisciplinary collaboration and technological integration, and thereby drive innovative breakthroughs and industrial transformation in agricultural modernization.

This study optimizes the extraction process and explores the antioxidant activity of Gastrodia elata polysaccharides, aiming to provide theoretical reference for the extraction, development, and application of the polysaccharides. Polysaccharides were extracted from G. elata by an ultrasonic-assisted method with deep eutectic solvents. The extraction process was optimized by single factor and response surface tests. The antioxidant activity of polysaccharides was evaluated by DPPH and ABTS⁺ free radical scavenging rates. The optimal deep eutectic solvents were composed of choline chloride and lactic acid at a molar ratio of 1:2. The optimal extraction conditions were the ultrasonic treatment at 50 ℃ for 48 min, a solid-to-liquid ratio of 1:38, and a water content of 42%. Under these conditions, the polysaccharide yield reached (19.88±0.93)%. The results of antioxidant activity experiment in vitro showed that the scavenging rates of G. elata polysaccharides on DPPH and ABTS⁺ free radicals were up to (26.39±1.47)% and (30.61±0.16)%, respectively, which indicated that the polysaccharides extracted by the deep eutectic solvents had a certain antioxidant ability. The extracted polysaccharides can be further studied and developed as a potential natural antioxidant.

Accurately obtaining the crop quantity and density is not only crucial for the demand-based input of water and fertilizer in the field but also vital for ensuring the yield and quality of crops. Aerial photography by unmanned aerial vehicles (UAVs) can quickly acquire the distribution image information of crops over a large area. However, the accurate recognition of a single type of dense targets is a huge challenge for most recognition algorithms. Taking banana seedlings as an example in this study, we captured the images of banana plantations by UAVs from high altitudes to explore an efficient recognition method for dense targets. We proposed a strategy of "cut-recognition-stitch" and constructed a counting method based on the improved Faster R-CNN algorithm. First, the images containing highly dense targets were cropped into a large number of image tiles according to different sizes (simulating different flight altitudes), and the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm was adopted to improve the image quality. A banana seedling dataset containing 36 000 image tiles was constructed. Then, the Faster R-CNN network with optimized parameters was used to train the banana seedling recognition model. Finally, the recognition results were reversely stitched together, and a boundary deduplication algorithm was designed to correct the final counting results to reduce the repeated recognition caused by image cropping. The results show that the recognition accuracy of the Faster R-CNN with optimized parameters for banana image datasets of different sizes can reach up to 0.99 at most. The deduplication algorithm can reduce the average counting error for the original aerial images from 1.60% to 0.60%, and the average counting accuracy of banana seedlings reaches 99.4%. The proposed method effectively addresses the challenge of recognizing dense small objects in high-resolution aerial images, providing an efficient and reliable technical solution for intelligent crop density monitoring in precision agriculture.

Genetically modified (GM) crops, as a pivotal innovation in modern agriculture, exhibit significant advantages such as pest and disease resistance, herbicide tolerance, stress tolerance, and yield enhancement. However, their widespread adoption has been associated with potential ecological risks, including weediness of transgenic plants, gene flow, emergence of novel viral strains in virus-resistant crops, impacts on non-target organisms and soil ecosystems, and evolution of target pest resistance. This review focuses on the dual characteristics of GM crops, systematically examining their agronomic benefits and the underlying mechanisms of ecological risks. This review provides a theoretical foundation for optimizing the development of GM crops and ecological risk management, facilitating sustainable agricultural practices.

Geminiviruses cause substantial crop yield losses worldwide. The replication initiator protein (Rep) encoded by geminiviruses is indispensable for geminiviral replication. The Rep protein encoded by beet severe curly top virus (BSCTV, genus Curtovirus, family Geminiviridae) induces VARIANT IN METHYLATION 5 (VIM5) expression in Arabidopsis leaves upon BSCTV infection. VIM5 functions as a ubiquitination-related E3 ligase to promote the proteasomal degradation of methyltransferases, resulting in reduction of methylation levels in the BSCTV C2-3 promoter. However, the specific domains of Rep responsible for VIM5 induction remain poorly characterized. Although Rep proteins from several geminiviruses act as viral suppressors of RNA silencing (VSRs), whether BSCTV Rep also possesses VSR activity remains to be illustrated. In this study, we employed a transient expression system in the 16c-GFP transgenic and the wild-type Nicotiana benthamiana plants to analyze the VSR and the VIM5-inducing activities of different truncated Rep proteins haboring distinct domains. We found that the N-terminal domain (amino acids 1-180) of Rep suppressed GFP silencing in 16c-GFP transgenic N. benthamiana leaves. The minimal N-terminal fragment (amino acids 1-104) induced VIM5 expression upon co-infiltration, while C-terminal truncations lacked VIM5-inducing activity. Our results indicate that the N-terminal domain of Rep encoded by BSCTV mediates the suppression of RNA silencing and induces VIM5 expression. Thus, our findings contribute to a better understanding of interactions between geminiviral Rep and plant hosts.

Fusarium head blight (FHB), caused by Fusarium graminearum, not only leads to severe yield losses but also poses a threat to food safety due to the mycotoxins produced by the pathogen. Since this disease is preventable but not curable, the current control mainly relies on chemical fungicides, the long-term use of which may lead to pathogen resistance and environmental pollution. To develop green control methods, we screened 13 biocontrol strains from the rhizosphere soil of wheat, among which strain No. 12 (identified as Pythium aphanidermatum) showed significant antifungal effects. In the plate confrontation test, this strain reduced the colony diameter of the pathogen by 69.2% (1.47 mm vs. 4.78 mm in the control group), with an inhibition rate of 77% (P < 0.01). Microscopic observation revealed obvious deformations in the pathogen hyphae, suggesting a lysing effect. The coleoptile experiment further confirmed that the pre-treatment with this strain reduced the incidence rate to 0. These findings provide new candidate strains for the biocontrol of FHB and offer a scientific basis for reducing the use of chemical fungicides and promoting sustainable agricultural development.

Small RNAs (sRNAs), the key components of RNA interference (RNAi) or RNA silencing, can mediate cell-autonomous gene silencing and function as signaling molecules across species. Microbe-induced gene silencing (MIGS), which is based on interspecies RNAi, is an effective approach for controlling fungal diseases in crops. The enolase gene VdEno is essential for the growth and development of the fungal pathogen Verticillium dahliae, which causes cotton Verticillium wilt. In this study, we engineered Trichoderma harzianum (Th) to express the double-stranded RNA (dsRNA) targeting VdEno. The engineered strain Th-VdEnoi successfully generated VdEno-specific small interfering RNA (siVdEno). We further confirmed that Th-VdEnoi effectively induced VdEno silencing at the translational level. The results of crop protection assays revealed that the cotton plants co-inoculated with V. dahliae (strain V592) and Th-VdEnoi presented significantly reduced disease severity and lower fungal biomass in their roots than the control plants inoculated with V. dahliae alone or with V. dahliae and Th-GFPi (a control strain expressing GFP-targeting dsRNA). Collectively, our findings demonstrate that VdEno is an effective target for controlling cotton Verticillium wilt and confirm that MIGS is a promising strategy for managing soil-borne fungal pathogens in crops. MIGS provides strong technical support for reducing the application of conventional chemical pesticides, developing eco-friendly biopesticides, and facilitating the sustainable development of agriculture.

To explore the feasibility of using UAV-LiDAR for measuring the leaf area index (LAI) of crop canopies, we employed UAV-LiDAR to scan sugarcane canopies during the tillering and elongation stages, acquiring canopy point cloud data. Subsequently, features such as average row height, projected row area, point cloud density at different canopy layers, and the ratios between these parameters were extracted. Three feature selection methods-partial least squares regression (PLSR), XGBoost feature importance (XGBoost-FI), and random forest-recursive feature elimination (RF-RFE)-were adopted to evaluate and identify the optimal input variables for modeling. With these selected variables, LAI inversion models were developed based on random forest (RF) and adaptive boosting (AdaBoost) algorithms, and their performance was assessed. Among the extracted features, the projected row area S_p and the total row point count C_total exhibited strong correlations with LAI, with correlation coefficients of 0.73 and 0.72, respectively. The AdaBoost-based LAI inversion model, using the projected row area S_p, average height H_avg, mid-layer point cloud density C_m, and total row point count C_total as input variables, achieved the best performance, with a coefficient of determination (R_v²) of 0.713 and a root mean square error (RMSE_v) of 0.25 on the validation set. This study provides an effective method for high-throughput acquisition of LAI in field crops, offering valuable scientific support for sugarcane field management and breeding efforts.