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[学术文献 ] Impact of pest-induced Burkholderia inoculation on tea seedings: Integrated rhizosphere microbiome, transcriptome and metabolome profiling 进入全文
Industrial Crops and Products 期刊
This study explored the effects of single strain (S1) and mixed strain (S9) Burkholderia inoculations on rhizobacterial communities, and the transcriptomic and metabolic profiles of tea seedlings, aiming to clarify their roles in plant-microbe interactions. Inoculation with S9 enhanced Burkholderia colonization (4.7 % vs. S1:2.3 %) but reduced rhizobacterial diversity and network complexity, whereas S1 increased bacterial richness and community complexity; both treatments significantly altered bacterial community composition, with S1 upregulating 13 genera (e.g., Bacillus, Streptomyces) and S9 downregulating 18 genera. Furthermore, FAPROTAX functional prediction analysis indicated that both the S1 and S9 treatments promoted soil nitrogen cycling functions, specifically nitrogen fixation and ureolysis. Transcriptomic profiling revealed that both treatments significantly altered gene expression patterns in tea seedling roots and leaves, with roots prioritizing amino acid synthesis and metabolism, while leaves emphasized the synthesis of defensive secondary metabolites. Metabolomic profiling identified 731 metabolites in tea leaves, with S1 exhibiting greater metabolic reprogramming than S9, highlighting 27 key compounds significantly altered by the inoculations. The results collectively underscore the potential of Burkholderia, both singly and in combination, to promote beneficial microbial associations and enhance the metabolic capabilities of tea seedlings, with implications for sustainable agricultural practices.
[会议论文 ] Transcriptomic and Phytochemical Analyses Reveal Root-Mediated Resource-Based Defense Response to Leaf Herbivory by Ectropis oblique in Tea Plant (Camellia sinensis) 进入全文
ACS 会议
Leaf herbivory on tea plants (Camellia sinensis) by tea geometrids (Ectropis oblique) severely threaten the yield and quality of tea. In previous work, we found that local defense response was induced in damaged leaves by geometrids at the transcriptome level. Here, we investigated the systemic response triggered in undamaged roots and the potential role of roots in response to leaf herbivory. Comparative transcriptome analysis and carbohydrate dynamics indicated that leaf herbivory activated systemic carbon reallocation to enhance resource investment for local secondary metabolism. The crucial role of jasmonic acid and the involvement of other potential hormone signals for local and systemic signaling networks were supported by phytohormone quantification and dynamic expression analysis of phytohormone-related genes. This work represents a deep understanding of the interaction of tea plants and geometrids from the perspective of systems biology and reveals that tea plants have evolved an intricate root-mediated resource-based resistance strategy to cope with geometrid attack.
[学术文献 ] Transgenic torenia plant emitting 1,8-cineole from petals repels thrips 进入全文
In Vitro Cellular & Developmental Biology - Plant 期刊
To create an ornamental plant that repels pests, transgenic torenia (Torenia fournieri Lind.) plants were generated expressing the 1,8-cineole synthase (CINS) from lavandin (Lavandula × intermedia Emeric ex Loisel.) under the control of the petal-specific MYB1 promoter of morning glory (Ipomoea nil L.). All the regenerated transgenic plants showed CINS expression in petals but did not show morphological differences compared with non-transgenic plants. In regenerated transgenic CINS6 and CINS8 plants, which exhibited higher expression of CINS than the other transgenic plants, 1,8-cineole was detected in the head space above whole plants. Furthermore, in a two-choice assay using florets, CINS6 petals demonstrated significant repellent effects against western flower thrips (Frankliniella occidentalis (Pergrande)) compared with the non-transgenic control petals. These results suggest another way to prevent pest damage by herbivores in ornamental plants by releasing transgenic volatile compounds from florets.
[学术文献 ] Differential electrophysiological responses of wingless and winged forms of three non-host-alternating aphids to plant volatile compounds 进入全文
Journal of Asia-Pacific Entomology 期刊
From spring to autumn, aphids produce two types of asexual morphs: wingless and winged. Olfactory cues are often utilized by the winged morph in long-distance host plant selection, and by the wingless morph in short-range host plant location. Electroantennogram (EAG) responses to a range of plant volatiles were recorded from wingless and winged forms of the English grain aphid Sitobion avenae, greenbug Schizaphis graminum, and pea aphid Acyrthosiphon pisum. The response patterns of the three aphid species were similar, although some variations did occur. (E)-2-Hexenal elicited the largest EAG responses in both asexual forms (i.e., wingless and winged) of the three species. In general, green leaf volatiles and benzaldehyde produced relatively large EAGs. The winged form was more responsive than the wingless form to all the plant volatile compounds tested but 4-ethylbenzaldehyde for S. graminum, and hexanal and benzyl acetate for A. pisum. This study indicates that both forms of S. avenae, S. graminum, and A. pisum are able to detect various volatile compounds, and generally higher EAG response in winged forms suggest that they have a more responsive olfactory system than wingless forms, and are better-adapted for switching host plants under unfavorable environmental conditions.
[学术文献 ] Effect of symbiotic microbiota and arginine on host plant selection by the tea green leafhopper in tea cultivation 进入全文
Industrial Crops and Products 期刊
The tea green leafhopper (TGLH), Empoasca (Matsumurasca) onukii Matsuda, poses a significant challenge to tea cultivation in East Asia because of its ability to infest specific tea plant cultivars. Here, we investigated the complex interactions between TGLHs, various tea cultivars, and their symbiotic microbiota, especially the effect of arginine on host selection. A detailed two-year field study involving 16 tea cultivars, coupled with controlled laboratory and field experiments, was conducted to establish a clear link between TGLH infestation and the arginine content of tea plants. Metagenomic analysis revealed a predominance of bacterial taxa in TGLHs, primarily from the phylum Proteobacteria, with significant contributions from orders such as Pseudomonadales, Enterobacterales, and Flavobacteriales, which are crucial for the biosynthesis of essential amino acids but lack the argF gene necessary for arginine synthesis. The absence of the argF gene indicates the potential presence of microbial-mediated dietary adaptation strategies in TGLHs. Additionally, our research examines microbial diversity within TGLH populations and confirms the critical role that symbiotic bacteria play in influencing dietary preferences. The results of our study provide insights into the dynamic interplay between pests, plants, and microorganisms. Our findings are preliminary, and further research is needed to explore the potential applications of symbiotic bacteria in sustainable tea cultivation and integrated pest management strategies.
[学术文献 ] TDDet: A novel lightweight and efficient tea disease detector 进入全文
Computers and Electronics in Agriculture 期刊
This paper proposes a lightweight and efficient detector called TDDet to quickly and accurately detect tea diseases. TDDet is mainly composed of two key innovations: feature extraction and feature aggregation. For feature extraction, we use lightweight depthwise separable convolution to reduce the computational load and enhance the ability to extract key local features in images of tea diseases. In addition, attention mechanisms including channel-, spatial-, and self-attentions, are employed to enable the model to focus on the most important parts of tea diseases, thereby improving the performance of the model. For feature aggregation, we propose a novel Cross-scale Feature Fusion (CFF) module to focus on tea disease areas, boosting the model’s sensitivity to feature details. Based on CFF, TDDet repeatedly fuses multiscale features of different levels in a top-down and bottom-up manner, enhancing feature representation capability. Besides, a lightweight and efficient upsampling module, called Dysample, is used to reduce computational costs and improve model performance by dynamically adjusting the sampling rate of feature maps. Experimental results demonstrate that TDDet with fewer parameters outperforms other state-of-the-art object detection models, enabling fast and accurate identification of tea diseases.
