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Jia-Lin Zhang

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Open access Sep 2026

Foliar and Root Dynamic Analyses Reveal a Coordinated Defense Regulatory Network Against Aeolesthes induta Infestation in Tea Plants

The stem-boring herbivore Aeolesthes induta severely threatens tea (Camellia sinensis) production, yet the systemic defense mechanisms of tea plants remain largely elusive. The unique age-dependent infestation pattern of A. induta—with minimal damage to young tea plants but infestation rates reaching 20% in 30-year-old trees and nearly 100% in ancient tea trees—necessitated field sampling from naturally infested old tea plantations rather than controlled laboratory conditions. By integrating rhizosphere microbiomics, transcriptomics, and multi-omics modeling, this study characterized the defensive regulatory networks of 30-year-old Shuixian tea cultivars under A. induta infestation. Rhizosphere microbiome analysis revealed that herbivore attack significantly reshaped the microbial community structure, reducing bacterial diversity and simplifying co-occurrence network complexity. Transcriptomic and metabolomic profiling demonstrated a precise source–sink defense allocation between host tissues. In leaves acting as the photosynthetic source, metabolic reprogramming was dominated by the systematic accumulation of soluble sugars and sugar acids for systemic energy reallocation. Concurrently, the roots acting as the metabolic sink vigorously activated the jasmonic acid (JA) signaling cascade and upregulated genes enriched in phenylpropanoid biosynthesis and alpha-linolenic acid metabolism. This molecular activation drove the substantial de novo synthesis of defensive phenolic acids, while downregulating growth-related flavonoids. Integrated network modeling further highlighted the phenylpropanoid pathway as the central regulatory node coupling transcript–metabolite fluctuations. This study constructs an integrated soil microbiome–root–leaf defense network, providing novel mechanistic insights into plant–borer interactions and a valuable foundation for future insect-resistant breeding programs in the tea industry.

Cheng-Cong Lu, Jia-Lin Zhang, Ke Chen et al. · 0 citations

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