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Updated: Sep 17, 2026

A Hydroponic Co-cultivation System for Simultaneous and Systematic Analysis of Plant/Microbe Molecular Interactions and Signaling
Published on: July 22, 2017
Decoding the rhizosphere immune signaling network: Microbiome-driven modulation of plant immunity and disease
Su Sun1, Jiarong Li2, Liufei Liu2
1School of Smart Cities and Biohealth, Wuchang Shouyi University, Wuhan, 430064, PR China; Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan, 430074, PR China.
Abstract:
Classical plant immunity models rely on pattern-triggered immunity (PTI) and effector-triggered immunity (ETI), yet these frameworks largely overlook the rhizosphere microbiome as a functional determinant of disease resistance. Plants act as holobionts, their root exudates comprising flavonoids, coumarins, benzoxazinoids, strigolactones, and primary metabolites selectively recruit microbial communities whose composition is shaped by host genotype and dynamically reprogrammed under biotic and abiotic stress. Recruited microorganisms return a diverse signal range including flagellin, siderophores, lipopeptides, lactones, mycorrhizal lipochitooligosaccharides, and volatile organic compounds, which are perceived by LRR (leucine rich repeats) and LysM (lysin motif) domain receptors. This in turn engages the salicylic acid, jasmonic acid, and ethylene signaling pathways. The beneficial rhizosphere members predominantly trigger the JA/ET-dependent induced systemic resistance (ISR) through epigenetic mechanisms, including the H3K4me3 deposition at defense loci that establish heritable primed states that enhance the immune response when pathogens attack. This review synthesizes these interactions within the rhizosphere immune signaling network (RIsN) framework. This reconceptualizes the rhizosphere as multi-kingdom signaling systems whose emergent properties including the signal cooperation, competitive interference, and feedback stabilization, collectively determine disease suppression capacity. Climate change threatens the RIsN stability through microbiome dysbiosis while advances in syncoms, spatial metabolomics, and AI-driven network modeling provide new opportunities for predictive and targeted rhizosphere engineering for durable crop protection.
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