Systems-Level Decoding of Root-to-Shoot Microbiome Dynamics via Integrated Multi-Omics and Network Analysis
摘要
The rhizosphere–phylosphere continuum constitutes a multifaceted biological interface that integrates root- and leaf-associated microbiomes into a single, functionally cohesive phytobiome capable of maintaining systemic homeostasis and stress resilience. This review delineates how distinct microbial taxa inhabiting plant tissues, along with the associated biochemical signaling networks, including volatile organic compounds (VOCs), phytohormones, extracellular vesicles (EVs), and small RNAs (sRNAs), collectively underpin the molecular and physiological interconnectivity that links the belowground and aerial compartments of the plant. Using a combination of bibliometric analysis and multi-omics integration, this work synthesizes global research trends, thematic advancements, and mechanistic insights into the crosstalk between the rhizosphere and phyllosphere. The integration of metagenomic, metabolomic, and transcriptomic datasets enables a comprehensive reconstruction of microbial interaction networks, revealing how these communities coordinate nutrient fluxes, regulate plant defense responses, and mediate adaptive strategies under diverse environmental conditions. Additionally, the use of synthetic microbial communities (SynComs) and computational network modeling supports these findings by experimentally confirming the regulatory interdependencies among microbial groups. These methods provide mechanistic evidence of how engineered microbial consortia can be optimized to enhance crop productivity, accelerate nutrient cycling, and improve plant resilience against both abiotic and biotic stressors. Overall, this synthesis presents a systems-level framework that links microbial ecology, molecular signaling, and network biology. It highlights the emerging approach of microbiome-informed crop engineering, where ecological and molecular insights converge to promote sustainable agriculture and the long-term stability of agroecosystems.
Graphical abstract