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<p>This review synthesizes recent advances in the integration of omics, synthetic biology, and artificial intelligence (AI) to deepen understanding of plant–microbe interactions and support sustainable agriculture. Omics approaches have provided molecular-level insights into microbial diversity, functional genes, and regulatory pathways shaping rhizosphere dynamics. Synthetic biology has enabled the design of microbial strains and synthetic communities (SynComs) with enhanced traits such as nutrient solubilization, stress tolerance, and pathogen suppression, offering targeted solutions for crop improvement. AI-driven tools have accelerated these advances by enabling predictive modelling, multi-omics data integration, and real-time phenotyping, while also enhancing disease forecasting and microbiome-informed crop management. The combined application of these technologies demonstrates potential for the rational design of next-generation plant growth-promoting rhizobacteria and synthetic microbial consortia optimized for diverse agroecosystems. Key challenges remain in translating laboratory findings to field conditions, ensuring biosafety of engineered microbes, and addressing ethical and regulatory issues. Addressing these barriers through interdisciplinary frameworks and responsible innovation will pave the way for climate specific high-yielding, and sustainable cropping systems.</p>

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Rooted intelligence: Integrating AI, Omics, and Synthetic biology to engineer the plant microbiome

  • 期刊论文

  • 发表日期：

    2025年12月8日

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  • Anushree Kamath,
  • Dhara Patel,
  • Meenu Saraf,
  • Stuti Patel

摘要

This review synthesizes recent advances in the integration of omics, synthetic biology, and artificial intelligence (AI) to deepen understanding of plant–microbe interactions and support sustainable agriculture. Omics approaches have provided molecular-level insights into microbial diversity, functional genes, and regulatory pathways shaping rhizosphere dynamics. Synthetic biology has enabled the design of microbial strains and synthetic communities (SynComs) with enhanced traits such as nutrient solubilization, stress tolerance, and pathogen suppression, offering targeted solutions for crop improvement. AI-driven tools have accelerated these advances by enabling predictive modelling, multi-omics data integration, and real-time phenotyping, while also enhancing disease forecasting and microbiome-informed crop management. The combined application of these technologies demonstrates potential for the rational design of next-generation plant growth-promoting rhizobacteria and synthetic microbial consortia optimized for diverse agroecosystems. Key challenges remain in translating laboratory findings to field conditions, ensuring biosafety of engineered microbes, and addressing ethical and regulatory issues. Addressing these barriers through interdisciplinary frameworks and responsible innovation will pave the way for climate specific high-yielding, and sustainable cropping systems.