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Review

Rhizosphere engineering 2.0: Predictive microbiome design for climate-resilient agriculture, sustainable food production, and global food security.

Sep 2026 · Plant Science · pp. 113469 · 0 citations · 131 references
Medicine

TL;DR

This work introduces Rhizosphere Engineering 2.0 (RE 2.0), a predictive, systems-level framework that integrates systems biology, multi-omics, ecological network analysis, synthetic biology, artificial intelligence (AI), and precision agriculture to forecast and design microbiome composition and function before field deployment, rather than selecting inoculants by trial and error.

Abstract

The rhizosphere is a dynamic interface among plant roots, soil, and microbiota, where the resident microbial community shapes plant health, ecosystem resistance and resilience, nutrient cycling, and sustainable crop production. Yet the limited efficacy of conventional microbial inoculants under field conditions - reflecting poor persistence of introduced microorganisms, incomplete mechanistic understanding of plant-microbiome signalling, and high context-dependence across soils and climates - has created a need for predictive, rather than empirical, microbiome engineering. To close this gap, we introduce Rhizosphere Engineering 2.0 (RE 2.0), defined here as a predictive, systems-level framework that integrates systems biology, multi-omics, ecological network analysis, synthetic biology, artificial intelligence (AI), and precision agriculture to forecast and design microbiome composition and function before field deployment, rather than selecting inoculants by trial and error. We review the biological underpinnings of RE 2.0 - the plant-soil-microbiome holobiont, root-exudate-driven microbiome assembly, interkingdom communication, and ecological network organisation - that govern nutrient uptake, disease resistance, carbon sequestration and ecosystem stability. We then evaluate the engineering strategies that operationalise this framework, including synthetic microbial communities (SynComs), root exudate engineering, biochar-assisted microbiome engineering, regenerative soil management, CRISPR-based microbiome editing, and AI- and digital-twin-guided microbiome prediction, for improving nutrient-use efficiency, crop productivity, climate resilience and soil restoration. Key translational challenges are critically examined, including ecological complexity, poor field persistence of introduced microorganisms, incomplete mechanistic understanding, and biosafety and regulatory constraints. We conclude by outlining a research and implementation roadmap through which the integrated RE 2.0 approach can advance sustainable agricultural intensification, climate resilience, soil restoration and global food security.

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