Engineering Plant Microbiomes for Enhanced Growth and Stress Resilience

Plants are associated with diverse microbial communities that play a crucial role in plant growth promotion and improving stability under stress conditions. Microbiome engineering involves the targeted manipulation, recruitment, and optimization of plant-associated microbial communities to enhance plant performance. However, the effectiveness of microbiome engineering can vary with plant genotype, environmental conditions, microbial composition, and the stability of introduced or selected communities. This review paper summarizes emerging strategies for plant microbiome engineering, including synthetic microbial consortia (SynComs) and host-mediated microbiome selection. SynCom approaches involve the rational assembly of selected microbial strains at the community scale, whereas host-mediated engineering uses plant–microbiome interactions and host genetic variation to enrich beneficial microbial communities. Evidence suggests that combining complementary microbial functions with host-mediated selection may improve microbiome establishment and functional consistency; however, translating these benefits into reliable field performance remains challenging because of context-dependent microbial interactions, competition with resident communities, and limited long-term persistence. Furthermore, this review also discusses omics technologies, including metagenomics, metabolomics, and transcriptomics, which facilitate the identification of functional microbial traits and plant–microbe interactions. Artificial intelligence and machine learning provide complementary tools for microbiome prediction and targeted intervention design. However, their predictive reliability depends on representative datasets, robust validation, and integration of environmental and biological variables. The review highlights that successful microbiome engineering requires a shift from microbial community assembly alone toward functionally validated, ecologically stable, and field-tested strategies. Integrating microbiome engineering with multi-omics, AI-driven prediction, and precision agriculture could support more predictable, resilient, and sustainable crop production.