Ecological Engineering of the Human Gut Microbiome: A Review and Testable Framework for Next-Generation Therapeutics

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Abstract
The human gut microbiome is a complex adaptive ecosystem whose functions arise from interactions among microbial populations rather than from isolated taxa. Nevertheless, many microbiome-directed interventions remain based on the administration of individual strains, with limited consideration of the ecological processes governing community assembly, succession, and resilience. This review integrates evidence from microbial ecology, comparative genomics, systems biology, mechanistic physiology, and clinical microbiome research to propose a testable framework for the ecological engineering of the human gut microbiome. Within this framework, selected spore-forming probiotics are hypothesized to function as transient pioneer organisms that modify intestinal physicochemical and metabolic conditions, thus facilitating the establishment and activity of functionally complementary microbial populations delivered through rationally designed synbiotic consortia. The proposed process comprises five stages: pioneer activity, niche remodeling, facilitated community assembly, functional-network stabilization, and the emergence of host-associated outcomes. Available genomic, physiological, and clinical observations support the biological plausibility of individual components of this model but do not yet demonstrate directed ecological succession as a complete causal process. Accordingly, the framework distinguishes established evidence from ecological inference and generates experimentally testable predictions of temporal niche modification, metabolic cross-feeding, functional redundancy, resilience after treatment withdrawal, and host metabolic responses. This ecological perspective shifts the objective of microbiome therapeutics from transient strain supplementation toward the predictable modulation of community trajectories, providing an experimental foundation for developing more resilient, mechanism-based interventions.

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