The widespread use of antibiotics has severely disrupted the structure of microbial communities, but the responses of these communities vary in different environments. Interestingly, even when the species composition changes, some microbial communities can still maintain crucial functions, a phenomenon known as “decoupling of structure and function.” Among them, functional redundancy (FR) - the characteristic that multiple microorganisms perform the same ecological function - is the key mechanism for maintaining this stability. This review focuses on how functional redundancy may enhance microbial community resilience under antibiotic perturbation. We first start from the insurance hypothesis and the YAS (yield - acquisition - stress) framework to explain the ecological principles behind functional redundancy, and explain how microorganisms allocate resources and make trade-offs in different environments. We systematically analyze the multi-level defense strategies of microorganisms at five levels, including: ecological niche differentiation at the species level, horizontal transfer of resistance genes at the genetic level, cross-feeding reconstruction of metabolic networks, dormancy strategies at the temporal dimension (seed bank), and population regulation mediated by bacteriophages. Methodologically, we review metatranscriptomic approaches for distinguishing active signals from residual DNA, structural entropy algorithms for inferring FR, and AI-based tools for identifying latent resistance genes. Evidence from ecosystems such as the gut, respiratory tract, soil, and wastewater suggests the broad relevance of functional redundancy, although its stabilizing effect depends on antibiotic type, exposure duration, initial community composition, and ecological context. Finally, we explore the application prospects of this principle in the construction of synthetic communities and the optimization of fecal microbiota transplantation, and point out the evolutionary costs that may accompany maintaining functional redundancy, which is an important challenge that future research needs to address.
Jingnan Ge (Thu,) studied this question.