Engineering resilient environmental microbiomes: from multi-omics early-warning signals to predictive control and functional recovery

Microbial consortia are used in environmental bioprocesses, particularly wastewater treatment and anaerobic digestion. High performance under controlled conditions does not ensure stability or functional recovery after disturbance or scale-up. This review examines disturbance, destabilization, detection, prediction, intervention, and functional recovery in engineered microbiomes. We distinguish stability, resistance, resilience, recovery, and functional redundancy as distinct but interrelated properties and classify major physicochemical, ecological, operational, and evolutionary disturbances that destabilize microbial consortia. We examine competitive exclusion, loss of keystone populations, syntrophic decoupling, metabolic cheating, phage pressure, genetic instability, and spatial reorganization as mechanisms of functional failure. We evaluate observability across four layers: community structure, functional potential, active function, and process phenotype. Multi-omics, single-cell methods, spatial measurements, online sensors, and biosensors are assessed for their ability to provide early-warning signals. We assess ecological and metabolic models, machine learning, and hybrid models, distinguishing reported process predictions from the proposed use of microbiome-informed digital twins for control. Strategies include functional redundancy, controlled metabolic interdependence, ecological steering, bioaugmentation, predefined recovery protocols, synthetic biology, and scale-aware process design. We propose a conceptual Microbiome Resilience Qualification Framework covering six domains: function, stability, resilience, observability, controllability, and scalability. The framework links defined disturbance–recovery tests with evidence on monitoring, intervention and scale-dependent function. Its criteria require prospective validation.