Ontology highlight
ABSTRACT: Environmental co-contamination presents significant challenges. To tackle these, while microbial consortia offer advantages over single-strain approaches, such as functional redundancy and synergistic degradation, rationally designing effective synthetic microbiomes specifically for complex co-contamination scenarios remains a major challenge. Here, we utilized our advanced genome-scale metabolic modeling (GSMM) tool, SuperCC, to simulate the metabolic behavior of communities consisting of six isolated key strains under single- and multi-carbon source conditions, mimicking single-pollutant or co-contamination scenarios respectively. By integrating multi-omics data with metabolic modeling of cultured consortia, we systematically elucidated key strain interaction networks and adaptive strategies under co-contamination. This revealed that the specific secretory products of broad-spectrum resource-utilizing bacteria serve as key metabolites driving cooperation and highlighted the pivotal role of indigenous keystone strains in stabilizing and enhancing community function. Consequently, we propose a novel and rational paradigm for consortium design: DHP-Com (Degrader-Helper-Potentiator). Synthetic microbiomes constructed based on this framework exhibited enhanced ecological fitness (survival and growth) and, most importantly, substantially improved remediation performance across diverse co-contamination scenarios. Our findings advance the practical application of GSMM predictions to decipher intricate multi-pollutant/multi-strain interaction networks, offering a powerful rational framework and robust methodological tools for engineering multi-functional and effective synthetic microbiomes for complex environmental remediation.
INSTRUMENT(S): Liquid Chromatography MS - negative - reverse phase, Liquid Chromatography MS - positive - reverse phase
PROVIDER: MTBLS12809 | MetaboLights | 2025-11-20
REPOSITORIES: MetaboLights
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