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Metabolic programming and functional remodeling by a c-di-GMP-centric hierarchy in aerobic granular sludge

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NIAID Data Ecosystem2026-05-10 收录
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https://www.omicsdi.org/dataset/metabolights_dataset/MTBLS13486
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This study systematically elucidates the hierarchical signaling regulatory network in aerobic granular sludge (AGS) by integrating dynamic analysis of quorum sensing signal molecules, microbial community structure profiling, and metabolomic characterization. The research reveals that c-di-GMP functions as the highest-priority signal directing systemic metabolism. AI-2 acts as a synergistic optimizer and the functional expression of AHLs is governed by upstream signals. This signaling hierarchy precisely controls central carbon metabolic fluxes, thereby determining the pollutant removal efficiency, structural stability, and system resilience of AGS. Experimental results demonstrate that the synergistic action of c-di-GMP and AI-2 significantly enhances short-chain AHLs production (C8-HSL reaching 22.6 nmol/L), while AI-2 alone predominantly regulates long-chain AHLs turnover. Signal combinations achieve metabolic reprogramming through specific enrichment of functional bacterial groups (e.g., Rhodocyclaceae increased by 2.7-52.9%, Comamonadaceae increased by 6.3-53.7%). Under different storage conditions, the system exhibits differentiated recovery strategies. In response to stress, refrigerated granules activate their metabolic network globally. In contrast, dried granules initiate a recovery process that prioritizes the repair of oxidative damage following desiccation. Correlation analyses further underscore the functional links between signal molecules and key metabolic activities, such as the positive relationship between C8-HSL and ICDHc activity (p < 0.05), thereby validating the proposed hierarchical regulatory model. This study paves the way for targeted quorum sensing regulation strategies and the advancement of stable, efficient, next-generation wastewater treatment processes.
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2025-12-10
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