From dynamic transcripts to stable proteins: multi-omics revealed regulatory buffering of Candidatus Accumulibacter under cyclic conditions

Abstract

Enhanced biological phosphorus removal (EBPR) relies on polyphosphate-accumulating organisms that experience dynamic fluctuations in redox conditions and substrate availability. How these organisms regulate metabolism across molecular layers under cyclic operation remains incompletely understood. Here, we investigated molecular regulation in a long-term, stable aerobic granular sludge system dominated by Candidatus Accumulibacter. We combined metagenomics, time-resolved metatranscriptomics, and matched metaproteomics across three consecutive operational cycles. Genome-resolved metagenomics revealed an Accumulibacter-dominated community encoding canonical EBPR functions. Time-resolved metatranscriptomics revealed extensive and reproducible transcriptional dynamics affecting hundreds of genes. These dynamics did not align with discrete EBPR phases or instantaneous environmental transitions, but instead unfolded gradually over the cycle. Despite pronounced transcript-level heterogeneity, aggregation at the functional level revealed strong consolidation, with only a limited number of KEGG orthologs exhibiting coherent temporal regulation. Quantitative metaproteomics revealed a stable proteome across EBPR cycles, with no individual proteins or functional categories showing significant differential abundance despite direct transcript-protein mapping and time-matched sampling. This indicated that transcriptional dynamics did not translate into measurable changes in protein pool size on the time scale of individual cycles, consistent with slow, growth-coupled proteome turnover relative to cycle duration. Together, these results support a hierarchical model of regulation in Candidatus Accumulibacter, in which dynamic transcriptional responses are buffered at both the functional and protein levels. This organization provides a plausible basis for stable EBPR performance under predictable cyclic operation and demonstrates how time-resolved multi-omics can be used to resolve regulatory dynamics across molecular layers in engineered microbial ecosystems.