Metagenomic and metabolomic analysis reveals the effects of chemical phosphorus recovery on biological nutrient removal system

- The effects of side-stream P recovery on biological nutrient removal were explored.
- Both nutrients removal and P recovery were achieved at the optimal SSR of 0.3.
- Higher SSRs (>0.3) disrupted the phosphorus balance of A2N-IC process.
- Microbial community and metabolism were changed by the introduced P recovery unit.
- Combined bio-omics approach was valuable for revealing the influencing mechanism.

Side-stream phosphorus recovery coupled with biological nutrient removal can achieve the dual goals of resource recycling and meeting effluent discharge standards in wastewater treatment processes. However, suboptimal side-stream ratios (SSRs) for phosphorus recovery exert a negative effect on the performance of the combined process. The aim of this study was to reveal the comprehensive effect of chemical phosphorus recovery on the biological nutrient removal process using combined bio-omics (metagenomics and metabolomics) analysis. The optimal SSR was 0.3, at which point the effluent concentrations of COD, TN, NH4+-N and TP were approximately 32.56, 11.35, 3.71 and 0.23 mg/L, respectively. Initially increasing the SSR favored resource recovery; however, SSRs > 0.3 disrupted the phosphorus balance of the system and inhibited the metabolic activity of microorganisms related to the phosphorus removal process. Variations of activated sludge characteristics at different SRR indicated that the polysaccharide were more important than protein in resisting the toxicity of the imported Ca2+ on microorganisms. Relevant changes in the microbial community, functional potential, key enzymes and intracellular metabolites were illustrated in the bio-omics analysis, which revealed the influencing mechanism of chemical phosphorus recovery on activated sludge system at the micro level. The results of this study provide a novel perspective on the interactions between resource recovery and pollutant removal in a combined process using a bio-omics approach.

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