Multilevel correlations in the biological phosphorus removal process: From bacterial enrichment to conductivity‐based metabolic batch tests and polyphosphatase assays. Issue 12 (10th September 2014) - Weissbrodt, David G.; Maillard, Julien; Brovelli, Alessandro; Chabrelie, Alexandre; May, Jonathan; Holliger, Christof
ABSTRACT Enhanced biological phosphorus removal (EBPR) from wastewater relies on the preferential selection of active polyphosphate‐accumulating organisms (PAO) in the underlying bacterial community continuum. Efficient management of the bacterial resource requires understanding of population dynamics as well as availability of bioanalytical methods for rapid and regular assessment of relative abundances of active PAOs and their glycogen‐accumulating competitors (GAO). A systems approach was adopted here toward the investigation of multilevel correlations from the EBPR bioprocess to the bacterial community, metabolic, and enzymatic levels. Two anaerobic‐aerobic sequencing‐batch reactors were operated to enrich activated sludge in PAOs and GAOs affiliating with "Candidati Accumulibacter and Competibacter phosphates", respectively. Bacterial selection was optimized by dynamic control of the organic loading rate and the anaerobic contact time. The distinct core bacteriomes mainly comprised populations related to the classes Betaproteobacteria, Cytophagia, and Chloroflexi in the PAO enrichment and of Gammaproteobacteria, Alphaproteobacteria, Acidobacteria, and Sphingobacteria in the GAO enrichment. An anaerobic metabolic batch test based on electrical conductivity evolution and a polyphosphatase enzymatic assay were developed for rapid and low‐cost assessment of the active PAO fraction and dephosphatation potential of activated sludge. Linear correlations were obtained between the PAO fraction, biomass specific rate of conductivity increase under anaerobic conditions, and polyphosphate‐hydrolyzing activity of PAO/GAO mixtures. The correlations between PAO/GAO ratios, metabolic activities, and conductivity profiles were confirmed by simulations with a mathematical model developed in the aqueous geochemistry software PHREEQC. Biotechnol. Bioeng. 2014;111: 2421–2435. © 2014 Wiley Periodicals, Inc.