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.@en

Background: In molecular microbial ecology, massive sequencing is gradually replacing classical fingerprinting techniques such as terminal-restriction fragment length polymorphism (T-RFLP) combined with cloning-sequencing for the characterization of microbiomes. Here, a bioinformatics methodology for pyrosequencing-based T-RF identification (PyroTRF-ID) was developed to combine pyrosequencing and T-RFLP approaches for the description of microbial communities. The strength of this methodology relies on the identification of T-RFs by comparison of experimental and digital T-RFLP profiles obtained from the same samples. DNA extracts were subjected to amplification of the 16S rRNA gene pool, T-RFLP with the HaeIII restriction enzyme, 454 tag encoded FLX amplicon pyrosequencing, and PyroTRF-ID analysis. Digital T-RFLP profiles were generated from the denoised full pyrosequencing datasets, and the sequences contributing to each digital T-RF were classified to taxonomic bins using the Greengenes reference database. The method was tested both on bacterial communities found in chloroethene-contaminated groundwater samples and in aerobic granular sludge biofilms originating from wastewater treatment systems. Results: PyroTRF-ID was efficient for high-throughput mapping and digital T-RFLP profiling of pyrosequencing datasets. After denoising, a dataset comprising ca. 10[prime]000 reads of 300 to 500 bp was typically processed within ca. 20 minutes on a high-performance computing cluster, running on a Linux-related CentOS 5.5 operating system, enabling parallel processing of multiple samples. Both digital and experimental T-RFLP profiles were aligned with maximum cross-correlation coefficients of 0.71 and 0.92 for high- and low-complexity environments, respectively. On average, 63+/-18% of all experimental T-RFs (30 to 93 peaks per sample) were affiliated to phylotypes. Conclusions: PyroTRF-ID profits from complementary advantages of pyrosequencing and T-RFLP and is particularly adapted for optimizing laboratory and computational efforts to describe microbial communities and their dynamics in any biological system. The high resolution of the microbial community composition is provided by pyrosequencing, which can be performed on a restricted set of selected samples, whereas T-RFLP enables simultaneous fingerprinting of numerous samples at relatively low cost and is especially adapted for routine analysis and follow-up of microbial communities on the long run.@en

Production of biogas from different organic materials is a most interesting source of renewable energy. The biomethane potential (BMP) of these materials has to be determined to get insight in design parameters for anaerobic digesters. A workshop was held in June 2015 in Leysin Switzerland to agree on common solutions to the conundrum of inconsistent BMP test results. A discussion covers actions and criteria that are considered compulsory ito accept and validate a BMP test result; and recommendations concerning the inoculum substrate test setup and data analysis and reporting ito obtain test results that can be validated and reproduced.@en

New-generation bioprocesses using granular sludge aim for a high-rate removal of nutrients from wastewater with low footprint. Achieving enhanced biological phosphorus removal (EBPR) relies on the design of sludge beds and wastewater feeding conditions to optimally load the biomass and to select for polyphosphate- (PAOs) over glycogen-accumulating organisms (GAOs) and over other heterotrophs. A hydraulic–metabolic mathematical model was developed to elucidate the impact of hydraulic transport patterns and environmental conditions on the PAO/GAO competition during up-flow feeding through an EBPR granular sludge bed. Tracer experiments highlighted plug-flow regimes with dispersion under both rapid (9 m h−1, Rebed = 1.6, Pez = 7.2, Pet = 4.6) and slow (0.9 m h−1, Rebed = 0.2, Pez = 21.3, Pet = 3.4) feeding. Non-turbulent regimes (Rebed << 103) promote a safe implementation of simultaneous fill/draw. Feeding time, pH, and temperature significantly impacted bacterial competition for carbon uptake under anaerobic slow feeding. Feeding duration should be designed to avoid full depletion of intracellular storage polymers within static granules. PAOs bear twice longer feeding than GAOs by using both polyphosphate and glycogen hydrolysis to sustain anaerobic C-uptake. Alkaline conditions (pH 7.25–8.0) by, e.g., dosing lime in the feed select for PAOs independently of temperature (10−30°C). A twice higher bed is required for full anaerobic conversions at 10 rather than 20°C. Biosystem responses for anaerobic C-uptake can be anticipated using the model toward designing robust anaerobic selectors to manage the microbial resource in EBPR granular sludge. Biotechnol. Bioeng. 2017;114: 1688–1702.@en

Aerobic granular sludge (AGS) is based on self-granulated flocs forming mobile biofilms with a gel-like consistence. Bacterial and structural dynamics from flocs to granules were followed in anaerobic-aerobic sequencing batch reactors (SBR) fed with synthetic wastewater, namely a bubble column (BC-SBR) operated under wash-out conditions for fast granulation, and two stirred-tank enrichments of Accumulibacter (PAO-SBR) and Competibacter (GAO-SBR) operated at steady-state. In the BC-SBR, granules formed within 2 weeks by swelling of Zoogloea colonies around flocs, developing subsequently smooth zoogloeal biofilms. However, Zoogloea predominance (37-79%) led to deteriorated nutrient removal during the first months of reactor operation. Upon maturation, improved nitrification (80-100%), nitrogen removal (43-83%), and high but unstable dephosphatation (75-100%) were obtained. Proliferation of dense clusters of nitrifiers, Accumulibacter, and Competibacter from granule cores outwards resulted in heterogeneous bioaggregates, inside which only low abundance Zoogloea (@en

Aerobic granular sludge is attractive for high-rate biological wastewater treatment. Biomass wash-out conditions stimulate the formation of aerobic granules. Deteriorated performances in biomass settling and nutrient removal during start-up have however often been reported. The effect of wash-out dynamics was investigated on bacterial selection, biomass settling behavior, and metabolic activities during the formation of early-stage granules from activated sludge of two wastewater treatment plants (WWTP) over start-up periods of maximum 60 days. Five bubble-column sequencing batch reactors were operated with feast-famine regimes consisting of rapid pulse or slow anaerobic feeding followed by aerobic starvation. Slow-settling fluffy granules were formed when an insufficient superficial air velocity (SAV; 1.8 cm s~1) was applied, when the inoculation sludge was taken from a WWTP removing organic matter only, orwhen reactors were operated at 30oC. Fast-settling dense granules were obtained with 4.0 cms1 SAV, or when the inoculation sludge was taken from a WWTP removing all nutrients biologically. However, only carbon was aerobi-cally removed during start-up. Fluffy granules and dense granules were displaying distinct predominant phylotypes, namely filamentous Burkholderiales affiliates and Zoogloea relatives, respectively. The latter were predominant in dense granules independently from the feeding regime. A combination of insufficient solid retention time and of leakage of acetate into the aeration phase during intensive biomass wash-out was the cause for the proliferation of Zoogloea spp. in dense granules, and for the deterioration of BNR performances. It is however not certain that Zoogloea-like organisms are essential in granule formation. Optimal operation conditions should be elucidated for maintaining a balance between organisms with granulation propensity and nutrient removing organisms in order to form granules with BNR activities in short start-up periods.@en

Nutrient removal performances of sequencing batch reactors using granular sludge for intensified biological wastewater treatment rely on optimal underlying microbial selection. Trigger factors of bacterial selection and nutrient removal were investigated in these novel biofilm systems with specific emphasis on polyphosphate- (PAO) and glycogen-accumulating organisms (GAO) mainly affiliated with Accumulibacter and Competibacter, respectively. In a first dynamic reactor operated with stepwise changes in concentration and ratio of acetate and propionate (Ac/Pr) under anaerobic feeding and aerobic starvation conditions and without wasting sludge periodically, propionate favorably selected for Accumulibacter (35% relative abundance) and stable production of granular biomass. A Plackett-Burman multifactorial experimental design was then used to screen in eight runs of 50 days at stable sludge retention time of 15 days for the main effects of COD concentration, Ac/Pr ratio, COD/P ratio, pH, temperature, and redox conditions during starvation. At 95% confidence level, pH was mainly triggering direct Accumulibacter selection and nutrient removal. The overall PAO/GAO competition in granular sludge was statistically equally impacted by pH, temperature, and redox factors. High Accumulibacter abundances (30-47%), PAO/GAO ratios (2.8-8.4), and phosphorus removal (80-100%) were selected by slightly alkaline (pH>7.3) and lower mesophilic (@en

Intensive nutrient removal from wastewater in anaerobic-aerobic systems using granular sludge should rely on optimal balances at biofilm and microbial ecology levels. This study targets the impacts of reactor characteristics and fluctuations in operation conditions on nutrient removal and bacterial community structures by means of microbial and numerical ecology methods. The dynamics of both predominant and accompanying populations were investigated with high resolution on temporal and phylogenetic scales in two reactors operated during 5 months with synthetic wastewater. Multivariate analyses highlighted significant correlations from process to microbial scales in the first reactor, whereas nitrification and phosphorus removal might have been affected by oxygen mass transfer limitations with no impact at population level in the second system. The bacterial community continuum of the first reactor was composed of two major antagonistic Accumulibacter-Nitrosomonas-Nitrospira and Competibacter-Cytophaga-Intrasporangiaceae clusters that prevailed under conditions leading to efficient P- (> 95%) and N-removal (> 65%) and altered P- (<90%) and N-removal (<60%), respectively. A third cluster independent of performances was dominated by Xanthomonadaceae affiliates that were on average more abundant at 25 °C (31 ± 5%) than at 20 °C (22 ± 4%). Starting from the physiological traits of the numerous phylotypes identified, a conceptual model is proposed as a base for functional analysis in the granular sludge microbiome and for future investigations with complex real wastewater.@en