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. 2012 Sep 13:3:332.
doi: 10.3389/fmicb.2012.00332. eCollection 2012.

Bacterial Selection during the Formation of Early-Stage Aerobic Granules in Wastewater Treatment Systems Operated Under Wash-Out Dynamics

Affiliations

Bacterial Selection during the Formation of Early-Stage Aerobic Granules in Wastewater Treatment Systems Operated Under Wash-Out Dynamics

David G Weissbrodt et al. Front Microbiol. .

Abstract

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, or when reactors were operated at 30°C. Fast-settling dense granules were obtained with 4.0 cm s(-1) SAV, or when the inoculation sludge was taken from a WWTP removing all nutrients biologically. However, only carbon was aerobically 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.

Keywords: aerobic granular sludge; bacterial selection; biological wastewater treatment; granule formation; nutrient removal limitations; wash-out dynamics.

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Figures

Figure 1
Figure 1
Example of early-stage aerobic granule structures observed with light microscopy. Fluffy slow-settling granule obtained after 30 days in reactor R2 with OMR-sludge and low up-flow SAV of 1.8 cm s−1, and exhibiting filamentous outer structures (A). Filamentous segmented chain bacterial structures interspersing across the granular biofilm observed on a sample collected on day 22 in R2 (B). Dense fast-settling granule present after 50 days in R6 with BNR-sludge and moderate up-flow SA of 0.025 m s−1, and displaying a tulip-like folded structure around a more opaque internal core (C).
Figure 2
Figure 2
Dynamics of predominant bacterial OTUs analyzed with T-RFLP during the six granulation experiments. Reactors R1 and R2 were inoculated with activated sludge from the OMR-WWTP (A). R3, R4, and R5 were inoculated with activated sludge from the BNR-WWTP (B). High resolution bacterial ecology data were collected from R6 to assess the effect of wash-out dynamics on bacterial selection during granulation (C). Main operation conditions are indicated at the top of each graph. Closest bacterial affiliations of target OTUs presented in Table 2 are given on the right.
Figure 3
Figure 3
Detailed evolution of biomass parameters during granulation in reactor R6 under wash-out dynamics, in function of the imposed settling time. The evolution of the biomass concentration and of the height of the settled sludge blanket displayed similar profiles as soon as the settling time was decreased to 3 min (A). The application of wash-out conditions resulted in the re-coupling of the SRT to the HRT at day 8 (B). A high amount of biomass was withdrawn with the effluent wastewater during wash-out from day 8 on (C). Under reactor operation with a constant volumetric OLR, the biomass specific OLR exhibited a drastic increase during the period of extensive wash-out between day 8 and day 20 (D). Zoogloea, Tetrasphaera, Rhodocyclaceae, and Hyphomonadaceae affiliates displayed distinct biomass evolutions (E). Early-stage granules nuclei formed after 10 days.
Figure 4
Figure 4
Detailed evolution of the nutrient removal performances in reactor R6. The application of wash-out dynamics resulted in the transient loss of anaerobic acetate uptake (A), nitrification, nitrogen removal, and phosphorus removal performances (B) from day 6 to day 40. Orthophosphate cycling activities in alternating anaerobic-aerobic conditions were not detected during the same period (C).
Figure 5
Figure 5
The bacterial community present in R6 exhibited a strong decrease of about 66% in richness (A) and of about 52% in Shannon’s H’ diversity (B) from inoculation with flocculent activated sludge from a full-scale BNR-WWTP fed with real wastewater to formation of early-stage granules fed with an acetate-based synthetic influent. Mathematical negative exponential growth models successfully explained the evolution of both indices during reactor start-up (R2 = 0.97–0.98). The model trends are given with standard deviation intervals computed from 1000 Monte Carlo simulations. Legend: y0: initial richness or diversity value, ybase: average final richness or diversity value after 60 days, r: negative growth rate, RMS: root mean square error.
Figure A1
Figure A1
Bacteriome phylogenetic tree constructed in MG-RAST (Meyer et al., 2008) with the pyrosequencing datasets of the two biomass samples collected on day 2 (flocculent sludge, red bar plot) and day 59 (early-stage AGS, green bar plot) in the R6 reactor. Each bar plot is related to the number of pyrosequencing reads detected per bacterial affiliation. The tree is presented with classes (outer black circle segments) and orders subdivisions (colored slices), and bacterial genera names. The identity of target orders marked with an asterisk is given for each left-hand and right-hand half of the circular tree. The RDP database (Cole et al., 2009) was used as annotation source, and a minimum identity cutoff of 97% was applied.
Figure A2
Figure A2
Differences in the bacteriome composition of the flocculent sludge present in R6 before wash-out, and of the early-stage granular sludge present at day 59, at the order level (A) and at the genus level (B).

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References

    1. Adav S. S., Lee D. J., Lai J. Y. (2010). Microbial community of acetate utilizing denitrifiers in aerobic granules. Appl. Microbiol. Biotechnol. 85, 753–76210.1007/s00253-009-2317-9 - DOI - PubMed
    1. Allen M. S., Welch K. T., Prebyl B. S., Baker D. C., Meyers A. J., Sayler G. S. (2004). Analysis and glycosyl composition of the exopolysaccharide isolated from the floc-forming wastewater bacterium Thauera sp. MZ1T. Environ. Microbiol. 6, 780–79010.1111/j.1462-2920.2004.00615.x - DOI - PubMed
    1. Baytshtok V., Kim S., Yu R., Park H., Chandran K. (2008). Molecular and biokinetic characterization of methylotrophic denitrification using nitrate and nitrite as terminal electron acceptors. Water Sci. Technol. 58, 359–36510.2166/wst.2008.391 - DOI - PubMed
    1. Benson D. A., Karsch-Mizrachi I., Lipman D. J., Ostell J., Sayers E. W. (2011). GenBank. Nucleic Acids Res. 39, D32–D3710.1093/nar/gkq1079 - DOI - PMC - PubMed
    1. Beun J. J., Heijnen J. J., van Loosdrecht M. C. M. (2001). N-removal in a granular sludge sequencing batch airlift reactor. Biotechnol. Bioeng. 75, 82–9210.1002/bit.1167 - DOI - PubMed