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The Advanced Anaerobic Expanded Granular Sludge Bed (AnaEG) Possessed Temporally and Spatially Stable Treatment Performance and Microbial Community in Treating Starch Processing Wastewater.

ABSTRACT: This study implements temporal and spatial appraisals on the operational performance and corresponding microbial community structure of a full-scale advanced anaerobic expanded granular sludge bed (AnaEG) which was used to treat low organic loading starch processing wastewater. Results showed stable treatment efficiency could be maintained with long-term erratic influent quality, and a major reaction zone located at the bottom of the AnaEG, where the main pollutant removal rate was greater than 90%. Remarkably, high-throughput sequencing of 16S rRNA gene amplicons displayed that the predominant members constructed the major part of the overall microbial community and showed highly temporal stability. They were affiliated to Chloroflexi (16.4%), Proteobacteria (14.01%), Firmicutes (8.76%), Bacteroidetes (7.85%), Cloacimonetes (3.21%), Ignavibacteriae (1.80%), Synergistetes (1.11%), Thermotogae (0.98%), and Euryarchaeota (3.18%). This part of microorganism implemented the long-term stable treatment efficiency of the reactor. Simultaneously, an extraordinary spatial homogeneity in the granule physic properties and microbial community structure along the vertical direction was observed within the AnaEG. In conclusion, the microbial community structure and the bioreactor's performance showed notable spatial and temporal consistency, and the predominant populations guaranteed a long-term favorable treatment performance of the AnaEG. It provides us with a better understanding of the mechanism of this recently proposed anaerobic reactor which was used in low organic loading wastewater treatment.

SUBMITTER: Qin X

PROVIDER: S-EPMC5882818 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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The Advanced Anaerobic Expanded Granular Sludge Bed (AnaEG) Possessed Temporally and Spatially Stable Treatment Performance and Microbial Community in Treating Starch Processing Wastewater.

Qin Xianchao X Wu Xiaogang X Li Lingfang L Li Chunjie C Zhang Zhenjia Z Zhang Xiaojun X

Frontiers in microbiology 20180328

This study implements temporal and spatial appraisals on the operational performance and corresponding microbial community structure of a full-scale advanced anaerobic expanded granular sludge bed (AnaEG) which was used to treat low organic loading starch processing wastewater. Results showed stable treatment efficiency could be maintained with long-term erratic influent quality, and a major reaction zone located at the bottom of the AnaEG, where the main pollutant removal rate was greater than ...[more]

PMID: 29643847

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Project description:Studies investigating the feasibility of new, or improved, biotechnologies, such as wastewater treatment digesters, inevitably start with laboratory-scale trials. However, it is rarely determined whether laboratory-scale results reflect full-scale performance or microbial ecology. The Expanded Granular Sludge Bed (EGSB) bioreactor, which is a high-rate anaerobic digester configuration, was used as a model to address that knowledge gap in this study. Two laboratory-scale idealizations of the EGSB-a one-dimensional and a three- dimensional scale-down of a full-scale design-were built and operated in triplicate under near-identical conditions to a full-scale EGSB. The laboratory-scale bioreactors were seeded using biomass obtained from the full-scale bioreactor, and, spent water from the distillation of whisky from maize was applied as substrate at both scales. Over 70 days, bioreactor performance, microbial ecology, and microbial community physiology were monitored at various depths in the sludge-beds using 16S rRNA gene sequencing (V4 region), specific methanogenic activity (SMA) assays, and a range of physical and chemical monitoring methods. SMA assays indicated dominance of the hydrogenotrophic pathway at full-scale whilst a more balanced activity profile developed during the laboratory-scale trials. At each scale, Methanobacterium was the dominant methanogenic genus present. Bioreactor performance overall was better at laboratory-scale than full-scale. We observed that bioreactor design at laboratory-scale significantly influenced spatial distribution of microbial community physiology and taxonomy in the bioreactor sludge-bed, with 1-D bioreactor types promoting stratification of each. In the 1-D laboratory bioreactors, increased abundance of Firmicutes was associated with both granule position in the sludge bed and increased activity against acetate and ethanol as substrates. We further observed that stratification in the sludge-bed in 1-D laboratory-scale bioreactors was associated with increased richness in the underlying microbial community at species (OTU) level and improved overall performance.

Project description:IntroductionThe expanded granular sludge bed (EGSB) is a major form of anaerobic digestion system during wastewater treatment. Yet, the dynamics of microbial and viral communities and members functioning in nitrogen cycling along with monthly changing physicochemical properties have not been well elucidated.MethodsHere, by collecting the anaerobic activated sludge samples from a continuously operating industrial-scale EGSB reactor, we conducted 16S rRNA gene amplicon sequencing and metagenome sequencing to reveal the microbial community structure and variation with the ever-changing physicochemical properties along within a year.ResultsWe observed a clear monthly variation of microbial community structures, while COD, the ratio of volatile suspended solids (VSS) to total suspended solids (TSS) (VSS/TSS ratio), and temperature were predominant factors in shaping community dissimilarities examined by generalized boosted regression modeling (GBM) analysis. Meanwhile, a significant correlation was found between the changing physicochemical properties and microbial communities (p <0.05). The alpha diversity (Chao1 and Shannon) was significantly higher (p <0.05) in both winter (December, January, and February) and autumn (September, October, and November) with higher organic loading rate (OLR), higher VSS/TSS ratio, and lower temperature, resulting higher biogas production and nutrition removal efficiency. Further, 18 key genes covering nitrate reduction, denitrification, nitrification, and nitrogen fixation pathways were discovered, the total abundance of which was significantly associated with the changing environmental factors (p <0.05). Among these pathways, the dissimilatory nitrate reduction to ammonia (DNRA) and denitrification had the higher abundance contributed by the top highly abundant genes narGH, nrfABCDH, and hcp. The COD, OLR, and temperature were primary factors in affecting DNRA and denitrification by GBM evaluation. Moreover, by metagenome binning, we found the DNRA populations mainly belonged to Proteobacteria, Planctomycetota, and Nitrospirae, while the denitrifying bacteria with complete denitrification performance were all Proteobacteria. Besides, we detected 3,360 non-redundant viral sequences with great novelty, in which Siphoviridae, Podoviridae, and Myoviridae were dominant viral families. Interestingly, viral communities likewise depicted clear monthly variation and had significant associations with the recovered populations (p <0.05).DiscussionOur work highlights the monthly variation of microbial and viral communities during the continuous operation of EGSB affected by the predominant changing COD, OLR, and temperature, while DNRA and denitrification pathways dominated in this anaerobic system. The results also provide a theoretical basis for the optimization of the engineered system.

Dataset Information

The Advanced Anaerobic Expanded Granular Sludge Bed (AnaEG) Possessed Temporally and Spatially Stable Treatment Performance and Microbial Community in Treating Starch Processing Wastewater.

Publications

The Advanced Anaerobic Expanded Granular Sludge Bed (AnaEG) Possessed Temporally and Spatially Stable Treatment Performance and Microbial Community in Treating Starch Processing Wastewater.

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