Literature DB >> 25222332

Metabolic modelling of full-scale enhanced biological phosphorus removal sludge.

Ana B Lanham1, Adrian Oehmen2, Aaron M Saunders3, Gilda Carvalho4, Per H Nielsen5, Maria A M Reis6.   

Abstract

This study investigates, for the first time, the application of metabolic models incorporating polyphosphate accumulating organisms (PAOs) and glycogen accumulating organisms (GAOs) towards describing the biochemical transformations of full-scale enhanced biological phosphorus removal (EBPR) activated sludge from wastewater treatment plants (WWTPs). For this purpose, it was required to modify previous metabolic models applied to lab-scale systems by incorporating the anaerobic utilisation of the TCA cycle and the aerobic maintenance processes based on sequential utilisation of polyhydroxyalkanoates, followed by glycogen and polyphosphate. The abundance of the PAO and GAO populations quantified by fluorescence in situ hybridisation served as the initial conditions of each biomass fraction, whereby the models were able to describe accurately the experimental data. The kinetic rates were found to change among the four different WWTPs studied or even in the same plant during different seasons, either suggesting the presence of additional PAO or GAO organisms, or varying microbial activities for the same organisms. Nevertheless, these variations in kinetic rates were largely found to be proportional to the difference in acetate uptake rate, suggesting a viable means of calibrating the metabolic model. The application of the metabolic model to full-scale sludge also revealed that different Accumulibacter clades likely possess different acetate uptake mechanisms, as a correlation was observed between the energetic requirement for acetate transport across the cell membrane with the diversity of Accumulibacter present. Using the model as a predictive tool, it was shown that lower acetate concentrations in the feed as well as longer aerobic retention times favour the dominance of the TCA metabolism over glycolysis, which could explain why the anaerobic TCA pathway seems to be more relevant in full-scale WWTPs than in lab-scale systems.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Anaerobic TCA cycle; Glycogen accumulating organisms (GAOs); Glycolysis; Maintenance processes; Metabolic modelling; Polyphosphate accumulating organisms (PAOs)

Mesh:

Substances:

Year:  2014        PMID: 25222332     DOI: 10.1016/j.watres.2014.08.036

Source DB:  PubMed          Journal:  Water Res        ISSN: 0043-1354            Impact factor:   11.236


  5 in total

1.  Integrative microbial community analysis reveals full-scale enhanced biological phosphorus removal under tropical conditions.

Authors:  Yingyu Law; Rasmus Hansen Kirkegaard; Angel Anisa Cokro; Xianghui Liu; Krithika Arumugam; Chao Xie; Mikkel Stokholm-Bjerregaard; Daniela I Drautz-Moses; Per Halkjær Nielsen; Stefan Wuertz; Rohan B H Williams
Journal:  Sci Rep       Date:  2016-05-19       Impact factor: 4.379

Review 2.  Metabolic Modeling of Microbial Community Interactions for Health, Environmental and Biotechnological Applications.

Authors:  Kok Siong Ang; Meiyappan Lakshmanan; Na-Rae Lee; Dong-Yup Lee
Journal:  Curr Genomics       Date:  2018-12       Impact factor: 2.236

3.  Global Sensitivity Analysis of Metabolic Models for Phosphorus Accumulating Organisms in Enhanced Biological Phosphorus Removal.

Authors:  Minh Nguyen Quang; Tim Rogers; Jan Hofman; Ana B Lanham
Journal:  Front Bioeng Biotechnol       Date:  2019-10-04

4.  An improved ASM-GDA approach to evaluate the production kinetics of loosely bound and tightly bound extracellular polymeric substances in biological phosphorus removal process.

Authors:  Hai Cui; Shan-Shan Yang; Ji-Wei Pang; Hai-Rong Mi; Chen-Chen Nuer; Jie Ding
Journal:  RSC Adv       Date:  2020-01-14       Impact factor: 3.361

5.  Novel Self-driven Microbial Nutrient Recovery Cell with Simultaneous Wastewater Purification.

Authors:  Xi Chen; Dongya Sun; Xiaoyuan Zhang; Peng Liang; Xia Huang
Journal:  Sci Rep       Date:  2015-10-27       Impact factor: 4.379

  5 in total

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