Physiological adaptation of growth kinetics in activated sludge

Friedrich, Michael W.; Takács, Imre; Tränckner, Jens

doi:10.1016/j.watres.2015.08.010

Cited by 35 publications

(6 citation statements)

References 27 publications

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“…The estimated half rate constant for all N species was 1 μM, which is in the same range as those reported in literature. ,− The maximum rate constant ( V ) is different from literature values because it is normalized to functional enzyme abundance, whereas this parameter in Monod-type models is normalized to biomass. The estimated parameter for biomass and enzyme decay was 0.01 and 0.005 h –1 , respectively, which were similar to those reported in the literature. ,− …”

Section: Results and Discussionsupporting

confidence: 85%

Functional Enzyme-Based Approach for Linking Microbial Community Functions with Biogeochemical Process Kinetics

Qian

Gao

et al. 2017

Environ. Sci. Technol.

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The kinetics of biogeochemical processes in natural and engineered environmental systems is typically described using Monod-type or modified Monod-type models. These models rely on biomass as surrogates for functional enzymes in microbial communities that catalyze biogeochemical reactions. A major challenge of applying such models is the difficulty of quantitatively measuring functional biomass for the constraining and validation of the models. However, omics-based approaches have been increasingly used to characterize microbial community structure, functions, and metabolites. Here, we propose an enzyme-based model that can incorporate omics data to link microbial community functions with biogeochemical process kinetics. The model treats enzymes as time-variable catalysts for biogeochemical reactions and applies a biogeochemical reaction network to incorporate intermediate metabolites. The sequences of genes and proteins from metagenomes, as well as those from the UniProt database, were used for targeted enzyme quantification and to provide insights into the dynamic linkage among functional genes, enzymes, and metabolites that are required in the model. The application of the model was demonstrated using denitrification, as an example, by comparing model simulations with measured functional enzymes, genes, denitrification substrates, and intermediates.

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Section: Results and Discussionsupporting

confidence: 85%

Functional Enzyme-Based Approach for Linking Microbial Community Functions with Biogeochemical Process Kinetics

Qian

Gao

et al. 2017

Environ. Sci. Technol.

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“…The substrate consumption rate of the entire activated sludge community is often monitored through respirogram bulk tests (i.e., biomass normalized maximal oxygen uptake rate (OUR) analyses)65 and has been previously reported to slow with increasing MRT50,66, suggesting an adaptation of the community. Our model allows predicting the instantaneous substrate utilization rate (k theo ), and the previously published slowing trend is not observed from the initial default parameters (modelled k theo of 5.0 and 5.8 d -1 at 1 and 15 d, respectively).…”

Section: Resultsmentioning

confidence: 99%

Microbial residence time is a controlling parameter of the taxonomic composition and functional profile of microbial communities

et al. 2019

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A remaining challenge within microbial ecology is to understand the determinants of richness and diversity observed in environmental microbial communities. In a range of systems, including activated sludge bioreactors, the microbial residence time (MRT) has been previously shown to shape the microbial community composition. However, the physiological and ecological mechanisms driving this influence have remained unclear. Here, this relationship is explored by analyzing an activated sludge system fed with municipal wastewater. Using a model designed in this study based on Monod-growth kinetics, longer MRTs were shown to increase the range of growth parameters that enable persistence, resulting in increased richness and diversity in the modelled community. In laboratory experiments, six sequencing batch reactors treating domestic wastewater were operated in parallel at MRTs between 1-15 d. The communities were characterized using both 16S ribosomal RNA and non-target messenger RNA sequencing (metatranscriptomic analysis), and model-predicted monotonic increases in richness were confirmed in both profiles. Accordingly, taxonomic Shannon diversity also increased with MRT. In contrast, the diversity in enzyme class annotations resulting from the metatranscriptomic analysis displayed a non-monotonic trend over the MRT gradient. Disproportionately high abundances of transcripts encoding for rarer enzymes occur at longer MRTs and contribute to the disconnect between taxonomic and functional diversity profiles.

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“…The results showed that long starvation periods in the investigated biofilms are linked to a significant lower decay rate of just a tenth of the recommended decay rate used in the ASM [12]. Experiments with activated sludge support these findings [22,23]. Actually, both decay rate and particulate inert fraction are rather a function of nutritional state than a constant.…”

Section: Discussionmentioning

confidence: 52%

“…These are rather mechanistic assumptions and only valid for systems with rather low load variations. Current research in activated sludge systems proved that both the X E fraction [22] and the decay rate b H [23] are a function of sludge retention time SRT (i.e., function of substrate supply). Due to this observation at extreme conditions of low COD, the question arises if organisms can adapt their decay rate and the assumption of a constant decay rate has to be reconsidered or if the existing ASM has to be extended with an additional very slowly degradable COD fraction (consisting of "hard" external COD and/or cell-internal reserves) and according degradation process.…”

Section: Introductionmentioning

confidence: 99%

Development of Decay in Biofilms under Starvation Conditions—Rethinking of the Biomass Model

Cramer

Tränckner

2020

Water

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The study investigates the decay of heterotrophic biomass in biofilms under starvation conditions based on measurements of the oxygen uptake rate (OUR). Original incentive was to understand the preservation of active biomass in SBR-trickling filter systems (SBR-TFS), treating event-based occurring, organically polluted stormwater. In comparison with activated sludge systems, the analyzed biofilm carrier of SBR trickling filters showed an astonishing low decay rate of 0.025 d−1, that allows the biocenosis to withstand long periods of starvation. In activated sludge modeling, biomass decay is regarded as first order kinetics with a 10 times higher constant decay rate (0.17–0.24 d−1, depending on the model used). In lab-scale OUR measurements, the degradation of biofilm layers led to wavy sequence of biomass activity. After long starvation, the initial decay rate (comparable to activated sludge model (ASM) approaches) dropped by a factor of 10. This much lower decay rate is supported by experiments comparing the maximum OUR in pilot-scale biofilm systems before and after longer starvation periods. These findings require rethinking of the approach of single-stage decay rate approach usually used in conventional activated sludge modelling, at least for the investigated conditions: the actual decay rate is apparently much lower than assumed, but is overshadowed by degradation of either cell-internal substrate and/or the ability to tap “ultra-slow” degradable chemical oxygen demand (COD) fractions. For the intended stormwater treatment, this allows the application of technical biofilm systems, even for long term dynamics of wastewater generation.

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Physiological adaptation of growth kinetics in activated sludge

Cited by 35 publications

References 27 publications

Functional Enzyme-Based Approach for Linking Microbial Community Functions with Biogeochemical Process Kinetics

Functional Enzyme-Based Approach for Linking Microbial Community Functions with Biogeochemical Process Kinetics

Microbial residence time is a controlling parameter of the taxonomic composition and functional profile of microbial communities

Development of Decay in Biofilms under Starvation Conditions—Rethinking of the Biomass Model

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