Dataset Information

Integrating Genome-Resolved Metagenomics with Trait-Based Process Modeling to Determine Biokinetics of Distinct Nitrifying Communities within Activated Sludge.

ABSTRACT: Conventional bioprocess models for wastewater treatment are based on aggregated bulk biomass concentrations and do not incorporate microbial physiological diversity. Such a broad aggregation of microbial functional groups can fail to predict ecosystem dynamics when high levels of physiological diversity exist within trophic guilds. For instance, functional diversity among nitrite-oxidizing bacteria (NOB) can obfuscate engineering strategies for their out-selection in activated sludge (AS), which is desirable to promote energy-efficient nitrogen removal. Here, we hypothesized that different NOB populations within AS can have different physiological traits that drive process performance, which we tested by estimating biokinetic growth parameters using a combination of highly replicated respirometry, genome-resolved metagenomics, and process modeling. A lab-scale AS reactor subjected to a selective pressure for over 90 days experienced resilience of NOB activity. We recovered three coexisting Nitrospira population genomes belonging to two sublineages, which exhibited distinct growth strategies and underwent a compositional shift following the selective pressure. A trait-based process model calibrated at the NOB genus level better predicted nitrite accumulation than a conventional process model calibrated at the NOB guild level. This work demonstrates that trait-based modeling can be leveraged to improve our prediction, control, and design of functionally diverse microbiomes driving key environmental biotechnologies.

SUBMITTER: Sampara P

PROVIDER: S-EPMC9387530 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Integrating Genome-Resolved Metagenomics with Trait-Based Process Modeling to Determine Biokinetics of Distinct Nitrifying Communities within Activated Sludge.

Sampara Pranav P Luo Yaqian Y Lin Xuan X Ziels Ryan M RM

Environmental science & technology 20220805 16

Conventional bioprocess models for wastewater treatment are based on aggregated bulk biomass concentrations and do not incorporate microbial physiological diversity. Such a broad aggregation of microbial functional groups can fail to predict ecosystem dynamics when high levels of physiological diversity exist within trophic guilds. For instance, functional diversity among nitrite-oxidizing bacteria (NOB) can obfuscate engineering strategies for their out-selection in activated sludge (AS), which ...[more]

PMID: 35929783

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Dataset Information

Integrating Genome-Resolved Metagenomics with Trait-Based Process Modeling to Determine Biokinetics of Distinct Nitrifying Communities within Activated Sludge.

Publications

Integrating Genome-Resolved Metagenomics with Trait-Based Process Modeling to Determine Biokinetics of Distinct Nitrifying Communities within Activated Sludge.

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