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Ecogenomics-Based Mass Balance Model Reveals the Effects of Fermentation Conditions on Microbial Activity

Fermentation of waste activated sludge (WAS) is an alternative approach to reduce solid wastes while providing valuable soluble products, such as volatile fatty acids and alcohols. This study systematically identified optimal fermentation conditions and key microbial populations by conducting two se...

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Autores principales: Kim, Jinha, Mei, Ran, Wilson, Fernanda P., Yuan, Heyang, Bocher, Benjamin T. W., Liu, Wen-Tso
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7738435/
https://www.ncbi.nlm.nih.gov/pubmed/33343535
http://dx.doi.org/10.3389/fmicb.2020.595036
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author Kim, Jinha
Mei, Ran
Wilson, Fernanda P.
Yuan, Heyang
Bocher, Benjamin T. W.
Liu, Wen-Tso
author_facet Kim, Jinha
Mei, Ran
Wilson, Fernanda P.
Yuan, Heyang
Bocher, Benjamin T. W.
Liu, Wen-Tso
author_sort Kim, Jinha
collection PubMed
description Fermentation of waste activated sludge (WAS) is an alternative approach to reduce solid wastes while providing valuable soluble products, such as volatile fatty acids and alcohols. This study systematically identified optimal fermentation conditions and key microbial populations by conducting two sets of experiments under different combinations of biochemical and physical parameters. Based on fermentation product concentrations, methane production, and solid removal, fermentation performance was enhanced under the combined treatments of inoculum heat shock (>60°C), pH 5, 55°C, and short solid retention time (<10 days). An ecogenomics-based mass balance (EGMB) approach was used to determine the net growth rates of individual microbial populations, and classified them into four microbial groups: known syntrophs, known methanogens, fermenters, and WAS-associated populations. Their growth rates were observed to be affected by the treatment conditions. The growth rates of syntrophs and fermenters, such as Syntrophomonas and Parabacteroides increased with a decrease in SRT. In contrast, treatment conditions, such as inoculum heat shock and high incubation temperature inhibited the growth of WAS-associated populations, such as Terrimonas and Bryobacter. There were also populations insensitive to the treatment conditions, such as those related to Microbacter and Rikenellaceae. Overall, the EGMB approach clearly revealed the ecological roles of important microbial guilds in the WAS fermentation system, and guided the selection of optimal conditions for WAS fermentation in future pilot-scale operation.
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spelling pubmed-77384352020-12-17 Ecogenomics-Based Mass Balance Model Reveals the Effects of Fermentation Conditions on Microbial Activity Kim, Jinha Mei, Ran Wilson, Fernanda P. Yuan, Heyang Bocher, Benjamin T. W. Liu, Wen-Tso Front Microbiol Microbiology Fermentation of waste activated sludge (WAS) is an alternative approach to reduce solid wastes while providing valuable soluble products, such as volatile fatty acids and alcohols. This study systematically identified optimal fermentation conditions and key microbial populations by conducting two sets of experiments under different combinations of biochemical and physical parameters. Based on fermentation product concentrations, methane production, and solid removal, fermentation performance was enhanced under the combined treatments of inoculum heat shock (>60°C), pH 5, 55°C, and short solid retention time (<10 days). An ecogenomics-based mass balance (EGMB) approach was used to determine the net growth rates of individual microbial populations, and classified them into four microbial groups: known syntrophs, known methanogens, fermenters, and WAS-associated populations. Their growth rates were observed to be affected by the treatment conditions. The growth rates of syntrophs and fermenters, such as Syntrophomonas and Parabacteroides increased with a decrease in SRT. In contrast, treatment conditions, such as inoculum heat shock and high incubation temperature inhibited the growth of WAS-associated populations, such as Terrimonas and Bryobacter. There were also populations insensitive to the treatment conditions, such as those related to Microbacter and Rikenellaceae. Overall, the EGMB approach clearly revealed the ecological roles of important microbial guilds in the WAS fermentation system, and guided the selection of optimal conditions for WAS fermentation in future pilot-scale operation. Frontiers Media S.A. 2020-12-02 /pmc/articles/PMC7738435/ /pubmed/33343535 http://dx.doi.org/10.3389/fmicb.2020.595036 Text en Copyright © 2020 Kim, Mei, Wilson, Yuan, Bocher and Liu. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Kim, Jinha
Mei, Ran
Wilson, Fernanda P.
Yuan, Heyang
Bocher, Benjamin T. W.
Liu, Wen-Tso
Ecogenomics-Based Mass Balance Model Reveals the Effects of Fermentation Conditions on Microbial Activity
title Ecogenomics-Based Mass Balance Model Reveals the Effects of Fermentation Conditions on Microbial Activity
title_full Ecogenomics-Based Mass Balance Model Reveals the Effects of Fermentation Conditions on Microbial Activity
title_fullStr Ecogenomics-Based Mass Balance Model Reveals the Effects of Fermentation Conditions on Microbial Activity
title_full_unstemmed Ecogenomics-Based Mass Balance Model Reveals the Effects of Fermentation Conditions on Microbial Activity
title_short Ecogenomics-Based Mass Balance Model Reveals the Effects of Fermentation Conditions on Microbial Activity
title_sort ecogenomics-based mass balance model reveals the effects of fermentation conditions on microbial activity
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7738435/
https://www.ncbi.nlm.nih.gov/pubmed/33343535
http://dx.doi.org/10.3389/fmicb.2020.595036
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