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Structural and Functional Changes in Prokaryotic Communities in Artificial Pit Mud during Chinese Baijiu Production

The Chinese alcoholic beverage strong-flavor baijiu (SFB) gets its characteristic flavor during fermentation in cellars lined with pit mud. Microbes in the pit mud produce key precursors of flavor esters. The maturation time of natural pit mud of over 20 years has promoted attempts to produce artifi...

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Autores principales: Liu, Mao-Ke, Tang, Yu-Ming, Guo, Xiao-Jiao, Zhao, Ke, Penttinen, Petri, Tian, Xin-Hui, Zhang, Xin-Yu, Ren, Dao-Qun, Zhang, Xiao-Ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7093824/
https://www.ncbi.nlm.nih.gov/pubmed/32209718
http://dx.doi.org/10.1128/mSystems.00829-19
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author Liu, Mao-Ke
Tang, Yu-Ming
Guo, Xiao-Jiao
Zhao, Ke
Penttinen, Petri
Tian, Xin-Hui
Zhang, Xin-Yu
Ren, Dao-Qun
Zhang, Xiao-Ping
author_facet Liu, Mao-Ke
Tang, Yu-Ming
Guo, Xiao-Jiao
Zhao, Ke
Penttinen, Petri
Tian, Xin-Hui
Zhang, Xin-Yu
Ren, Dao-Qun
Zhang, Xiao-Ping
author_sort Liu, Mao-Ke
collection PubMed
description The Chinese alcoholic beverage strong-flavor baijiu (SFB) gets its characteristic flavor during fermentation in cellars lined with pit mud. Microbes in the pit mud produce key precursors of flavor esters. The maturation time of natural pit mud of over 20 years has promoted attempts to produce artificial pit mud (APM) with a shorter maturation time. However, knowledge about the molecular basis of APM microbial dynamics and associated functional variation during SFB brewing is limited, and the role of this variability in high-quality SFB production remains poorly understood. We studied APM maturation in new cellars until the fourth brewing batch using 16S rRNA gene amplicon sequencing, quantitative PCR, metaproteomics, and metabolomics techniques. A total of 36 prokaryotic classes and 195 genera were detected. Bacilli and Clostridia dominated consistently, and the relative abundance of Bacilli decreased along with the APM maturation. Even though both amplicon sequencing and quantitative PCR showed increased abundance of Clostridia, the levels of most of the Clostridium proteins were similar in both the first- and fourth-batch APM samples. Six genera correlated with eight or more major flavor compounds in SFB samples. Functional prediction suggested that the prokaryotic communities in the fourth-batch APM samples were actively engaged in organic acid metabolism, and the detected higher concentrations of proteins and metabolites in the corresponding metabolic pathways supported the prediction. This multi-omics approach captured changes in the abundances of specific microbial species, proteins, and metabolites during APM maturation, which are of great significance for the optimization of APM culture technique. IMPORTANCE Strong-flavor baijiu (SFB) accounts for more than 70% of all Chinese liquor production. In the Chinese baijiu brewing industry, artificial pit mud (APM) has been widely used since the 1960s to construct fermentation cellars for production of high-quality SFB. To gain insights at the systems level into the mechanisms driving APM prokaryotic taxonomic and functional dynamics and into how this variation is connected with high-quality SFB production, we performed the first combined metagenomic, metaproteomic, and metabolomic analyses of this brewing microecosystem. Together, the multi-omics approach enabled us to develop a more complete picture of the changing metabolic processes occurring in APM microbial communities during high-quality SFB production, which will be helpful for further optimization of APM culture technique and improvement of SFB quality.
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spelling pubmed-70938242020-04-02 Structural and Functional Changes in Prokaryotic Communities in Artificial Pit Mud during Chinese Baijiu Production Liu, Mao-Ke Tang, Yu-Ming Guo, Xiao-Jiao Zhao, Ke Penttinen, Petri Tian, Xin-Hui Zhang, Xin-Yu Ren, Dao-Qun Zhang, Xiao-Ping mSystems Research Article The Chinese alcoholic beverage strong-flavor baijiu (SFB) gets its characteristic flavor during fermentation in cellars lined with pit mud. Microbes in the pit mud produce key precursors of flavor esters. The maturation time of natural pit mud of over 20 years has promoted attempts to produce artificial pit mud (APM) with a shorter maturation time. However, knowledge about the molecular basis of APM microbial dynamics and associated functional variation during SFB brewing is limited, and the role of this variability in high-quality SFB production remains poorly understood. We studied APM maturation in new cellars until the fourth brewing batch using 16S rRNA gene amplicon sequencing, quantitative PCR, metaproteomics, and metabolomics techniques. A total of 36 prokaryotic classes and 195 genera were detected. Bacilli and Clostridia dominated consistently, and the relative abundance of Bacilli decreased along with the APM maturation. Even though both amplicon sequencing and quantitative PCR showed increased abundance of Clostridia, the levels of most of the Clostridium proteins were similar in both the first- and fourth-batch APM samples. Six genera correlated with eight or more major flavor compounds in SFB samples. Functional prediction suggested that the prokaryotic communities in the fourth-batch APM samples were actively engaged in organic acid metabolism, and the detected higher concentrations of proteins and metabolites in the corresponding metabolic pathways supported the prediction. This multi-omics approach captured changes in the abundances of specific microbial species, proteins, and metabolites during APM maturation, which are of great significance for the optimization of APM culture technique. IMPORTANCE Strong-flavor baijiu (SFB) accounts for more than 70% of all Chinese liquor production. In the Chinese baijiu brewing industry, artificial pit mud (APM) has been widely used since the 1960s to construct fermentation cellars for production of high-quality SFB. To gain insights at the systems level into the mechanisms driving APM prokaryotic taxonomic and functional dynamics and into how this variation is connected with high-quality SFB production, we performed the first combined metagenomic, metaproteomic, and metabolomic analyses of this brewing microecosystem. Together, the multi-omics approach enabled us to develop a more complete picture of the changing metabolic processes occurring in APM microbial communities during high-quality SFB production, which will be helpful for further optimization of APM culture technique and improvement of SFB quality. American Society for Microbiology 2020-03-24 /pmc/articles/PMC7093824/ /pubmed/32209718 http://dx.doi.org/10.1128/mSystems.00829-19 Text en Copyright © 2020 Liu et al. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Liu, Mao-Ke
Tang, Yu-Ming
Guo, Xiao-Jiao
Zhao, Ke
Penttinen, Petri
Tian, Xin-Hui
Zhang, Xin-Yu
Ren, Dao-Qun
Zhang, Xiao-Ping
Structural and Functional Changes in Prokaryotic Communities in Artificial Pit Mud during Chinese Baijiu Production
title Structural and Functional Changes in Prokaryotic Communities in Artificial Pit Mud during Chinese Baijiu Production
title_full Structural and Functional Changes in Prokaryotic Communities in Artificial Pit Mud during Chinese Baijiu Production
title_fullStr Structural and Functional Changes in Prokaryotic Communities in Artificial Pit Mud during Chinese Baijiu Production
title_full_unstemmed Structural and Functional Changes in Prokaryotic Communities in Artificial Pit Mud during Chinese Baijiu Production
title_short Structural and Functional Changes in Prokaryotic Communities in Artificial Pit Mud during Chinese Baijiu Production
title_sort structural and functional changes in prokaryotic communities in artificial pit mud during chinese baijiu production
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7093824/
https://www.ncbi.nlm.nih.gov/pubmed/32209718
http://dx.doi.org/10.1128/mSystems.00829-19
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