Exploring the Role of Active Functional Microbiota in Flavor Generation by Integrated Metatranscriptomics and Metabolomics during Niulanshan Baijiu Fermentation

Active functional microbiota for producing volatile flavors is critical to Chinese baijiu fermentation. Microbial communities correlated with the volatile metabolites are generally explored using DNA-based sequencing and metabolic analysis. However, the active functional microbiota related to the vo...
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Autor*in:	Yuanyuan Pan [verfasserIn] Ying Wang [verfasserIn] Wenjun Hao [verfasserIn] Sen Zhou [verfasserIn] Chengbao Duan [verfasserIn] Qiushi Li [verfasserIn] Jinwang Wei [verfasserIn] Gang Liu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	light-flavor baijiu metatranscriptomics active functional microbiota untargeted metabolomics flavor generation fermented grain

Übergeordnetes Werk:	In: Foods - MDPI AG, 2013, 12(2023), 22, p 4140
Übergeordnetes Werk:	volume:12 ; year:2023 ; number:22, p 4140

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/foods12224140

Katalog-ID:	DOAJ101246013

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520			\|a Active functional microbiota for producing volatile flavors is critical to Chinese baijiu fermentation. Microbial communities correlated with the volatile metabolites are generally explored using DNA-based sequencing and metabolic analysis. However, the active functional microbiota related to the volatile flavor compounds is poorly understood. In this study, an integrated metatranscriptomic and metabolomics analysis was employed to unravel the metabolite profiles comprehensively and the contributing active functional microbiota for flavor generation during Niulanshan baijiu fermentation. A total of 395, 83, and 181 compounds were annotated using untargeted metabolomics, including LC-MS, GC-MS, and HS-SPME-GC-MS, respectively. Significant variances were displayed in the composition of compounds among different time-point samples according to the heatmaps and orthogonal partial least-square discriminant analysis. The correlation between the active microbiota and the volatile flavors was analyzed based on the bidirectional orthogonal partial least squares discriminant analysis (O2PLS-DA) model. Six bacterial genera, including <i<Streptococcus</i<, <i<Lactobacillus</i<, <i<Pediococcus</i<, <i<Campylobacter</i<, <i<Yersinia,</i< and <i<Weissella</i<, and five fungal genera of <i<Talaromyces</i<, <i<Aspergillus</i<, <i<Mixia</i<, <i<Rhizophagus,</i< and <i<Gloeophyllum</i< were identified as the active functional microbiota for producing the volatile flavors. In summary, this study revealed the active functional microbial basis of unique flavor formation and provided novel insights into the optimization of Niulanshan baijiu fermentation.
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spelling	10.3390/foods12224140 doi (DE-627)DOAJ101246013 (DE-599)DOAJ4a7308a86a4f41bf8ae89f6515c77004 DE-627 ger DE-627 rakwb eng TP1-1185 Yuanyuan Pan verfasserin aut Exploring the Role of Active Functional Microbiota in Flavor Generation by Integrated Metatranscriptomics and Metabolomics during Niulanshan Baijiu Fermentation 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Active functional microbiota for producing volatile flavors is critical to Chinese baijiu fermentation. Microbial communities correlated with the volatile metabolites are generally explored using DNA-based sequencing and metabolic analysis. However, the active functional microbiota related to the volatile flavor compounds is poorly understood. In this study, an integrated metatranscriptomic and metabolomics analysis was employed to unravel the metabolite profiles comprehensively and the contributing active functional microbiota for flavor generation during Niulanshan baijiu fermentation. A total of 395, 83, and 181 compounds were annotated using untargeted metabolomics, including LC-MS, GC-MS, and HS-SPME-GC-MS, respectively. Significant variances were displayed in the composition of compounds among different time-point samples according to the heatmaps and orthogonal partial least-square discriminant analysis. The correlation between the active microbiota and the volatile flavors was analyzed based on the bidirectional orthogonal partial least squares discriminant analysis (O2PLS-DA) model. Six bacterial genera, including <i<Streptococcus</i<, <i<Lactobacillus</i<, <i<Pediococcus</i<, <i<Campylobacter</i<, <i<Yersinia,</i< and <i<Weissella</i<, and five fungal genera of <i<Talaromyces</i<, <i<Aspergillus</i<, <i<Mixia</i<, <i<Rhizophagus,</i< and <i<Gloeophyllum</i< were identified as the active functional microbiota for producing the volatile flavors. In summary, this study revealed the active functional microbial basis of unique flavor formation and provided novel insights into the optimization of Niulanshan baijiu fermentation. light-flavor baijiu metatranscriptomics active functional microbiota untargeted metabolomics flavor generation fermented grain Chemical technology Ying Wang verfasserin aut Wenjun Hao verfasserin aut Sen Zhou verfasserin aut Chengbao Duan verfasserin aut Qiushi Li verfasserin aut Jinwang Wei verfasserin aut Gang Liu verfasserin aut In Foods MDPI AG, 2013 12(2023), 22, p 4140 (DE-627)737287632 (DE-600)2704223-6 23048158 nnns volume:12 year:2023 number:22, p 4140 https://doi.org/10.3390/foods12224140 kostenfrei https://doaj.org/article/4a7308a86a4f41bf8ae89f6515c77004 kostenfrei https://www.mdpi.com/2304-8158/12/22/4140 kostenfrei https://doaj.org/toc/2304-8158 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2023 22, p 4140
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allfieldsGer	10.3390/foods12224140 doi (DE-627)DOAJ101246013 (DE-599)DOAJ4a7308a86a4f41bf8ae89f6515c77004 DE-627 ger DE-627 rakwb eng TP1-1185 Yuanyuan Pan verfasserin aut Exploring the Role of Active Functional Microbiota in Flavor Generation by Integrated Metatranscriptomics and Metabolomics during Niulanshan Baijiu Fermentation 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Active functional microbiota for producing volatile flavors is critical to Chinese baijiu fermentation. Microbial communities correlated with the volatile metabolites are generally explored using DNA-based sequencing and metabolic analysis. However, the active functional microbiota related to the volatile flavor compounds is poorly understood. In this study, an integrated metatranscriptomic and metabolomics analysis was employed to unravel the metabolite profiles comprehensively and the contributing active functional microbiota for flavor generation during Niulanshan baijiu fermentation. A total of 395, 83, and 181 compounds were annotated using untargeted metabolomics, including LC-MS, GC-MS, and HS-SPME-GC-MS, respectively. Significant variances were displayed in the composition of compounds among different time-point samples according to the heatmaps and orthogonal partial least-square discriminant analysis. The correlation between the active microbiota and the volatile flavors was analyzed based on the bidirectional orthogonal partial least squares discriminant analysis (O2PLS-DA) model. Six bacterial genera, including <i<Streptococcus</i<, <i<Lactobacillus</i<, <i<Pediococcus</i<, <i<Campylobacter</i<, <i<Yersinia,</i< and <i<Weissella</i<, and five fungal genera of <i<Talaromyces</i<, <i<Aspergillus</i<, <i<Mixia</i<, <i<Rhizophagus,</i< and <i<Gloeophyllum</i< were identified as the active functional microbiota for producing the volatile flavors. In summary, this study revealed the active functional microbial basis of unique flavor formation and provided novel insights into the optimization of Niulanshan baijiu fermentation. light-flavor baijiu metatranscriptomics active functional microbiota untargeted metabolomics flavor generation fermented grain Chemical technology Ying Wang verfasserin aut Wenjun Hao verfasserin aut Sen Zhou verfasserin aut Chengbao Duan verfasserin aut Qiushi Li verfasserin aut Jinwang Wei verfasserin aut Gang Liu verfasserin aut In Foods MDPI AG, 2013 12(2023), 22, p 4140 (DE-627)737287632 (DE-600)2704223-6 23048158 nnns volume:12 year:2023 number:22, p 4140 https://doi.org/10.3390/foods12224140 kostenfrei https://doaj.org/article/4a7308a86a4f41bf8ae89f6515c77004 kostenfrei https://www.mdpi.com/2304-8158/12/22/4140 kostenfrei https://doaj.org/toc/2304-8158 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2023 22, p 4140
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callnumber-first	T - Technology
author	Yuanyuan Pan
spellingShingle	Yuanyuan Pan misc TP1-1185 misc light-flavor baijiu misc metatranscriptomics misc active functional microbiota misc untargeted metabolomics misc flavor generation misc fermented grain misc Chemical technology Exploring the Role of Active Functional Microbiota in Flavor Generation by Integrated Metatranscriptomics and Metabolomics during Niulanshan Baijiu Fermentation
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topic_title	TP1-1185 Exploring the Role of Active Functional Microbiota in Flavor Generation by Integrated Metatranscriptomics and Metabolomics during Niulanshan Baijiu Fermentation light-flavor baijiu metatranscriptomics active functional microbiota untargeted metabolomics flavor generation fermented grain
topic	misc TP1-1185 misc light-flavor baijiu misc metatranscriptomics misc active functional microbiota misc untargeted metabolomics misc flavor generation misc fermented grain misc Chemical technology
topic_unstemmed	misc TP1-1185 misc light-flavor baijiu misc metatranscriptomics misc active functional microbiota misc untargeted metabolomics misc flavor generation misc fermented grain misc Chemical technology
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title	Exploring the Role of Active Functional Microbiota in Flavor Generation by Integrated Metatranscriptomics and Metabolomics during Niulanshan Baijiu Fermentation
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title_full	Exploring the Role of Active Functional Microbiota in Flavor Generation by Integrated Metatranscriptomics and Metabolomics during Niulanshan Baijiu Fermentation
author_sort	Yuanyuan Pan
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author_browse	Yuanyuan Pan Ying Wang Wenjun Hao Sen Zhou Chengbao Duan Qiushi Li Jinwang Wei Gang Liu
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title_sort	exploring the role of active functional microbiota in flavor generation by integrated metatranscriptomics and metabolomics during niulanshan baijiu fermentation
callnumber	TP1-1185
title_auth	Exploring the Role of Active Functional Microbiota in Flavor Generation by Integrated Metatranscriptomics and Metabolomics during Niulanshan Baijiu Fermentation
abstract	Active functional microbiota for producing volatile flavors is critical to Chinese baijiu fermentation. Microbial communities correlated with the volatile metabolites are generally explored using DNA-based sequencing and metabolic analysis. However, the active functional microbiota related to the volatile flavor compounds is poorly understood. In this study, an integrated metatranscriptomic and metabolomics analysis was employed to unravel the metabolite profiles comprehensively and the contributing active functional microbiota for flavor generation during Niulanshan baijiu fermentation. A total of 395, 83, and 181 compounds were annotated using untargeted metabolomics, including LC-MS, GC-MS, and HS-SPME-GC-MS, respectively. Significant variances were displayed in the composition of compounds among different time-point samples according to the heatmaps and orthogonal partial least-square discriminant analysis. The correlation between the active microbiota and the volatile flavors was analyzed based on the bidirectional orthogonal partial least squares discriminant analysis (O2PLS-DA) model. Six bacterial genera, including <i<Streptococcus</i<, <i<Lactobacillus</i<, <i<Pediococcus</i<, <i<Campylobacter</i<, <i<Yersinia,</i< and <i<Weissella</i<, and five fungal genera of <i<Talaromyces</i<, <i<Aspergillus</i<, <i<Mixia</i<, <i<Rhizophagus,</i< and <i<Gloeophyllum</i< were identified as the active functional microbiota for producing the volatile flavors. In summary, this study revealed the active functional microbial basis of unique flavor formation and provided novel insights into the optimization of Niulanshan baijiu fermentation.
abstractGer	Active functional microbiota for producing volatile flavors is critical to Chinese baijiu fermentation. Microbial communities correlated with the volatile metabolites are generally explored using DNA-based sequencing and metabolic analysis. However, the active functional microbiota related to the volatile flavor compounds is poorly understood. In this study, an integrated metatranscriptomic and metabolomics analysis was employed to unravel the metabolite profiles comprehensively and the contributing active functional microbiota for flavor generation during Niulanshan baijiu fermentation. A total of 395, 83, and 181 compounds were annotated using untargeted metabolomics, including LC-MS, GC-MS, and HS-SPME-GC-MS, respectively. Significant variances were displayed in the composition of compounds among different time-point samples according to the heatmaps and orthogonal partial least-square discriminant analysis. The correlation between the active microbiota and the volatile flavors was analyzed based on the bidirectional orthogonal partial least squares discriminant analysis (O2PLS-DA) model. Six bacterial genera, including <i<Streptococcus</i<, <i<Lactobacillus</i<, <i<Pediococcus</i<, <i<Campylobacter</i<, <i<Yersinia,</i< and <i<Weissella</i<, and five fungal genera of <i<Talaromyces</i<, <i<Aspergillus</i<, <i<Mixia</i<, <i<Rhizophagus,</i< and <i<Gloeophyllum</i< were identified as the active functional microbiota for producing the volatile flavors. In summary, this study revealed the active functional microbial basis of unique flavor formation and provided novel insights into the optimization of Niulanshan baijiu fermentation.
abstract_unstemmed	Active functional microbiota for producing volatile flavors is critical to Chinese baijiu fermentation. Microbial communities correlated with the volatile metabolites are generally explored using DNA-based sequencing and metabolic analysis. However, the active functional microbiota related to the volatile flavor compounds is poorly understood. In this study, an integrated metatranscriptomic and metabolomics analysis was employed to unravel the metabolite profiles comprehensively and the contributing active functional microbiota for flavor generation during Niulanshan baijiu fermentation. A total of 395, 83, and 181 compounds were annotated using untargeted metabolomics, including LC-MS, GC-MS, and HS-SPME-GC-MS, respectively. Significant variances were displayed in the composition of compounds among different time-point samples according to the heatmaps and orthogonal partial least-square discriminant analysis. The correlation between the active microbiota and the volatile flavors was analyzed based on the bidirectional orthogonal partial least squares discriminant analysis (O2PLS-DA) model. Six bacterial genera, including <i<Streptococcus</i<, <i<Lactobacillus</i<, <i<Pediococcus</i<, <i<Campylobacter</i<, <i<Yersinia,</i< and <i<Weissella</i<, and five fungal genera of <i<Talaromyces</i<, <i<Aspergillus</i<, <i<Mixia</i<, <i<Rhizophagus,</i< and <i<Gloeophyllum</i< were identified as the active functional microbiota for producing the volatile flavors. In summary, this study revealed the active functional microbial basis of unique flavor formation and provided novel insights into the optimization of Niulanshan baijiu fermentation.
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title_short	Exploring the Role of Active Functional Microbiota in Flavor Generation by Integrated Metatranscriptomics and Metabolomics during Niulanshan Baijiu Fermentation
url	https://doi.org/10.3390/foods12224140 https://doaj.org/article/4a7308a86a4f41bf8ae89f6515c77004 https://www.mdpi.com/2304-8158/12/22/4140 https://doaj.org/toc/2304-8158
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The correlation between the active microbiota and the volatile flavors was analyzed based on the bidirectional orthogonal partial least squares discriminant analysis (O2PLS-DA) model. Six bacterial genera, including <i<Streptococcus</i<, <i<Lactobacillus</i<, <i<Pediococcus</i<, <i<Campylobacter</i<, <i<Yersinia,</i< and <i<Weissella</i<, and five fungal genera of <i<Talaromyces</i<, <i<Aspergillus</i<, <i<Mixia</i<, <i<Rhizophagus,</i< and <i<Gloeophyllum</i< were identified as the active functional microbiota for producing the volatile flavors. 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Exploring the Role of Active Functional Microbiota in Flavor Generation by Integrated Metatranscriptomics and Metabolomics during Niulanshan Baijiu Fermentation

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