Insights into Butyrate Production in a Controlled Fermentation System via Gene Predictions

ABSTRACT Butyrate is a common fatty acid produced in important fermentative systems, such as the human/animal gut and other H2 production systems. Despite its importance, there is little information on the partnerships between butyrate producers and other bacteria. The objective of this work was to...

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Autores principales:	S. Esquivel-Elizondo, Z. E. Ilhan, E. I. Garcia-Peña, R. Krajmalnik-Brown
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2017
Materias:	butyrate production pathways PICRUSt Prevotellaceae hydrogen partial pressure interconversion reactions predicted metagenome functional content Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/3cca76d15afb4a6ba6c00755ac6620be
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spelling	oai:doaj.org-article:3cca76d15afb4a6ba6c00755ac6620be2021-12-02T19:45:30ZInsights into Butyrate Production in a Controlled Fermentation System via Gene Predictions10.1128/mSystems.00051-172379-5077https://doaj.org/article/3cca76d15afb4a6ba6c00755ac6620be2017-08-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00051-17https://doaj.org/toc/2379-5077ABSTRACT Butyrate is a common fatty acid produced in important fermentative systems, such as the human/animal gut and other H2 production systems. Despite its importance, there is little information on the partnerships between butyrate producers and other bacteria. The objective of this work was to uncover butyrate-producing microbial communities and possible metabolic routes in a controlled fermentation system aimed at butyrate production. The butyrogenic reactor was operated at 37°C and pH 5.5 with a hydraulic retention time of 31 h and a low hydrogen partial pressure (PH2). High-throughput sequencing and metagenome functional prediction from 16S rRNA data showed that butyrate production pathways and microbial communities were different during batch (closed) and continuous-mode operation. Lactobacillaceae, Lachnospiraceae, and Enterococcaceae were the most abundant phylotypes in the closed system without PH2 control, whereas Prevotellaceae, Ruminococcaceae, and Actinomycetaceae were the most abundant phylotypes under continuous operation at low PH2. Putative butyrate producers identified in our system were from Prevotellaceae, Clostridiaceae, Ruminococcaceae, and Lactobacillaceae. Metagenome prediction analysis suggests that nonbutyrogenic microorganisms influenced butyrate production by generating butyrate precursors such as acetate, lactate, and succinate. 16S rRNA gene analysis suggested that, in the reactor, a partnership between identified butyrogenic microorganisms and succinate (i.e., Actinomycetaceae), acetate (i.e., Ruminococcaceae and Actinomycetaceae), and lactate producers (i.e., Ruminococcaceae and Lactobacillaceae) took place under continuous-flow operation at low PH2. IMPORTANCE This study demonstrates how bioinformatics tools, such as metagenome functional prediction from 16S rRNA genes, can help understand biological systems and reveal microbial interactions in controlled systems (e.g., bioreactors). Results obtained from controlled systems are easier to interpret than those from human/animal studies because observed changes may be specifically attributed to the design conditions imposed on the system. Bioinformatics analysis allowed us to identify potential butyrogenic phylotypes and associated butyrate metabolism pathways when we systematically varied the PH2 in a carefully controlled fermentation system. Our insights may be adapted to butyrate production studies in biohydrogen systems and gut models, since butyrate is a main product and a crucial fatty acid in human/animal colon health.S. Esquivel-ElizondoZ. E. IlhanE. I. Garcia-PeñaR. Krajmalnik-BrownAmerican Society for Microbiologyarticlebutyrate production pathwaysPICRUStPrevotellaceaehydrogen partial pressureinterconversion reactionspredicted metagenome functional contentMicrobiologyQR1-502ENmSystems, Vol 2, Iss 4 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	butyrate production pathways PICRUSt Prevotellaceae hydrogen partial pressure interconversion reactions predicted metagenome functional content Microbiology QR1-502
spellingShingle	butyrate production pathways PICRUSt Prevotellaceae hydrogen partial pressure interconversion reactions predicted metagenome functional content Microbiology QR1-502 S. Esquivel-Elizondo Z. E. Ilhan E. I. Garcia-Peña R. Krajmalnik-Brown Insights into Butyrate Production in a Controlled Fermentation System via Gene Predictions
description	ABSTRACT Butyrate is a common fatty acid produced in important fermentative systems, such as the human/animal gut and other H2 production systems. Despite its importance, there is little information on the partnerships between butyrate producers and other bacteria. The objective of this work was to uncover butyrate-producing microbial communities and possible metabolic routes in a controlled fermentation system aimed at butyrate production. The butyrogenic reactor was operated at 37°C and pH 5.5 with a hydraulic retention time of 31 h and a low hydrogen partial pressure (PH2). High-throughput sequencing and metagenome functional prediction from 16S rRNA data showed that butyrate production pathways and microbial communities were different during batch (closed) and continuous-mode operation. Lactobacillaceae, Lachnospiraceae, and Enterococcaceae were the most abundant phylotypes in the closed system without PH2 control, whereas Prevotellaceae, Ruminococcaceae, and Actinomycetaceae were the most abundant phylotypes under continuous operation at low PH2. Putative butyrate producers identified in our system were from Prevotellaceae, Clostridiaceae, Ruminococcaceae, and Lactobacillaceae. Metagenome prediction analysis suggests that nonbutyrogenic microorganisms influenced butyrate production by generating butyrate precursors such as acetate, lactate, and succinate. 16S rRNA gene analysis suggested that, in the reactor, a partnership between identified butyrogenic microorganisms and succinate (i.e., Actinomycetaceae), acetate (i.e., Ruminococcaceae and Actinomycetaceae), and lactate producers (i.e., Ruminococcaceae and Lactobacillaceae) took place under continuous-flow operation at low PH2. IMPORTANCE This study demonstrates how bioinformatics tools, such as metagenome functional prediction from 16S rRNA genes, can help understand biological systems and reveal microbial interactions in controlled systems (e.g., bioreactors). Results obtained from controlled systems are easier to interpret than those from human/animal studies because observed changes may be specifically attributed to the design conditions imposed on the system. Bioinformatics analysis allowed us to identify potential butyrogenic phylotypes and associated butyrate metabolism pathways when we systematically varied the PH2 in a carefully controlled fermentation system. Our insights may be adapted to butyrate production studies in biohydrogen systems and gut models, since butyrate is a main product and a crucial fatty acid in human/animal colon health.
format	article
author	S. Esquivel-Elizondo Z. E. Ilhan E. I. Garcia-Peña R. Krajmalnik-Brown
author_facet	S. Esquivel-Elizondo Z. E. Ilhan E. I. Garcia-Peña R. Krajmalnik-Brown
author_sort	S. Esquivel-Elizondo
title	Insights into Butyrate Production in a Controlled Fermentation System via Gene Predictions
title_short	Insights into Butyrate Production in a Controlled Fermentation System via Gene Predictions
title_full	Insights into Butyrate Production in a Controlled Fermentation System via Gene Predictions
title_fullStr	Insights into Butyrate Production in a Controlled Fermentation System via Gene Predictions
title_full_unstemmed	Insights into Butyrate Production in a Controlled Fermentation System via Gene Predictions
title_sort	insights into butyrate production in a controlled fermentation system via gene predictions
publisher	American Society for Microbiology
publishDate	2017
url	https://doaj.org/article/3cca76d15afb4a6ba6c00755ac6620be
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Insights into Butyrate Production in a Controlled Fermentation System via Gene Predictions

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