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通过基因预测对受控发酵系统中丁酸盐产生的见解。

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

作者信息

Esquivel-Elizondo S, Ilhan Z E, Garcia-Peña E I, Krajmalnik-Brown R

机构信息

Biodesign Swette Center for Environmental Biotechnology, Arizona State University, Tempe, Arizona, USA.

School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, Arizona, USA.

出版信息

mSystems. 2017 Jul 18;2(4). doi: 10.1128/mSystems.00051-17. eCollection 2017 Jul-Aug.

Abstract

Butyrate is a common fatty acid produced in important fermentative systems, such as the human/animal gut and other H 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 (PH). 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. , , and were the most abundant phylotypes in the closed system without PH control, whereas , , and were the most abundant phylotypes under continuous operation at low PH. Putative butyrate producers identified in our system were from , , , and . 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., ), acetate (i.e., and ), and lactate producers (i.e., and ) took place under continuous-flow operation at low PH. 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 PH 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.

摘要

丁酸盐是在重要的发酵系统中产生的一种常见脂肪酸,如人类/动物肠道和其他产氢系统。尽管其很重要,但关于丁酸盐产生菌与其他细菌之间的伙伴关系的信息却很少。这项工作的目的是在一个旨在生产丁酸盐的受控发酵系统中揭示产生丁酸盐的微生物群落和可能的代谢途径。产丁酸反应器在37°C和pH 5.5下运行,水力停留时间为31小时,氢气分压较低(PH)。通过高通量测序和基于16S rRNA数据的宏基因组功能预测表明,在分批(封闭)和连续模式运行期间,丁酸盐产生途径和微生物群落有所不同。在没有PH控制的封闭系统中,[具体菌属1]、[具体菌属2]和[具体菌属3]是最丰富的系统发育型,而在低PH连续运行条件下,[具体菌属4]、[具体菌属5]和[具体菌属6]是最丰富的系统发育型。在我们的系统中鉴定出的推定丁酸盐产生菌来自[具体菌属7]、[具体菌属8]、[具体菌属9]和[具体菌属10]。宏基因组预测分析表明,非产丁酸微生物通过产生丁酸盐前体如乙酸盐、乳酸盐和琥珀酸盐来影响丁酸盐的产生。16S rRNA基因分析表明,在反应器中,在低PH连续流运行条件下,已鉴定的产丁酸微生物与琥珀酸盐(即[具体菌属11])、乙酸盐(即[具体菌属12]和[具体菌属13])以及乳酸盐产生菌(即[具体菌属14]和[具体菌属15])之间存在伙伴关系。 这项研究展示了生物信息学工具,如基于16S rRNA基因的宏基因组功能预测,如何有助于理解生物系统并揭示受控系统(如生物反应器)中的微生物相互作用。从受控系统获得的结果比从人类/动物研究获得的结果更容易解释,因为观察到的变化可能具体归因于施加在系统上的设计条件。当我们在一个精心控制的发酵系统中系统地改变PH时,生物信息学分析使我们能够识别潜在的产丁酸系统发育型和相关的丁酸盐代谢途径。由于丁酸盐是人类/动物结肠健康中的主要产物和关键脂肪酸,我们的见解可能适用于生物制氢系统和肠道模型中的丁酸盐生产研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd32/5516221/7470fa80dbe8/sys0041721200001.jpg

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