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Diagnosing and Predicting Mixed-Culture Fermentations with Unicellular and Guild-Based Metabolic Models
mSystems ( IF 6.4 ) Pub Date : 2020-09-29 , DOI: 10.1128/msystems.00755-20
Matthew J Scarborough 1, 2, 3 , Joshua J Hamilton 4 , Elizabeth A Erb 5 , Timothy J Donohue 6, 7 , Daniel R Noguera 2, 6
Affiliation  

Multispecies microbial communities determine the fate of materials in the environment and can be harnessed to produce beneficial products from renewable resources. In a recent example, fermentations by microbial communities have produced medium-chain fatty acids (MCFAs). Tools to predict, assess, and improve the performance of these communities, however, are limited. To provide such tools, we constructed two metabolic models of MCFA-producing microbial communities based on available genomic, transcriptomic, and metabolomic data. The first model is a unicellular model (iFermCell215), while the second model (iFermGuilds789) separates fermentation activities into functional guilds. Ethanol and lactate are fermentation products known to serve as substrates for MCFA production, while acetate is another common cometabolite during MCFA production. Simulations with iFermCell215 predict that low molar ratios of acetate to ethanol favor MCFA production, whereas the products of lactate and acetate coutilization are less dependent on the acetate-to-lactate ratio. In simulations of an MCFA-producing community fed a complex organic mixture derived from lignocellulose, iFermGuilds789 predicted that lactate was an extracellular cometabolite that served as a substrate for butyrate (C4) production. Extracellular hexanoic (C6) and octanoic (C8) acids were predicted by iFermGuilds789 to be from community members that directly metabolize sugars. Modeling results provide several hypotheses that can improve our understanding of microbial roles in an MCFA-producing microbiome and inform strategies to increase MCFA production. Further, these models represent novel tools for exploring the role of mixed microbial communities in carbon recycling in the environment, as well as in beneficial reuse of organic residues.

中文翻译:

使用单细胞和基于公会的代谢模型诊断和预测混合培养发酵

多物种微生物群落决定了材料在环境中的命运,并且可以利用可再生资源生产有益的产品。在最近的一个例子中,微生物群落的发酵产生了中链脂肪酸 (MCFA)。然而,用于预测、评估和改善这些社区绩效的工具是有限的。为了提供这样的工具,我们基于可用的基因组、转录组和代谢组数据构建了两个产生 MCFA 的微生物群落的代谢模型。第一个模型是单细胞模型 (iFermCell215),而第二个模型 (iFermGuilds789) 将发酵活动分为功能行会。乙醇和乳酸盐是已知用作 MCFA 生产底物的发酵产物,而乙酸盐是 MCFA 生产过程中的另一种常见共代谢物。iFermCell215 的模拟预测醋酸与乙醇的低摩尔比有利于 MCFA 的生产,而乳酸和醋酸共同利用的产物较少依赖于醋酸与乳酸的比率。在模拟来自木质纤维素的复杂有机混合物的 MCFA 生产群落中,iFermGuilds789 预测乳酸是一种细胞外共代谢物,可作为丁酸 (C4) 生产的底物。iFermGuilds789 预测细胞外己酸 (C6) 和辛酸 (C8) 来自直接代谢糖类的群落成员。建模结果提供了几个假设,可以提高我们对微生物在产生 MCFA 的微生物组中的作用的理解,并为增加 MCFA 产量的策略提供信息。更远,
更新日期:2020-09-29
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