Integrating genome-scale metabolic models into the prediction of microbial kinetics in natural environments
Integrating genome-scale metabolic models into the prediction of microbial kinetics in natural environments
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DOI：
10.1016/j.gca.2018.08.047
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发表时间：
2018-12
影响因子：
5
通讯作者：
B. Shapiro;T. Hoehler;Q. Jin
中科院分区：
文献类型：
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作者：
B. Shapiro;T. Hoehler;Q. Jin
我们提出了一种新的方法来预测微生物代谢率在自然环境中使用基因组规模的代谢模型。该方法是现有方法的混合，即，速率定律和通量平衡分析（FBA）。它解释了环境中化学能和生长营养物质的可用性，并将FBA独立地应用于基因组尺度代谢模型的呼吸和生物合成途径。我们说明了新的方法，通过模拟代谢的一个代表性的产甲烷菌-巴氏甲烷八叠球菌-在实验室反应器和原始和生物刺激含水层。实验室应用表明，混合方法预测的整体细胞代谢和跟踪，明确，碳和能量的细胞通量内的个别生化反应的速率。含水层的应用表明，在自然系统中的产甲烷菌的增长可能会受到多种因素的限制，包括能源和生长营养物质，并受到李比希的最小值定律的限制。这些结果突出了新方法在生态地球化学反应模拟中的改进，包括其对从富营养到贫营养的不同环境的适用性。
We propose a new method to predict microbial metabolic rates in natural environments using genome-scale metabolic models. This method is a hybrid of existing approaches, i.e., rate laws and flux balance analysis (FBA). It accounts for the availabilities of chemical energy and growth nutrients in the environment, and applies FBA independently to the respiration and biosynthesis pathways of genome-scale metabolic models. We illustrate the new method by modeling the metabolism of a representative methanogen –Methanosarcina barkeri– in laboratory reactors and in pristine and biostimulated aquifers. The laboratory application demonstrates that the hybrid method predicts the rates of individual biochemical reactions within overall cell metabolism and tracks, explicitly, cellular fluxes of carbon and energy. The aquifer applications reveal that the growth of methanogens in natural systems can be limited by multiple factors, including energy sources and growth nutrients, and that the limitations are subject to Liebig’s Law of the Minimum. These results highlight the improvements of the new method in biogeochemical reaction modeling, including its applicability to diverse environments, from eutrophic to oligotrophic.