Geomicrobial kinetics: a genome-scale metabolic modeling approach

这位研究人员建议开发一种新的建模方法来解决地球生物学中一个引人注目的问题-微生物过程在自然环境中进行的速度有多快？目前的方法使用Monod方程和其他实验室培养模型来预测环境中的微生物速率。但与在人工培养基中培养不同，自然微生物面临着营养供应有限和波动的挑战，因此必须调节生化途径，微调新陈代谢的速度和效率。为了将代谢途径和调控引入微生物速率的预测，研究人员将开发一种新的建模方法，明确将微生物基因组学与地球化学联系起来。这种建模方法可以回答这样一个问题--微生物过程在自然环境中进行的速度有多快？该项目为高中生提供学习机会，支持一名博士和两名本科生。新方法将整个细胞内的酶反应分为分解代谢和生物合成两个网络。它用酶动力学模拟分解代谢网络，用通量平衡分析模拟生物合成网络。模拟的输出范围从细胞水平的酶和代谢物浓度到生物体水平的微生物速率。研究人员将应用这一新方法，结合生物地球化学反应模型，模拟具有代表性的地下微生物群--乙酰裂解产甲烷菌的代谢，并研究地质环境中的产甲烷动力学。这一新方法代表着一项重要的尝试，即超越经典的基于Monod方程的模型，转向基于组学的新陈代谢方法来分析和预测地质环境中的微生物过程。具体地说，这种新方法从基因组和环境的地球化学预测微生物动力学和酶的表达，而不需要纯粹的培养或实验室实验。因此，这种方法为研究地质环境的微生物过程提供了一种新的、潜在的强大方法，特别是那些无法在现场准确分析或在实验室中忠实重建的神秘过程。

The investigator proposes to develop a new modeling method to address a compelling question in geobiology - how fast do microbial processes proceed in natural environments? Current methods predict microbial rates in the environment using Monod equation and other models of laboratory cultures. But unlike cultures grown in synthetic media, natural microbes face the challenge of limited and fluctuating availability of nutrients, and thus have to regulate biochemical pathways and to fine-tune the rate and efficiency of metabolism. To bring metabolic pathways and regulations into the prediction of microbial rates, the investigator will develop a new modeling method that explicitly links microbial genomics to geochemistry. This modeling approach would allow to answer the question - how fast do microbial processes proceed in natural environments? The project offers learning opportunities to high school students and supports one Ph.D. and two undergraduate students.The new method groups enzyme reactions within entire cells into two networks of catabolism and biosynthesis. It simulates the catabolic network using enzyme kinetics and biosynthesis network using flux balance analysis. The output of the simulation ranges from enzyme and metabolite concentrations at cellular level to microbial rates at organismal level. The investigator will apply the new method, coupled to biogeochemical reaction modeling, to simulate the metabolism of acetoclastic methanogens, a representative group of subsurface microbes, and to investigate the kinetics of methanogenesis in geological environments. The new method represents an important attempt to move beyond classical Monod equation-based models, toward an omics-enabled metabolism-based approach to the analysis and prediction of microbial processes in geological environments. Specifically, the new method predicts microbial kinetics and enzyme expression from genome and geochemistry of the environment, without the need of pure culture or laboratory experiment. This method therefore offers a new, and potentially powerful, method for studying microbial processes of geological environments, especially those cryptic processes that cannot be accurately analyzed in the field or faithfully reconstructed in the laboratory.