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通过体外代谢工程从生物质中高产制氢:混合糖共利用及动力学建模

High-yield hydrogen production from biomass by in vitro metabolic engineering: Mixed sugars coutilization and kinetic modeling.

作者信息

Rollin Joseph A, Martin del Campo Julia, Myung Suwan, Sun Fangfang, You Chun, Bakovic Allison, Castro Roberto, Chandrayan Sanjeev K, Wu Chang-Hao, Adams Michael W W, Senger Ryan S, Zhang Y-H Percival

机构信息

Department of Biological Systems Engineering, Virginia Tech, Blacksburg, VA 24061; Cell-Free Bioinnovations, Blacksburg, VA 24060;

Department of Biological Systems Engineering, Virginia Tech, Blacksburg, VA 24061;

出版信息

Proc Natl Acad Sci U S A. 2015 Apr 21;112(16):4964-9. doi: 10.1073/pnas.1417719112. Epub 2015 Apr 6.

Abstract

The use of hydrogen (H2) as a fuel offers enhanced energy conversion efficiency and tremendous potential to decrease greenhouse gas emissions, but producing it in a distributed, carbon-neutral, low-cost manner requires new technologies. Herein we demonstrate the complete conversion of glucose and xylose from plant biomass to H2 and CO2 based on an in vitro synthetic enzymatic pathway. Glucose and xylose were simultaneously converted to H2 with a yield of two H2 per carbon, the maximum possible yield. Parameters of a nonlinear kinetic model were fitted with experimental data using a genetic algorithm, and a global sensitivity analysis was used to identify the enzymes that have the greatest impact on reaction rate and yield. After optimizing enzyme loadings using this model, volumetric H2 productivity was increased 3-fold to 32 mmol H2⋅L(-1)⋅h(-1). The productivity was further enhanced to 54 mmol H2⋅L(-1)⋅h(-1) by increasing reaction temperature, substrate, and enzyme concentrations--an increase of 67-fold compared with the initial studies using this method. The production of hydrogen from locally produced biomass is a promising means to achieve global green energy production.

摘要

将氢气(H₂)用作燃料可提高能量转换效率,并具有减少温室气体排放的巨大潜力,但以分布式、碳中和、低成本的方式生产氢气需要新技术。在此,我们展示了基于体外合成酶途径将植物生物质中的葡萄糖和木糖完全转化为H₂和CO₂。葡萄糖和木糖同时转化为H₂,每碳产生两个H₂,这是可能的最大产量。使用遗传算法将非线性动力学模型的参数与实验数据进行拟合,并通过全局敏感性分析来确定对反应速率和产量影响最大的酶。使用该模型优化酶负载后,氢气的体积生产率提高了3倍,达到32 mmol H₂·L⁻¹·h⁻¹。通过提高反应温度、底物和酶浓度,生产率进一步提高到54 mmol H₂·L⁻¹·h⁻¹,与使用该方法的初始研究相比提高了67倍。利用本地生产的生物质生产氢气是实现全球绿色能源生产的一种有前景的方式。

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