Collaborative Research: Use of 13C-labeling and flux modeling to analyze metabolic reactions and gas-liquid mass transfer during syngas fermentations

合作研究：使用 13C 标记和通量模型来分析合成气发酵过程中的代谢反应和气液传质

• 批准号: 1438125
• 负责人: Yinjie Tang
• 金额: $ 15万
• 依托单位: Washington University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-10-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1438125&HistoricalAwards=false
• 关键词: Collaborative; Research; Use; 13C; labeling

Collaborative Research: Use of 13C-labeling and flux modeling to analyze metabolic reactions and gas-liquid mass transfer during syngas fermentationsPI: Ziyou Wen (Iowa State University)Yinjie Tang (Washington University at St. Louis)Proposal IDs: 1438042 (Wen), 1438125 (Tang)AbstractSugar-based feedstocks or oil-rich crops are primarily used in today?s biofuel industry. These biofuel production approaches pose a threat to the global food supply. As an alternative, this research will use inexpensive lignocellulosic biomass (e.g., corn stover or switchgrass) as a feedstock for producing biofuel. The conversion process proposed is based on the gasification of the biomass into syngas (mainly CO, CO2 and H2), and the subsequent fermentation of those gaseous molecules into fuels (such as ethanol). The objectives of this project aim to address two important fundamental issues in syngas fermentations: 1. the mass transfer limitations of transporting gaseous substrates (CO, CO2 and H2) into microbes; 2. the bottleneck enzymes in microbes to convert syngas into biofuels. This study will advance the current research on syngas fermentation using methods in systems biology. By linking macroscopic syngas mass transfer conditions to intracellular enzyme reaction rates in biofuel producing microbes, a holistic view of syngas fermentation will be provided. Ultimately, this project will also produce guidelines for developing other gas-to-liquid biorefineries.Transient 13C techniques and metabolic models will be used to examine syngas mass transfer and biological utilization by Clostridium carboxidivorans. The first task will incorporate 13C tracing to accurately determine gas-liquid mass transfer parameters and analyze their influence on cellular carbon assimilation. The second task will be to develop a flux balance model to predict microbial growth and ethanol production in response to bioreactor control parameters, such as gas flow rate and mixing. The third task will include pilot scale syngas fermentation at the flux-model-predicted conditions. This project will determine the mass transfer coefficient (KLa) of different syngas composition under complex fermentation conditions, and improve the understandings of the bioavailability of gaseous substrates under various bioreactor operations. Meanwhile, 13C-assisted flux balance analysis will also reveal key enzymatic reactions, which control syngas bioconversion into ethanol. The combination of a metabolic flux model with gas-liquid mass transfer dynamics will offer rational approaches for further work in syngas fermentation development. This research is a partnership between Iowa State University and Washington University in St. Louis. The PIs, with their complementary skills, will provide excellent training and interdisciplinary educational opportunities (including summer research, workshop, international studies, etc.) for students to study reaction engineering, bioprocessing, analytical chemistry, and metabolic modeling.

合作研究：利用13 C标记和通量模型分析合成气发酵过程中的代谢反应和气液传质PI：温子友（爱荷华州州立大学）唐银杰（华盛顿大学圣路易斯分校）提案ID：1438042（文），1438125（唐）摘要当今主要使用糖基原料还是富含油的作物？生物燃料产业。这些生物燃料生产方法对全球粮食供应构成威胁。作为替代方案，这项研究将使用廉价的木质纤维素生物质（例如，玉米秸秆或柳枝稷）作为生产生物燃料的原料。提出的转化过程是基于生物质气化成合成气（主要是CO，CO2和H2），以及随后将这些气体分子发酵成燃料（如乙醇）。该项目的目标旨在解决合成气发酵中的两个重要的基本问题：1。将气态底物（CO、CO2和H2）输送到微生物中的传质限制; 2.微生物中将合成气转化为生物燃料的瓶颈酶。本研究将推动目前合成气发酵的系统生物学方法的研究。通过将宏观合成气传质条件与生物燃料生产微生物中的细胞内酶反应速率联系起来，将提供合成气发酵的整体视图。最终，该项目还将为开发其他气-液生物精炼厂提供指导。瞬态13 C技术和代谢模型将用于研究合成气传质和Clostridium carboxidivorans的生物利用。第一个任务将结合13 C示踪，以准确地确定气液传质参数，并分析其对细胞碳同化的影响。第二个任务将是开发一个通量平衡模型，以预测微生物的生长和乙醇的生产响应生物反应器的控制参数，如气体流速和混合。第三个任务将包括在通量模型预测条件下的中试规模合成气发酵。本项目将测定复杂发酵条件下不同合成气组成的传质系数（KLa），提高对不同生物反应器操作条件下气态底物生物利用度的认识。同时，13 C辅助通量平衡分析还将揭示控制合成气生物转化为乙醇的关键酶促反应。代谢通量模型与气液传质动力学的结合将为合成气发酵的进一步研究提供合理的途径。这项研究是由爱荷华州州立大学和圣路易斯的华盛顿大学合作进行的。PI凭借其互补的技能，将提供出色的培训和跨学科教育机会（包括夏季研究，研讨会，国际研究等）。为学生学习反应工程，生物加工，分析化学和代谢建模。