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

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:
$15.0万
依托单位:
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
项目状态:
已结题
起止时间:
2014-10-01 至 2018-12-31

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项目成果

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中文摘要
翻译
合作研究:利用13c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[j]:温子友(爱荷华州立大学)唐银杰(华盛顿大学圣路易斯分校)提案id: 1438042(文),1438125(唐)摘要目前主要使用的是糖基原料还是富油作物?美国生物燃料产业。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),然后将这些气体分子发酵成燃料(如乙醇)。本项目旨在解决合成气发酵中的两个重要的基本问题:1。气态底物(CO、CO2和H2)进入微生物的传质限制;2. 微生物将合成气转化为生物燃料的瓶颈酶。本研究将进一步推进合成气发酵的系统生物学研究。通过将宏观合成气传质条件与生物燃料生产微生物的细胞内酶反应速率联系起来,将提供合成气发酵的整体观点。最终,该项目还将为开发其他气转液生物精炼厂提供指导方针。瞬态13C技术和代谢模型将用于研究碳梭菌的合成气传质和生物利用。第一项任务将包括13C示踪,以准确确定气液传质参数并分析其对细胞碳同化的影响。第二项任务将是开发通量平衡模型,以预测微生物生长和乙醇生产对生物反应器控制参数的响应,如气体流速和混合。第三项任务将包括在通量模型预测的条件下进行中试规模的合成气发酵。本项目将测定复杂发酵条件下不同合成气组分的传质系数(KLa),提高对不同生物反应器操作下气态底物生物利用度的认识。同时,13c辅助通量平衡分析也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思路。这项研究是爱荷华州立大学和圣路易斯华盛顿大学合作进行的。这些具有互补技能的pi将为学生提供优秀的培训和跨学科教育机会(包括暑期研究,研讨会,国际研究等),以学习反应工程,生物加工,分析化学和代谢建模。
英文摘要
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.
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Transition: Metabolomics-driven understanding of rules that coordinate metabolic responses and adaptive evolution of synthetic biology chassis
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    2320104
  • 项目类别:
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  • 资助金额:
    $75.0万
  • 财政年份:
    2023
  • 负责人:
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  • 依托单位:
URoL:EN: A non-parametric framework to understand emergent behaviors of microbial consortia
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  • 资助金额:
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  • 财政年份:
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  • 依托单位:
Development of a machine learning pipeline for assisting strain design of nonmodel yeasts
  • 批准号:
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  • 项目类别:
    Standard Grant
  • 资助金额:
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EAGER: Collaborative Research: Integrating microtome sectioning with isotopic tracing to study biotransformation in synthetic Escherichia coli biofilms
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  • 资助金额:
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国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
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  • 负责人:
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  • 依托单位:
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