GOALI: Development of Spatiotemporal Metabolic Models for Syngas Fermentation in Industrial Bubble Column Reactors

制造可再生液体燃料和化学品最有前途的途径之一是由特殊的微生物对废碳进行发酵。这不仅可以实现先进的生物燃料和可再生化学生产，还可以帮助减少碳排放。气体发酵技术的商业化发展正由LanzaTech等新兴公司引领，但要进一步推动该技术走向经济竞争力，还必须解决许多基础研究问题。一个特别重要的挑战是开发综合代谢和运输模型，以描述工业上相关的气泡塔反应器中的气体发酵。这种时空代谢模型的发展是一个新兴的研究问题，在环境科学、生物技术、生物能源和人类健康方面具有许多潜在的应用。这个GOALI项目的目标是开发时空代谢建模的通用工具，并通过在气泡塔反应器中应用来评估这些方法。PIs计划将富含CO的废物流以及合成气（合成气-主要由H2/CO/CO2组成）转化为气泡塔反应器中的液体燃料和化学品。他提出的建模方法包括将物种代谢的基因组尺度重建与控制空间变化系统中相关对流和/或扩散过程的传输方程相结合。由此产生的模型包括细胞内代谢的线性程序嵌入在细胞外环境的空间和动态变化的部分不同方程中。马萨诸塞大学将开发有效的模型公式和强大的数值解决技术，使用气体发酵和生物膜生长问题作为硅测试平台。合成气发酵模型将与LanzaTech合作开发，LanzaTech是气体发酵和气泡柱反应器技术的行业领导者。这些模型将结合最近开发的合成气发酵杆菌的基因组尺度代谢重建，以及原料气成分和主要代谢副产物乙醇和醋酸盐的对流输运方程来制定。在马萨诸塞大学进行初步测试后，合成气发酵模型将使用从LanzaTech实验室/试点设施收集的数据进行验证。利用这些数据，时空代谢模型将根据需要进行细化，以捕捉工业气泡塔反应器的关键特征。更广泛的影响：拟议的研究将推动基础研究和影响工业实践。虽然在时空代谢建模方面已经发表了一些孤立的论文，但我们的研究将对这一重要问题产生相当广泛的处理。我们期望在合成气发酵方面的应用工作能够产生新的计算工具来模拟、设计和优化工业气泡塔反应器。由美国国家科学基金资助的麻省大学研究生将在LanzaTech完成为期四个月的实习。在伊利诺斯州斯科奇的研究机构参与数据收集，并执行模型改进和验证。学生将由两位项目调查员共同指导，Henson教授（UMass， PI）领导方法开发工作，Griffin博士（LanzaTech, co-PI）监督气泡柱模型开发工作。在LanzaTech期间，学生将在高度多学科和团队导向的环境中与众多科学家和工程师一起工作。UMass和LanzaTech的紧密整合将通过频繁的电子邮件交流、两周一次的视频会议和两年一次的项目会议来实现。至少有两名本科生将参与研究，由资助的博士生担任部分指导角色。这些学生将与麻省生物燃料研究所（TIMBR）资助的其他学生互动，并参加正在进行的TIMBR活动。

Henson - 1511346One of the most promising routes to renewable liquid fuels and chemicals is the fermentation of waste carbon by specialized microbes. This can not only enable advanced biofuel and renewable chemical production but could also help reduce carbon emissions. Commercial development of gas fermentation technology is being led by emerging companies such as LanzaTech, but many fundamental research problems must be addressed to further advance the technology towards economic competitiveness. A particularly important challenge is to develop integrated metabolic and transport models that describe gas fermentation in industrially relevant bubble column reactors. The development of such spatiotemporal metabolic models is an emerging research problem with numerous potential applications in environmental science, biotechnology, bioenergy and human health. The objectives of this GOALI project are to develop general tools for spatiotemporal metabolic modeling and to evaluate the methods through application to gas fermentation in bubble column reactors.The PIs plan to convert CO-rich waste streams as well as synthesis gas (syngas - mainly comprised of H2/CO/CO2) to liquid fuels and chemicals in bubble column reactors. His proposed modeling approach involves combining genome-scale reconstructions of species metabolism with transport equations that govern the relevant convective and/or diffusional processes within the spatially varying system. The resulting models consist of linear programs for intracellular metabolism embedded within partial different equations for spatial and dynamic variations within the extracellular environment. UMass will develop efficient model formulation and robust numerical solution techniques using gas fermentation and biofilm growth problems as in silico testbeds. The syngas fermentation models will be developed in collaboration with LanzaTech, an industrial leader in gas fermentation and bubble column reactor technology. These models will be formulated by combining a recently developed genome-scale metabolic reconstruction of the syngas fermenting bacterium Clostridium ljungdahlii with convective transport equations for the feed gas components and the major metabolic byproducts, ethanol and acetate. Following initial testing at UMass, the syngas fermentation models will be validated with data collected from a LanzaTech laboratory/pilot facility. Using these data, the spatiotemporal metabolic models will be refined as necessary to capture the key features of industrial bubble column reactors.Broader Impacts: The proposed research will both advance fundamental research and impact industrial practice. While a few isolated papers have been published on spatiotemporal metabolic modeling, our research will produce a considerably more general treatment of this important problem. We expect the application work focused on syngas fermentation to produce new computational tools to simulate, design and optimize industrial bubble column reactors. The UMass graduate student supported by NSF funds will complete a four month internship at LanzaTech?s Skokie, IL research facility to participate in data collection and to perform model refinement and validation. The student will be co-advised by the two project investigators, with Prof. Henson (UMass, PI) leading the methods development work and Dr. Griffin (LanzaTech, co-PI) overseeing the bubble column model development work. While at LanzaTech, the student will work with a broad array of scientists and engineers in a highly multidisciplinary and team oriented environment. Tight integration of the UMass and LanzaTech efforts will be achieved through frequent email exchanges, biweekly videoconferences and biannual project meetings. At least two undergraduate students will participate in the research by having the funded Ph.D. student serve a partial advising role. These students will interact with other students funded through the Institute of Massachusetts Biofuels Research (TIMBR) and participate in ongoing TIMBR activities.