Bacterial Thermodynamics for Modeling Biodegradation of Anthropogenic Compounds

用于模拟人为化合物生物降解的细菌热力学

• 批准号: 0219330
• 负责人: Jeanne VanBriesen
• 金额: $ 32.98万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-04-01 至 2007-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0219330&HistoricalAwards=false
• 关键词: Bacterial; Thermodynamics; Modeling; Biodegradation; Anthropogenic

0219330 VanBriesen The goal of the proposed research is to improve biological models for prediction of microbiological growth yield and stoichiometry in systems involving in situ bioremediation or ex situ biotreatment of anthropogenic compounds. A series of hypothesis-driven tasks are designed to evaluate current available yield, thermodynamic, and quantitative pathway information for anthropogenic compounds and to develop improved microbiological models for these compounds.The crux of the work depends upon the hypothesis that maximum theoretical bacterial yield is a fundamental parameter of cell growth that controls the removalof anthropogenic compounds by biodegradation pathways in natural and engineered systems. Further, bacterial yield, coupled with the principle of mass balance, specifies the stoichiometry of biodegradation, thus allowing prediction of the formation of intermediates, the requirement of co-substrates and nutrients, and the utilization or generation of inorganic species (e.g., O2, NH4 + ) that can affect the system biogeochemistry.Specific research objectives are to:1. Evaluate the available yield data for microbiological systems growing under a wide range of environmental conditions and using a wide variety of natural and anthropogenic compounds. Compile these data into a searchable, web-enabled database for microbiological stoichiometric and kinetic data.2. Modify an existing thermodynamic efficiency-based yield and stoichiometry prediction methodology to account for biodegradation mechanisms observed for anthropogenic compounds.3. Evaluate the predictive ability of the newly developed model for multiple microbial systems using the database generated in objective 1.The improved model structures developed on this project will have widespread utility in biological ecosystem modeling, bioremediation and microbial ecology modeling, and biotechnology and engineered bioprocess modeling. Modeling in all these fields will improve our understanding of the complexity of living systems and will enhance our ability to control this complexity to our benefit.

0219330 范布里森 拟议的研究的目标是改善生物模型的预测微生物的生长产量和化学计量的系统，涉及在原位生物修复或非原位生物处理的人为化合物。一系列的假设驱动的任务，旨在评估目前可用的产量，热力学和定量途径的人为化合物的信息，并开发这些化合物的改进的微生物模型，工作的关键取决于假设，即最大理论细菌产量是细胞生长的基本参数，控制removalof人为化合物的生物降解途径在自然和工程系统。此外，细菌产量与质量平衡原理相结合，规定了生物降解的化学计量，从而允许预测中间体的形成、共基质和营养物的需求以及无机物质（例如，O2、NH4 +）对系统的生物化学特性的影响。评估在各种环境条件下生长的微生物系统的可用产量数据，并使用各种天然和人为化合物。将这些数据编译成一个可搜索的网络数据库，用于微生物化学计量和动力学数据。修改现有的基于热力学效率的产量和化学计量预测方法，以解释人为化合物的生物降解机制。利用目标1中生成的数据库评价新开发的多微生物系统模型的预测能力。本项目开发的改进模型结构将在生物生态系统建模、生物修复和微生物生态学建模以及生物技术和工程生物过程建模中具有广泛的实用性。所有这些领域的建模将提高我们对生命系统复杂性的理解，并将增强我们控制这种复杂性的能力。