Bacterial Thermodynamics for Modeling Biodegradation of Anthropogenic Compounds

0219330 VanBriesen拟议研究的目标是改进生物学模型，以便在涉及人工化合物的原位生物修复或异地生物处理的系统中预测微生物生长产量和化学计量比。一系列假设驱动的任务旨在评估当前人工化合物的可用产率、热力学和定量途径信息，并为这些化合物开发改进的微生物模型。工作的关键取决于这样一个假设，即最大理论细菌产量是细胞生长的基本参数，控制着天然和工程系统中生物降解途径对人造化合物的去除。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比，从而能够预测中间体的形成、共基质和营养物质的需求，以及可能影响系统生物地球化学的无机物种(例如O2、NH4+)的利用或生成。具体的研究目标是：1.评估在广泛的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工化合物。2.将这些数据汇编成一个可搜索的、可联网的微生物化学计量和动力学数据数据库。修改现有的基于热力学效率的产量和化学计量比预测方法，以解释观察到的人为化合物的生物降解机制。利用目标1中建立的数据库评估新开发的模型对多个微生物系统的预测能力。基于该项目开发的改进的模型结构将在生物生态系统建模、生物修复和微生物生态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价值。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，从而使我们受益。

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.