Proteomic Analysis of a Bacterial Consortium during Biodegradation of Chemical Mixtures (TSE-03N)

化学混合物生物降解过程中细菌群落的蛋白质组学分析 (TSE-03N)

• 批准号: 0329514
• 负责人: Kenneth Reardon
• 金额: $ 9.98万
• 依托单位: Colorado State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-02-01 至 2006-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0329514&HistoricalAwards=false
• 关键词: Proteomic; Analysis; Bacterial; Consortium; during

Kenneth F ReardonColorado State University0329514Assessment of Proteomics as a Tool to Improve Performance of Biological Waste Treatment Processes (TSE03-N; Exploratory Proposal) Engineered environmental bioprocesses (e.g., wastewater treatment, in situ bioremediation) rely almost exclusively on microbial communities. However, the complexity of these communities can make it very difficult to appropriately design, control, and trouble-shoot those processes based on microbial parameters; instead, observed chemical changes must be monitored and biological factors inferred from them. This can lead to poor control and fault diagnosis, and does not allow optimization of the microbial consortium involved. Over the past 20 years, the use of nucleic acid-based methods has proven to be valuable to understand certain aspects of microbial communities. Nonetheless, these methods have significant limitations, primarily because ribosomal DNA analysis reveals an organism's phylogeny instead of its function, and the latter is far more important for engineering applications. The goal of this exploratory project is to obtain initial evidence of the type and utility of data that can be obtained by a proteomics analysis of a model waste treatment bioreactor. Specific objectives are (1) to demonstrate the ability to obtain 2-dimensional electrophoresis images from mixed culture samples, (2) to use pattern recognition techniques from computer science to determine whether protein markers of significant process changes can be identified, and (3) to compare these proteomic data with 16S rDNA population analysis and chemical concentrations. The project objectives will be achieved by analyzing samples from a model bio treatment system: a mixed-culture bioreactor degrading a mixture of organics that is subjected to different environmental perturbations (feed composition, pH, and toxin), and samples analyzed for proteome profiles, population composition, and organic chemical composition. This research is of significance and intellectual merit because it would produce the first evaluation of a new approach to analysis of environmental bioprocesses, with potential to reveal new information on the function of a microbial consortium with which to improve a bioprocess.

Kenneth F Reardon科罗拉多州立大学0329514蛋白质组学评估作为提高生物废物处理过程性能的工具（TSE03-N；探索性提案）工程环境生物过程（例如废水处理、原位生物修复）几乎完全依赖于微生物群落。然而，这些群落的复杂性使得根据微生物参数适当地设计、控制和排除这些过程变得非常困难；相反，必须监测观察到的化学变化，并从中推断出生物因素。这可能导致控制和故障诊断不良，并且不允许优化所涉及的微生物群落。在过去的 20 年里，基于核酸的方法的使用已被证明对于了解微生物群落的某些方面非常有价值。尽管如此，这些方法也有很大的局限性，主要是因为核糖体 DNA 分析揭示了生物体的系统发育而不是其功能，而后者对于工程应用来说更为重要。 该探索性项目的目标是获得数据类型和效用的初步证据，这些数据可以通过模型废物处理生物反应器的蛋白质组学分析获得。具体目标是 (1) 证明从混合培养样品中获取二维电泳图像的能力，(2) 使用计算机科学的模式识别技术来确定是否可以识别显着过程变化的蛋白质标记，以及 (3) 将这些蛋白质组数据与 16S rDNA 群体分析和化学浓度进行比较。该项目的目标将通过分析来自模型生物处理系统的样品来实现：混合培养生物反应器降解受到不同环境扰动（饲料成分、pH 和毒素）的有机物混合物，并对样品进行蛋白质组图谱、群体组成和有机化学成分分析。 这项研究具有重要意义和智力价值，因为它将首次评估环境生物过程分析的新方法，并有可能揭示有关微生物群落功能的新信息，从而改善生物过程。