Molecular Insight into Polyaromatic Toxicant Degradation by Microbial Communities

微生物世界是多样化的，因为它有37亿年的进化历史，这为 未发现的代谢能力的机遇，包括污染物降解能力，以及 检测并恢复此活动。众所周知，超过99%的微生物世界没有 已被培养，因此仍未被发现。我们建议探索和恢复两个密钥的基因 细菌DNA中氯代多环芳香化合物脱毒的生物降解步骤 这种未经培养的微生物多样性，然后使用这项研究的分子标记来帮助 污染场地生物降解的场地评估和定量预测。我们是 以还原脱卤酶和芳香族加氧酶为关键功能恢复以来 它们通常是多氯二恶英降解的限速步骤和 二苯并呋喃、多氯联苯和多环芳烃(PAHs)，超级基金关注的化学品 我们的书房。我们的具体目标是：(1)探索和恢复大自然的催化多样性，目标是 开发这些多芳香族化合物的微生物代谢能力的全面概况， (2)利用最有效的印刷电路板异种伯克霍尔德氏菌LB400的基因组序列信息 降解剂，以研究对这些化学物质的降解重要的代谢特征和(3)，开发 基于贝叶斯概率网络的生物降解性定量诊断工具 受污染的场地。我们建议使用富集物来帮助识别功能活跃的种群和 因此，使用稳定同位素探测从活跃的降解种群中恢复DNA的基因，以使用 元基因组文库回收完整的基因和操纵子，并使用高通量的PCR筛选 识别具有目标基因家族的克隆。这个项目结合了罗格斯大学的专业知识 大学科学家在芳香加氧酶和高通量筛选和元基因组学方面的研究 密歇根州立大学在还原脱氯、基因组学和微阵列技术方面的专业知识。

The microbial world is diverse owing to its 3.7 billion years of evolution, which provides for both the opportunity of undiscovered metabolic capacity, including that for pollutant degradation, and the challenge of detecting and recovering this activity. It is well known that more than 99% of the microbial world has not been cultured and hence remains undiscovered. We propose to explore and recover genes for two key biodegradative steps in the detoxification of chlorinated polyaromatic compounds from the DNA of this uncultured microbial diversity, and then to use the molecular markers from this study to aid in site assessment and quantitative predictions of biodegradation at contaminated sites. We are targeting the reductive dehalogenases and the aromatic oxygenases as the key functions to recover since they are most often the rate limiting steps in the degradation of the polychlorinated dioxins and dibenzofurans, PCBs and polynuclear aromatic hydrocarbons (PAHs), the Superfund chemicals of focus in our study. Our specific aims are to: (1) explore and recover nature's catalytic diversity with the goal of developing a comprehensive profile of microbial metabolic capabilities for these polyaromatic compounds, (2) use the genome sequence information of Burkholderia xenovorans LB400, the most effective PCB degrader, to study the metabolic features important to the degradation of these chemicals and (3), develop quantitative diagnostic tools based on Bayesian probabilistic networks to predict biodegradation at contaminated sites. We propose to use enrichments to help identify the functionally active populations and hence genes, to use stable isotope probing to recover DNA from the active degrading populations, to use metagenomic libraries to recover the full genes and operons, and to use high throughput PCR screening for identifying clones with the targeted gene families. This project combines the expertise of the Rutgers University scientists in aromatic oxygenases and high throughput screening and metagenomics with the expertise at Michigan State University in reductive dechlorination and genomics and microarray technology.