RUI: Automated Metabolic Reconstruction for All Sequenced Microbial Genomes

微生物代谢的计算机模型已被证明有助于理解生物将底物转化为生物质成分和能量的生化过程。这些计算机模型组成了一个网络的一部分，代表了生物体基因组中编码的酶催化的生化反应。代谢重建的挑战是创建一个完整的反应网络，适用于直接从带注释的基因组进行系统水平分析。代谢重建在很大程度上仍然是一个人工过程，到目前为止，只公布了少数几个生物体的代谢重建。因此，迫切需要对这一过程进行更实质性的自动化。这项研究将采取广度优先的方法，为所有已测序的微生物基因组生成基本上完整的代谢重建。这种方法涉及一个迭代过程，即识别数据库中尚未显示的微生物基因组中编码的新陈代谢区域，为它们创建新的反应网络组件，并生成更新的新陈代谢重建。这些代谢重建中的每一个都需要一定程度的手工精炼才能完成。因此，将通过为一小部分选定的生物体产生完整的代谢重建来开发和验证软件工具。将建立一个网站，向科学界提供所有新陈代谢重建和改进工具。代谢成分数据库和软件将与SEED--一个广泛使用的比较基因组注释和分析环境--完全整合，主要研究人员将与SEED社区合作传播研究结果。开发的数据库和软件将大大减少创建适合系统水平分析的完整代谢重建所需的人工工作量。这将为特定生物体科学界的建模工作提供高质量的起点。不同微生物的代谢重建将导致对它们的系统发育关系的新的科学研究，以及分析基因组、代谢组和蛋白质组数据的新方法。更广泛的影响：不同微生物的代谢重建将导致在工业、医疗和环境背景下的新应用。这个项目将为生物学和计算机科学的本科生提供跨学科研究的实践经验，为他们的研究生工作或其他科学活动做好准备。研究活动还将反馈到生物信息学、科学计算和微生物学的课程中。该计划将利用霍普学院与当地社区大学和当地公立学校系统的现有合作，为科学中代表性不足的群体的学生提供研究机会。

Computer models of microbial metabolism have proven useful for understanding the biochemical processes by which organisms transform substrates into biomass components and energy. These computer models consist in part of a network representing the biochemical reactions catalyzed by the enzymes encoded in an organism's genome. The challenge of metabolic reconstruction is to create a complete reaction network suitable for systems level analysis directly from an annotated genome. Metabolic reconstruction is still largely a manual process, and to date metabolic reconstructions have been published for only a handful of organisms. Thus, there is an urgent need for more substantial automation of this process. The research will take a breadth-first approach to generating substantially complete metabolic reconstructions for all sequenced microbial genomes. This approach involves an iterative process of identifying areas of metabolism encoded in microbial genomes that are not yet represented in the database, creating new reaction network components for them, and generating updated metabolic reconstructions. Each of these metabolic reconstructions will require some degree of manual refinement to reach completion. Therefore, software tools will be developed and validated by producing complete metabolic reconstructions for a small set of selected organisms. A web site will be created to make available to the scientific community all of the metabolic reconstructions and refinement tools. The database of metabolic components and software will be fully integrated with the SEED, a widely used comparative genome annotation and analysis environment, and the principal investigators will collaborate with the SEED community to disseminate the research results. The database and software developed will significantly reduce the amount of manual effort required to create complete metabolic reconstructions that are suitable for systems level analysis. This will provide high-quality starting points for modeling efforts by organism-specific scientific communities. Metabolic reconstructions for diverse microbes will lead to new scientific investigations into their phylogenetic relationships as well as new methods for analyzing genomic, metabolomic and proteomic data. Broader Impacts: Metabolic reconstructions for diverse microbes will lead to new applications in industrial, medical and environmental contexts. This project will provide undergraduate students in biology and computer science with hands-on experience in interdisciplinary research that will prepare them for graduate work or other scientific activity. The research activities will also feed back into courses in bioinformatics, scientific computing, and microbiology. The program will draw on Hope College's existing collaborations with area community colleges and the local public school system to provide research opportunities to students from underrepresented groups in the sciences.