Developing a Bioinformatics Database for Stoichioproteomics

快速增长的DNA和蛋白质序列数据库，对单个蛋白质基本生物学功能的了解，以及表征相对基因表达强度的信息的可用性，为构建生态基因组假说和测试他们的预测提供了独特而令人兴奋的机会。一个基本问题涉及环境约束（如营养限制）如何影响蛋白质序列。特别是，该奖项探讨了环境中营养物质的可用性如何通过调节其氨基酸组成来影响蛋白质。这个问题可以解决，因为生态学家已经证明了生物及其组织在元素组成和蛋白质含量方面存在广泛的种间差异（例如，植物相对于食草昆虫来说是缺氮的；蚱蜢相对于蝴蝶来说是富氮的）。氨基酸是所有蛋白质的组成部分，它们的原子组成（如碳[C]、氮[N]、硫[S]和氧[O]）可能不同，这是因为“r基团”（侧链）的差异，这有助于单个氨基酸的独特化学反应性，并使它们在蛋白质序列中发挥各自的结构和功能作用。结合生态学和基因组学的观点，可以直接检查富氮和贫氮物种的蛋白质组在其蛋白质侧链的标准化n含量方面是否存在差异。“化学-蛋白质组学”中的这些问题需要探索蛋白质元素组成的种间和基因间变异。为了促进这些探索，这个项目将在生态学、进化学和基因组学的界面上创建一个生物信息学知识库。这个数据库，即基因组学资源访问Stoichio-Proteomics (GRASP)，将作为一个多层的、数据驱动的网络应用程序来实现。它将是一个灵活和可扩展的系统，将包含一个集成的生态数据集（表征昆虫物种的关键生活史特征）和一个蛋白质组成数据库。一些化学蛋白质组学研究假设将使用这些数据进行检验。这项研究的更广泛影响超越了直接的科学利益，体现在三个方面。首先，grasp数据库及其查询/检索系统将提供一个广泛的、易于使用的工具，用于探索和分析蛋白质的化学计量特征，并将免费提供给研究界。GRASP将促进多种化学-蛋白质组学分析，远远超出我们自己的研究兴趣。数据库技术将提供给任何对开发类似资源感兴趣的人。其次，所提出的计算平台将成为全球大学本科生和研究生的有用教学工具。第三，在该提案的支持下进行的研究和开发将对跨学科生物学的人力资源开发做出重大而集中的贡献，特别是在计算基因组学和生态进化的接口。

PI: William Fagan, University of MarylandCoPI: James Elser, Arizona State University Sudhir Kumar, Arizona State University Fast growing DNA and protein sequence databases, knowledge of the basic biological function of individual proteins, and availability of information characterizing relative gene expression intensities provide unique and exciting opportunities to construct eco-genomic hypotheses and test their predictions. One fundamental question involves how environmental constraints (such as nutrient limitation) shape protein sequences. In particular, this award explores how the availability of nutrients in the environment affects proteins by modulating their amino acid composition. This issue can be addressed because ecologists have demonstrated extensive interspecific variation in the elemental compositions and protein content of organisms and their tissues (e.g., plants are nitrogen-poor relative to insect herbivores; grasshoppers are nitrogen-rich relative to butterflies)., Amino acids, which are the building blocks of all proteins, can differ in their atomic compositions (e.g., carbon [C], nitrogen [N], sulfur [S], and oxygen [O]) because of differences in the "R-groups" (side-chains), which contribute to the unique chemical reactivity of individual amino acids and allow them to play individual structural and functional roles within protein sequences. Combining ecological and genomic perspectives allows examining directly whether the proteomes of N-rich and N-poor species differ with regard to the standardized N-content of the side chains of their proteins. These problems in "stoichio-proteomics" require the exploration of interspecific and intergenic variation in the elemental composition of proteins. To facilitate these explorations, this project will create a bioinformatics knowledgebase at the interface of ecology, evolution, and genomics. This database, the Genomics Resource Access for Stoichio-Proteomics (GRASP), will be implemented as a multi-tiered, data-driven web application. It will be a flexible and scalable system that will contain an integrated ecological dataset (characterizing key life history traits of insect species) and a database of protein composition. Some of the stoichioproteomic research hypotheses will be tested using these data. The Broader Impacts from this research extend beyond the immediate scientific interests in three ways. First, the GRASP-database and its query/retrieval system will provide an extensive, easy-to-use tool for the exploration and analysis of stoichiometric characteristics of proteins that will be freely available to the research community. GRASP will facilitate diverse stoichio-proteomic analyses far beyond our own research interests. The database technology will be made available to anyone who is interested in developing similar resources. Second, the proposed computing platform will be a useful teaching tool for undergraduate and graduate students at universities worldwide. Third, research and development conducted under the auspices of this proposal will make a significant, but focused, contribution to human resources development in interdisciplinary biology, especially at the interface of computational genomics and ecological evolution.