Informatics of Lyme Disease Biogeography (pilot)

描述（申请人提供）：生物信息学是现代信息技术， 生物数据的计算机化仓储、可视化和分析。该技术是为了应对生物信息的爆炸性增长而出现的，其形式包括全基因组序列、全基因组表达模式和蛋白质的高通量结构表征。生物信息的一种形式，即生物系统的多物种相互作用，具有更高的复杂性，自然需要生物信息学解决方案。然而，与基因组学和蛋白质组学计算系统的激增相比，物种相互作用的生物信息学系统的发展还处于起步阶段。莱姆病是美国最流行的媒介传播疾病，是研究病原体（伯氏疏螺旋体）、其媒介（硬蜱）和宿主（脊椎动物）之间物种相互作用的模型系统。在本申请中，我们建议开发 莱姆病作为一个多物种的地理变异研究的数据库系统 传染系统该数据库将包含多个疏螺旋体基因组、疏螺旋体和硬蜱的多位点序列变异以及与基因组和序列信息相关的地理和生态信息。将从公共数据库和已发表的研究中收集基因组、序列变异和基因组学信息。将开发进化分析工具，如系统发育重建和序列变异中性进化测试，并将其纳入数据库系统。此外，我们将实施和策划一个网络接口的数据库系统。拟议的试点项目有两个具体目标。首先，我们将开发一个莱姆病病毒学概念验证数据库，包括疏螺旋体基因组信息、疏螺旋体和蜱多位点遗传变异以及疏螺旋体-蜱-宿主关联的生态数据。其次，我们将通过测试两个进化假设，一个关于疏螺旋体和蜱虫的共同进化历史，另一个关于疏螺旋体地理区域之间的适应性分歧，来验证数据库系统的实用性。该项目将为生物信息学系统铺平道路， 自动分析和可视化媒介传播的传染系统的地理模式。

DESCRIPTION (provided by applicant): Bioinformatics is a modern information technology for computerized warehousing, visualization and analysis of biological data. The technology emerged in response to the explosive growth of biological information, in forms such as whole-genome sequences, whole-genome expression patterns and high-throughput structure characterization of proteins. One form of biological information, namely the multi-species interactions of a biological system, is of a higher-level complexity that naturally requires bioinformatics solutions. Development of bioinformatics systems of species interactions, however, is in its infancy compared with the proliferation of computing systems for genomics and proteomics. Lyme disease, the most prevalent vector-borne disease in the United States, is a model system for the study of species interactions between a pathogen (Borrelia burgdorferi), its vector (Ixodes ticks) and hosts (vertebrates). In this application, we propose to develop a database system for the study of biogeographic variations of Lyme disease as a multi-species infectious system. The database will host multiple Borrelia genomes, multi-locus sequence variations of Borrelia and Ixodes, as well as biogeographic and ecological information associated with the genome and sequence information. Genomes, sequence variations and biogeographic information will be collected from public databases and published studies. Tools for evolutionary analyses, such as phylogenetic reconstruction and tests of neutral evolution of sequence variations, will be developed and integrated with the database system. In addition, we will implement and curate a web interface to the database system. There are two specific aims for the proposed pilot project. First, we will develop a proof-of-concept database of Lyme disease biogeography, complete with Borrelia genome information, Borrelia and tick multi-locus genetic variations and ecological data on Borrelia-Tick-Host associations. Secondly, we will validate the utility of the database system by testing two evolutionary hypotheses, one on the co-evolutionary history of Borrelia and ticks, and the other on the Borrelia adaptive divergence between geographic localities. The project will pave the way for a bioinformatics system for automated analyses and visualization of biogeographic patterns of vector-borne infectious systems.