Genome Variability and Population Processes of Lyme Disease Pathogens

描述(申请人提供)：进化基因组学是通过识别病原体基因组中的毒力基因和揭示疾病传播的模式和机制来控制新出现的传染病的关键。莱姆病是由伯氏疏螺旋体复合细菌群的病原体引起的，是北美和欧洲最常见的媒介传播疾病。尽管受地理限制，莱姆病的流行范围在最近几十年里大大扩大，几乎没有可预测性。在过去的四年里，PI和他的合作者已经对23种具有代表性的莱姆病病原体菌株的基因组进行了测序。与该研究小组和其他研究小组之前测得的六个基因组一起，这些大量的疏螺旋体基因组开启了一个通过进化和比较基因组学来理解莱姆病流行的基因组和生态学基础的新时代。1998-2012年期间SC3的支持是PI在全基因组测序基于系统发育的菌株选择、广泛重组的发现和其比率的估计以及由几个主要表面抗原座位特别是外表面蛋白C(OSPC)座位的免疫逃逸驱动的伯氏杆菌基因组多样性计算模型开发中的主导作用。此外，SC3项目在PI的实验室中产生了成熟的生物信息学和分析基础设施，包括例如定制的基因组数据库、一套 基于Perl/BioPerl的软件工具(“DNatwezers”)和细菌基因组进化的模拟器(“SimBac”)。后两个工具已经作为开放源码项目发布到公共存储库Sourceforge.net。建议的SC1项目的具体目标是：(I)通过积极和净化的自然选择测试，揭示与伯氏杆菌毒力相关的基因组变异性；(Ii)启动疏螺旋体系统动力学的新研究路线，以预测莱姆病流行的传播；以及(Iii)通过开发进化生物信息学工具，使病原体的比较基因组学研究现代化。PI将通过扩大与疏螺旋体分子遗传学家和莱姆病生态学家的合作，并开发莱姆病种群基因组学方面的翻译和创新研究计划，制定非评分研究提案。总而言之，该项目的总体目标和预期结果将是阐明与毒力相关的基因组变异、莱姆病地方性疾病传播的预测模型，以及在新出现的传染病的生态学和进化方面具有国家竞争力的研究计划。该项目通过识别毒力基因和预测病原体在自然界的传播，帮助控制莱姆病的传播。

DESCRIPTION (provided by applicant): Evolutionary genomics is a key to controlling emerging infectious diseases by identifying virulence genes in the pathogen genome and by revealing patterns and mechanisms of disease spread. Lyme disease, caused by pathogens belonging to the bacterial species complex Borrelia burgdorferi sensu lato, is the most common vector-borne disease in North America and Europe. Although geographically limited, the Lyme disease endemic has greatly expanded in range in recent decades with little predictability. In the past four years, the PI and his collaborators have sequenced the genomes of twenty-three world-wide representative strains of Lyme disease pathogens. Along with the half dozen genomes previously sequenced by this and other research groups, this large amount of Borrelia genomes usher in a new era of understanding the genomic and ecological basis of Lyme disease endemics through evolutionary and comparative genomics. The SC3 support during 1998- 2012 is behind the PI's leading roles in the phylogeny-based selection of strains for whole-genome sequencing, the discovery of widespread recombination and estimation of its rates, and the development of a computational model of B. burgdorferi genome diversity driven by immune escape at a few major surface antigen loci and the outer-surface protein C (ospC) locus in particular. In addition, the SC3 projects resulted in a mature bioinformatics and analytical infrastructure in the PI's lab including, e.g., a customized genome database, a suite of Perl/BioPerl based software tools ("DNATweezers"), and a simulator of bacterial genome evolution ("SimBac"). The latter two tools have been released into public repository SourceForge.net as Open Source projects. The PI's specific aims for the proposed SC1 project are to (i) reveal genome variability associated with B. burgdorferi virulence by tests of positive and purifying natural selection, (ii) launch a new line of research in the phylodynamics of Borrelia for predicting the spread of Lyme endemics, and (iii) modernize comparative genomics studies of pathogens by develop evolutionary bioinformatics tools. The PI will develop non-SCORE research proposals through widening collaboration with Borrelia molecular geneticists and Lyme ecologists and developing translational and innovative research programs in population genomics of Lyme disease. To summarize, the overall goal and expected outcomes of the project will be an elucidation of virulence-associated genomic variations, predictive models of the spread of Lyme disease endemics, and a nationally competitive research program in ecology and evolution of emerging infectious diseases. The project helps to control the spread of Lyme disease by identifying virulence genes and by predicting pathogen spread in nature.