Spread of Lyme borreliosis bacteria in the U.S.

描述（由申请人提供）：美国莱姆病的新人类病例数量最近跃升至创纪录的高位，这表明致病基因型的伯氏疏螺旋体（s.s）的种群正在加速扩张。该应用程序的广泛和长期目标是解开作用于细菌的进化过程，以促进对美国伯氏疏螺旋体致病基因型传播的建模，并为开发新的诊断工具和设计莱姆病的特定控制方法提供依据。建立基于内房基因的伯氏疏螺旋体多位点序列分型（Multilocus Sequence Typing， MLST）方案，以分析美国近年来伯氏疏螺旋体致病基因型的种群增长、范围扩展和种群动态。具体目标是：(1)建立基于内控基因的伯氏疏螺旋体的MLST方案；(2)利用MLST和景观遗传学评估美国东北部野生型伯氏疏螺旋体种群的遗传群体结构；(3)推断伯氏疏螺旋体最近的人口统计学模式，如种群瓶颈和扩张。研究人员将在新英格兰不同的地理尺度上采集来自蜱虫的伯氏疏螺旋体分离株，并利用MLST进行基因分型。利用一种新的算法（eBURST），细菌种群之间的进化下降模式将得到澄清。疏螺旋体种群的空间结构将由空间统计决定，并与景观变量有关。使用GIS，将生成一个综合地图，显示插值的遗传表面。形成细菌种群的进化过程的相对重要性，如突变、重组、迁移和选择，将被估计。利用管理基因和景观遗传学对野生型伯氏疏螺旋体种群进行的MLST分析是新颖的、探索性的，可以为我们理解新出现的媒介传播的人畜共患病原体的进化开辟新的领域。

DESCRIPTION (provided by applicant): The number of new human cases of Lyme borreliosis in the United States has recently leaped to record highs, suggesting that the populations of the disease-causing genotypes of Borrelia burgdorferi sensu stricto (s.s.) are expanding at an accelerating rate. The broad and long-term objectives of this application are to disentangle the evolutionary processes acting on the bacteria to facilitate modelling the spread of disease-causing genotypes of B. burgdorferi s.s. in the United States, and to provide rationales for developing new diagnostic tools and for designing specific control methods of Lyme borreliosis. There is urgent need to establish a Multilocus Sequence Typing (MLST) scheme for B. burgdorferi s.s. based on housekeeping genes in order to analyze the recent population growth, range expansion and population dynamics of pathogenic genotypes in the United States. The specific aims are (i) to establish a MLST scheme of B. burgdorferi s.s. based on housekeeping genes, (ii) to assess the present day genetic population structures of wild-type B. burgdorferi s.s. populations in the Northeast United States using MLST and landscape genetics, and (iii) to infer the recent demographic patterns of B. burgdorferi s.s., such as population bottlenecks and expansions. Isolates of B. burgdorferi s.s. derived from questing ticks will be sampled at different geographical scales across New England and will be genotyped by MLST. Using a new algorithm (eBURST), the patterns of evolutionary descent amongst the bacterial populations will be clarified. The spatial structure of the Borrelia populations will be determined by spatial statistics and related to landscape variables. Using GIS, a synthesis map will be generated that displays an interpolated genetic surface. The relative importance of the evolutionary processes that have been shaping the bacterial populations, such as mutation, recombination, migration and selection, will be estimated. The analyses of wild-type Borrelia populations by MLST at housekeeping genes and by landscape genetics is novel and explorative, and could break new ground in our understanding of the evolution of emerging vector-borne zoonotic pathogens.