Spread of Lyme borreliosis bacteria in the U.S.

描述(申请人提供)：美国莱姆疏螺旋体新人病例数量最近跃升至创纪录高位，表明致病基因伯氏疏螺旋体的种群数量。正在以加速的速度扩张。这项应用的广泛和长期目标是理清作用于细菌的进化过程，以便于对伯氏杆菌致病基因的传播进行建模。并为开发新的诊断工具和设计莱姆疏螺旋体病的具体控制方法提供理论依据。目前迫切需要建立一种伯氏杆菌多位点序列分型(MLST)方案。以看家基因为基础，分析近年来美国致病基因的种群增长、范围扩大和种群动态。具体目标是(1)建立伯氏假单胞菌的MLST方案。基于看家基因，(Ii)评估野生型Burgdorferi S.S.的现有遗传种群结构。使用MLST和景观遗传学对美国东北部的白背飞虱种群进行研究，以及(Iii)推断伯氏白僵菌最近的种群模式，如种群瓶颈和扩张。伯氏杆菌的分离株从调查中提取的扁虱将在新英格兰各地不同的地理范围内进行采样，并将由MLST进行基因分型。使用一种新的算法(EBURST)，将澄清细菌种群之间的进化下降模式。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。利用地理信息系统，将生成一张显示内插遗传曲面的合成地图。将估计一直在塑造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。利用管家基因的MLST和景观遗传学对野生型疏螺旋体种群的分析是新颖和探索性的，可以为我们理解新出现的媒介传播的人畜共患病病原体的进化开辟新的天地。

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.