five

Data from: Adaptation of the pathogen, Pseudomonas syringae during experimental evolution on a native versus alternative host plant

收藏
DataONE2017-03-13 更新2024-06-26 收录
下载链接:
https://search.dataone.org/view/null
下载链接
链接失效反馈
官方服务:
资源简介:
The specialization and distribution of pathogens among species has substantial impact on disease spread, especially when reservoir hosts can maintain high pathogen densities or select for increased pathogen virulence. Theory predicts that optimal within-host growth rate will vary among host genotypes/species and therefore that pathogens infecting multiple hosts should experience different selection pressures depending on the host environment in which they are found. This should be true for pathogens with broad host ranges, but also those experiencing opportunistic infections on novel hosts or that spill over among host populations. There is very little empirical data, however, regarding how adaptation to one host might directly influence infectivity and growth on another. We took an experimental evolution approach to examine short-term adaptation of the plant pathogen, Pseudomonas syringae pathovar tomato, to its native tomato host compared with an alternative host, Arabidopsis, in either the presence or absence of bacteriophages. After four serial passages (20 days of selection in planta), we measured bacterial growth of selected lines in leaves of either the focal or alternative host. We found that passage through Arabidopsis led to greater within-host bacterial densities in both hosts than did passage through tomato. Whole genome resequencing of evolved isolates identified numerous single nucleotide polymorphisms based on our novel draft assembly for strain PT23. However, there was no clear pattern of clustering among plant selection lines at the genetic level despite the phenotypic differences observed. Together, the results emphasize that previous host associations can influence the within-host growth rate of pathogens.
创建时间:
2017-03-13
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作