Evolutionary dynamics and phylogenetic inference of CRISPR systems in prokaryotic populations

改变基因组的革命性CRISPR/Cas技术起源于细菌和古细菌的天然CRISPR系统。这些系统中的许多可以作为针对特定病毒序列的适应性防御系统。除了这种防御功能之外，CRISPR系统还可以在没有病毒参与的情况下影响细菌种群的进化。该项目的总体目标是开发和应用新的先进模型，用于原核生物中CRISPR的进化。许多研究都集中在具有CRISPR的细菌和相应的病毒之间的共同进化方面。相比之下，我们将考虑细菌和古细菌中CRISPR Cas系统的内在进化。特别是，我们的目标是回答以下问题：a)为了识别特定的靶标，CRISPR系统包含一系列与靶标对齐的间隔物。这个间隔器数组提供了一个独特的洞察进化史，因为这个数组中的间隔器是按时间顺序排列的。我们能否解释间隔符数组中观察到的模式，并在选择中识别间隔符？我们能重建祖先的间隔器插入时间并将它们与祖先的历史联系起来吗？b)意外的自我靶向通常导致死亡，因此细菌基因组中潜在的自我靶标可能处于强选择之下。我们能否从拥有CRISPR的细菌基因组序列中模拟自靶向CRISPR系统的选择效应？c)针对密切相关物种的CRISPR系统能够阻止细菌菌株之间的重组，并可以调节种群中基因的频率。此外，细菌可以利用这种系统作为攻击武器，攻击关系密切的竞争对手。CRISPR如何影响细菌中基因的频率？我们能否理解靶向相关物种的CRISPR阵列的种群动态？靶向亚群的CRISPR系统是一种有希望的新型抗微生物治疗方法吗？我们将混合使用数学和计算方法来解决这些问题。

The revolutionary CRISPR/Cas technology to alter genomes has its origin in the natural CRISPR systems in bacteria and archaea.Many of these systems can act as an adaptive defense system targeting specific viral sequences.Beyond this defensive function, CRISPR systems can influence the evolution of bacterial populations without viruses being involved.The overarching goal of this project is to develop and apply new state of the art models for the evolution of CRISPR in prokaryotes. Many studies have focused on the coevolutionary aspects between CRISPR possessing bacteria and the corresponding viruses. In contrast, we will consider the intrinsic evolution of CRISPR Cas systems in bacteria and archaea. In particular, we aim to answer the following questions:a) To identify specific targets the CRISPR system contains an array of spacers that align with the targets. This spacer array provides a unique insight into the evolutionary history since spacers in this array are arranged in chronological order. Can we explain the observed pattern in spacer arrays and identify spacers under selection?Can we reconstruct ancestral spacer insertion times and link them to their ancestral history?b) Accidental self-targeting usually leads to death such that potential self-targets in the bacterial genome are presumably under strong selection.Can we model the selective effect of self-targeting CRISPR systems from the genome sequences of bacteria possessing CRISPR?c) CRISPR systems that target closely related species are capable to block recombination between bacterial strains and can modulate the frequency of genes in the population. Moreover, bacteria can use such systems as an offensive weapon targeting closely related competitors.How does CRISPR influence the frequency of genes in bacteria?Can we understand within population dynamics of CRISPR arrays targeting related species? Are CRISPR systems targeting subpopulations a promising new anti-microbial treatment?We will address these questions with a mixture of mathematical and computational approaches.