Capturing the genomic variation present in Cryptosporidium and cryptosporidiosis

标题：捕捉隐孢子虫和隐孢子虫病的基因组变异 项目总结 隐孢子虫属的寄生虫每年在美国导致74.8万例隐孢子虫病， 是全球婴儿腹泻疾病的第二大原因。2016年在全球范围内，在年龄较小的儿童中 5岁以上，急性隐孢子虫病造成48,000人死亡，420万残疾调整生命年损失 780万以上的DALY可归因于增长停滞不前。隐孢子虫是真核生物 顶端复合体寄生虫被归类为生物防御B类病原体。由水传播的猪瘟暴发 在美国，隐孢子虫在一次事件中就造成了多达40万人的疾病，并且是一个持续的威胁 对全世界的公共卫生。疾控中心估计，自2005年以来，美国隐孢子虫病病例增加了3倍。 2004年。为了解决这一紧迫的公共卫生问题，我们建议开发和使用新的基因组资源来 通过描述DNA变异的分布更好地了解感染人类的隐孢子虫物种 在当地和全球范围内。我们将从大量的53,000份精选样本中对约1500份样本进行排序，以 生成广泛适用的种群遗传数据和基因组资源，这些物种迄今 难以进行广泛的序列表征。拟议的研究和资源将需要 隐孢子虫研究社区更上一层楼，有效地改变了可以 通过提供新的背景来生成假设和新的工具，这些假设和新的工具可以重复使用来推动我们的 对这些病原体的了解。具体地说，AIM 1将开发精致的混合诱饵集，用于强大的 鉴定隐孢子虫的新方法。我们将开发两套用于捕获浓缩测序的诱饵 (CES)，一个用于全基因组特征描述(专注于最常感染人类的物种)和一个 用于高通量表征所有通常感染人类的隐孢子虫物种。CES是一种 改变游戏规则的隐孢子虫研究，促进多位点和全基因组表征 隐孢子虫DNA丰度较低的粪便DNA或环境样本。目标2将产生 并改进了人隐翅虫、泰泽里隐翅虫、巨型隐翅虫和隐翅虫的基因组组装和注释。 丘比特。这些组合完成了通常感染的物种所需的参考序列 人类(或者是一个模型)，并将作为将在Aim 3中生成的数据的参考 生物医学研究社区的资源。目的3研究微小隐孢子虫的遗传多样性。 通过调查基因组多样性在特定环境中的分布情况，发现了人类和人间隐孢子虫。我们把重点放在这些 两种，因为它们导致90%的隐孢子虫病病例。我们将在1152上进行高吞吐量的CES 样本，确定其中的384个，外加全基因组CES的384个额外样本。我们将使用生成的 检验假设的数据：隐孢子虫种群结构、混合感染、重组和 人类体型菌株的进化。该项目将为隐孢子虫产生改变游戏规则的新工具 研究社区，并提供对寄生虫生物学的新见解，这些寄生虫每天感染数千名儿童。

Title: Capturing the genomic variation present in Cryptosporidium and cryptosporidiosis PROJECT SUMMARY Parasites of the genus Cryptosporidium cause 748,000 cases of cryptosporidiosis annually in the U.S. and are the second-leading cause of diarrheal disease in infants worldwide. Globally in 2016, among children younger than 5, acute cryptosporidiosis caused 48,000 deaths and 4.2 million disability-adjusted life-years (DALYs) lost with 7.8 million more DALYs attributable to growth faltering. Cryptosporidium species are eukaryotic apicomplexan parasites classified as bio-defense category B pathogens. Waterborne outbreaks of Cryptosporidium have caused up to 400,000 illnesses in a single incident in the U.S., and are a constant threat to public health worldwide. The CDC estimates a >3-fold increase in cases of cryptosporidiosis in the U.S. since 2004. To address this urgent public health problem, we propose to develop and use new genomic resources to better understand Cryptosporidium species that infect humans by characterizing the distribution of DNA variants in local and global contexts. We will sequence ~1500 samples from a vast set of >53,000 curated samples to generate broadly-applicable population genetic data and genomic resources for species that have thus far been refractory to extensive sequence characterization. The proposed studies and resources will take the Cryptosporidium research community to the next level, effectively changing the types of questions that can be asked by providing a new context to generate hypotheses and new tools that can be re-used to further our knowledge of these pathogens. Specifically, AIM 1 will develop refined hybrid capture bait sets for powerful new assays to characterize Cryptosporidium. We will develop two bait sets for capture enriched sequencing (CES), one for whole genome characterization (focusing on species that most frequently infect humans) and one for high-throughput characterization of all Cryptosporidium species that commonly infect humans. CES is a game-changer for Cryptosporidium research, facilitating multi-locus and whole genome characterization from fecal DNA or environmental samples where Cryptosporidium DNA is low in abundance. AIM 2 will generate and improve genome assemblies and annotation for C. hominis, C. tyzzeri, C. meleagridis, and C. cuniculus. These assemblies complete the reference sequences needed for species that commonly infect humans (or are a model) and will serve as a reference for the data that will be generated in Aim 3 and as a resource for the biomedical research community. AIM 3 will characterize the genetic diversity of C. parvum and C. hominis through surveys of the distribution of genomic diversity in specific contexts. We focus on these two species because they cause >90% cryptosporidiosis cases. We will conduct high-throughput CES on 1152 samples, identifying 384 of those plus 384 additional samples for full genome CES. We will use the resulting data to test hypotheses on: Cryptosporidium population structure, mixed infections, recombination, and the evolution of anthroponotic strains. This project will generate game-changing new tools for the Cryptosporidium research community and provide new insight into the biology of parasites that sicken thousands of children daily.