Phylogenomic epidemiology of Clostridium difficile

描述（由申请人提供）：由艰难梭菌引起的胃肠炎是一个全球性的卫生保健问题，也是抗生素治疗的常见并发症。产生毒素的艰难梭菌菌株的一个子集最近出现，引起大规模的医院暴发和持续的艰难梭菌大流行。解释大流行毒株出现的一个假设是毒素的过量生产和形成环境抗性孢子的能力增强。然而，最近的研究包括来自更大的代表性分离物的数据，挑战了这一假设，并说明需要新的遗传特征，以改善这些病原体的监测和分子流行病学。本文提出的工作将提供艰难梭菌分离物广泛多样性的基因组序列，并验证某些基因组特征与人类艰难梭菌感染（CDI）严重程度显著相关的假设。作为密歇根大学正在进行的艰难梭菌临床研究的一部分，将从有症状的住院患者中收集分离株。将使用高通量荧光pcr进行基因分型，并使用多位点可变数串联重复分析（MLVA）进行亚型分型。基于这些特征，将选择150个具有代表性的分离株进行基因组测序，这些分离株的基因型多样性和CDI严重程度的临床谱。作为一个并行项目的一部分，目前正在对我们收集的另外约200例CDI病例的分离株进行测序。所有分离株（~350株）的序列数据将根据患者记录数据库中的临床参数进行生物信息学处理和分析。该分析结果将在流行病学上将艰难梭菌单核苷酸多态性（snp）形式的遗传多样性与CDI严重程度和对治疗的反应联系起来。SNP数据将用于开发一种新的基于系统发育的分型系统，用于艰难梭菌菌株的快速基因组表征。SNP分型将用于描述大量分离株（n= 5000）的基因组多样性，并评估基于细菌基因组的CDI严重程度相关性。这项研究的完成要求候选人完成一个教学培训计划，旨在专门掌握生物信息学，计算生物学和基因组学领域的概念和工具。课程作业、领域领导者的指导以及从深入的数据分析中获得的经验知识相结合，将确保研究和候选人未来职业生涯的成功。

DESCRIPTION (provided by applicant): Gastroenteritis caused by the bacterium, Clostridium difficile, is a global healthcare problem and a common complication of antibiotic therapy. A subset of toxin-producing C. difficile strains has recently emerged to cause large nosocomial outbreaks and an ongoing C. difficile pandemic. One hypothesis to explain the emergence of pandemic strains is the overproduction of toxins and an increased ability to form environmentally-resistant spores. However, recent studies that include data from a larger set of representative isolates challenge this hypothesis and illustrate the need for novel genetic characterizations that improve the surveillance and molecular epidemiology of these pathogens. The work proposed here will provide genome sequences of a broad diversity of C. difficile isolates and test the hypothesis that certain genomic traits are significantly associated with the severity of human C. difficile infection (CDI). Isolates will be collected from symptomatic hospita inpatients as part of an ongoing C. difficile clinical study at the University of Michigan. A totalof 1,500 isolates will be genotyped using high-throughput fluorescent-PCR ribotyping and subtyped using multi-locus variable number tandem repeat analysis (MLVA). Based on these characterizations, 150 representative isolates spanning the genotypic diversity of isolates and clinical spectrum of CDI severity will be selected for genome sequencing. Isolates from an additional ~200 CDI cases in our collection are presently being sequenced as part of a parallel project. Sequence data for all isolates (~350) will be bioinformatically manipulated and analyzed with respect to clinical parameters from the patient record database. Results from this analysis will epidemiologically link C. difficile genetic diversity in the form of single nucleotide polymorphisms (SNPs) with CDI severity and response to therapy. SNP data will be used to develop a novel phylogenetically-based typing system for the rapid genomic characterization of C. difficile strains. SNP typing will be used to characterize the genomic diversity of a large collection of isolates (n=5,000) and assess the bacterial genome-based correlates of CDI severity. The completion of this research requires that the candidate complete a didactic training program designed to specifically master concepts and tools from the fields of bioinformatics, computational biology, and genomics. A combination of coursework, mentorship from leaders in the field, and experiential knowledge to be gained from in depth data analysis will ensure the success of the research and the future career of the candidate.