Phylogenomic epidemiology of Clostridium difficile

描述（由申请方提供）：艰难梭菌引起的胃肠炎是一个全球性的医疗保健问题，也是抗生素治疗的常见并发症。产毒素C.艰难梭菌菌株最近出现，导致大规模的医院爆发和正在进行的C。艰难的大流行解释大流行菌株出现的一个假设是毒素的过度生产和形成环境抗性孢子的能力增加。然而，最近的研究，包括数据从一个更大的代表性的菌株挑战这一假设，并说明需要新的遗传特征，提高这些病原体的监测和分子流行病学。本工作将提供广泛多样性的C.艰难梭菌分离株和测试的假设，某些基因组性状显着相关的严重性，人类C。艰难梭菌感染（CDI）。作为正在进行的C.在密歇根大学的艰难临床研究。将使用高通量荧光PCR核糖体分型对总共1，500个分离株进行基因分型，并使用多位点可变数目串联重复序列分析（MLVA）进行亚型分型。基于这些特征，将选择150株代表性分离株进行基因组测序，这些分离株涵盖分离株的基因型多样性和CDI严重程度的临床谱。作为平行项目的一部分，我们收集的另外约200例CDI病例的分离株目前正在测序。将对所有分离株（约350株）的序列数据进行生物信息学处理，并根据患者记录数据库中的临床参数进行分析。这项分析的结果将流行病学联系C。单核苷酸多态性（SNP）形式的艰难遗传多样性与CDI严重程度和对治疗的反应。SNP数据将用于开发一种新的基于遗传学的分型系统，用于快速的C.艰难菌株SNP分型将用于表征大量分离株（n= 5，000）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，该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的结合将确保研究的成功和候选人的未来职业生涯。

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.