Genomic Epidemiology for Hospital Outbreak Detection

描述（由申请人提供）：允许全基因组测序的技术的发展，通过在单核苷酸多态性（SNP）水平上进行区分，为传染病研究人员提供了极大增强的研究系统发育和细菌病原体传播的能力。全基因组测序（WGS）还可以提供其他病原体特征的信息，如抗生素耐药性和毒力特征。虽然WGS已广泛用于研究，但尚未转变为常规使用，以检测与医院有关的细菌性病原体的爆发，这是发病率和死亡率的严重来源，并导致医疗费用增加。基因组流行病学将全基因组测序获得的高分辨率分型信息与常规流行病学信息相结合，大大增强了检测和跟踪传播事件的能力。在医院疫情调查中常规使用基因组流行病学在一定程度上取决于可负担性和周转时间，这两者最近都大幅减少。然而，在医院环境中采用基因组流行病学还取决于克服目前存在的与WGS用于医院流行病学验证相关的障碍以及WGS数据分析的困难。本应用程序中提出的研究将有助于克服这些障碍。该项目的具体目标是1)验证WGS快速识别医院疫情的能力，2)开发WGS数据的自动分析系统，以易于理解的格式生成医院疫情调查所需的信息。从多次特征明确的医院暴发中获得的四种重要医院病原体（鲍曼不动杆菌、艰难梭菌、金黄色葡萄球菌和肺炎克雷伯菌）分离物的全基因组将进行WGS。这些分离物已通过流行病学和常规分子分型方法进行了鉴定。这些序列的基因组比较将与现有的常规分型数据相关联，以验证WGS检测暴发菌株和区分无关菌株的能力。这些序列将用于制定基因组标准，以确定遗传相关的分离株和确定疫情。这些标准将

DESCRIPTION (provided by applicant): The development of technologies that allow sequencing of whole genomes provides infectious disease researchers with a greatly enhanced ability to investigate phylogenetics and transmission of bacterial pathogens by enabling discrimination at the single nucleotide polymorphism (SNP) level. Whole genome sequencing (WGS) can also provide information about other pathogen characteristics, such as antibiotic resistance and virulence traits. While WGS has become widely used in research, it has not yet transitioned into routine use to detect outbreaks of hospital-associated bacterial pathogens, which are a serious source of morbidity and mortality and contribute to increased healthcare costs. Genomic epidemiology combines the high-resolution typing information obtained by sequencing whole genomes with conventional epidemiologic information, resulting in a greatly enhanced ability to detect and track transmission events. Routine use of genomic epidemiology in hospital outbreak investigations relies partly on affordability and turnaround time, both of which have seen recent dramatic decreases. However, adoption of genomic epidemiology in the hospital setting also depends on overcoming currently existing obstacles related to validation of WGS for hospital epidemiology and difficulty of analysis of WGS data. The research proposed in this application will aid in overcoming those obstacles. The specific aims of this project are 1) t validate the ability of WGS to rapidly identify outbreaks in the hospital and 2) to develop an automated analysis system for WGS data that will generate the information needed for hospital outbreak investigation in an easily understood format. Whole genomes of isolates of four important hospital pathogens (Acinetobacter baumannii, Clostridium difficile, Staphylococcus aureus, and Klebsiella pneumoniae), obtained from multiple well-characterized hospital outbreaks, will undergo WGS. These isolates have been characterized epidemiologically and by conventional molecular typing methods. Genomic comparisons of these sequences will be correlated with the existing conventional typing data to validate the ability of WGS to detect outbreak strains and discriminate unrelated strains. The sequences will be used to develop genomic criteria to define genetically related isolates and identify outbreaks. These criteria will be utilized in the development of a WGS analysis system that will automatically generate data relevant to hospital outbreak epidemiology, producing a user-friendly results display. Input from hospital infection control and clinical microbiology personnel will contribute to the design of bot the analysis system and the results display. This study will help overcome the current obstacles to routine use of genomics for hospital outbreak detection.