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为传染病研究人员提供了通过在单核苷酸多态性（SNP）水平上进行区分来研究细菌病原体的遗传学和传播的能力大大增强。全基因组测序（WGS）还可以提供有关其他病原体特征的信息，如抗生素耐药性和毒力性状。虽然WGS已被广泛用于研究，但它尚未过渡到常规用途，以检测医院相关细菌病原体的爆发，这是发病率和死亡率的严重来源，并导致医疗保健成本增加。基因组流行病学将通过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。基因组流行病学在医院爆发调查中的常规使用部分依赖于可负担性和周转时间，这两个因素最近都急剧下降。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验证WGS用于医院流行病学和分析WGS数据的困难相关的障碍。本申请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快速识别医院爆发的能力; 2）开发一个WGS数据自动分析系统，以易于理解的格式生成医院爆发调查所需的信息。从多个充分表征的医院爆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）的分离株的全基因组将进行WGS。这些分离株的特点是流行病学和传统的分子分型方法。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检测爆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 该系统将自动生成与医院爆发流行病学相关的数据，并生成用户友好的结果显示。来自医院感染控制和临床微生物学人员的输入将有助于分析系统和结果显示的设计。这项研究将有助于克服目前常规使用基因组学进行医院暴发检测的障碍。

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.