Population Structure and Clinical Impact of Multi-strain and Mixed-species Cryptococcal Infections

摘要 隐球菌病，由隐球菌属的担子菌酵母菌引起，代表一种亚 持续的全球健康负担。新生隐球菌，最常见的感染源，是UbIQ- 在环境中是有害的，很可能大多数人在基因上接触到了多种 和表型多样的隐球菌菌株在其一生中。尽管如此，人类 历史上对隐球菌病的研究是在假设大多数感染是 由单一致病菌株引起。因此，人们对该病的发病率和流行率知之甚少。 多株或混合种隐球菌感染或其临床影响。 在对杜克大学医院系统患者样本的初步研究中，我们发现 发现了数量惊人的混合隐球菌感染。我们现在提议-- 描述我国混合隐球菌群基因组结构及流行病学相关因素 使用了一组来自美国东南部的500多个患者样本，这些样本是在 过去的30年里。我们将分析这些患者样本中的表型和基因组异质性。 识别混合感染，并将这些数据与种群基因组和种系相结合- 对同一地理区域的环境分离株进行基因分析，以了解其致病机理。 混合感染的环境来源。关于频率和人口结构的信息 混合感染的发生率将与患者人口统计和流行病学分析相关联 健康结果，以了解谁有可能感染混合隐球菌，以及这种感染是什么 感染意味着健康结果。我们还将探索表型异质性的影响， 混合感染的一个关键特征，即对抗真菌药物的敏感性和与 宿主免疫系统。

Abstract Cryptococcal disease, caused by basidiomycete yeasts of the genus Cryptococcus, represents a sub- stantial global health burden. Cryptococcus neoformans, the most common infectious agent, is ubiq- uitous in the environment and it is likely that most people are exposed to multiple genetically and phenotypically diverse Cryptococcus strains throughout their lifetimes. Despite this, human cryptococcosis has historically been studied under the assumption that a majority of infections are caused by single pathogenic strains. As a result, little is known about the incidence and prevalence of multi-strain or mixed-species cryptococcal infections or their clinical impact. In a preliminary study of patient samples from the Duke University Hospital System we de- tected a surprisingly high number of mixed Cryptococcus infections. We now propose to charac- terize the population genomic structure and epidemiological correlates of mixed Cryptococcus in- fections, using a set of more than 500 patient samples from the southeastern US collected over the last 30 years. We will analyze phenotypic and genomic heterogeneity within these patient samples to identify mixed infections, and combine these data with with population genomic and phyloge- netic analyses of environmental isolates from the same geographic region to understand the en- vironmental origins of mixed infections. Information on the frequency and population structure of mixed infections will be correlated with epidemiological analyses of patient demographics and health outcomes to understand who is likely to get mixed Cryptococcus infections and what such infections mean for health outcomes. We will also explore the impact of phenotypic heterogeneity, a key characteristic of mixed infections, on sensitivity to antifungal drugs and interactions with the host immune system.