IDENTIFICATION OF NATURAL GENOMIC VARIANTS THAT INFLUENCE CRYPTOCOCCAL VIRULENCE

决定隐球菌致病性的天然基因组变异的鉴定新生隐球菌是一种全球性病原体，每年导致数十万艾滋病毒阳性患者死亡，并在非艾滋病患者群体中增加发病率。在这种微生物的自然菌株之间观察到了显著的毒力差异，但尚未有导致这种不同毒力的自然基因组变异的报道。这项研究的目标是填补这一知识空白。要做到这一点，需要克服目前的挑战，即单个菌株集合中菌株多样性不足，依赖多位点序列分型(MLST)来表征基因组，以及在宿主基因组水平和潜在发病率水平上混淆宿主因素。我们假设，通过在标准化的小鼠模型中评估一组不同的全基因组测序菌株的毒力，我们将能够通过计算识别和实验验证影响毒力的自然变异。在这个R21的应用中，我们建议用一组初始的临床分离株来检验这一假设。实现我们的目标所需的分析范围将通过两个实验室的协同努力来实现，这两个实验室在计算和实验生物学方面具有互补的技能，并在新生假单胞菌方面有生产性合作的历史。在目标1中，我们将从不同的临床分离株和新生弧菌基因杂交后代中收集全基因组序列(WGS)和相应的小鼠感染数据。在目标2中，我们将利用我们在隐球菌生物学和基因调控方面的专业知识进行全基因组关联研究(GWAS)和批量分离分析(BSA)，以产生并优先考虑哪些基因组变异影响毒力的假说。在目标3中，我们将通过基因组工程和毒力研究直接测试高优先级假说的子集。这一应用的意义在于该病原体对人类健康的影响；对隐球菌基因调控和蛋白质功能的基础生物学可能有新的见解；以及未来在疾病监测、患者分层和确定新的治疗靶点方面应用的潜力。创新方面包括使用不同的临床分离株，批量分离分析，一种新的计算管道，以及对假设的因果变量的实验验证。总之，这些研究将为研究新生葡萄球菌的自然变异及其在毒力中的作用提供一个模板，为研究界产生重要的资源，并有可能识别和验证影响毒力的因果变异。这一探索性的建议还将为未来对更大菌株集的研究以及我们和其他人在基本生物学理解和潜在应用方面的后续工作奠定基础。

Identification of natural genomic variants that determine cryptococcal pathogenicity Cryptococcus neoformans is a global pathogen responsible for hundreds of thousands of deaths yearly in HIV+ individuals and increasing morbidity in non-AIDS patient populations. Striking differences in virulence are observed among naturally occurring strains of this microbe, but no natural genomic variant responsible for this differential virulence has yet been reported. The goal of this research is to fill this gap in knowledge. Doing this will require overcoming the current challenges of insufficient strain diversity in individual strain collections, reli- ance on multi-locus sequence typing (MLST) to characterize genomes, and confounding host factors at the levels of the host genome and underlying morbidities. We hypothesize that by assessing the virulence of a diverse group of whole genome sequenced strains in a standardized mouse model, we will be able to computationally identify and experimentally validate natural variants that influence virulence. In this R21 application we propose to test this hypothesis with an initial set of clinical isolates. The range of analyses required to achieve our goal will be enabled by the synergistic efforts of two labs with complementary skills sets in computational and experimental biology and a history of productive collaboration on C. neoformans. In Aim 1 we will assemble whole genome sequences (WGS) and corresponding mouse infection data from diverse clinical isolates and progeny of C. neoformans genetic crosses. In Aim 2 we will perform genome-wide association studies (GWAS) and bulk segregant analysis (BSA), interpreted using our expertise in cryptococcal biology and gene regulation, to generate and prioritize hypotheses about which genomic variants influence virulence. In Aim 3 we will directly test a subset of high-priority hypotheses by genome engineering and virulence studies. The significance of this application lies in the impact of the pathogen on human health; the likely new insights into basic biology of cryptococcal gene regulation and protein function; and the potential for future application in terms of disease surveillance, patient stratification, and identification of new therapeutic targets. Innovative aspects include the use of diverse clinical isolates, bulk segregant analysis, a novel computational pipeline, and experimental validation of hypothesized causal variants. Together, these studies will provide a template for investigations of natural variants in C. neoformans and their role in virulence, generate significant resources for the research community, and potentially identify and validate causal variants that influence virulence. This exploratory proposal will additionally lay the groundwork for future studies of larger strain sets and follow-up by us and others in the directions of both fundamental biological understanding and potential application.