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IDENTIFICATION OF NATURAL GENOMIC VARIANTS THAT INFLUENCE CRYPTOCOCCAL VIRULENCE

影响隐球菌毒力的自然基因组变异的鉴定

基本信息

批准号：
9308524
负责人：
MICHAEL R BRENT
金额：
$ 22.88万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-01-06 至 2018-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9308524
关键词：
Address Affect Alleles Antifungal Therapy Biological Biology Cessation of life Characteristics Classification Clinical Collaborations Collection Communities Cryptococcal Meningitis Cryptococcus neoformans Cryptococcus neoformans infection Dangerousness Data Data Set Disease Disease Outcome Disease model Employee Strikes Fungal Genome Future Gene Expression Regulation Gene Proteins Genetic Genetic Crosses Genome Genome engineering Genomics Genotype Goals Growth HIV Health Human In Vitro Individual Infection Integration Host Factors Investigation Knowledge Laboratories Measures Meningoencephalitis Methods Microbe Modeling Molecular Molecular Profiling Morbidity - disease rate Mus Organism Pathogenicity Patient Care Patient Isolators Patient-Focused Outcomes Probability Production Recording of previous events Reporting Research Research Personnel Resources Role Severity of illness Standardization Testing Transcriptional Regulation Validation Variant Virulence Virulence Factors base data resource data sharing drug development fascinate follow-up fungus genetic variant genome analysis genome wide association study innovation insight killings mouse model new therapeutic target novel pathogen patient population patient stratification protein function skills therapeutic biomarker therapeutic target whole genome

项目摘要

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.

确定隐球菌致病性的天然基因组变体的鉴定新型隐球菌是一种全球性病原体，每年导致数十万HIV+个体死亡，并增加非AIDS患者人群的发病率。在这种微生物的天然菌株中观察到毒力的显著差异，但尚未报道导致这种差异毒力的天然基因组变体。这项研究的目的是填补这一知识空白。要做到这一点，需要克服当前的挑战，即单个菌株收集中菌株多样性不足、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上混淆宿主因素和潜在发病率。我们假设，通过在标准化小鼠模型中评估不同组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。在本R21申请中，我们建议使用初始临床分离株集来检验这一假设。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，并且在C.新人类在目标1中，我们将收集来自不同临床分离株和后代的C. neoformans基因杂交。在目标2中，我们将进行全基因组关联研究（GWAS）和批量分离分析（BSA），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解释，以生成并优先考虑有关哪些基因组变异影响毒力的假设。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设的子集。该应用的意义在于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的可能新见解;以及在疾病监测，患者分层和新治疗靶点鉴定方面的未来应用潜力。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，和实验验证假设的因果变异。总之，这些研究将为C.新形式病毒及其在毒力中的作用，为研究界产生了重要的资源，并可能识别和验证影响毒力的致病变异。这一探索性的建议将为我们和其他人在基础生物学理解和潜在应用方面进一步研究更大的菌株集和后续工作奠定基础。