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Natural genomic variants that influence cryptococcal pathogenicity

影响隐球菌致病性的自然基因组变异

基本信息

批准号：
10647845
负责人：
Tamara L Doering
金额：
$ 59.37万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-07-01 至 2025-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10647845
关键词：
Alleles Antifungal Agents Antifungal Therapy Applied Genetics Biological Biology Candidate Disease Gene Cessation of life Clinical Collection Communities Cryptococcal Meningitis Cryptococcosis Cryptococcus Cryptococcus neoformans Cryptococcus neoformans infection DNA Sequence Dangerousness Data Data Set Disease Disease Outcome Disease Progression Drug Targeting Engineering Environment Evolution Fungal Genes Future Gene Expression Genes Genetic Genome Genome engineering Genomic Segment Genomics Goals Growth HIV In Vitro Individual Investigation Laboratories Laboratory culture Lung Measures Meningoencephalitis Methods Microbe Molecular Morbidity - disease rate Mus Organism Outcome Parents Pathogenesis Pathogenicity Patients Persons Phenotype Physiology Population Process Production Reagent Recombinants Records Research Research Personnel Resolution Resources Severity of illness Stress Structure Surveys Validation Variant Virulence Virulence Factors comorbidity drug development falls fascinate follow-up fungus genetic analysis genetic variant innovation interest mouse model mutant offspring pathogen pathogenic fungus pathogenic microbe patient population resilience therapeutic biomarker therapeutic target

项目摘要

PROJECT SUMMARY Natural genomic variants that influence 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. C. neoformans strains collected from pa- tients with cryptococcal meningitis have been used to elucidate C. neoformans evolution and in efforts to corre- late disease outcome with in vitro measures such as virulence factor production or fungal growth. We know that distinct genome sequences are associated with varied clinical outcomes. However, we do not know which natural genomic variants are responsible for the differential virulence of clinical isolates. Our long-term goal is to understand the molecular mechanisms by which natural variation in the cryptococcal genome determines pathogenicity. A first step toward this goal is to identify naturally occurring variants that can be experimentally proven to influence virulence, at single-gene resolution. The next step is to characterize the impact of variants in these genes on cryptococcal biology and disease progression. We hypothesize that we can combine genetic and genomic methods with experimental follow-up to identify, validate, and characterize natu- rally occurring variants that significantly influence cryptococcal virulence. This hypothesis is supported by our compelling preliminary data, in which two distinct genetic methods implicate variants in the same genomic region as influencing infectivity. We propose to achieve our goals by pursuing three Aims: Aim 1 is to use two distinct, complementary statistical genetics methods to discover genomic regions containing naturally occurring variants that influence fungal viru- lence. Aim 2 is to further apply genetics, supported by expression analysis and mutant studies, to refine these regions and identify specific high-priority genes within them. Aim 3 is to use genome engineering to validate the influence of selected variant genes on virulence and to assess their effects on fungal gene expression, physiol- ogy, and pathogenicity in a mouse model. Applying an unbiased strategy to identify genes harboring natural variants that influence virulence will highlight new potential targets for antifungal therapy. Characterizing these variants will also pave the way for future inves- tigations of the mechanistic basis of their effects, which will elucidate key features of cryptococcal biology and pathogenesis. Our methods are applicable to other fundamental questions in cryptococcal biology, and poten- tially to other microbial pathogens. Finally, our studies will produce valuable reagents and data sets that will enhance investigations by other C. neoformans researchers.

项目总结影响隐球菌致病力的天然基因组变异新生隐球菌是一种全球性病原体，每年在HIV+中造成数十万人死亡在非艾滋病患者群体中，个人和发病率不断增加。从巴氏杆菌分离的新生隐孢子菌隐球菌性脑膜炎已被用来阐明新生葡萄球菌的进化和努力纠正的努力。通过体外措施，如毒力因子的产生或真菌生长，晚期疾病的结果。我们知道不同的基因组序列与不同的临床结果相关。然而，我们不知道是哪种天然的基因组变异是导致临床分离株毒力差异的原因。我们的长期目标是了解隐球菌自然变异的分子机制基因组决定致病性。迈向这一目标的第一步是确定自然发生的变异，这些变异可以被实验证明影响毒力，在单基因分辨率。下一步是描述这些基因变异对隐球菌生物学和疾病进展的影响。我们假设我们可以将遗传学和基因组学方法与实验跟踪相结合，以鉴定、验证和表征自然界。重振显著影响隐球菌毒力的变种。这一假设得到了我们的令人信服的初步数据，其中两种不同的遗传方法涉及同一基因组区域的变异因为它影响传染性。我们建议通过追求三个目标来实现我们的目标：目标1是使用两个截然不同的、互补的统计数据发现包含影响真菌病毒的自然发生变异的基因组区域的遗传学方法- 伦斯。目标2是在表达分析和突变研究的支持下，进一步应用遗传学来提炼这些并确定其中特定的高优先级基因。目标3是使用基因组工程来验证筛选的变异基因对致病力的影响以及它们对真菌基因表达的影响。 OGY，并在小鼠模型中致病。应用不偏不倚的策略来识别含有影响毒力的自然变异的基因将突出抗真菌治疗的新潜在靶点。确定这些变体的特征也将为未来的投资铺平道路- 其作用的机制基础的触发，这将阐明隐球菌生物学和发病机制。我们的方法适用于隐球菌生物学中的其他基本问题，并有可能-- 主要是对其他微生物病原体的影响。最后，我们的研究将产生有价值的试剂和数据集，加强其他新生隐孢子虫研究人员的调查。