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.

项目概要影响隐球菌致病性的自然基因组变异新型隐球菌是一种全球性病原体，每年导致数十万人因艾滋病病毒感染者死亡个人和非艾滋病患者群体发病率的增加。 C. 新型隐球菌菌株收集自 pa- 患有隐球菌脑膜炎的患者已被用来阐明新型隐球菌的进化并努力纠正通过体外测量（例如毒力因子产生或真菌生长）来确定晚期疾病结果。我们知道不同的基因组序列与不同的临床结果相关。然而，我们不知道哪种自然基因组变异是造成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。实现这一目标的第一步是识别自然发生的变异，这些变异可以经实验证明可在单基因分辨率下影响毒力。下一步是表征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和基因组方法与实验跟踪相结合，以识别、验证和表征自然集会发生显着影响隐球菌毒力的变异。这个假设得到了我们的支持令人信服的初步数据，其中两种不同的遗传方法暗示同一基因组区域中的变异因为影响传染性。我们建议通过追求三个目标来实现我们的目标：目标 1 是使用两种不同的、互补的统计数据遗传学方法发现含有影响真菌病毒的自然发生变异的基因组区域伦斯。目标 2 是进一步应用遗传学，在表达分析和突变研究的支持下，完善这些区域并识别其中特定的高优先级基因。目标 3 是利用基因组工程来验证选定的变异基因对毒力的影响，并评估它们对真菌基因表达、生理学的影响 ogy 和小鼠模型中的致病性。应用公正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的潜在靶点。表征这些变体也将为未来的研究铺平道路其作用的机制基础的研究，这将阐明隐球菌生物学的关键特征和发病。我们的方法适用于隐球菌生物学中的其他基本问题，并且具有潜力主要针对其他微生物病原体。最后，我们的研究将产生有价值的试剂和数据集，加强其他新型隐球菌研究人员的研究。

项目成果

期刊论文数量（2）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

How host-like signals drive gene expression and gene expression drives capsule expansion in Cryptococcus neoformans.

类宿主信号如何驱动基因表达，基因表达如何驱动新生隐球菌的荚膜扩张。

DOI：
发表时间：
2023-04-20
期刊：
影响因子：
0
作者：
Jung, Jeffery;Kang, Yu Sung;Brown, Holly;Mateusiak, Chase;Doering, Tamara L;Brent, Michael R
通讯作者：
Brent, Michael R

Unbiased discovery of natural sequence variants that influence fungal virulence.

公正地发现影响真菌毒力的自然序列变异。

DOI：
发表时间：
2023-11-08
期刊：
影响因子：
30.3
作者：
Agustinho, Daniel Paiva;Brown, Holly Leanne;Chen, Guohua;Gaylord, Elizabeth Anne;Geddes;Brent, Michael Richard;Doering, Tamara Lea
通讯作者：
Doering, Tamara Lea