Systematic Analysis of Morphogenesis, Commensalism, and Virulence in a Leading Human Fungal Pathogen

主要人类真菌病原体的形态发生、共生性和毒力的系统分析

• 批准号: 10574728
• 负责人: LEAH Elizabeth Cowen
• 金额: $ 60.3万
• 依托单位: UNIVERSITY OF TORONTO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10574728
• 关键词: Address; Affect; Alleles; Aneuploidy; Animal Disease Models; Anoxia; Antifungal Agents; Bar Codes; Biological; Biological Assay; Blood Circulation; Candida albicans; Candidiasis; Carbon; Carbon Dioxide; Cell physiology; Cells; Cellular Morphology; Cellular Structures; Cessation of life; Clinical; Collection; Communities; Cost of Illness; Cues; Data Set; Defect; Development; Diagnostic tests; Diploidy; Disease; Dissection; Drug Targeting; Drug resistance; Economics; Engineering; Essential Genes; Filament; Filtration; Fostering; Foundations; Funding; Fungi Model; Gene Expression; Genes; Genetic; Genome; Glucosamine; Health; Hospitals; Human; Image Analysis; Immune; In Vitro; Infection; Investments; Life; Messenger RNA; Methods; Modeling; Molecular; Morphogenesis; Mus; Mutation; Organism; Pathogenesis; Pathogenicity; Patients; Persons; Phagocytosis; Pharmaceutical Preparations; Phenotype; Positioning Attribute; Protocols documentation; RNA; RNA Splicing; Resistance development; Resolution; Resources; Saccharomycetales; Sepsis; Serum; Source; Symbiosis; Systemic infection; Systems Biology; Temperature; Testing; Tetracyclines; Toxic effect; Transcript; Validation; Virulence; Work; Yeast Model System; Yeasts; base; drug testing; fitness; functional genomics; fungus; gene replacement; genetic analysis; genetic approach; genetic resource; genome wide screen; genome-wide; genomic platform; gut colonization; high resolution imaging; high throughput analysis; human disease; human pathogen; immunoregulation; in vitro testing; in vivo; insight; machine learning model; macrophage; mortality; mouse model; mutant; next generation sequencing; novel; novel therapeutic intervention; opportunistic pathogen; pathogen; pathogenic fungus; programs; promoter; public database; response; screening; social; trait; transcription factor; transcriptomics; whole genome

SUMMARY/ABSTRACT Fungal pathogens pose a devastating threat to human health, infecting billions of people worldwide and causing more than 1.5 million deaths each year. Candida albicans is one of the most pervasive fungal pathogens, killing almost 40% of people suffering from bloodstream infections. Treating these infections is extremely difficult, as fungi are closely related to humans and there are very few drugs that kill the fungus without host toxicity. With the emergence of drug resistance, the development of new therapeutic strategies is now crucial. To address this important clinical need and identify new antifungal drug targets, it is critical to uncover mechanisms that enable C. albicans to cause life-threatening human disease. We are one of the first academic labs to obtain a powerful functional genomics resource that we are uniquely positioned to expand to allow us to test the function of almost every gene in the C. albicans genome. This resource includes a collection of conditional expression strains that covers ~40% of the genome where one allele of a target gene is deleted in the diploid pathogen, and expression of the remaining wild-type allele is governed by the tetracycline-repressible promoter. During the prior funding period we: developed a pipeline to expand the resource to genome scale, optimized a functional genomics platform for massively parallel analysis of fungal virulence traits using next generation sequencing with pooled assays to quantify the relative proportion of each strain, which are uniquely marked with molecular barcodes; optimized high-resolution image analysis of cellular morphology and structures; and developed assays for identifying genes important for commensalism, virulence, and interaction with host immune cells. Our efficient high-throughput analyses established the power of systematic genetic analysis to uncover new biological insights that could not have been predicted based on current paradigms and enabled focused, hypothesis-driven dissection of key mechanisms governing host- pathogen interactions. Our studies will provide the first global analysis of C. albicans morphogenesis, commensalism, and virulence, and will reveal fundamental biological mechanisms that could not be predicted without a systematic genetic approach. Our studies will: 1) complete the collection of tetracycline-repressible conditional expression strains to cover non-essential genes, since genes required for pathogen viability in vitro provide little insight into host adaptation or virulence; 2) identify novel regulators of key virulence traits such as morphogenesis; and 3) identify determinants of C. albicans host adaptation and virulence on a genome scale. Our comprehensive strain resources and compendium of phenotypic profiles will be made available to the community, advancing the field with a publicly accessible database and interpretive machine learning model to maximize insight. This work will provide the most comprehensive functional genomics resource for any fungal pathogen and will reveal genes governing host adaptation, revealing new strategies to cripple fungal pathogens.

摘要/摘要 真菌病原体对人类健康构成毁灭性威胁，感染全世界数十亿人， 每年造成超过 150 万人死亡。白色念珠菌是最普遍的真菌病原体之一， 导致近 40% 的血液感染患者死亡。治疗这些感染极其困难 由于真菌与人类关系密切，能够杀死真菌而不对宿主产生毒性的药物很少。和 耐药性的出现，开发新的治疗策略现在至关重要。致地址 为了满足这一重要的临床需求并确定新的抗真菌药物靶点，揭示机制至关重要 使白色念珠菌能够引起危及生命的人类疾病。 我们是最早获得强大功能基因组学资源的学术实验室之一 具有独特的扩展能力，使我们能够测试白色念珠菌基因组中几乎每个基因的功能。 该资源包括一系列条件表达菌株，覆盖约 40% 的基因组，其中一个 二倍体病原体中目标基因的等位基因被删除，剩余野生型等位基因的表达为 由四环素抑制型启动子控制。在之前的资助期间，我们： 开发了一条管道 将资源扩展到基因组规模，优化功能基因组学平台以进行大规模并行分析 使用下一代测序和合并分析来量化真菌毒力性状的相对比例 每个菌株都有独特的分子条形码标记；优化的高分辨率图像分析 细胞形态和结构；并开发了鉴定对共生主义重要的基因的分析方法， 毒力以及与宿主免疫细胞的相互作用。我们高效的高通量分析建立了力量 系统的遗传分析来揭示新的生物学见解，这些见解无法根据 当前的范式，并能够对控制宿主的关键机制进行有针对性的、假设驱动的剖析 病原体相互作用。我们的研究将提供对白色念珠菌形态发生的首次全球分析， 共栖性和毒力，并将揭示无法被证实的基本生物机制 无需系统的遗传方法即可预测。 我们的研究将：1）完成四环素抑制条件表达菌株的收集，以 涵盖非必需基因，因为病原体在体外生存所需的基因几乎无法深入了解宿主 适应或毒力； 2）确定形态发生等关键毒力特征的新型调节因子； 3) 识别 白色念珠菌在基因组规模上宿主适应和毒力的决定因素。我们的综合应变 将向社区提供资源和表型概况概要，推动该领域的发展 具有可公开访问的数据库和解释性机器学习模型，以最大限度地提高洞察力。这项工作将 为任何真菌病原体提供最全面的功能基因组学资源，并将揭示 控制宿主适应的基因，揭示了削弱真菌病原体的新策略。