CAPSULE REGULATION AND VIRULENCE IN CRYPTOCOCCUS NEOFORMANS

新型隐球菌的荚膜调节和毒力

• 批准号: 9261466
• 负责人: MICHAEL R BRENT
• 金额: $ 45.48万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9261466
• 关键词: Acquired Immunodeficiency Syndrome; Affect; Area; Binding; Biological Assay; Biology; Categories; ChIP-seq; Characteristics; Communities; Complex; Computational Biology; Cryptococcus neoformans; Cues; Data; Data Set; Development; Disease; Environment; Event; Foundations; Funding; Gene Expression; Gene Targeting; Genes; Genetic Engineering; Genetic Transcription; Genomics; Goals; Grant; Growth; Human; Immunocompromised Host; Individual; Investigation; Knowledge; Maps; Meningoencephalitis; Microbe; Modeling; Molecular Computations; Mus; Organism; Pathogenesis; Pathogenicity; Pathway interactions; Patients; Phenotype; Polysaccharides; Population; Post-Transcriptional Regulation; Process; Regulation; Research; Resources; Severity of illness; Source; Stimulus; Testing; Therapeutic; Thick; Time; Transcriptional Regulation; Virulence; Virulence Factors; Work; capsule; computational network modeling; environmental change; experience; fascinate; fungus; in vivo; insight; killings; mutant; network models; public health relevance; response; skills; transcription factor; transcriptome sequencing

 DESCRIPTION (provided by applicant): The fungus Cryptococcus neoformans causes meningoencephalitis that kills more than 625,000 people each year. The goal of this research is to produce a mechanistic understanding of how the environmental changes experienced by this microbe upon entry into the human host stimulate the expression of virulence factors that advance fungal disease. There are major gaps in our understanding of how C. neoformans senses that it is in a host and coordinates a transcriptional response that leads to virulence factor expression. At the top of this chain of events, our knowledge of how individual characteristics of the host environment stimulate changes in transcription factor (TF) activity is patchy. At an intermediate level, we probably do not yet know all the TFs involved in the cryptococcal response to environmental change, nor how TF activities change during induction. Downstream of the TFs, we do not know which of their effects on gene expression are critical for the development of virulence factors. In this renewal application, we propose to use a powerful combination of molecular and computational biology to fill these gaps, focusing on the major cryptococcal virulence factor, its polysaccharide capsule. In Aim 1 we will exploit recent technical advances to assay strains deleted for all non-essential TFs for gene expression (by RNA-Seq) and capsule phenotypes (using a new automated assay and ELISAs). Incorporating this data set into our initial map of the TF network will greatly enhance it, informing our subsequent studies. In Aim 2 we propose to collect gene expression data on selected TFs at multiple time points during capsule induction. This will allow us to computationally model the network as a dynamic circuit that processes information from the environment and coordinates a complex transcriptional response. In Aim 3 we propose to identify the key changes in TF activity that transduce each capsule-inducing stimulus from the environment. We will computationally estimate these activity changes and then test, by genetic engineering, whether selected changes in TF activity are sufficient to substitute for a given environmental stimulus. In Aim 4, we will move downstream in the pathway and computationally generate hypotheses about which transcriptional changes in genes encoding non-regulatory proteins are necessary for capsule growth. We will then test each hypothesis by genetically eliminating the corresponding transcriptional change. This range of studies will be enabled by the synergistic efforts of two labs with complementary skill sets. This work will build on the foundation provided by our highly productive first grant period to elucidate fundamental mechanisms of transcriptional regulation, fill gaps in our understanding of the mechanisms of cryptococcal pathogenesis, and provide resources that will powerfully enable future research progress in areas ranging from fungal pathogenesis to computational genomics.

 描述（由申请人提供）：新型隐球菌会引起脑膜脑炎，每年导致超过 625,000 人死亡。这项研究的目的是从机制上理解这种微生物在进入人类宿主后所经历的环境变化如何刺激促进真菌疾病的毒力因子的表达。我们对新型隐球菌如何感知其在宿主体内并协调导致毒力因子表达的转录反应的理解存在重大差距。在这一系列事件的顶部，我们对宿主环境的个体特征如何刺​​激转录因子（TF）活性变化的了解是不完整的。在中间水平上，我们可能还不知道所有参与隐球菌对环境变化反应的转录因子，也不知道转录因子活性在诱导过程中如何变化。在转录因子的下游，我们不知道它们对基因表达的哪些影响对于毒力因子的发展至关重要。在这个更新的应用中，我们建议使用分子和计算生物学的强大组合来填补这些空白，重点关注主要的隐球菌毒力因子，即其多糖胶囊。在目标 1 中，我们将利用最新的技术进步来分析删除所有非必需 TF 的菌株，以进行基因表达（通过 RNA 测序）和荚膜表型（使用新的自动化分析和 ELISA）。将此数据集纳入我们的 TF 网络初始地图将极大地增强它，为我们后续的研究提供信息。在目标 2 中，我们建议在胶囊诱导期间的多个时间点收集选定 TF 的基因表达数据。这将使我们能够通过计算将网络建模为动态电路，处理来自环境的信息并协调复杂的转录响应。在目标 3 中，我们建议确定 TF 活性的关键变化，这些变化可转换来自环境的每个胶囊诱导刺激。我们将通过计算估计这些活性变化，然后通过基因工程测试 TF 活性的选定变化是否足以替代给定的环境刺激。在目标 4 中，我们将向该通路的下游移动，并通过计算生成关于编码非调节蛋白的基因的转录变化对于荚膜生长所必需的假设。然后，我们将通过基因消除相应的转录变化来检验每个假设。这一系列的研究将通过两个具有互补技能的实验室的协同努力来实现。这项工作将建立在我们高效的第一个资助期提供的基础上，以阐明转录调控的基本机制，填补我们对隐球菌发病机制理解的空白，并提供资源，有力地促进从真菌发病机制到计算基因组学等领域的未来研究进展。