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The spatial organization of the Plasmodium genome throughout its infectious cycle

疟原虫基因组在整个感染周期中的空间组织

基本信息

批准号：
8862371
负责人：
Karine Gaelle Le Roch
金额：
$ 45.2万
依托单位：
UNIVERSITY OF WASHINGTON
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-06-07 至 2016-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8862371
关键词：
Accounting Agreement Antibodies Antimalarials Architecture Area Biology Cell Cycle Cell Nucleus ChIP-seq Chromatin Chromatin Structure Chromosome Structures Communicable Diseases Computer Simulation Computer software Computing Methodologies DNA DNA Sequence DNA Structure DNA-Binding Proteins Data Data Set Development Disease Drug Design Drug Targeting Epigenetic Process Erythrocytes Event Exhibits Gene Expression Gene Expression Regulation Genes Genetic Transcription Genome Genomic DNA Genomics Goals Health Human Human Genome Laboratories Life Cycle Stages Machine Learning Malaria Maps Measurement Messenger RNA Metabolic stress Methodology Methods Microscopy Modeling Molecular Molecular Profiling Nuclear Nucleosomes Organism Parasite Control Parasite resistance Parasites Pattern Pharmaceutical Preparations Phase Plasmodium Plasmodium falciparum Play Publishing Research Personnel Resolution Role Series Staging Structure Techniques Technology Time Time Series Analysis Transcriptional Regulation Vaccines Variant Virulence Virulent base combat computerized tools design genome-wide histone modification improved in vivo innovation insight novel novel therapeutic intervention novel therapeutics predictive modeling response three dimensional structure three-dimensional modeling tool transcription factor vaccine development

项目摘要

DESCRIPTION (provided by applicant): Malaria remains one of the most deadly infectious diseases in the developing world. The absence of a vaccine and the development of parasite resistance to commonly used antimalarial drugs underscore the urgent need for new therapeutic approaches. The goal of this project is to generate insights into the mechanisms whereby Plas- modium falciparum, the parasite responsible for the most virulent form of malaria, regulates its genes' expression throughout its life cycle. Mechanisms controlling gene expression in the parasite are still poorly understood. Increasing evidence indicates that control of gene expression in Plasmodium occurs at multiple levels, via local protein-DNA binding events, patterns of histone modifications, local chromatin structure and nucleosome occupancy, and large-scale chromatin structure. A variety of existing genome-wide data sets, including the genomic DNA sequence as well as measurements of RNA expression levels and nucleosome occupancy, provide insight into many aspects of this regulatory machinery. However, a global picture of the structure of DNA in the nucleus of the parasite is not yet available. This project will apply a recently developed technology to map in Plasmodium all intra- and inter-chromosomal interactions at kilobase resolution throughout the parasite life cycle. These data will be used to build a dynamic three-dimensional model of the Plasmodium genome in vivo. The project will also generate a series of maps of histone modifications genome-wide. Finally, these two new data sets, along with existing data sets, will be integrated using machine learning methods to produce a predictive model of gene expression across the Plasmodium eryrthrocytic cycle. Rational drug design requires a detailed understanding of the molecular basis of disease. By providing fundamental insight into the regulatory mechanisms of the malaria parasite, this project will improve our ability to design new drugs and novel lines of defense against malaria.

描述（由申请人提供）：疟疾仍然是发展中国家最致命的传染病之一。缺乏疫苗和寄生虫对常用抗疟药物产生抗药性，突出表明迫切需要新的治疗方法。该项目的目标是深入了解恶性疟原虫（恶性疟原虫）在其整个生命周期中调节其基因表达的机制。控制寄生虫基因表达的机制仍然知之甚少。越来越多的证据表明，疟原虫基因表达的控制发生在多个层面上，通过局部蛋白质-DNA结合事件，组蛋白修饰的模式，局部染色质结构和核小体占用，以及大规模的染色质结构。各种现有的全基因组数据集，包括基因组DNA序列以及RNA表达水平和核小体占有率的测量，提供了对这种调控机制的许多方面的见解。然而，目前还没有寄生虫细胞核DNA结构的全球图片。该项目将应用最近开发的技术，以酶解的方式绘制疟原虫整个生命周期中所有染色体内和染色体间相互作用的图谱。这些数据将用于建立疟原虫基因组在体内的动态三维模型。该项目还将生成一系列全基因组组组蛋白修饰的图谱。最后，这两个新的数据集，沿着与现有的数据集，将使用机器学习方法进行整合，以产生一个预测模型的基因表达在整个疟原虫红细胞周期。合理的药物设计需要详细了解疾病的分子基础。通过提供对疟疾寄生虫调节机制的基本见解，该项目将提高我们设计新药和新的疟疾防御线的能力。