Comprehensive Mapping and Annotation of the E. coli Transcriptome

描述（由申请人提供）：一个跨学科的实验生物学家团队（Tyrrell Conway博士，巴里L。Wanner和Daoguo Zhou），计算生物学家（Michael R. Gribskov，Daisuke Kihara，and大卫W. Ussery）和数学建模者（Julio Collado-Vides博士和Bernhard O. Palsson）将解决在模型细胞E的单核苷酸水平上创建全转录组图谱的挑战。大肠杆菌K-12。总细胞RNA（RNA_Seq）cDNA的高通量深度测序结果将用于生成整个基因组中所有转录区域的综合图谱，以计算方式定义所有大小蛋白质编码和非编码RNA，并定量野生型细胞和选定转录因子突变体在各种生长条件下的表达水平。转录起始位点的综合地图将通过使用我们的顾问Joerg Vogel最近开发的协议来创建，以识别初级转录本。这些测量将与数学建模一起使用，以解码活细胞的第一个全面的转录网络，从而为整合不同数据类型的测量提供框架，这些数据类型来自遗传相互作用、蛋白质-DNA相互作用（ChIP芯片和ChIP_Seq）、蛋白质-蛋白质相互作用、代谢组学、表型分析、蛋白质组学、大肠杆菌的细胞定位。coli蛋白（E.例如，在一个实施例中，荧光标记的E. coli ASKA ORFeome clones at www.EcoliHub.org/GenoBase），大肠杆菌的三维成像（电子断层扫描）。大肠杆菌细胞，以及其他地方产生的其他数据集。这些研究将扩展到其他E.通过构建致病性大肠杆菌的全转录组图谱，coliEDL 933，原型肠出血性E.大肠杆菌O 157：H7（EHEC）在体外和小鼠肠中生长期间，导致第一个全面的细胞外体内表达转录组的产生。这些研究将采用我们的顾问Jay C.欣顿用于从小鼠（和感染的细胞培养物）中分离细菌RNA以制备用于深度测序的cDNA。类似的程序将用于在体外生长期间以及在感染培养的巨噬细胞和上皮细胞之后生成鼠伤寒沙门氏菌血清型的全转录组图谱，从而创建第一个全面的细胞内体内表达转录组。在整个项目过程中获得的结果将根据NIH数据共享指南公开，用于分析，可视化，比较和下载www.EcoliHub.org/GenExpDB。同样地，在这个项目中实现或开发的所有计算工具将免费提供给www.EcoliHub.org的用户。大肠杆菌的基线信息量和实验易处理性的所有测量所需的全细胞系统生物学。建立了E.大肠杆菌的研究将为建立大肠杆菌的数学模型奠定基础。大肠杆菌的生物化学和生理学，从而创造了一个计算机化的，交互式的“虚拟细胞”。“解决E.大肠杆菌细胞将为生命的基本性质提供重要的新见解。 公共卫生相关性：没有其他生物接近E。大肠杆菌的组成部分或细胞过程的现有知识的绝对深度或广度。了解这些过程如何相互作用形成活细胞将需要它们的表征，量化，整合和数学建模-即系统生物学。一个完整的E.大肠杆菌K-12将为预测包括致病微生物在内的其他细胞的行为提供基础。

DESCRIPTION (provided by applicant): An interdisciplinary team of experimental biologists (Drs. Tyrrell Conway, Barry L. Wanner, and Daoguo Zhou), computational biologists (Drs. Michael R. Gribskov, Daisuke Kihara, and David W. Ussery), and mathematical modelers (Drs. Julio Collado-Vides and Bernhard O. Palsson) will tackle the challenge of creating whole transcriptome maps at the single nucleotide level of the model cell E. coli K-12. Results from high-throughput deep sequencing of cDNAs of total cellular RNA (RNA_Seq) will be used to generate comprehensive maps of all transcribed regions across the entire genome, to define computationally all large and small protein-encoding and non-encoding RNAs, and to quantify expression levels under a variety of growth conditions in wild-type cells and selected transcription factor mutants. Comprehensive maps of transcription start sites will be created by use of a protocol recently developed by our consultant Joerg Vogel to identify primary transcripts. These measurements will be used together with mathematical modeling to decode the first comprehensive transcriptional network of a living cell, thereby providing the framework for integration of measurements of different data types, from results for genetic interactions, protein-DNA interactions (ChIPchip and ChIP_Seq), protein-protein interactions, metabolomics, phenotyping, proteomics, cellular localization of E. coli proteins (e. g., imaging data for fluorescently tagged E. coli ASKA ORFeome clones at www.EcoliHub.org/GenoBase), three-dimensional imaging (electron tomography) of E. coli cells, and for other data sets generated elsewhere. These studies will be extended to other E. coli by development of whole transcriptome maps of pathogenic E. coli EDL933, the prototype terohemorrhagic E. coli O157:H7 (EHEC) during growth in vitro and in the mouse intestine, leading to creation of the first comprehensive extracellular in vivo expression transcriptome. These studies will be carried out with methods developed by our consultant Jay C. Hinton for isolation of bacterial RNA from mice (and infected cell cultures) for preparation of cDNAs for deep sequencing. Similar procedures will be used to generate whole transcriptome maps of Salmonella enterica serovar Typhimurium during growth in vitro and following infection of cultured macrophages and epithelial cells, thereby creating the first comprehensive intracellular in vivo expression transcriptome. Results obtained throughout the course of this project will be made public in accordance with NIH data sharing guidelines, for analysis, visualization, comparison, and downloading at www.EcoliHub.org/GenExpDB. Likewise, all computational tools implemented or developed in this project will be freely provided to users at www.EcoliHub.org. No organism can rival E. coli in the amount of baseline information and experimental tractability for all the measurements required for whole cell systems biology. The development of whole transcriptome maps of E. coli will lay the foundation for development of robust mathematical models of E. coli biochemistry and physiology and thereby the creation of a computerized, interactive "virtual cell." Solving the E. coli cell will provide critical new insights into the fundamental nature of life. PUBLIC HEALTH RELEVANCE: No other organism comes close to E. coli in the sheer depth or breadth of existing knowledge of its component parts or cellular processes. Understanding how these processes interact to form a living cell will require their characterization, quantification, integration, and mathematical modeling - that is, Systems Biology. A comprehensive whole transcriptome map of E. coli K-12 will provide the groundwork for predicting the behavior of other cells, including disease-causing microbes.