Comprehensive Mapping and Annotation of the E. coli Transcriptome

描述(由申请人提供)：一个由实验生物学家(Tyrrell Conway博士、Barry L.Wanner博士和周道国博士)、计算生物学家(Michael R.Griskov博士、Kihara Daisuke Kihara博士和David W.Ussery博士)以及数学建模师(Julio Collado-Vdes博士和Bernhard O.Palsson博士)组成的跨学科团队将解决在模型细胞E.Coli K-12的单核苷酸水平上创建完整转录组图的挑战。细胞总RNA(RNA_Seq)的高通量深度测序结果将用于生成整个基因组所有转录区域的全面图谱，以计算方式定义所有大小蛋白编码和非编码RNA，并量化各种生长条件下野生型细胞和选定的转录因子突变体中的表达水平。将使用我们的顾问Joerg Vogel最近开发的一种程序来创建全面的转录起始点地图，以识别初级转录。这些测量结果将与数学模型一起用于破译活细胞的第一个全面转录网络，从而为整合不同数据类型的测量结果提供框架，这些数据类型来自遗传相互作用、蛋白质-DNA相互作用(ChIPChip和ChIP_Seq)、蛋白质-蛋白质相互作用、代谢组学、表型鉴定、蛋白质组学、大肠杆菌蛋白质的细胞定位(例如，www.EcoliHub.org/genobase上荧光标记的大肠杆菌ASKA ORFeome克隆的成像数据)、大肠杆菌细胞的三维成像(电子断层扫描)，以及其他地方产生的其他数据集。通过开发致病性大肠杆菌EDL933的完整转录组图谱，这些研究将扩展到其他大肠杆菌。EDL933是出血性大肠杆菌O157：H7(EHEC)的原型，在体外和小鼠肠道中生长，导致第一个全面的细胞外体内表达转录组的创建。这些研究将使用我们的顾问Jay C.Hinton开发的方法从小鼠(和受感染的细胞培养物)中分离细菌RNA，以准备用于深度测序的cDNA。类似的程序将被用来生成肠伤寒沙门氏菌在体外生长过程中以及在培养的巨噬细胞和上皮细胞感染后的完整转录组图谱，从而创建第一个全面的细胞内表达转录组。根据NIH数据共享指南，在整个项目过程中获得的结果将在www.EcoliHub.org/GenExpDB上公布，用于分析、可视化、比较和下载。同样，在该项目中实施或开发的所有计算工具都将免费提供给www.EcoliHub.org上的用户。在整个细胞系统生物学所需的所有测量的基线信息量和实验可控性方面，没有一种生物能与大肠杆菌相媲美。大肠杆菌整个转录组图谱的开发将为建立健全的大肠杆菌生物化学和生理数学模型奠定基础，从而创建一个计算机化的、交互的“虚拟细胞”。解决大肠杆菌细胞将提供对生命根本本质的关键新见解。 与公共卫生相关：在现有的有关其组成部分或细胞过程的知识的深度或广度上，没有其他生物能与大肠杆菌相提并论。理解这些过程如何相互作用以形成活细胞，将需要它们的表征、量化、集成和数学建模--即系统生物学。一张完整的大肠杆菌K-12转录组图谱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.