Global Genetic Interaction Profiling in Prokaryotes

描述（由申请人提供）：功能基因组学自然建立在比较原核基因组学最近的成功。这些方法在研究调节生长的途径方面的力量最近在酵母中得到了证明，但在细菌方面还不太发达，部分原因是缺乏实验工具。我们建议开发和利用原核生物的定量遗传方法，首先将这些方法的力量开放给两种生物，大肠杆菌，一种革兰氏阴性模式生物和肺炎链球菌，一种革兰氏阳性病原体。我们将建立我们在大肠杆菌中开发的方法，一次系统地引入两个基因破坏。我们将集体进行这一过程，最初将重点放在参与细胞包膜功能和DNA代谢的基因上，这样就可以分析和比较数千种成对破坏组合对细菌生长的影响。我们将应用分析工具，导致酵母细胞生物学的重要见解，我们的数据集和完善他们的细菌。这些方法已被证明对发现未表征基因的功能以及细胞内蛋白质通路和网络的性质具有强大的作用。我们将补充定量遗传相互作用研究与化学遗传倡议，从而实验连接药理学目标与基因参与其生物学。通过这种方式，一个更完整的关于细菌蛋白质如何发挥作用，以及细菌细胞生物学的不同领域如何相互联系的图景将被组装起来。此外，这项针对大肠杆菌和肺炎链球菌的研究将为现有的数百种细菌的比较基因组数据提供更多的力量。重点将放在通过可搜索的数据库传播结果（这将引起广泛的兴趣），该数据库将链接到其他相关网站（例如EcoliHub），以便整合不同的数据集，以及为社区提供将这种方法扩展到其他生物体所需的实验工具（菌株，质粒，库，计算机程序等）。细菌是自然界中最简单的生物之一。通过一次移除两个基因并观察效果，我们将建立大肠杆菌的4000个基因如何相互关联的第一张综合图片。这种类型的工作可以帮助我们了解细菌细胞是如何工作的，这些信息可以用来设计对工业有用的生物体，确定药物靶点，并改善对细菌性疾病的治疗。

DESCRIPTION (provided by applicant): Functional genomics builds naturally on recent successes in comparative prokaryotic genomics. The power of these methods for interrogation of the pathways regulating growth has recently been demonstrated for yeast, but the field is less developed for bacteria, partly due to a lack of experimental tools. We propose to develop and exploit quantitative genetic approaches for prokaroytic organisms, opening up the power of these approaches initially to two organisms, E. coli, a gram negative model organism and S. pneumoniae, a gram positive pathogen. We will build the methodology we developed in E. coli to systematically introduce gene disruptions two at a time. We will carry out the procedure en masse, initially focusing on genes involved in cell envelope function and DNA metabolism, so that the effect on bacterial growth of thousands of combinations of pair-wise disruptions can be analyzed and compared. We will apply the analytical tools that had led to important insights into yeast cell biology to our data set and refine them for bacteria. These approaches have proven powerful for discovering the function of uncharacterized genes and the nature of protein pathways and networks within the cell. We will complement quantitative genetic interaction studies with chemical genetic initiatives, thus experimentally linking pharmacological targets to the genes involved in their biology. In this way, a more complete picture of how bacterial proteins function, and how different areas of bacterial cell biology are interconnected, will be assembled. Moreover, this work in E. coli and S. pneumoniae will confer more power on existing comparative genomic data for hundreds of bacteria. Great emphasis will be placed on dissemination of the results (which will be of wide interest) via searchable database that will link to other relevant websites (e.g. EcoliHub) so that diverse datasets can be integrated, as well as providing the community with the experimental tools (strains, plasmids, libraries, computer programs etc.) needed to extend this approach to other organisms. Bacteria are among the simplest organisms in nature. By removing genes two at a time and observing the effect, we will build the first comprehensive picture of how the E.coli bacterium's 4000 genes relate to each other. This type of work can help us understand how a bacterial cell works, and the information can be used to design useful organisms for industry, to identify drug targets, and improve therapy for bacterial disease.