Systems approach to study sRNAs in Escherichia coli

我的NSERC研究计划的总体目标是了解小非编码RNA（sRNA）在细菌细胞应激中的作用。我建议联合收割机高通量和分子生物学的方法来研究如何siRNA介导的基因调控有助于模型细菌，大肠杆菌的生长和应激反应。E.大肠杆菌表达约200种sRNA，其中大多数编码在基因组的基因间区域或嵌入蛋白质编码基因的非翻译部分。sRNA基因通常由生长环境的变化诱导，例如由于营养胁迫或化学扰动。一旦表达，sRNA通过与部分互补的mRNA碱基配对并改变翻译和/或RNA稳定性来调节蛋白质合成。sRNA的基因调控被认为对细菌的应激反应至关重要。有趣的是，很少有例子表明，破坏sRNA介导的基因调控导致细菌生长或存活中可辨别的表型。事实上，我们对sRNA功能的大部分了解来自对少数sRNA的深入研究，而大多数sRNA的功能尚不清楚。近年来，我的团队率先开发了大规模研究大肠杆菌基因功能的工具。杆菌我们开发了一套仪器和软件，用于测量高密度菌落阵列中的细菌生长速率。我们还创建了一个成像设备，由3D打印外壳，单板计算机，相机和软件组成，用于研究菌落阵列中的荧光。这些工具使我们能够在系统方法中取得成功，以理解我们通常使用化学或遗传扰动的基因功能。到目前为止，我们的努力只集中在有助于细菌适应性的蛋白质编码基因上。在拟议的研究中，我们将努力了解sRNAs对细菌生长和细胞应激反应的重要性。目前细菌基因组的暗物质，我们的目标是描述一个全基因组的sRNA功能网络在E。杆菌短期目标包括：1。探索细菌细胞应激中sRNAs的功能网络2.测试sRNA功能网络提出的假设3.虽然迄今为止旨在理解sRNA功能的方法在很大程度上是简化的，但所提出的方法将允许我们询问大量的扰动及其组合。这些将包括基因突变，通过一次删除一个或多个sRNA基因，以及不同的环境压力。此外，我们将在数百种条件下以高时间分辨率分析sRNA启动子的转录。这种系统方法将为使用常规生物化学和分子遗传学方法进行详细研究提供新的假设。总之，我们将解决在理解细菌sRNAs对细胞应激的重要性方面的一个主要知识缺口。

The overall objective of my NSERC research program is to understand the role of small non-coding RNAs (sRNA) to cell stress in bacteria. I propose to combine high-throughput and molecular biology approaches to study how sRNA-mediated gene regulation contributes to the growth and stress responses of the model bacterium, Escherichia coli. E. coli expresses some 200 sRNAs, most of which are encoded in intergenic regions of the genome or embedded within untranslated portions of protein-coding genes. sRNA genes are typically induced by changes in the growth environment due, for example, to nutrient stress or chemical perturbants. Once expressed, sRNAs regulate protein synthesis by base-pairing to partially complementary mRNAs and altering translation and/or RNA stability. Gene-regulation by sRNAs is thought to be vital to bacterial stress responses. Paradoxically, there are few examples where disruption of sRNA-mediated gene regulation results in a discernable phenotype in bacterial growth or survival. Indeed, much of our knowledge of sRNA function comes from in-depth studies on a small handful of sRNAs, leaving the function of most unknown. In recent years, my group has pioneered the development of tools for large-scale investigations of gene function in E. coli. We developed a suite of instrumentation and software for measuring bacterial growth rates in high-density colony arrays. We have also created an imaging device, comprised of a 3D-printed housing, single board computer, camera and software, for studying fluorescence in colony arrays. These tools have us uniquely positioned for success in systems approaches to understanding gene function where we typically use chemical or genetic perturbation. To date, our efforts have focused exclusively on protein-coding genes that contribute to bacterial fitness. In the proposed research we will work to understand the importance of sRNAs to bacterial growth and cell stress responses. Currently the dark matter of bacterial genomes, we aim to describe a genome-wide functional network for sRNAs in E. coli. Short-term objectives include: 1. Probe the functional network of sRNAs in bacterial cell stress 2. Test hypotheses posed by the sRNA functional network 3. Measure sRNA expression dynamics in different growth conditions While approaches to date aimed at understanding sRNA function have largely been reductionist, the proposed approach will allow us to interrogate a large number of perturbations and combinations thereof. These will include genetic mutations, through deletion of one or more sRNA genes at a time, and diverse environmental stresses. In addition we will profile transcription of sRNA promoters across hundreds of conditions with high temporal resolution. This systems approach will provide new hypotheses for detailed study using conventional biochemical and molecular genetic methods. In all we will address a major knowledge gap in understanding the importance of bacterial sRNAs to cell stress.