Systems approach to study sRNAs in Escherichia coli

研究大肠杆菌 sRNA 的系统方法

• 批准号: RGPIN-2019-07090
• 负责人: Brown, Eric
• 金额: $ 5.03万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=739303
• 关键词: Systems; approach; study; sRNAs; Escherichia

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.

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。我建议结合高通量和分子生物学方法来研究srna介导的基因调控如何促进模式细菌大肠杆菌的生长和应激反应。大肠杆菌表达约200种sRNAs，其中大多数编码在基因组的基因间区域或嵌入在蛋白质编码基因的未翻译部分。sRNA基因通常是由生长环境的变化引起的，例如，营养胁迫或化学干扰。一旦表达，sRNAs通过碱基配对部分互补的mrna和改变翻译和/或RNA稳定性来调节蛋白质合成。sRNAs的基因调控被认为对细菌的应激反应至关重要。矛盾的是，很少有srna介导的基因调控的破坏导致细菌生长或存活中可识别的表型的例子。事实上，我们对sRNA功能的大部分知识来自于对少数sRNA的深入研究，而对大多数sRNA的功能一无所知。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。我们开发了一套测量高密度菌落阵列细菌生长速率的仪器和软件。我们还创造了一个成像设备，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。这些工具使我们在理解基因功能的系统方法中取得了独特的成功，而我们通常使用化学或遗传扰动。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。目前是细菌基因组的暗物质，我们的目标是描述大肠杆菌中sRNAs的全基因组功能网络。短期目标包括：细菌细胞应激中sRNAs的功能网络探讨检验sRNA功能网络提出的假设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，但所提出的方法将使我们能够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。这种系统方法将为传统生化和分子遗传学方法的详细研究提供新的假设。总之，我们将在理解细菌sRNAs对细胞应激的重要性方面解决一个主要的知识缺口。