NsrR regulation of the small noncoding RNA RybB in Escherichia coli

描述(由申请人提供)：系统生物学知识对于我们理解医学和合成生物学应用的细胞和分子基础至关重要。它还为各种生物系统的代谢组学研究提供了一个框架。系统生物学知识将通过确认细胞生理学的计算模型或发现以前未描述的新途径的研究来推进。使用E.ColiK12作为细胞生理学研究的模型系统是最理想的，因为它的生物学简单性和遗传易感性。细菌细胞生理学研究中缺少的一个关键因素是定义两种不同应激反应之间的串扰的精确机制。应激反应是对环境变化的快速生理适应。细菌小分子调控RNA是具有转录后调控功能的非编码RNA分子。小RNA经常起到遗传开关的作用，通过对中央调节因子或途径中涉及的酶的转录后调节，以主要方式影响特定的代谢途径。出于这个原因，对小RNA的研究特别适合于旨在定义生理回路和串扰的研究。在大肠杆菌中，小分子调控RNA RbB受胞质外功能(ECF)Sigma因子RpoE的调控。RpoE是大肠杆菌包膜应激反应的中心调节因子，类似于真核细胞内质网中未折叠的蛋白质反应。NsrR通过诱导NO解毒酶HmpA的表达来响应一氧化氮(NO)的暴露。因此，NsrR是大肠杆菌亚硝化应激反应的中心调节因子。我们有初步证据表明，一氧化氮感应转录调节因子NsrR对RbB的表达也有调节作用。这一观察结果的含义是，在大肠杆菌中，亚硝化应激和包膜应激反应之间可能存在生理串扰；并且，可以通过表征NsrR在RbB上所起的作用来研究这一现象。我们的主要假设是NsrR是RbB表达的直接调节因子。我们提出了两个模型，作为我们的假设的机制，即NsrR直接调节RbB。我们的第一个模型是，NsrR通过与DNA，特别是rybB基因的启动子相互作用，对RbB发挥调节作用。我们的第二个模型是，NsrR通过与RpoE蛋白直接相互作用，发挥其对RbB的调节作用，作为一个抗Sigma因子，阻止它调节IS的转录靶标(包括rybB)。为了验证我们的假设，我们将首先确定NsrR对RbB表达的调控水平(特定目标#1)。然后，我们将确定NsrR对RbB表达的影响所必需的生化相互作用(特定目标2)。最后，我们将确定外源性NO暴露对RbB表达的影响(特定目标3)。综上所述，这些实验将表征NsrR对RbB的调节作用，并有助于了解细菌细胞中的生理串扰。这些研究产生的模型将有助于系统生物学应用的精炼生理学模型。

DESCRIPTION (provided by applicant): Systems biology knowledge is crucial for our understanding of the cellular and molecular basis of medicine and synthetic biology applications. It also provides a framework for metabolomic studies of various biological systems. Systems biology knowledge will advance through investigations that confirm computational models of cellular physiology or discover new pathways not previously described. Using E. coli K12 as a model system for cellular physiology studies is optimal due to its biological simplicity and genetic tractability. One crucial element missing from bacterial cell physiology studies is precise mechanisms defining cross-talk between two different stress responses. Stress responses are rapid physiological adaptations to environmental changes. Bacterial small regulatory RNAs are noncoding RNA molecules with a post- transcriptional regulatory function. Small RNAs frequently act as genetic switches, by affecting specific metabolic pathways in major ways, via post-transcriptional regulation of a central regulator or enzyme involved in a pathway. For this reason, the study of small RNAs is uniquely suited for studies aimed at defining physiological circuits and cross-talk. The small regulatory RNA RybB is regulated by the Extracytoplasmic function (ECF) sigma factor, RpoE, in E. coli. RpoE is a central regulator of the envelope stress response in E. coli and is analogous to the unfolded protein response in eukaryotic endoplasmic reticulum. NsrR responds to nitric oxide (NO) exposure by inducing the expression of HmpA, a NO-detoxification enzyme. Hence, NsrR is a central mediator of the nitrosative stress response in E. coli. We have preliminary evidence to suggest that a nitric oxide sensing transcriptional regulator, NsrR, has a regulatory effect on RybB expression as well. The implications for this observation is that there may be physiological cross-talk between the nitrosative stress and envelope stress responses in E. coli; and, it can be studied by characterizing the role NsrR plays on RybB. Our main hypothesis is that NsrR is a direct regulator of RybB expression. We have two models we propose as a mechanism for our hypothesis that NsrR directly regulates RybB. Our first model is that NsrR exerts its regulatory effect on RybB via an interaction with DNA, specifically the promoter of the rybB gene. Our second model is that NsrR exerts its regulatory effect on RybB via a direct interaction with the RpoE protein, acting as an anti-sigma factor and preventing it from regulating is transcriptional targets (including rybB). To test our hypothesis, we will first determine the regulatory level at which NsrR acts on RybB expression (Specific Aim #1). Then, we will identify biochemical interactions necessary for the NsrR effect on RybB expression (Specific Aim #2). Finally, we will determine the role that exogenous NO exposure plays on the expression of RybB (Specific Aim #3). Taken together, these experiments will characterize NsrR's regulatory effect on RybB and contribute to knowledge of physiological cross-talk in bacterial cells. The models resulting from these studies will contribute to refined physiological models for systems biology applications.