Systems-analysis of the Nf-kappaB signalling networks that control levels of reactive oxygen species

控制活性氧水平的 Nf-kappaB 信号网络的系统分析

• 批准号: BB/I002510/1
• 负责人: Chris Bakal
• 金额: $ 41.07万
• 依托单位: Institute of Cancer Research
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2011
• 资助国家: 英国
• 起止时间: 2011 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FI002510%2F1
• 关键词: Systems; analysis; Nf; kappaB; signalling

Reactive Oxygen Species (ROS) are oxygen-containing free radicals that are a natural by-product of cellular metabolism. ROS levels also dramatically increase in response to cellular stresses such as heat or UV exposure, tissue wounding, or infection. ROS are highly damaging to cell structures and can result in genetic mutation. Importantly, ROS accumulation is thought to be the cause of ageing, and underlies health problems associated with ageing including impairment of memory and cognitive function. High levels of ROS are also thought to promote the onset of neurodegenerative diseases, diabetes, and cancer. Due to the toxic effects of ROS, cells have evolved a number of genes and biochemical mechanisms in order to prevent the build-up of ROS, and many of these genes are in fact activated as part of the normal stress response. Mutation of these genes can cause the stress response to breakdown, leading to ROS accumulation and subsequent acceleration of the ageing process, and/or the development of diverse pathologies. Through genetic screens, we have found that a gene called Nf-kappaB (or Nf-kB) has a very important role in controlling ROS levels. Nf-kB is a transcription factor that regulates ROS levels by controlling the levels of other genes. Our experiments reveal that loss of Nf-kB activity raises ROS levels, but we also found that excessive Nf-kB activity has the same effect. Therefore, Nf-kB activity must be finely-tuned in order to keep ROS levels low. Using novel genetic screening technology we have developed, we also discovered approximately 200 genes that work together with Nf-kB to control ROS. We predict these genes act as a complex network to modulate the concentration of cellular ROS. While our studies have identified these critical genes, it is currently unknown how the genes work to control ROS levels. Using a number of different technologies and methods, we aim to study the function of these genetic network towards the goal of developing therapeutics that could be used to maintain the proper balance of Nf-kB activity, and thus improve wellbeing during the ageing process. (1) By inhibiting the function of each of these individually we will study how the genes might act to control Nf-kB entry into the nucleus and thus activate transcription. We will also study how inhibition of these genes controls the activity of another important transcription factor called FOXO that we have found regulates metabolism in response to increases in ROS levels. (2) We plan to study how the genes we have discovered are involved in regulating and responding to endoplasmic reticulum (ER) stress and a process called autophagy. Both ER stress and autophagy have been previously linked to the regulation of cellular ROS levels. We will also study how these genes are involved in regulating the metabolic changes in cells that are caused by the exposure of cells to insulin as insulin has also been implicated in controlling ROS levels. (3) Although we identified 213 genes that work together with Nf-kB to regulate ROS levels, there remain many more to be discovered. We will continue to perform further genetic screening in order to determine all the genes that work together with Nf-kB to control the generation of ROS. Many of the genes could novel targets for therapeutics that will improve wellbeing and/or prevent disease. (4) We will develop and implement computational methods in order to map all the relationships that exist between the genes we have discovered. Thus we will generate a map of the Nf-kB gene network that control ROS levels. By developing this map we will be able to determine critical points or 'nodes' in the network that can be targeted by therapeutics to control ROS levels.

活性氧（ROS）是含氧自由基，是细胞代谢的天然副产物。ROS水平还响应于细胞应激如热或UV暴露、组织创伤或感染而显著增加。ROS对细胞结构具有高度破坏性，可导致基因突变。重要的是，ROS积累被认为是衰老的原因，并且是与衰老相关的健康问题的基础，包括记忆和认知功能的损害。高水平的ROS也被认为会促进神经退行性疾病、糖尿病和癌症的发病。由于ROS的毒性作用，细胞已经进化出许多基因和生化机制，以防止ROS的积聚，并且这些基因中的许多基因实际上作为正常应激反应的一部分被激活。这些基因的突变可导致应激反应崩溃，导致ROS积累和随后的衰老过程加速，和/或多种病理学的发展。通过基因筛选，我们发现一种名为Nf-kappaB（或Nf-kB）的基因在控制ROS水平方面具有非常重要的作用。Nf-kB是一种转录因子，通过控制其他基因的水平来调节ROS水平。我们的实验表明，Nf-kB活性的丧失会提高ROS水平，但我们也发现过量的Nf-kB活性也有同样的效果。因此，Nf-kB活性必须进行微调，以保持ROS水平较低。利用我们开发的新的遗传筛选技术，我们还发现了大约200个与Nf-kB一起控制ROS的基因。我们预测这些基因作为一个复杂的网络来调节细胞ROS的浓度。虽然我们的研究已经确定了这些关键基因，但目前尚不清楚这些基因如何控制ROS水平。使用许多不同的技术和方法，我们的目标是研究这些遗传网络的功能，以开发可用于维持Nf-kB活性的适当平衡的治疗方法，从而改善衰老过程中的健康状况。(1)通过单独抑制这些基因的功能，我们将研究这些基因如何控制Nf-kB进入细胞核，从而激活转录。我们还将研究这些基因的抑制如何控制另一个重要的转录因子FOXO的活性，我们发现FOXO调节代谢以响应ROS水平的增加。(2)我们计划研究我们发现的基因如何参与调节和响应内质网（ER）应激和一个称为自噬的过程。ER应激和自噬之前都与细胞活性氧水平的调节有关。我们还将研究这些基因如何参与调节细胞中由细胞暴露于胰岛素引起的代谢变化，因为胰岛素也参与控制ROS水平。(3)虽然我们鉴定了213个与Nf-kB一起调节ROS水平的基因，但仍有更多的基因有待发现。我们将继续进行进一步的基因筛选，以确定与Nf-kB一起控制ROS产生的所有基因。许多基因可能是改善健康和/或预防疾病的治疗方法的新靶点。(4)我们将开发和实施计算方法，以绘制我们发现的基因之间存在的所有关系。因此，我们将生成控制ROS水平的Nf-kB基因网络的图谱。通过开发这张地图，我们将能够确定网络中的关键点或“节点”，这些节点可以被治疗药物靶向以控制ROS水平。

项目成果

How cells explore shape space: a quantitative statistical perspective of cellular morphogenesis.

• DOI: 10.1002/bies.201400011
• 发表时间: 2014-12
• 期刊: BIOESSAYS
• 影响因子: 4
• 作者: Yin, Zheng;Sailem, Heba;Sero, Julia;Ardy, Rico;Wong, Stephen T. C.;Bakal, Chris
• 通讯作者: Bakal, Chris

Identification of clinically predictive metagenes that encode components of a network coupling cell shape to transcription by image-omics.

• DOI: 10.1101/gr.202028.115
• 发表时间: 2017-02
• 期刊: Genome research
• 影响因子: 7
• 作者: Sailem HZ;Bakal C
• 通讯作者: Bakal C

Signaling networks converge on TORC1-SREBP activity to promote endoplasmic reticulum homeostasis.

• DOI: 10.1371/journal.pone.0101164
• 发表时间: 2014
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Sanchez-Alvarez M;Finger F;Arias-Garcia Mdel M;Bousgouni V;Pascual-Vargas P;Bakal C
• 通讯作者: Bakal C

Cross-talk between Rho and Rac GTPases drives deterministic exploration of cellular shape space and morphological heterogeneity.

• DOI: 10.1098/rsob.130132
• 发表时间: 2014-01-22
• 期刊: Open biology
• 影响因子: 5.8
• 作者: Sailem H;Bousgouni V;Cooper S;Bakal C
• 通讯作者: Bakal C

Inferring signalling networks from images.

• DOI: 10.1111/jmi.12062
• 发表时间: 2013-10
• 期刊: Journal of microscopy
• 影响因子: 2
• 作者: Evans L;Sailem H;Vargas PP;Bakal C
• 通讯作者: Bakal C