Stochastic dynamical modelling for prokaryotic gene regulatory networks

原核基因调控网络的随机动力学模型

• 批准号: BB/F003765/1
• 负责人: Dov Stekel
• 金额: $ 3.22万
• 依托单位: University of Birmingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2007
• 资助国家: 英国
• 起止时间: 2007 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FF003765%2F1
• 关键词: Stochastic; dynamical; modelling; prokaryotic; gene

The DNA inside every living cell contains thousands of genes, encoding protein molecules, which allow the cell to carry out its essential functions. But not all genes can produce proteins at the same time: the cell must be able to turn some genes on, and others off, in response to different environmental conditions. Turning genes on and off is a haphazard process, because it relies on reactions between chemicals inside the cell that are present in very small numbers. For example, for a gene to be turned on, a protein assembly called RNA polymerase must bind to the DNA sequence for that gene. However, the number of free RNA polymerases in a typical bacterium is only around 30, while the number of copies of the DNA sequence is typically 1-10. As a result of these small numbers, the essential control mechanisms that turn genes on and off are 'noisy' - the level of expression of a typical gene varies very much from cell to cell. This effect is called 'stochasticity' and the objective of the StoMP research network is to understand how stochasticity in the regulation of gene expression affects how bacteria function. Around half the total living mass on our planet is thought to consist of bacteria, making them the most numerous living things. They have legendary ability to survive in hostile and rapidly changing environments, including hot sulphur springs, salt lakes and the human stomach. Bacteria impact on our lives for both ill and good; we couldn't digest our food without them, yet undesired bacterial infestations cause expensive 'bio-fouling' problems for industry by growing in pipes, antibiotic resistance contributes an increasing numbers of deaths in hospitals and we waste countless minutes removing biofilms from our teeth every morning. This remarkable ability of bacteria to deal with stressful conditions is closely connected with the stochasticity of their gene expression. For example, stochastic gene expression is thought to result in a few cells in every population being resistant to antibiotics: these few cells can make the difference between population extermination and survival. The StoMP research network will address three areas where stochastic gene regulation is important: how bacteria survive starvation or chemical attack, how bacteria co-ordinate their behaviour to maximise their chances of survival, and how genes encoding resistance or virulence spread through bacterial populations. We will apply both traditional microbiology and mathematical modelling of stochastic dynamics to these problems: in fact a key aim of the network is to bring together, in a series of workshops, mathematical modellers with expertise in computer simulation and mathematical analysis and microbiologists with experience in the lab. The UK has a number of experts in the field of stochastic modelling with specialities ranging from high-powered mathematical analysis, to modelling the diffusion of molecules in space, to developing methods to increase the computational efficiency of calculations. Our aim is to foster the development of a UK-wide stochastic dynamical modelling community, where ideas and software can be shared and new methods developed. Since this area has until now been largely dominated by the US, this would be a very valuable contribution to UK research. Finally our network is to reach out to other researchers - to attract biologists who have not used modelling before, and mathematicians and physical scientists who have not applied their expertise to this kind of biological problem. We will do this by hosting a 'tutorial-style' workshop, by constructing and maintaining a website and mailing list, and by welcoming new members at any time.

每个活细胞内的DNA都包含数千个基因，编码蛋白质分子，使细胞能够执行其基本功能。但并非所有的基因都能同时产生蛋白质：细胞必须能够根据不同的环境条件打开一些基因，关闭另一些基因。基因的开启和关闭是一个偶然的过程，因为它依赖于细胞内化学物质之间的反应，这些化学物质的数量非常少。例如，要打开一个基因，一种称为RNA聚合酶的蛋白质组装体必须与该基因的DNA序列结合。然而，典型细菌中游离RNA聚合酶的数量仅为30个左右，而DNA序列的拷贝数通常为1-10个。由于这些小数目，开启和关闭基因的基本控制机制是“嘈杂的”-典型基因的表达水平在细胞与细胞之间差异很大。这种效应被称为“随机性”，StoMP研究网络的目标是了解基因表达调控的随机性如何影响细菌的功能。我们星球上大约一半的生物被认为是由细菌组成的，使它们成为数量最多的生物。他们有传奇般的能力在恶劣和快速变化的环境中生存，包括热硫磺泉，盐湖和人类的胃。细菌对我们生活的影响有好有坏;没有它们，我们就无法消化食物，然而不受欢迎的细菌感染通过在管道中生长而给工业带来昂贵的“生物污染”问题，抗生素耐药性导致医院死亡人数增加，我们每天早上浪费无数分钟从牙齿上去除生物膜。细菌应对压力条件的这种非凡能力与其基因表达的随机性密切相关。例如，随机基因表达被认为会导致每个种群中的少数细胞对抗生素产生耐药性：这些少数细胞可以在种群灭绝和存活之间产生差异。StoMP研究网络将解决随机基因调控重要的三个领域：细菌如何在饥饿或化学攻击中生存，细菌如何协调其行为以最大限度地提高生存机会，以及编码抗性或毒力的基因如何通过细菌种群传播。我们将应用传统的微生物学和随机动力学的数学建模来解决这些问题：事实上，该网络的一个关键目标是在一系列研讨会中，将具有计算机模拟和数学分析专业知识的数学建模人员以及具有实验室经验的微生物学家聚集在一起。联合王国在随机建模领域有许多专家，他们的专业范围从高性能数学分析到模拟分子在空间中的扩散，再到开发提高计算效率的方法。我们的目标是促进英国范围内的随机动态建模社区的发展，在那里可以分享想法和软件，并开发新方法。由于这一领域到目前为止主要由美国主导，这将是对英国研究的非常有价值的贡献。最后，我们的网络是接触其他研究人员-吸引以前没有使用过建模的生物学家，以及没有将他们的专业知识应用于这类生物问题的数学家和物理科学家。我们将通过举办一个“辅导式”研讨会，通过建设和维护一个网站和邮件列表，并欢迎新成员在任何时候。