Mathematical Modeling - Biochemical Networks in Yeast

数学建模 - 酵母中的生化网络

• 批准号: 7060748
• 负责人: REINHARD LAUBENBACHER
• 金额: $ 29.51万
• 依托单位: VIRGINIA POLYTECHNIC INST AND ST UNIV
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-05-01 至 2008-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7060748
• 关键词: SDS polyacrylamide gel electrophoresis; Saccharomyces cerevisiae; aerobiosis; biochemistry; computer program /software; fungal genetics; gene deletion mutation; gene expression; glutathione; mathematical model; matrix assisted laser desorption ionization; metabolomics; microarray technology; model design /development; oxidative stress; proteomics; time resolved data

DESCRIPTION (provided by applicant): The goal of this project is to develop mathematical tools to model biochemical networks from experimental data. These tools will then be applied to transcriptomics, proteomics, and metabolomics data collected from a network of ten genes of the model organism Saccharomyces cerevisiae that are involved in oxidative stress response. The proposed approach is to develop a two-stage modeling process. Viewing a biochemical network as a continuous dynamical system, described by a collection of ordinary differential equations, we first approximate the system by a discrete-time system, using numerical methods. Several tools are then used to analyze this discrete system. One of these tools is a further reduction, achieved by categorizing the state values of the variables into a finite set of states. The resulting framework allows the use of well-developed methods from computational algebra to study the whole space of possible models for the discrete-time system on a finite state set. To demonstrate and test the mathematical methodologies, experiments will be carded out with the baker's yeast Saccharomyces cerevisiae. Cell cultures of wild type yeast will be perturbed by addition of cumene hydroperoxide, and oxidative stress, and samples will be measured in a time course. The experiment will be repeated ten times, each time with a different gene deletion mutant. Mutants will be selected according to the hypotheses generated by the mathematical models. In addition to supporting the mathematical developments, the experiments are expected to reveal details about the regulation of glutathione metabolism and related antioxidant molecules (such as Lascorbic acid).

描述（由申请人提供）：该项目的目标是开发数学工具来根据实验数据对生化网络进行建模。 然后，这些工具将应用于从参与氧化应激反应的模型生物酿酒酵母的十个基因网络收集的转录组学、蛋白质组学和代谢组学数据。 所提出的方法是开发一个两阶段建模过程。将生化网络视为一个由常微分方程组描述的连续动力系统，我们首先使用数值方法通过离散时间系统来近似该系统。然后使用多种工具来分析这个离散系统。这些工具之一是进一步减少，通过将变量的状态值分类为一组有限的状态来实现。由此产生的框架允许使用计算代数中成熟的方法来研究有限状态集上离散时间系统的整个可能模型空间。 为了演示和测试数学方法，将使用面包酵母酿酒酵母进行实验。野生型酵母的细胞培养物将受到氢过氧化异丙苯的添加和氧化应激的干扰，并且将在一段时间内测量样品。该实验将重复十次，每次都使用不同的基因缺失突变体。将根据数学模型产生的假设来选择突变体。除了支持数学发展之外，这些实验预计还将揭示有关谷胱甘肽代谢和相关抗氧化剂分子（例如抗坏血酸）调节的细节。