MOSES - MicroOrganism Systems Biology: Energy and Saccharomyces cerevisiae: Coordination plus WPs 1 and 7 and contributions to 5 and 6

为了补充现有的自上而下和自下而上的SB策略，这里开发了一种多米诺骨牌、面向问题的SB方法，它遵循与选定的高度连接的分子属性相关的调节路线。所选属性为ATP(‘能源’)。这种方法是在最合适的、定义明确的、工业上最相关的有机体--面包酵母中开发的。摩西计划连接SYSMO国家的酵母系统生物学核，并与酵母系统生物学网络和肝脏系统联系在一起。它将向新的团体开放。酵母帮助我们生产面包、葡萄酒和啤酒。它也是生长最快的生物体之一：当提供过量的食物时，它会尽快利用这些食物。在这种“盛宴”的情况下，生物体对能量的利用效率非常低。在“饥荒”的情况下，酵母改变了策略。它降低了它的生长和生产酒精的速度，试图只生产二氧化碳(温室气体)。然后，它恢复增长，但效率更高，速度也更慢。所有这一切都涉及同时对许多过程进行微妙的监管。以前人们认为，这种类型的调节是通过处于‘开’状态或‘关’状态的单个‘关键’分子来实现的。最近，有一点变得很清楚，在活的有机体中，调节往往涉及许多分子的网络。这使得生物调节变得更加难以理解，这可能是为什么科学仍然很难找到有效的治疗方法来治疗困扰我们的复杂疾病，如癌症、糖尿病和关节炎。一种新类型的科学正在发展中，它专注于生物有机体的这种网络方面。它被称为“系统生物学”。到目前为止，大多数系统生物学要么是通过同时研究所有许多活着的有机体分子开始的，要么是通过只研究其中很少的几个分子开始的。前一种方法往往非常复杂，导致的困惑多于理解。后者可能会导致理解，这可能与整个活着的有机体无关。在这里，我们建议发展一种新型的系统生物学，称为多米诺骨牌系统生物学。它首先评估网络中最强的调控途径和分子，然后首先对它们进行研究。然后，它有一个机制，可以移动到下一个重要的调节路线和分子等。细胞的能量状态可以从细胞内ATP分子的浓度读取。这种三磷酸腺苷分子已知为许多重要的细胞内过程提供所需的能量。我们建议从涉及三磷酸腺苷的调控途径开始，为酵母发展多米诺骨牌系统生物学。该项目是由五个欧洲国家中最合适的团体合作完成的。这可能会导致理解如何使酵母更有效地为我们做事情。多米诺骨牌系统生物学的开发应该是一个无价的工具，也是分析疾病细胞和发现更好的药物靶点。

To complement existing top-down and bottom-up SB strategies, here a domino, problem oriented SB approach is developed, which follows the lines of regulation, pertinent to a selected highly connected molecule property. The selected property is ATP ('energy'). The approach is developed in the most suitable, well-defined, industrially most relevant organism, baker's yeast. The MOSES program connects yeast Systems Biology nuclei in SYSMO countries and is associated with the Yeast Systems Biology Network and HepatoSys. It will be open to new groups. Yeast helps us produce bread, wine and beer. It is also one of the fastest growing organisms: When provided with an excess of food it utilizes this as quickly as it can. Under such conditions of 'feast', the organism uses the energy very inefficiently. Under conditions of 'famine' yeast changes its strategy. It reduces the rate at which it grows and produces alcohol, tries to switch to producing carbon dioxide (the greenhouse gas) only. It then resumes growth but much more efficiently and more slowly. All of this involves subtle regulation of many processes at the same time. It was previously thought that regulation of this type is achieved by single 'key' molecules that would either be in an 'on' state or in an 'off' state. Recently, it has become clear that in living organisms, regulation tends to involve networks of many molecules. This makes biological regulation much more difficult to understand and may be one reason why the sciences still have a hard time to find effective treatments for the complex diseases that plague us, such as cancer, diabetes and arthritis. A new type of science is being developed that focuses on this network aspect of living organisms. It is called 'Systems Biology'. Until now most Systems Biology has either begun by looking at all of the many, many molecules of living organisms at the same time, or by looking at just a very few of them. The former approach tends to be so complex that it leads to confusion more than understanding. The latter may lead to understanding that may not be relevant to the living organism as a whole. Here we propose to develop a new type of Systems Biology, called domino systems biology. It begins by assessing what are the strongest regulatory routes and molecules in the network and then studies these first. It then has a mechanism to move to the next important regulatory routes and molecules, etc. The energy state of the cell may be read from the intracellular concentration of the molecule ATP. This molecules ATP is known to provide many important intracellular processes with the energy they require. We here propose to develop domino systems biology for yeast starting with the regulatory routes that involve ATP. The project is a collaboration between the most appropriate groups of five European countries. It is likely to result in understanding of how yeast can be made to do the things it does for us more efficiently. The domino systems biology developed should be an invaluable tool also for the analysis of diseased cells and the discovery of better drug targets.