Developing methods for inferring regulatory mechanisms from intact systems: a neisseria case study

生物系统的行为是通过“调节器”和其他控制细胞内基因表达的细胞内相互作用网络来控制和协调的。在细菌中，信使RNA的产生和蛋白质的产生密切相关，细胞行为的大部分控制方式都是在转录水平上完成的。使用微阵列可以同时测量细胞中所有基因的转录，这可以相对直接地读出细胞行为的许多方面受到控制的方式。这种方法给出了转录基因的快照，当从许多快照中观察到的结果结合在一起时，细胞控制其功能的方式可以逐渐拼凑在一起，就像电影的意义可以通过多帧的组合拼凑在一起一样。找到方法利用这些信息来建立可测试的模型，这些模型可以用来剖析控制生物系统的这些中央过程，这是系统生物学和理解生物系统如何在基础和“整个细胞”水平上工作的关键组成部分。如果控制细胞行为的因果关系和关键相互作用可以根据这种类型的“观察”信息来确定，那么这意味着这些系统可以在不需要单独处理每个基因的情况下被解决(通常不可能、不切实际或负担不起)。细胞生存需要许多基因。其他基因不是生命所必需的，但当正常成分被移除时，所产生的细胞在几种方式上不能正常运作，而且很难区分哪些影响是直接或间接的基因/基因产物的影响。为了了解细胞系统是如何工作的，我们建议我们需要一些方法来分析和使用来自‘完整/未破坏’生物系统的信息。在这项提议中，我们将利用最大的“成绩单”数据集合之一，并用专门设计的信息来补充，以帮助对细胞控制的方式进行建模。这个模型的有效性将得到测试，模型将通过制造突变和测试它们在多大程度上根据模型预测来处理关键基因来增强和改进模型。通过这种方式，我们将开发一种普遍适用的方法，该方法可以普遍应用，而不需要在未来产生昂贵、耗时和潜在误导的突变。

The behaviour of biological systems is controlled and coordinated through a network of 'regulators' and other intracellular interactions that control the expression of the genes within the cell. In bacteria the production of the messenger RNA and the production of proteins are closely linked, and much of the way in which a cell's behaviour is controlled is done at the level of transcription. Transcription can be measured for all of the genes in a cell simultaneously, using microarrays, and this gives a relatively direct read-out of the way in which many aspects of the cell's behaviour are being controlled. This method gives a 'snap shot' of the transcribed genes, and when the observations from many snap shots are combined, the way in which the cell controls its functions can be progressively pieced together, much as the meaning of a movie can be pieced together from the combination of multiple 'frames'. Finding ways to use this information to make testable models that can be used to dissect these central processes that control biological systems is a critical component of systems biology and understanding how biological systems work at a fundamental and 'whole cell' level. If causal relationship and key interactions controlling a cell's behaviour can be determined based upon this type of 'observational' information, then this means that these systems can be addressed without the (frequently impossible, impractical, or unaffordable) need to address each gene individually. Many genes are required for a cell to survive. Other genes are not required for life, but the resulting cell does not function 'normally' in several ways when a normal component has been removed / and it is very difficult to tell which effects are directly or indirectly due to the effects of a gene / gene product. To understand how cellular systems work, we propose that we need ways to analyze and use the information from 'intact / unbroken' biological systems. In this proposal we will make use of one of the largest collections of 'transcript' data, and augment this with information specifically designed to assist modeling the ways in which the cell is controlled. The effectiveness of this modeling will be tested, and the models will be augmented and refined by addressing the key genes by making mutants and testing to what extent they behave according to the model predictions. In this way, we will develop a generally applicable approach that can be applied generally, without the need for expensive, time consuming, and potentially misleading mutant generation in the future.