Multiple light input signals to the gene network of the circadian clock

植物的生长支持地球上的生命，对我们的经济和生存至关重要。植物生长不仅对农民和林业工作者以及他们所供应的消费者很重要，而且现在也被认为在全球碳循环中发挥着关键作用，并影响着我们星球的气候。最近的进展已经确定了叶片中光合作用机制的组成和运作，以及控制植物活动时间的许多基因，以及在实验室中监测基因活动的工具。通过结合这些进展，我们已经表明，植物生物活动（昼夜节律）与外部昼夜周期的同步化赋予了生长和生存优势。这一结果提供了第一个证据的优势，每日植物生长所产生的节奏的行为，现有的植物生长模型不能解释这种行为，因此是不够的。植物节律与昼夜周期同步，所涉及的原理与人体生物钟的同步非常相似，使旅行者能够克服时差，而轮班工人很难实现。我们现在的目标是通过一系列实验和相关的建模研究，确定这种同步在时钟基因水平上是如何工作的。在我的实验室和其他人之前的研究已经确定了相关的时钟基因和相关的光感受器通路。两者都很复杂。我的实验室最近提出了植物时钟的第一个数学模型，它允许在计算机中模拟许多相互作用的部分。这个模型引导我们进行了新的实验，确定了时钟网络的另一部分。这是植物科学的第一次，在任何生物体中仍然是一个罕见的成就，尽管人们对“系统生物学”方法产生了浓厚的兴趣，这种方法通常旨在做出这种类型的预测。从那以后，我们开发了一种扩展模型，它甚至更现实（就我们所知，它是任何地方都能得到的最好的模型），尽管它仍然简化或遗漏了我们目前的许多分子知识。有趣的是，新模型非常类似于动物大脑中的时钟模型，尽管这些时钟涉及连接的神经元，而我们的模型发生在单个植物细胞中。我们现在希望了解植物和动物是如何使它们的时钟与昼夜周期同步的，尽管它们的时钟机制不同。这项提议的主要部分是基于我们的模型，比以前更仔细地测试光对时钟基因的影响，并使用这些数据来完善模型。我们建议使用一种新的实验方法来获得比以前更精细的数据。这种方法已被证明是有效的，但尚未经过广泛的测试，尽管如此，它是在一个我们非常熟悉的实验领域，它承诺的主要好处，将是有用的许多其他植物研究人员，它将使我们领先于我们的竞争对手。我们还建议扩展过去已证明可靠的实验类型。在建模方面，我们还将使用新技术，部分是数学，部分是利用爱丁堡物理系提供的非常快的计算机。如果这项工作取得成功，它将为其他实验室提供一个范例，以了解其他具有多个输入信号的复杂基因网络/这些是控制癌症，糖尿病和其他复杂疾病的网络类型。

The growth of plants supports life on Earth and is vital to our economy and survival. Plant growth is important not just to farmers and foresters, and the consumers that they supply, but is also now understood to play a critical role in the global carbon cycle, and to affect the climate of our planet. Recent advances have identified the components and workings of the photosynthetic machinery in leaves and many of the genes that control the timing of plant activity, together with tools for monitoring gene activity in the laboratory. By combining these advances, we have shown that the synchronization of biological activity in plants (circadian rhythms) with external day-night cycles confers a growth and survival advantage. This result provides the first evidence of an advantage to daily plant growth arising from rhythmic behaviour; existing models of plant growth cannot account for this behaviour and are thus inadequate. Plant rhythms are synchronised to the day/night cycle, and the principles involved are very similar to the synchronisation of the human body clock that enables travellers to overcome jet lag, and that can be difficult for shift workers to achieve. Our goal now is to determine how this synchronisation works at the level of the clock genes, through a series of experiments and linked modelling studies. Previous studies in my lab and others have identified the relevant clock genes and the photoreceptor pathways involved. Both are complex. My lab has recently proposed the first mathematical models of the plant clock, which allow the many interacting parts to be simulated in a computer. The model led us to new experiments, identifying an additional part of the clock network. This was a first for plant science and is still a rare achievement in any organism, despite a wave of interest in the 'systems biology' approach that often aims to make this type of prediction. We have since developed an extended model that is even more realistic (so far as we know it's the best available anywhere) though it still simplifies or leaves out a lot of our current molecular knowledge. Fascinatingly, the new model very much resembles current models of the clocks in animal brains, despite the fact that those clocks involve connected neurones whereas our model occurs within a single plant cell. We now wish to understand how plants and animals both synchronise their clocks to the day/night cycle, despite the differences in the clock mechanisms. A major part of this proposal is based on our models, testing the effect of light on the clock genes much more carefully than before, and using these data to refine the models. We propose to use a new experimental method to get much finer data than before. This method has been proven to work but has not been extensively tested, nevertheless it is in an area of experiments that we know very well, it promises major benefits that will be useful for many other plant researchers and it will keep us ahead of our competitors. We also propose to extend the types of experiment that have proved reliable in the past. On the modelling side, we will also use new technology, part of it mathematical, part of it exploiting a very fast computer that is available to us through the Physics department in Edinburgh. If this work is successful, it will provide an example for other labs to follow, to understand other complex gene networks with multiple input signals / these are the types of network that control cancer, diabetes and other complex diseases.