A Complexity Science Approach to Plant Tissue Regeneration

无论从基础科学的角度还是从应用的角度来看，多细胞生物体中的组织再生都是一个非常有趣的话题。为了阐明组织再生机制的基本本质，这个项目打算通过实验测试一个关于再生过程中细胞分裂组织方式的相当技术性但有趣的假说。所研究的实验案例是植物的根，当它被机械切除时，它的尖端完全再生，随后采用了一种结合实时成像和高级统计分析的多学科方法。从实验的角度来看，主要的挑战是开发一种显微镜，可以非常频繁地观察再生根的内部组织，当然不会杀死根。这个想法是为了能够收集关于组织重新生长和重组期间细胞分裂发生的时间和地点的数据，这可以通过一种检测样本中荧光蛋白的非侵入性技术来实现。诀窍是从基因上设计一种仅在细胞分裂时表达的荧光蛋白，这一点已经完成。该项目的初始部分致力于优化显微镜--从现有的原型开始--专门重新设计，以便在许多天内以细胞分辨率对再生的根进行成像。然后，该仪器将系统地收集延时序列，以更详细地捕捉根尖的再生。该项目的更高级部分旨在对这些数据进行统计分析，以检验这样一种假设，即指导根再生的细胞分裂动力学与物理和生物学中发现的广泛类别的复杂现象具有共同特征，如沙堆、地震、飞鸟或神经网络。这类系统有时被称为自组织临界(SOC)系统，其特点是：(I)全局模式简单地从系统所有元素之间的相互作用中产生，并且不需要中心导向器(自组织)，以及(Ii)系统表现出向特殊(临界)状态的自发收敛。在临界状态下，系统被认为是无标度的，这意味着在潜在的动力学中没有典型的长度或持续时间。此外，在临界状态下，描述系统动力学的一些统计分布具有普遍的形状(幂分布)。这有点技术性，但事实证明，这些统计分布可以通过本项目中使用的显微镜收集的数据来测量，因此可以测试再生根的行为是否像SOC系统一样。然后，我们将能够通过开发一个数学模型来更详细地测试细胞相互作用和全球组织行为之间的因果联系，该模型旨在给出系统所有关键特征的简化表示。这将基于应用数学家在复杂性科学领域获得的先前经验，其中对SOC和类似现象进行了非常详细的研究。最后，可以理解的是，我们对严重伤害后根如何再生尖端的理解的任何重大改进，都可能提高具有经济价值的植物在恶劣条件下的生长和抗性。此外，对导致组织修复和再生的自然机制的任何新见解都是生物医学和生物技术社区的主要兴趣。

Tissue regeneration in multi-cellular organisms is a topic of great interest both from a basic scientific point of view and from an applied one. In the attempt to shed new light on the fundamental nature of the mechanisms underlying tissue regeneration, this project intends to test experimentally a quite technical but intriguing hypothesis on the way cellular divisions are organized during regeneration.The experimental case studied is that of a plant's root that completely regenerates its tip when this is excised by mechanical means, and a multi-disciplinary approach combining live imaging and advanced statistical analysis is followed.From the experimental point of view, the main challenge is to develop a type of microscope that allows very frequent observations of the internal organisation of a regenerating root, without of course killing the root. The idea is to be able to collect data about when and where cell divisions occur during the tissue re-growth and reorganization, and this can be achieved through a non-invasive technique that detects fluorescent proteins in the sample. The trick is to genetically engineer a fluorescent protein that is expressed in a cell only at the moment of its division, and this has been done, already.The initial part of this project is dedicated to the optimisation of a microscope - starting from existing prototypes - specifically redesigned to image for many days a regenerating root, quite often and at cellular resolution. Time-lapse sequences will be then systematically collected with this instrument, to capture in great details the regeneration of the root tip.The more advanced part of the project is aimed at the statistical analysis of such data, to test the hypothesis that the dynamics of cellular divisions guiding root regeneration shares common features with a wide class of complex phenomena found in physics and biology, as different from each other as sand piles, earthquakes, flying birds or neural networks. This class is sometimes called Self-Organizing Critical (SOC) systems, and is characterized by the ideas that (i) global patterns emerge simply from interactions among all the system's elements and without the need of a central director (self-organization) and that (ii) the system exhibits a spontaneous convergence towards a special (critical) state. At the critical state the system is said to be scale-free, which means that there is no typical length or duration in the underlying dynamics. Moreover, at the critical state some statistical distributions that describe the system's dynamics take a universal shape (power law distributions). It is a bit technical, but it turns out that these statistical distributions can be measured from the data collected with the microscope used in this project, and therefore it becomes possible to test whether a regenerating root behaves like a SOC system or not. We will then be able to test more in details the causal link between cellular interactions and global tissue behavior by developing a mathematical model designed to give a simplified representation of all the key characteristics of the system. This will be based on previous experience gained by applied mathematicians in the field of complexity science, where SOC and similar phenomena are studied in great details.Finally, it is understood that any major improvement of our understanding on how a root can regenerate its tip after a major injury opens the possibility to enhance growth and resistance of plants of economic interests in harsh conditions. Moreover, any new insight in natural mechanisms leading to tissue repair and regeneration is of major interest for the biomedical and biotech community.