SynBio3D: Establishing the engineering fundamentals of three-dimensional synthetic biology

合成生物学将合理的工程原理应用于新型生物分子装置的设计和制造。这使得我们可以使用合成的遗传‘电路’来编程微生物，使其表现为活的加工单位。一个基本目标是在生命系统中获得有用的(人类定义的)行为。这种方法建立在数学建模的预测能力和对分子生物学的当前理解的基础上，以设计最终将对社会具有重大价值的生物。这些程序化微生物的应用包括生物技术过程，从生产生物燃料到制药、生物修复策略、农业和生物诊断。然而，目前有一个问题可能会破坏合成生物学未来的成功：完全无视空间维度。这与许多其他工程学科形成了鲜明对比，在这些学科中，设计像飞机这样的复杂系统必须为其电路部件指定准确的物理位置。到目前为止，除了细胞内外的概念外，合成生物学还没有空间分辨率。在细胞内引入了新的生物遗传电路，但没有注意到它们的去向。这样做的一个主要问题是，细胞被抽象为一个黑匣子，因此只从输入/输出的角度来看待，而不考虑它的内部工作。当生物体被使用/测试时，这种信息的排除会造成重要的问题。通常需要重新设计和重新测试具有不同遗传部分的电路，以微调其功能。如果在设计阶段就考虑了空间维度，那么这种“重构”过程不仅费时费钱，而且在许多情况下也是不必要的。例如，我们的初步研究最近表明，给定遗传电路组件之间的物理距离可以显著改变其功能。因此，对几何效应的认识将有助于设计健壮和可预测的电路。每个基因序列和每个蛋白质可能需要在细胞的空间框架中有一个特定的物理地址才能实现最佳性能，这是一个迫切需要进一步关注的问题，以使合成生物学能够发挥其潜力。在这第一笔赠款中，我们将测量空间在合成结构中的影响，并利用它来建立我们称为“三维合成生物学”的新概念的基本原理。SynBio3D将通过增加空间信息来升级合成生物学的生命周期，这是迄今为止任何其他研究小组都没有达到的目标。该项目将解决取得成功的两大障碍。首先，数学模型是遗传电路发展的核心，绝大多数都是以时间为唯一参考。这将我们表示生物分子相互作用的方式限制在基于时间的动力学上，这假设了一个不切实际的零维场景。作为对第一个问题的回应，我们将开发新的计算方法，使我们能够使用空间约束(如距离和分子拥挤)来模拟遗传电路。第二个问题涉及基因位置和单分子位移的体内直接可视化。我们将使用超分辨率显微镜对定制的遗传电路进行三维、实时测量。综合起来，最终的信息将第一次正式地将遗传电路在时间上的动态与它在空间上的几何特征联系起来。这将使空间工程基础形式化。这种合成生物学的三维方法将在将分子网络转变为可编程系统方面发挥带头作用；这一目标被认为是传统的基于时间的方法难以实现的。此外，它还将影响从生物物理学到计算机科学等明显遥远领域的研究领域。

Synthetic biology applies rational engineering principles to the design and build of novel biomolecular devices. This allows us to use synthetic genetic 'circuits' to program microbes to behave as living processing units. A fundamental aim is to obtain useful (human-defined) behaviour in living systems. This approach builds on the predictive power of mathematical modelling and the current understanding of molecular biology to engineer organisms that will ultimately be of major value to society. Applications of these programmed microbes include biotechnological processes, from the production of biofuels to pharmaceuticals, bioremediation strategies, agriculture and bio-diagnostics. However, there is currently one issue which threatens to undermine the success of synthetic biology going forwards: the complete disregard for spatial dimensions. This is in contrast to many other engineering disciplines, where the design of a complex system such an airplane must specify accurate physical locations for its circuit's components. To date, synthetic biology has no spatial resolution apart from the notions of inside and outside the cell. Novel biological genetic circuits are introduced inside cells with no notable attention to their whereabouts.A major problem with this is that a cell is abstracted as a black box, thus viewed in terms of inputs/outputs alone without considering its internal workings. The exclusion of such information causes important problems when the organisms come to be used/tested. It is commonly required to re-engineer and retest the circuit with different genetic parts to fine-tune its function. That "refactoring" process is not only time consuming and costly but also unnecessary in many cases - if spatial dimensions were considered at the design stage. For example, our initial investigations have recently shown that the physical distance between the components of a given genetic circuit can change its functioning considerably. Therefore, the awareness of geometrical effects will assist the design of robust and predictable circuits. Each gene sequence and each protein may need a specific physical address in the spatial frame of a cell for optimal performance, a question that urgently needs further attention to enable synthetic biology to fulfil its potential. In this first grant, we will measure the impact of space in synthetic constructs and use it to establish the fundamentals of a new concept that we refer to as 'three-dimensional synthetic biology'.SynBio3D will upgrade the synthetic biology lifecycle by adding spatial information, a goal unattained by any other research group to date. The project will address two major barriers to achieve success. Firstly, mathematical models, which are at the heart of genetic circuit development, are overwhelmingly based on time as the only reference. This restricts the way we represent biomolecular interactions to time-based kinetics, which assume an unrealistic zero-dimensional scenario. In response to this first problem we will develop novel computational methods to allow us to simulate genetic circuits using spatial constraints such as distances and molecular crowding. The second problem concerns the direct visualization in vivo of gene locations and single-molecule displacements. We will use super-resolution microscopy to obtain three-dimensional, real-time measurements of bespoke genetic circuits. Together, the resulting information will formally correlate, for the first time, a genetic circuit's dynamics in time with its geometrical features in space. This will allow to formalize spatial engineering fundamentals.This three-dimensional approach to synthetic biology will lead the way in turning molecular networks into programmable systems; a goal revealed to be elusive with traditional time-based approaches. Furthermore, it will impact research lines in apparently distant fields ranging from biophysics to computer science.