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构建。这使我们能够使用合成的遗传“电路”来编程微生物，使其表现为活的处理单元。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目前对分子生物学的理解的基础上，以设计最终对社会具有重大价值的生物体。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的成功：完全无视空间维度。这与许多其他工程学科形成对比，在这些学科中，复杂系统（如飞机）的设计必须为其电路组件指定准确的物理位置。迄今为止，合成生物学除了细胞内外的概念外，还没有空间分辨率。新的生物遗传电路被引入细胞内部，而没有注意到它们的位置。这种方法的一个主要问题是，细胞被抽象为一个黑盒子，因此只从输入/输出的角度来看待，而不考虑其内部工作。排除这些信息会在使用/测试生物体时造成重要问题。通常需要用不同的遗传部分重新设计和重新测试电路，以微调其功能。如果在设计阶段就考虑空间维度的话，这种“重构”过程不仅耗时且成本高昂，而且在许多情况下也是不必要的。例如，我们最近的初步调查表明，给定遗传电路组件之间的物理距离可以大大改变其功能。因此，几何效应的意识将有助于设计鲁棒性和可预测的电路。每个基因序列和每个蛋白质都可能需要在细胞的空间框架中具有特定的物理地址以实现最佳性能，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。在这第一笔资助中，我们将测量空间对合成结构的影响，并利用它来建立一个新概念的基础，我们称之为“三维合成生物学”。SynBio 3D将通过添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无法实现的目标。该项目将解决取得成功的两个主要障碍。首先，作为基因电路开发核心的数学模型，绝大多数都是以时间为唯一参考的。这限制了我们表示生物分子相互作用的基于时间的动力学，假设一个不切实际的零维场景。为了解决第一个问题，我们将开发新型计算方法，使我们能够使用距离和分子拥挤等空间约束来模拟遗传电路。第二个问题涉及在体内的基因位置和单分子位移的直接可视化。我们将使用超分辨率显微镜来获得定制遗传电路的三维实时测量。总之，由此产生的信息将首次正式将遗传电路在时间上的动态与其在空间上的几何特征相关联。这种三维合成生物学方法将引领将分子网络转化为可编程系统的道路;这一目标在传统的基于时间的方法中是难以实现的。此外，它将影响从生物物理学到计算机科学等显然遥远的领域的研究路线。

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.