The role of the cellular economics in the expression of exogenous genes: Towards modularity in synthetic circuit design.

合成生物学的目标之一是设计和构建能够进行逻辑计算的生物系统，即整合环境信号以产生所需的输出。这是朝着该领域的进一步发展迈出的非常重要的一步，例如构建合成组织和器官。为了实现这一目标，需要将工程学原理应用于生物系统。这项建议侧重于将模块化原则作为生物学中的一种设计规则。模块化将允许快速、可靠地构建复杂的合成遗传电路。大型电路可以很容易地实现为众所周知的模块的总和，这些模块保持它们在隔离时表现出的相同属性，就像在电子产品中发生的那样。这对合成生物学家来说是一个巨大的挑战，因为这些模块很少相互独立。这主要是因为它们都为其组成基因的表达而竞争相同的细胞资源池。因此，在资源可获得性的限制下，细胞可以被设想为一个分子经济市场，其中许多基因同时竞争相同的转录和翻译机制。这些机制分别催化RNA的合成和蛋白质的合成，最终在细胞中发挥功能。可用于基因表达的资源并不是无限的，因此，根据细胞资源的投入方式，一些基因将受益于池中较大部分的基因，而另一些基因将只能获得非常少量的资源。因此，这种不对称的分布或资源反映在同时表达的基因编码的蛋白质的不同相对丰度上。这种不均匀的分布特别影响了人工遗传电路的性能，并最终损害了模块化的概念。与计算机科学相比，合成电路将是系统的软件--一组旨在执行某一功能的脚本--而细胞机器将是完成外源DNA中编码的指令所需的硬件。在这个项目中，我们的目标是确定硬件的修改，增加细胞的处理能力，以便可以使用模型系统大肠杆菌来运行更复杂的程序。我们将在测试电路中分析与RNA聚合酶和核糖体的合成和功能有关的基因修改的效果。对于这项任务，我们将使用我之前开发和应用的电路来确定使用荧光记者进行基因表达的竞争程度。一旦确定了用于资源分配的相关基因，我们将开发出针对电路实现进行优化的菌株。这些新进化的菌株将被用于基于编码转录级联、振荡器和多层逻辑门的遗传电路进行复杂的计算。为了了解这些复杂系统的行为，我们将生成描述在小区资源有限的条件下运行的每个电路的数学模型。这些模型将被用来对电路性能进行预测，这些预测将得到实验验证。根据这些研究的结果，我们的目标是绕过由于共享单元中的资源而导致的电路性能差的问题，这一现象极大地限制了可构建电路的复杂性。此外，我们还将在细菌中测试模块化设计的局限性。实现遗传网络的模块化构建，将对我们在生物体内设计复杂的决策过程产生重大影响。它将有助于将合成生物学转变为一门真正的工程学科，为多种生物技术应用铺平道路。

One of the goals of synthetic biology is the design and construction of biological systems capable of performing logic computations, that is, to integrate environmental signals to produce desired outputs. This is a very important step towards further developments of the field, such as the construction of synthetic tissues and organs. To achieve that goal, it is required that engineering principles could be applied into biological systems. This proposal focuses in the principle of modularity as a rule of design in biology. Modularity will allow fast and reliable building of complex synthetic genetic circuits. Large circuits could be easily implemented as the sum of well-known modules that keep the same properties that they exhibit when they are isolated, as it happens in electronics. That is a big challenge for synthetic biologists as the modules are rarely independent from each other. This is mainly because all of them compete for the same pool of cellular resources for the expression of their constituent genes.As a consequence in the limitations of the availability of resources, the cell can be envisioned as a molecular economical market where many genes compete simultaneously for the same transcriptional and translational machineries. These machineries catalyse, respectively, the synthesis of the RNA and the synthesis of the proteins that ultimately perform functions in the cell. The resources available for gene expression are not infinite and, therefore, depending on how the cellular resources are invested, some genes will benefit from larger fractions of the pool while some others will only have access to very small amounts. This asymmetric distribution or resources is consequently reflected in the different relative abundances of the proteins encoded by genes being expressed at the same time. This uneven distribution affects particularly the performance of artificial genetic circuits and, ultimately, compromise the notion of modularity.In a comparison with computer science, the synthetic circuits would be the software of the system - a set of scripts designed to perform a function -, whereas the cell machinery would be the hardware needed to accomplish the instructions coded in the exogenous DNA. In this project we aim to identify modifications of the hardware increasing the processing capabilities of the cell so that more complex programs can be run using to that end the model system Escherichia coli. We will analyse in a test circuit the effect of modifications in genes involved in the synthesis and function of the RNA polymerase and ribosomes. We will use for this task a circuit that I developed and applied previously to determine the extent of competition in gene expression using fluorescent reporters. Once the relevant genes for resource allocation have been identified, we will develop strains optimized for circuit implementation. These newly evolved strains will be used to implement complex computations based on genetic circuits encoding transcriptional cascades, oscillators and multi-layered logic gates. To understand the behaviour of these complex systems we will generate mathematical models describing each of the circuits operating in conditions where the cell resources are limited. The models will be used to make predictions about circuit performance, and these predictions will be validated experimentally.With the results of these investigations we aim to bypass the problem of poor circuit performance due to sharing of resources in the cell, a phenomenon that substantially limits the complexity of the circuits that can be built. In addition, we will test the limits of modular design in bacteria. Achieving modular construction of genetic networks will have a great impact in the way that we can design complex processes for making decisions in living organisms. It will help to transform synthetic biology into a real engineering discipline, paving the path for multiple biotechnological applications.