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。这是该领域进一步发展的非常重要的一步，例如合成组织和器官的构建。为了实现这一目标，需要将工程原理应用到生物系统中。这一建议的重点是模块化的原则，作为一个规则的设计在生物学。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，当它们被隔离时保持相同的特性，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了表达它们的组成基因而竞争相同的细胞资源池。由于资源的有限性，细胞可以被设想为一个分子经济市场，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的合成和最终在细胞中发挥作用的蛋白质的合成。可用于基因表达的资源不是无限的，因此，取决于细胞资源的投入方式，一些基因将受益于更大比例的资源池，而另一些基因只能获得很少的资源池。这种资源的不对称分布反映在同时表达的基因所编码的蛋白质的相对丰度不同上。这种不均匀分布尤其会影响人工遗传电路的性能，并最终损害模块化的概念。与计算机科学相比，合成电路将是系统的软件——一组设计用于执行功能的脚本——而细胞机器将是完成外源DNA编码指令所需的硬件。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，以便更复杂的程序可以使用大肠杆菌模型系统来运行。我们将在测试电路中分析参与RNA聚合酶和核糖体合成和功能的基因修饰的影响。我们将在这项任务中使用我之前开发并应用的电路，该电路使用荧光报告基因来确定基因表达的竞争程度。一旦确定了资源分配的相关基因，我们将开发适合电路实现的菌株。这些新进化的菌株将用于实现基于编码转录级联、振荡器和多层逻辑门的遗传电路的复杂计算。为了理解这些复杂系统的行为，我们将生成数学模型，描述在细胞资源有限的条件下运行的每个电路。这些模型将用于对电路性能进行预测，这些预测将在实验中得到验证。根据这些研究结果，我们的目标是绕过由于单元中资源共享而导致的电路性能差的问题，这种现象实质上限制了可以构建的电路的复杂性。此外，我们将在细菌中测试模块化设计的极限。实现基因网络的模块化构建将对我们设计复杂的生物决策过程产生重大影响。这将有助于将合成生物学转变为一门真正的工程学科，为多种生物技术的应用铺平道路。

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.