Manzoni Romilde, Urrios Arturo, Velazquez-Garcia Silvia, de Nadal Eulàlia, Posas Francesc
Cell Signaling Research Group, Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra (UPF), E-08003 Barcelona, Spain.
Integr Biol (Camb). 2016 Apr 18;8(4):518-32. doi: 10.1039/c5ib00274e. Epub 2016 Apr 13.
Organisms have evolved a broad array of complex signaling mechanisms that allow them to survive in a wide range of environmental conditions. They are able to sense external inputs and produce an output response by computing the information. Synthetic biology attempts to rationally engineer biological systems in order to perform desired functions. Our increasing understanding of biological systems guides this rational design, while the huge background in electronics for building circuits defines the methodology. In this context, biocomputation is the branch of synthetic biology aimed at implementing artificial computational devices using engineered biological motifs as building blocks. Biocomputational devices are defined as biological systems that are able to integrate inputs and return outputs following pre-determined rules. Over the last decade the number of available synthetic engineered devices has increased exponentially; simple and complex circuits have been built in bacteria, yeast and mammalian cells. These devices can manage and store information, take decisions based on past and present inputs, and even convert a transient signal into a sustained response. The field is experiencing a fast growth and every day it is easier to implement more complex biological functions. This is mainly due to advances in in vitro DNA synthesis, new genome editing tools, novel molecular cloning techniques, continuously growing part libraries as well as other technological advances. This allows that digital computation can now be engineered and implemented in biological systems. Simple logic gates can be implemented and connected to perform novel desired functions or to better understand and redesign biological processes. Synthetic biological digital circuits could lead to new therapeutic approaches, as well as new and efficient ways to produce complex molecules such as antibiotics, bioplastics or biofuels. Biological computation not only provides possible biomedical and biotechnological applications, but also affords a greater understanding of biological systems.
生物体已经进化出一系列广泛的复杂信号机制，使它们能够在各种环境条件下生存。它们能够感知外部输入，并通过计算信息产生输出响应。合成生物学试图对生物系统进行合理设计，以实现所需的功能。我们对生物系统不断加深的理解指导着这种合理设计，而电子学中构建电路的丰富背景则定义了方法。在这种背景下，生物计算是合成生物学的一个分支，旨在使用工程化的生物基序作为构建模块来实现人工计算设备。生物计算设备被定义为能够整合输入并按照预定规则返回输出的生物系统。在过去十年中，可用的合成工程设备数量呈指数级增长；简单和复杂的电路已在细菌、酵母和哺乳动物细胞中构建。这些设备可以管理和存储信息，根据过去和当前的输入做出决策，甚至将瞬态信号转换为持续响应。该领域正在快速发展，每天实现更复杂的生物学功能都变得更加容易。这主要归功于体外DNA合成、新的基因组编辑工具、新颖的分子克隆技术、不断增长的元件库以及其他技术进步。这使得现在可以在生物系统中设计和实现数字计算。可以实现并连接简单的逻辑门以执行新的所需功能，或更好地理解和重新设计生物过程。合成生物数字电路可能会带来新的治疗方法，以及生产抗生素、生物塑料或生物燃料等复杂分子的新的有效方法。生物计算不仅提供了可能的生物医学和生物技术应用，还能让我们对生物系统有更深入的理解。
