Anna B. Matuszyńska, O. Ebenhöh, Matias D Zurbriggen, Daniel C Ducat, Ilka M. Axmann
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引用次数: 0
摘要
合成生物学将生物复杂性概念化为具有预定功能的生物部件、装置和系统网络,对基础研究和应用研究产生了革命性的影响。由于合成和跨生物体转移任何 DNA 和 RNA 的能力前所未有,合成生物学的范围不断扩大,并以以前无法想象的方式进行再创造。该领域已经发展到可以构建高度复杂网络的水平,例如合成生物的人工群落。与此同时,计算生物学也成为生物学研究不可或缺的一部分,计算模型有助于揭示生物现象不断升级的复杂性和新特性。然而,将建模完全融入合成设计过程仍有巨大的潜力尚未开发,这为科学进步带来了令人兴奋的机遇。在此,我们首先重点介绍微生物群落计算机辅助设计的最新进展。接下来,我们提出,这种设计可以受益于无生物模块建模方法,这种方法将重点放在生物功能模块上,从而设计出多物种群落。我们主张转变视角,从以单一生物为中心的方法转向强调群落内生物的功能贡献。通过使用具有部件和电路数学描述的模块化计算模型组装合成生物系统,我们可以定制生物体,使其在群落中发挥特定的功能作用。这种方法符合合成生物学战略,为设计人工群落提供了令人兴奋的可能性。
A new era of Synthetic Biology - microbial community design
Synthetic biology conceptualises biological complexity as a network of biological parts, devices and systems with predetermined functionalities, and has had a revolutionary impact on fundamental and applied research. With the unprecedented ability to synthesise and transfer any DNA and RNA across organisms, the scope of synthetic biology is expanding and being recreated in previously unimaginable ways. The field has matured to a level where highly complex networks, such as artificial communities of synthetic organisms can be constructed. In parallel, computational biology became an integral part of biological studies, with computational models aiding the unravelling of the escalating complexity and emerging properties of biological phenomena. However, there is still a vast untapped potential for the complete integration of modelling into the synthetic design process, presenting exciting opportunities for scientific advancements. Here, we first highlight the most recent advances in computer-aided design of microbial communities. Next, we propose that such a design can benefit from an organism-free modular modelling approach that places its emphasis on modules of organismal function towards the design of multi-species communities. We argue for a shift in perspective from single organism-centred approaches to emphasising the functional contributions of organisms within the community. By assembling synthetic biological systems using modular computational models with mathematical descriptions of parts and circuits, we can tailor organisms to fulfil specific functional roles within the community. This approach aligns with synthetic biology strategies and presents exciting possibilities for the design of artificial communities.