Matuszyńska Anna, Ebenhöh Oliver, Zurbriggen Matias D, Ducat Daniel C, Axmann Ilka M
Computational Life Science, Department of Biology, RWTH Aachen University, Aachen 52074, Germany.
Cluster of Excellence on Plant Sciences, CEPLAS, Heinrich Heine University Düsseldorf, Düsseldorf 40225, Germany.
Synth Biol (Oxf). 2024 Jul 16;9(1):ysae011. doi: 10.1093/synbio/ysae011. eCollection 2024.
Synthetic biology conceptualizes 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 synthesize 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 multispecies communities. We argue for a shift in perspective from single organism-centred approaches to emphasizing 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. .
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、装置和系统的网络,对基础研究和应用研究产生了革命性影响。凭借前所未有的跨生物体合成和转移任何DNA和RNA的能力,合成生物学的范围正在不断扩大,并以以前无法想象的方式得以重塑。该领域已发展到可以构建高度复杂网络的水平,比如合成生物体的人工群落。与此同时,计算生物学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日益增加的复杂性和新出现的特性。然而,将建模完全整合到合成设计过程中仍有巨大的未开发潜力,这为科学进步带来了令人兴奋的机遇。在此,我们首先强调微生物群落计算机辅助设计的最新进展。接下来,我们提出这样的设计可以受益于一种无生物体的模块化建模方法,该方法在多物种群落设计中强调生物体功能模块。我们主张视角从以单一生物体为中心的方法转向强调群落内生物体的功能贡献。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以在群落中发挥特定的功能作用。这种方法与合成生物学策略相一致,并为人工群落的设计带来了令人兴奋的可能性。