Gorochowski Thomas E, Hauert Sabine, Kreft Jan-Ulrich, Marucci Lucia, Stillman Namid R, Tang T-Y Dora, Bandiera Lucia, Bartoli Vittorio, Dixon Daniel O R, Fedorec Alex J H, Fellermann Harold, Fletcher Alexander G, Foster Tim, Giuggioli Luca, Matyjaszkiewicz Antoni, McCormick Scott, Montes Olivas Sandra, Naylor Jonathan, Rubio Denniss Ana, Ward Daniel
School of Biological Sciences, University of Bristol, Bristol, United Kingdom.
Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom.
Front Bioeng Biotechnol. 2020 Jun 26;8:705. doi: 10.3389/fbioe.2020.00705. eCollection 2020.
Many complex behaviors in biological systems emerge from large populations of interacting molecules or cells, generating functions that go beyond the capabilities of the individual parts. Such collective phenomena are of great interest to bioengineers due to their robustness and scalability. However, engineering emergent collective functions is difficult because they arise as a consequence of complex multi-level feedback, which often spans many length-scales. Here, we present a perspective on how some of these challenges could be overcome by using multi-agent modeling as a design framework within synthetic biology. Using case studies covering the construction of synthetic ecologies to biological computation and synthetic cellularity, we show how multi-agent modeling can capture the core features of complex multi-scale systems and provide novel insights into the underlying mechanisms which guide emergent functionalities across scales. The ability to unravel design rules underpinning these behaviors offers a means to take synthetic biology beyond single molecules or cells and toward the creation of systems with functions that can only emerge from collectives at multiple scales.
生物系统中的许多复杂行为源自大量相互作用的分子或细胞,由此产生的功能超越了单个部分的能力。由于其稳健性和可扩展性,这类集体现象引起了生物工程师的极大兴趣。然而,设计出涌现的集体功能很困难,因为它们是复杂的多级反馈的结果,这种反馈通常跨越多个长度尺度。在此,我们提出一种观点,即如何通过将多智能体建模用作合成生物学中的设计框架来克服其中一些挑战。通过涵盖从合成生态构建到生物计算和合成细胞性的案例研究,我们展示了多智能体建模如何能够捕捉复杂多尺度系统的核心特征,并为指导跨尺度涌现功能的潜在机制提供新的见解。揭示支撑这些行为的设计规则的能力提供了一种手段,可使合成生物学超越单个分子或细胞,朝着创建具有只能从多个尺度的集体中涌现的功能的系统发展。