通过生物信号传播网络模型评估电基因激活作用

Kayla Chun, Eric VanArsdale, Elebeoba May, Gregory F. Payne, William E. Bentley
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引用次数: 0

摘要

引言分子通讯是由分子结构和活动编码的信息传递。我们研究了细菌联合体内的分子通讯,因为具有不同生物合成能力的细胞可以组装在一起以增强功能。它们之间的协调,无论是在单个细胞内的工程遗传回路方面,还是在群体规模的功能方面,都需要确保强大的性能。我们认为,"电遗传学",即使用电子设备激活特定的基因电路,是电子设备介导分子通信的一种手段,最终实现可编程控制。方法:在这里,我们开发了一个图形网络模型,用于动态评估电子和分子信号传播方案,其中节点代表单个细胞,其边缘代表信号分子传输的通信通道。我们利用边缘动态和图拓扑等图属性来研究特定工程细菌联合体的信号动态:结果:我们能够利用我们的模型再现以前的实验系统。此外,我们还发现,具有更多不同亚群(高网络模块化)的网络传播信号的速度比随机网络慢,而亚群相对于诱导源(电极)的策略性排列可以增加信号输出,并优于其他同质网络:我们建立这个模型是为了更好地理解之前的实验结果,同时也是为了在未来的设计中,通过改变亚群组成、遗传回路和空间配置来调整性能。我们认为,这项工作可以让我们深入了解在合成系统和本地微生物群落中发生的信号传递。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessing electrogenetic activation via a network model of biological signal propagation
Introduction: Molecular communication is the transfer of information encoded by molecular structure and activity. We examine molecular communication within bacterial consortia as cells with diverse biosynthetic capabilities can be assembled for enhanced function. Their coordination, both in terms of engineered genetic circuits within individual cells as well as their population-scale functions, is needed to ensure robust performance. We have suggested that “electrogenetics,” the use of electronics to activate specific genetic circuits, is a means by which electronic devices can mediate molecular communication, ultimately enabling programmable control.Methods: Here, we have developed a graphical network model for dynamically assessing electronic and molecular signal propagation schemes wherein nodes represent individual cells, and their edges represent communication channels by which signaling molecules are transferred. We utilize graph properties such as edge dynamics and graph topology to interrogate the signaling dynamics of specific engineered bacterial consortia.Results: We were able to recapitulate previous experimental systems with our model. In addition, we found that networks with more distinct subpopulations (high network modularity) propagated signals more slowly than randomized networks, while strategic arrangement of subpopulations with respect to the inducer source (an electrode) can increase signal output and outperform otherwise homogeneous networks.Discussion: We developed this model to better understand our previous experimental results, but also to enable future designs wherein subpopulation composition, genetic circuits, and spatial configurations can be varied to tune performance. We suggest that this work may provide insight into the signaling which occurs in synthetically assembled systems as well as native microbial communities.
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