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通过生物信号传播网络模型评估电基因激活。

Assessing electrogenetic activation via a network model of biological signal propagation.

作者信息

Chun Kayla, VanArsdale Eric, May Elebeoba, Payne Gregory F, Bentley William E

机构信息

Fischell Department of Bioengineering, University of Maryland, College Parko, MD, United States.

Institute for Bioscience and Biotechnology Research, University of Maryland, College Park, MD, United States.

出版信息

Front Syst Biol. 2024 Mar 1;4:1291293. doi: 10.3389/fsysb.2024.1291293. eCollection 2024.

Abstract

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. 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. 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. 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.

摘要

分子通信是由分子结构和活性编码的信息传递。我们研究细菌群落中的分子通信,因为具有不同生物合成能力的细胞可以组装起来以增强功能。为确保强大的性能,需要在单个细胞内的工程遗传电路及其群体规模功能方面进行协调。我们提出,“电遗传学”,即利用电子设备激活特定的遗传电路,是电子设备介导分子通信的一种方式,最终实现可编程控制。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,边代表信号分子传递的通信通道。我们利用诸如边动态和图拓扑等图属性来研究特定工程细菌群落的信号动态。我们能够用我们的模型重现以前的实验系统。此外,我们发现具有更多不同亚群(高网络模块性)的网络比随机网络传播信号的速度更慢,而亚群相对于诱导源(电极)的战略安排可以增加信号输出并优于其他均匀网络。我们开发这个模型不仅是为了更好地理解我们以前的实验结果,也是为了实现未来的设计,其中亚群组成、遗传电路和空间配置可以改变以调整性能。我们认为这项工作可能为合成组装系统以及天然微生物群落中发生的信号传递提供见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7898/12342027/38bbc3b66a87/fsysb-04-1291293-g001.jpg

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