Revealing the Host-Dependent Nature of an Engineered Genetic Inverter in Concordance with Physiology.

Q2 Agricultural and Biological Sciences 生物设计研究(英文) Pub Date : 2023-08-16 eCollection Date: 2023-01-01 DOI:10.34133/bdr.0016
Dennis Tin Chat Chan, Geoff S Baldwin, Hans C Bernstein
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引用次数: 1

Abstract

Broad-host-range synthetic biology is an emerging frontier that aims to expand our current engineerable domain of microbial hosts for biodesign applications. As more novel species are brought to "model status," synthetic biologists are discovering that identically engineered genetic circuits can exhibit different performances depending on the organism it operates within, an observation referred to as the "chassis effect." It remains a major challenge to uncover which genome-encoded and biological determinants will underpin chassis effects that govern the performance of engineered genetic devices. In this study, we compared model and novel bacterial hosts to ask whether phylogenomic relatedness or similarity in host physiology is a better predictor of genetic circuit performance. This was accomplished using a comparative framework based on multivariate statistical approaches to systematically demonstrate the chassis effect and characterize the performance dynamics of a genetic inverter circuit operating within 6 Gammaproteobacteria. Our results solidify the notion that genetic devices are strongly impacted by the host context. Furthermore, we formally determined that hosts exhibiting more similar metrics of growth and molecular physiology also exhibit more similar performance of the genetic inverter, indicating that specific bacterial physiology underpins measurable chassis effects. The result of this study contributes to the field of broad-host-range synthetic biology by lending increased predictive power to the implementation of genetic devices in less-established microbial hosts.

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揭示与生理学相一致的工程遗传逆变器的宿主依赖性。
广泛的宿主合成生物学是一个新兴的前沿领域,旨在扩大我们目前的微生物宿主工程领域,用于生物设计应用。随着越来越多的新物种被带到“模型状态”,合成生物学家发现,相同工程的遗传回路可以根据其运行的生物体表现出不同的性能,这一观察结果被称为“底盘效应”。“揭示哪些基因组编码和生物决定因素将支撑控制工程遗传设备性能的底盘效应仍然是一个重大挑战。在这项研究中,我们比较了模型和新型细菌宿主,以询问宿主生理学中的系统发育组学相关性或相似性是否是遗传回路性能的更好预测指标基于多变量统计方法的辅助框架,系统地证明了底盘效应,并表征了在6个伽马射线细菌中运行的遗传逆变器电路的性能动力学。我们的研究结果巩固了遗传装置受到宿主环境强烈影响的观点。此外,我们正式确定,表现出更相似的生长和分子生理指标的宿主也表现出更类似的遗传逆变器性能,这表明特定的细菌生理学是可测量的底盘效应的基础。这项研究的结果为在不太成熟的微生物宿主中实施遗传装置提供了更高的预测能力,从而为广泛的宿主合成生物学领域做出了贡献。
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CiteScore
3.90
自引率
0.00%
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审稿时长
12 weeks
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