Host Evolution Improves Genetic Circuit Function in Complex Growth Environments

IF 3.7 2区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

ACS Synthetic Biology Pub Date : 2025-05-20 DOI:10.1021/acssynbio.5c0016810.1021/acssynbio.5c00168

Joanna T. Zhang*, Andrew Lezia, Philip Emmanuele, Muyao Wu, Elina C. Olson, Aayush Somani, Adam M. Feist and Jeff Hasty,

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引用次数: 0

Abstract

The systematic design of genetic circuits with predictable behaviors in complex environments remains a significant challenge. Here, we engineered a population control circuit and used a combination of evolutionary and rational engineering approaches to enhance Escherichia coli for robust genetic circuit behavior in nontraditional growth environments. We utilized adaptive laboratory evolution (ALE) on E. coli MG1655 in minimal media with a sole carbon source and saw improved dynamics of the circuit after host evolution. Additionally, we applied ALE to E. coli Nissle, a probiotic strain, in a more complex medium environment with added reactive oxygen species (ROS) stress. In combination with directed mutagenesis and high-throughput microfluidic screening, we observed restored circuit function and improved tolerance of the circuit components. These findings serve as a framework for the optimization of relevant bacterial host strains for improved growth and gene circuit performance in complex environments.

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宿主进化在复杂生长环境中改善遗传回路功能

在复杂环境中系统地设计具有可预测行为的遗传电路仍然是一个重大挑战。在这里，我们设计了一个种群控制电路，并使用进化和合理工程方法的结合来增强大肠杆菌在非传统生长环境中健壮的遗传电路行为。我们在单一碳源的最小培养基中对大肠杆菌MG1655进行了适应性实验室进化（ALE），发现宿主进化后电路的动力学得到了改善。此外，我们将ALE应用于大肠杆菌Nissle，一种益生菌菌株，在更复杂的培养基环境中添加活性氧（ROS）胁迫。结合定向诱变和高通量微流体筛选，我们观察到电路功能恢复和电路元件耐受性提高。这些发现可作为优化相关细菌宿主菌株的框架，以改善复杂环境下的生长和基因回路性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

ACS Synthetic Biology 生物-

CiteScore

8.00

自引率

10.60%

发文量

380

审稿时长

6-12 weeks

期刊介绍： The journal is particularly interested in studies on the design and synthesis of new genetic circuits and gene products; computational methods in the design of systems; and integrative applied approaches to understanding disease and metabolism. Topics may include, but are not limited to: Design and optimization of genetic systems Genetic circuit design and their principles for their organization into programs Computational methods to aid the design of genetic systems Experimental methods to quantify genetic parts, circuits, and metabolic fluxes Genetic parts libraries: their creation, analysis, and ontological representation Protein engineering including computational design Metabolic engineering and cellular manufacturing, including biomass conversion Natural product access, engineering, and production Creative and innovative applications of cellular programming Medical applications, tissue engineering, and the programming of therapeutic cells Minimal cell design and construction Genomics and genome replacement strategies Viral engineering Automated and robotic assembly platforms for synthetic biology DNA synthesis methodologies Metagenomics and synthetic metagenomic analysis Bioinformatics applied to gene discovery, chemoinformatics, and pathway construction Gene optimization Methods for genome-scale measurements of transcription and metabolomics Systems biology and methods to integrate multiple data sources in vitro and cell-free synthetic biology and molecular programming Nucleic acid engineering.