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用于细菌合成生物学的标准化基因组结构 (SEGA)。

A standardized genome architecture for bacterial synthetic biology (SEGA).

机构信息

Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark.

出版信息

Nat Commun. 2021 Oct 7;12(1):5876. doi: 10.1038/s41467-021-26155-5.

Abstract

Chromosomal recombinant gene expression offers a number of advantages over plasmid-based synthetic biology. However, the methods applied for bacterial genome engineering are still challenging and far from being standardized. Here, in an attempt to realize the simplest recombinant genome technology imaginable and facilitate the transition from recombinant plasmids to genomes, we create a simplistic methodology and a comprehensive strain collection called the Standardized Genome Architecture (SEGA). In its simplest form, SEGA enables genome engineering by combining only two reagents: a DNA fragment that can be ordered from a commercial vendor and a stock solution of bacterial cells followed by incubation on agar plates. Recombinant genomes are identified by visual inspection using green-white colony screening akin to classical blue-white screening for recombinant plasmids. The modular nature of SEGA allows precise multi-level control of transcriptional, translational, and post-translational regulation. The SEGA architecture simultaneously supports increased standardization of genetic designs and a broad application range by utilizing well-characterized parts optimized for robust performance in the context of the bacterial genome. Ultimately, its adaption and expansion by the scientific community should improve predictability and comparability of experimental outcomes across different laboratories.

摘要

与基于质粒的合成生物学相比,染色体重组基因表达具有许多优势。然而,应用于细菌基因组工程的方法仍然具有挑战性,远未标准化。在这里,我们试图实现想象中最简单的重组基因组技术,并促进从重组质粒向基因组的转变,创建了一种称为标准化基因组架构(SEGA)的简单方法和综合菌株库。在其最简单的形式中,SEGA 通过仅结合两种试剂来实现基因组工程:可以从商业供应商订购的 DNA 片段和细菌细胞的储备溶液,然后在琼脂平板上孵育。通过类似于经典蓝-白筛选重组质粒的绿色-白色菌落筛选,通过目视检查来鉴定重组基因组。SEGA 的模块化性质允许对转录、翻译和翻译后调节进行精确的多级控制。SEGA 架构通过利用针对细菌基因组中稳健性能进行了优化的特征明确的部件,同时支持遗传设计的标准化程度提高和更广泛的应用范围。最终,科学界对其的适应和扩展应该会提高不同实验室之间实验结果的可预测性和可比性。

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