Matteo Vajente, Riccardo Clerici, Hendrik Ballerstedt, Lars M Blank, Sandy Schmidt
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引用次数: 0
Abstract
Bacteria are a treasure trove of metabolic reactions, but most industrial biotechnology applications rely on a limited set of established host organisms. In contrast, adopting nonmodel bacteria for the production of various chemicals of interest is often hampered by their limited genetic amenability coupled with their low transformation efficiency. In this study, we propose a series of steps that can be taken to increase electroporation efficiency in nonmodel bacteria. As a test strain, we use Cupriavidus necator H16, a lithoautotrophic bacterium that has been engineered to produce a wide range of products from CO2 and hydrogen. However, its low electroporation efficiency hampers the high-throughput genetic engineering required to develop C. necator into an industrially relevant host organism. Thus, conjugation has often been the method of choice for introducing exogenous DNA, especially when introducing large plasmids or suicide plasmids. We first propose a species-independent technique based on natively methylated DNA and Golden Gate assembly to increase one-pot cloning and electroporation efficiency by 70-fold. Second, bioinformatic tools were used to predict defense systems and develop a restriction avoidance strategy that was used to introduce suicide plasmids by electroporation to obtain a domesticated strain. The results are discussed in the context of metabolic engineering of nonmodel bacteria.
细菌是新陈代谢反应的宝库,但大多数工业生物技术应用都依赖于有限的既定宿主生物。与此相反,采用非模式细菌生产各种相关化学物质时,往往因其有限的遗传适应性和较低的转化效率而受到阻碍。在本研究中,我们提出了一系列提高非模式细菌电穿孔效率的步骤。作为测试菌株,我们使用了坏死杯状芽孢杆菌(Cupriavidus necator H16),这是一种石生自养细菌,经改造后可利用二氧化碳和氢气生产多种产品。然而,其较低的电穿孔效率阻碍了将坏死杯状芽孢杆菌培养成工业相关宿主生物所需的高通量基因工程。因此,共轭通常是引入外源 DNA 的首选方法,尤其是在引入大型质粒或自杀质粒时。我们首先提出了一种基于原生甲基化 DNA 和 Golden Gate 组装的不依赖物种的技术,将一锅克隆和电穿孔效率提高了 70 倍。其次,我们利用生物信息学工具预测了防御系统,并制定了限制性规避策略,通过电穿孔引入自杀质粒,从而获得驯化菌株。本文结合非模式细菌的代谢工程对研究结果进行了讨论。
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.