{"title":"Construction and Characterization of MoClo-Compatible Vectors for Modular Protein Expression in <i>E. coli</i>.","authors":"Jochem R Nielsen, Michael J Lewis, Wei E Huang","doi":"10.1021/acssynbio.4c00564","DOIUrl":null,"url":null,"abstract":"<p><p>Cloning methods are fundamental to synthetic biology research. The capability to generate custom DNA constructs exhibiting predictable protein expression levels is crucial to the engineering of biology. Golden Gate cloning, a modular cloning (MoClo) technique, enables rapid and reliable one-pot assembly of genetic parts. In this study, we expand on the existing MoClo toolkits by constructing and characterizing compatible low- (p15A) and medium-copy (pBR322) destination vectors. Together with existing high-copy vectors, these backbones enable a protein expression range covering a 500-fold difference in normalized fluorescence output. We further characterize the expression- and burden profiles of each vector and demonstrate their use for the optimization of growth-coupled enzyme expression. The optimal expression of <i>adhE</i> (encoding alcohol dehydrogenase) for ethanol-dependent growth of <i>Escherichia coli</i> is determined using randomized Golden Gate Assembly, creating a diverse library of constructs with varying expression strengths and plasmid copy numbers. Through selective growth experiments, we show that relatively low expression levels of <i>adhE</i> facilitated optimal growth using ethanol as the sole carbon source, demonstrating the importance of adding low-copy vectors to the MoClo vector repertoire. This study emphasizes the importance of varying vector copy numbers in selection experiments to balance expression levels and burden, ensuring accurate identification of optimal conditions for growth. The vectors developed in this work are publicly available via Addgene (catalog #217582-217609).</p>","PeriodicalId":26,"journal":{"name":"ACS Synthetic Biology","volume":" ","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2025-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Synthetic Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1021/acssynbio.4c00564","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Cloning methods are fundamental to synthetic biology research. The capability to generate custom DNA constructs exhibiting predictable protein expression levels is crucial to the engineering of biology. Golden Gate cloning, a modular cloning (MoClo) technique, enables rapid and reliable one-pot assembly of genetic parts. In this study, we expand on the existing MoClo toolkits by constructing and characterizing compatible low- (p15A) and medium-copy (pBR322) destination vectors. Together with existing high-copy vectors, these backbones enable a protein expression range covering a 500-fold difference in normalized fluorescence output. We further characterize the expression- and burden profiles of each vector and demonstrate their use for the optimization of growth-coupled enzyme expression. The optimal expression of adhE (encoding alcohol dehydrogenase) for ethanol-dependent growth of Escherichia coli is determined using randomized Golden Gate Assembly, creating a diverse library of constructs with varying expression strengths and plasmid copy numbers. Through selective growth experiments, we show that relatively low expression levels of adhE facilitated optimal growth using ethanol as the sole carbon source, demonstrating the importance of adding low-copy vectors to the MoClo vector repertoire. This study emphasizes the importance of varying vector copy numbers in selection experiments to balance expression levels and burden, ensuring accurate identification of optimal conditions for growth. The vectors developed in this work are publicly available via Addgene (catalog #217582-217609).
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.