Construction of “small-intelligent” focused mutagenesis libraries using well-designed combinatorial degenerate primers
Site-saturation mutagenesis is a powerful tool for protein optimization due to its efficiency and simplicity. A degenerate codon NNN or NNS (K) is often used to encode the 20 standard amino acids, but this will produce redundant codons and cause uneven distribution of amino acids in the constructed...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2012-03-01
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| Series: | BioTechniques |
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| Online Access: | https://www.future-science.com/doi/10.2144/000113820 |
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| _version_ | 1850152378308755456 |
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| author | Lixia Tang Hui Gao Xuechen Zhu Xiong Wang Ming Zhou Rongxiang Jiang |
| author_facet | Lixia Tang Hui Gao Xuechen Zhu Xiong Wang Ming Zhou Rongxiang Jiang |
| author_sort | Lixia Tang |
| collection | DOAJ |
| description | Site-saturation mutagenesis is a powerful tool for protein optimization due to its efficiency and simplicity. A degenerate codon NNN or NNS (K) is often used to encode the 20 standard amino acids, but this will produce redundant codons and cause uneven distribution of amino acids in the constructed library. Here we present a novel “small-intelligent” strategy to construct mutagenesis libraries that have a minimal gene library size without inherent amino acid biases, stop codons, or rare codons of Escherichia coli by coupling well-designed combinatorial degenerate primers with suitable PCR-based mutagenesis methods. The designed primer mixture contains exactly one codon per amino acid and thus allows the construction of small-intelligent mutagenesis libraries with one gene per protein. In addition, the software tool DC-Analyzer was developed to assist in primer design according to the user-defined randomization scheme for library construction. This small-intelligent strategy was successfully applied to the randomization of halohydrin dehalogenases with one or two randomized sites. With the help of DC-Analyzer, the strategy was proven to be as simple as NNS randomization and could serve as a general tool to efficiently randomize target genes at positions of interest. |
| format | Article |
| id | doaj-art-37c42a98c7a843328bdf3e474e7d7811 |
| institution | OA Journals |
| issn | 0736-6205 1940-9818 |
| language | English |
| publishDate | 2012-03-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | BioTechniques |
| spelling | doaj-art-37c42a98c7a843328bdf3e474e7d78112025-08-20T02:25:59ZengTaylor & Francis GroupBioTechniques0736-62051940-98182012-03-0152314915810.2144/000113820Construction of “small-intelligent” focused mutagenesis libraries using well-designed combinatorial degenerate primersLixia Tang0Hui Gao1Xuechen Zhu2Xiong Wang3Ming Zhou4Rongxiang Jiang51School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China2School of Computer Science and Technology, University of Electronic Science and Technology of China, Chengdu, China1School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China1School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China2School of Computer Science and Technology, University of Electronic Science and Technology of China, Chengdu, China1School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, ChinaSite-saturation mutagenesis is a powerful tool for protein optimization due to its efficiency and simplicity. A degenerate codon NNN or NNS (K) is often used to encode the 20 standard amino acids, but this will produce redundant codons and cause uneven distribution of amino acids in the constructed library. Here we present a novel “small-intelligent” strategy to construct mutagenesis libraries that have a minimal gene library size without inherent amino acid biases, stop codons, or rare codons of Escherichia coli by coupling well-designed combinatorial degenerate primers with suitable PCR-based mutagenesis methods. The designed primer mixture contains exactly one codon per amino acid and thus allows the construction of small-intelligent mutagenesis libraries with one gene per protein. In addition, the software tool DC-Analyzer was developed to assist in primer design according to the user-defined randomization scheme for library construction. This small-intelligent strategy was successfully applied to the randomization of halohydrin dehalogenases with one or two randomized sites. With the help of DC-Analyzer, the strategy was proven to be as simple as NNS randomization and could serve as a general tool to efficiently randomize target genes at positions of interest.https://www.future-science.com/doi/10.2144/000113820randomizationlibrary constructiondegenerate codon designcodon redundancyamino acid bias |
| spellingShingle | Lixia Tang Hui Gao Xuechen Zhu Xiong Wang Ming Zhou Rongxiang Jiang Construction of “small-intelligent” focused mutagenesis libraries using well-designed combinatorial degenerate primers BioTechniques randomization library construction degenerate codon design codon redundancy amino acid bias |
| title | Construction of “small-intelligent” focused mutagenesis libraries using well-designed combinatorial degenerate primers |
| title_full | Construction of “small-intelligent” focused mutagenesis libraries using well-designed combinatorial degenerate primers |
| title_fullStr | Construction of “small-intelligent” focused mutagenesis libraries using well-designed combinatorial degenerate primers |
| title_full_unstemmed | Construction of “small-intelligent” focused mutagenesis libraries using well-designed combinatorial degenerate primers |
| title_short | Construction of “small-intelligent” focused mutagenesis libraries using well-designed combinatorial degenerate primers |
| title_sort | construction of small intelligent focused mutagenesis libraries using well designed combinatorial degenerate primers |
| topic | randomization library construction degenerate codon design codon redundancy amino acid bias |
| url | https://www.future-science.com/doi/10.2144/000113820 |
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