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...

Full description

Saved in:
Bibliographic Details
Main Authors: Lixia Tang, Hui Gao, Xuechen Zhu, Xiong Wang, Ming Zhou, Rongxiang Jiang
Format: Article
Language:English
Published: Taylor & Francis Group 2012-03-01
Series:BioTechniques
Subjects:
Online Access:https://www.future-science.com/doi/10.2144/000113820
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850152378308755456
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
work_keys_str_mv AT lixiatang constructionofsmallintelligentfocusedmutagenesislibrariesusingwelldesignedcombinatorialdegenerateprimers
AT huigao constructionofsmallintelligentfocusedmutagenesislibrariesusingwelldesignedcombinatorialdegenerateprimers
AT xuechenzhu constructionofsmallintelligentfocusedmutagenesislibrariesusingwelldesignedcombinatorialdegenerateprimers
AT xiongwang constructionofsmallintelligentfocusedmutagenesislibrariesusingwelldesignedcombinatorialdegenerateprimers
AT mingzhou constructionofsmallintelligentfocusedmutagenesislibrariesusingwelldesignedcombinatorialdegenerateprimers
AT rongxiangjiang constructionofsmallintelligentfocusedmutagenesislibrariesusingwelldesignedcombinatorialdegenerateprimers