Literature DB >> 16325201

A statistical analysis of random mutagenesis methods used for directed protein evolution.

Tuck Seng Wong1, Danilo Roccatano, Martin Zacharias, Ulrich Schwaneberg.   

Abstract

We have developed a statistical method named MAP (mutagenesis assistant program) to equip protein engineers with a tool to develop promising directed evolution strategies by comparing 19 mutagenesis methods. Instead of conventional transition/transversion bias indicators as benchmarks for comparison, we propose to use three indicators based on the subset of amino acid substitutions generated on the protein level: (1) protein structure indicator; (2) amino acid diversity indicator with a codon diversity coefficient; and (3) chemical diversity indicator. A MAP analysis for a single nucleotide substitution was performed for four genes: (1) heme domain of cytochrome P450 BM-3 from Bacillus megaterium (EC 1.14.14.1); (2) glucose oxidase from Aspergillus niger (EC 1.1.3.4); (3) arylesterase from Pseudomonas fluorescens (EC 3.1.1.2); and (4) alcohol dehydrogenase from Saccharomyces cerevisiae (EC 1.1.1.1). Based on the MAP analysis of these four genes, 19 mutagenesis methods have been evaluated and criteria for an ideal mutagenesis method have been proposed. The statistical analysis showed that existing gene mutagenesis methods are limited and highly biased. An average amino acid substitution per residue of only 3.15-7.4 can be achieved with current random mutagenesis methods. For the four investigated gene sequences, an average fraction of amino acid substitutions of 0.5-7% results in stop codons and 4.5-23.9% in glycine or proline residues. An average fraction of 16.2-44.2% of the amino acid substitutions are preserved, and 45.6% (epPCR method) are chemically different. The diversity remains low even when applying a non-biased method: an average of seven amino acid substitutions per residue, 2.9-4.7% stop codons, 11.1-16% glycine/proline residues, 21-25.8% preserved amino acids, and 55.5% are amino acids with chemically different side-chains. Statistical information for each mutagenesis method can further be used to investigate the mutational spectra in protein regions regarded as important for the property of interest.

Entities:  

Mesh:

Substances:

Year:  2005        PMID: 16325201     DOI: 10.1016/j.jmb.2005.10.082

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  27 in total

1.  Quantifying plasmid copy number to investigate plasmid dosage effects associated with directed protein evolution.

Authors:  Samuel Million-Weaver; David L Alexander; Jennifer M Allen; Manel Camps
Journal:  Methods Mol Biol       Date:  2012

2.  A method for multi-codon scanning mutagenesis of proteins based on asymmetric transposons.

Authors:  Jia Liu; T Ashton Cropp
Journal:  Protein Eng Des Sel       Date:  2011-12-18       Impact factor: 1.650

3.  A high-throughput screening method to reengineer DNA polymerases for random mutagenesis.

Authors:  Tsvetan Kardashliev; Anna Joëlle Ruff; Jing Zhao; Ulrich Schwaneberg
Journal:  Mol Biotechnol       Date:  2014-03       Impact factor: 2.695

4.  Secretion of slow-folding proteins by a Type 1 secretion system.

Authors:  Christian K W Schwarz; Michael H H Lenders; Sander H J Smits; Lutz Schmitt
Journal:  Bioengineered       Date:  2012-06-29       Impact factor: 3.269

5.  The power of multiplexed functional analysis of genetic variants.

Authors:  Molly Gasperini; Lea Starita; Jay Shendure
Journal:  Nat Protoc       Date:  2016-09-01       Impact factor: 13.491

6.  Assessing directed evolution methods for the generation of biosynthetic enzymes with potential in drug biosynthesis.

Authors:  David P Nannemann; William R Birmingham; Robert A Scism; Brian O Bachmann
Journal:  Future Med Chem       Date:  2011-05       Impact factor: 3.808

7.  Identification of lethal mutations in yeast threonyl-tRNA synthetase revealing critical residues in its human homolog.

Authors:  Zhi-Rong Ruan; Zhi-Peng Fang; Qing Ye; Hui-Yan Lei; Gilbert Eriani; Xiao-Long Zhou; En-Duo Wang
Journal:  J Biol Chem       Date:  2014-11-21       Impact factor: 5.157

8.  Computational design of orthogonal nucleoside kinases.

Authors:  Lingfeng Liu; Paul Murphy; David Baker; Stefan Lutz
Journal:  Chem Commun (Camb)       Date:  2010-10-19       Impact factor: 6.222

9.  Random mutagenesis by error-prone pol plasmid replication in Escherichia coli.

Authors:  David L Alexander; Joshua Lilly; Jaime Hernandez; Jillian Romsdahl; Christopher J Troll; Manel Camps
Journal:  Methods Mol Biol       Date:  2014

10.  The mutagenic footprint of low-fidelity Pol I ColE1 plasmid replication in E. coli reveals an extensive interplay between Pol I and Pol III.

Authors:  Christopher Troll; Jordan Yoder; David Alexander; Jaime Hernández; Yueling Loh; Manel Camps
Journal:  Curr Genet       Date:  2013-11-02       Impact factor: 3.886

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.