Literature DB >> 16724918

The diversity challenge in directed protein evolution.

Tuck Seng Wong1, Daria Zhurina, Ulrich Schwaneberg.   

Abstract

Over the past decade, we have witnessed a bloom in the field of evolutive protein engineering which is fueled by advances in molecular biology techniques and high-throughput screening technology. Directed protein evolution is a powerful algorithm using iterative cycles of random mutagenesis and screening for tailoring protein properties to our needs in industrial applications and for elucidating proteins' structure function relationships. This review summarizes, categorizes and discusses advantages and disadvantages of random mutagenesis methods used for generating genetic diversity. These random mutagenesis methods have been classified into four main categories depending on the method employed for nucleotide substitutions: enzyme based methods (Category I), synthetic chemistry based methods (Category II), whole cell methods (Category III) and combined methods (Category I-II, I-III and II-III). The basic principle of each method is discussed and varied mutagenic conditions are summarized in Tables and compared (benchmarked) to each other in terms of: mutational bias, controllable mutation frequency, ability to generate consecutive nucleotide substitutions and subset diversity, dependency on gene length, technical simplicity/robustness and cost-effectiveness. The latter comparison shows how highly-biased and limited current diversity creating methods are. Based on these limitations, strategies for generating diverse mutant libraries are proposed and discussed (RaMuS-Flowchart; KISS principle). We hope that this review provides, especially for researchers just entering the field of directed evolution, a guide for developing successful directed evolution strategies by selecting complementary methods for generating diverse mutant libraries.

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Year:  2006        PMID: 16724918     DOI: 10.2174/138620706776843192

Source DB:  PubMed          Journal:  Comb Chem High Throughput Screen        ISSN: 1386-2073            Impact factor:   1.339


  16 in total

1.  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

2.  Fine-tuning gene networks using simple sequence repeats.

Authors:  Robert G Egbert; Eric Klavins
Journal:  Proc Natl Acad Sci U S A       Date:  2012-08-27       Impact factor: 11.205

3.  Hierarchy and extremes in selections from pools of randomized proteins.

Authors:  Sébastien Boyer; Dipanwita Biswas; Ananda Kumar Soshee; Natale Scaramozzino; Clément Nizak; Olivier Rivoire
Journal:  Proc Natl Acad Sci U S A       Date:  2016-03-11       Impact factor: 11.205

4.  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

Review 5.  Beyond directed evolution--semi-rational protein engineering and design.

Authors:  Stefan Lutz
Journal:  Curr Opin Biotechnol       Date:  2010-09-24       Impact factor: 9.740

6.  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

7.  Saccharomyces cerevisiae in directed evolution: An efficient tool to improve enzymes.

Authors:  David Gonzalez-Perez; Eva Garcia-Ruiz; Miguel Alcalde
Journal:  Bioeng Bugs       Date:  2012-05-01

8.  Mutagenic Organized Recombination Process by Homologous IN vivo Grouping (MORPHING) for directed enzyme evolution.

Authors:  David Gonzalez-Perez; Patricia Molina-Espeja; Eva Garcia-Ruiz; Miguel Alcalde
Journal:  PLoS One       Date:  2014-03-10       Impact factor: 3.240

9.  Development of potent in vivo mutagenesis plasmids with broad mutational spectra.

Authors:  Ahmed H Badran; David R Liu
Journal:  Nat Commun       Date:  2015-10-07       Impact factor: 14.919

10.  High throughput mutagenesis for identification of residues regulating human prostacyclin (hIP) receptor expression and function.

Authors:  Anke Bill; Elizabeth M Rosethorne; Toby C Kent; Lindsay Fawcett; Lynn Burchell; Michiel T van Diepen; Anthony Marelli; Sergey Batalov; Loren Miraglia; Anthony P Orth; Nicole A Renaud; Steven J Charlton; Martin Gosling; L Alex Gaither; Paul J Groot-Kormelink
Journal:  PLoS One       Date:  2014-06-02       Impact factor: 3.240

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