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Jul 28, 2014

Accelerating Protein Engineering through Rational Oligo Library Design

  • The previous article in this series, From Conventional Mutagenesis to Complex, Rationally Designed Mutant Libraries, described how conventional site-directed mutagenesis methods have been improved to enable rapid creation of mutations at a limited number of sites. However, these methods have been limited in utility due to their requirement for prior protein structural knowledge. A new synthetic biology approach offers the capability of random mutagenesis methods to survey large target regions without prior structural knowledge, while enabling the user-specified changes facilitated by fast site-directed methods.

  • Rationally Designed Mutant Libraries

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    Figure 1. The Agilent QuikChange HT system for rational design of oligo libraries that enable rapid, large-scale mutagenesis to determine structure/function relationships and accelerate protein engineering at a price point that makes it accessible to all researchers.

    Custom mutant library construction using gene synthesis is most effective for characterizing small numbers of variants (10’s), as the costs increase rapidly when building libraries to comprehensively uncover critical positions and identify improved variants across a complete domain.

    A new high-throughput site-directed mutagenesis method (Figure 1) dramatically reduces the cost and limitations of custom mutant library synthesis, while overcoming the screening burden posed by site-directed mutagenesis with degenerate (mixed base) codon primers. This approach combines the high fidelity of massively parallel oligo synthesis with the ease of use and efficiency of QuikChange site-directed mutagenesis. This oligo library method enables rationalized single amino acid (e.g., Alanine) scanning, codon saturation scanning and targeted combinatorial mutagenesis, providing structural and functional linkage while identifying improved variants. The rationally designed library minimizes the number of clones to screen, without the prohibitive expense of synthesizing the entire gene.

    This new approach begins with the in silico design of as many as tens of thousands of user-defined sequences using a dedicated web-based software (Figure 1). Every codon within a 20–70 amino acid region can be precisely targeted with a single oligo set. Multiple oligo sets can be designed to mutate continuous or discrete sites, including other regions of the same or different proteins, in parallel reactions. This rational design approach eliminates the codon redundancy and bias, as well as the non-coding, wild type and non-target mutations observed when using degenerate oligos and error-prone (EP)-PCR.

    Once the oligo sets are produced and received by the researcher, they are amplified via PCR, purified, and incorporated into an appropriate plasmid vector (containing the wild-type GOI and propagated in an X strain) using linear amplification and high-fidelity Pfu DNA polymerase to minimize the frequency of unintended secondary mutations outside the primer-binding region (Figure 1). The methylated and hemi-methylated parental plasmid is then digested with Dpn I enzyme, and the mutant plasmids are transformed into supercompetent cells developed for this application.

  • Discover Faster, Learn More

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    Figure 2. The three modes of mutagenesis made possible by a mutant oligo library mutagenesis approach.

    Two key advantages of this rational oligo design approach are coverage and a dramatic reduction in the number of clones that must be screened. Conventional site-directed methods are limited in the number of mutations that can be created in parallel, and random mutagenesis methods do not cover all the hotspots, or do not generate all the needed mutations at every site of interest. This new approach provides only the mutations of interest, and as many as thousands of those mutations per experiment, delivering comprehensive coverage. It is ideal for rationalized single amino acid scanning, site saturation scanning and targeted combinatorial mutagenesis (Figure 2).

    One of the key rate-limiting steps that can also constrain the scope of an investigation is screening of mutant clones. Using site-directed methods with degenerate content can require screening of 1.7 to 3.5 times as many clones as would be necessary using this new method for a single site. This becomes a minimum of eight times more when looking at combinations of 4 saturated sites. Because of the limitations of random mutagenesis, it cannot be practically used for a comprehensive screening as it has been estimated that in average only 7 aminoacids are represented per site in an extensive random mutagenesis library.

    • Dramatically reduced screening
    • Optimized codon usage
    • Confident structure-function assignments
    • Comprehensive coverage improves intellectual property creation and protection
  • Proof of Principle

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    Figure 3. Codon saturation scanning of GFP. The GFP structure appears to be very sensitive to modification, as seen by the overall low number of mutants that retain fluorescence. However, 15 mutants with brighter fluorescence than enhanced hrGFP II were identified.

    This oligo library mutagenesis method was used in a codon saturation experiment to discover single amino acid variants of Renilla reniformis GFP (green fluorescent protein) with increased fluorescence. A brighter variant was previously generated by random mutagenesis of the humanized wild-type gfp gene. Using codon saturation scanning, forty independent amino acid changes were identified that increase fluorescent intensity of wild-type GFP; of these, 15 point mutants were brighter than enhanced hrGFP II (Figure 3). Most interestingly, the mutations were in two domains not directly involved with the chromophore, making them candidates for subsequent combinatorial mutagenesis.

    Key Applications:

    • Antibody Engineering
    • Enzyme Engineering
    • Protein Folding and Solubility
    • ID functional sites
    • Phosphorylation sites
    • Protein/Protein Interactions
    • Protein Expression Optimization
    • SNP validation


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