Combinatorial Recombination of Gene Fragments to Construct a Library of Chimeras

Abstract

Recombination of distantly related and nonrelated genes is difficult using traditional PCR-based techniques, and truncation-based methods result in a large proportion of nonviable sequences due to frame shifts, deletions, and insertions. This unit describes a method for creating libraries of chimeras through combinatorial assembly of gene fragments. It allows the experimenter to recombine genes of any identity and to select the sites where recombination takes place. Combinatorial recombination is achieved by generating gene fragments with specific overhangs, or sticky ends. The overhangs permit the fragments to be ligated in the correct order while allowing independent assortment of blocks with identical overhangs. Genes of any identity can be recombined so long as they share 3 to 5 base pairs of identity at the desired recombination sites. Simple adaptations of the method allow incorporation of specific gene fragments.

Random Field Model Reveals Structure of the Protein Recombinational Landscape

“…Sequencing of unselected chimeric genes found 9 of 13 to have frame shift mutations [16] , which almost certainly result in inactive proteins. Since a majority of frame shifts are incorporated at the PCR step during library construction, it is likely these errors are present throughout all constructed chimeras [11] . The maximum likelihood estimate for the proportion of correctly constructed chimeras is , with 95% confidence intervals between 0.09 and 0.61 using the Clopper-Pearson interval [51] .…”

Library Generation by Gene Shuffling

“…Alternatively, Type IIB restriction endonuclease sites may be introduced into predefined cross-over points. When the template is digested, each domain is left with unique overhangs that allow for scar-less ligation of fragments in the correct order (Hiraga and Arnold, 2003; Farrow and Arnold, 2010). …”

“…This is discussed further in Alternatives-Defined Cross-over Points. A detailed method for this alternative can be found in Current Protocols in Protein Science, UNIT 26.2 (Farrow and Arnold, 2010). …”

Computational tools for metabolic engineering

“…In making its prediction, Gene Designer’s codon optimization module considers four major properties: codon usage, restriction endonuclease sites, sequence homology, and mRNA secondary structure. An additional capability of this tool that metabolic engineers may enjoy is the ability to specify custom sequence constraints to minimize or maximize regions of homology with respect to a reference sequence, and this feature has been used for applications such as RNAi (Kumar et al, 2006) or gene recombination (Farrow and Arnold, 2010). …”