One-step zero-background IgG reformatting of phage-displayed antibody fragments enabling rapid and high-throughput lead identification
Author(s) -
ChaoGuang Chen,
Louis Fabri,
Michael J. Wilson,
Con Panousis
Publication year - 2013
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gkt1142
Subject(s) - biology , cloning (programming) , recombinant dna , insert (composites) , genomic library , microbiology and biotechnology , escherichia coli , clone (java method) , antibody , high throughput screening , selection (genetic algorithm) , phagemid , molecular cloning , expression cloning , phage display , computational biology , dna , genetics , bacteriophage , gene , gene expression , computer science , peptide sequence , base sequence , engineering , programming language , mechanical engineering , artificial intelligence
We describe a novel cloning method, referred to as insert-tagged (InTag) positive selection, for the rapid one-step reformatting of phage-displayed antibody fragments to full-length immunoglobulin Gs (IgGs). InTag positive selection enables recombinant clones of interest to be directly selected without cloning background, bypassing the laborious process of plating out cultures and colony screening and enabling the cloning procedure to be automated and performed in a high-throughput format. This removes a significant bottleneck in the functional screening of phage-derived antibody candidates and enables a large number of clones to be directly reformatted into IgG without the intermediate step of Escherichia coli expression and testing of soluble antibody fragments. The use of InTag positive selection with the Dyax Fab-on-phage antibody library is demonstrated, and optimized methods for the small-scale transient expression of IgGs at high levels are described. InTag positive selection cloning has the potential for wide application in high-throughput DNA cloning involving multiple inserts, markedly improving the speed and quality of selections from protein libraries.
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