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Abstract
Here we describe a facile and robust genetic selection for isolating full-length IgG antibodies from combinatorial libraries expressed in the cytoplasm of redox-engineered Escherichia coli cells. The method is based on the transport of a bifunctional substrate comprised of an antigen fused to chloramphenicol acetyltransferase, which allows positive selection of bacterial cells co-expressing cytoplasmic IgGs called cyclonals that specifically capture the chimeric antigen and sequester the antibiotic resistance marker in the cytoplasm. The utility of this approach is first demonstrated by isolating affinity-matured cyclonal variants that specifically bind their cognate antigen, the leucine zipper domain of a yeast transcriptional activator, with subnanomolar affinities, which represent a ~20-fold improvement over the parental IgG. We then use the genetic assay to discover antigen-specific cyclonals from a naïve human antibody repertoire, leading to the identification of lead IgG candidates with affinity and specificity for an influenza hemagglutinin-derived peptide antigen.
Discovery of full-length antibodies can be slow and labor intensive. Here, the authors describe a robust genetic assay for facile isolation of IgG antibodies from combinatorial libraries expressed in the cytoplasm of redox-engineered bacteria.
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1 Cornell University, Robert F. Smith School of Chemical and Biomolecular Engineering, Ithaca, USA (GRID:grid.5386.8) (ISNI:000000041936877X)
2 Cornell University, Biomedical and Biological Sciences, College of Veterinary Medicine, Ithaca, USA (GRID:grid.5386.8) (ISNI:000000041936877X)
3 New England Biolabs, Ipswich, USA (GRID:grid.273406.4) (ISNI:0000 0004 0376 1796)
4 Cornell University, Robert F. Smith School of Chemical and Biomolecular Engineering, Ithaca, USA (GRID:grid.5386.8) (ISNI:000000041936877X); Cornell University, Biomedical and Biological Sciences, College of Veterinary Medicine, Ithaca, USA (GRID:grid.5386.8) (ISNI:000000041936877X); Cornell University, Cornell Institute of Biotechnology, Ithaca, USA (GRID:grid.5386.8) (ISNI:000000041936877X)