High-throughput Sorting of an Anticalin Library via EspP-mediated Functional Display on the Escherichia coli Cell Surface

We demonstrate that small engineered single-chain binding proteins based on the lipocalin scaffold, so-called Anticalins, can be functionally displayed on the Gram-negative bacterial cell envelope. To this end, the beta-domains of five different bacterial autotransporters (the IgA protease from Neisseria gonorrhoeae, the esterase EstA from Pseudomonas aeruginosa, the YpjA autotransporter from E. coli K12, the AIDA-I adhesin from enteropathogenic E. coli O127:H27 strain 2787 and the protease EspP from enterohemorrhagic E. coli O157:H7 strain EDL933) were compared with respect to display level, functional variance, and bacterial cell viability. Use of the EspP autotransporter led to a system with high genetic stability for the display of fully functional Anticalins in high density on the cell surface of E. coli as shown by quantitative flow cytofluorimetry. This system was applied to engineer an immunostimulatory Anticalin that binds and blocks the extracellular region of human CTLA4 to achieve a slower dissociation rate. A combinatorial library of the original Anticalin was generated by error-prone PCR, subjected to E. coli cell surface display, and applied to repeated cycles of cell sorting after incubation with the fluorescently labelled target protein under competition with the unlabelled extracellular domain of CTLA-4. The resulting Anticalin variants, which were expressed and purified as soluble proteins, showed more than eightfold decelerated target dissociation, as revealed by real time surface plasmon resonance analysis. Hence, the EspP autotransporter-mediated E. co/i surface display in combination with high-throughput fluorescence-activated cell sorting (FACS) provides an efficient strategy to select for Anticalins, and possibly other small protein scaffolds, with improved binding properties, which is particularly useful for in vitro affinity maturation but may also serve for the selection of novel target specificity from naive libraries. (C) 2010 Elsevier Ltd. All rights reserved.