A model system for optimising the selection of membrane antigen-specific human antibodies on intact cells using phage antibody display technology
The functional expression of human antibody fragments on the surface of filamentous bacteriophage, and selection of phage antibodies (PhAbs) with antigens, has provided a powerful tool for generating novel antibodies. Applications of phage antibody display technology have increased over the past dec...
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Veröffentlicht in: | Journal of immunological methods 2002-04, Vol.262 (1), p.191-204 |
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Sprache: | eng |
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Zusammenfassung: | The functional expression of human antibody fragments on the surface of filamentous bacteriophage, and selection of phage antibodies (PhAbs) with antigens, has provided a powerful tool for generating novel antibodies. Applications of phage antibody display technology have increased over the past decade. Successful isolation of phage antibodies has been reported mostly using purified antigens. Isolation has proven to be more complicated with complex mixtures of antigens, such as intact cells. A given cell type contains thousands of different epitopes, each capable in theory of binding phage antibodies. Often antigens are not known or cannot be purified without disrupting their conformational integrity. To overcome problems involving phage antibody selections on intact cells, we have developed an experimental model system that allows for optimisation and comparison of various selection strategies. The model system comprises labelling of intact cells with the fluorescently labelled phospholipid fluorescein-DHPE. Upon incubation, this phospholipid is readily incorporated in the membrane of any cell type. Labelling intensity is regulated by varying the phospholipid concentration. After optimisation of key steps in the selection procedure, we were able to isolate fluorescein-DHPE specific phage from a synthetic library using intact cells. This model system can be applied to any cell type and we demonstrate that it can be used to efficiently compare and optimise selection strategies. |
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ISSN: | 0022-1759 1872-7905 |
DOI: | 10.1016/S0022-1759(02)00005-4 |