Development of a novel mammalian display system for selection of antibodies against membrane proteins

摘要

Reliable, specific polyclonal and monoclonal antibodies are important tools in research and medicine. However, the discovery of antibodies against their targets in their native forms is difficult. Here, we present a novel method for discovery of antibodies against membrane proteins in their native configuration in mammalian cells. The method involves the co-expression of an antibody library in a population of mammalian cells that express the target polypeptide within a natural membrane environment on the cell surface. Cells that secrete a single-chain fragment variable (scFv) that binds to the target membrane protein thereby become self-labeled, enabling enrichment and isolation by magnetic sorting and FRET-based flow sorting. Library sizes of up to 109 variants can be screened, thus allowing campaigns of naïve scFv libraries to be selected against membrane protein antigens in a Chinese hamster ovary cell system. We validate this method by screening a synthetic naïve human scFv library against Chinese hamster ovary cells expressing the oncogenic target epithelial cell adhesion molecule and identify a panel of three novel binders to this membrane protein, one with a dissociation constant (KD) as low as 0.8 nm. We further demonstrate that the identified antibodies have utility for killing epithelial cell adhesion molecule–positive cells when used as a targeting domain on chimeric antigen receptor T cells. Thus, we provide a new tool for identifying novel antibodies that act against membrane proteins, which could catalyze the discovery of new candidates for antibody-based therapies. Reliable, specific polyclonal and monoclonal antibodies are important tools in research and medicine. However, the discovery of antibodies against their targets in their native forms is difficult. Here, we present a novel method for discovery of antibodies against membrane proteins in their native configuration in mammalian cells. The method involves the co-expression of an antibody library in a population of mammalian cells that express the target polypeptide within a natural membrane environment on the cell surface. Cells that secrete a single-chain fragment variable (scFv) that binds to the target membrane protein thereby become self-labeled, enabling enrichment and isolation by magnetic sorting and FRET-based flow sorting. Library sizes of up to 109 variants can be screened, thus allowing campaigns of naïve scFv libraries to be selected against membrane protein antigens in a Chinese hamster ovary cell system. We validate this method by screening a synthetic naïve human scFv library against Chinese hamster ovary cells expressing the oncogenic target epithelial cell adhesion molecule and identify a panel of three novel binders to this membrane protein, one with a dissociation constant (KD) as low as 0.8 nm. We further demonstrate that the identified antibodies have utility for killing epithelial cell adhesion molecule–positive cells when used as a targeting domain on chimeric antigen receptor T cells. Thus, we provide a new tool for identifying novel antibodies that act against membrane proteins, which could catalyze the discovery of new candidates for antibody-based therapies. Mammalian display was originally conceived for affinity maturation of single-chain variable fragments (scFv) expressed on the surface of human cells (1Ho M. Nagata S. Pastan I. Isolation of anti-CD22 Fv with high affinity by Fv display on human cells.Proc. Natl. Acad. Sci. U.S.A. 2006; 103 (16763048): 9637-964210.1073/pnas.0603653103Crossref PubMed Scopus (133) Google Scholar) and has been further developed for screening full-length antibody cell surface–expressed libraries (2Akamatsu Y. Pakabunto K. Xu Z. Zhang Y. Tsurushita N. Whole IgG surface display on mammalian cells: application to isolation of neutralizing chicken monoclonal anti-IL-12 antibodies.J. Immunol. Methods. 2007; 327 (17719061): 40-5210.1016/j.jim.2007.07.007Crossref PubMed Scopus (54) Google Scholar, 3Zhou