Generation and analyses of human synthetic antibody libraries and their application for protein microarrays

Abstract Antibody-based proteomics offers distinct advantages in the analysis of complex samples for discovery and validation of biomarkers associated with disease. However, its large-scale implementation requires tools and technologies that allow development of suitable antibody or antibody fragmen...

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Veröffentlicht in:Protein engineering, design and selection design and selection, 2016-10, Vol.29 (10), p.427-437
Hauptverfasser: Säll, Anna, Walle, Maria, Wingren, Christer, Müller, Susanne, Nyman, Tomas, Vala, Andrea, Ohlin, Mats, Borrebaeck, Carl A. K., Persson, Helena
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Sprache:eng
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Zusammenfassung:Abstract Antibody-based proteomics offers distinct advantages in the analysis of complex samples for discovery and validation of biomarkers associated with disease. However, its large-scale implementation requires tools and technologies that allow development of suitable antibody or antibody fragments in a high-throughput manner. To address this we designed and constructed two human synthetic antibody fragment (scFv) libraries denoted HelL-11 and HelL-13. By the use of phage display technology, in total 466 unique scFv antibodies specific for 114 different antigens were generated. The specificities of these antibodies were analyzed in a variety of immunochemical assays and a subset was further evaluated for functionality in protein microarray applications. This high-throughput approach demonstrates the ability to rapidly generate a wealth of reagents not only for proteome research, but potentially also for diagnostics and therapeutics. In addition, this work provides a great example on how a synthetic approach can be used to optimize library designs. By having precise control of the diversity introduced into the antigen-binding sites, synthetic libraries offer increased understanding of how different diversity contributes to antibody binding reactivity and stability, thereby providing the key to future library optimization.
ISSN:1741-0126
1741-0134
1741-0134
DOI:10.1093/protein/gzw042