Journal article
High-throughput sequencing enhanced phage display enables the identification of patient-specific epitope motifs in serum
Department of Micro- and Nanotechnology, Technical University of Denmark1
Fluidic Array Systems and Technology, Department of Micro- and Nanotechnology, Technical University of Denmark2
Department of Systems Biology, Technical University of Denmark3
Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark4
National Food Institute, Technical University of Denmark5
Roche NimbleGen, Inc.6
Quadram Institute7
Medical University of Vienna8
Regulatory Genomics, Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark9
Phage display is a prominent screening technique with a multitude of applications including therapeutic antibody development and mapping of antigen epitopes. In this study, phages were selected based on their interaction with patient serum and exhaustively characterised by high-throughput sequencing.
A bioinformatics approach was developed in order to identify peptide motifs of interest based on clustering and contrasting to control samples. Comparison of patient and control samples confirmed a major issue in phage display, namely the selection of unspecific peptides. The potential of the bioinformatic approach was demonstrated by identifying epitopes of a prominent peanut allergen, Ara h 1, in sera from patients with severe peanut allergy.
The identified epitopes were confirmed by high-density peptide micro-arrays. The present study demonstrates that high-throughput sequencing can empower phage display by (i) enabling the analysis of complex biological samples, (ii) circumventing the traditional laborious picking and functional testing of individual phage clones and (iii) reducing the number of selection rounds.
Language: | English |
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Publisher: | Nature Publishing Group |
Year: | 2015 |
Pages: | 12913 |
ISSN: | 20452322 |
Types: | Journal article |
DOI: | 10.1038/srep12913 |
ORCIDs: | Bøgh, Katrine Lindholm , De Masi, Federico , Nielsen, Morten , Lund, Ole and Dufva, Martin |