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High-throughput sequencing enhanced phage display enables the identification of patient-specific epitope motifs in serum.


ABSTRACT: 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.

SUBMITTER: Christiansen A 

PROVIDER: S-EPMC4650709 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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High-throughput sequencing enhanced phage display enables the identification of patient-specific epitope motifs in serum.

Christiansen Anders A   Kringelum Jens V JV   Hansen Christian S CS   Bøgh Katrine L KL   Sullivan Eric E   Patel Jigar J   Rigby Neil M NM   Eiwegger Thomas T   Szépfalusi Zsolt Z   de Masi Federico F   Nielsen Morten M   Lund Ole O   Dufva Martin M  

Scientific reports 20150806


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  ...[more]

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