Peptide phage display using random peptide genes has been applied with limited success over almost 25 years without any substantial changes in the way epitopes are identified. Epitope mapping usually results in a set of a few sequences sharing similar or identical residues with the target. New methods in gene synthesis based on trinucleotide synthesis, high throughput sequencing by next generation sequencing (NGS), availability of computational methods and increased computing power have led to substantial improvements. The general limitations of phage display approaches with respect to the clonal stability, library complexity and reproducibility have, however, remained. The high error rate of NGS creates additional problems in the reliability of counting individual sequences.
- Quality from knowledge
- Resolution of epitopes at the amino acid level
- New ways to understand epitope variability
- Superior to mapping with synthetic peptides
- EPITOPIC’s Service requires µg quantities
To overcome these limitations, EPITOPIC uses an optimized trinucleotide synthesis-based library with high complexity in a reliable phagemid system. Instead of epitope data obtained from the alignment of a limited number of full length sequences, this approach allows the statistical analysis of short peptide motifs’ frequencies in NGS data sets to obtain very detailed information about epitopes and their variations accepted by antibodies based on many thousands or more different sequences, often after a single round of selection.
The results of EPITOPIC’s epitope mapping are best visualized as a graphic displaying the enrichment of each tetramer peptide in the antigen sequence in the data set of selected sequences. The following example is from the mapping of an antibody binding the repetitive motif of the tumor marker protein Mucin-1 (CD227, BD Pharmingen™ Cat. No. 550486, Clone HMPV). Due to the high stability of the library and even amino acid composition, one can easily identify those motifs that have been enriched. Unlike peptide arrays this allows the precise localisation of the antibody’s epitope and the data can be used further to visualize allowed sequence variations by epitope fingerprinting. (Data with permission from Fraunhofer IZI, Leipzig)
Alignments for CD227 mAb recognizing the Mucin-1 PDTRP motif. Variance of the central amino acid in all sequences containing PDxRP. Already the first selection round (left) generates enough data to generate a complete fingerprint.
A complete report for this antibody is available here.
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