Antibody Industrial Symposium 2019
NGS instead of Sanger sequencing for deep mining of antibody repertoires.
Deep mining of protein diversity is becoming increasingly useful for selecting the best candidate as therapeutic biologics. In the case of antibodies, hit discovery relies on natural, immune or synthetic repertoires out of which antibody hits are selected either by phage, yeast or mammalian cell display or using B-cell sorting. In such work-flows, there are steps where clones of interest need to be isolated to determine their individual sequences. To optimize the benefit of using repertoires of such high diversity, it would be advantageous to sequence hundreds to thousands of clones, but this is usually time and cost consuming, which often limits the effort to a few tens of sequences.
In this work, we suggest a new and general method to sequence a diversity of antibody chains, and even more generally, a diversity of DNA constructs. We applied it to 1920 clones, previously isolated and stored in 96 well plates: a single NGS run allowed us to determine each sequence in a fast, reliable and cost-effective way. The bioinformatics pipeline to analyze all the data takes only a few minutes and is embedded into Yumatix, our all-in-one software for protein science teams.
As a conclusion, we think employing the method described here to antibody generation or antibody maturation projects will enable a deeper screening, resulting in a greater quality of the therapeutic candidates. When applied to antibody projects in the field of immunomodulation, it may ultimately result in a benefit for Immunotherapy patients.