Publications
Nature communicationsFeb 2024 |
15
(
1
),
1577
DOI:
10.1038/s41467-024-45601-8

Efficient encoding of large antigenic spaces by epitope prioritization with Dolphyn

Liebhoff, Anna-Maria; Venkataraman, Thiagarajan; Morgenlander, William R; Na, Miso; Kula, Tomasz; Waugh, Kathleen; Morrison, Charles; Rewers, Marian; Longman, Randy; Round, June; Elledge, Stephen; Ruczinski, Ingo; Langmead, Ben; Larman, H Benjamin
Product Used
Variant Libraries
Abstract
We investigate a relatively underexplored component of the gut-immune axis by profiling the antibody response to gut phages using Phage Immunoprecipitation Sequencing (PhIP-Seq). To cover large antigenic spaces, we develop Dolphyn, a method that uses machine learning to select peptides from protein sets and compresses the proteome through epitope-stitching. Dolphyn compresses the size of a peptide library by 78% compared to traditional tiling, increasing the antibody-reactive peptides from 10% to 31%. We find that the immune system develops antibodies to human gut bacteria-infecting viruses, particularly E.coli-infecting Myoviridae. Cost-effective PhIP-Seq libraries designed with Dolphyn enable the assessment of a wider range of proteins in a single experiment, thus facilitating the study of the gut-immune axis.
Product Used
Variant Libraries

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