Efficient encoding of large antigenic spaces by epitope prioritization with Dolphyn.

TitleEfficient encoding of large antigenic spaces by epitope prioritization with Dolphyn.
Publication TypeJournal Article
Year of Publication2023
AuthorsLiebhoff, A-M, Venkataraman, T, Morgenlander, WR, Na, M, Kula, T, Waugh, K, Morrison, C, Rewers, M, Longman, R, Round, J, Elledge, S, Ruczinski, I, Langmead, B, H Larman, B
JournalbioRxiv
Date Published2023 Jul 31
Abstract

We investigated a relatively underexplored component of the gut-immune axis by profiling the antibody response to gut phages using Phage Immunoprecipitation Sequencing (PhIP-Seq). To enhance this approach, we developed Dolphyn, a novel method that uses machine learning to select peptides from protein sets and compresses the proteome through epitope-stitching. Dolphyn improves the fraction of gut phage library peptides bound by antibodies from 10% to 31% in healthy individuals, while also reducing the number of synthesized peptides by 78%. In our study on gut phages, we discovered that the immune system develops antibodies to bacteria-infecting viruses in the human gut, 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.

DOI10.1101/2023.07.30.551179
Alternate JournalbioRxiv
PubMed ID37577562
PubMed Central IDPMC10418057
Grant ListR01 GM136724 / GM / NIGMS NIH HHS / United States
R37 DK032493 / DK / NIDDK NIH HHS / United States
P30 DK116073 / DK / NIDDK NIH HHS / United States
R35 GM139602 / GM / NIGMS NIH HHS / United States
R01 DK032493 / DK / NIDDK NIH HHS / United States