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

Authors :
Liebhoff AM
Venkataraman T
Morgenlander WR
Na M
Kula T
Waugh K
Morrison C
Rewers M
Longman R
Round J
Elledge S
Ruczinski I
Langmead B
Larman HB
Source :
Nature communications [Nat Commun] 2024 Feb 21; Vol. 15 (1), pp. 1577. Date of Electronic Publication: 2024 Feb 21.
Publication Year :
2024

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.<br /> (© 2024. The Author(s).)

Details

Language :
English
ISSN :
2041-1723
Volume :
15
Issue :
1
Database :
MEDLINE
Journal :
Nature communications
Publication Type :
Academic Journal
Accession number :
38383452
Full Text :
https://doi.org/10.1038/s41467-024-45601-8