Efficient encoding of large antigenic spaces by epitope prioritization with Dolphyn

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...
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Autor*in:	Anna-Maria Liebhoff [verfasserIn] Thiagarajan Venkataraman [verfasserIn] William R. Morgenlander [verfasserIn] Miso Na [verfasserIn] Tomasz Kula [verfasserIn] Kathleen Waugh [verfasserIn] Charles Morrison [verfasserIn] Marian Rewers [verfasserIn] Randy Longman [verfasserIn] June Round [verfasserIn] Stephen Elledge [verfasserIn] Ingo Ruczinski [verfasserIn] Ben Langmead [verfasserIn] H. Benjamin Larman [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2024

Übergeordnetes Werk:	In: Nature Communications - Nature Portfolio, 2016, 15(2024), 1, Seite 12
Übergeordnetes Werk:	volume:15 ; year:2024 ; number:1 ; pages:12

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1038/s41467-024-45601-8

Katalog-ID:	DOAJ091180554

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allfields	10.1038/s41467-024-45601-8 doi (DE-627)DOAJ091180554 (DE-599)DOAJf671256a5dbb468ba920e54a8c3dd8ac DE-627 ger DE-627 rakwb eng Anna-Maria Liebhoff verfasserin aut Efficient encoding of large antigenic spaces by epitope prioritization with Dolphyn 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Science Q Thiagarajan Venkataraman verfasserin aut William R. Morgenlander verfasserin aut Miso Na verfasserin aut Tomasz Kula verfasserin aut Kathleen Waugh verfasserin aut Charles Morrison verfasserin aut Marian Rewers verfasserin aut Randy Longman verfasserin aut June Round verfasserin aut Stephen Elledge verfasserin aut Ingo Ruczinski verfasserin aut Ben Langmead verfasserin aut H. Benjamin Larman verfasserin aut In Nature Communications Nature Portfolio, 2016 15(2024), 1, Seite 12 (DE-627)626457688 (DE-600)2553671-0 20411723 nnns volume:15 year:2024 number:1 pages:12 https://doi.org/10.1038/s41467-024-45601-8 kostenfrei https://doaj.org/article/f671256a5dbb468ba920e54a8c3dd8ac kostenfrei https://doi.org/10.1038/s41467-024-45601-8 kostenfrei https://doaj.org/toc/2041-1723 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_211 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2110 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2024 1 12
spelling	10.1038/s41467-024-45601-8 doi (DE-627)DOAJ091180554 (DE-599)DOAJf671256a5dbb468ba920e54a8c3dd8ac DE-627 ger DE-627 rakwb eng Anna-Maria Liebhoff verfasserin aut Efficient encoding of large antigenic spaces by epitope prioritization with Dolphyn 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Science Q Thiagarajan Venkataraman verfasserin aut William R. Morgenlander verfasserin aut Miso Na verfasserin aut Tomasz Kula verfasserin aut Kathleen Waugh verfasserin aut Charles Morrison verfasserin aut Marian Rewers verfasserin aut Randy Longman verfasserin aut June Round verfasserin aut Stephen Elledge verfasserin aut Ingo Ruczinski verfasserin aut Ben Langmead verfasserin aut H. Benjamin Larman verfasserin aut In Nature Communications Nature Portfolio, 2016 15(2024), 1, Seite 12 (DE-627)626457688 (DE-600)2553671-0 20411723 nnns volume:15 year:2024 number:1 pages:12 https://doi.org/10.1038/s41467-024-45601-8 kostenfrei https://doaj.org/article/f671256a5dbb468ba920e54a8c3dd8ac kostenfrei https://doi.org/10.1038/s41467-024-45601-8 kostenfrei https://doaj.org/toc/2041-1723 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_211 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2110 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2024 1 12
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authorswithroles_txt_mv	Anna-Maria Liebhoff @@aut@@ Thiagarajan Venkataraman @@aut@@ William R. Morgenlander @@aut@@ Miso Na @@aut@@ Tomasz Kula @@aut@@ Kathleen Waugh @@aut@@ Charles Morrison @@aut@@ Marian Rewers @@aut@@ Randy Longman @@aut@@ June Round @@aut@@ Stephen Elledge @@aut@@ Ingo Ruczinski @@aut@@ Ben Langmead @@aut@@ H. Benjamin Larman @@aut@@
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author	Anna-Maria Liebhoff
spellingShingle	Anna-Maria Liebhoff misc Science misc Q Efficient encoding of large antigenic spaces by epitope prioritization with Dolphyn
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topic_title	Efficient encoding of large antigenic spaces by epitope prioritization with Dolphyn
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title	Efficient encoding of large antigenic spaces by epitope prioritization with Dolphyn
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title_sort	efficient encoding of large antigenic spaces by epitope prioritization with dolphyn
title_auth	Efficient encoding of large antigenic spaces by epitope prioritization with Dolphyn
abstract	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.
abstractGer	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.
abstract_unstemmed	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.
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title_short	Efficient encoding of large antigenic spaces by epitope prioritization with Dolphyn
url	https://doi.org/10.1038/s41467-024-45601-8 https://doaj.org/article/f671256a5dbb468ba920e54a8c3dd8ac https://doaj.org/toc/2041-1723
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