Cargando…
Longitudinal serum proteomics analyses identify unique and overlapping host response pathways in Lyme disease and West Nile virus infection
Advancement in proteomics methods for interrogating biological samples has helped identify disease biomarkers for early diagnostics and unravel underlying molecular mechanisms of disease. Herein, we examined the serum proteomes of 23 study participants presenting with one of two common arthropod-bor...
Autores principales: | , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9784464/ https://www.ncbi.nlm.nih.gov/pubmed/36569838 http://dx.doi.org/10.3389/fimmu.2022.1012824 |
_version_ | 1784857818143129600 |
---|---|
author | Boada, Patrick Fatou, Benoit Belperron, Alexia A. Sigdel, Tara K. Smolen, Kinga K. Wurie, Zainab Levy, Ofer Ronca, Shannon E. Murray, Kristy O. Liberto, Juliane M. Rashmi, Priyanka Kerwin, Maggie Montgomery, Ruth R. Bockenstedt, Linda K. Steen, Hanno Sarwal, Minnie M. |
author_facet | Boada, Patrick Fatou, Benoit Belperron, Alexia A. Sigdel, Tara K. Smolen, Kinga K. Wurie, Zainab Levy, Ofer Ronca, Shannon E. Murray, Kristy O. Liberto, Juliane M. Rashmi, Priyanka Kerwin, Maggie Montgomery, Ruth R. Bockenstedt, Linda K. Steen, Hanno Sarwal, Minnie M. |
author_sort | Boada, Patrick |
collection | PubMed |
description | Advancement in proteomics methods for interrogating biological samples has helped identify disease biomarkers for early diagnostics and unravel underlying molecular mechanisms of disease. Herein, we examined the serum proteomes of 23 study participants presenting with one of two common arthropod-borne infections: Lyme disease (LD), an extracellular bacterial infection or West Nile virus infection (WNV), an intracellular viral infection. The LC/MS based serum proteomes of samples collected at the time of diagnosis and during convalescence were assessed using a depletion-based high-throughput shotgun proteomics (dHSP) pipeline as well as a non-depleting blotting-based low-throughput platform (MStern). The LC/MS integrated analyses identified host proteome responses in the acute and recovery phases shared by LD and WNV infections, as well as differentially abundant proteins that were unique to each infection. Notably, we also detected proteins that distinguished localized from disseminated LD and asymptomatic from symptomatic WNV infection. The proteins detected in both diseases with the dHSP pipeline identified unique and overlapping proteins detected with the non-depleting MStern platform, supporting the utility of both detection methods. Machine learning confirmed the use of the serum proteome to distinguish the infection from healthy control sera but could not develop discriminatory models between LD and WNV at current sample numbers. Our study is the first to compare the serum proteomes in two arthropod-borne infections and highlights the similarities in host responses even though the pathogens and the vectors themselves are different. |
format | Online Article Text |
id | pubmed-9784464 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97844642022-12-24 Longitudinal serum proteomics analyses identify unique and overlapping host response pathways in Lyme disease and West Nile virus infection Boada, Patrick Fatou, Benoit Belperron, Alexia A. Sigdel, Tara K. Smolen, Kinga K. Wurie, Zainab Levy, Ofer Ronca, Shannon E. Murray, Kristy O. Liberto, Juliane M. Rashmi, Priyanka Kerwin, Maggie Montgomery, Ruth R. Bockenstedt, Linda K. Steen, Hanno Sarwal, Minnie M. Front Immunol Immunology Advancement in proteomics methods for interrogating biological samples has helped identify disease biomarkers for early diagnostics and unravel underlying molecular mechanisms of disease. Herein, we examined the serum proteomes of 23 study participants presenting with one of two common arthropod-borne infections: Lyme disease (LD), an extracellular bacterial infection or West Nile virus infection (WNV), an intracellular viral infection. The LC/MS based serum proteomes of samples collected at the time of diagnosis and during convalescence were assessed using a depletion-based high-throughput shotgun proteomics (dHSP) pipeline as well as a non-depleting blotting-based low-throughput platform (MStern). The LC/MS integrated analyses identified host proteome responses in the acute and recovery phases shared by LD and WNV infections, as well as differentially abundant proteins that were unique to each infection. Notably, we also detected proteins that distinguished localized from disseminated LD and asymptomatic from symptomatic WNV infection. The proteins detected in both diseases with the dHSP pipeline identified unique and overlapping proteins detected with the non-depleting MStern platform, supporting the utility of both detection methods. Machine learning confirmed the use of the serum proteome to distinguish the infection from healthy control sera but could not develop discriminatory models between LD and WNV at current sample numbers. Our study is the first to compare the serum proteomes in two arthropod-borne infections and highlights the similarities in host responses even though the pathogens and the vectors themselves are different. Frontiers Media S.A. 2022-12-09 /pmc/articles/PMC9784464/ /pubmed/36569838 http://dx.doi.org/10.3389/fimmu.2022.1012824 Text en Copyright © 2022 Boada, Fatou, Belperron, Sigdel, Smolen, Wurie, Levy, Ronca, Murray, Liberto, Rashmi, Kerwin, Montgomery, Bockenstedt, Steen and Sarwal https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Boada, Patrick Fatou, Benoit Belperron, Alexia A. Sigdel, Tara K. Smolen, Kinga K. Wurie, Zainab Levy, Ofer Ronca, Shannon E. Murray, Kristy O. Liberto, Juliane M. Rashmi, Priyanka Kerwin, Maggie Montgomery, Ruth R. Bockenstedt, Linda K. Steen, Hanno Sarwal, Minnie M. Longitudinal serum proteomics analyses identify unique and overlapping host response pathways in Lyme disease and West Nile virus infection |
title | Longitudinal serum proteomics analyses identify unique and overlapping host response pathways in Lyme disease and West Nile virus infection |
title_full | Longitudinal serum proteomics analyses identify unique and overlapping host response pathways in Lyme disease and West Nile virus infection |
title_fullStr | Longitudinal serum proteomics analyses identify unique and overlapping host response pathways in Lyme disease and West Nile virus infection |
title_full_unstemmed | Longitudinal serum proteomics analyses identify unique and overlapping host response pathways in Lyme disease and West Nile virus infection |
title_short | Longitudinal serum proteomics analyses identify unique and overlapping host response pathways in Lyme disease and West Nile virus infection |
title_sort | longitudinal serum proteomics analyses identify unique and overlapping host response pathways in lyme disease and west nile virus infection |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9784464/ https://www.ncbi.nlm.nih.gov/pubmed/36569838 http://dx.doi.org/10.3389/fimmu.2022.1012824 |
work_keys_str_mv | AT boadapatrick longitudinalserumproteomicsanalysesidentifyuniqueandoverlappinghostresponsepathwaysinlymediseaseandwestnilevirusinfection AT fatoubenoit longitudinalserumproteomicsanalysesidentifyuniqueandoverlappinghostresponsepathwaysinlymediseaseandwestnilevirusinfection AT belperronalexiaa longitudinalserumproteomicsanalysesidentifyuniqueandoverlappinghostresponsepathwaysinlymediseaseandwestnilevirusinfection AT sigdeltarak longitudinalserumproteomicsanalysesidentifyuniqueandoverlappinghostresponsepathwaysinlymediseaseandwestnilevirusinfection AT smolenkingak longitudinalserumproteomicsanalysesidentifyuniqueandoverlappinghostresponsepathwaysinlymediseaseandwestnilevirusinfection AT wuriezainab longitudinalserumproteomicsanalysesidentifyuniqueandoverlappinghostresponsepathwaysinlymediseaseandwestnilevirusinfection AT levyofer longitudinalserumproteomicsanalysesidentifyuniqueandoverlappinghostresponsepathwaysinlymediseaseandwestnilevirusinfection AT roncashannone longitudinalserumproteomicsanalysesidentifyuniqueandoverlappinghostresponsepathwaysinlymediseaseandwestnilevirusinfection AT murraykristyo longitudinalserumproteomicsanalysesidentifyuniqueandoverlappinghostresponsepathwaysinlymediseaseandwestnilevirusinfection AT libertojulianem longitudinalserumproteomicsanalysesidentifyuniqueandoverlappinghostresponsepathwaysinlymediseaseandwestnilevirusinfection AT rashmipriyanka longitudinalserumproteomicsanalysesidentifyuniqueandoverlappinghostresponsepathwaysinlymediseaseandwestnilevirusinfection AT kerwinmaggie longitudinalserumproteomicsanalysesidentifyuniqueandoverlappinghostresponsepathwaysinlymediseaseandwestnilevirusinfection AT montgomeryruthr longitudinalserumproteomicsanalysesidentifyuniqueandoverlappinghostresponsepathwaysinlymediseaseandwestnilevirusinfection AT bockenstedtlindak longitudinalserumproteomicsanalysesidentifyuniqueandoverlappinghostresponsepathwaysinlymediseaseandwestnilevirusinfection AT steenhanno longitudinalserumproteomicsanalysesidentifyuniqueandoverlappinghostresponsepathwaysinlymediseaseandwestnilevirusinfection AT sarwalminniem longitudinalserumproteomicsanalysesidentifyuniqueandoverlappinghostresponsepathwaysinlymediseaseandwestnilevirusinfection |