TY - JOUR
T1 - Impact of infection on proteome-wide glycosylation revealed by distinct signatures for bacterial and viral pathogens
AU - Willems, Esther
AU - Gloerich, Jolein
AU - Suppers, Anouk
AU - van der Flier, Michiel
AU - van den Heuvel, Lambert P.
AU - van de Kar, Nicole
AU - Philipsen, Ria H.L.A.
AU - van Dael, Maurice
AU - Kaforou, Myrsini
AU - Wright, Victoria J.
AU - Herberg, Jethro A.
AU - Torres, Federico Martinon
AU - Levin, Michael
AU - de Groot, Ronald
AU - van Gool, Alain J.
AU - Lefeber, Dirk J.
AU - Wessels, Hans J.C.T.
AU - de Jonge, Marien I.
AU - PERFORM consortium
A2 - Zavadska, Dace
A2 - Balode, Anda
A2 - Bārzdiņa, Arta
A2 - Gardovska, Dace
A2 - Grāvele, Dagne
A2 - Grope, Ilze
A2 - Meiere, Anija
A2 - Nokalna, Ieva
A2 - Urbāne, Urzula Nora
A2 - Pavāre, Jana
A2 - Pučuka, Zanda
A2 - Deksne, Dārta
A2 - Selecka, Katrina
A2 - Sidorova, Aleksandra
N1 - Funding Information:
This research, part of the PERFORM project, has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 668303 . The samples collected previously were funded by: the European Seventh Framework Programme for Research and Technological Development ( FP7 ) under EUCLIDS Grant Agreement No. 279185 .
Funding Information:
This research, part of the PERFORM project, has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 668303. The samples collected previously were funded by: the European Seventh Framework Programme for Research and Technological Development (FP7) under EUCLIDS Grant Agreement No. 279185. We would like to thank all the patients and the healthy controls for donating their blood for the EUCLIDS, IRIS, and Westra studies. We would like to thank the Radboud Consortium for Glycoscience for their advice for data interpretation. We also thank the PERFORM consortium (see supplemental material for all participants) for their collaboration and fruitful discussions. Conceptualization, E.W. H.W. and M.J.; Methodology, E.W. M.D. H.W. and M.J.; Investigation, E.W.; Software, A.S. and H.W.; Formal Analysis, E.W. and H.W.; Visualization, E.W. and H.W.; Resources, M.F. L.H. N.K. R.P. M.K. V.W. J.H. and F.M.; Writing – Original Draft, E.W. and M.J.; Writing – Review & Editing, E.W. J.G. A.S. M.F. L.H. N.K. R.P. M.D. M.K. V.W. J.H. F.M. M.L. R.G. A.G. D.L. H.W. and M.J.; Funding Acquisition, M.J. R.G. and M.L.; Supervision, H.W. D.L. and M.J. The authors declare no competing interests. We support inclusive, diverse, and equitable conduct of research.
Publisher Copyright:
© 2023 The Author(s)
PY - 2023/8/18
Y1 - 2023/8/18
N2 - Mechanisms of infection and pathogenesis have predominantly been studied based on differential gene or protein expression. Less is known about posttranslational modifications, which are essential for protein functional diversity. We applied an innovative glycoproteomics method to study the systemic proteome-wide glycosylation in response to infection. The protein site-specific glycosylation was characterized in plasma derived from well-defined controls and patients. We found 3862 unique features, of which we identified 463 distinct intact glycopeptides, that could be mapped to more than 30 different proteins. Statistical analyses were used to derive a glycopeptide signature that enabled significant differentiation between patients with a bacterial or viral infection. Furthermore, supported by a machine learning algorithm, we demonstrated the ability to identify the causative pathogens based on the distinctive host blood plasma glycopeptide signatures. These results illustrate that glycoproteomics holds enormous potential as an innovative approach to improve the interpretation of relevant biological changes in response to infection.
AB - Mechanisms of infection and pathogenesis have predominantly been studied based on differential gene or protein expression. Less is known about posttranslational modifications, which are essential for protein functional diversity. We applied an innovative glycoproteomics method to study the systemic proteome-wide glycosylation in response to infection. The protein site-specific glycosylation was characterized in plasma derived from well-defined controls and patients. We found 3862 unique features, of which we identified 463 distinct intact glycopeptides, that could be mapped to more than 30 different proteins. Statistical analyses were used to derive a glycopeptide signature that enabled significant differentiation between patients with a bacterial or viral infection. Furthermore, supported by a machine learning algorithm, we demonstrated the ability to identify the causative pathogens based on the distinctive host blood plasma glycopeptide signatures. These results illustrate that glycoproteomics holds enormous potential as an innovative approach to improve the interpretation of relevant biological changes in response to infection.
KW - Glycobiology
KW - Glycomics
KW - Health sciences
KW - Immunology
UR - http://www.scopus.com/inward/record.url?scp=85165028111&partnerID=8YFLogxK
UR - https://ars.els-cdn.com/content/image/1-s2.0-S2589004223013342-mmc2.pdf
U2 - 10.1016/j.isci.2023.107257
DO - 10.1016/j.isci.2023.107257
M3 - Article
AN - SCOPUS:85165028111
SN - 2589-0042
VL - 26
JO - iScience
JF - iScience
IS - 8
M1 - 107257
ER -