Ultra-High-Throughput Clinical Proteomics Reveals Classifiers of COVID-19 Infection

Christoph B. Messner; Vadim Demichev; Daniel Wendisch; Laura Michalick; Matthew White; Anja Freiwald; Kathrin Textoris-Taube; Spyros I. Vernardis; Anna Sophia Egger; Marco Kreidl; Daniela Ludwig; Christiane Kilian; Federica Agostini; Aleksej Zelezniak; Charlotte Thibeault; Moritz Pfeiffer; Stefan Hippenstiel; Andreas Hocke; Christof von Kalle; Archie Campbell; Caroline Hayward; David J. Porteous; Riccardo E. Marioni; Claudia Langenberg; Kathryn S. Lilley; Wolfgang M. Kuebler; Michael Mülleder; Christian Drosten; Norbert Suttorp; Martin Witzenrath; Florian Kurth; Leif Erik Sander; Markus Ralser

doi:10.1016/j.cels.2020.05.012

Ultra-High-Throughput Clinical Proteomics Reveals Classifiers of COVID-19 Infection

Christoph B. Messner, Vadim Demichev, Daniel Wendisch, Laura Michalick, Matthew White, Anja Freiwald, Kathrin Textoris-Taube, Spyros I. Vernardis, Anna Sophia Egger, Marco Kreidl, Daniela Ludwig, Christiane Kilian, Federica Agostini, Aleksej Zelezniak, Charlotte Thibeault, Moritz Pfeiffer, Stefan Hippenstiel, Andreas Hocke, Christof von Kalle, Archie CampbellCaroline Hayward, David J. Porteous, Riccardo E. Marioni, Claudia Langenberg, Kathryn S. Lilley, Wolfgang M. Kuebler, Michael Mülleder, Christian Drosten, Norbert Suttorp, Martin Witzenrath, Florian Kurth, Leif Erik Sander, Markus Ralser^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Research › peer-review

405 Citations (Scopus)

Abstract

The COVID-19 pandemic is an unprecedented global challenge, and point-of-care diagnostic classifiers are urgently required. Here, we present a platform for ultra-high-throughput serum and plasma proteomics that builds on ISO13485 standardization to facilitate simple implementation in regulated clinical laboratories. Our low-cost workflow handles up to 180 samples per day, enables high precision quantification, and reduces batch effects for large-scale and longitudinal studies. We use our platform on samples collected from a cohort of early hospitalized cases of the SARS-CoV-2 pandemic and identify 27 potential biomarkers that are differentially expressed depending on the WHO severity grade of COVID-19. They include complement factors, the coagulation system, inflammation modulators, and pro-inflammatory factors upstream and downstream of interleukin 6. All protocols and software for implementing our approach are freely available. In total, this work supports the development of routine proteomic assays to aid clinical decision making and generate hypotheses about potential COVID-19 therapeutic targets.

Original language	English
Pages (from-to)	11-24.e4
Journal	Cell Systems
Volume	11
Issue number	1
DOIs	https://doi.org/10.1016/j.cels.2020.05.012
Publication status	Published - 22 Jul 2020
Externally published	Yes

Keywords

antiviral immune response
clinical classifiers
COVID-19 infection
high-throughput proteomics
mass spectrometry
SWATH-MS

Access to Document

10.1016/j.cels.2020.05.012

Cite this

Messner, C. B., Demichev, V., Wendisch, D., Michalick, L., White, M., Freiwald, A., Textoris-Taube, K., Vernardis, S. I., Egger, A. S., Kreidl, M., Ludwig, D., Kilian, C., Agostini, F., Zelezniak, A., Thibeault, C., Pfeiffer, M., Hippenstiel, S., Hocke, A., von Kalle, C., ... Ralser, M. (2020). Ultra-High-Throughput Clinical Proteomics Reveals Classifiers of COVID-19 Infection. Cell Systems, 11(1), 11-24.e4. https://doi.org/10.1016/j.cels.2020.05.012

@article{a83ca1630eaa48a0890e7d75991f61d2,

title = "Ultra-High-Throughput Clinical Proteomics Reveals Classifiers of COVID-19 Infection",

abstract = "The COVID-19 pandemic is an unprecedented global challenge, and point-of-care diagnostic classifiers are urgently required. Here, we present a platform for ultra-high-throughput serum and plasma proteomics that builds on ISO13485 standardization to facilitate simple implementation in regulated clinical laboratories. Our low-cost workflow handles up to 180 samples per day, enables high precision quantification, and reduces batch effects for large-scale and longitudinal studies. We use our platform on samples collected from a cohort of early hospitalized cases of the SARS-CoV-2 pandemic and identify 27 potential biomarkers that are differentially expressed depending on the WHO severity grade of COVID-19. They include complement factors, the coagulation system, inflammation modulators, and pro-inflammatory factors upstream and downstream of interleukin 6. All protocols and software for implementing our approach are freely available. In total, this work supports the development of routine proteomic assays to aid clinical decision making and generate hypotheses about potential COVID-19 therapeutic targets.",

keywords = "antiviral immune response, clinical classifiers, COVID-19 infection, high-throughput proteomics, mass spectrometry, SWATH-MS",

author = "Messner, {Christoph B.} and Vadim Demichev and Daniel Wendisch and Laura Michalick and Matthew White and Anja Freiwald and Kathrin Textoris-Taube and Vernardis, {Spyros I.} and Egger, {Anna Sophia} and Marco Kreidl and Daniela Ludwig and Christiane Kilian and Federica Agostini and Aleksej Zelezniak and Charlotte Thibeault and Moritz Pfeiffer and Stefan Hippenstiel and Andreas Hocke and {von Kalle}, Christof and Archie Campbell and Caroline Hayward and Porteous, {David J.} and Marioni, {Riccardo E.} and Claudia Langenberg and Lilley, {Kathryn S.} and Kuebler, {Wolfgang M.} and Michael M{\"u}lleder and Christian Drosten and Norbert Suttorp and Martin Witzenrath and Florian Kurth and Sander, {Leif Erik} and Markus Ralser",

note = "Publisher Copyright: {\textcopyright} 2020 The Authors",

year = "2020",

month = jul,

day = "22",

doi = "10.1016/j.cels.2020.05.012",

language = "English",

volume = "11",

pages = "11--24.e4",

journal = "Cell Systems",

issn = "2405-4712",

publisher = "Cell Press",

number = "1",

}

Messner, CB, Demichev, V, Wendisch, D, Michalick, L, White, M, Freiwald, A, Textoris-Taube, K, Vernardis, SI, Egger, AS, Kreidl, M, Ludwig, D, Kilian, C, Agostini, F, Zelezniak, A, Thibeault, C, Pfeiffer, M, Hippenstiel, S, Hocke, A, von Kalle, C, Campbell, A, Hayward, C, Porteous, DJ, Marioni, RE, Langenberg, C, Lilley, KS, Kuebler, WM, Mülleder, M, Drosten, C, Suttorp, N, Witzenrath, M, Kurth, F, Sander, LE & Ralser, M 2020, 'Ultra-High-Throughput Clinical Proteomics Reveals Classifiers of COVID-19 Infection', Cell Systems, vol. 11, no. 1, pp. 11-24.e4. https://doi.org/10.1016/j.cels.2020.05.012

TY - JOUR

T1 - Ultra-High-Throughput Clinical Proteomics Reveals Classifiers of COVID-19 Infection

AU - Messner, Christoph B.

AU - Demichev, Vadim

AU - Wendisch, Daniel

AU - Michalick, Laura

AU - White, Matthew

AU - Freiwald, Anja

AU - Textoris-Taube, Kathrin

AU - Vernardis, Spyros I.

AU - Egger, Anna Sophia

AU - Kreidl, Marco

AU - Ludwig, Daniela

AU - Kilian, Christiane

AU - Agostini, Federica

AU - Zelezniak, Aleksej

AU - Thibeault, Charlotte

AU - Pfeiffer, Moritz

AU - Hippenstiel, Stefan

AU - Hocke, Andreas

AU - von Kalle, Christof

AU - Campbell, Archie

AU - Hayward, Caroline

AU - Porteous, David J.

AU - Marioni, Riccardo E.

AU - Langenberg, Claudia

AU - Lilley, Kathryn S.

AU - Kuebler, Wolfgang M.

AU - Mülleder, Michael

AU - Drosten, Christian

AU - Suttorp, Norbert

AU - Witzenrath, Martin

AU - Kurth, Florian

AU - Sander, Leif Erik

AU - Ralser, Markus

PY - 2020/7/22

Y1 - 2020/7/22

N2 - The COVID-19 pandemic is an unprecedented global challenge, and point-of-care diagnostic classifiers are urgently required. Here, we present a platform for ultra-high-throughput serum and plasma proteomics that builds on ISO13485 standardization to facilitate simple implementation in regulated clinical laboratories. Our low-cost workflow handles up to 180 samples per day, enables high precision quantification, and reduces batch effects for large-scale and longitudinal studies. We use our platform on samples collected from a cohort of early hospitalized cases of the SARS-CoV-2 pandemic and identify 27 potential biomarkers that are differentially expressed depending on the WHO severity grade of COVID-19. They include complement factors, the coagulation system, inflammation modulators, and pro-inflammatory factors upstream and downstream of interleukin 6. All protocols and software for implementing our approach are freely available. In total, this work supports the development of routine proteomic assays to aid clinical decision making and generate hypotheses about potential COVID-19 therapeutic targets.

AB - The COVID-19 pandemic is an unprecedented global challenge, and point-of-care diagnostic classifiers are urgently required. Here, we present a platform for ultra-high-throughput serum and plasma proteomics that builds on ISO13485 standardization to facilitate simple implementation in regulated clinical laboratories. Our low-cost workflow handles up to 180 samples per day, enables high precision quantification, and reduces batch effects for large-scale and longitudinal studies. We use our platform on samples collected from a cohort of early hospitalized cases of the SARS-CoV-2 pandemic and identify 27 potential biomarkers that are differentially expressed depending on the WHO severity grade of COVID-19. They include complement factors, the coagulation system, inflammation modulators, and pro-inflammatory factors upstream and downstream of interleukin 6. All protocols and software for implementing our approach are freely available. In total, this work supports the development of routine proteomic assays to aid clinical decision making and generate hypotheses about potential COVID-19 therapeutic targets.

KW - antiviral immune response

KW - clinical classifiers

KW - COVID-19 infection

KW - high-throughput proteomics

KW - mass spectrometry

KW - SWATH-MS

UR - http://www.scopus.com/inward/record.url?scp=85086671757&partnerID=8YFLogxK

U2 - 10.1016/j.cels.2020.05.012

DO - 10.1016/j.cels.2020.05.012

M3 - Article

C2 - 32619549

AN - SCOPUS:85086671757

SN - 2405-4712

VL - 11

SP - 11-24.e4

JO - Cell Systems

JF - Cell Systems

IS - 1

ER -

Ultra-High-Throughput Clinical Proteomics Reveals Classifiers of COVID-19 Infection

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this