Ultra-high-throughput clinical proteomics reveals classifiers of COVID-19 infection
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Christoph Messner Vadim Demichev Daniel Wendisch Laura Michalick Matthew White Anja Freiwald Kathrin Textoris-Taube Spyros 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 Toggle all authors (33)
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.
Journal details
Journal Cell systems
Volume 11
Issue number 1
Pages 11-24.e4
Available online
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Publisher website (DOI) 10.1016/j.cels.2020.05.012
Figshare View on figshare
Europe PubMed Central 32619549
Pubmed 32619549
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