vPro-MS enables identification of human-pathogenic viruses from patient samples by untargeted proteomics

Marica Grossegesse, Fabian Horn, Andreas Kurth, Peter Lasch, Andreas Nitsche and Joerg Doellinger ()
Additional contact information
Marica Grossegesse: WHO Collaboration Center for Emerging Threats and Special Pathogens
Fabian Horn: Centre for Biological Threats and Special Pathogens: Proteomics and Spectroscopy (ZBS 6)
Andreas Kurth: Centre for Biological Threats and Special Pathogens: Biosafety Level-4 Laboratory (ZBS 5)
Peter Lasch: Centre for Biological Threats and Special Pathogens: Proteomics and Spectroscopy (ZBS 6)
Andreas Nitsche: WHO Collaboration Center for Emerging Threats and Special Pathogens
Joerg Doellinger: WHO Collaboration Center for Emerging Threats and Special Pathogens

Nature Communications, 2025, vol. 16, issue 1, 1-13

Abstract: Abstract Viral infections are commonly diagnosed by the detection of viral genome fragments or proteins using targeted methods such as PCR and immunoassays. In contrast, metagenomics enables the untargeted identification of viral genomes, expanding its applicability across a broader spectrum. In this study, we introduce proteomics as a complementary approach for the untargeted identification of human-pathogenic viruses from patient samples. The viral proteomics workflow (vPro-MS) is based on an in-silico derived peptide library covering the human virome in UniProtKB (331 viruses, 20,386 genomes, 121,977 peptides). A scoring algorithm (vProID score) is developed to assess the confidence of virus identification from proteomics data ( https://github.com/RKI-ZBS/vPro-MS ). In combination with diaPASEF-based data acquisition, this workflow enables the analysis of up to 60 samples per day. The specificity is determined to be >99,9% in an analysis of 221 plasma, swab and cell culture samples covering 17 different viruses. The sensitivity of this approach for the detection of SARS-CoV-2 in nasopharyngeal swabs corresponds to a PCR cycle threshold of 27 with comparable quantitative accuracy to metagenomics. vPro-MS enables the integration of untargeted virus identification in large-scale proteomic studies of biofluids such as human plasma to detect previously undiscovered virus infections in patient specimens.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-025-62469-4 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-62469-4

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-025-62469-4

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().