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

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-

SUBMITTER: Grossegesse M 

PROVIDER: S-EPMC12314097 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature