P4PP: A Universal Shotgun Proteomics Data Analysis Pipeline for Virus Identification
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG33__%2F25%3AN0000003" target="_blank" >RIV/60162694:G33__/25:N0000003 - isvavai.cz</a>
Result on the web
<a href="https://www.mcponline.org/article/S1535-9476(25)00103-3/fulltext" target="_blank" >https://www.mcponline.org/article/S1535-9476(25)00103-3/fulltext</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.mcpro.2025.101004" target="_blank" >10.1016/j.mcpro.2025.101004</a>
Alternative languages
Result language
angličtina
Original language name
P4PP: A Universal Shotgun Proteomics Data Analysis Pipeline for Virus Identification
Original language description
Humans can be infected by a wide variety of virus species. We developed a data analysis approach for shotgun proteomic data to detect these viruses. A proteome for pandemic preparedness (P4PP) pipeline, a corresponding database (P4PP v01), and a web application (P4PP) were constructed. The P4PP pipeline enables the identification of 1896 virus species from the 32 virus families, based on multiple identified discriminatory peptides, in which at least one human infectious virus is described. P4PP was evaluated using different datasets of cell-cultivated viruses, generated at different institutes, measured with different instruments, and prepared with different sample preparation methods. In total, 174 mass spectrometry datasets of 160 and 14 protein trypsin digests of virus-infected and noninfected cell lines were analyzed, respectively. Of the 160 samples, 146 were correctly identified at the species level, and an additional four samples were identified at the family level. In the remaining 10 samples, no virus was detected. However, all these 10 samples tested positive in follow-up samples obtained later in time series were negative samples were measured, indicating that the number of peptides derived from the virus was initially too low in the samples obtained at the start of the experiment. Furthermore, results show that influenza A or severe acute respiratory syndrome coronavirus 2 can be subtyped if enough discriminative peptides of the virus are identified. In the noninfected cell lines, no virus was detected except in one sample where the in that experiment studied virus was detected. Shotgun proteomics, in combination with the developed data analysis approach, can identify all types of virus species after cultivation in a cell line. Implementing this agnostic virus proteome analysis capability in viral diagnostic laboratories has the potential to improve their capabilities to cope with unexpected, mutated, or re-emerging viruses.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10608 - Biochemistry and molecular biology
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Molecular & Cellular Proteomics
ISSN
1535-9476
e-ISSN
1535-9484
Volume of the periodical
24
Issue of the periodical within the volume
7
Country of publishing house
US - UNITED STATES
Number of pages
10
Pages from-to
číslo článku 101004
UT code for WoS article
001523055700003
EID of the result in the Scopus database
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