Evidence map›Paper›PMID 40449796›Full record

ArticleMolecular & cellular proteomics : MCP2025

P4PP: A Universal Shotgun Proteomics Data Analysis Pipeline for Virus Identification.

Armand Paauw, Evgeni Levin, Ingrid A I Voskamp-Visser, Ilka M F Marissen, Vincent Ramisse, Marine Eschlimann, Jiří Dresler, Petr Pajer, Christoph Stingl, Hans C van Leeuwen and 2 more

Abstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Armand PaauwDepartment of CBRN Protection, Netherlands Organization for Applied Scientific Research TNO, TNO, Rijswijk, the Netherlands. Electronic address: armand.paauw@tno.nl.
Evgeni LevinHORAIZON Technology BV., Delft, the Netherlands.
Ingrid A I Voskamp-VisserDepartment of CBRN Protection, Netherlands Organization for Applied Scientific Research TNO, TNO, Rijswijk, the Netherlands.
Ilka M F MarissenDepartment of CBRN Protection, Netherlands Organization for Applied Scientific Research TNO, TNO, Rijswijk, the Netherlands.
Vincent RamisseDGA CBRN Defence Center, Vert-le-Petit, France.
Marine EschlimannDGA CBRN Defence Center, Vert-le-Petit, France.
Jiří DreslerMilitary Health Institute, Military Medical Agency, Prague, Czech Republic.
Petr PajerMilitary Health Institute, Military Medical Agency, Prague, Czech Republic.
Christoph StinglDepartment of Neurology, Erasmus MC, Rotterdam, the Netherlands.
Hans C van LeeuwenDepartment of CBRN Protection, Netherlands Organization for Applied Scientific Research TNO, TNO, Rijswijk, the Netherlands.
Theo M LuiderDepartment of Neurology, Erasmus MC, Rotterdam, the Netherlands.
Luc M HornstraDepartment of CBRN Protection, Netherlands Organization for Applied Scientific Research TNO, TNO, Rijswijk, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

ProteomeProteomicsViral ProteinsVirusesCell LineData AnalysisDatabases, ProteinHumansMass SpectrometrySARS-CoV-2ProteomeViral ProteinsP4PP pipelinepandemic preparednesspeptidesproteomicsvirus identification

Identifiers

PMID40449796
PMCPMC12418414

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.