Evidence map›Paper›PMID 41923394›Full record

ArticleProteomics2026

SPROUTS_DB: An Implemented Database of Contaminants for Extracellular Vesicle Proteomics Studies.

Maria Gaetana Giovanna Pittalà, Loredana Leggio, Greta Paternò, Elena Giusto, Laura Civiero, Vincenzo Cunsolo, Silvia Vivarelli, Antonella Di Francesco, Emanuele Alpi, Nunzio Iraci and 1 more

Abstract read
In one paragraph

Article in Proteomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Maria Gaetana Giovanna PittalàOrganic Mass Spectrometry Laboratory, Department of Chemical Sciences, University of Catania, Catania, Italy.
Loredana LeggioDepartment of Biomedical and Biotechnological Sciences, University of Catania, Catania, Italy.
Greta PaternòDepartment of Biomedical and Biotechnological Sciences, University of Catania, Catania, Italy.
Elena GiustoIRCCS San Camillo Hospital, Venice, Italy.
Laura CivieroIRCCS San Camillo Hospital, Venice, Italy.
Vincenzo CunsoloOrganic Mass Spectrometry Laboratory, Department of Chemical Sciences, University of Catania, Catania, Italy.
Silvia VivarelliDepartment of Biomedical and Dental Sciences and Morphofunctional Imaging, Occupational Medicine Section, University of Messina, Messina, Italy.
Antonella Di FrancescoOrganic Mass Spectrometry Laboratory, Department of Chemical Sciences, University of Catania, Catania, Italy.
Emanuele AlpiAbzena, Babraham Research Campus, Cambridge, UK.
Nunzio IraciDepartment of Biomedical and Biotechnological Sciences, University of Catania, Catania, Italy.
Rosaria SalettiOrganic Mass Spectrometry Laboratory, Department of Chemical Sciences, University of Catania, Catania, Italy.

Funding

University of Catania
6 · The paper itself

Abstract

Current proteomics techniques allow rapid identification and quantification of proteins within any given biological source. However, LC-MS/MS proteomics is vulnerable to laboratory and sample-associated contaminants. Therefore, accurate identification and annotation of such contaminants is crucial for development of reliable databases, especially for secretome and extracellular vesicle studies. When working in ex vivo/in vitro settings, proteins from fetal bovine serum (FBS) interfere with the proteome analysis. To address this issue, we designed SPROUTS_DB, Serum Protein Repository Of Unwanted Target(ed) Sequences DataBase, a dedicated resource to catalog serum-derived contaminants. Starting from media with EV-depleted FBS, we simulated cell growth conditions-without cells-followed by ultracentrifugation. LC-MS/MS analysis resulted in the identification of a novel set of 1288 contaminant proteins. SPROUTS_DB contains primarily soluble proteins linked to the Extracellular Region and Space, in line with the nature of the starting sample. In contrast, few membrane-associated proteins were found, confirming minimal vesicle contamination from the use of EV-depleted FBS. Finally, we demonstrated that SPROUTS_DB outperforms existing contaminants' databases, ensuring that only peptide spectra relevant to the examined sample are retained as true positive data. It is, to our knowledge, the most up-to-date resource for proteomic analysis of secretomes and EV-containing samples.

Indexed as

Databases, ProteinExtracellular VesiclesProteomeProteomicsAnimalsCattleHumansLiquid Chromatography-Mass SpectrometryTandem Mass SpectrometryProteomecontaminant proteinsexosomesextracellular vesicleshigh‐resolution mass spectrometrymolecular databaseproteomics

Identifiers

PMID41923394
PMCPMC13327711

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.