SPROUTS_DB: an implemented database of contaminants for extracellular vesicle proteomics studies

preprint OA: closed
📄 Open PDF Full text JSON View at publisher
Full text 2,873 characters · extracted from oa-doi-fallback · 3 sections · click to expand

Abstract

Background Current proteomics techniques allow rapid identification and quantification of proteins within any given biological source. In particular, nanoUHPLC/High-Resolution nanoESI-MS/MS enables the characterization of proteins in complex biological samples due to its high sensitivity, accuracy, and scalability. However, LC-MS/MS proteomics might still be susceptible to laboratory and sample-associated contaminants, which can significantly compromise the quality and reliability of data. Therefore, an accurate identification and annotation of such contaminants is crucial for the development of robust proteomics databases and spectral-libraries related search engines. This approach is of special interest in the field of secretome and extracellular vesicles (EVs), membrane-enclosed nanostructures that contain a variety of proteins crucial for cell-to-cell communication and translational applications.

Results

When working in ex vivo/in vitro settings, proteins from fetal bovine serum (FBS), commonly employed in standard cell culture media, may interfere with the proteome analysis. To address this issue, we conceived and designed SPROUTS_DB, Serum Protein Repository Of Unwanted Target(ed) Sequences DataBase, a dedicated resource to catalog serum-derived contaminants. Starting from media supplemented with EV-depleted FBS, we simulated cell growth conditions - in the absence of cells - followed by ultracentrifugation. LC-MS/MS analysis of these samples resulted in the identification of a novel set of 1,288 contaminant proteins, which has been deposited in the ProteomeXchange repository (identifier PXD044137). SPROUTS_DB contains primarily soluble proteins, mainly related to the Gene Ontology categories Extracellular Region and Extracellular Space, in line with the nature of the starting sample. In contrast, only a small fraction of the contaminants is classified as membrane-associated proteins, supporting the limited vesicle contamination in the complete medium, due to the use of EV-depleted FBS. Of note, we demonstrated that SPROUTS_DB outperforms existing contaminants’ databases, ensuring that only peptide spectra relevant to the examined sample are retained and identified as true positive data.

Conclusions

Considering that even proteins from phylogenetically distant organisms share extensive stretches of sequences, SPROUTS_DB is designed to discern contaminants from real sample proteins of interest, minimizing false positive identifications. To the best of our knowledge, SPROUTS_DB is the most updated database of contaminants useful for proteomics investigations of cellular secretomes and EV-containing samples. - High-resolution Mass Spectrometry - Proteomics - Extracellular Vesicles - Exosomes - Molecular Database - Contaminant Proteins Competing Interest Statement The authors have declared no competing interest.

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: oa-doi-fallback

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2025) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00