Evidence map›Paper›PMID 40210874›Full record

ArticleScientific data2025

A reference database enabling in-depth proteome and PTM analysis of mouse immune cells.

Devon Siemes, Hannah Voss, Federica Benvenuti, Francesca Simoncello, Dominik Kopczynski, Bente Siebels, Hartmut Schlüter, Laxmikanth Kollipara, Albert Sickmann, Daniel Robert Engel and 1 more

Abstract readDataset
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
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.

Devon SiemesDepartment of Immunodynamics, Institute for Experimental Immunology and Imaging, University Duisburg-Essen, Essen, 45141, Germany.ORCID http://orcid.org/0000-0003-1869-1930
Hannah VossDepartment of Immunodynamics, Institute for Experimental Immunology and Imaging, University Duisburg-Essen, Essen, 45141, Germany.
Federica BenvenutiCellular Immunology Laboratory, International Centre for Genetic Engineering and Biotechnology (ICGEB), Trieste, Italy.
Francesca SimoncelloCellular Immunology Laboratory, International Centre for Genetic Engineering and Biotechnology (ICGEB), Trieste, Italy.
Dominik KopczynskiInstitute for Analytical Chemistry, University of Vienna, Währingerstrasse 38, Vienna, 1090, Austria.
Bente SiebelsSection Mass Spectrometry and Proteomics, Center for Diagnostics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Hartmut SchlüterSection Mass Spectrometry and Proteomics, Center for Diagnostics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Laxmikanth KolliparaLeibniz-Institut für Analytische Wissenschaften-ISAS-e.V., Dortmund, 44139, Germany.
Albert SickmannLeibniz-Institut für Analytische Wissenschaften-ISAS-e.V., Dortmund, 44139, Germany.
Daniel Robert EngelDepartment of Immunodynamics, Institute for Experimental Immunology and Imaging, University Duisburg-Essen, Essen, 45141, Germany.
Olga ShevchukDepartment of Immunodynamics, Institute for Experimental Immunology and Imaging, University Duisburg-Essen, Essen, 45141, Germany. olga.shevchuk@uk-essen.de.ORCID http://orcid.org/0000-0003-1150-7344

Funding

Deutsche Forschungsgemeinschaft (German Research Foundation) FOR5427 SP1Deutsche Forschungsgemeinschaft (German Research Foundation) FOR5427 SP4; EN984/15-1, 16-1 and 18-1; TR296 P09; TR332 A3 and Z1; INST 20876/486-1Deutsche Forschungsgemeinschaft (German Research Foundation) INST 337/15-1
6 · The paper itself

Abstract

Spectral libraries fulfill multiple functions in biological and analytical applications. For biologists, these libraries provide a valuable resource to verify the presence and abundance of proteins or pathways within a selected cell type thus determine the feasibility of further experiments. Despite advances, existing libraries are incomplete and provide researchers only a limited amount of information. To address this, we introduce the reference database - Spectral Library of Immune Cells (SpLICe), a resource covering B-cells, CD4 and CD8 T-cells, macrophages and dendritic cells containing nearly 9,000 protein groups and 110,346 proteotypic peptides. Additionally, the database provides data on > 20,000 post-translationally modified proteotypic peptides (oxidation, phosphorylation, methylation, acetylation, deamidation and N-glycosylation) across the selected immune cell populations. SpLICe supports the quantification of more than half of total murine proteins annotated by UniProtKB/Swiss-Prot, enabling monitoring of selected proteins or pathways from Reactome pathways and Gene Ontology databases. The platform provides relative protein abundances and supports the generation of targeted mass spectrometry assays by identifying and scoring proteotypic peptides.

Indexed as

Databases, ProteinProtein Processing, Post-TranslationalProteomeAnimalsB-LymphocytesCD4-Positive T-LymphocytesCD8-Positive T-LymphocytesDendritic CellsMacrophagesMiceProteome

Identifiers

PMID40210874
PMCPMC11986169

What OpenQuestion holds

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LicenceCC BY
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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.