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Updated: Feb 3, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
Mapping of equine mesenchymal stromal cell surface proteomes for identification of specific markers using proteomics
Louise Bundgaard1, Allan Stensballe2, Kirstine Juul Elbæk2
1Department of Veterinary Clinical Sciences, University of Copenhagen, Agrovej 8, DK-2630, Taastrup, Denmark. lb@sund.ku.dk.
Background:
Stem cells have great potential for tissue regeneration, but before stem cell populations can be used in the clinic, it is crucial that the stem cells have been definitely characterized by a set of specific markers. Although there have been attempts to identify a set of immunophenotypic markers to characterize equine mesenchymal stromal cells (MSCs), immunophenotyping of equine MSCs is still challenging due to the limited availability of suitable antibodies of high quality and consistent performance across different laboratories. The aim of this study was to evaluate a strategy for mapping the equine MSCs surface proteome by use of biotin-enrichment and mass spectrometry (MS) analysis and mine the proteome for potential equine MSCs surface markers belonging to the cluster of differentiation protein group. Gene expression analysis was used for verification.
Methods:
Equine MSCs derived from bone marrow (BM) (n = 3) and adipose tissue (AT) (n = 3) were expanded to P3 and either used for (1) cell differentiation into mesodermal lineages (chondrogenic and osteogenic), (2) enrichment of the MSCs surface proteins by biotinylation followed by in-gel digest of the isolated proteins and nanoLC-MS/MS analysis to unravel the enriched cell surface proteome, and (3) RNA isolation and quantitative real-time reverse transcriptase PCR analysis of the CD29, CD44, CD90, CD105, CD166, CD34, CD45, and CD79a gene expression.
Results:
A total of 1239 proteins at 1% FDR were identified by MS analysis of the enriched MSCs surface protein samples. Of these proteins, 939 were identified in all six biological samples. The identified proteins included 19 proteins appointed to the cluster of differentiation classification system as potential cell surface targets. The protein and gene expression pattern was positive for the commonly used positive MSCs markers CD29, CD44, CD90, CD105, and CD166, and lacked the negative MSCs markers CD34, CD45, and CD79a.
Conclusions:
The findings of this study show that enrichment of the MSCs surface proteome by biotinylation followed by MS analysis is a valuable alternative to immunophenotyping of surface markers, when suitable antibodies are not available. Further, they support gene expression analysis as a valuable control analysis to verify the data.
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