Evidence map›Paper›PMID 38755675›Full record

ArticleCell communication and signaling : CCS2024

Integrated proteomic, phosphoproteomic, and N-glycoproteomic analyses of small extracellular vesicles from C2C12 myoblasts identify specific PTM patterns in ligand-receptor interactions.

Xiulan Chen, Xi Song, Jiaran Li, Jifeng Wang, Yumeng Yan, Fuquan Yang

Abstract read
In one paragraph

Article in Cell communication and signaling : CCS, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Review
  6. Article
  7. Review
  8. Plasma-Derived Extracellular Vesicle Proteomics.Journal of proteome research · 2025
    Review
  9. Article
  10. Article
  11. Whole-Genome Sequences of 13 Chinese Indigenous Pinewood Nematodes,International journal of molecular sciences · 2024
    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

6 authors.

Xiulan ChenKey Laboratory of Protein and Peptide Pharmaceuticals & Laboratory of Proteomics, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China. chenxiulan@moon.ibp.ac.cn.
Xi SongKey Laboratory of Protein and Peptide Pharmaceuticals & Laboratory of Proteomics, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
Jiaran LiKey Laboratory of Protein and Peptide Pharmaceuticals & Laboratory of Proteomics, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
Jifeng WangKey Laboratory of Protein and Peptide Pharmaceuticals & Laboratory of Proteomics, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
Yumeng YanKey Laboratory of Protein and Peptide Pharmaceuticals & Laboratory of Proteomics, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
Fuquan YangKey Laboratory of Protein and Peptide Pharmaceuticals & Laboratory of Proteomics, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China. fqyang@ibp.ac.cn.

Funding

National Key Research and Development Program of China Grant Nos. 2018YFA0507103
6 · The paper itself

Abstract

Small extracellular vesicles (sEVs) are important mediators of intercellular communication by transferring of functional components (proteins, RNAs, and lipids) to recipient cells. Some PTMs, including phosphorylation and N-glycosylation, have been reported to play important role in EV biology, such as biogenesis, protein sorting and uptake of sEVs. MS-based proteomic technology has been applied to identify proteins and PTM modifications in sEVs. Previous proteomic studies of sEVs from C2C12 myoblasts, an important skeletal muscle cell line, focused on identification of proteins, but no PTM information on sEVs proteins is available.In this study, we systematically analyzed the proteome, phosphoproteome, and N-glycoproteome of sEVs from C2C12 myoblasts with LC-MS/MS. In-depth analyses of the three proteomic datasets revealed that the three proteomes identified different catalogues of proteins, and PTMomic analysis could expand the identification of cargos in sEVs. At the proteomic level, a high percentage of membrane proteins, especially tetraspanins, was identified. The sEVs-derived phosphoproteome had a remarkably high level of tyrosine-phosphorylated sites. The tyrosine-phosphorylated proteins might be involved with EPH-Ephrin signaling pathway. At the level of N-glycoproteomics, several glycoforms, such as complex N-linked glycans and sialic acids on glycans, were enriched in sEVs. Retrieving of the ligand-receptor interaction in sEVs revealed that extracellular matrix (ECM) and cell adhesion molecule (CAM) represented the most abundant ligand-receptor pairs in sEVs. Mapping the PTM information on the ligands and receptors revealed that N-glycosylation mainly occurred on ECM and CAM proteins, while phosphorylation occurred on different categories of receptors and ligands. A comprehensive PTM map of ECM-receptor interaction and their components is also provided.In summary, we conducted a comprehensive proteomic and PTMomic analysis of sEVs of C2C12 myoblasts. Integrated proteomic, phosphoproteomic, and N-glycoproteomic analysis of sEVs might provide some insights about their specific uptake mechanism.

Indexed as

Extracellular VesiclesMyoblastsProteomicsAnimalsCell LineGlycoproteinsGlycosylationLigandsMicePhosphoproteinsPhosphorylationProtein Processing, Post-TranslationalProteomeGlycoproteinsLigandsPhosphoproteinsProteomeC2C12 myoblastLC–MS/MSLigand-receptor interactionMembrane transportersN-glycoproteomicsPhosphoproteomicsProteomicsSkeletal muscleSmall extracellular vesicles (sEVs)

Identifiers

PMID38755675
PMCPMC11097525

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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.