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Unraveling the complexity of the extracellular vesicle landscape with advanced proteomics
- Source :
- Repisalud, Instituto de Salud Carlos III (ISCIII)
- Publication Year :
- 2022
- Publisher :
- Informa UK Limited, 2022.
-
Abstract
- The field of extracellular vesicles (EVs) is rapidly advancing. This progress is fueled by the applications of these agents as biomarkers and also as an attractive source to encapsulate therapeutics.Different types of EVs, including exosomes, and other nanoparticles have been identified with key regulatory functions in cell-cell communication. However, the techniques used for their purification possess inherent limitations, resulting in heterogeneous preparations contaminated by other EVs subtypes and nano-size structures. It is therefore urgent to deconvolute the molecular constituents present in each type of EVs in order to accurately ascribe their specific functions. In this context, proteomics can profile, not only the lumen proteins and surface markers, but also their post-translational modifications, which will inform on the mechanisms of cargo selection and sorting.Mass spectrometry-based proteomics is now a mature technique and has started to deliver new insights in the EV field. Here, we review recent developments in sample preparation, mass spectrometry (MS) and computational analysis and discuss how these advances, in conjunction with improved purification protocols, could impact thecharacterization of the complex landscape of EVs and other secreted nanoparticles.
- Subjects :
- Proteomics
EXOSOMES
MASS SPECTROMETRY
GeneralLiterature_INTRODUCTORYANDSURVEY
BIOMARKERS
EXTRACELLULAR VESICLES
Proteins
PURIFICATION TECHNIQUES
Exosomes
Biochemistry
Mass Spectrometry
Extracellular Vesicles
ComputingMethodologies_PATTERNRECOGNITION
Humans
PROTEOMICS
Molecular Biology
Biomarkers
Subjects
Details
- ISSN :
- 17448387 and 14789450
- Volume :
- 19
- Database :
- OpenAIRE
- Journal :
- Expert Review of Proteomics
- Accession number :
- edsair.doi.dedup.....d26dafe3d6e4a8a50c9323d6f434c7ee
- Full Text :
- https://doi.org/10.1080/14789450.2022.2052849