AI Article Synopsis

  • Small extracellular vesicles (sEVs) are tiny vesicles (30-150nm) released by cells, important for diagnosing and treating diseases, with varied biological compositions influencing their functions.
  • The study combined surface-enhanced Raman spectroscopy (SERS) and machine learning to analyze individual sEVs, revealing that specific spectral features (biomolecular "fingerprints") correspond to the vesicles' biomolecular makeup.
  • The findings suggest that size-based isolation methods effectively yield sEVs with similar biochemical properties, enabling better differentiation among sub-populations, as over 84% of vesicles in the same size group exhibited distinct SERS features.

Article Abstract

Small extracellular vesicles (sEVs) are cell-released vesicles ranging from 30-150nm in size. They have garnered increasing attention because of their potential for both the diagnosis and treatment of disease. The diversity of sEVs derives from their biological composition and cargo content. Currently, the isolation of sEV subpopulations is primarily based on bio-physical and affinity-based approaches. Since a standardized definition for sEV subpopulations is yet to be fully established, it is important to further investigate the correlation between the biomolecular composition of sEVs and their physical properties. In this study, we employed a platform combining single-vesicle surface-enhanced Raman spectroscopy (SERS) and machine learning to examine individual sEVs isolated by size-exclusion chromatography (SEC). The biomolecular composition of each vesicle examined was reflected by its corresponding SERS spectral features (biomolecular "fingerprints"), with their roots in the composition of their collective Raman-active bonds. Origins of the SERS spectral features were validated through a comparative analysis between SERS and mass spectrometry (MS). SERS fingerprinting of individual vesicles was effective in overcoming the challenges posed by EV population averaging, allowing for the possibility of analyzing the variations in biomolecular composition between the vesicles of similar and/or different sizes. Using this approach, we uncovered that each of the size-based fractions of sEVs contained particles with predominantly similar SERS spectral features. Indeed, more than 84% of the vesicles residing within a particular group were clearly distinguishable from that of the other EV sub-populations, despite some spectral variations within each sub-population. Our results suggest the possibility that size-based EV fractionation methods produce samples where similarly eluted sEVs are correlated with their respective biochemical contents, as reflected by their SERS spectra. Our findings therefore highlight the possibility that the biogenesis and respective biological functionalities of the various sEV fractions may be inherently different.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11185487PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0305418PLOS

Publication Analysis

Top Keywords

biomolecular composition
16
sers spectral
12
spectral features
12
raman spectroscopy
8
small extracellular
8
extracellular vesicles
8
sev subpopulations
8
sers
7
composition
6
vesicles
6

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!