AI Article Synopsis

  • A new method was created to analyze extracellular vesicles (EVs) in bovine milk by using serial-pelleting purification combined with mass spectrometry to identify differences in EV populations.
  • Different speeds of ultracentrifugation helped separate large EVs (>200 nm) from small EVs (<200 nm), leading to the discovery of 476 proteins, with 340 tied to vesicular components.
  • Findings showed that a greater number of proteins were enriched in large EVs, with specific protein types indicating their origins, thus offering potential new marker proteins for distinct vesicle populations.

Article Abstract

In the work presented herein, a simple serial-pelleting purification strategy combined with a mass spectrometry-based proteomics analysis was developed as a means of discerning differences in extracellular vesicle (EV) populations found in bovine milk samples. A sequence of ultracentrifugation speeds was used to generate changes in the abundances of EV populations, allowing for the identification of associated proteins. A metric was developed to determine the relative abundances of proteins in large EVs (>200 nm) and small EVs (<200 nm). Of the 476 proteins consistently found in this study, 340 are associated with vesicular components. Of these, 156 were heavily enriched in large EVs, 155 shared between large and small EVs, and 29 heavily enriched in small EVs. Additionally, out of 68 proteins annotated as exosome proteins, 32 were enriched in large EVs, 27 shared between large and small EVs, 5 enriched in small EVs, and 7 were found to be nonvesicular contaminant proteins. The top correlated proteins in the small EV group were predominantly membrane-bound proteins, whereas the top correlated proteins in the large EV group were mostly cytosolic enzymes for molecular processing. This method provides a means of assessing the origins of vesicle components and provides new potential marker proteins within discrete vesicle populations.

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http://dx.doi.org/10.1021/acs.jproteome.4c00352DOI Listing

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