Nanoprojectile Secondary Ion Mass Spectrometry Enables Multiplexed Analysis of Individual Hepatic Extracellular Vesicles.


Journal

bioRxiv : the preprint server for biology
Titre abrégé: bioRxiv
Pays: United States
ID NLM: 101680187

Informations de publication

Date de publication:
22 Aug 2023
Historique:
medline: 4 9 2023
pubmed: 4 9 2023
entrez: 4 9 2023
Statut: epublish

Résumé

Extracellular vesicles (EVs) are nanoscale lipid bilayer particles secreted by cells. EVs may carry markers of the tissue of origin and its disease state which makes them incredibly promising for disease diagnosis and surveillance. While the armamentarium of EV analysis technologies is rapidly expanding, there remains a strong need for multiparametric analysis with single EV resolution. Nanoprojectile (NP) secondary ion mass spectrometry (NP-SIMS) relies on bombarding a substrate of interest with individual gold NPs resolved in time and space. Each projectile creates an impact crater of 10-20 nm in diameter while molecules emitted from each impact are mass analyzed and recorded as individual mass spectra. We demonstrate the utility of NP-SIMS for analysis of single EVs derived from normal liver cells (hepatocytes) and liver cancer cells. EVs were captured on antibody (Ab)-functionalized gold substrate then labeled with Abs carrying lanthanide (Ln) MS tags (Ab@Ln). These tags targeted four markers selected for identifying all EVs, and specific to hepatocytes or liver cancer. NP-SIMS was used to detect Ab@Ln-tags co-localized on the same EV and to construct scatter plots of surface marker expression for thousands of EVs with the capability of categorizing individual EVs. Additionally, NP-SIMS revealed information about the chemical nano-environment where targeted moieties co-localized. Our approach allowed analysis of population heterogeneity with single EV resolution and distinguishing between hepatocyte and liver cancer EVs based on surface marker expression. NP-SIMS holds considerable promise for multiplexed analysis of single EVs and may become a valuable tool for identifying and validating EV biomarkers of cancer and other diseases.

Identifiants

pubmed: 37662200
doi: 10.1101/2023.08.21.554053
pmc: PMC10473594
pii:
doi:

Types de publication

Preprint

Langues

eng

Commentaires et corrections

Type : UpdateIn

Auteurs

Classifications MeSH