Issue 42, 2023

Label-free detection and mapping of graphene oxide in single HeLa cells based on MCR-Raman spectroscopy

Abstract

GO is a 2D nanomaterial that has attracted attention in many industries in recent years, such as the chemical industry, electronics or medicine. Due to its unique properties such as strength, hydrophilicity and large specific surface area with the possibility of functionalization, GO is a particularly attractive material in biomedicine as a candidate for use in targeted drug delivery. In such a case, we need information on whether graphene oxide penetrates into cells and whether we are able to detect and monitor GO in these cells during and also after the treatment to evaluate possible degradation process of GO and its interaction within the cell compartements. This work introduces the Raman spectroscopy as label-free detection method showing the advantages of combining Raman spectroscopy with MCR (Multivariate Curve Resolution) analysis for advanced detection of GO in cervical cancer (HeLa) cells. Our synthesized GO is characterized firstly by AFM, SEM and Raman spectroscopy and then MCR-Raman spectroscopy is used to detect internalized GO in individual HeLa cells. Moreover, by using our methodology, distribution of GO as well as its chemical stability inside the cell for up to six months is investigated without using any additional labeling or tracing the GO. Thus, MCR-Raman spectroscopy may become a new analytical tool in preclinical and clinical applications of graphene-based nanotheranostics.

Graphical abstract: Label-free detection and mapping of graphene oxide in single HeLa cells based on MCR-Raman spectroscopy

Article information

Article type
Paper
Submitted
03 Jul 2023
Accepted
18 Sep 2023
First published
18 Sep 2023
This article is Open Access
Creative Commons BY-NC license

Anal. Methods, 2023,15, 5582-5588

Label-free detection and mapping of graphene oxide in single HeLa cells based on MCR-Raman spectroscopy

Z. Chaloupková, L. Žárská, J. Belza and K. Poláková, Anal. Methods, 2023, 15, 5582 DOI: 10.1039/D3AY01122D

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