Development of a Mass Spectrometry Imaging Method for Detecting and Mapping Graphene Oxide Nanoparticles in Rodent Tissues

Abstract

Graphene-based nanoparticles are continuously being developed for biomedical applications, and their use raises concerns about their environmental and biological impact. In the literature, some imaging techniques based on fluorescence and radioimaging have been used to explore their fate in vivo. Here, we report on the use of label-free mass spectrometry and mass spectrometry imaging (MSI) for graphene oxide (GO) and reduced graphene oxide (rGO) analyses in rodent tissues. Thereby, we extend previous work by focusing on practical questions to obtain reliable and meaningful images. Specific radical anionic carbon clusters ranging from C 2 −• to C 9 −• were observed for both GO and rGO species, with a base peak at m/z 72 under negative laser desorption ionization mass spectrometry (LDI-MS) conditions. Extension to an LDI-MSI method was then performed, thus enabling the efficient detection of GO nanoparticles in lung tissue sections of previously exposed mice. The possibility of quantifying those nanoparticles on tissue sections has also been investigated. Two different ways of building calibration curves (i.e., GO suspensions spotted on tissue sections, or added to lung tissue homogenates) were evaluated and returned similar results, with linear dynamic concentration ranges over at least 2 orders of magnitude. Moreover, intra-and inter-day precision studies have been assessed, with relative standard deviation below 25% for each concentration point of a calibration curve. In conclusion, our study confirms that LDI-MSI is a relevant approach for biodistribution studies of carbon-based nanoparticles, as quantification can be achieved, provided that nanoparticle suspension and manufacturing are carefully controlled.

Composition and Structure of Fluorescent Graphene Quantum Dots Generated by Enzymatic Degradation of Graphene Oxide

“…Also, the ideal composition candidates must contain at least three elements, i.e., C, H, and O. Different from laser desorption ionization (LDI) and/or matrix-assisted laser desorption ionization (MALDI) methods, which produce primarily singly charged ions, − ESI could generate a range of multiply charged species for each molecule: +2, +3, +4, and so on. Moreover, as ESI is one of the softest ionization techniques, detectability of some adducts during the ESI process depends on the availability of the small ions in the analytical process. , For example, sodium is one of the most common impurity, which could arise from multiple sources such as mobile-phase additives, solvents, glassware, and so on. , Therefore, sodium adducts could be formed during the MS analysis.…”

Mass Spectrometric Biosensing: A Powerful Approach for Multiplexed Analysis of Clinical Biomolecules

“…With this real label-free MSI method, mapping and quantification of the carbon nanotubes, graphene oxide, and carbon nanodots were realized, and distinct sub- and interorgan distribution regularities were uncovered. Cazier et al further evaluated MALDI- and LDI-MS-based imaging methods for graphene oxide and reduced graphene oxide analyses in tissues, and confirmed the carbon cluster anions as sensing signatures. It can be inferred that the proposed method may play an important role in the study and assessment of functionalized nanomaterial before clinical biomedical applications.…”

Surface‐assisted laser desorption/ionization mass spectrometry imaging: A review

“…Thus, SALDI‐MSI experiments are generally characterized by a higher reproducibility (Krasny et al, 2015 ) and higher spatial fidelity and resolution than conventional MALDI‐MSI (Lopez de Laorden et al, 2015 ). In turn, this leads to more accurate quantitative analyses in SALDI‐MS (Qiao & Liu, 2010 ), which opens new opportunities in terms of quantitative imaging analyses (Cazier et al, 2020 ).…”

“…Indeed, the heterogeneity of the analyte/matrix co‐crystallization creating “sweet spots” (with corresponding problems of poor mass accuracy and poor shot‐to‐shot and sample‐to‐sample reproducibility [Chiang et al, 2010 ]) is a major factor preventing the quantitative analyses (Qiao & Liu, 2010 ). However, with experimental optimization and appropriate internal standard (Wall et al, 2004 ), SALDI‐MS has been proven to be capable of performing quantitative analyses (Go et al, 2003 ; Okuno et al, 2005 ; Wall et al, 2004 ), therefore opening new opportunities in quantitative MSI (Cazier et al, 2020 ; Wu et al, 2020 ). In particular, ion signal calibration and normalization strategies, adapted to each specific microenvironment of the sample, are required (Wu et al, 2020 ).…”