Nanoparticle identification using single particle ICP-ToF-MS acquisition coupled to cluster analysis. From engineered to natural nanoparticles

Tharaud, Mickaël; Schlatt, Lukas; Shaw, P. F. D.; Benedetti, Marc F.

doi:10.1039/d2ja00116k

Cited by 19 publications

(21 citation statements)

References 27 publications

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“…The emerging growth in the development, production, and application of multi-element engineered NPs (ENPs), which are widely incorporated into commercial products, requires advanced analytical methods which allow for size fractionation and chemical quantification of nanomaterials [72,73]. Some of the published studies regarding determination of the elemental and isotopic composition of NPs are summarized in Table 3.…”

Section: Determination Of the Elemental And Isotopic Composition Of Npsmentioning

confidence: 99%

“…SP-ICP-MS technique enables rapid measurements of size, mass, concentration, and element/isotope concentration. However, the monitoring of multiple elements in an individual NP in a single run is not possible [4,72,78]. Although the increase in acquisition time and peak-jumping enables for multi-element analysis of single particle to some extent, it was observed that the multiple detection is still limited to at most two targeted elements in each NP [69].…”

Section: Determination Of the Elemental And Isotopic Composition Of Npsmentioning

confidence: 99%

“…Several studies used single-particle inductively coupled plasma time-of-flight mass spectrometry (SP-ICP-TOF-MS) for the characterization of NPs in environmental and biological matrices. The researchers identified that the large amount of data and information obtained using mentioned technique makes the results' interpretation very challenging [72]. Thus, in recent years, SP-ICP-TOF-MS emerged as a useful method for classification of NP type based on multi-element fingerprinting using machine learning algorithm such as the hierarchical agglomerative clustering [29,89].…”

Section: Determination Of the Elemental And Isotopic Composition Of Npsmentioning

confidence: 99%

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Basic and advanced spectrometric methods for complete nanoparticles characterization in bio/eco systems: current status and future prospects

Borowska

Jankowski

2023

Anal Bioanal Chem

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The use of engineered nanoparticles in the environment and human life has increased in the last 20 years. The risk assessment concerning application of nanomaterials in biological systems requires their thorough characterization. Understanding the correlations between physicochemical properties of nanoparticles concerning not only the size, particle size distribution, number concentration, degree of aggregation, or agglomeration but also solubility, stability, binding affinity, surface activity, chemical composition, and nanoparticle synthesis yield allows their reliable characterization. Thus, to find the structure-function/property relationship of nanoparticles, multifaceted characterization approach based on more than one analytical technique is required. On the other hand, the increasing demand for identification and characterization of nanomaterials has contributed to the continuous development of spectrometric techniques which enables for their qualitative and quantitative analysis in complex matrices giving reproducible and reliable results. This review is aimed at providing a discussion concerning four main aspects of nanoparticle characterization: nanoparticle synthesis yield, particle size and number concentration, elemental and isotopic composition of nanoparticles, and their surface properties. The conventional and non-conventional spectrometric techniques such as spectrophotometry UV-Vis, mass spectrometric techniques working in conventional and single-particle mode, or those based on optical emission detection systems are described with special emphasis paid on their advantages and drawbacks. The application and recent advances of these methods are also comprehensively reviewed and critically discussed. Graphical abstract

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Section: Determination Of the Elemental And Isotopic Composition Of Npsmentioning

confidence: 99%

Section: Determination Of the Elemental And Isotopic Composition Of Npsmentioning

confidence: 99%

Section: Determination Of the Elemental And Isotopic Composition Of Npsmentioning

confidence: 99%

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Basic and advanced spectrometric methods for complete nanoparticles characterization in bio/eco systems: current status and future prospects

Borowska

Jankowski

2023

Anal Bioanal Chem

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“…As a drawback, the analysis of elements from the lower mass range with biological key functions is not possible with this kind of instrumentation. There are currently different ICP-TOFMS systems on the market that provide the capability to measure m / z = 14–256 − and, therefore, imaging of endogenous elements at the cellular level . Several LA-ICPMS studies employed quadrupole-based ICP–MS systems, limiting the number of elements that can be measured simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Multiparametric Tissue Characterization Utilizing the Cellular Metallome and Immuno-Mass Spectrometry Imaging

Schaier

Theiner

Baier

et al. 2023

JACS Au

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In this study, we present a workflow that enables spatial single-cell metallomics in tissue decoding the cellular heterogeneity. Low-dispersion laser ablation in combination with inductively coupled plasma time-of-flight mass spectrometry (LA-ICP-TOFMS) provides mapping of endogenous elements with cellular resolution at unprecedented speed. Capturing the heterogeneity of the cellular population by metals only is of limited use as the cell type, functionality, and cell state remain elusive. Therefore, we expanded the toolbox of single-cell metallomics by integrating the concepts of imaging mass cytometry (IMC). This multiparametric assay successfully utilizes metallabeled antibodies for cellular tissue profiling. One important challenge is the need to preserve the original metallome in the sample upon immunostaining. Therefore, we studied the impact of extensive labeling on the obtained endogenous cellular ionome data by quantifying elemental levels in consecutive tissue sections (with and without immunostaining) and correlating elements with structural markers and histological features. Our experiments showed that the elemental tissue distribution remained intact for selected elements such as sodium, phosphorus, and iron, while absolute quantification was precluded. We hypothesize that this integrated assay not only advances single-cell metallomics (enabling to link metal accumulation to multi-dimensional characterization of cells/cell populations), but in turn also enhances selectivity in IMC, as in selected cases, labeling strategies can be validated by elemental data. We showcase the power of this integrated single-cell toolbox using an in vivo tumor model in mice and provide mapping of the sodium and iron homeostasis as linked to different cell types and function in mouse organs (such as spleen, kidney, and liver). Phosphorus distribution maps added structural information, paralleled by the DNA intercalator visualizing the cellular nuclei. Overall, iron imaging was the most relevant addition to IMC. In tumor samples, for example, iron-rich regions correlated with high proliferation and/or located blood vessels, which are key for potential drug delivery.

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“…21 Examples of supervised learning methods used for NP and mP classication from spICP-TOFMS datasets include gradient boosted classiers (GBC), 32 light-GBC, 21 k-nearest neighbor embedding (KNN), 35 and binomial logistic regression (LR). 19 Unsupervised approaches, such as clustering analysis 20,33,34,39 or t-stochastic neighbor embedding, 21 have also been reported for NP classi-cation from spICP-TOFMS datasets.…”

Section: Introductionmentioning

confidence: 99%

Machine learning analysis to classify nanoparticles from noisy spICP-TOFMS data

Buckman,

Gundlach-Graham

2023

J. Anal. At. Spectrom.

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Nanoparticle identification using single particle ICP-ToF-MS acquisition coupled to cluster analysis. From engineered to natural nanoparticles

Abstract: In this study, mono-, bi-, and tri-metallic engineered nanoparticles (ENPs) are first analysed using an ICP-ToF-MS in single particle mode. The method is also used to characterize natural NPs (NNPs)...

Cited by 19 publications

References 27 publications

Basic and advanced spectrometric methods for complete nanoparticles characterization in bio/eco systems: current status and future prospects

Basic and advanced spectrometric methods for complete nanoparticles characterization in bio/eco systems: current status and future prospects

Multiparametric Tissue Characterization Utilizing the Cellular Metallome and Immuno-Mass Spectrometry Imaging

Machine learning analysis to classify nanoparticles from noisy spICP-TOFMS data

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