Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Sep 15:418:126282.
doi: 10.1016/j.jhazmat.2021.126282. Epub 2021 Jun 2.

Comparative and mechanistic toxicity assessment of structure-dependent toxicity of carbon-based nanomaterials

Affiliations

Comparative and mechanistic toxicity assessment of structure-dependent toxicity of carbon-based nanomaterials

Tao Jiang et al. J Hazard Mater. .

Abstract

The wide application of carbon-based nanomaterials (CNMs) has resulted in the ubiquity of CNMs in the natural environment and they potentially impose adverse consequences on ecosystems and human health. In this study, we comprehensively evaluated and compared potential toxicological effects and mechanisms of seven CNMs in three representative types (carbon blacks, graphene nanoplatelets, and fullerenes), to elucidate the correlation between their physicochemical/structural properties and toxicity. We employed a recently-developed quantitative toxicogenomics-based toxicity testing system with GFP-fused yeast reporter library targeting main cellular stress response pathways, as well as conventional phenotype-based bioassays. The results revealed that DNA damage, oxidative stress, and protein stress were the major mechanisms of action for all the CNMs at sub-cytotoxic concentration levels. The molecular toxicity nature were concentration-dependent, and they exhibited both similarity within the same structural group and distinctiveness among different CNMs, evidencing the structure-driven toxicity of CNMs. The toxic potential based on toxicogenomics molecular endpoints revealed the remarkable impact of size and structure on the toxicity. Furthermore, the phenotypic endpoints derived from conventional phenotype-based bioassays correlated with quantitative molecular endpoints derived from the toxicogenomics assay, suggesting that the selected protein biomarkers captured the main cellular effects that are associated with phenotypic adverse outcomes.

Keywords: Carbon blacks (CBs); Fullerenes; Graphene nanoplatelets (GNPs); Nanotoxicity; Quantitative toxicogenomics assay.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
CNMs morphology measured using a scanning electron microscope (SEM): (A) Carbon black N110; (B) Carbon black N550; (C) Carbon black N990; (D) Graphene nanoplatelets; (E) Fullerene nC60; (F) Fullerene nC70; (G) Fullerene nC84. The scale bars are displayed at the left bottom corner.
Figure 2.
Figure 2.
(A) Hierarchical cluster (HCL) analysis diagram on the basis of differential protein expressions (mean lnI, n = 3) of 74 selected yeast proteins induced by the 7 carbon-based nanomaterials (CNMs) across 6 concentrations. The mean natural log of positive induction factor (lnI) denotes the change in protein expression level (color-coded by green-black-red spectrum, with green and red indicating downregulations and upregulations, respectively. The lnI outside (−2, 2) are displayed as −2 or 2). X-axis bottom: CNM names and concentrations, and their cluster root. C1-C6 indicate concentrations 1–6, which are 0.031, 0.125, 0.5, 2, 8, and 32 mg/L, respectively. Y-axis left: protein markers classified in the 5 stress categories (caption on top). Y-axis right: cluster root of protein markers and sub-clusters I and II. High concentration CNMs (C5, C6) are with light blue background. (B) Principal component analysis (PCA) with differential protein expressions (mean lnI, n = 3) in the GFP-fused yeast library exposed to the 7 CNMs across 6 concentrations. Samples are color-coded and each legend shape indicates one treatment with larger legend size representing the higher concentration.
Figure 3.
Figure 3.
Quantitative molecular toxicity profiles of the 7 tested carbon-based nanomaterials (CNMs) in terms of the PELI values for the 5 stress response categories and total PELI: (A) Carbon black N110; (B) Carbon black N550; (C) Carbon black N990; (D) Graphene nanoplatelets; (E) Fullerene C60; (F) Fullerene C70; and (G) Fullerene C84. X-axis: concentration of the tested CNMs (mg/L). Y-axis: PELI as the molecular toxicity endpoint. Mean ± SD, n = 3. The “*” indicates the enriched stress categories revealed by the gene set enrichment analysis (GSEA).
Figure 4.
Figure 4.
(A) Intracellular ROS generation (equivalent to mg/L H2O2) in yeast for the 7 carbon-based nanomaterials (CNMs) at 8 and 32 mg/L, and (B) % Tail DNA compared to the untreated control measured by the alkaline comet assay for the 7 CNMs in human A549 cells. X-axis (A) and (B): Names of the 7 CNMs. Y-axis: (A) Intracellular ROS production (equivalent to mg/L H2O2), and (B) % tail DNA compared to the untreated control. The asterisk (*) denotes statistical significance (p < 0.05) of % Tail DNA compared to the untreated control. Mean ± SD, n = 3 for ROS generation and n = 4 for comet assay.
Figure 5.
Figure 5.
Correlation of intracellular ROS production (equivalent to H2O2) with (A) PELIoxi and (B) PELIoverall in yeast, and (C) correlation of % Tail DNA compared to untreated control measured by alkaline comet assay in human A549 cells with molecular genotoxicity endpoint 1/PELI1.5geno for the 7 tested carbon-based nanomaterials (CNMs). Dash lines denote the 95% confidence interval. r is the Pearson correlation coefficient, and p characterizes the statistical significance. Mean ± SD, n = 3 for ROS production and n = 4 for comet assay. Error bars are not shown if they are smaller than the size of markers.

References

    1. Kemp KC, Seema H, Saleh M, Le NH, Mahesh K, Chandra V, Kim KS, Environmental applications using graphene composites: water remediation and gas adsorption, Nanoscale 5 (8) (2013) 3149–3171. - PubMed
    1. Goenka S, Sant V, Sant S, Graphene-based nanomaterials for drug delivery and tissue engineering, J. Control. Release 173 (2014) 75–88. - PubMed
    1. Akhavan O, Ghaderi E, Toxicity of graphene and graphene oxide nanowalls against bacteria, ACS Nano 4 (10) (2010) 5731–5736. - PubMed
    1. Unfried K, Sydlik U, Bierhals K, Weissenberg A, Abel J, Carbon nanoparticle-induced lung epithelial cell proliferation is mediated by receptor-dependent Akt activation, Am. J. Physiol. Lung Cell. Mol. Physiol 294 (2) (2008) L358–L367. - PubMed
    1. Hussain S, Boland S, Baeza-Squiban A, Hamel R, Thomassen LCJ, Martens JA, Billon-Galland MA, Fleury-Feith J, Moisan F, Pairon J, Marano F, Oxidative stress and proinflammatory effects of carbon black and titanium dioxide nanoparticles: role of particle surface area and internalized amount, Toxicology 260 (1–3) (2009) 142–149. - PubMed

Publication types

LinkOut - more resources