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
. 2011 Mar 22;5(3):1805-17.
doi: 10.1021/nn102734s. Epub 2011 Feb 16.

Use of a high-throughput screening approach coupled with in vivo zebrafish embryo screening to develop hazard ranking for engineered nanomaterials

Saji George  1 , Tian Xia, Robert Rallo, Yan Zhao, Zhaoxia Ji, Sijie Lin, Xiang Wang, Haiyuan Zhang, Bryan France, David Schoenfeld, Robert Damoiseaux, Rong Liu, Shuo Lin, Kenneth A Bradley, Yoram Cohen, André E Nel
Affiliations

Use of a high-throughput screening approach coupled with in vivo zebrafish embryo screening to develop hazard ranking for engineered nanomaterials

Saji George et al. ACS Nano. .

Abstract

Because of concerns about the safety of a growing number of engineered nanomaterials (ENM), it is necessary to develop high-throughput screening and in silico data transformation tools that can speed up in vitro hazard ranking. Here, we report the use of a multiparametric, automated screening assay that incorporates sublethal and lethal cellular injury responses to perform high-throughput analysis of a batch of commercial metal/metal oxide nanoparticles (NP) with the inclusion of a quantum dot (QD1). The responses chosen for tracking cellular injury through automated epifluorescence microscopy included ROS production, intracellular calcium flux, mitochondrial depolarization, and plasma membrane permeability. The z-score transformed high volume data set was used to construct heat maps for in vitro hazard ranking as well as showing the similarity patterns of NPs and response parameters through the use of self-organizing maps (SOM). Among the materials analyzed, QD1 and nano-ZnO showed the most prominent lethality, while Pt, Ag, SiO2, Al2O3, and Au triggered sublethal effects but without cytotoxicity. In order to compare the in vitro with the in vivo response outcomes in zebrafish embryos, NPs were used to assess their impact on mortality rate, hatching rate, cardiac rate, and morphological defects. While QDs, ZnO, and Ag induced morphological abnormalities or interfered in embryo hatching, Pt and Ag exerted inhibitory effects on cardiac rate. Ag toxicity in zebrafish differed from the in vitro results, which is congruent with this material's designation as extremely dangerous in the environment. Interestingly, while toxicity in the initially selected QD formulation was due to a solvent (toluene), supplementary testing of additional QDs selections yielded in vitro hazard profiling that reflect the release of chalcogenides. In conclusion, the use of a high-throughput screening, in silico data handling and zebrafish testing may constitute a paradigm for rapid and integrated ENM toxicological screening.

PubMed Disclaimer

Figures

Figure 1
Figure 1. Heat map display of the HTS data
The raw data normalized by robust Z-score transformation was used to develop the heat map, using MeV software. The rows and columns in the heat map correspond to the dose range and exposure times, respectively, in each cell type. Blue colors indicate no harmful activity while yellow/red indicates a significant increase in cellular responsiveness. The responses are designated: (i) ROS = measurement of mitochondrial superoxide generation measured by MitoSox Red, (ii) MMP = perturbation of mitochondrial membrane potential as measured by JC1, (iii) [Ca]i = increased intracellular Ca2+ flux measured by Fluo-4, (iv) PI = measurement of membrane permeability by propidium iodide uptake. QD1 and ZnO NPs generated a significant increase (values ≥ +3) in robust z-scores in a dose and time-dependent manner. These particles generated sub-lethal and lethal cellular responses. By contrast, Pt, Ag, SiO2, Al2O3 and Au NPs generated sub-lethal effects only that are not accompanied by increased membrane permeability. These experiments were repeated three times with four replicates in each group. A complete description of the procedures and materials to conduct the HTS assay and data analysis appear in the Materials and Methods.
Figure 2
Figure 2. Single response assays for comparison to the HTS results
In order to identify potential false positive/negative results in the HTS assay, NPs were tested in traditional single parameter assays that reflect cellular ATP level and mitochondrial dehydrogenase activity (MTS assay). This adjunct screening confirmed the cytotoxicity of QD1 of ZnO. Noteworthy, nano-Pt also resulted in decreased ATP levels and a decrease in MTS activity, while SiO2 showed a slight decrease in ATP levels at the highest dose. This could mean that Pt may be potentially cytotoxic and that the SiO2 effects in the HTS assay could be either true mitochondrial perturbation or a false positive response due to the tendency of these particles to agglomerate at high doses. *values statistically significant from control values (p≤0.05), where each experiment was conducted three times with three replicates in each group. Error bars represent standard deviation from average value.
Figure 2
Figure 2. Single response assays for comparison to the HTS results
In order to identify potential false positive/negative results in the HTS assay, NPs were tested in traditional single parameter assays that reflect cellular ATP level and mitochondrial dehydrogenase activity (MTS assay). This adjunct screening confirmed the cytotoxicity of QD1 of ZnO. Noteworthy, nano-Pt also resulted in decreased ATP levels and a decrease in MTS activity, while SiO2 showed a slight decrease in ATP levels at the highest dose. This could mean that Pt may be potentially cytotoxic and that the SiO2 effects in the HTS assay could be either true mitochondrial perturbation or a false positive response due to the tendency of these particles to agglomerate at high doses. *values statistically significant from control values (p≤0.05), where each experiment was conducted three times with three replicates in each group. Error bars represent standard deviation from average value.
Figure 3
Figure 3. Evaluation of QD cytotoxicity due to differences in particle composition and tendency to shed chalcogenide ions
Three different QDs are being compared for their ability to induce toxicity in the HTS and MTS assays. These are: (i) QD1, which is a core/shell CdSe/ZnS particle from Sigma prepared in toluene, (ii) QD2 which is a core/shell CdSe/ZnS particles stabilized by mecaptoundecanoic acid in water; (iii) QD3 which is a core CdSe particles stabilized by mecaptoundecanoic acid in water. (A) ICP-MS analysis. QDs suspended in CDMEM and BEGM media were subjected to ultracentrifugation after 24 hrs and the supernatants were assayed for the presence of Cd, Se and Zn by ICP-MS (Perkin-Elmer SCIEX Elan DRCII). (B) Heat map representation of robust z-score transformed multiparametric HTS data comparing dose and time dependent toxicity as described in Figure 1. The abbreviations for the cellular responses are the same as in Figure 1. (C) MTS based cell viability assays in BEAS-2B and RAW 264.7 cells. The MTS assay was performed at increasing particle concentrations 24 hrs after their introduction. * values statistically significant from control values (p≤0.05), where each experiment was conducted three times with three replicates in each group. Error bars represent standard deviation from average value.
Figure 3
Figure 3. Evaluation of QD cytotoxicity due to differences in particle composition and tendency to shed chalcogenide ions
Three different QDs are being compared for their ability to induce toxicity in the HTS and MTS assays. These are: (i) QD1, which is a core/shell CdSe/ZnS particle from Sigma prepared in toluene, (ii) QD2 which is a core/shell CdSe/ZnS particles stabilized by mecaptoundecanoic acid in water; (iii) QD3 which is a core CdSe particles stabilized by mecaptoundecanoic acid in water. (A) ICP-MS analysis. QDs suspended in CDMEM and BEGM media were subjected to ultracentrifugation after 24 hrs and the supernatants were assayed for the presence of Cd, Se and Zn by ICP-MS (Perkin-Elmer SCIEX Elan DRCII). (B) Heat map representation of robust z-score transformed multiparametric HTS data comparing dose and time dependent toxicity as described in Figure 1. The abbreviations for the cellular responses are the same as in Figure 1. (C) MTS based cell viability assays in BEAS-2B and RAW 264.7 cells. The MTS assay was performed at increasing particle concentrations 24 hrs after their introduction. * values statistically significant from control values (p≤0.05), where each experiment was conducted three times with three replicates in each group. Error bars represent standard deviation from average value.
Figure 3
Figure 3. Evaluation of QD cytotoxicity due to differences in particle composition and tendency to shed chalcogenide ions
Three different QDs are being compared for their ability to induce toxicity in the HTS and MTS assays. These are: (i) QD1, which is a core/shell CdSe/ZnS particle from Sigma prepared in toluene, (ii) QD2 which is a core/shell CdSe/ZnS particles stabilized by mecaptoundecanoic acid in water; (iii) QD3 which is a core CdSe particles stabilized by mecaptoundecanoic acid in water. (A) ICP-MS analysis. QDs suspended in CDMEM and BEGM media were subjected to ultracentrifugation after 24 hrs and the supernatants were assayed for the presence of Cd, Se and Zn by ICP-MS (Perkin-Elmer SCIEX Elan DRCII). (B) Heat map representation of robust z-score transformed multiparametric HTS data comparing dose and time dependent toxicity as described in Figure 1. The abbreviations for the cellular responses are the same as in Figure 1. (C) MTS based cell viability assays in BEAS-2B and RAW 264.7 cells. The MTS assay was performed at increasing particle concentrations 24 hrs after their introduction. * values statistically significant from control values (p≤0.05), where each experiment was conducted three times with three replicates in each group. Error bars represent standard deviation from average value.
Figure 4
Figure 4. Use of SOMs to identify similarity patterns for NPs and cellular responses
(A) SOM defined by the distribution of NPs on a 2D grid that considers all response characteristics in both cell types. This SOM is generated by the integration of the entire data set to distribute NPs based on the biological response measurements. NPs showing similarity in their cytotoxicity responses cluster together. Noteworthy is the clustering of highly toxic NPs (ZnO and QD1) at moderate to high concentrations in clusters C1 and C2, while cluster C3 is comprised of Pt and SiO2 with cluster 4 incorporating most non-cytotoxic NPs. (B) SOM defined by the clustering of the various biological response parameters. This SOM is generated by integrating the entire data set to distribute the cellular responses to the entire set of NPs. Four clusters emerged from the analysis of the distribution of the various biological response parameters. Cluster C1 grouped mostly RAW 264.7 intracellular calcium flux and mitochondrial membrane depolarization. Cluster C2 grouped BEAS-2B calcium flux and PI uptake exclusively.
Figure 4
Figure 4. Use of SOMs to identify similarity patterns for NPs and cellular responses
(A) SOM defined by the distribution of NPs on a 2D grid that considers all response characteristics in both cell types. This SOM is generated by the integration of the entire data set to distribute NPs based on the biological response measurements. NPs showing similarity in their cytotoxicity responses cluster together. Noteworthy is the clustering of highly toxic NPs (ZnO and QD1) at moderate to high concentrations in clusters C1 and C2, while cluster C3 is comprised of Pt and SiO2 with cluster 4 incorporating most non-cytotoxic NPs. (B) SOM defined by the clustering of the various biological response parameters. This SOM is generated by integrating the entire data set to distribute the cellular responses to the entire set of NPs. Four clusters emerged from the analysis of the distribution of the various biological response parameters. Cluster C1 grouped mostly RAW 264.7 intracellular calcium flux and mitochondrial membrane depolarization. Cluster C2 grouped BEAS-2B calcium flux and PI uptake exclusively.
Figure 5
Figure 5. NP toxicity in zebrafish embryos
(A) Images of the zebrafish embryos exposed to Holtfreters medium with and without the NPs added at 15 μg/mL for 72 hpf. Note the gross morphological defects seen in nano-Ag treated embryos. The QD1 treatment resulted in the disintegration of embryo, while ZnO treatment inhibited embryo hatching. Zebrafish embryos exposed to increasing doses of NPs were also assessed for: (B) the hatching rate at 72 hpf, and (C) the mortality rate at 120 hpf. The average value was calculated for a total of 36 embryos from three experiments with twelve embryos in each group. * Values statistically significant from control (p≤0.05). Error bars represent standard deviation from average value.
Figure 5
Figure 5. NP toxicity in zebrafish embryos
(A) Images of the zebrafish embryos exposed to Holtfreters medium with and without the NPs added at 15 μg/mL for 72 hpf. Note the gross morphological defects seen in nano-Ag treated embryos. The QD1 treatment resulted in the disintegration of embryo, while ZnO treatment inhibited embryo hatching. Zebrafish embryos exposed to increasing doses of NPs were also assessed for: (B) the hatching rate at 72 hpf, and (C) the mortality rate at 120 hpf. The average value was calculated for a total of 36 embryos from three experiments with twelve embryos in each group. * Values statistically significant from control (p≤0.05). Error bars represent standard deviation from average value.
Figure 5
Figure 5. NP toxicity in zebrafish embryos
(A) Images of the zebrafish embryos exposed to Holtfreters medium with and without the NPs added at 15 μg/mL for 72 hpf. Note the gross morphological defects seen in nano-Ag treated embryos. The QD1 treatment resulted in the disintegration of embryo, while ZnO treatment inhibited embryo hatching. Zebrafish embryos exposed to increasing doses of NPs were also assessed for: (B) the hatching rate at 72 hpf, and (C) the mortality rate at 120 hpf. The average value was calculated for a total of 36 embryos from three experiments with twelve embryos in each group. * Values statistically significant from control (p≤0.05). Error bars represent standard deviation from average value.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Nel A, Xia T, Madler L, Li N. Toxic Potential of Materials at the Nanolevel. Science. 2006;311:622–627. - PubMed
    1. Nanotechnology Consumer Product Inventory. Project on Emerging Nanotechnology; Woodrow Wilson International Center for Scholars; Washington Dc: Available at http://www.nanotechproject.org/inventories/consumer/
    1. Service RF. Nanotechnology - Can High-Speed Tests Sort Out which Nanomaterials are Safe? Science. 2008;321:1036–1037. - PubMed
    1. Hartung T. Toxicology for the Twenty-First Century. Nature. 2009;460:208–212. - PubMed
    1. Council NR. Toxicity Testing in the 21st Century: A Vision and a Strategy. National Academy Press; Washington, D.C: 2007.

Publication types