Molecular characterization of the cytotoxic mechanism of multiwall carbon nanotubes and nano-onions on human skin fibroblast

Abstract

The increasing use of nanotechnology in consumer products and medical applications underlies the importance of understanding its potential toxic effects to people and the environment. Although both fullerene and carbon nanotubes have been demonstrated to accumulate to cytotoxic levels within organs of various animal models and cell types and carbon nanomaterials have been exploited for cancer therapies, the molecular and cellular mechanisms for cytotoxicity of this class of nanomaterial are not yet fully apparent. To address this question, we have performed whole genome expression array analysis and high content image analysis based phenotypic measurements on human skin fibroblast cell populations exposed to multiwall carbon nano-onions (MWCNOs) and multiwall carbon nanotubes (MWCNTs). Here we demonstrate that exposing cells to MWCNOs and MWCNTs at cytotoxic doses induces cell cycle arrest and increases apoptosis/necrosis. Expression array analysis indicates that multiple cellular pathways are perturbed after exposure to these nanomaterials at these doses, with material-specific toxigenomic profiles observed. Moreover, there are also distinct qualitative and quantitative differences in gene expression profiles, with each material at different dosage levels (6 and 0.6 microg/mL for MWCNO and 0.6 and 0.06 microg/mL for MWCNT). MWCNO and MWCNT exposure activates genes involved in cellular transport, metabolism, cell cycle regulation, and stress response. MWCNTs induce genes indicative of a strong immune and inflammatory response within skin fibroblasts, while MWCNO changes are concentrated in genes induced in response to external stimuli. Promoter analysis of the microarray results demonstrate that interferon and p38/ERK-MAPK cascades are critical pathway components in the induced signal transduction contributing to the more adverse effects observed upon exposure to MWCNTs as compared to MWCNOs.

Figure 1

Scanning electron microscopy (SEM) images and high-resolution transmission electron microscopy (HRTEM) images of carbon nanomaterials used in this study. (A) SEM image of multiwalled carbon nanotubes (scale bar = 200 nm). (B) SEM image of carbon nano-onions (scale bar = 200 nm). (C) HRTEM images of multiwalled carbon nanotubes (MWCNTs) (scale bar = 5 nm). (D) HRTEM images of multiwalled carbon nano-onions (MWCNO) (scale bar = 10 nm).

Figure 2

Cell viability measurements after treatment with carbon nanomaterials at cytotoxic doses. Cells were plated on 96-well plates, treated for 48 h, and then stained with Hoechst (nucleus stain for cell number indicator), YO-PRO 1 (apoptosis indicator) and PI (necrosis indicator). Plates were transported to KineticScan (KSR, Cellomics, Pittsburgh, PA) for image collection, then automated analysis was performed on the collected images. (A) The number of skin fibroblast cells per well 48 h after mock treatment with ethanol or treatment with either MWCNOs (NO) or nanotubes (NT). The numbers of low doses (0.6 μg/mL for MWCNO and 0.06 μg/mL for MWCNT) and high doses (6 μg/mL for MWCNO and 0.6 μg/mL for MWCNT) represent the nanomaterial concentration used for treatment. Bars represent the mean of cell numbers from 10 imaged view fields in 10 treated wells, and error bars represent a 95% confidence interval. Each nuclei imaged by the KSR was identified with the Cell Health Profiling software in the blue channel by Hoechst staining. (B) YO-PRO 1 is visualized in the green channel and PI is visualized in the red channel, where measurement such as dye intensity and area can be made using the Cell Health Profiling algorithm. Average intensity of YO-PRO 1 intensity and PI intensity of mock treated and treated skin fibroblasts at 48 h. The YO-PRO 1 intensity is proportional to apoptosis and the PI intensity correlates to necrosis. Bars represent the mean of cell numbers from eight treated wells and the error bars represent a 95% confidence interval. Data for lung fibroblast treated under the same condition are presented in Supporting Information Figure S1.

Figure 3

Measurement of cell proliferation after treatment with carbon nanomaterials at cytotoxic doses. Cells were plated on 96-well plates, treated, pulsed with BrdU, fixed, and then stained with anti-BrdU and PI. Plates were transported to the KSR for image collection and then automated analysis was performed on the collected images. (A) Images generated by the KSR. Channel 1 is images of PI stained nuclei, and this is used for cell identification, counting, and DNA content. Channel 2 represents BrdU staining, and this shows cells that have passed through the S-phase during the pulse with BrdU. The composite image is also shown. (B) Typical scatter plot of BrdU staining intensity versus PI intensity. This is used for calculating the number of cells in G0/G1, S, and G2/M phases. (C) Summary of cell cycle data for nanomaterial-treated cells as compared to controls. An average of 20 000 cells were measured for each treatment condition.

Figure 4

(A) Numbers of genes whose expression levels changed after treatment with carbon nanomaterials at cytotoxic doses. (B–E) Venn diagrams comparing numbers of genes that showed expression changes. Each Venn diagram is divided into three areas and labeled as I, II, and III. Area II is the overlapping area of two circles, representing commonly changed genes in both conditions. Area I and III represent genes that changed only in the condition specified in the circle. Bioconductor software was used to perform significance analysis to determine the difference between expression levels in treated sample, and the control sample possesses statistical significance. The empirical Bayesian model was used with Bonferroni’s multitest correction. The cutoff of p-values produced through the analysis was determined by at least 10 times less than the p-values of the smallest p-value of control probe sets on the chip. (B) Comparing different doses for the nano-onions. (C) Comparing different doses for the nanotubes. (D) Comparing different particles at low doses (0.6 μg/mL for MWCNO and 0.06 μg/mL for MWCNT). (E) Comparing different particles at high doses (6 μg/mL for MWCNO and 0.6 μg/mL for MWCNT).

Figure 5

Promoter analysis. The interaction matrix for the differentially expressed genes (horizontal) and transcription regulatory elements (vertical) in the up- and down-regulated gene sets at different dosage using different carbon nanoparticles. The PAINT software (Supporting Information) then computes p-values to look for the overrepresented TREs in the set of promoters analyzed in reference to all the genes in the PAINT database to generate filtered (p-value < 0.1) interaction matrixes. Individual elements of the matrix are colored by the significance p-values: over-representation in the matrix is colored in red. The brightest red represents low p-value (most significantly over-represented). Enriched transcription regulatory elements for the nanoparticle dataset.

Figure 6

A comparison of activated signal transduction networks for higher dose responses to carbon tubes and carbon onions. PathwayBuilder software (Arkin Group, LBNL) is used to analyze and create pathways differentially activated with the treatment matrix based on published literature.