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Effects of Graphene Oxide and Oxidized Carbon Nanotubes on the Cellular Division, Microstructure, Uptake, Oxidative Stress and Metabolic Profiles Xiangang Hu, Shaohu Ouyang, Li Mu, Jing An, and Qixing Zhou Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.5b02102 • Publication Date (Web): 21 Aug 2015 Downloaded from http://pubs.acs.org on August 25, 2015

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Environmental Science & Technology

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Effects of Graphene Oxide and Oxidized Carbon Nanotubes on the Cellular

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Division, Microstructure, Uptake, Oxidative Stress and Metabolic Profiles

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Xiangang Hu†, Shaohu Ouyang†, Li Mu‡, Jing An§, Qixing Zhou*, †

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†

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Education)/Tianjin Key Laboratory of Environmental Remediation and Pollution

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Control, College of Environmental Science and Engineering, Nankai University,

Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of

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Tianjin 300071, China.

11

‡

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China.

13

§

14

Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China.

Institute of Agro-environmental Protection, Ministry of Agriculture, Tianjin 300191,

Key Laboratory of Pollution Ecology and Environment Engineering, Institute of

15 16

ABSTRACT

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Nanomaterial oxides are common formations of nanomaterials in the natural

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environment. Herein, the nanotoxicology of typical graphene oxide (GO) and

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carboxyl single-walled carbon nanotubes (C-SWCNT) was compared. The results

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showed that cell division of Chlorella vulgaris was promoted at 24 h and then

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inhibited at 96 h after nanomaterial exposure. At 96 h, GO and C-SWCNT inhibited

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the rates of cell division by 0.08–15% and 0.8–28.3%, respectively. Both GO and C-

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SWCNT covered the cell surface, but the uptake percentage of C-SWCNT was 2-fold

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higher than that of GO. C-SWCNT induced stronger plasmolysis and mitochondrial

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membrane potential loss and decreased the cell viability to a greater extent than GO.

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Moreover, C-SWCNT-exposed cells exhibited more starch grains and lysosome

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formation and higher reactive oxygen species (ROS) levels than GO-exposed cells.

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Metabolomics analysis revealed significant differences in the metabolic profiles

ACS Paragon Plus Environment


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among the control, C-SWCNT and GO groups. The metabolisms of alkanes, lysine,

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octadecadienoic acid and valine was associated with ROS and could be considered as

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new biomarkers of ROS. The nanotoxicological mechanisms involved the inhibition

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of fatty acid, amino acid and small molecule acid metabolisms. These findings

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provide new insights into the effects of GO and C-SWCNT on cellular responses.

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.

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KEYWORDS: Graphene oxide; Carbon nanotube; Nanotoxicology; Phytotoxicity;

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ROS; Metabolism

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INTRODUCTION

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The dramatic development of carbon nanoscience and nanotechnology in recent years

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has offered numerous opportunities and innovative solutions in various fields and

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applications. Of the carbonaceous nanomaterials, carbon nanotubes and graphene

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have been more widely and rapidly developed compared with other materials.1-3

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Carbon nanotubes are commonly referred to as rolled up graphene sheets, and both

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allotropes have a meshwork of sp2-hybridized carbon atoms. However, it remains

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unknown which form is ecologically safer. Notably, carbon nanomaterials commonly

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form oxides in the natural environment; for example, pristine carbon nanotubes and

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graphene are transformed into carboxyl single-walled carbon nanotubes (C-SWCNT)

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and graphene oxide (GO) in aqueous solution under visible light irradiation,

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respectively.4-6 Herein, the nanotoxicology of GO and C-SWCNT is compared.

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Although a direct comparison of GO and C-SWCNT phytotoxicity has not been

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reported, both materials have adverse effects on organisms. C-SWCNT inhibit growth

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and photosynthetic activity in alga to a greater extent than pristine carbon nanotubes.7

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Similarly, GO damages cellular structures and chlorophyll synthesis in wheat.6 It has

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been proposed that carbonaceous nanomaterials aggregate on cell surfaces and hinder

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cell hydraulic conductivity and water availability, thus reducing transpiration and

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affecting plant development.8 In contrast to animal cells, plant cells have a

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semipermeable cell wall that serves as an extra protective barrier against


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nanomaterials.9,10 Because cell wall pores have a diameter of less than 10 nm, the

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internalization of large carbonaceous nanomaterials is still a controversial issue.11,12 In

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the present work, C. vulgaris was used as a model organism, and a Raman

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spectrometer was employed to identify the internalization of GO and C-SWCNT. In

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addition, the microstructural damage and cell viability defects in algal cells were

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analyzed using electron microscopy and fluorescent probes.

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Phytotoxicity tests of nanomaterials typically involve examinations of plant

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development, antioxidase activities, and gene or protein alterations.13,14 In contrast to

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genes and proteins, metabolites serve as direct signatures of biochemical activity and

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are readily correlated with cellular biochemistry and biological phenomena.15-17 In

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addition, alterations in reactive oxygen species (ROS) levels are a common indicator

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of nanotoxicity.18 Understanding the metabolic mechanisms of ROS generation is

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critical for controlling nanotoxicity through the regulation of the corresponding

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metabolic pathways. However, the mechanisms of ROS generation by nanomaterials

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at a metabolomic level remain unclear. In the present study, we analyzed the ROS

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levels and mitochondrial membrane potential losses in algal cells. Moreover, the

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comparative metabolomics of GO and C-SWCNT were examined, relationships

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between ROS levels and metabolites were established, alterations in key metabolic

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pathways were identified, and nanotoxicological mechanisms were elucidated.

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MATERIALS AND METHODS

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Characterization of materials

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GO (product number XF002-1) and C-SWCNT (product number S07) were purchased

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from the Nanjing XFNANO Materials Tech Co., Ltd., China. The morphology of GO

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and C-SWCNT was examined using field emission transmission electron microscopy

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(JEM-2010 FEF, JEOL, Japan) and atomic force microscopy (Nanoscope IV, VEECO,

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USA). The size distribution and zeta potential of the nanomaterials were measured

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using a ZETAPALS/BI-200SM instrument equipped with a 30-mW, 635-nm laser

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(Brookhaven Instruments Corporation, USA). The surface chemistry was analyzed via

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X-ray photoelectron spectroscopy (XPS). XPS measurements were performed using



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an Axis Ultra XPS system (Kratos, Japan) with a monochromatic Al Kα X-ray source

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(1486.6 eV). The XPS spectra were analyzed using Casa-XPS V2.3.13 software.

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Nanomaterials were dispersed in algal medium, and the redox potential of these

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particles was measured using an oxidation-reduction potentiometer (Sinomeasure,

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China). The hydrodynamic diameters and ζ-potential of the nanomaterials in algal

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medium were obtained using a dynamic light scattering machine equipped with a 30-

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mW, 657-nm laser (ZetaPALS, Brookhaven Instruments Corporation, USA). Electron

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paramagnetic resonance (EPR) was performed to measure unpaired electrons. All X-

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band EPR spectra were collected at room temperature (296 K) using a Magnettech

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MiniScope 400 EPR spectrometer operated at a microwave frequency of 9.4 GHz and

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a magnetic field modulation frequency of 100 kHz. The spectrometer was controlled

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using MiniScope Control software. We used 2,6,6-tetramethyl-1-piperidinyloxy

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(TEMPO) as an unpaired electron probe. The samples were individually placed in

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quartz EPR tubes. Before the samples were loaded, the quartz EPR tubes were

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thoroughly washed with ultrapure water and subsequently dried.

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Cultivation of algal cells

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C. vulgaris was obtained from the Freshwater Algae Culture Collection at the Institute

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of Hydrobiology, Wuhan, China. The algae were cultured in an illumination incubator

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(Shanghai Bank Equipment, LRH-250 Gb, China) at 24.0 ± 0.5°C and 80% humidity.

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The current and future concentrations of GO or C-SWCNT in the natural environment

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are unknown. To compare the reported concentrations of carbonaceous nanomaterials

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in toxicological tests,7,19 C. vulgaris were exposed to 0.01–10 mg/L GO and C-

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SWCNT in 250 mL glass flasks containing 100 mL of BG-11 medium. The

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components of BG-11 medium are listed in Table S1. The initial cell density was 6.48

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× 104 cells/mL. Algal cells exposed to nanomaterials were counted using a cell

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counter 24, 48, 72 and 96 h (CASY TT, Innovatis, Germany). Chlorophyll a was

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measured using a UV–vis spectrophotometer (TU-1900, Beijing Purkinje General

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Instrument, China), as previously described.20 To detect alterations in the DNA

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concentration, the algal suspension was washed three times using BG-11 medium and

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then centrifuged at 9000 g for 5 min. The pellet was collected and analyzed using a


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DNeasy Plant Mini Kit (product number 69104, QIAGEN, China) according to the

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manufacturer’s instructions.

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Electron microscopy observation

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For scanning electron microscopy (SEM), 5-mL algal suspensions were centrifuged,

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chemically fixed for 2 h using 2.5% glutaraldehyde, washed three times using BG-11

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medium, and postfixed in 1% osmium tetroxide for 2 h. Subsequently, the samples

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were dehydrated in a graded ethanol series (30%, 50%, 70%, 80%, 90%, 95% and

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100%), washed with tert-butyl alcohol and dried under vacuum. Images were obtained

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using SEM (SU8010, Hitachi, Japan). For cellular ultrastructure observation, the algal

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suspensions were centrifuged, washed, fixed, postfixed and dehydrated as described

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above for the SEM sample preparation, and they were subsequently embedded in

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epoxy resin. Ultrathin sections (70–90 nm) of algal cells were obtained using a

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diamond knife (EM FC7, Leica, Germany), followed by staining with uranyl acetate

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and lead citrate for 15 min. The samples were observed using a transmission electron

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microscope (TEM) (HT7700, Hitachi, Japan).

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Raman spectra

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Raman spectra (RS) were generated to analyze the surface chemistry of the cells. The

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cells were washed three times with fresh BG-11 medium, placed on glass slides, and

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analyzed using a Raman spectrometer (Renishaw plc, UK) with excitation at 780 nm

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from a diode-pumped solid-state (DPSS) laser (DXR, Thermo Scientific, USA).

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Subsequently, RS were generated to quantify the nanomaterials in cells.21,22 Prior to

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quantifying GO and C-SWCNT in cells, a homogeneous algal matrix was obtained

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using a cell disruptor (Sonifier 250A, Branson, China). GO and C-SWCNT were

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spiked into the cellular matrix to prepare standard curves. The water in the samples

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was removed through lyophilization. The specific G bands of GO and C-SWCNT

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were recorded through Raman microscopy using a 780-nm laser (DXR, Thermo

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Scientific, USA).

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Cell viability

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Cell viability was determined using a fluorescein diacetate (FDA) probe. The algal

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cell suspension was centrifuged and washed three times with BG-11 medium.



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Subsequently, 1 mmol/L FDA was incubated with algal cells for 30 min under dark

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conditions at room temperature. The samples were centrifuged and washed three

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times with BG-11 medium. The fluorescence intensity was measured on a

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fluorescence microscope (Olympus IX71, Olympus, Japan) with an excitation

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wavelength of 485 nm and an emission wavelength of 521 nm. The fluorescence

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images were obtained on a 100 W light source intensity, a 1.3 numerical aperture, a

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100 × objective, a 60 s exposure time and a 1.0 detector gain. The pixel intensity

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measurements were taken overall field of view (whole image).

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ROS and superoxide dismutase

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2′,7′-Dichlorodihydrofluorescein diacetate (DCFH-DA) was used as a fluorescent

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probe to measure the intracellular ROS. Briefly, algal cells were centrifuged and

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washed three times with BG-11 medium. The algal suspension was incubated with 10

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μmol/L DCFH-DA in the dark at 25°C for 30 min, followed by washing three times

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with BG-11 medium. The fluorescence intensity was measured using a fluorescence

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spectrophotometer (LS55, Perkin Elmer, USA) with an excitation wavelength of 485

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nm and an emission wavelength of 530 nm. The relative ROS level was represented

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as the fluorescence intensity ratio of the exposure group to the control group.

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Superoxide dismutase (SOD) activity was determined using a SOD assay kit (A001-2,

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Nanjing JianCheng Bioengineering Institute, China). The assay was conducted

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according to the manufacturer’s instructions, and the absorbance was read at 450 nm

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using a UV–vis spectrophotometer (TU-1900, Beijing Purkinje General Instrument,

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China).

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Mitochondrial membrane potential

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The algal suspension was centrifuged, and the pellets were washed three times with

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BG-11 medium. Subsequently, the cell pellets were incubated with 10 mmol/L JC-1

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(tetrachloro-tetraethyl benzimidazol carbocyanine iodide) at 37°C for 30 min in the

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dark. Before observation, the algal cells were washed three times with BG-11

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medium. The JC-1-stained algal cells were cultivated in BG-11 medium and observed

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using fluorescence microscopy (Olympus IX71, Olympus, Japan). The double-

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excitation wavelengths were 485 nm and 521 nm, and the corresponding green and


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red fluorescence levels were detected at 530 nm and 590 nm. Mitochondrial

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membrane potential loss was quantified as the ratio of red to green fluorescence

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intensity, and the relevant analysis was performed using Image J software.

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Metabolic profile

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The metabolites were analyzed through gas chromatography-mass spectrometry

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(GC−MS), and samples were prepared using the derivatization method. Cell

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metabolism was terminated at 96 h using liquid nitrogen, and subsequently, the cell

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wall/membrane was lysed through repeated freeze-thawing using liquid nitrogen. The

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metabolites were extracted from the algal matrix using a methanol:chloroform:water

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solution (2 mL, 2.5:1:1 volume ratio) via ultrasound (300 W, 10 min) in an ice bath,

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followed by centrifugation to collect the supernatant. The pellet was extracted,

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centrifuged again and mixed with the first supernatant. Subsequently, water (500 μL)

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was added, and the mixture was centrifuged at 5000 g for 3 min. Methanol and water

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were removed from the upper layer via nitrogen blow-off and lyophilization,

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respectively. The lower layer of chloroform was also removed via nitrogen blow-off.

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Methoxamine hydrochloride (20 mg/mL, 50 μL) and N-methyl-N-(trimethylsilyl)

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trifluoroacetamide (80 μL) were used as derivatives. The samples (1 μL) were

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injected into the GC column in split mode (1:5). The GC (Agilent 6890N, Agilent,

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USA) was linked to a quadrupole MS (Agilent 5973, Agilent, USA). Metabolite

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separation was conducted on a DB-5 MS capillary column (30 m, 0.25 mm i.d., 0.25

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mm film thickness). The injection temperature was 230°C, and the transfer line and

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ion source were set at 250°C. The spectrometer was operated in electron-impact

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mode. The detection voltage was 2100 V. The full scan range was from 60 to 800

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amu. Helium was used as the carrier gas at a constant flow rate of 2 mL/min. The

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oven temperature was maintained at 80°C for 2 min and subsequently increased at a

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rate of 15°C/min to 320°C, with holding for 6 min. The metabolites were identified

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using the NIST 08 library.

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Statistical analysis

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All experiments were performed at least in triplicate, and the results are presented as

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the means ± standard deviation, except for the specific annotation. Differences were



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regarded as significant at P < 0.05. The data were analyzed using one-way analysis of

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variance (ANOVA) and compared using Tukey’s test. Orthogonal partial least squares

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discriminant analysis (OPLS-DA) was performed using SIMCA-P 11.5 software. The

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thermal map was drawn using MeV 4.8.1 software. The default distance metric for

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hierarchical clustering (HCL) was the Pearson correlation, and the linkage method

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selection was achieved through average linkage clustering.

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RESULTS and DISCUSSION

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Nanomaterial characteristics

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Given that nanomaterial toxicity is determined based on physical properties, the

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morphology, ζ-potential, relative size, surface chemistry and chemical reactivity of

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GO and C-SWCNT were analyzed. GO and C-SWCNT presented nanosheet and

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nanotube morphologies, respectively, as shown in Figures S1 and S2. The lateral

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length and thickness of GO were approximately 0.5–5 μm and 0.8–1.2 nm,

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respectively. The outer diameter, inner diameter and length of C-SWCNT were

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approximately 1–2 nm, 0.8–1.6 and 0.5–3 μm, respectively. To directly compare the

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sizes of GO and C-SWCNT, the relative hydrodynamic diameters of the

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nanomaterials were measured using dynamic light scattering based on the zero-

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dimension spherical particle model. As shown in Figure S3a, the relative

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hydrodynamic diameters of GO and C-SWCNT were 295–825 nm and 396–712 nm,

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respectively. The ζ-potential was used to study the dispersion of nanomaterials. As

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shown in Figure S3b, the ζ-potential of both materials decreased with increasing pH.

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At the environmentally relevant pH range of 5–11, the ζ-potentials of GO and C-

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SWCNT were similar and presented negative charges. The surface chemistry of

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nanomaterials controls their dispersion and direct interactions with cells. The results

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for XPS, shown in Figure S4, showed that the spectrum of GO comprised 67.2% C1s,

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30.4% O1s, and 2.4% S2p (based on the percentages of atoms). The spectrum of C-

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SWCNT comprised 62.7% C1s, 29.4% O1s, 7.2% Na1s, and 0.7% Cl2p. The similar

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ratios of C1s to O1s in GO and C-SWCNT are consistent with the dispersity of these

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materials, as shown in Figure S3b.


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In Figure S3b, limited amounts of S, Na and Cl were obtained during material

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fabrication. It has been suggested that the impurities in graphene and carbon

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nanotubes influence the redox properties of these compounds.23 Nanomaterials with

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redox potentials higher or lower than those of biologically active redox couples will

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disturb the redox homeostasis in vivo and induce serious cellular responses.24 In

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Figure S5a, the redox potentials of GO and C-SWCNT in algal medium were similar,

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ranging from 109–385 mV and from 133–247 mV, respectively. To further explore the

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chemical activity of the nanomaterials, their unpaired electrons were studied.

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Unpaired electrons influence the purity of nanomaterials and directly affect the

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chemical activity and nanotoxicity of these materials.25,26 To measure the unpaired

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electrons of the nanomaterials, EPR was performed, using TEMPO as an unpaired

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electron probe. As shown in Figure S5b and S5c, GO exerted a limited influence on

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the EPR signals and slightly reduced these signals, which was consistent with the

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results presented in a previous work.27 In contrast, C-SWCNT at 10 mg/L slightly

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promoted EPR signals. Compared with ζ-potentials, surface chemistry and chemical

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activities, morphology may be more responsible for the difference between GO and

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C-SWCNT.

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Cell division

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The initial number of cells (6.48 × 104/mL) increased after 24 h, as shown in Figure

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S6a. During this period, cell division was slightly increased by the nanomaterials in a

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concentration-dependent manner. At 48 h, as shown in Figure S6a, the number of cells

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continued to increase, while cell division was disturbed in response to the

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nanomaterials. Specifically, the cell number increased when cells were exposed to 0.1

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and 1 mg/L GO for 48 h; however, cells exposed to 10 mg/L GO did not show

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significant differences compared with the control. At 72 h, as shown in Figure S6b,

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the nanomaterials increased cell division, except at the highest concentration of 10

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mg/L. The inhibitory effects were obvious at 96 h, with 0.08–15% and 0.8–28.3%

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inhibition for GO and C-SWCNT, respectively, compared with the control. Notably, at

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1 and 10 mg/L, C-SWCNT induced more obvious inhibition than GO. The above



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results showed that the tested nanomaterials first promoted and then inhibited algal

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cell division, and C-SWCNT led to more remarkable inhibition of cell division than

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GO after 48 h. Given that DNA replication is critical for cell growth, DNA

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concentrations were investigated, as shown in Figure S7. At the lowest concentration

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(0.1 mg/L), GO and C-SWCNT did not significantly inhibit DNA replication

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compared with the control, while both nanomaterials inhibited DNA replication at the

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highest concentration tested (10 mg/L). At the intermediate concentration (1 mg/L),

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DNA replication was significantly inhibited by C-SWCNT.

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Modification of the cellular surface

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As shown in Figure S8a–c, the diameters of the cells were approximately 4–5 μm in

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all images. In the control group, shown in Figure S8a, irregular wrinkles were

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distributed on the surfaces of the cells, forming lateral grooves of approximately 0.5–

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1 μm in length. In the GO and C-SWCNT groups, shown in Figures S8b and S8c,

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foreign structures likely covered the cell surface, and the grooves were filled and

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invisible, as denoted with red arrows. In addition, some cells exposed to C-SWCNT

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were completely damaged, as denoted with yellow arrows in Figure S8c. To clarify

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the chemical composition of the foreign structures covering the cell surface in Figure

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S8b and S8c, RS was performed, as shown in Figure S8d. The typical D and G peaks

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of carbonaceous nanomaterials centered at 1312 cm-1 and 1585 cm-1, respectively,

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were detected on cells exposed to GO and C-SWCNT, indicating that both carbon

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nanomaterials were adsorbed onto the cells. GO and C-SWCNT with large specific

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surfaces have C=C and oxygen/hydrogen-containing groups and are easily adsorbed

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onto cells via π-π stacking, hydrogen bonds or electrostatic interactions.28

293 294

Cellular ultrastructure and nanomaterial uptake

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To compare the damage to the cellular ultrastructure between cells exposed to GO and

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those exposed to C-SWCNT, TEM was performed, as shown in Figure 1a–c. The

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ultrastructural morphology of the control cells was not damaged, as the cell wall,

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plasma membrane, chloroplast, nucleus and other cytoplasmic compartments were


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intact. Two apparent physiological changes in cells exposed to GO and C-SWCNT

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were plasmolysis and increases in the number of starch grains and the number of

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lysosomes. Shrinkage of the cytoplasm contributed to plasmolysis, as indicated by the

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irregular morphology of the plasma membrane edges (the metabolic mechanisms of

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plasma membrane damage are explored in the last section of this work). The

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shrinkage of the cytoplasm in C-SWCNT-exposed cells was more intense than that in

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GO-exposed cells. Furthermore, C-SWCNT entered into the space created by

306

plasmolysis and the cytoplasm, as indicated by green and yellow arrows, respectively.

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A significantly large amount of GO was not observed in the algal TEM images (n =

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15), although a small amount of GO might have entered the cells (the uptake of GO

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and C-SWCNT is quantified in the next section). The increase in the number of starch

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grains and the number of lysosomes was considered a self-defense strategy in these

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cells,29,30 and the increase in the number of lysosomes was remarkably observed only

312

in C-SWCNT-exposed cells. Moreover, thylakoid structures were obscured in GO-

313

and C-SWCNT-exposed cells, demonstrating the destruction of the chloroplasts.

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RS were used to identify and quantify GO and C-SWCNT in algal cells.21,22 As

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shown in Figure 1d, the typical G band from the sp2 structure of C-SWCNT was

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identified in both the algal matrix spiked with C-SWCNT and in the samples,

317

confirming the uptake of C-SWCNT in the TEM image. In GO-exposed cells, the G

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band was also detected, but the peak shapes were influenced by carbohydrates. A

319

more obvious influence of carbohydrates was observed in GO-exposed cells, likely

320

reflecting the fact that carbohydrates can more readily adhere to nanosheets of GO

321

than to C-SWCNT.31 Standard curves for the quantification of GO and C-SWCNT in

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cells were prepared through the detection of nanomaterials spiked in the algal matrix

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using RS.21,22 The concentrations of GO and C-SWCNT were 2.66 and 9.51 mg/g,

324

respectively, in alga when the cells were exposed to 10 mg/L GO or C-SWCNT. The

325

uptake percentages (ratios of nanomaterial mass in cells to the total nanomaterial

326

mass) of GO and C-SWCNT were 11% and 26%, respectively. These results directly

327

confirm that C-SWCNT cellular uptake occurs more readily than GO uptake.



328

The TEM images illustrate the endocytosis pathway of C-SWCNT across the

329

biological membrane, denoted as yellow arrows in Figure 1c. In addition to

330

endocytosis, the enhancement of diffusion due to cell membrane damage was

331

considered an additional pathway for nanomaterial translocation across the cell

332

membrane.32,33 Plasmolysis and shrinkage of the cytoplasm in the TEM images was

333

associated with an dncrease in cell viability in C-SWCNT-exposed cells. Cell viability

334

was analyzed, as shown in Figure S9. There was no significant difference between the

335

controls and cells exposed to GO, except at 1 mg/L. In contrast, the fluorescence

336

intensity significantly increased by 12.5% and 45.7% upon exposure to 1 and 10 mg/L

337

of C-SWCNT, respectively, demonstrating the remarkable decrease in cell viability.

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These results are consistent with the uptake of nanomaterials.

339 340

Oxidative stress

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As shown in Figure 2a, both GO and C-SWCNT significantly promoted the

342

generation of ROS in the range of 0.01–10 mg/L. The fluorescence intensities of GO

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and C-SWCNT were 15.5–52.1% and 29.0–100.9% higher than the control,

344

respectively. At the tested concentration range of 0.01–10 mg/L, C-SWCNT induced

345

significantly higher ROS levels than GO. SOD is a critical antioxidant enzyme that

346

maintains redox balance in vivo. As presented in Figure 2b, there were no significant

347

differences in SOD activity between the control and GO-exposed cells, except at the

348

higher concentrations of 1 and 10 mg/L. In contrast, C-SWCNT significantly

349

enhanced SOD levels at concentrations from 0.01 to 10 mg/L. The up-regulation of

350

SOD levels was consistent with an increase in ROS induced in response to exposure

351

to nanomaterials. It has been suggested that a high level of oxidative stress influences

352

the biosynthesis of chlorophyll a.34 However, there was no significant difference in

353

the chlorophyll a contents in the tested groups, except for the group exposed to C-

354

SWCNT at 10 mg/L, which showed a significant reduction in chlorophyll a content.

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Mitotoxicity is a pathway for increasing oxidative stress.35 The results of

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mitochondrial membrane potential loss are presented in Figure 2d–g. Compared with

357

the control, the ratios of red to green fluorescence intensity significantly decreased by


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11.1% (P = 0.024) and 30.5% (P < 0.01) in response to GO and C-SWCNT exposure,

359

respectively, indicating that C-SWCNT triggered a greater loss of mitochondrial

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membrane potential than GO.

361 362

Metabolic profile

363

In the fields of nanotoxicology and nanomedicine, the potential unique benefits of

364

applying metabolomics have only recently been recognized.36,37 To determine the

365

effects of GO and C-SWCNT exposure on the metabolic profile, a total of 66

366

metabolites were analyzed using GC-MS, as shown in Tables S2 and S3. Compared

367

with previous metabolic analyses (e.g., 1H NMR technology), GC-MS with

368

derivatization is effective for analyzing metabolites in microalgae.38,39 The identified

369

metabolites were involved in major metabolic pathways, including carbohydrate,

370

amino acid, fatty acid, urea and small molecule acid metabolic pathways. The HCL

371

algorithm is a powerful approach for grouping metabolites based on similarities in

372

their components. HCL was performed with average linkage and Pearson correlation

373

analyses, and the results are summarized in the dendrogram shown in Figure 3, in

374

which the pattern of the branches reflects the relatedness of the samples. Using HCL

375

analysis, the samples were divided into two clusters: control/GO0.01/C-SWCNT0.01

376

and GO0.1/GO1/GO10/C-SWCNT0.1/C-SWCNT1/C-SWCNT10. The latter cluster

377

was divided into two sub-clusters: GO0.1/GO1/GO10 and C-SWCNT0.1/C-

378

SWCNT1/C-SWCNT10. HCL analysis supported distinctions in the metabolic

379

profiles among the control, GO and C-SWCNT groups. Furthermore, ANOVA,

380

followed by Tukey’s test, suggested that the metabolic profiles of GO10, C-

381

SWCNT0.1, C-SWCNT1 and C-SWCNT10 were significantly different from that of

382

the control. The above analysis suggested that C-SWCNT exerted a stronger influence

383

on the algal metabolic profile compared with GO.

384

The results shown in Figure 2a suggest that the level of ROS is a sensitive indicator

385

of GO and C-SWCNT cytotoxicity. To further examine the relationships between

386

ROS and metabolic disturbance, OPLS-DA modeling was conducted using ROS as a

387

Y variable and metabolites as X variables. As shown in Figures 3 and S10, 13 of the



388

66 metabolites, labeled with “+”, exhibited a positive coefficient CS (CoeffCS),

389

indicating that these metabolites make positive contributions to the generation of

390

ROS. The remaining 53 metabolites, labeled with “-”, make negative contributions to

391

the generation of ROS. The VIP (variable importance in the projection) plot in Figure

392

S11 summarizes the contributions of the X variables (metabolites) to the Y variable

393

(ROS). The metabolites labeled with a red “+” in Figure 3, including butylated

394

hydroxytoluene, alkane, lysine and propanoic acid, exhibited VIP values greater than

395

1 and made significant positive contributions to ROS generation. The metabolites

396

labeled with a red “-” in Figure 3, including octadecadienoic acid, aspartic acid,

397

valine, butanedioic acid, isoleucine and linolenic acid, showed VIP values greater

398

than 1.5 and made significant negative contributions to ROS generation. The high-

399

VIP metabolites could be considered new biomarkers of ROS levels in future studies.

400

ANOVA followed by Tukey’s test showed that the metabolic profiles of the

401

GO10, C-SWCNT0.1, C-SWCNT1 and C-SWCNT10 groups were significantly

402

different from that of the control group. Metabolites that were upregulated or

403

downregulated in the four exposure groups compared with the control group are

404

denoted as blue (GO) and red (C-SWCNT) arrows in Figure 4. Both GO and C-

405

SWCNT reduced the levels of most fatty acids, urea, amino acids and small molecule

406

acids. It has been suggested that the downregulation of amino acid metabolism is

407

associated with the enhancement of oxidative stress.40,41 The downregulation of

408

glycine, serine and valine is consistent with the results shown in Figure 2a at the

409

metabolic level. The metabolic decrease in unsaturated fatty acids is associated with

410

the deterioration of membrane fluidity and osmotic stress;42 thus, in our study, it is

411

likely that plasmolysis was enhanced and cell viability was reduced, as shown in

412

Figures 1a–c and S8. Inositol is also an important compound in the cell membrane.

413

The levels of inositol increased and decreased in the GO and C-SWCNT groups,

414

respectively, which is consistent with the enhanced plasmolysis and the decreased cell

415

viability in C-SWCNT-exposed cells. With the exception of lysine, all components of

416

the urea cycle were inhibited by GO and C-SWCNT. As a result, the biosynthesis of


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417

relevant amino acids and other nitrogen-containing compounds associated with cell

418

division could be affected, as shown in Figure S6b.43

419

As shown in Figure S6, C-SWCNT stimulate cell growth at earlier stages, and this

420

is especially obvious at 48 h. A similar phenomenon has been reported for TiO2

421

nanoparticles; however, the relevant mechanisms are unclear.44 To examine the

422

nanotoxicology and possible mechanisms of action of GO and C-SWCNT, oxidative

423

stress (ROS level) and metabolism were investigated at 48 h, as shown in Figures S12

424

and S13. At 1 and 10 mg/L, both GO and C-SWCNT significantly increased the levels

425

of ROS in algal cells, while both nanomaterials, especially C-SWCNT, stimulated cell

426

growth. These results imply that other toxicity mechanisms might exist. Secondary

427

metabolites not only counteract environmental stresses but are also part of normal

428

growth and developmental processes.45 Fatty acids have an antioxidant capacity that is

429

attributed to their electron donating ability.46 The levels of secondary metabolites

430

(coronene and lanostane) and fatty acids (hexadecanoic acid) are increased by

431

nanomaterials, especially C-SWCNT, which likely played roles in the stimulation of

432

cell growth.

433

Metabolomics can provide insights into genotypic and environmental effects.47,48

434

The primary objective of metabolic analysis is to identify differences in metabolites,

435

establish relationships between metabolic alterations and biological responses, and

436

discover the underlying metabolic mechanisms of biological responses.49 However,

437

relevant information is rare in the literature. In the present work, we used a

438

metabolomics strategy to evaluate the cytotoxicity of nanoparticles, screen new

439

biomarkers of nanotoxicity, and understand the underlying molecular mechanisms of

440

nanotoxicology.

441 442 443 444 445 446



447

ASSOCIATED CONTENT

448

Supporting Information

449

Composition of BG-11 medium (Table S1), metabolites of C. vulgaris (Tables S2 and

450

S3), nanomaterial characterization (Figures S1-S5), algal reproduction (Figure S6),

451

cellular surface modifications (Figure S7 and S8), cell viability (Figure S9) and

452

metabolic analysis (Figure S10 and S13). This information is available free of charge

453

via the Internet at http://pubs.acs.org/.

454 455

AUTHOR INFORMATION

456

Corresponding author

457

* E-mail: [email protected] (Q.Z). Telephone: +86-022-23507800; fax: +86-

458

022-66229562.

459 460

Notes

461

The authors declare no competing financial interests.

462 463

ACKNOWLEDGMENTS

464

This work was financially supported by the Ministry of Education of China as an

465

innovative team project (grant no. IRT 13024), the National Natural Science

466

Foundation of China (grant nos. 31170473, 21037002, 21307061 and 21407085), the

467

Tianjin Natural Science Foundation (grant no. 14JCQNJC08900), the Specialized

468

Research Fund for the Doctoral Program of Higher Education of China (grant no.

469

2013003112016) and the Postdoctoral Science Foundation of China (grant no.

470

2014M550138).

471 472

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620 621 622 623 624 625 626



627

Figure Legends

628

Figure 1. Damage to the cellular ultrastructure and uptake of nanomaterials at 96 h.

629

Transmission electron microscopy images (a–c) and Raman spectra (d). a, Algal cells

630

that were not exposed to nanomaterials; b, algal cells exposed to GO at 10 mg/L; c,

631

algal cells exposed to C-SWCNT at 10 mg/L. The red double arrows denote

632

plasmolysis. The green and yellow arrows denote C-SWCNT located outside and

633

inside the plasma membrane, respectively. The scale bars in a–c are 1 μm. Cw, cell

634

wall; Pm, plasma membrane; N, nucleus; Chl, chloroplast; S, starch grain; Thy,

635

thylakoid; L, lysosome; Pc, pyrenoid center; Psp, pyrenoid starch plate. In the Raman

636

spectra, St represents nanomaterials spiked in the algal matrix for the preparation of

637

standard curves. Sa represents nanomaterials in the sample.

638 639

Figure 2. Oxidative stress of cells exposed to nanomaterials at 96 h. a, Relative levels

640

of reactive oxygen species (ROS) detected using 2′,7′-dichlorodihydrofluorescein

641

diacetate (DCFH-DA) staining; b, relative levels of superoxide dismutase (SOD)

642

activity; c, concentrations of chlorophyll a; d–g, mitochondrial membrane potential

643

loss analyzed by fluorescence microscopy; d, control; e, cells exposed to GO at 10

644

mg/L; f, cells exposed to C-SWCNT at 10 mg/L; f, red to green fluorescence intensity

645

ratios for nanomaterials at 10 mg/L. The black and red asterisks denote significant

646

differences at p < 0.05 (n = 3, indicates three independent sample replicates)

647

compared with the control and GO groups, respectively.

648 649

Figure 3. Metabolic analysis of algal cells exposed to graphene oxide (GO) and

650

single-walled carbon nanotubes (C-SWCNT) at 96 h. The heat map of the metabolites

651

represents the relative levels of metabolites, and cluster analysis of the metabolites

652

was conducted using the hierarchical clustering (HCL) model. The asterisks represent

653

significant differences (P < 0.05) compared with the control. “+” and “−” indicate the

654

positive and negative correlations of metabolites with ROS levels, respectively, using

655

OPLS-DA model analysis. The metabolites indicated with red “+” and “−” have VIP


Page 22 of 28

Page 23 of 28


656

values greater than 1 and 1.5, respectively. OPLS-DA, orthogonal partial least squares

657

discriminant analysis; VIP, variable importance in the projection.

658 659

Figure 4. Effects of graphene oxide (GO) and single-walled carbon nanotubes (C-

660

SWCNT) on the main metabolic pathways of algal cells at 96 h. The metabolic

661

alterations labeled with blue and red arrows were determined based on comparisons of

662

the experimental groups (GO10, C-SWCNT0.1, C-SWCNT1 and C-SWCNT10) with

663

the control. The metabolic profiles of GO10, C-SWCNT0.1, C-SWCNT1 and C-

664

SWCNT10 were significantly different from the control group. The directions of the

665

blue (GO) and red (C-SWCNT) arrows represent the upregulation or downregulation

666

of the metabolites compared with the control. The black solid and dotted arrows

667

represent direct and indirect reactions, respectively.

668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685



Figures

686 687

688 689

Figure 1.

690 691 692 693 694 695 696 697 698 699 700 701 702 703


Page 24 of 28

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704

705 706

Figure 2.

707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724



725 100000

1700000

﹡﹡ ﹡﹡

Control GO0.01 C-SWCNT0.1 GO0.1 GO1 GO10 C-SWCNT0.1 C-SWCNT1 C-SWCNT10

0

-

+ + + + + + + + + + + + +

726 727

Figure 3.

728


Page 26 of 28

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729 730

Figure 4.



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Graphene oxide Oxidized carbon nanotube

Phytotoxicity Balance


Effects of Graphene Oxide and Oxidized Carbon ... - ACS Publications

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