SEARCH

SEARCH BY CITATION

Keywords:

  • CuO nanoparticle ecotoxicity;
  • Nitellopsis obtusa;
  • Thamnocephalus platyurus;
  • Brachionus calyciflorus;
  • LuminoTox assay

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSIONS
  7. Acknowledgements
  8. REFERENCES

Toxicity effects induced by nanosuspensions of CuO (<50 nm; Sigma-Aldrich) on macrophytic algae cells of Nitellopsis obtusa (96-h median lethal concentration [LC50]), microphytic algae Chlorella (30-min median inhibitory concentration [IC50]), shrimp Thamnocephalus platyurus (24-h LC50), and rotifer Brachionus calyciflorus (24-h LC50) were investigated. No substantial differences between the effects of nonsonicated and sonicated nCuO suspensions were observed. The particle size distribution analysis accomplished by the laser diffraction technique at suspension concentration from 3 to 100 mg/L revealed rapid (within 5 min) reagglomeration of the particles after the sonication. The observed adverse effects on N. obtusa cells may be attributed to nanoparticles per se, but not to ionic Cu, because neither chemical analysis nor biological testing (algae survival in the supernatants of suspensions) confirmed the presence of cupric ions in toxic amounts. Contrary to ionic Cu form, nCuO delayed the initial phase of N. obtusa cell membrane depolarization. Lethality tests with rewash demonstrated that the least used 5-min exposure in 100 mg/L nCuO sonicated suspension induced 70% mortality in charophyte cells after 8 d, whereas the rewash after a short exposure to a noticeably toxic concentration of Cu2+ prevented cell mortality. The obtained data suggested the possible influence of a thick charophyte cell wall on the dynamics of nanotoxicity effects. Environ. Toxicol. Chem. 2012;31:108–114. © 2011 SETAC


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSIONS
  7. Acknowledgements
  8. REFERENCES

Development of nanotechnology in various fields such as the chemical industry, electronics, biomedicine, cosmetics, and others, induces a threat of nanoparticle appearance in the hydrosphere 1, 2. Increasing the application of nano-sized CuO in technology 3 and medicine as a bactericidal agent 4 has recently been emphasized; however, the knowledge of biological effects, target sites, and especially the modes of action of the engineered particles seems to be inappropriate. According to Nowack 5, in an editorial following the 2009 NanoECO Conference (Ascona, Switzerland), the first documented detection of an engineered nano-TiO2 leached out by runoff from house facades into surface waters 6 was reported, thus delimiting speculations on possible pollution 7 from the actual quantitative data. This data, along with the growing knowledge that nanoparticle properties serve as a background for relevant risk-based classification systems 8 and validation of theoretical models further stimulate precise toxicological investigations. One purpose of these investigations is to understand the metallic nanoparticle-caused biological effects that are conditioned by at least two modes of action. Namely, these modes include dissociated metal ions and nanoparticles per se because below a critical size, simply scaling the properties of the bulk materials based on surface area to predict the properties of nanoparticles is not possible 9. Both aspects of nanotoxicity tightly relate to the physical and chemical state of the suspension.

The conventional approach used to stabilize nanoparticle suspension and, therefore, increase bioavailability is sonication 10. However, during sonication, ions can be released from metallic nanoparticles, for example, 1,000 mg/L suspension of Cu nanoparticles sonicated for 1 h releases 0.3 mg/L cupric ions 11. Under a similar magnitude of cupric ion concentrations, toxic effects were observed with unicellular algae Selenastrum capricornutum (72-h growth inhibition at median inhibitory concentration IC50 = 0.04 mg/L 12), macrophytic algae Nitellopsis obtusa (96-h median lethal concentration [LC50] = 0.13 mg/L 13), rotifers Brachionus calyciflorus (24-h LC50 = 0.023 mg/L 14), or shrimp Thamnocephalus platyurus (24-h LC50 = 0.04 mg/L 15). Thus, in assessing ecotoxicological effects of metallic nanosuspensions, especially those obtained by means of sonication, a possible contribution of the toxicity attributable to metal ions should be taken into account.

Although few data on nCuO-induced effects in aquatic organisms have been obtained 16, scientific references available for ecotoxicity of metallic or metallic oxide nanoparticles focus on two groups of explanations. The first ascribes observed effects solely to simple solubility, as was found for microalgae Pseudokirchneriella subcapitata17, bacteria Vibrio fischeri, crustaceans Daphnia magna, and T. platyurus15 affected by ZnO nanoparticles. The second attributes the effects to the toxicity resulting from nanoparticles and ions. For example, Griffit et al. demonstrated that nano-copper toxicity neither on Zebrafish gill 18 nor on Daphnia pulex survival 19 could be attributed to dissolved metals. Jiang et al. 20 showed that the toxicity of nano-scaled aluminium, silicon, titanium, and zinc oxides to bacteria were not only from the dissolved metal ions, but also from their ability to attach to the cell walls rather than to form aggregates. Van Hoecke et al. 21 demonstrated the adsorption of SiO2 nanoparticles on the cell wall of P. subcapitata and thus concluded that toxicity occurs through the surface interaction. Lee et al. 11 reported that toxicity effects on the growth inhibition of Phaseolus radiatus and Triticum aestivum seedlings clearly resulted from Cu nanoparticles that were observed agglomerated inside the plant cells, but not from cupric ions. Because numerous publications exist on the toxicity of metal salts to a wide range of aquatic organisms, a productive way to distinguish between the alternatives of the toxic action of metallic nanoparticles is to identify their likely dissolved concentration in the suspension under conditions of experimental media. In the case of measured ionic concentrations that are below toxicological susceptibility to certain organisms, one could attribute the observed effects to nanoparticles per se.

To expand the data on metal oxide nanoparticle toxicity to aquatic biota, the present study aimed to elucidate the effects of sonicated and nonsonicated nCuO suspensions on macrophytic N. obtusa (resting potential depolarization and cell lethality) and microphytic Chlorella spp. (photosynthetic efficiency) algae as well as lethality of shrimp T. platyurus and rotifer B. calyciflorus. To distinguish toxicities of different Cu chemical forms, ionic and nanoform, the presence of Cu2+ in both sonicated and nonsonicated suspensions was analyzed by capillary electrophoresis and atomic absorption spectrophotometry. The dynamics of toxicity effects induced by nCuO suspensions and copper nitrate were compared by evaluating the time-course curves of lethality and electrophysiological reactions in N. obtusa.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSIONS
  7. Acknowledgements
  8. REFERENCES

Charophyte algae material

The freshwater charophyte N. obtusa (Desv.) was harvested in Lake Švenčius (Lithuania) in autumn 2008 22. Before the experiment, internodal cells (second or third internode below the tip of growing plants) were separated from the neighboring cells. After separating them from the bulk, single cells were kept at room temperature (20 ± 2°C) in glass aquariums filled with equal parts of nonchlorinated tap water, lake water, and artificial pond water (APW) containing (mM) 0.1 KH2PO4, 1.0 NaHCO3, 0.4 CaCl2, 0.1 Mg (NO3)2, and 0.1 MgSO4 (pH 7–7.4) 23.

Preparation of nCuO suspensions

Powder of ultrafine copper(II) oxide nanoparticles, with an average particle size of less than 50 nm (mean ∼30 nm), was purchased from Sigma-Aldrich. A stock of 10 g/L CuO nanoparticles was prepared by dispersing the nanoparticles in deionized H2O with sonication for 15 min in a bath-type sonicator (Intersonic, IS-2, 300W, 35 kHz). The final working concentrations of 1, 3, 10, 30, and 100 mg/L were prepared in APW immediately before the experimentation from the stock. The treatments included the sonicated (30 min immediately before testing), nonsonicated (vortexed), sonicated + centrifuged (sonicated for 15 min and then centrifuged for 10 min, 1,500 g), and nonsonicated + centrifuged (centrifuged for 10 min, 1,500 g) suspensions. The supernatants were removed from pellet and left for 1 d at room temperature.

N. obtusa cell lethality testing

Lethality response of macrophytic algae cells of N. obtusa was investigated for 192 h. The APW medium was used as the control. Single internodal cells (each 4–15 cm in length) were placed on petri dishes (10 cells per dish, 3–5 replicates), preadapted for 1 to 2 d in APW, and then kept at room temperature (18–24°C) in the dark. The preadaptation in APW before the test allowed occasionally discarding dead cells that had been injured during the transfer to the petri dishes. Survival of the cells was checked daily by gently picking up each cell with a spatula. A cell was judged to be dead if a disappearance of turgor pressure occurred when it was picked up, a state in which a cell bends on the spatula. The solutions of Cu (NO3)2 × 2.5 H2O (Aldrich) were prepared in APW.

Two different exposure patterns and their respective toxicity endpoints were employed. Besides the routine exposure pattern for the assessment of LC50, the median lethal exposure duration (LED50), which determines the time for 50% of the exposure group to die at a certain concentration, was used. The latter endpoint definition is similar to the 50% lethal time endpoint 24 definition, but employs a different exposure pattern. To reveal the differences between these two endpoints, a convenient approach would be to distinguish exposure duration (ED, the interval from the beginning of the test, during which cells are treated with a toxicant) from the endpoint duration (t, time from the beginning of the test, after which mortality data are evaluated). Endpoints of LC50 and 50% lethal time endpoints are calculated when cells are treated permanently, that is, ED = t. In the rewash lethality test, the exposure pattern in LED50 finding protocol includes periods of exposure and successive rewash in APW; thus, the endpoint duration is a sum of both periods. The durations of exposure to Cu salt and CuO suspension were 5 min, 15 min, 30 min, 1 h, 6 h, 12 h, and 192 h. Different rewash periods were used to achieve fixed endpoint durations.

Electrophysiological experiments

Bioelectrical activity of up to 32 living internodal cells of N. obtusa was measured simultaneously according to the K+-anesthesia method 25, modified for multichannel recording with extracellular chlorinated silver wire electrodes 26. The discrete values of membrane (plasmalemma) potential difference from distinct cells were taken every second. After amplification, the output signals were channeled into a personal computer by means of a controller. The data on the kinetics of cell transmembrane resting potential for all 32 cells were plotted on a graphic display for visual control and stored for further analysis. The details of the computer-assisted experimental setup have been published previously 13, 26. To ameliorate the physiological state of charophyte cells throughout the prolonged measurement of their bioelectrical activity (up to 30 h), the full content of the control medium, such as APW instead of APWT13, was used.

Toxkit bioassays

The bioassays for 24-h mortality of shrimp T. platyurus (Thamnotoxkit F) 27 and rotifers B. calyciflorus (Rotoxkit F) 28 were performed following the standard operational procedures of the respective toxkits.

LuminoTox assay

The LuminoTox 29 toxicity testing procedure uses the measurement of fluorescence emitted by PSII complexes in stabilized unicellular green algae Chlorella spp. (stabilized aqueous photosynthetic systems). To evaluate the photochemical quantum yield, also referred to as photosynthetic efficiency (Φp), by fluorescence measurements, the stabilized aqueous photosynthetic systems must be dark-adapted with two levels of light illumination. The analyzer measures Φp based on the following formula

  • equation image

F1 fluorescence relates to fully oxidized plastoquinone Qa after a corresponding application of low-light-intensity excitation to stabilized aqueous photosynthetic systems, whereas F2 fluorescence relates to fully reduced Qa after a rapid application of high-light-intensity excitation.

Fluorescence emissions of stabilized aqueous photosynthetic systems for both F1 and F2 are measured at a wavelength greater than 700 nm after light excitation at 470 nm. Percentages of inhibition based on exposure of the sample can then be calculated as follows

  • equation image

Chemical analysis

Atomic absorption spectrophotometry

Copper concentrations were measured using a flame atomic absorption spectrophotometer (PerkinElmer Model 630). Titrisol (Merck) standards (1,000 mg) diluted up to required concentration were used for calibration. The detection limit for Cu using a flame atomic absorption spectrophotometer was 10 µg/L.

Capillary electrophoresis

A P/ACE MDQ Capillary Electrophoresis System equipped with a photodiode array detector (Beckman Coulter) was used. Before the analysis, all centrifuged sonicated and nonsonicated suspensions of CuO nanoparticles prepared in APW (10, 30, 100, and 300 mg/L) were passed through a 0.2-µm filter. Next, 0.4 ml of the sample was mixed with 0.1 ml of the mixture containing 0.25 mM Na-ethylenediaminetetra-acetic acid (Titriplex III) and 0.5 mM NaOH.

Samples were injected into the capillary at 0.5 psi (0.03 bar) for 5 s. The temperature was maintained at 25°C. Ionic concentrations were analyzed in a quartz capillary of 67 cm (effective length, 60 cm), with an inner diameter of 75 µm at −25 kV. Mobile phase was a borate buffer containing 100 mM boric acid, 0.3 mM tetradecyltrimethylammonium hydroxide, 1 mM Titriplex III, and pH 8.8 (adjusted by NaOH). All chemicals were from Merck and were pure for analysis. The electrolyte buffer was filtered (0.45 µm) and subjected to ultrasonic degassing before use. The capillary was rinsed with 100 mM sodium hydroxide for 5 min and then equilibrated with a background electrolyte for 5 min at the beginning of each day. The capillary was rinsed with 100 mM boric acid for 1 min and with a background electrolyte for 4 min between all electrophoretic separations. The detector was operated at 195 and 250 nm in direct detection mode. The detection limits for Cu ethylenediaminetetra-acetic acid complexes by capillary electrophoresis was 0.1 mg/L. The data were analyzed by a 32 Karat (Ver 8.0) software.

Particle characterization

The particle size was examined by the laser diffraction technique (Helos, Sympatec GmbH), which can measure particle sizes between 0.1 and 875 µm. In the present study, a range from 0.2 to 90 µm was selected. The stock solution of nCuO was prepared at 10 g/L in Milli-Q water and sonicated for 30 min with a 3-mm ultrasonic horn (Bioblock Scientific, Vibracell) and stored at 4°C for 3 d in the dark. The suspensions of 3, 10, 30, and 100 mg/L were prepared in APW either before 24 h (24-h batch) or just before (0-h batch) measurements. For the 24-h sonicated batch, the suspensions in glass dishes were sonicated for 30 min with a bath-type sonicator (Bandelin Electronic Sonorex RK 510, 160-320 W, and 35 kHz).

The 0-h batch (sonicated or not) was prepared directly in the laser granulometer, which had an integrated bath-type sonicator. The samples were continuously pumped by the device, and the nanoparticles were added after each measured concentration for the nonsonicated batch. The device was emptied after each measured concentration of sonicated batch, to avoid sonicating the same particles twice.

The device did not arrive in time to focus the laser for the 24-h samples of 100 mg/L (nonsonicated or sonicated), thus making the measurement impossible. However, when these samples were sonicated for 60 s in the device, the measurement was performed, although it was impossible 2 min later. This might have resulted either because of high concentration or aggregation. Two consecutive measurements of 10 s each spaced by 5 s were executed.

RESULTS AND DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSIONS
  7. Acknowledgements
  8. REFERENCES

Characterization of suspensions

We did not check the size of the manufactured CuO nanoparticles purchased from Sigma-Aldrich because they had recently been characterized by scanning 30, 31 and transmission microscopy 32. The mean (∼30 nm) and the range (< 50–60 nm) of nanoparticle sizes 32 coincided well with that declared by the manufacturer. In the present study, the characterization of nCuO suspension was conducted by laser diffraction technique and focused on the size distribution of nanoparticle agglomerates rather than on primary nanoparticles. Because of rapid reagglomeration, identifying particles smaller than 0.2 µm was not possible. Nevertheless, at least in the case of the 3 to 30 mg/L suspensions analyzed at the 0-h measurement, the suspensions contained nanoparticles below 0.2 µm. Overall, the mode of agglomerated particle size distribution drifts toward larger sizes, with an increase of concentration at 0 h for both nonsonicated and sonicated suspensions. The mode of nonsonicated suspensions shifted from 500 nm at 3 mg/L to 6,000 nm at 100 mg/L, and the mode of sonicated suspension shifted from 500 nm at 3 to 10 mg/L to 4,000 nm at 100 mg/L (Fig. 1). After 24 h, nanoparticle size distributions of both nonsonicated and sonicated suspensions were characterized by similar modes at 3 to 100 mg/L of nCuO concentrations (Fig. 1). When 3-mg/L sonicated suspension was repeatedly inspected after 3 min (after 0-h measurement), the maximum of the size distribution stayed at 500 nm. However, when 30-mg/L sonicated suspension was repeatedly measured after 3 and 5 min, the maximum size distribution shifted from approximately 1,000 nm to 3,500 nm and to 5,000 nm, respectively (Fig. 1), indicating fast reagglomeration. The dynamics of reagglomeration can be seen from two consecutive measurements with a 5-s delay. The difference between those measurements was highest immediately after sonication (Fig. 2, A1 and A2), becoming lower 3 min later (Fig. 2, B1 and B2) and becoming negligible in 5 min (Fig. 2, C1 and C2). Generally, sonication has quite a short-term, concentration-dependent effect on agglomerate disruption in CuO suspensions, at least under conditions of the control medium used in the present study.

thumbnail image

Figure 1. Relationship between the mode of size distribution of agglomerated nanoparticles and nCuO concentration in artificial pond water. Measurements were performed in nonsonicated (s) and sonicated (s+) suspensions with laser diffraction technique at 0-h and 24-h times.

Download figure to PowerPoint

thumbnail image

Figure 2. Particle size distributions analyzed immediately after sonication in 30-mg/L nCuO suspension at 0-min (A1 and A2), 3-min (B1 and B2), and 5-min (C1 and C2) measurements. Curves indexed by 1 and 2 represent two successive measurements separated by 5-s gap. Each measurement lasted 10 s.

Download figure to PowerPoint

To ensure that the observed biological effects are not related to a soluble fraction of Cu, both nonsonicated and sonicated suspensions were centrifuged to settle down the nanoparticles, and then supernatants were analyzed by capillary electrophoresis and atomic absorption spectrophotometer. Copper was not detected in the supernatants by applying both methods (detection threshold for atomic absorption spectrophotometer ≥ 0.01 mg/L of Cu and for capillary electrophoresis ≥ 0.1 mg/L of Cu2+).

Ecotoxicity of nCuO suspensions

Toxicity data of sonicated and nonsonicated nCuO suspensions and two Cu salts generated with various biotests are presented in Table 1. A comparison of test-organism responses to Cu and ionic Cu shows that, in general, the sensitivity sequence of the endpoint values obtained after exposure to nCuO resembles that of CuSO4 (Table 1). Among aquatic organisms used in the present study, the test with rotifers was most sensitive to an ionic form of Cu and to CuO nanoparticles. Fluorescence response expressed as a 30-min inhibition of photosynthetic efficiency in Chlorella cells 29 was the least sensitive to both forms of Cu. Suspensions either sonicated or nonsonicated induced similar toxicity to shrimp T. platyurus, with 24-h LC50s of 8.5 and 9.8 mg/L, respectively (Table 1). These values were lower by a factor of approximately 10 in comparison to those found in Heinlaan et al. 15. Although the same source (Sigma-Aldrich) and similar particle size of CuO nanopowder (mean ∼30 nm) were used, various conditions of the stock storage duration, preparation of dilutions, and technical manipulations could be the reasons for the observed difference in LC50s.

Table 1. Effects of different forms of copper, nanoparticle,a and ionicb on charophyte algae cells of Nitellopsis obtusa, shrimp Thamnocephalus platyurus, rotifers Brachionus calyciflorus, and Chlorella expressed as median lethal concentration and median inhibitory concentration (mg/L of Cu, mean ± standard error)
 N. obtusaT. platyurusB. calyciflorusN. obtusaChlorella
96-h LC5024-h LC5024-h LC5090-min IC5030-min IC50
nsnsnsnsnS
  • LC50 = median lethal concentration; IC50 = median inhibitory concentration; NPs = nanoparticles.

  • a

     Applied as nonsonicated (n) and sonicated (s) CuO nanopowder suspensions.

  • b

     Applied as CuSO4 and Cu(NO3)2 solutions.

  • c

     Depolarization of N. obtusa cell membrane was lower than 10% within 90 min.

Nano form
 Cu, mg/L (CuO NPs)4.3 ± 0.352.8 ± 0.239.8 ± 0.28.5 ± 0.80.24 ± 0.010.39 ± 0.01No reactioncNo reactionc57 ± 7.847 ± 7.5
Ionic form
 Cu2+, mg/L (CuSO4)0.13 ± 0.03 130.04 ± 0.02 150.023 144.3 ± 0.4613 ± 2.0
 Cu2+, mg/L [Cu(NO3)2]0.11 ± 0.04  7.0 ± 2.6 

The biotests with conventional EDs did not reveal substantial differences between the effects of nonsonicated and sonicated CuO suspensions (Table 1). The differences between the effects of nonsonicated and sonicated suspensions consisted of 35% for N. obtusa 96-h LC50 values and 38% for B. calyciflorus 24-h LC50 values (sonicated suspension was more toxic than nonsonicated suspension in the case of N. obtusa, and the opposite situation was found for B. calyciflorus). To reveal the effect of sonication further, the lethality kinetics was found useful. Although the rotifer test was more sensitive, the lethality test with algal cells was used because the test design allows inspecting the viability of algal cells easily and without a limitation on testing duration. The effect of sonication can be clearly seen from the lethality kinetics (Fig. 3), for example, in the case of 10 mg/L nonsonicated and sonicated nCuO suspensions. Figure 4 shows the dependence of calculated LC50s against exposure. The highest (10-fold) difference between the two curves representing nonsonicated and sonicated suspensions falls at approximately 40 h of exposure, and significant difference (twofold) remains until approximately 80 h. An unexpected result was generated by an electrophysiological response of the macrophytic algae of N. obtusa; that is, a rapid endpoint of 90-min 50% depolarization of the resting potential was found to be insensitive when algae cells were incubated up to 1 g/L of CuO suspensions.

thumbnail image

Figure 3. Mortality time-courses of charophyte algae cells of Nitellopsis obtusa during the 192-h exposure period to nonsonicated (n) and sonicated (s) suspensions of CuO (mg/L). Lowercase numbers depict respective concentrations in mg/L.

Download figure to PowerPoint

thumbnail image

Figure 4. Change of 50% lethal concentration (LC50) values with time for charophyte algae cells of Nitellopsis obtusa during the 192-h exposure period to nonsonicated and sonicated suspensions of CuO (mg/L).

Download figure to PowerPoint

Effect of nCuO suspension on cell membrane potential

Electrophysiological biotest with charophyte cells routinely employs the endpoint of 45 to 90 min 50% depolarization of cell membrane potential 13, 33. The 90-min IC50 values generated by this rapid test are usually higher than 96-h LC50 values obtained with the same algae 33. For example, for heavy metal salts, IC50s are higher than LC50s for up to three orders of magnitude; for organic compounds, IC50s are higher than LC50s from several times up to one order of magnitude, but for multicomponent mixtures such as municipal wastewater, these two endpoints have approximately the same sensitivity. Keeping in mind that the ratio of 90-min IC50 and 96-h LC50 values is approximately 50 for Cu salts (Table 1), a 100-fold higher concentration of nCuO than that of 96-h LC50 might induce fast depolarization. However, no significant depolarization was reached within a 90-min exposure period even if concentration was increased to 500 or even 1,000 mg/L (Fig. 5). Because the measuring of membrane potential by means of external electrodes can be conducted for several hours without a significant change in the average level of cells' resting potential, the exposure to nCuO was prolonged to approximately 30 h. Depolarization of 50% was reached after a 12-h treatment with sonicated suspension of 500 mg/L; the same depolarization was reached before 24 h at 30 to 100 mg/L suspensions (Fig. 5). Nonsonicated suspensions of 10 to 100 mg/L induced substantially lower depolarization; for example, within 24 h, 100 mg/L of nonsonicated suspension induced approximately 30% depolarization (data not shown). One possible reason for the very slow effect on charophyte algae could be an insufficient amount of presumably active (relatively small) particles because of the formation of agglomerates (see the Characterization of suspensions section).

thumbnail image

Figure 5. The kinetics of resting potential (RP) of Nitellopsis obtusa cells treated with 10 to 1,000 mg/L of sonicated nCuO suspensions. Each curve represents an average of 14 to 16 cells. Treatments were started at 0-h time.

Download figure to PowerPoint

The loss of a fast bioelectrical response of charophyte algal cells treated by nCuO suspensions was a reason to include green algae Chlorella with a rapid 30-min IC50 endpoint of photosynthetic efficiency. Contrary to N. obtusa, the endpoint of photosynthetic efficiency inhibition was found to be sensitive enough to calculate an IC50 value for Cu nanoform, although this endpoint was less sensitive to CuSO4 (Table 1). These findings suggest that a possible cause of the effect delay in the case of charophyte cells might be cell wall morphology; for example, the cell wall of a charophyte cell is more than 100 times thicker than that of Chlorella34, 35. As has been shown for tuberculosis bacteria, the effect pathways can be mediated by the thickness of the cell wall, because susceptibility of certain strains to drugs can be conditioned by this parameter 36.

Ionic- and nano-Cu effects on N. obtusa lethality kinetics

After the chemical analysis data, CuO nanosuspensions of 10, 30, 100, and 300 mg/L prepared in the control medium and used in biotesting with N. obtusa contained less than 0.01 mg/L Cu2+. Because this concentration is only approximately 10-fold lower than the 96-h LC50 value for charophyte cells (Table 1), the absence of toxicity stemming from ionic Cu was further investigated. Algae cells were exposed to supernatants obtained from nonsonicated and sonicated suspensions of 10 to 300 mg/L of nCuO. During 192 h, the cells survived all treatments (mortality was less than 10%), thus biologically confirming the absence of soluble Cu in toxic concentration. Because nCuO suspensions induced approximately 100% mortality within 2 to 4 d (Fig. 3), mortality of N. obtusa cells observed in nanosuspensions is to be attributed to nanoform-caused toxicity.

Visual inspection of concentration-dependent mortality kinetics of sonicated nCuO suspensions and Cu(NO3)2 did not show obvious differences (data not shown). To show that the effectiveness of the barrier, causing a delay in a short-term electrophysiological response of the cells (Fig. 5), depends on ED, LED50-finding tests that include exposure and rewash phases were applied. For the experiment with varying EDs, two concentrations of respective Cu forms that showed similar lethality kinetics during permanent exposure were chosen (0.64 mg/L of Cu2+ and 100 mg/L-nCuO) (Fig. 6). Surprisingly, no threshold was found in terms of ED within the exposure range studied. Even the shortest 5-min exposure induced 70% mortality within 8 d. In the case of cupric ions, a substantially lower effect was observed. The 6-h exposure was able to evoke less than 40% mortality within 8 d. The difference between ionic and nanoform of Cu can be clearly seen in the plot of LED50 against the endpoint time (Fig. 6). With an increase in endpoint time, LED50 for nCuO decreases steeply, contrary to LED50 for Cu2+. For example, at a 48-h endpoint time, both Cu form LED50s are equal for approximately 20 h, whereas in 120 h, LED50 for Cu2+ exceeds LED50 for nCuO by more than two orders of magnitude. At endpoint durations longer than approximately 144 h, the LED50 values for nCuO were obtained by extrapolation, because all exposures exceeded 50% mortality. The obtained results show that N. obtusa cells can be rewashed after 6 h of exposure to 0.64 mg/L Cu2+ and most cells survive, whereas even after 5 min of exposure to 100 mg/L nCuO, the nanoparticles bind to the cell wall. The tight adsorption on the cell wall may indicate that charophytes can accumulate nanoparticles, and eventually they can cause cell death even at low concentrations. Our data obtained with nCuO are similar to those with SiO2 nanoparticles 21, which have shown that nanoparticles adsorb on the cell wall of P. subcapitata to cause a decrease in cell growth rate.

thumbnail image

Figure 6. The kinetics of lethality of Nitellopsis obtusa cells exposed to 0.64 mg/L Cu2+, as Cu(NO3)2, and 100 mg/L sonicated nCuO suspension (solid symbols), and the kinetics of 50% lethal exposure duration (LED50) calculated for 0.64 mg/L of Cu2+, as Cu(NO3)2, and 100 mg/L of sonicated nCuO suspension.

Download figure to PowerPoint

CONCLUSIONS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSIONS
  7. Acknowledgements
  8. REFERENCES

Following the data obtained by the laser diffraction technique, sonication had no influence on the particle size distribution in 3- to 100-mg/L nCuO suspensions after 24 h. Reagglomeration was observed immediately after sonication within 15 s, and the particle size distributions of nonsonicated and sonicated 30-mg/L nCuO suspensions practically did not differ after 5 min. Biotests with conventional exposure durations, for example, macrophytic algae cells of N. obtusa (96-h LC50), microphytic algae Chlorella (30-min IC50), shrimp T. platyurus (24-h LC50), and rotifer B. calyciflorus (24-h LC50) did not reveal substantial differences between the effects of nonsonicated and sonicated nCuO suspensions.

Surprisingly, the lethal concentrations of nCuO suspensions were not able to evoke a rapid N. obtusa cell membrane depolarization phase within the initial 90-min period, whereas for various toxicant classes such as heavy metal salts, organic compounds, or effluents, the values of 96-h LC50s could be predicted from charophyte cell 90-min IC50s. This finding suggests that the factor (presumably charophyte cell wall), which delays the toxic effects of nCuO suspensions, does exist. Significant depolarization of the cell membrane occurred only after approximately 6 h. Also, the rewash lethality tests highlighted a specific action of nCuO: the least-used 5-min exposure in 100-mg/L nCuO suspension induced 70% mortality of charophyte cells after 8 d, whereas the rewash after a short exposure in noticeably toxic concentration of cupric ions prevented cell mortality. The observed lethal effects of algae cells as well as delayed cell membrane depolarization were evoked by nanoparticles or their agglomerates per se, but not by dissolved Cu, because neither chemical analysis nor biological testing (i.e., algae survived in the supernatants of suspensions) confirmed the presence of cupric ions in toxic amounts.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSIONS
  7. Acknowledgements
  8. REFERENCES

We thank K. Rubekin for technical assistance in testing with Chlorella. The research was executed under the France-Lithuania Research Programme, Gilibert, and funded by grants T-70/08 and V-40/09 from the Lithuanian State Science and Studies Foundation, and TAP-42/10 from the Research Council of Lithuania.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSIONS
  7. Acknowledgements
  8. REFERENCES
  • 1
    Klaine SJ, Alvarez JJ, Batley E, Fernandes TF, Handy RD, Lyun DY, Mahendra S, McLaughlin J, Lead JR. 2008. Nanomaterials in the environment: Behavior, fate, bioavailability, and effects. Environ Toxicol Chem 27: 18251851.
  • 2
    Blaise C, Gagné F, Férard JF, Eullaffroy P. 2008. Ecotoxicity of selected nano-materials to aquatic organisms. Environ Toxicol 23: 591598.
  • 3
    Xu LJ, Zhao JX, Zhang T, Ren GG, Yang Z. 2009. In vitro study on influence of nanoparticles of CuO on CA1 pyramidal neurons of rat hippocampus potassium currents. Environ Toxicol 24: 211217.
  • 4
    Gajjar P, Pettee B, Britt DW, Huang W, Johnson WP, Anderson AJ. 2009. Antimicrobial activities of commercial nanoparticles against an environmental soil microbe, Pseudomonas putida KT2440. J Biol Eng 3: 9.
  • 5
    Nowack B. 2009. The behaviour and effects of nanoparticles in the environment. Environ Pollut 157: 10631064.
  • 6
    Kaegi R, Ulrich A, Sinnet B, Vonbank R, Wichser A, Zuleeg S, Simmler H, Brunner S, Vonmont H, Burkhardt M, Boller M. 2008. Synthetic TiO2 nanoparticle emission from exterior facades into the aquatic environment. Environ Pollut 156: 233239.
  • 7
    Moore MN. 2006. Do nanoparticles present ecotoxicological risks for the health of the aquatic environment? Environ Int 32: 967976.
  • 8
    Tervonen T, Linkov I, Figueira JR, Steevens J, Chappell M, Merad M. 2009. Risk-based classification system of nanomaterials. J Nanopart Res 11: 757766.
  • 9
    Auffan M, Rose J, Wiesner MR, Bottero JY. 2009. Chemical stability of metallic nanoparticles: a parameter controlling their potential cellular toxicity in vitro. Environ Pollut 157: 11271133.
  • 10
    Handy RD, von der Kammer F, Lead JR, Hassellöv M, Owen R, Crane M. 2008. The ecotoxicology and chemistry of manufactured nanoparticles. Ecotoxicology 17: 287314.
  • 11
    Lee WM, An YJ, Yoon H, Kweon HS. 2008. Toxicity and bioavailability of copper nanoparticles to the terrestrial plants mung bean (Phaseolus radiatus) and wheat (Triticum aestivum): plant agar test for water-insoluble nanoparticles. Environ Toxicol Chem 27: 19151921.
  • 12
    Persoone G. 1998. Development and first validation of a “stock-culture free” algal microbiotest: the Algaltoxkit. In Wells PG, Lee K, Blaise C, eds, Microscale Testing in Aquatic Toxicology: Advances, Techniques, and Practice. CRS, Boca Raton, FL, USA, pp 311320.
  • 13
    Manusadžianas L, Maksimov G, Darginavičienė J, Jurkonienė S, Sadauskas K, Vitkus R. 2002. Response of charophyte Nitellopsis obtusa to heavy metals at the cellular, cell membrane and enzyme levels. Environ Toxicol 17: 275283.
  • 14
    Clemedson C, McFarlane-Abdulla E, Andersson M, Barile FA, Calleja MC, Chesné C, Clothier R, Cottin M, Curren R, Daniel-Szoglay E, Dierickx P, Ferro M, Fiskesjö G, Garza-Ocanas L, Gomez-Lechon MJ, Gülden M, Isomaa B, Janus J, Judge P, Kahru A, Kemp RB, Kerszman G, Kristen U, Kunimoto M, Kärenlampi S, Lavrijsen K, Lewan L, Lilius H, Ohno T, Persoone G, Roguet R, Romert L, Sawyer TW, Seibert H, Shrivastava R, Stammati A, Tanaka N, Torres-Alanis O, Voss JU, Wakuri S, Walum E, Wang XH, Zucco F, Ekwall B, Sandberg M, Sjöström M. 1996. Part II. In vitro results from 68 toxicity assays used to test the first 30 reference chemicals and a comparative cytotoxicity analysis. Altern Lab Anim 24: 273311.
  • 15
    Heinlaan M, Ivask A, Blinova I, Dubourguier HC, Kahru A. 2008. Toxicity of nanosized and bulk ZnO, CuO and TiO2 to bacteria Vibrio fischeri and crustaceans Daphnia magna and Thamnocephalus platyurus. Chemosphere 71: 13081316.
  • 16
    Cattaneo AG, Gornati R, Chiriva-Internati M, Bernardini G. 2009. Ecotoxicology of nanomaterials: The role of invertebrate testing. Invertebr Surviv J 6: 7897.
  • 17
    Franklin NM, Rogers NJ, Apte SC, Batley GE, Gadd GE, Casey PS. 2007. Comparative toxicity of nanoparticulate ZnO, bulk ZnO, and ZnCl2 to freshwater microalga (Pseudokirchneriella subcapitata): The importance of particle solubility. Environ Sci Technol 41: 84848490.
  • 18
    Griffitt RJ, Weil R, Hyndman KA, Denslow ND, Powers K, Taylor D, Barber DS. 2007. Exposure to copper nanoparticles causes gill injury and acute lethality in zebrafish (Danio rerio). Environ Sci Technol 41: 81788186.
  • 19
    Griffitt RJ, Luo J, Gao J, Bonzongo JC, Barber DS. 2008. Effects of particle composition and species on toxicity of metallic nanomaterials in aquatic organisms. Environ Toxicol Chem 9: 19721978.
  • 20
    Jiang W, Mashayekhi H, Xing B. 2009. Bacterial toxicity comparison between nano- and micro-scaled oxide particles. Environ Pollut 157: 16191625.
  • 21
    Van Hoecke K, De Schamphelaere KAC, Van der Meeren P, Lucas S, Janssen CR. 2008. Ecotoxicity of silica nanoparticles to the green alga Pseudokirchneriella subcapitata: Importance of surface area. Environ Toxicol Chem 27: 19481957.
  • 22
    Kostkevičienė J, Sinkevičienė Z. 2008. A preliminary checklist of Lithuanian macroalgae. Bot Lith 14: 1127.
  • 23
    Vorobiov LN, Manusadžianas L. 1983. Bioelectrical reactions of Nitellopsis obtusa cells induced by indole-3-acetic acid. Physiol Plantarum 59: 651658.
  • 24
    Bliss CI. 1937. The calculation of the time mortality curve. Ann Appl Biol 24: 815852.
  • 25
    Shimmen T, Kikuyama M, Tazawa M. 1976. Demonstration of two stable potential states of plasmalemma of Chara without tonoplast. J Membr Biol 30: 249270.
  • 26
    Manusadžianas L, Vitkus R, Pörtner R, Märkl H. 1999. Phytotoxicities of selected chemicals and industrial effluents to Nitellopsis obtusa cells assessed by a rapid electrophysiological charophyte test. Altern Lab Anim 27: 379386.
  • 27
    Microbiotests. 2003. Thamnotoxkit F™. Freshwater Toxicity Screening Test for Freshwater. Standard Operational Procedure. Nazareth, Belgium.
  • 28
    Microbiotests. 2003. Rotoxkit F™. Rotifer Toxicity Screening Test for Freshwater. Standard Operational Procedure. Nazareth, Belgium.
  • 29
    Boucher N, Lorrain L, Rouette ME, Perron E, Déziel N, Tessier L, Bellemare F. 2005. Rapid testing of toxic chemicals. Am Lab 37: 3437.
  • 30
    Kahru A, Dubourguier H-C, Blinova I, Ivask A, Kasemets K. 2008. Biotests and biosensors for ecotoxicology of metal oxide nanoparticles: a minireview. Sensors 8: 51535170.
  • 31
    Sosová T, Koči V, Kochánková L. 2009. Ecotoxicity of nano and bulk forms of metal oxides. Proceedings, NANOCON Conference, Rožnov pod Radhoštěm, Czech Republic, October 20-22, p 62.
  • 32
    Blinova I, Ivask A, Heinlaan M, Mortimer M, Kahru A. 2010. Ecotoxicity of nanoparticles of CuO and ZnO in natural water. Environ Pollut 158: 4147.
  • 33
    Manusadžianas L, Karitonas R, Sadauskas K, Vitkus R. 2007. Prediction of charophyte cell lethality from sublethal cell response after short-term exposure. Abstracts, 13th International Symposium on Toxicity Assessment, Toyama, Japan, August 19-24, p 51.
  • 34
    Proseus TE, Boyer JS. 2006. Calcium pectate chemistry controls growth rate of Chara corallina. J Exp Bot 57: 39894002.
  • 35
    Němcová Y, Kalina T. Cell wall development, microfibril and pyrenoid structure in type strains of Chlorella vulgaris, C. kessleri, C. sorokiniana compared with C. luteoviridis (Trebouxiophyceae, Chlorophyta). Algological Stud 100: 95105.
  • 36
    Velayati AA, Farnia P, Ibrahim TA, Haroun RZ, Kuan HO, Ghanavi J, Farnia P, Kabarei AN, Tabarsi P, Omar AR, Varahram M, Masjedi MR. 2009. Differences in cell wall thickness between resistant and non-resistant strains of Mycobacterium tuberculosis: Using transmission electron microscopy. Chemotherapy 55: 303307.