Ecotoxicology DOI 10.1007/s10646-014-1249-z

Early warning tools for ecotoxicity assessment based on Phaeodactylum tricornutum Monia Renzi • Leonilde Roselli • Andrea Giovani Silvano E. Focardi • Alberto Basset

•

Accepted: 25 April 2014 Ó Springer Science+Business Media New York 2014

Abstract Phaeodactylum tricornutum was exposed to various toxic substances (zinc, copper or dodecylbenzenesulfonic acid sodium salt) in accordance with the AlgalToxkitÒ protocol based on the UNI EN ISO 10253 method in order to quantitatively compare the responses obtained by traditional growth-rate inhibition tests with morphological (biovolume) and physiological (chlorophyll-a, phaeophytin ratio) endpoints. A novel approach is proposed for detecting early and sub-lethal effects based on biovolume quantification using confocal microscopy coupled with an image analysis system. The results showed that effects on both biovolume and the photosynthetic complex are sensitive and powerful early warning tools for evaluating sub-lethal effects of exposure. Specifically, biovolume showed significant sensitive and early responses for the tested surfactant. Qualitatively, we also observed structural anomalies and effects on natural auto-fluorescence in exposed cells that also represent potentially useful tools for ecotoxicological studies. Keywords Ecotoxicological tests  Phaeodactylum tricornutum  Morphological alterations  Physiological alterations  Growth inibition rate

M. Renzi (&)  L. Roselli  A. Basset Department of Biological and Environmental Sciences and Technologies, University of the Salento, SP Lecce-Monteroni, 73100, Lecce, Italy e-mail: [email protected] A. Giovani  S. E. Focardi Department of Environmental Sciences, University of Siena, Via Mattioli 4, 53100, Siena, Italy

Introduction Ecotoxicological tests on unicellular algal organisms are considered relatively simple to perform and standardized protocols are widely available. Indeed, disposable laboratory materials, stock cell cultures and nutrient media can be purchased from specialized factories, enabling better standardization of the whole procedure and increasing the repeatability and reproducibility of test results (RTI CTN_AIM 4 RTI CTN_AIM 2001; ISPRA 2011). The Phaeodactylum tricornutum growth-rate inhibition test is now routinely performed to evaluate water quality in marine and brackish water environments (Stauber et al. 2002; Eisentraeger et al. 2003; Moreira-Santos et al. 2004). P. tricornutum is a suitable target species because of the extensive knowledge of its biology (Martin-Je´ze´quel et al. 2000; De Martino et al. 2011), ecology (Rushforth et al. 1988; Francius et al. 2008) and ecotoxicology (Aidar et al. 1997; Pavlic´ et al. 2005; Falasco et al. 2009). In addition, results obtained using this species may be considered representative of phytoplankton primary producer responses to specific physico-chemical stressors. Furthermore, a recent study, testing the sensitivity of different phytoplankton species to the exposure to stressor, evidenced that sensitivity was linked to cell size and that the smallest phytoplankton species (i.e. P. tricornutum) are the most affected (Othman et al. 2012). The internationally recognized protocol for this species (UNI EN ISO 10253) is based on growth-rate inhibition after 72 h of exposure. Advantages of this method include the ease of performing the test, good reproducibility and availability of standardised protocols. Furthermore, data on growth-rate inhibition enable toxic effects to be compared to primary producer population dynamics (Knauer and Hommen 2012). The method thus allows the impact of the tested stressors to be

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considered from an ecological viewpoint. These features have led to the protocol’s widespread adoption. On the other hand, the method has some important disadvantages. As example, it is not suitable for assessing the effects of volatile compounds (Lin et al. 2005). Even if toxicity data based on growth-rate were found to provide better comparability for test results from different laboratories (Organization for Economic Cooperation and Development (OECD) 2000), this endpoint frequently exhibits high variability between replicates (Kraufvelin 1998; Knauer et al. 2005). Furthermore, growth-rate inhibition may be less sensitive than physiological endpoints (Knauer and Hommen 2012), and for this reason may be unsuitable for determining early or sub-lethal effects. The development of more sensitive methods for assessing early exposure to stress that are able to highlight physiological or morphological changes in algal species is thus a priority goal for further research. Specifically, in the case of algal species, possible indicators of early stress include alteration of the phaeophytin ratio (Ronen and Galun 1984) and the photosynthetic complex (Geider et al. 1993), which in turn provides direct and indirect information on the whole phytoplankton community and on the ecological state of the ecosystem (Knauer and Hommen 2012). However, the use of these endpoints for ecotoxicological testing needs further research in order to better determine dose-dependent and/or time-dependent responses. Previous research has shown that measurements of both photosynthetic efficiency and fluorescence may represent rapid and sensitive ecotoxicological methods (Streiber et al. 2002; Katsumata et al. 2006), although the applicability of these endpoints in P. tricornutum has yet to be evaluated. Algal species display natural auto-fluorescent properties due to the presence of photosynthetic pigments, allowing rapid screenings of toxicant-driven fluorescence inhibition (Neu and Lawrence 1997). Confocal laser scanning microscopy is used to investigate the complexity of cell morphology and relative biovolume at single-cell level (Larson and Passy 2005; Roselli et al. 2013). Different methods are available to perform biovolume measurements. Among them, flow cytometry gives relatively quickly the mean cell volume; however, these equipments can give erroneous results when the biovolume of nonspherical algae as well as P. tricornutum is measured. In such species, the possible alternative is represented by microscopic measurements (Hillebrand et al. 1999). Since the main effects of toxicants at the individual level are biochemical and growth-process alterations (Falasco et al. 2009), for diatom cells we hypothesize that physiological and morphological aspects of auto-fluorescence capacity and frustule formation and/or morphology represent interesting quantitative endpoints for ecotoxicological tests. Endpoints that can be investigated by confocal microscopy include alterations in

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chlorophyll auto-fluorescence, alterations in the fluorescence signal of the growing frustules and biovolume changes, all of which are assumed to reflect alteration of both frustule formation and the metabolic pathways involved in the photosynthetic complex. Changes in biovolume in algal species represent an ecotoxicological endpoint of great ecological significance. Indeed, they may have a cascade effect on the food web at upper trophic levels (Cloern and Dufford 2005). However, the confocal microscopy technique requires fluorescent samples, technical expertise, advanced equipment and high acquisition and running costs that discourage its use in monitoring the ecological state of aquatic ecosystems (Roselli et al. 2013). Unconventional endpoints could help to increase test sensitivity and the efficiency of responses to toxicants and highlight early effects and cell responses at high doses. In addition they may be able to detect early stress effects after exposure to doses below what is needed to cause effects detectable by traditional methods. However, further research is needed to evaluate their applicability to P. tricornutum. In this study, P. tricornutum was exposed to suitable dilutions of three toxic substances (zinc, copper and dodecylbenzenesulfonic acid sodium salt) in order to: (i) evaluate the best method (spectrophotometry vs. Burker’s chamber) of performing cell counts in traditional growth-rate inhibition tests; (ii) investigate dose-dependent responses after 24, 48 and 72 h of exposure in terms of growth-rate inhibition and morphological (biovolume) and physiological (chlorophyll-a concentration, phaeophytin ratio) endpoints; and (iii) compare, on the basis of EC50 values, responses obtained by growth-rate inhibition tests with the considered morphological and physiological endpoints to evaluate whether the latter (newly proposed) endpoints can increase test sensitivity and reduce the time required.

Materials and methods Selection of toxic substances Algal species were exposed to varying concentrations of zinc (Zn), copper (Cu) and dodecylbenzenesulfonic acid sodium salt (C18H29NaO3S). Zn and Cu are trace elements of major environmental concern, whereas dodecylbenzenesulfonic acid sodium salt is the main component of laundry detergent and thus representative of a methyleneblue active substance (MBAS). The tested dilutions of toxicants were 25, 38, 50, 75, and 100 mg L-1 for Zn and Cu, and 0.025, 0.038, 0.050, 0.075, and 0.100 mg L-1 for MBAS. Acidified concentrated solutions of Zn (lot n. 3L763193N) and Cu (lot n. 4D750284E) were purchased

Early warning tools for ecotoxicity assessment

Fig. 1 Logical model adopted for experimental design. The figure summarises the logical model adopted for the ecotoxicological tests performed. Experimental procedures were conducted in triplicate (n = 3). Cell cultures were treated as described in the text

from Carlo Herba whereas dodecylbenzenesulfonic acid sodium salt (lot n. 455609/1) was purchased from Fluka. After the addition of these solutions, pH was corrected to 8.0 ± 0.1 by adding NaOH (1 M) to avoid pH-driven stress on the algal population.

The following endpoints were tested: growth-rate inhibition after 72 h of exposure, and morphological changes (biovolume) and physiological changes (chlorophyll-a concentration, phaeophytin ratio) after 24, 48, and 72 h of exposure.

Experimental design

Algal cell cultures

Experimental design is shown as a logical model in Fig. 1. Mono-specific algal cultures of P. tricornutum Bohlin (Bacillariophyceae) were exposed to varying concentrations of Zn, Cu and MBAS in three statistical replicates (n = 3) to evaluate ecotoxicological effects induced by exposure compared to control populations. Exposures were performed simultaneously in a multiple battery of 72-h toxicity tests. For controls and for each toxicant dosage, sample aliquots were collected after 24, 48 and 72 h of exposure for determination of cell density by both spectrophotometry and Burker’s chamber counts. One sample aliquot was filtered for the quantification of physiological endpoints (Chl-a; Phe) while another aliquot was fixed after 24 and 72 h of exposure for the confocal microscopy analysis.

An algal lot (PT 151112, expiration date 30/04/13) of the marine AlgalToxkitÒ purchased from EcotoxÒ (Italy) was pre-enriched up to a final density of 3 9 105 cells mL-1 in a culture medium composed of ASPM (lot n. 130712, expiration date 13/07/14), sodium silicate (100 mM), nutrient stock solution (NS290812) and LysoTracker Yellow HCK-123 (lot n. 778064, Invitrogen) at 1 mM concentration (Descle´s et al. 2008; Annenkov et al. 2010). Illumination, temperature, salinity, pH and dark/light photo-cycle were set as indicated in AlgalToxkitÒ. Growth-rate inhibition test Growth-rate inhibition tests were performed in accordance with UNI EN ISO 10253, which is based on the exposure

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of exponentially growing cells of P. tricornutum to various concentrations of the tested substance over several generations and under standardized conditions. Inhibition of growth compared to a control culture is determined over a fixed period of time. Pre-enriched cultures are suitably diluted in toxicant solutions to obtain a cell density of about 104 cells mL-1 at the start (T0) of experiments. In this study, salinity (32 PSU) and temperature (20 ± 0.5 °C) were constantly monitored, while pH was measured and recorded at 24, 48 and 72 h to check that it did not deviate from its starting value by more than one unit. Cell densities were determined both by spectrophotometry and Burker’s chamber counts. Optical density was obtained by double-ray spectrophotometer (Jenway, mod. 6505 UV/Vis, wavelength 670 nm, optical length 10 cm) and the absorbance trend of the culture medium was determined by performing a full scan in the 500–750 nm spectral region to test for possible interference due to the dye. Maximum absorbance of the culture medium (0.249) was observed at 525 nm but at 670 nm (-0.016) measurement was not affected by the dye. Cell counts were performed with a Burker’s chamber from three aliquots of 100 lL. Measurements were performed at start (T0) and after 24 h (T24), 48 h (T48) and 72 h (T72) of exposure. The cell growth inhibition percentage at each test substance concentration (I %) was calculated as the difference between the area under the control growth curve (Ac) and the area under the growth curve at each test substance concentration (At), i.e.: I % ¼ AcAAi  100: c

Areas were calculated as follows: A¼

NT24  NT0 NT24 þ NT48  2NT0 K þ K 2 2 NT72 þ NT48  2NT0  K; þ 2

where NT0, NT24, NT48, NT72 are the nominal numbers of cells mL-1 at T0, T24, T48, T72 respectively and K is the time between observations (24 h). Growth-rates determined by cell counts are used to calculate the IC50 (95 % confidence interval) and IC20 (95 % confidence interval) after 72 h of exposure. The inhibition (%) values are plotted on a semi-logarithmic probit paper against the corresponding concentrations. The points plotted on the probit paper are fitted by a computed regression line to interpolate both IC20 and IC50, which are the concentrations at which the regression line passes through the 20 and 50 % inhibition levels. The reliability of cell culture responses is evaluated using both negative (culture medium; variation coefficient \10 %) and positive (potassium dichromate, K2Cr2O7) controls (n = 3). Test validity criteria required algal growth in controls to increase by a factor of 16 within the 72 h test period and pH not to have varied by more than ±1 unit during the test.

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Alteration of the photosynthetic complex During the growth-rate experiment, a suitable sample aliquot of each toxicant dose at each exposure time was collected for evaluation of the sensitivity of the photosynthetic complex, which is considered a useful physiological endpoint for assessing early effects on cells exposed to sub-lethal doses of toxicants. The collected aliquots were filtered on pre-cleaned glass fibre filters, using a vacuum bottle to reduce filtration time to a maximum 10 min, for spectrophotometric determination of photosynthetic pigments. Immediately after filtration, filters were treated in the dark using a weak green light to avoid pigment deterioration. Glass fibre filters were kept on ice and extracted by potter for 5 min using a solution of 3 mL of dimethyl sulfoxide and 3 mg of polyvinyl-poly-pyrrolidone. Extracts were stored in darkness for 18 h and then centrifuged (4,000 RPM for 10 min) to collect the supernatant. Precipitates were extracted for a second time with 3 mL of dimethyl sulfoxide to maximize recovery and stored for 6 h in darkness. The unified extracts were analyzed by spectrophotometry after checking for turbidity interference. If the measured absorbance at k = 750 nm was \0.01, samples were analyzed at k = 415, 435, 480, 649 and 665 nm. Concentrations of chlorophyll-a (Chl-a) and its allomers (b-carotene and xanthophyll, Chl-cx) were estimated using Wellburn (1994) equations: chla ¼ ð12:19  ABS665Þ  ð3:45  ABS649Þ and chlcx ¼ ðð1; 000 ABS480Þ  ð2:14  chlaÞÞ  0:00455. Chl-a degradation is expressed as the ratio of phaeophytin (Phe) in exposed cells to phaeophytin in controls. Phe was calculated in accordance with Ronen and Galun (1984), as Phe = ABS435/ABS415. Measurements by confocal and optical microscopy During the growth-rate experiment, a suitable sample aliquot of each toxicant dose was collected for confocal microscopy analysis, which for technical reasons was conducted for three times (T0, T24 and T72) and for the minimum and maximum concentrations for each toxicant (Cu and Zn 25–100 mg L-1; MBAS 0.025–0.100 mg L-1). A confocal laser scanning microscopy system (Nikon C1 Confocal Microscope) equipped with an inverted microscope (Nikon TE300 ECLIPSE) and an image analysis system (NIS Elements AR software, Nikon) was used to determine physiological and morphological endpoints such as cell fluorescence and biovolume variation. Diatoms co-precipitate the dye LysoTracker Yellow HCK-123 within the silica deposition vesicles where new siliceous frustules are formed (Li et al. 1989; Descle´s et al. 2008), making it possible to detect growing frustules by their fluorescence. Samples of exposed and non-exposed algal

Early warning tools for ecotoxicity assessment Table 1 Ecotoxicity tests: methods, physiological versus morphological endpoints, advantages and disadvantages Method

Growth inhibition

Spectrophotometer

Burker’s chamber

Endpoints Physiological

Morphological

Advantages

Disadvantages

Number of exponentiallygrowing cells under experimental conditions

No

Ease of performing tests, good reproducibility and availability of standardised protocols

Results affected by turbidity of sample/Early or sub-lethal effects are not detected

Ease of performing tests, good reproducibility and availability of standardised protocols/Avoids errors due to turbidity of sample

Time consuming/Counting errors due to operator

Alteration of the photosynthetic complex

Spectrophotometer

Efficiency of the photosynthetic complex

No

Early detected effects of toxicity at sub-lethal doses

Limits due to low concentration of cells in sample

Cell biovolume

Confocal microscopy

No

Biovolume variation

Cell size is modified in different ways under different kinds of environmental stress

Need for technical expertise, advanced equipment and high acquisition and running costs

Cell fluorescence

Confocal microscopy

Detection by fluorescence of growing frustules

No

Early detected effects of toxicity at sub-lethal doses

Need for technical expertise, advanced equipment and high acquisition and running costs/ At present method is qualitative and needed to be tested for quantitative analysis

Cell structural alteration

Optical microscopy

No

Structural cell variation in shape

Cell size is modified in different ways under different kinds of environmental stress/ Highlights effects occurring at single-cell level

Technical advances and high acquisition and running costs are required/At the moment the method is qualitative and needed to be tested for quantitative analysis

cells were fixed with formaldehyde at a final concentration of 5 %, stored in darkness and imaged for chlorophyll fluorescence within a week of fixation to prevent significant effects of formaldehyde on algal fluorescence (Larson and Passy 2005). The confocal microscope was equipped with Ar ion and HeNe lasers with excitation wavelengths of 488 and 543 nm respectively to record optical sections. The confocal microscope was coupled to a Z-stage piezocontroller. The objective used was an 1009 oil immersion plan APO. For each experimental condition 25 random cells were selected in order to reconstruct a 3D model of each cell using NIS-Elements AR software (Nikon Instruments, version 3.06). Image acquisition settings were initially optimized on control samples and were not changed during the acquisition of subsequent images. Cells were optically z-sectioned using the pinhole diameter to regulate the thickness depending on the fluorescence intensity of the control sample. Seeking the best compromise between resolution and acquisition time, the number of slices was 53 ± 11 (mean ± SD) and the distance between slices was 0.2 lm. Confocal microscopy analyses were performed as reported in the literature (Roselli et al. 2013). The acquired images were processed with the image analysis system in

order to visualize cell morphology in the xyz orthogonal projection and to measure morphometric cell distances on the xyz axes (Roselli et al. 2013). Biovolume was calculated by association with an ellipsoid in accordance with references (Hillebrand et al. 1999), taking account of all three dimensions. The lengths of all the segments needed to calculate volume were measured from the acquired images as described in Roselli et al. (2013). The confocal microscopy approach (Table 1) was used for biovolume quantification (morphological endpoint) and for qualitative analysis of other possible physiological endpoints (autofluorescence alterations). Statistical analysis Statistical analyses were performed using GraphPad Prism (GraphPad Software, San Diego, CA, USA, www.graph pad.com). A specific-sized GraphPad Prism routine was used to plot and interpolate the EC50 and EC20 values and their 95 % confidence intervals. The results were statistically analyzed to calculate the average values (±standard deviation) and the significance of observed differences between treated samples and controls. Graphics were

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M. Renzi et al. Fig. 2 Comparison of cell density values obtained by different methods. Differences between results obtained by Burker’s chamber counts (average values ? SD, n = 20) and spectrophotometric readings (average values ? SD, n = 3) for different doses at each exposure time. T0 readings were performed immediately after toxicant addition. Results are expressed as number of cells per millilitre of culture solution. Average differences (%) among control counts (±SD) were: 1.3(±0.05), 6.5(±0.03), 15.5(±0.1), 0.3(±0.03) at T0, T24, T48 and T72 respectively. Average counts (as number of cells per millilitre) for the Burker’s chamber were: 100,121 (T0), 150,035 (T24), 249,099 (T48), 951,060 (T72); for the spectrophotometric readings they were: 98,693 (T0), 140,277 (T24), 211,083 (T48), and 953,045 (T72)

drawn and analyses (Student t test and F-test) were conducted. Concerning cell growth tests, cell count values measured in replicates (n = 3) are used to perform both the F test (homogeneity of variance) and the Student t test to evaluate the significance of differences between samples

123

and controls. The same statistical analyses were performed on morphological (biovolume, length, width and height) and physiological (Chl-a, Phe) endpoints (dependent variables) to evaluate significant differences between experimental conditions (time and concentrations as independent

Early warning tools for ecotoxicity assessment

variables) and control conditions. In both cases, differences are considered significant if they exceed 10 % compared to controls at a p level below 0.05 (Sarni and Onorati 2009). Comparison of different endpoints was performed on the basis of EC50 and EC20 values.

Results Results obtained by different cell count methods In Fig. 2 cell densities (average number of cells per mL of culture medium ? standard deviation) measured by spectrophotometry are compared to the Burker‘s chamber counts. Results are reported for each dose at each exposure time. Readings performed on controls with the two considered methods show comparable values with differences within the range 0.3–15.5 % (F test, p [ 0.05). Significant differences between the methods (F test, p \ 0.01) were recorded for Zn and Cu solutions. Specifically, higher values were recorded by spectrophotometry. Regarding Zn, major differences (over 200 %) were recorded after 48 and 72 h of exposure but no dose-dependency was observed. Concerning Cu, differences in cell numbers were negligible at lower concentrations at all times but were within the ranges 520–689 % at 50 mg L-1, 987–1004 % at 75 mg L-1 and 2,262–5,429 % at 100 mg L-1. Concerning MBAS, the differences observed were within statistical errors for each dilution and exposure time (F test, p [ 0.05).

Fig. 3 Growth inhibition test results. Average number of cells (n = 3) is reported for each dose and time (reported data are from Burker’s Chamber counts)

Dose-dependent responses

Photosynthetic complex

Growth-rate inhibition test (values derived from Burker‘s chamber counts)

The efficiency of the photosynthetic complex (the Chla ratio, given as a percentage) is evaluated as the ratio of chlorophyll-a to chlorophyll-a plus its allomers. The results obtained are represented in Fig. 4, which also shows the phaeophytin ratios. At the start of the experiment (T0), the observed average Chl-a ratios were within the range 85–92 % for the tested toxic compounds and controls (92 %). After 24 h of exposure, Chl-a ratios were significantly lower (Student t test, p \ 0.01) than controls for all concentrations of Zn (79–83 %) and Cu (31–56 %). In contrast, for MBAS, Chl-a ratios were not significantly different (82–87 %). After 48 h of exposure, the Chla ratios of treated cell cultures were significantly lower than controls for all concentrations of Zn, Cu and MBAS (Student t test, p \ 0.01). The trend was similar after 72 h of exposure. Figure 4 also shows a clear and progressive increase in Phe ratios after 24, 48 and 72 h of exposure for all toxicants. The observed values at these times being significantly higher than both controls and T0 values (Student t test, p \ 0.01). Particularly high values were

Figure 3 shows growth inhibition curves (average values, n = 3) for each tested toxicant compared to controls. After 24 h (T24) of exposure to Zn, treated cells show greater growth than controls at all concentrations. In contrast, at the end of the experiment, clear inhibition of growth is observed for all concentrations, with the average cell number close to the T0 value for the higher doses (50, 75 and 100 mg L-1). Cu displays clear toxicity at T24, T48 and T72 at higher doses (50, 75 and 100 mg L-1), with the average cell numbers lower than starting values for T24 and T48 and lower than controls for all times. Exposure to 25 and 38 mg L-1 for 24 h stimulates cells but a decreased cell number is seen after 48 and 72 h. Cells exposed to MBAS concentrations of 0.025–0.075 mg L-1 show greater growth than controls after 24 h, and all doses show greater growth than controls at 48 h. Inhibition is observed after 72 h at all concentrations.

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M. Renzi et al. Fig. 4 Efficiency of photosynthetic complex. The efficiency of the photosynthetic complex is reported in the figure as Chl-a/Chl-a ? allomer % ratios (left) and Phaeophytin ratios (right). The time scale on the left is reversed with respect to the right. Average control values for the Chl-a/Chla ? allomer % ratios were: 92 % (T0), 90 % (T24), 90 % (T48) and 89 % (T72), with an average Chl-a value of about 0.056 ± 0.002 pg cell-1. Average Phe levels in controls were 0.006 ± 0.001 pg cell-1

observed for Cu exposure at higher doses (50, 75 and 100 mg L-1) after 48 (15.3–21.4) and 72 h (16.6–20.7). A clear tendency of the Phe ratio to increase with dose was observed for each toxicant at each exposure time. Physiological and morphological endpoints Table 2 shows cell biovolume and linear dimensions (length, width, height) as maxima, minima, average values (±standard deviation, significance level below 0.05) for each tested concentration after 24 and 72 h of exposure. The volume of cells ranged from 58 to 112 lm3 in controls and from a minimum of 55 lm3 in MBAS-treated cells to a maximum of 174 lm3 in Zn-treated cells. After 24 h’ exposure to low toxicant concentrations, biovolume was lower for Zn and greater for Cu and MBAS. In contrast, at higher concentrations biovolume was greater for Zn and lower for Cu and MBAS. However, 72 h of exposure to

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both Cu and MBAS at all concentrations caused cells to decrease in biovolume while exposure to Zn caused cell biovolume to increase in accordance with a clear pattern. Although the biovolume of treated samples differed from controls, the Student t-test showed significant differences in only a few cases (Table 2). The Student t-test was also performed on the three linear dimensions (length, width, height) individually, again showing few significant differences (Table 2). However, the F test performed on the same dataset showed significant differences in biovolume (or at least one of the three measured cell dimensions) between controls and treated samples after 72 h of exposure (underlined values in Table 2). Some physiological (i.e. chloroplast and frustule autofluorescence) and morphological alterations (frustule formation) were observed by confocal and optical microscopy during measurements of the morphological endpoint (biovolume) and are shown in Figs. 5 and 6. From an

2.1

1.8

Cell size was determined from analysis of 25 random cells by inverted microscope at 1009 magnification and image analysis system. Cell dimensions are cell length, width and height (at widest section). SD = standard deviation. Significant differences with respect to controls at a p level below 0.05 for Student t test and F test are in bold and underlined respectively. Volumes were calculated by visualizing cell as an ellipsoid

2.7 0.2 2.4 2.3 2.9 0.2 22.9 – Control

89.4

16.7

111.9

58.4

27.3

2.5

31.8

2.6

2.0 2.9

2.9 0.4

0.2 2.3

2.4 2.2

2.2 2.7

3.2 0.3

0.2

22.2

2.6

21.3

1.8

28.3

23.8

24.8 55.1

51.6 89.3

122.2 21.6

10.9 67.2 0.025

0.1

MBAS

MBAS

81.4

2.4

27.8

2.4

1.8

1.6 2.9 0.4 2.1 1.7 3.2 0.5 24.6 100 Cu

73.4

30.0

137.7

37.1

27.8

2.1

31.2

2.3

1.7 3.2

3.0 0.4

0.5 2.5

2.4 1.8

2.1 3.7

3.5 0.5

0.5

24.2

2.6

24.2

2.4

31.6

29.0

27.5 43.5

60.0 174.7

130.3 26.4

39.3 112.8 100

25

Zn

Cu

88.2

2.6

33.3

2.9

2.0

1.9 3.2

3.1 0.3

0.4 2.5

2.6 2.2

2.2 3.5

3.3 0.3

0.4 2.8

2.9

25.0

21.8

31.6

30.8 2.2

2.0 27.2

26.6 60.6

58.7 150.5

155.0 28.7

29.3 101.6

105.3

–

25

Control

Zn 72 h

2.3

1.8 2.8

3.2 0.3

0.3 2.3

2.8 2.5

1.8 3.1

3.5 0.3

0.4 22.4 30.5

3.0 23.9 31.4 2.3

2.5 26.7

28.4 76.1

43.6 125.4

169.5 27.9

25.3 80.9

126.1 0.025

0.1

MBAS

MBAS

100 Cu

83.6

32.9

139.1

35.0

26.9

2.6

23.8

2.5

2.1

1.6 2.3 0.4 2.3 1.6 3.3 0.5

2.0

32.4

2.5

3.2 0.3 2.6 2.4 3.5 0.3 23.9 25 Cu

106.3

26.6

167.4

67.3

27.4

1.3

28.6

2.8

2.0 3.1

3.2 0.4

0.3 2.4

2.7 2.3

2.1 3.4

3.7 0.4

0.4

23.0

3.0

19.9

2.8

32.3

24.7

28.0 64.6

47.7 138.6

183.2 32.3

27.0

100 Zn

83.8 25 Zn 24 h

117.8

3.0

29.5

2.6

SD Mean SD Mean Min Max SD Mean SD

Max

Min Mean

Width (lm) Lenght (lm) Volume (lm3) Dose (mg L-1) Treatment Exposure time

Table 2 Biovolume, length, width and height (mean, standard deviation) of P. tricornutum exposed to Zn, Cu or MBAS at 24 and 72 h

Max

Min

Height (lm)

Max

Min

Early warning tools for ecotoxicity assessment

observational point of view, cells showed fusiform and oval morphotypes corresponding to ellipsoid biovolume, in which the larger part represents the chloroplast (red arrow, Fig. 5) and the thinner sextremes presumably the newly formed frustule (white arrows, Fig. 5). Comparing images of controls and treated samples, a clearly reduced fluorescence signal was observed after 72 h of exposure to both Zn and Cu for each dose tested. A substantial effect on cell fluorescence was also observed for Cu after 24 h for each dose. However, exposure of cells to MBAS (0.025 and 0.1 mg L-1) did not seem to result in lower fluorescence than controls. Figure 6 shows morphological differences between treated P. tricornutum cells and controls. Specifically, cells exposed to Zn and Cu showed chloroplast reduction, and cellular frustules had irregular boundaries and shrivelled shapes compared to controls. Plasmolysis was also observed. Specifically, cells treated with Cu and Zn displayed significant alteration of the structure at each tested toxicant dilution after 24 and 72 h. Cells did not show morphological effects as a result of exposure to MBAS at any dilution or time.

Comparison of endpoints Comparisons of tested endpoints were performed on the basis of IC50/EC50 and IC20/EC20 values. Table 3 shows data for the traditional ecotoxicological endpoint, evaluated on the basis of the growth curves as growthrate inhibition after 72 h of exposure. Of the tested toxicants the highest absolute toxicity was recorded for MBAS (IC50 = 0.227 mg L-1) followed by Cu (IC50 = 36.51 mg L-1) and Zn (IC50 = 177.08 mg L-1). The growth-rate inhibition recorded for the tested concentrations of Zn and MBAS did not allow direct calculation of the IC50, which was possible only for Cu. The IC50 calculated by extrapolation for Zn is 177.1 mg L-1 (range 149.5–204.6 mg L-1), whereas the IC20 lies within the tested dilutions: 70.8 mg L-1 (range 59.8–81.9 mg L-1). Cu displays higher toxicity, the IC50 being calculated as 36.5 mg L-1 (range 29.2–43.8 mg L-1) and IC20 as 14.6 mg L-1 (range 11.7–17.5 mg L-1). The IC50 of MBAS calculated by extrapolation is 0.23 mg L-1 (range 0.05–0.41 mg L-1), which is twice the maximum tested concentration, and the IC20 is 0.09 mg L-1 (range 0.02–0.16 mg L-1), which is close to the maximum tested concentration. Reliability tests performed using both negative (culture medium) and positive (K2Cr2O7) controls highlight growth stimulation for negative controls and strong inhibition for positive ones. The selected doses are at sub-lethal concentrations both for MBAS (IC20 = 0.09 mg L-1) and Zn (IC20 = 70.8 mg L-1), while the tested Cu doses go beyond the lethal threshold.

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M. Renzi et al. Fig. 5 Acquisition of cell fluorescence. Confocal microscopy images of P. tricornutum showing autofluorescence of chloroplasts in central part of cells (red arrow) and fluorescence of newly synthesized frustules (white arrows). Scale bar 10 lm (Color figure online)

Table 4 shows EC20 and EC50 data for the physiological endpoints, evaluated on the basis of Chl-a and phaeophytin alteration after 24, 48 and 72 h of exposure. Concerning chlorophylls, after 24 and 48 h of exposure to Zn, the EC50 values are not calculable, whereas the EC20 is calculable after 48 h (88.3 mg L-1). After 72 h of exposure, the EC50 calculated for Zn is 75.3 mg L-1, whereas the EC20 is 32.2 mg L-1. Cu shows higher toxicity, the EC50 being calculated as 36.9 mg L-1 after 24 h whereas at 48 and 72 h the EC50 is lower than the minimum dose tested. The EC50 of MBAS is not calculable at any time whereas the EC20 after 72 h is 0.041 mg L-1. Regarding phaeophytin, after 24, 48 and 72 h of Zn exposure, the EC50 values range from 41.9 to 59.4 mg L-1, whereas the EC20 is calculable

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after 48 h (26.1 mg L-1). Specifically, after 72 h of exposure, the EC50 calculated for Zn is 41.9 mg L-1, whereas the EC20 is lower than the minimum dose tested. Cu shows higher toxicity, the EC50 being calculated as 26.0 mg L-1 after 24 h whereas; at 48 and 72 h the EC50 is lower than the minimum dose tested. The EC50 of MBAS is 0.053 mg L-1 after 24 h whereas EC20 is 0.041 mg L-1. After 48 and 72 h of MBAS exposure both the EC20 and EC50 are lower than the minimum dose tested. Table 5 shows EC20 values calculated for the morphological endpoint proposed (change in average biovolume) after 24 and 72 h of exposure. Biovolume changes are reported as percentages and given as average values. EC50 values were not calculable for any tested concentration at

Early warning tools for ecotoxicity assessment Fig. 6 Structural and morphological alterations due to toxicant exposure. Light microscopy images of P. tricornutum showing cell morphological alterations. Scale bar 10 lm

any time. Concerning Cu, the EC20 was not calculable even after 72 h of exposure while the EC20 of Zn after 24 h of exposure is 100 mg L-1 and after 72 h is 25–100 mg L-1. The EC20 of MBAS is lower than 0.025 mg L-1 after both 24 and 72 h of exposure. The EC20 and EC50 were not calculated for other morphological endpoints (frustule formation, structural alterations).

Discussion Comparison of spectrophotometric readings with counts performed by optical microscopy using a Burker’s chamber did not show significant differences for controls or MBAS, confirming that the methods produce comparable results in ecotoxicological tests based on algal cells. However,

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M. Renzi et al. Table 3 Ecotoxicological endpoints calculated for traditional growth inhibition test Toxic substance

Dose (mg L-1)

pH T0

pH T72

Zn

25

7.48 ± 0.17

7.63 ± 0.38

6

Zn

38

7.58 ± 0.09

7.86 ± 0.11

10

Zn

50

7.69 ± 0.06

7.90 ± 0.09

16

Zn

75

7.49 ± 0.12

7.85 ± 0.09

19

Zn

100

7.85 ± 0.05

7.85 ± 0.07

30

Cu

25

7.47 ± 0.03

7.48 ± 0.04

34

Cu Cu

38 50

7.42 ± 0.09 7.64 ± 0.06

7.51 ± 0.16 7.29 ± 0.02

52 86

Cu

75

7.81 ± 0.17

7.75 ± 0.13

91

Cu

100

8.00 ± 0.16

7.39 ± 0.01

114

MBAS

0.025

7.24 ± 0.02

8.05 ± 0.16

-118

Growth inhibition %

IC20

CI 95 %

IC50

CI 95 %

70.8

59.8

81.9

177.1

149.5

204.6

14.6

11.7

17.5

36.5

29.2

43.8

0.09

0.02

0.16

0.23

0.05

0.41

MBAS

0.038

7.56 ± 0.13

8.01 ± 0.03

-67

MBAS

0.050

7.33 ± 0.03

8.07 ± 0.01

-20

MBAS

0.075

7.40 ± 0.17

8.00 ± 0.08

9

MBAS

0.100

7.54 ± 0.11

8.14 ± 0.02

22

Culture medium

–

7.68 ± 0.10

8.29 ± 0.08

–

N.c.

–

–

N.c.

–

–

K2Cr2O7

–

7.95 ± 0.09

8.19 ± 0.05

–

N.c.

–

–

9.75

9.25

10.82

Ecotoxicological endpoints calculated for traditional growth inhibition tests; pH values (T0, T72), and 95 % confidence intervals (CI95 %) are reported. Notes: IC average values (n = 3) and 95 % confidence intervals are expressed as mg L-1 and calculated as detailed in methods. Negative growth inhibition percentages indicate biostimulation. Reliability of cell stock culture responses was evaluated using both negative (culture medium, average variation coefficient = 5.3 %) and positive (K2Cr2O7) controls N.c. not calculated

measurements performed on both Zn and Cu solutions showed significant differences between the two methods, with important implications. This difference was probably due to two factors. Concerning Zn, spectrophotometric readings are significantly affected by the formation of white precipitates. This interference is time-dependent but not dose-dependent. Precipitate formation is probably enhanced by pH correction (from acidic to basic conditions) by addition of NaOH before the algal cells, which serves to create conditions compatible with the algal cells’ life. In contrast, the interference in Cu displayed significant dose-dependency and non-significant time-dependency. This was mainly due to the blue pigmentation of coppercontaining solutions, which show notable dose-dependent absorbance at the wavelength of 670 nm, significantly affecting cell density evaluations by spectrophotometry. These findings suggest caution should be applied when using this procedure in ecotoxicological tests based on precipitate-forming mixtures and coloured solutions, in order to avoid overestimates of cell densities and hence false negatives. Specifically, prudence is advised when working with natural environmental samples that are characterized by high turbidity and/or yellow or red pigmentation, as found for example in transitional waters or harbours. Such ecosystems are characterized by high

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concentrations of small-diameter sediment particles and pigments originating from humic and dissolved organic substances in water. In these cases more realistic cell counts can be obtained by optical microscopy techniques using the traditional Burker’s chamber method and suitable replication of data acquisitions to reduce statistical errors caused by the operator. The development of new endpoints for P. tricornutum could also help to overcome this procedural limitation and highlight early and sub-lethal ecotoxicological effects that are not detected by the traditional growth-rate inhibition test. Different mechanisms of toxicity are responsible for the different dose-dependent behaviour observed in this study of the considered ecotoxicological endpoints. The selected toxicants belong to different classes of compounds, heavy metals and surfactants, acting on both algal metabolism and cellular structure via different molecular mechanisms, which may affect the tested endpoints differently. Cells exposed to heavy metals displayed early effects (even at lower doses) on the photosynthetic pathway rather than on growth-rate inhibition. Heavy metals may affect photosynthesis directly. Once inside the cell, they can cause membrane depolarization and cytoplasmic acidification, leading to the disruption of cellular homeostasis (Pinto et al. 2003). At this point, heavy metals bind to proteins to

Early warning tools for ecotoxicity assessment Table 4 Physiological endpoints Chl-a

T48

T24

T72

EC20

EC50

Zn

[100

N.c.

88.3 (85.9–96.4)

N.c.

32.2 (29.7–38.1)

75.3 (69.9–81.5)

Cu

\25

36.9 (32.5–41.7)

\25

\25

\25

\25

MBAS

N.c.

N.c.

N.c.

N.c.

0.041 (0.031–0.052)

N.c.

Phe

EC20

T24

EC50

EC20

T48

EC50

T72

EC20

EC50

EC20

EC50

EC20

EC50

Zn

N.c.

59.4 (51.3–62.5)

26.1 (22.4–29.6)

53.1 (48.1–57.9)

\25

41.9 (36.6–44.3)

Cu

\25

26.0 (21.9–29.3)

\25

\25

\25

\25

MBAS

0.041 (0.035–0.048)

0.053 (0.047–0.059)

\25

\25

\25

\25

EC20 and EC50 values are evaluated with reference to the proposed physiological endpoints (Chlorophyll-a and phaeophytin alterations); 95 % confidence intervals are shown in brackets. Chl-a = % Chl-a/(Chl-a ? allomer); EC average values (n = 3) are expressed as mg L-1 and calculated as detailed in methods N.c. not calculated

Table 5 Morphological endpoint (biovolume) Toxicant

Biovolume change % (dose)

EC20

24 h

72 h

24 h

72 h

Zn

20.0 (HD)

26.2 (HD)

100

25–100

Cu

17.7 (HD)

17.9 (HD)

N.c.

N.c.

MBAS

24.2 (LD)

24.8 (LD)

\0.025

\0.025

EC20 values are evaluated with reference to the proposed morphological endpoint (average biovolume). EC50 values were not calculable. Biovolume changes are reported as percentages and calculated with reference to average values. The doses for which the measured changes are observed are also reported. EC values are expressed as mg L-1 N.c. not calculable, HD higher dose, LD lower dose

form a metal–protein complex, which can affect enzymatic systems, growth, photosynthesis, respiration, reproduction, nutrient assimilation, and molecular synthesis (Morin 2003). Specifically, when Zn is present in excess, crucial processes such as growth (Stauber and Florence 1990) and photosynthesis (Nguyen-Deroche et al. 2009) are partially or totally inhibited, while oxidative stress develops (Li et al. 2006; Rijstenbil 2003). Cu has been reported to inhibit growth more than photosynthesis (Cid et al. 1995) and to cause oxidative stress specifically in P. tricornutum (Wang and Zheng 2008). Like other metals, Cu affects the permeability of the plasma membrane, causing loss of organic matter (Steeman-Nielsen and Wium-Andersen 1971), loss of potassium (Rai et al. 1981) and reduction in the uptake of essential elements and compounds such as manganese (Sunda and Huntsman 1983) and silicic acid (Rueter et al. 1981). In contrast, surfactants have been shown to produce

significant alterations of lipids and biological membranes, inducing cell lysis at higher doses (Pavlic´ et al. 2005). In this study, cells exposed to lower surfactant (MBAS) doses displayed biostimulation (in the growth-rate inhibition test) that could represent an initial reaction to stressors (Soukupova et al. 1999) and an early effect on biovolume. Hormesis is a dose–response relationship that is characterized by low dose stimulation and a high dose inhibition (Calabrese 2008). This response is very generalizable, it is commonly reported to occur in vegetal being independent of the species, endpoint measured, and chemical class/ physical agent tested (Calabrese 2009). In nature, different factors such as symbiosis, density-dependent factors, time, and contrasting environmental factors (availability of nutrients, temperature, light, etc.) affect both the range and amplitude of hormetic responses and could determine different growth behaviour. In spite of its ecological importance, biphasic dose response phenomena in algae have not been extensively studied. Few studies that have focused on the growth parameter in algae found non-monotonic trends according to the dosage of an applied chemical (Hashmi et al. 2014). The hormetic model is quite common for a wide range of both inorganic and organic chemicals. The principal dose–response relationship is characterized by two different behaviours: the inverted U-shaped hormetic model and the J-shaped hormetic model (Hashmi et al. 2014). Results obtained in this study evidenced that cell growth followed a general U-shaped hormetic model as effect to the exposure to Cu, MBAS, and Zn with the exception of cells exposed to the highest Cu dose which showed a J-shape hormetic model. The biochemical and physiological effects of surfactants and their toxic effects on algal growth have been studied extensively (Yamane

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et al. 1984; Nyberg 1988; Dirilgen and Ince 1994) and it is reported that algae are highly variable in their sensitivity to surfactants (Aidar et al. 1997; Pavlic´ et al. 2005). According to Becaglia et al. (2011), increased MBAS concentrations could be a cause of phytoplankton blooms by supporting enhanced growth of algal cells. In contrast, the effects of MBAS on biovolume are described here for the first time. A comparison of sensitivity, performed on the basis of IC50/EC50 and IC20/EC20 values for both the traditional endpoint (growth-rate inhibition) and morphological and physiological endpoints (biovolume, Chl-a, Phe) is shown in Table 6. The same table also shows a preliminary and qualitative evaluation for the other morphological (structural alterations, anomalies of frustule formation) and physiological (auto-fluorescence inhibition) issues observed in this study. Physiological endpoints could be detected earlier and could show greater sensitivity of response than the traditional endpoint (growth-rate inhibition). The population endpoint (growth curve) at 72 h is affected to a greater extent than the photosynthetic endpoint at 24 h (Othman et al. 2012). Indeed, after exposures of 24 h or longer, the phaeophytin ratio can be used to estimate EC50 values for all toxicants. Furthermore, after 72 h, lower toxicant concentrations are sufficient for detection of EC50 values for both physiological endpoints (Chl-a; Phe) but not for IC50 values. Concerning MBAS, no data are available on the toxicity responses of P. tricornutum but ecotoxicological tests performed on another algal species (Selenastrum capricornutum) show IC50 values within the range of 1–1,000 mg L-1 (PAN-Pesticides Database—Chemical Toxicity Studies on Aquatic Organisms). IC50 reported for Dunaliella bardawil after 10 days of exposure to sodium dodecyl benzene sulfonate are 2,044 mg L-1 (637.3 SD) (Qv and Jiang 2013). Pavlic et al. (2005) evidenced IC50 ranging from 0.35 ± 0.03 to 1.25 ± 0.07 mg L-1 to surfactants in P. tricornutum. A recent research shows that the sensitivity to surfactants differ by one order of magnitude depending on the algae species being tested with a clear specie-specific response (Pavlic et al. 2005). In this study the sensitivity of the photosynthetic complex was found to be consistent with the results obtained for the biovolume endpoint. Previous research performed on natural assemblages and other phytoplankton species showed that biovolume calculation obtained by confocal microscopy may represent an interesting endpoint for both ecological and biomonitoring purposes (Larson and Passy 2005; Roselli et al. 2013). Few studies are available regarding the impact of Cu and Zn on alga morphology and proliferation capacity but a recent research evidences as Cu causes an increase in cell size of freshwater (Pseudokirchneriella subcapitata and Chlorella sp.) and marine (P. tricornutum) algae, while Zn-treated cells of the marine diatom Nitzschia closterium are larger

123

than control cells (Machado and Soares 2014). However, the differences between the cell volumes of treated samples and controls were significant in this study only for MBAS. The low sensitivity of size traits was also observed by Weiner et al. (2004). Biometric (morphological features) represent an important tool for highlighting species health and responses to environmental stressors (Sabetta et al. 2008a, b; Falasco et al. 2009; Ludovisi et al. 2012; Lugoli et al. 2012; Dromph et al. 2013; Vadrucci et al. 2013). However, no general trend appears to link copper-induced toxicity to cell size (Levy et al. 2007). Although in one study exposure of P. tricornutum to Cu at 10 lg L-1 caused cells to increase in size, at higher concentrations there was no further increase (Levy et al. 2008). In this study however, although biovolume as a morphological descriptor did not show (with the exception of MBAS) significant differences between control and exposed conditions in most cases, morphological alterations in cell structure were qualitatively observed. As reported in the literature, Cu and Zn produced asymmetrical, abnormal and bent frustules with notched or incised valves (Nunes et al. 2003). We also observed reduction of chloroplast size in cells exposed to Zn and Cu, as reported in the literature for chloroplasts exposed to heavy metals (SickoGoad 1982; Rachlin et al. 1984; Chan and Wong 1987; Rai et al. 1990; Visviki and Rachlin 1992). The endpoints explored in this study for detection of stress-induced alterations (i.e. fluorescence capacity, photosynthetic complex efficiency, cell biovolume and cell morphological changes) have important implications for the evaluation of early and sub-lethal effects that are not conventionally detected by the traditional growth-rate inhibition test. The efficiency of the photosynthetic complex proved to be a sensitive physiological endpoint for evaluating the early effects of toxicity and highlighting stress responses occurring at sub-lethal doses. Furthermore, chlorophyll-a degradation, expressed using the ratio of phaeophytin in exposed cells to phaeophytin in controls, is reported by the literature to be indicative of metabolic stress in algal cells (Lichtenberg et al. 1988), and was also found to be sensitive in this study. In ecotoxicological studies, multi-parametric optical detection methods have definite advantages over traditional growth-rate inhibition assays, including rapidity of acquisition, reduction of manual procedures and the possibility of reading early and sub-lethal endpoints. In this study, confocal microscopy images showed a clear decrease in pixel intensity, indicating lower cell fluorescence after 24 h of exposure at low doses of Zn and Cu, supporting their use in detecting both early and sub-lethal effects on algal cells, despite P. tricornutum being one of the most tolerant algae in terms of heavy metal pollution (Falasco et al. 2009). This irreversible damage to cells, expressed in gradually decreasing cell fluorescence, is probably due to

Early warning tools for ecotoxicity assessment Table 6 Sensitivity scale of tested endpoints Endpoint

Approach typology

Cu

Zn

MBAS

Growth inhibition

Quantitative

***

**

**

Alteration of the photosynthetic complex

Quantitative *****

***

**

Chl-a

*****

*****

*****

Cell biovolume

Quantitative

Phe

*

**

****

Cell fluorescence

Qualitative

Effects at low doses

Effects at low doses

Effects at low doses

Cell structural alteration

Qualitative

Effect observed

Effect observed

Effect observed

* IC20/EC20 not measurable after 72 h ** IC20/EC20 measurable after 72 h *** IC50/EC50 measurable after 72 h **** IC20/EC20 measurable after 24 h ***** IC50/EC50 measurable after 24 h

physiological stress affecting both photosynthetic activity and silicon metabolism in response to toxicant exposure. Since cellular energy for silification and transport does not depend directly on photosynthetic energy (Martin-Je´ze´quel et al. 2000), it may be assumed that the two physiological effects are independently induced. That alteration of chlorophyll metabolism and inhibition of auto-fluorescence are induced by toxicant exposure is supported by biochemical analyses performed to evaluate photosynthetic efficiency (Pouneva 1997; Nancharaiah et al. 2007). Our results indicate early alteration of both Chl-a and Phe ratios in exposed cells. Specifically, these descriptors are notably sensitive for the evaluation of sub-lethal responses in ecotoxicological tests performed with this species. At the same time, fluorescence due to new frustule formation was found to decrease in cells exposed to Zn and Cu. Cell wall silification and silicic acid transport are closely linked to the cell cycle, which means that silification is dependent on growth-rate (Martin-Je´ze´quel et al. 2000). Indeed, the results obtained in this study by confocal microscopy are consistent with growth-rate inhibition. Lower cell density values correspond to lower fluorescence signals for frustules, particularly in cells exposed to Zn and Cu. Copper can interfere with silicate metabolism in diatoms, increasing the per-cell quota of silicon necessary for cell division and/or inhibiting silicon uptake, with the result that metal-treated cells are swollen in comparison to untreated ones (Morel et al. 1978). Nevertheless, the relationship between heavy metals and silicic acid uptake is not yet fully understood and in this study cells exposed to Cu had a less clearly defined shape. In contrast, the detected fluorescence was found to increase with cell density. For cells exposed to MBAS, silicon metabolism seems to suffer no ecotoxicological effects. It may be hypothesized that since Si uptake is carrier-mediated (Paasche 1973; Azam et al. 1974), and since this transport may involve a sodium–silicic acid symporter in marine diatoms

(Bhattacharyya and Volcani 1980; Hildebrand et al. 1997; Falasco et al. 2009), dodecylbenzenesulfonic acid sodium salt (C18H29NaO3S) might actually foster this mechanism, promoting cell growth and thus new frustule formation. In addition, different kinds of environmental stress, from chemical–physical to toxicological, modify the frustule morphology of diatom cells, and consequently their relative size, in different ways (Falasco et al. 2009). P. tricornutum is pleomorphic, and it has been postulated that cell shape changes may represent a response to changes in environmental conditions (Wilson 1946; Borowitzka and Volcani 1978; De Martino et al. 2007) that can also be triggered by culture conditions (De Martino et al. 2011). The qualitative findings on cell morphology and cell fluorescence obtained in this study using confocal microscopy are encouraging and call for further experiments to develop a quick and easy strategy to quantify the observed reduction in fluorescence. Assessing fluorescence in statistically significant single-cell replicates could allow reproducible evaluations in terms of significant differences between single-cell fluorescence and fluorescence in controls. These techniques have been widely applied in biomedical research but their potential in ecotoxicological studies has yet to be fully explored (Halbuber and Konig 2003). The results obtained in this study show that the development of a methodological approach based on the use of confocal microscopy analysis to quantify fluorescence reduction could represent a useful tool for ecotoxicological applications and research.

Conclusions This study showed that alteration of the photosynthetic complex and changes in biovolume are powerful tools for evaluating both early and sub-lethal effects of toxicant exposure. Indeed, toxic effects are detected earlier and at

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lower exposure doses using the proposed physiological and morphological endpoints than using traditional approaches. The use of physiological and morphological endpoints for ecotoxicity assessment with P. tricornutum reported here represents an improvement with respect to the traditional growth-rate inhibition test. Specifically, their use makes it possible to: (i) evaluate early and sub-lethal effects; (ii) highlight effects occurring at the single-cell level as well as at the population level; and (iii) assess the effect of toxicants on cell size (biovolume) with the help of an image analysis system. Further research is needed: to test the applicability of this technique to complex matrices as well as natural samples with mixtures of toxicants at sub-lethal doses, also taking account of nutrient availability; to quantify the toxicological effects on cell structure and autofluorescence using confocal microscopy; and to identify ultrastructural impairments or damaged sites (cell wall, protoplasm, chloroplasts, growth). Acknowledgments This research was developed within the Project Sensor Network Infrastructure for Factors (SNIFF)—PON01_02422 and within the Project POR PUGLIA, Progetto Strategico 2009–2012 and BIOforIU—PONa3_00025. Authors are grateful to Dr. George Metcalf for the English language revision. The authors thank the staff of the Laboratory of General Physiology of the University of the Salento for their availability during confocal microscopy analysis. Conflict of interest of interest.

The authors declare that they have no conflict

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