Gene regulation in the marine diatom Thalassiosira pseudonana upon exposure to polycyclic aromatic hydrocarbons (PAHs)

Gene 396 (2007) 293 – 302 www.elsevier.com/locate/gene

Gene regulation in the marine diatom Thalassiosira pseudonana upon exposure to polycyclic aromatic hydrocarbons (PAHs) Stephanie K. Bopp, Teresa Lettieri ⁎ European Commission — DG Joint Research Centre, Institute for Environment and Sustainability, Rural, Water, and Ecosystem Resources Unit, T.P. 300, Via E. Fermi 1, 21020 Ispra (VA), Italy Received 4 December 2006; received in revised form 23 March 2007; accepted 23 March 2007 Available online 30 March 2007

Abstract Diatoms are eukaryotic algae, which can be found worldwide in oceans and freshwaters. These organisms are ecologically relevant due to their key role in the global carbon cycle, contributing to about 25% to the global primary production [Falciatore, A., Bowler, C., 2002. Revealing the molecular secrets of marine diatoms. Annu. Rev. Plant Biol. 53, 109–130]. We investigated the effects of three polycyclic aromatic hydrocarbons (PAHs, pyrene, fluoranthene, and benzo[a]pyrene), either as single compound or as mixture, at molecular level. Dose–response curves for growth inhibition were determined and four concentrations eliciting from “no effect” up to a severe growth inhibition were chosen for further investigation to detect alterations at gene expression level by Real-Time PCR. Among the eight selected genes, two were strongly influenced by the PAH treatment. lacsA, which is involved in the fatty acid metabolism, was found to be strongly up-regulated by all single PAHs, as well as by the mixture. sil3, involved in the formation of the silica shell, was repressed by a factor up to three even at low PAH concentrations not eliciting any growth inhibition. For other genes, involved e.g. in photosynthesis, a slight down-regulation was detected. Based on the effects at gene expression level it can be assumed that PAHs impair the fatty acid metabolism and silica shell formation. © 2007 Elsevier B.V. All rights reserved. Keywords: Ecotoxicology; Real-Time PCR; Gene expression; Cytotoxicity

1. Introduction Diatoms are eukaryotic algae, which can be found worldwide in oceans and freshwater. They play an important role in the global carbon cycle as they are thought to contribute at about 25% to the global primary production (Falciatore and Bowler, 2002). Thus, it is important to include diatoms in water quality investigations. The marine diatom Thalassiosira pseudonana was the first diatom species whose genome was completely sequenced Abbreviations: 3HfcpA and B, fucoxanthin-chlorophyll a/c light harvesting protein; BaP, benzo[a]pyrene; cDNA, DNA complementary to mRNA; desB, sphingolipid delta-8 saturase; Flu, fluoranthene; gapdh, glyceraldehyde 3phosphatase dehydrogenase; GTP, guanosine triphosphate; lacsA, long chain acyl-coA synthetase; PAH, polycyclic aromatic hydrocarbon; PCB, polychlorinated biphenyl; Pyr, pyrene; rbj, RBJ like protein; rcf, relative centrifugal force; PCR, polymerase chain reaction; sil1, 2, 3–; silaffin precursor 1, 2, 3. ⁎ Corresponding author. Tel.: +39 332 789868; fax: +39 332 789352. E-mail address: [email protected] (T. Lettieri). 0378-1119/$ - see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.gene.2007.03.013

(Armbrust et al., 2004), facilitating its use in the field of molecular ecotoxicology. The investigation of gene expression due to exposure to chemical stressors enables the detection of biological pathways affected by a certain compound in non-target organisms. In the current study, we investigated effects of polycyclic aromatic hydrocarbons (PAHs) on T. pseudonana at molecular level. Three PAHs (pyrene, fluoranthene, and benzo[a]pyrene) were chosen as model substances due to their wide presence as environmental contaminants. Diatoms were firstly exposed to the three PAHs as single compounds and secondly to a mixture of all three. Dose–response curves for growth inhibition were determined and four concentrations eliciting from “no effect” up to a severe growth inhibition were chosen for further investigation to detect alterations at gene expression level. Gene expression from exposed diatoms was investigated by Real-Time Polymerase Chain Reaction (Real-Time PCR). The selection of suitable genes (see Table 1) was based on an extensive literature study of the effects of PAHs described in various organisms (Harvey, 1991; Shaw et al., 2004) and mammalian systems (Park et al., 2006).

ATGGGAGCAGCGGTAATGG ATGGGAGCAGCGGTAATGG GCTGCGTCCTCCGACTTTC AGTCCGCGCCGACATG CCGTCACCCTCTCCTGAAAC CCGTCACCCTCTCCTGAAAC GGTGCAAAGAGTGCCAAGATG CTGGCAACAATTTGCATTCG NCBI AY706749 NCBI AY706750 NCBI AY706751 NCBI AY817154 Silaffin precursor 1 Silaffin precursor 2 Silaffin precursor 3 Sphingolipid delta-8 desaturase

sil1 sil2 sil3 desB

CGAACCTGTTTTTCTCGCAGTA TCGTGCATTGTCAAAAA CGGCAATACAAAGGTCGGTAA NCBI BK001289 rbj

AACGAGCCAAGTGC AACGAGCCAAGTGC CATGGACACCAAGAGT CGGACATGACTGTGGTC

Ras-related GTP binding protein, involved in the development and maintenance of nervous system and/ or reproductive apparatus Silica shell formation Silica shell formation Silica shell formation Fatty acid metabolism, signal transduction and cell recognition

TTGGCCTCGCACAATCG GGCATGTCGTGTGTGGTTTG NCBI AY730618 lacsA

Photosynthesis TCCAAGCGTGCCATT AGTTCGATGAGGAGACCAAGCT GGCACGTCCGTTGTTCAAC NCBI U66184 3HfcpB

Photosynthesis AGCCCTCCAGATCC AGCGAGCTCAAGGAATCCAA 3HfcpA

TGAAGGGAGGTGCCAAG Glycolysis TGGAGCCGAGATGACAACCT gapdh

Glyceraldehyde-3phosphate dehydrogenase Fucoxanthin-chlorophyll a/c light harvesting protein Fucoxanthin-chlorophyll a/c light harvesting protein Long chain acyl-coA synthetase RBJ like protein

JGI GGAGAAGGCCTCCATGCAT GENEWISE.123.33.1 NCBI U66183 CTCCCTCCAGGTTCCTGTTG

TaqMan probe Reverse primer Forward primer Abbreviation Source Name of gene

Table 1 Details on genes, analyzed by Real-Time PCR

TCGAGGAAGGAGTTGGA Fatty acid metabolism

S.K. Bopp, T. Lettieri / Gene 396 (2007) 293–302

Cellular processes involved

294

The list includes genes encoding for proteins involved in important cellular processes, e.g. in silica shell formation (Poulsen and Kroeger, 2004; Frigeri et al., 2006) and photosynthesis, since it has been shown that PAH stress responses affect the cell cycle progression and consequently the cellular processes (Pei et al., 1999). Further, we include also genes involved in lipid synthesis (Tonon et al., 2005a,b) since PAHs, being hydrophobic molecules, have the capacity to accumulate in lipid fractions and therefore, to interfere with their metabolism (Lotufo, 1998; Baussant et al., 2001; Verdin et al., 2006). 2. Materials and methods 2.1. Reagents Three different polycyclic aromatic hydrocarbons (PAHs) were used for exposure to single compounds and a mixture of the three. The chosen PAHs were pyrene (Pyr, purity N 99%, Fluka, Buchs, Switzerland), fluoranthene (Flu, purity N 99%, Aldrich, Buchs, Switzerland) and benzo[a]pyrene (BaP, purity N 97%, Fluka). PAHs were dissolved in methanol (purity ≥ 99.9%, Carlo Erba, Rodano (MI), Italy) for testing. 2.2. Diatom strain and routine culture T. pseudonana (strain CCMP 1335) was obtained as axenic culture from the Provasoli-Guillard National Center for Culture of Marine Phytoplankton (CCMP, West Boothbay Harbour, Maine, USA). Diatoms were maintained at 6–8 °C under a diurnal light cycle of 13 h light and 11 h darkness. The culture medium was f/2-medium (Guillard, 1975) based on 3.2% artificial sea water (ASW, Sigma-Aldrich, Steinheim, Germany). T. pseudonana was cultured in 250 mL Erlenmeyer flasks at densities between 0.5 × 106 and 5 × 106 cells/mL. Doubling times under these conditions were ca. 24 h. Fresh cultures for maintenance were inoculated every 7 days. 2.3. Exposure of T. pseudonana to PAHs Effects of three PAHs (Pyr, Flu, BaP) on T. pseudonana were tested as single compounds and as a mixture of the three. Growth inhibition was investigated in 20 mL batch cultures which were inoculated from seven day old cultures to a start cell density of 5× 105 cells/mL. After a pre-incubation period of 24 h, to avoid lagphases during exposure, cell density at the start of the exposure was measured as described below. PAHs were dissolved in methanol and added to the culture leading to a methanol concentration of 0.05% in the culture medium. Methanol was investigated before to have no effect on the diatom growth up to the highest tested concentration of 0.5%. Dosing of methanol (solvent control) and PAH solutions was performed 30 min before the light cycle started. Single PAHs were investigated at a concentration range of 2.5– 500 μg/L for Pyr, 3–3000 μg/L for Flu, and 0.05–328 μg/L for BaP. The mixture of the three PAHs contained at the highest concentration termed “1 × EC50,i” each single compound at its single EC50,i value. A three-fold dilution series of this solution

S.K. Bopp, T. Lettieri / Gene 396 (2007) 293–302

down to 2187-fold dilution was tested. After 24 h of exposure, cell densities were measured in order to determine growth inhibition with respect to the untreated control cultures using the growth rates. Then, diatom cultures were centrifuged at 1500 rcf for 10 min. The supernatant was removed and the cell pellet resuspended in 0.5 mL PBS buffer (Gibco, Invitrogen, Paisley, UK). The suspension was transferred to 1.5 mL tubes and centrifuged at 10,000 rcf for 10 min. Then, supernatants were removed and the remaining cell pellets were frozen at − 80 °C. 2.4. Detection of growth inhibition

295

at 95 °C, followed by 40 cycles with 15 s at 95 °C and 1 min at 60 °C. Gene expression data from Real-Time PCR were evaluated using Q-Gene (Muller et al., 2002), which takes into account the amplification efficiencies of target and reference genes. For all Real-Time PCR results, gapdh was used as housekeeping gene. gapdh threshold cycles for amplification in Real-Time PCR did not change significantly from each other for none of the different treatments (one way ANOVA). The calibrator sample was the control sample containing only the carrier solvent methanol (termed 0). For each exposure condition, the control plus four PAH treated samples were investigated. Samples were covering a range from “no effect” on growth up to a severe growth inhibition (≥40%).

Cell density was determined at the end of the exposure period transferring each 200 μL of diatom suspension to 96 well plates (Falcon, BD Biosciences, Erembodegem, Belgium) and measuring the absorption at 450 nm using a microplate spectrophotometer (Biorad, Hercules, CA, USA). (Correlation between absorption and cell density was investigated previously, R2 = 0.9997.) Growth rates were calculated from cell densities and used to determine growth inhibition compared to the control. Growth inhibition curves were fitted using a nonlinear regression sigmoidal dose–response curve model provided in the GraphPad Prism software.

3. Results

2.5. Total RNA isolation

3.1. Growth inhibition by PAHs

RNA extraction was performed using the Trizol LS (Invitrogen) method according to the manufacturer's protocol. In order to improve the yield and quality of the extracted RNA, time for cell lysis in Trizol LS was extended to 15 min, the first centrifugation step was extended to 20 min, and all centrifugation steps were performed at 16,000 rpm.

In order to analyze complete dose–response curves, a wide range of concentrations was tested for all compounds. Significant growth inhibition was found at rather high concentrations, with EC50 values determined at 1031 μg/L (5.1 μM) for Flu, 260.3 μg/ L (1.29 μM) for Pyr, and 55.24 μg/L (0.22 μM) for BaP (Fig. 1). For the mixture (Fig. 1D), the concentration scale on the Xaxis indicates the three-fold dilution series prepared from the highest tested concentration, i.e. the value 1 (1 × EC50,i) which corresponds to the mixture containing each of the three PAHs at their single EC50,i value. The EC50,mix value determined as a dilution factor of the EC50,i scale was 0.3497 × EC50,i, i.e. each single compound was present at ≈1/3 of its single EC50,i at the EC50,mix. Furthermore, growth inhibitory effects elicited by the mixture were predicted using the “concentration addition” method as described in Altenburger et al. (2004). Using this method, a very close agreement between measured values and those predicted by the “concentration addition” method was observed: single compound concentrations in the mixture at the EC50,mix were predicted to be 344, 87, and 18 μg/L for Flu, Pyr, and BaP respectively. Experimentally determined corresponding concentrations were 361, 91, and 19, respectively.

2.6. Reverse transcription Each 2 μg of RNA was treated according to the manufacturer's protocol with DNAse (DNase I, 1000 U/μL, Roche Diagnostics, Basel, Switzerland). The whole sample of DNase treated RNAwas then transcribed to cDNA using oligodT primers and SuperScript II Reverse Transcriptase Kit as recommended (Invitrogen). 2.7. Probe design and Real-Time PCR For Real-Time PCR, primers and MGB TaqMan probes, labeled at the 5′-end with the fluorescent dye FAM (6-carboxyfluorescein), were designed using Primer Express® Software and synthesized by Applied Biosystems (Foster City, CA, USA). All sequences for primers and probes can be found in Table 1. Amplification reactions were performed with 12.5 μL of double concentrated Master Mix (Applied Biosystems), 0.9 mM each primer, 0.1 mM probe, and 2.5 μL of 1:15 diluted cDNA in a final volume of 25 μL. Samples were loaded in triplicate on 96-well optical reaction plates and PCR was performed in the ABI Prism 7900HT sequence detection system (Applied Biosystem). The manufacturer's recommended universal thermal cycler protocol was used: 2 min preheating at 50 °C, 10 min

2.8. Statistical analysis Growth inhibition data as well as Real-Time PCR results were statistically evaluated using GraphPad Prism (GraphPad software, Inc., San Diego, USA). A one way ANOVA analysis was performed with Dunnett's test as post-test to compare each treatment to the solvent control sample. Data were considered as statistically different when the p-value was below 0.05.

3.2. Gene expression analysis by Real-Time PCR Growth inhibition was determined for a wide range of concentrations, leading from no effect to close to 100% growth inhibition. T. pseudonana samples from the same experiments were further investigated to detect alterations at gene expression level. For each exposure, four samples from “no effect” up

296

S.K. Bopp, T. Lettieri / Gene 396 (2007) 293–302

to a severe growth inhibition plus the solvent control were investigated by Real-Time PCR. 3.2.1. Long chain acyl-coA synthetase (lacsA) The gene lacsA, which is involved in the fatty acid biosynthesis, was up-regulated in all four exposure scenarios, i.e. in T. pseudonana exposed either to the three selected single PAHs or a mixture of the three (Fig. 2). A consistent up-regulation in all three replicates for each exposure scenario was found only for the highest exposure concentrations tested, which were lying closely below or above the EC50 values detected for growth inhibitory effects. Clear up-regulation tendencies with increasing PAH concentrations can be observed for nearly all single experiments (see Fig. S1, supplementary information), whereas the variability between experimental replicates was mostly too high to detect significant induction in the average of them. 3.2.2. Silaffin precursors (sil1, sil2, sil3) Silaffin precursor genes encode for biosilica-associated proteins involved in the formation of the diatom's silica shell. sil3 showed the most distinct pattern among the three. Gene expression of sil3 was relatively variable depending on the

tested PAH exposure concentrations, but a strong downregulation was evident especially in the samples exposed to the PAH mixture and to Pyr (Fig. 3). For the exposure to the PAH mixture, we observed a significant down-regulation in all tested concentrations in all experiments and also in the average. Interestingly, the two- to three-fold down-regulation occurred already at concentrations eliciting no growth inhibitory effect (1/2187 × EC50,i) or only slight growth inhibition below 10% (1/ 242 and 1/27 × EC50,i). Similar results were confirmed for Pyr exposure, but were not clearly observable in Flu and BaP exposures (see also Fig. S2, supplementary information). In contrast to the results for sil3, gene expressions of sil1 and sil2 showed a slight tendency for up-regulation (Figs. 4 and 5), which were not confirmed in all exposures and replicates (data not shown). Results for sil1 and sil2 were similar. 3.2.3. Other investigated genes Fucoxanthin-chlorophyll a/c light harvesting proteins (3HfcpA and 3HfcpB), which are involved in photosynthetic processes of T. pseudonana, showed both a nearly identical down-regulation trend (Figs. 6 and 7). Observed patterns were similar to those observed for sil3, but the average of the three experiments was statistically

Fig. 1. Dose–response curves for growth inhibition in T. pseudonana exposed for 24 h to either single PAHs (A) fluoranthene, (B) pyrene, (C) benzo[a]pyrene or (D) a mixture of all three compounds. The mixture contained the three PAHs at a ratio according to there single EC50,i value, i.e. at the highest tested concentration (1 × EC50,i) each single PAH was present at its single compound EC50,i. Lower mixture concentrations were prepared upon a three-fold dilution series of the 1 × EC50,i mixture and thus ranged from 1/3 down to 1/2187 fold dilution. Circles represent average measured values from four experiments; vertical lines indicate the standard error. The continuous line represents the fitted dose–response curve (using GraphPad Prism software) with dashed lines indicating the 95% confidence interval. Asterisks indicate significant growth inhibition with respect to the control (one way ANOVA, Dunnett's test, p b 0.05).

S.K. Bopp, T. Lettieri / Gene 396 (2007) 293–302

297

Fig. 2. Regulation of the lacsA gene in T. pseudonana due to exposure to single PAHs or a mixture of three PAHs. Bars represent the average calculated from three individual experiments with vertical lines representing the standard deviation of the mean. Asterisks indicate significant differences from the solvent control (zero) sample (one way ANOVA followed by Dunnett's test, p b 0.05).

significant only for the highest tested concentration of pyrene. For exposure to Pyr and the PAH mixture, down-regulation is confirmed over the whole investigated concentration range. For the exposure to Flu and BaP, the same uncertainties as for sil3 occurred due to the high variability between experimental replicates. Furthermore, two additional genes, sphingolipid delta8 desaturase (desB) (Tonon et al., 2005a) and RBJ like protein (rbj) (Nepomuceno-Silva et al., 2004), were investigated. No clear trend of regulation could be identified for neither of the two genes (see Figs. S3 and S4, supplementary information). Up-regulation occurred as well as down-regulation within the experimental triplicates for all exposures. This high variability made it impossible to identify any trend in gene expression elicited by the investigated PAHs. 4. Discussion 4.1. Growth inhibitory effects elicited by PAHs Growth inhibition was detected for all three singly tested PAHs as well as for the mixture only at rather high con-

centrations. Results for the mixture were in agreement with expected effects based on the concentration addition concept. As reported in the literature also for other algal species, BaP showed the highest toxicity in T. pseudonana among the three tested PAHs. Nevertheless, the growth inhibiting concentrations were relatively high, resulting in EC50 values even above the aqueous solubility of the compounds (factor of 2 for Pyr, 4 for Flu, and 15 for BaP). Environmental concentrations for the tested compounds were reported to lie in the range of pg/L to ng/L for unpolluted surface waters up to µg/L for polluted rivers (Maciel and Zaldivar, 2005). Comparing the effect concentrations of the current study to results described in the literature, other algal species appear to be more sensitive to PAHs than T. pseudonana. For example Scencedesmus vacuolatus was reported to have 5–14 times lower EC50 values for Pyr, 30 times for Flu, and 31–37 times for BaP (Altenburger et al., 2004; Djomo et al., 2004). Since the conditions applied in our tests are different from those used in the literature a final conclusion cannot be drawn. The observed lower sensitivity might be explained by the low culture temperature, which leads to a reduced uptake or

298

S.K. Bopp, T. Lettieri / Gene 396 (2007) 293–302

Fig. 3. Regulation of the sil3 gene in T. pseudonana due to exposure to single PAHs or a mixture of three PAHs. Bars represent the average calculated from three individual experiments with vertical lines representing the standard deviation of the mean. Asterisks indicate significant differences from the solvent control (zero) sample (one way ANOVA followed by Dunnett's test, p b 0.05).

Fig. 4. Regulation of the sil1 gene in T. pseudonana due to exposure to single PAHs or a mixture of three PAHs. Bars represent the average calculated from three individual experiments with vertical lines representing the standard deviation of the mean.

S.K. Bopp, T. Lettieri / Gene 396 (2007) 293–302

299

Fig. 5. Regulation of the sil2 gene in T. pseudonana due to exposure to single PAHs or a mixture of three PAHs. Bars represent the average calculated from three individual experiments with vertical lines representing the standard deviation of the mean.

Fig. 6. Regulation of the 3HfcpA gene in T. pseudonana due to exposure to single PAHs or a mixture of three PAHs. Bars represent the average calculated from three individual experiments with vertical lines representing the standard deviation of the mean. Asterisks indicate significant differences from the solvent control (zero) sample (one way ANOVA followed by Dunnett's test, p b 0.05).

300

S.K. Bopp, T. Lettieri / Gene 396 (2007) 293–302

Fig. 7. Regulation of the 3HfcpB gene in T. pseudonana due to exposure to single PAHs or a mixture of three PAHs. Bars represent the average calculated from the three individual experiments with vertical lines representing the standard deviation of the mean.

decelerated metabolism (Fan and Reinfelder, 2003). On the other hand, uptake into T. pseudonana is reported to be rather quick, due to its small size and therefore high surface area to volume ratio (Wang and Wang, 2006; Fan and Reinfelder, 2003). A major factor was probably also the ratio of light to dark periods during exposure. Indeed, many other studies used longer light periods, which could enhance the production of phototoxic compounds, thus leading to phototoxic effects especially for compounds like the investigated PAHs (Grote et al., 2005). Examples for diatoms used in ecotoxicological studies for assessment of effects caused by PAHs are very rare in the literature. Okay et al. (2002) used the diatom Phaeodactylum tricornutum to assess the (photo)toxicity of Pyr in an acute and a chronic test system. Pyr was found to be acutely toxic in this diatom. Using 14 C assimilation rate as an endpoint after 4 h of exposure, EC50 values of 68–70 mg/L were determined. In long-term experiments of 17 days, lagphases in growth were prolonged in diatoms treated with 40 and 80 mg/L of Pyr, but after 7 days growth rates between control and Pyr treated cultures were again similar. Therefore, it was concluded that Pyr has an effect only on actively growing cells. Furthermore, it was pointed out in the literature that the strain T. pseudonana CCMP 1335 (also called 3H) was isolated from an estuarine region, with higher fluctuations in chemical conditions, and showed a much lower sensitivity to e.g. a liquid waste containing organic pollutants (Murphy and Belastock, 1980) or PCBs (Fisher et al., 1973; Fisher, 1977) than other strains of the same species isolated from oceanic regions.

4.2. Gene expression analysis Eight target genes were selected for investigation of effects on gene expression induced by PAHs. Two genes are involved in the fatty acid metabolism (lacsA and desB), other two are included in photosynthesis pathways (3HfcpA and 3HfcpB). Furthermore, silaffin protein precursor genes (sil1, sil2, sil3) were investigated as they play an important role in the formation of the silica shell. Additionally, effects on a ras-related GTP binding protein encoding gene (rbj) were studied. Among the selected genes, sil3 and lacsA showed the most distinct effects. lacsA is involved in biosynthetic pathways of fatty acid derived molecules (Tonon et al., 2005b). It plays an important role in the accumulation of polyunsaturated fatty acids in triacylglycerols. PAHs, as strongly hydrophobic compounds, accumulate in lipids and are known to induce oxidative stress and lipid peroxidation (Kelly et al., 1998). Therefore it was one aim to look if PAHs could affect the lipid metabolism. We observed that lacsA was up-regulated in T. pseudonana by PAHs, although stronger induction was found mainly for higher exposure concentrations where also growth was significantly impaired. lacsA was described as constitutively expressed in untreated cultures over periods of up to 13 days (Tonon et al., 2005b). This underlines the induction due to exposure to PAHs. In the literature there is no information on the specific effects of PAHs on diatoms' lipid metabolism, but it was reported for one fungus, able to degrade PAHs, that the lipid content was decreasing upon exposure to BaP (Verdin et al., 2006). Staal et al. (2006) found a down-regulation of fatty

S.K. Bopp, T. Lettieri / Gene 396 (2007) 293–302

acid synthesis related genes in HepG2 cells after exposure to several higher molecular PAHs. According to our studies, it might be possible that some genes encoding proteins involved in lipid pathways were also down-regulated while lacsA was upregulated, either because it was involved in a feedback mechanism or it might show a regulatory activity. The other selected gene involved in lipid metabolism is the sphingolipid desaturase desB (Tonon et al., 2005a). For desB no coherent regulatory effects were detected. It remains unknown if T. pseudonana or diatoms in general are able to degrade PAHs, which often leads to more toxic metabolites and thus enhanced biological effects such as lipid peroxidation. The ability to metabolize PAHs is described for vertebrates, fungi and bacteria. For algae there is few information available (Juhasz and Naidu, 2000); the ability of S. capricornutum to degrade Pyr to a low extend was reported by Lei et al. (2002), as well as the ability of BaP degradation via a dioxygenase enzymatic pathway (Warshawsky et al., 1988), which is more characteristic for bacteria than for eukaryotic organisms, involving the monooxygenase system. The second clearly regulated gene was sil3. Silaffins cause, in combination with long chain polyamines in supramolecular assemblies, the deposition of silicic acid and thus initiate the formation of the silica shell (Poulsen and Kroeger, 2004). According to Frigeri et al. (2006), mRNA levels of sil1 and sil3 correspond to distinct stages in cell wall synthesis, i.e. sil1 levels are enhanced during girdle band formation and sil3 levels peak during valve formation. Thus, a down-regulation of sil3 by exposure to PAHs might inhibit the formation of valves and consequently lead to reduced cell division and growth rates. In the current study sil3 was clearly down-regulated by factors of 2 to 3.5, even at concentrations that did not affect the growth rate. Therefore, it might be an early marker of cell division impairment. sil1 and sil2 did not show a clear trend in gene expression after exposure to PAHs. Even if these two genes are not influenced by PAHs, the formation of the silica shell as a multi level process might be severely disturbed due to the downregulation of sil3. Furthermore, the form of silica precipitates can be modified, if the balance of the three silaffins is altered (Poulsen and Kroeger, 2004). Fucoxanthin-chlorophyll a/c light harvesting protein encoding genes (3HfcpA and 3HfcpB) showed both a nearly identical down-regulation trend, even if it was not as evident as for sil3, due to higher variability between experimental replicates. A down-regulation of 3HfcpA and 3HfcpB can be an indicator pointing at reduced photosynthetic activity. Inhibition of photosynthesis by PAHs, detected by pulse amplitude modulated chlorophyll-a fluorescence, was reported for phytoplankton and macrophytes (Marwood et al., 2003; Kummerová et al., 2006). In accordance with the down-regulation of 3HfcpA and 3HfcpB found in our study, Kummerová et al. (2006) identified furthermore a decrease in photosynthetic pigments. Thus, 3HfcpA and 3HfcpB might be useful markers for detecting influences on the photosynthetic activity. rbj, which belongs to a group of ras-related GTP binding proteins, involved in the development and maintenance of the nervous system and/or reproductive apparatus, did not show any

301

clear effect. Other genes involved in these pathways should be examined for further clarification. In general, a high variability in gene expression occurred between experimental replicates for most of the selected genes in this study. One possible reason might have been the culture conditions. Even if cultures used for experiments were always chosen from the same age and dosing was performed always at the same time with respect to the light cycle, these measures were probably insufficient to gain a homogeneous, synchronized culture. Thus, differences in gene expression might have been caused also due to cells staying in different stages of the cell cycle. Hildebrand and Dahlin (2000) report that diatom cultures can be synchronized to about 75% by the light cycle. A more effective method for synchronization is silica starvation as proposed by Darley and Volcani (1969) and Hildebrand and Dahlin (2000). However, silica starvation will surely affect the expression of e.g. the silaffin genes with respect to time (Frigeri et al., 2006) and thus will make the interpretation of perturbations caused by chemicals more difficult. In future studies, synchronization status of the cultures should be taken more in detail into account and monitored in parallel to gene expression analysis. 5. Concluding remarks The full sequencing of the diatom T. pseudonana (Armbrust et al., 2004) added a remarkable contribution to the ecotoxicology field. We used T. pseudonana to investigate effects of PAHs at gene expression level in order to identify genes which are involved in the response and which then can potentially serve as sensitive biomarkers. Based on eight candidate genes, our studies showed that lacsA and sil3 are regulated by PAH exposure, giving some hints about PAH response. In the future, the challenge will be to investigate the mechanistic effects of PAH action. For this purpose, we will use DNA microarray technology (Lettieri, 2006) to analyze the global gene expression profile upon exposure to PAHs. Particularly we will look at environmentally relevant concentrations of contaminants in order to identify sensitive and specific molecular biomarkers. Furthermore, we took into account combination effects and will continue including this aspect in the future. Indeed, aquatic organisms are exposed to environmental contaminants always as mixtures, and not only to chemical mixtures but also to combinations of other environmental pressures, such as light, temperature, and changes in nutrient supply. Acknowledgements We are grateful to Joaquin Pinto Grande for technical assistance and Una Cullinan for proofreading of the manuscript. This work was financially supported in part by the EU Integrated Project Thresholds of Environmental Sustainability. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.gene.2007.03.013.

302

S.K. Bopp, T. Lettieri / Gene 396 (2007) 293–302

References Altenburger, A., Walter, H., Grote, M., 2004. What contributes to the combined effect of a complex mixture? Environ. Sci. Technol. 38, 6353–6362. Armbrust, E.V., et al., 2004. The genome of the diatom Thalassiosira pseudonana: ecology, evolution, and metabolism. Science 306, 79–86. Baussant, T., Sanni, S., Jonsson, G., Skadsheim, A., Borseth, F., 2001. Bioaccumulation of polycyclic aromatic compounds: 1. Bioconcentration in two marine species and in semipermeable membrane devices during chronic exposure to dispersed crude oil. Environ. Toxicol. 20, 1175–1184. Darley, W.M., Volcani, B.E., 1969. Role of silicon in diatom metabolism. Exp. Cell. Res. 58, 334–342. Djomo, D.E., et al., 2004. Toxic effects of some major polyaromatic hydrocarbons found in crude oil and aquatic sediments on Scenedesmus subspicatus. Water Res. 38, 1817–1821. Falciatore, A., Bowler, C., 2002. Revealing the molecular secrets of marine diatoms. Annu. Rev. Plant Biol. 53, 109–130. Fan, C.-W., Reinfelder, J.R., 2003. Phenanthrene accumulation kinetics in marine diatoms. Environ. Sci. Technol. 37, 3405–3412. Fisher, N.S., 1977. On the differential sensitivity of estuarine and open-ocean diatoms to exotic chemical stress. Am. Nat. 111, 871–895. Fisher, N.S., Graham, L.B., Carpenter, E.J., 1973. Geographic differences in phytoplankton sensitivity to PCBs. Nature 241, 548–549. Frigeri, L.G., Radabaugh, T.R., Haynes, P.A., Hildebrand, M., 2006. Identification of proteins from a cell wall fraction of the diatom Thalassiosira pseudonana: insights into silica structure formation. Mol. Cell Proteomics. 5, 182–193. Grote, M., Schüürmann, G., Altenburger, R., 2005. Modelling photoinduced algal toxicity of polycyclic aromatic hydrocarbons. Environ. Sci. Technol. 39, 4141–4149. Guillard, R.R.L., 1975. Culture of phytoplankton for feeding marine invertebrates. In: Smith, W.L., Chanley, M.H. (Eds.), Culture of Marine Invertebrate Animals. Plenum Press, New York, pp. 29–60. Harvey, R.G., 1991. Polycyclic Aromatic Hydrocarbons: Chemistry and Carcinogenicity. Cambridge University Press, Cambridge, United Kingdom. Hildebrand, M., Dahlin, K., 2000. Nitrate transporter genes from the diatom Cylindrotheca fusiformis (bacillariophytcea): mRNA levels controlled by nitrogen source and by the cell cycle. J. Phycol. 36, 702–713. Juhasz, A.L., Naidu, R., 2000. Bioremediation of high molecular weight polycyclic aromatic hydrocarbons: a review of the microbial degradation of benzo[a]pyrene. Int. Biodeter. Biodegrad. 45, 57–88. Kelly, S.A., Havrilla, C.M., Brady, T.C., Abramo, K.H., Levin, E.D., 1998. Oxidative stress in toxicology: established mammalian and emerging piscine model systems. Environ. Health Perspect. 106, 375–384. Kummerová, M., Krulová, J., Zezulka, S., Tříska, J., 2006. Evaluation of fluoranthene phytotoxicity in pea plants by Hill reaction and chlorophyll fluorescence. Chemosphere 65, 489–496. Lei, A.P., Wong, Y.S., Tam, N.F.Y., 2002. Removal of pyrene by different microalgal species. Water Sci. Technol. 46, 195–201. Lettieri, T., 2006. Recent applications of DNA microarray technology to toxicology and ecotoxicology. Environ. Health Perspect. 114, 4–9. Lotufo, G.R., 1998. Bioaccumulation of sediment-associated fluoranthene in benthic copepods: uptake, elimination and biotransformation. Aquat. Toxicol. 44, 1–15.

Maciel, H., Zaldivar, J.M., 2005. An overview of chemical mixtures assessment and modeling in the aquatic environment. Report EUR 21859 EN. Marwood, C.A., Smith, R.E.H., Charlton, M.N., Solomon, K.R., Greenberg, B.M., 2003. Photoinduced toxicity to Lake Erie phytoplankton assemblages from intact and photomodified polycyclic aromatic hydrocarbons. J. Great Lakes Res. 29, 558–565. Muller, P.Y., Janovjak, H., Miserez, A.R., Dobbie, Z., 2002. Processing of gene expression data generated by Quantitative Real-Time RT-PCR. BioTechniques 32, 2–7. Murphy, L.S., Belastock, R.A., 1980. The effect of environmental origin on the response of marine diatoms to chemical stress. Limnol. Oceanogr. 25, 160–165. Nepomuceno-Silva, J.L., de Melo, L.D.B., Mendonc, S.M., Paixão, J.C., Lopes, U.G., 2004. RJLs: a new family of Ras-related GTP-binding proteins. Gene 327, 221–232. Okay, O.S., Tuefekci, V., Donkin, P., 2002. Acute and chronic toxicity of pyrene to the unicellular marine alga Phaeodactylum tricornutum. Bull. Environ. Contam. Toxicol. 68, 600–605. Park, S.-Y., et al., 2006. Benzo[a]pyrene-induced DNA damage and p53 modulation in human hepatoma HepG2 cells for the identification of potential biomarkers for PAH monitoring and risk assessment. Toxicol. Lett. 167, 27–33. Pei, X.-H., Nakanishi, Y., Takayama, K., Bai, F., Hara, N., 1999. Benzo[a] pyrene activates the human p53 gene through induction of nuclear factor κB activity. J. Biol. Chem. 274, 35240–35246. Poulsen, N., Kroeger, N., 2004. Silica morphogenesis by alternative processing of silaffins in the diatom Thalassiosira pseudonana. J. Biol. Chem. 279, 42993–42999. Shaw, J.P., et al., 2004. Seasonal variation in cytochrome P450 immunopositive protein levels, lipid peroxidation and genetic toxicity in digestive gland of the mussel Mytilus edulis. Aquat. Toxicol. 67, 325–336. Staal, Y.C.M., van Herwijnen, M.H.M., van Schooten, F.J., van Delft, J.H.M., 2006. Modulation of gene expression and DNA adduct formation in HepG2 cells by polycyclic aromatic hydrocarbons with different carcinogenic potencies. Carcinogenesis 27, 646–655. Tonon, T., et al., 2005a. Fatty acid desaturases from the microalga Thalassiosira pseudonana. FEBS J. 272, 3401–3412. Tonon, T., Quing, R., Harvey, D., Li, Y., Larson, T.R., Graham, I.A., 2005b. Identification of a long-chain polyunsaturated fatty acid acyl-coenzyme A synthetase from the diatom Thalassiosira pseudonana. Plant Physiol. 138, 402–408. Verdin, A., Lounès-Hadj Sahraoui, A., Laruelle, F., Grandmougin-Ferjani, A., Durand, R., 2006. Effect of the high polycyclic aromatic hydrocarbon, benzo [a]pyrene, on the lipid content of Fusarium solani. Mycol. Res. 110, 479–484. Warshawsky, D., Radike, M., Jayasimhulu, K., Cody, T., 1988. Metabolism of benzo[a]pyrene by a dioxygenase enzyme system of the freshwater green alga Selenastrum capricornutum. Biochem. Biophys. Res. Commun. 152, 540–544. Wang, X., Wang, W.-X., 2006. Bioaccumulation and transfer of benzo[a]pyrene in a simplified marine food chain. Mar. Ecol. Prog. Ser. 312, 101–111.