The chemical parameters pH and conductivity remained stable throughout the exposure, ranging between 7.8–7.9 and 422–452 μS cm^-1, respectively. Water temperatures ranged from 20.8 to 21.0°C. Ibuprofen-sodium increased measured pH by approximately 9% and conductivity by approximately 7% in the highest treatment (80 mg IB l^-1) compared with the control (data not shown).

Quantification of IB revealed that nominal concentrations were within ± 10% of the measured concentration; except for 20 mg IB l^-1 replicate three that was 10.6% lower than the nominal (data not shown). No mortality was observed in D. magna in any of the treatments following exposure.

Relative gene expression was estimated using DART-PCR (see Methods). There was a significant (p < 0.05) down-regulation of Atb and Cyp at 80 mg IB l^-1 compared with the control (Table 2). The eight candidate reference genes unaffected by the IB treatment were analysed by geNorm (see Methods) ranking the least variable genes as; UBC = GAPDH <Act <WARS <SDH <TBP <18S <28S (Table 2). Subsequently, geNorm was applied to estimate seven normalisation factors,NF₂ to NF₈, based on the geometric mean of the relative expression of the included reference genes. The geNorm algorithm allocates the two least variable genes, here GAPDH and UBC, to NF₂. Then the sequential NF₃ was based on the genes from NF₂ and the third least variable gene Act, and so on.

Pairwise comparisons of sequential normalisation factors computed by geNorm revealed a similar level of variability between NF₂ vs. NF₃, NF₃ vs. NF₄, NF₄ vs. NF₅ and NF₅ vs. NF₆ (Fig. 1). This suggests that the use of either of these NFs as internal control would be valid. But pairwise comparisons of NF₆ vs. NF₇ and NF₇ vs. NF₈, (28S (NF₇) and 18S (NF₈)), more than doubled the variability (Fig. 1). Vandesompele et al., 2002 10 recommend using as few reference genes as feasible, but a minimum of three. Thus, although it gave a similar variability to other combinations, we chose NF₃, (GAPDH, UBC and Act) since it gave an optimal NF with a low level of variation using the lowest possible number of reference genes.

There is a circular problem with normalising a target gene with reference genes that should be normalised themselves prior to target gene normalisation 9. Thus, in addition to normalising the target gene, we also normalised all 10 reference genes by NF₃. Atb had the same significant (p < 0.05) differences as prior to normalisation, and should therefore be regarded as a target gene. None of the other reference genes, including Cyp, were significantly (p > 0.05) affected by IB following normalisation (data not shown).

Without normalisation, the target gene Ltb4dh was significantly (p < 0.05) up-regulated at 80 mg IB l^-1 compared with any of the other treatment groups having a 3.24-fold higher expression than the control (Fig. 2). The relative expression of Ltb4dh followed a significant (p < 0.05) dose-dependent relationship (data not shown). Normalisation with NF₃ produced a similar expression (Fig. 2). The relative expression of Ltb4dh was normalised individually by each of the 10 candidate reference genes and by NF₃ to assess how their variability influenced target gene expression. Overall, the mean fold difference in relative expression between 80 mg IB l^-1 and the control was 3.34 ± 0.85 SD ranging from 1.66 (18S) to 5.15 (Atb) (Fig. 3). Target gene expression normalised to any of the reference genes was compared to normalisation with NF₃ revealing that there was a significant (p < 0.05) difference within the 80 mg IB l^-1 treatment between normalisation of Ltb4dh to Atb and Cyp respectively, and Ltb4dh normalised to NF₃ (Fig. 3). Although not significant (p > 0.05), normalisation of Ltb4dh to either 18S or 28S caused a large increase in the variation of target gene expression in any of the IB treatments (Fig. 3). Both rRNA genes reduced significant differences observed in Ltb4dh, with or without normalisation to NF₃ (data not shown).

Daphnia magna Straus (Clone Type 5 – IRCHA), originally obtained from the Water Research Centre (WRc), Medmenham, UK, were investigated. For further information on culturing conditions of D. magna please see Hooper et al., 2006 24.

The experimental design consisted of three replicates of a control and three treatments with ibuprofen-sodium (Sigma-Aldrich, CAS no. 31121-93-4) containing 20, 40 and 80 mg IB l^-1, respectively. Each replicate consisted of 100 third brood neonates (< 24 h old) placed in a 1000 ml glass beaker containing one litre of reconstituted freshwater with or without the addition of IB. Neonates were exposed to IB for 24 h under the same conditions as stock cultures (see Hooper et al., 2006 24), but without feeding. To quantify IB, 1.5 ml was sampled from each replicate at 0 h and 24 h and stored at -20°C. Subsequently, the free base concentration of IB was measured at 217 nm by UV-spectrophotometry using an Ultrospec3000 (Biochrom) after the method of Pascoe et al., 2003 25. Conductivity, pH and water temperature were checked at the beginning and at the end of the exposure to verify stable water chemistry.

Following exposure, the neonates were immediately placed in 0.2 ml of RNAlater^® (Ambion) and stored at -80°C. Subsequently, total RNA was extracted using the RNeasy Mini kit with on-column DNase treatment (Qiagen) to remove any traces of genomic DNA following the manufacturer's instructions. RNA concentrations were determined by spectrophotometry using GeneQuant Pro (Biochrom). The integrity of the RNA was verified by 1% agarose gel electrophoresis. Four micrograms of DNase-treated total RNA was reverse transcribed with Oligo(dT)_12–18 primers (Invitrogen) using the Omniscript Reverse Transcriptase kit (Qiagen) following the manufacturer's instructions. Once synthesised, cDNA was diluted 10-fold resulting in total RNA concentrations of 10 ng/μl and stored at -20°C.

Ten expressed sequence tags (ESTs) were obtained from the NCBI website 26 and the Daphnia Genomics Consortium website 27 (see Colbourne et al., 2005 28). ESTs were verified by BLASTN and BLASTX analysis 26. Primers were designed using Primer3 29, and synthesised by MWG. The investigated ESTs, accession numbers, primer sequences and gene ontology are shown in Table 1.

QPCR was conducted on the GeneAmp 5700 Sequence Detection System (SDS) (Applied Biosystems) using ABsolute™ QPCR SYBR^® Green ROX (500 nM) mix (ABgene). Each reaction was run in triplicate and contained 2.5 μl of cDNA template (equivalent to 25 ng total RNA) along with 900 nM primers in a final volume of 25 μl. Cycling parameters were 95°C for 15 min to activate the DNA polymerase, then 40 cycles of 95°C for 15 s and 60°C for 1 min. Melting curves were performed by using dissociation curve SDS software version 1.3 (Applied Biosystems) to verify that only a single product with no primer-dimers were amplified.

Following QPCR, the raw data was exported to an Excel workbook (Microsoft), entitled Data Analysis for Real-Time PCR (DART-PCR) 23. This programmed workbook enables calculation of threshold cycles and amplification efficiencies for every sample. Differences in amplification efficiency were assessed using one-way analysis of variance (ANOVA), based upon the null hypotheses: (i) that amplification efficiency is comparable within sample groups (outlier detection) and (ii) that amplification efficiency is comparable between sample groups (amplification equivalence) 23. Outliers identified by DART-PCR and samples diverging from the dissociation curve were omitted prior to further analysis.

Differences in relative expression were assessed on log-transformed data using ANOVA and Tukey's honestly significant difference (HSD) for post hoc comparisons. Equality of variance was tested using Levene's test. The relative expression of the reference genes calculated by DART-PCR was exported as an Excel workbook (Microsoft) to geNorm version 3.4 10. The "geNorm" algorithm is based on the proposition that, in any set of assays, the expression levels of suitable reference genes should be perfectly correlated. However, because of technical difficulties in assessing correlation in circumstances when there is little variation, a modified procedure is adopted as follows 10. First, the ratio of expression levels is calculated for any two candidate reference genes. Assuming that the expression ratios should not vary between assays, the variation between the expression ratios is used as an inverse measure, here referred to as gene variability, of the adequacy of the reference genes to be used for normalisation. Thus, the lower the variation, the better the reference genes. Variation is here measured as standard deviation. Given a set of assays that covers the treatments of interest, this procedure can be used to identify the best two reference genes from all possible pairs of reference genes available to the experimenter. A normalisation factor (NF₂) is then produced for these two genes, calculated as the geometric mean of their expression levels. The procedure is then extended to assess whether stepwise inclusion of additional reference genes – producing NF₃ to NF_n – will reduce the average pairwise variation between them. The optimal number of reference genes to be included in a NF is estimated by comparing the pairwise variation between sequential normalisation factors 10, e.g. NF₃ vs. NF₄. All statistical tests were performed in SPSS 12.0.1 for Windows (SPSS, Chicago, IL, USA) applying a significant level of 5%, except reference gene variability and NF analysis, which was computed in geNorm version 3.4 10.