Physiological Modes of Action of Fluoxetine and its Human

Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland, ETH Zurich, Institute of Biogeochemistry and Pollutant...
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Environ. Sci. Technol. 2009, 43, 6830–6837

Physiological Modes of Action of Fluoxetine and its Human Metabolites in Algae J U D I T H N E U W O E H N E R , †,‡ K A T H R I N F E N N E R , †,‡ A N D B E A T E I . E S C H E R * ,†,§ Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Du ¨ bendorf, Switzerland, ETH Zurich, Institute of Biogeochemistry and Pollutant Dynamics, 8092 Zurich, Switzerland, and National Research Centre for Environmental Toxicology (EnTox), University of Queensland, 39 Kessels Rd, Brisbane, Qld 4108, Australia

Received February 19, 2009. Revised manuscript received July 1, 2009. Accepted July 17, 2009.

Fluoxetine, the active ingredient of many antidepressants, was identified as specifically toxic toward algae in a quantitative structure-activity relationship (QSAR) analysis with literature data for algae, daphnia, and fish. The goal of this study was to elucidate the mode of action in algae and to evaluate the toxicity of the major human metabolites of fluoxetine using two different algae tests. The time dependence and sensitivity of the different effect endpoints yield information on the physiological mode of action. Baseline toxicity was predicted with QSARs based on measured liposome-water partition coefficients. The ratio of predicted baseline toxicity to experimental toxicity (toxic ratio TR) gives information on the intrinsic potency (extent of specificity of effect). The metabolite p-trifluoromethylphenol was classified to act as baseline toxicant. Fluoxetine (TR 60-150) and its pharmacologically active metabolite norfluoxetine (TR 10-80) exhibited specific toxicity. By comparison with reference compounds we conclude that fluoxetine and norfluoxetine have an effect on the energy budget of algal cells since the time pattern of these two compounds is most similartothatobservedfornorflurazon,buttheyactlessspecifically as indicated by lower TR values and the similarity of the effect pattern to baseline toxicants. The mixture toxicity of fluoxetine and its human metabolites norfluoxetine and p-TFMP can be predicted using the model of concentration addition for practical purposes of risk assessment despite small deviations from this model for the specific endpoints like PSII inhibition because the integrative endpoints like growth rate and reproduction in all cases gave agreement with the predictions for concentration addition.

Introduction There is currently much scientific and public interest in the environmental risk posed by fluoxetine, the active ingredient of the antidepressant Prozac. Besides its use as an antidepressant, fluoxetine is also prescribed to treat personality and eating disorders, and because of its mood* Corresponding author phone: +61 7 3274 9180; fax: +61 7 3274 9003; E-mail:[email protected]. † Eawag. ‡ ETH Zurich. § University of Queensland. 6830

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brightening effect, it has also been degenerated as a lifestyle drug. When the patent expired in 2000, a wave of generics flooded the market with the result that fluoxetine is one of the most prescribed active ingredients of this class of antidepressants, the selective serotonin reuptake inhibitors (SSRIs). After oral uptake, fluoxetine is metabolized, mainly in the liver, by cytochrome P-450 isoenzymes to norfluoxetine. This demethylated metabolite is even more pharmacologically active (1) and has a longer elimination half-life than the parent compound in rats and humans. Over a 30-day period, 65-75% of the orally administered dose is excreted via urine and 10-15% via feces. In urine, 2.5-11% is excreted as unchanged fluoxetine as well as 7-11% as norfluoxetine, 5.2-7% as conjugated fluoxetine and 8-9.5% as conjugated norfluoxetine, up to 20% as hippuric acid and traces as p-trifluoromethylphenol (p-TFMP) (Supporting Information (SI), Figure S1) (2, 3). In general, drugs reach the aquatic environment via excretion after human consumption or through improper disposal of unused pharmaceuticals (4). Fluoxetine seems to be more persistent in surface water than other SSRIs (5) and highest concentrations in surface water and sewage treatment plant effluents were observed in the U.S., Canada, Norway, and Sweden with concentrations up to 300 ng/L for fluoxetine and norfluoxetine (6-10). In Sweden, concentrations in sewage treatment plant effluents from residential areas were higher than concentrations in hospital effluents (11). The high relevance of fluoxetine compared to other pharmaceuticals for environmental hazard assessment is triggered by substantial toxicity of fluoxetine toward Daphnia magna and Pimephales promelas (12-15) and especially high toxicity toward algae (13, 15, 16). A quantitative structure-activity relationship (QSAR) analysis using literature data revealed that the effects on crustacea and fish are still due to baseline toxicity and mainly related to the hydrophobicity of fluoxetine, whereas the effect on algae must be caused by a specific mode of toxic action (17, 18). However, this type of QSAR analysis has many inherent uncertainties as with respect to the estimation of the hydrophobicity parameter. Therefore, the present study aims at answering (a) if the high toxicity of fluoxetine to algae is due to a specific mode of action or whether its toxicity is hydrophobicity dependent baseline toxicity, (b) if the biological activity of fluoxetine is retained after metabolism, i.e., if the metabolites still possess the same mode of action as the parent compound, and (c) whether these metabolites are of environmental concern. To evaluate whether the observed toxicity is due to baseline toxicity or a specific mode of action, QSARs were used. For each endpoint, a QSAR line describing the minimum toxicity as a function of hydrophobicity marks the baseline toxicity. The more the experimental toxicity deviates from the baseline QSAR, the higher is the intrinsic potency and the clearer it exhibits a specific mode of toxic action. The liposome-water distribution ratios at pH 7, which are used as a hydrophobicity descriptor in the QSAR model for baseline toxicity, were measured, and the effects of fluoxetine and its metabolites were investigated with two different diagnostic algae tests. The “combined algae test” with Pseudokirchneriella subcapitata is a fast screening test that allows a differentiation between direct inhibition of photosynthesis and nonspecific effects (19). The “synchronous algae toxicity test” with Scenedesmus 10.1021/es9005493 CCC: $40.75

 2009 American Chemical Society

Published on Web 08/10/2009

TABLE 1. Molecular Structure, Molecular Weight and Physicochemical Properties (Acidity Constant pKa, Experimental Octanol-Water Partition Coefficient Log Kow (for Estimated Log Kow See SI), Octanol-Water Distribution Ratio at pH 7 (log Dow (pH 7)), Experimental and Predicted Liposome-Water Distribution Ratios at pH 7 (log Dlipw (pH 7)) of Fluoxetine, Norfluoxetine, p-Trifluoromethylphenol and Hippuric Acidn

a Brooks et al. (13), calculated value with ACD/Laboratories Software Version 5.0. b Serjeant and Dempsey (46). Scifinder Scholar Version 2.0 MacOSX (Copyright 2006 ACS), calculated using ACD/Laboratories Software V8.14 for Solaris (1994-2007 ACD/Laboratories). d Adlard et al. (47). e Biobyte (http://www.biobyte.com). f Dollery et al. (48). g Balon et al. (33). h Wan et al. (49). i Hansch et al. (50). j Nakamura et al. (34). k Gulyaeva et al. (51). l Giaginis et al. (52). m Yamamoto et al. (35). n n.a. Not available. c

vacuolatus yields more detailed information on the physiological status of green algae (20-22). We have previously proposed a flow-chart to exploit the mechanistic information gained from the additional endpoints of photosynthesis inhibition, cell division, and cell volume growth for mode-of-action classification (21). Finally, mixture toxicity experiments were performed to confirm the results from the mode of action analysis and to confirm/reject the hypothesis that parent compound and metabolite possess a common mode of action.

Materials and Methods Test Chemicals. Molecular structures and physicochemical properties of the tested chemicals are listed in Table 1. Detailed information on procedures and analytical method of test and reference chemicals is given in the SI. Combined Algae Test with Pseudokirchneriella subcapitata. Algae were grown as described in the SI. The test was conducted according to Escher et al. (19) using a MaxiImaging-PAM (IPAM) (Walz GmbH, Effeltrich, Germany) for determination of the yield of photosynthesis Y after 2 and 24 h, and OD-readings (Spectramax Plus 384, Molecular Devices Corporation, Sunnyvale, U.S.) for the determination of the growth rate µ during 24 h. The inhibition of the photosynthetic yield after 2 h (2 h IPAM) or after 24 h (24 h

IPAM) and the growth rate inhibition were calculated using eqs 1 and 2. Inhibition2 h IPAM ) 1 -

Y2 h sample Y2 h control

or Inhibition24 h IPAM ) 1 -

Inhibition24 h growth rate ) 1 -

Y24 h sample Y24 h control

(1)

µsample µcontrol

(2)

Synchronous Algae Toxicity Test with Scenedesmus vacuolatus. Algae were grown and synchronized as described in the SI. Effects on the structural endpoints reproduction (Repro), cell division (CD), and cell volume growth (CVG) as well as on the functional endpoint photosynthesis efficiency (PSII) of synchronous cultures of S. vacuolatus after one generation (24 h) were measured according to the procedure described earlier (20, 21). For both algae toxicity tests, the concentrations resulting in a 50% effect (EC50) were derived from a log-logistic fit (eq 3) of the concentration-effect curves. VOL. 43, NO. 17, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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Inhibitionendpoint(%) )

100% 1 + 10

m·(logEC50-log concentration)

(3) Analysis of Toxic Ratio (TR). The toxic ratio TR (eq 4) is defined as the ratio of the predicted baseline effect concentration for a defined endpoint EC50endpoint, baseline QSAR (23) of a given compound to the experimentally determined EC50endpoint, experimental. TR indicates whether a compound acts according to baseline toxicity or a specific mode of toxic action with TR < 10 corresponding to baseline toxicity, and TR g 10 indicating a specific mode of toxic action (24, 25). TRi )

EC50endpoint, baseline QSAR EC50endpoint, experimental

(4)

Typically, the octanol-water partition coefficient Kow is used as descriptor of hydrophobicity in baseline toxicity QSARs. However, Kow is not a sufficient surrogate for biological membranes, the target site of baseline toxicity, when it comes topolarandionizablecompounds(26,27).Theliposome-water partition coefficient, or in the case of ionizable compounds, the liposome-water distribution ratios at pH 7 (Dlipw (pH 7)) are universal indicators for baseline toxicity (28) and various previous models have used this descriptor successfully for acidic and basic drugs (25, 29, 30). For the combined algae test, a QSAR based on Dlipw (pH 7) as descriptors, developed by Escher et al. (19), was used for the endpoints 24 h IPAM (eq 5) and 24 h growth rate (eq 6). log

log

1 ) 0.84 · log Dlipw (pH 7) + EC5024 h IPAM, baseline QSAR[M] 1.07 (5) 1 ) EC5024 h growth rate, baseline QSAR[M] 0.95 · log Dlipw (pH 7) + 1.16

(6)

For the synchronous algae toxicity test, a baseline toxicity QSAR developed by Altenburger et al. (20) for the same bioassay and the endpoint Repro was converted from octanol-water partition coefficient Kow to Dlipw (pH 7) (eq 7) as described according to Escher et al. (25, 31) using the relationship between log Kow and log Dlipw (pH 7) from Vaes et al. (32). log

1 ) 0.82 · log Dlipw (pH 7) + 1.16 EC50Repro, baseline QSAR[M] (7)

For the other endpoints of the synchronous algae test, no QSAR is available and therefore no TR analysis could be performed. Determination of Liposome-Water Partition Coefficients. Small unilamellar vesicles were prepared from 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine and liposome-water partitioning of fluoxetine and norfluoxetine was measured at pH 7 as described in the SI.

of 1.5 × 10-2 M (3 g/L) and is therefore not discussed further. Fluoxetine and norfluoxetine did not show any effect on the efficiency of photosynthesis after 2 h, only p-TFMP showed an effect after 2 h but at much higher concentrations than fluoxetine and norfluoxetine. For the classical growth inhibition assay with P. subcapitata, Brooks et al. (13) derived an EC50(96 h) of 24 µg/L for fluoxetine, Christensen et al. (15) an EC50(48 h) of 27 µg/L and Johnson et al. (16) an IC50(96 h) of 45 µg/L. The present results agree well with these literature data considering that incubation times in literature were 2-4 times longer, and EC50 were accordingly 2-4 times lower, which accounts for the expected time dependence of effect. In the synchronous algae toxicity test, the parent compound fluoxetine had its most pronounced effect on CVG with an EC50CVG of 2.7 × 10-7 M (93 µg/L) closely followed by Repro (3 × 10-7 M, 104 µg/L)) and PSII (2.5 × 10-6 M, 865 µg/L), which did not show full inhibition up to 100% (Table 3, concentration-effect curves in SI Figure S3). Norfluoxetine was only slightly less toxic than the parent compound (factor 1.3) whereas p-TFMP was clearly less toxic (factor 660). Both metabolites were most effective in the integral endpoint Repro followed by CVG and inhibition of PSII, but also for norfluoxetine PSII was not fully inhibited. Both test systems yielded consistent information: the growth endpoints were most affected by fluoxetine and norfluoxetine and the EC5024 h growth rate and EC50Repro were in the same range. Only p-TFMP showed a significant effect on photosynthesis efficiency but at higher concentrations than for the growth endpoints. In addition, the growth endpoints in both bioassays yielded very similar EC50. Liposome-Water Partitioning. Since liposome-water distribution ratios at pH 7 were crucial for the TR-analysis, they were derived experimentally from linear sorption isotherms. The slope of the isotherm corresponds to Dlipw (pH 7), which was determined to be 6880 ( 280 L · kgLip-1 for fluoxetine (r2 ) 0.99, F ) 591) and 11920 ( 160 L · kgLip-1 for norfluoxetine (r2 ) 1.00, F ) 5449). The experimental values were higher than previously estimated Dlipw (pH 7) values (see Table 1) and the value of 126 L · kgLip-1 for fluoxetine determined by Balon et al. (33), but the value is within a factor of 3 to the experimental Dlipw (pH 7) of 17000 L · kgLip-1 determined recently by Nakamura et al. (34) and is not significantly different from the value of 6200 ( 300 L · kgLip-1 of Yamamoto et al. (35). The experimentally determined Dlipw (pH 7) are much larger than earlier predictions from our group (17). Based on this observation and support from analysis of additional literature data, we modified the Dlipw (pH 7) prediction model as is described in more detail in the SI. Dlipw (pH 7) for p-TFMP can be predicted with high reliability since p-TFMP is neutral at pH 7 (Dlipw (pH 7) ≈ Klipw (neutral species)). Furthermore, a specific QSAR is available for phenolic compounds relating Kow to Klipw(neutral species) (eq 8 (36)) that was used to calculate the Klipw and therefore the Dlipw (pH 7) of p-TFMP. log Klipw (neutral species) ) 0.78 · log Kow + 1.12 (r2 ) 0.92, n ) 20)

(8)

Results and Discussion

Effect Specificity of Fluoxetine and Metabolites in Algae

Algal Toxicity. In the combined algae test, the effect of fluoxetine, norfluoxetine and p-TFMP increased from 2 to 24 h for the endpoint inhibition of photosynthesis and increased further up to the most sensitive endpoint growth (Table 2, concentration-effect curves in SI Figure S2. Fluoxetine was overall most toxic with an EC5024 h growth rate of 2.6 × 10-7 M (90 µg/L) followed by norfluoxetine (EC5024 h growth rate 7.3 × 10-7 M (242 µg/L)) and p-TFMP (EC5024 h growth rate 5.6 × 10-4 M (91 mg/L)). Hippuric acid showed no effect up to a concentration

The TR-analysis, which compares the experimental toxicity with the predicted baseline toxicity using a QSAR, yields information on the intrinsic potency. Fluoxetine provoked specific effects with a TR24 h growth rate of 62 in the combined algae test (Figure 1) and a TRRepro of 153 in the synchronous algae toxicity test (Figure 2 and SI Figure S7). The TR24 h growth rate of norfluoxetine was close to baseline toxicity, but just above the threshold value for specific effects with a value of 12 (Figure 1), whereas the TRRepro of 77 (Figure 2) indicated

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TABLE 2. EC50 Values and Statistical Estimates of Model Parameters of Fluoxetine, Norfluoxetine, p-Trifluoromethylphenol and the Mixtures for the Inhibition of PSII after 2 h (2 h IPAM) and 24 h (24 h IPAM), and the Inhibition of Growth Rate after 24 h in the Combined Algae Testa statistical estimates of model parameters test endpoint

log EC50 ( SD [M]

slope m ( SD

EC50 (95% confidence interval) [M]

fluoxetine

2 h IPAM 24 h IPAM 24 h growth rate

na -6.2 ( 0.1 -6.6 ( 0.1

na 1.6 ( 0.2 2.0 ( 0.2

na 5.7 × 10-7 (4.9 × 10-7-6.7 × 10-7) 2.6 × 10-7 (2.3 × 10-7-2.8 × 10-7)

norfluoxetine

2 h IPAM 24 h IPAM 24 h growth rate

na -5.8 ( 0.1 -6.1 ( 0.1

na 3.6 ( 0.4 2.1 ( 0.2

na 1.6 × 10-6 (1.5 × 10-6-1.7 × 10-6) 7.3 × 10-7 (6.6 × 10-7-8.2 × 10-7)

p-trifluoromethylphenol

2 h IPAM 24 h IPAM 24 h growth rate

-2.6 ( 0.1 -2.7 ( 0.1 -3.3 ( 0.1

1.7 ( 0.1 2.5 ( 0.3 1.8 ( 0.2

2.7 × 10-3 (2.6 × 10-3-2.9 × 10-3) 1.9 × 10-3 (1.7 × 10-3-2.1 × 10-3) 5.6 × 10-4 (4.8 × 10-4-6.5 × 10-4)

binary mixture of 73.3% fluoxetine and 26.7% norfluoxetine 2 h IPAM 24 h IPAM 24 h growth rate

na -6.1 ( 0.1 -6.3 ( 0.1

na 1.7 ( 0.2 2.1 ( 0.2

na 7.3 × 10-7 (6.4 × 10-7-8.3 × 10-7) 4.5 × 10-7 (3.9 × 10-7-5.3 × 10-7)

2 h IPAM 24 h IPAM 24 h growth rate

na -6.0 ( 0.1 -6.3 ( 0.1

na 2.0 ( 0.2 2.4 ( 0.3

na 9.6 × 10-7 (8.4 × 10-7-1.1 × 10-6) 5.5 × 10-7 (4.9 × 10-7-6.1 × 10-7)

2 h IPAM 24 h IPAM 24 h growth rate

na -5.9 ( 0.1 -6.2 ( 0.1

na 2.2 ( 0.3 2.3 ( 0.3

na 1.2 × 10-6 (1.1 × 10-6-1.4 × 10-6) 6.3 × 10-7 (5.5 × 10-7-7.2 × 10-7)

2 h IPAM 24 h IPAM 24 h growth rate

na -3.8 ( 0.1 -4.3 ( 0.1

na 1.4 ( 0.1 1.7 ( 0.1

na 1.62 × 10-4 (1.5 × 10-4-1.7 × 10-4) 5.0 × 10-5 (4.6 × 10-5-5.5 × 10-5)

compound

binary mixture of 50% fluoxetine and 50% norfluoxetine

binary mixture of 26.7% fluoxetine and 73.3% norfluoxetine

tertiary mixture of fluoxetine, norfluoxetine and p-TFMP

a SD, standard deviation; na, not affected, derivation of EC50 not possible because up to 100% inhibition in another endpoint, no effect was observed for the given endpoint.

TABLE 3. EC50 Values and Statistical Estimates of Model Parameters for the Endpoint Reproduction (Repro), Inhibition of Quantum Yield in PSII (PSII), Cell Division (CD), and Total Cell Volume Growth (CVG) in the Synchronous Algae Toxicity Testa statistical estimates of model parameters test endpoint

log EC50 ( SD [M]

slope m ( SD

EC50 (95% confidence interval) [M]

fluoxetine

Repro PSII CD CVG

-6.5 ( 0.1 -5.6 ( 0.1 na -6.6 ( 0.1

1.5 ( 0.4 1.0 ( 0.2 na 1.2 ( 0.2

3.0 × 10-7 (2.1 × 10-7-4.3 × 10-7) 2.5 × 10-6 (1.8 × 10-6-3.3 × 10-6) na 2.7 × 10-7 (2.0 × 10-7-3.7 × 10-7)

norfluoxetine

Repro PSII CD CVG

-6.4 ( 0.1 -5.4 ( 0.1 na -6.3 ( 0.1

2.7 ( 0.4 1.9 ( 0.2 na 2.3 ( 0.3

4.1 × 10-7 (3.6 × 10-7-4.6 × 10-7) 4.2 × 10-6 (3.9 × 10-6-4.6 × 10-6) na 5.5 × 10-7 (4.9 × 10-7-6.1 × 10-7)

p-trifluoromethylphenol

Repro PSII CD CVG

-3.8 ( 0.1 -3.1 ( 0.1 na -3.7 ( 0.1

2.1 ( 0.4 5.0 ( 0.4 na 2.3 ( 0.4

1.7 × 10-4 (1.4 × 10-4-2.2 × 10-4) 7.7 × 10-4 (7.5 × 10-4-7.7 × 10-3) na 1.8 × 10-4 (1.5 × 10-4-2.3 × 10-4)

compound

a SD, standard deviation; na, not affected, derivation of EC50 not possible because up to 100% in another endpoint, no effect was observed for the given endpoint.

a specific mode of action. These TRs are significantly smaller than the TRs of highly specifically acting biocides, all of which exhibit TRs in the range above 1000 (for TRs of the reference compounds in the combined algae test see Figure 1 and SI Figure S7 and Table S3 for the underlying experimental toxicity data and physicochemical descriptors, for TRs in the synchronous algae toxicity test see Figure 2, SI Figure S7, and data reported in ref 21). This difference in magnitude of TR is an indication that fluoxetine as well as norfluoxetine act specifically in algae, but do not possess a high intrinsic

potency. In contrast, p-TFMP could be identified as a baseline toxicant showing a TR below 10 in both test systems (TR24 h growth rate ) 0.1 and TRRepro ) 1). While the baseline QSAR for the combined algae test was developed with exactly the same procedure and at the same time in our lab (19), the QSAR of the synchronous algae test was taken from the literature (20). Therefore, slight sensitivity differences due to the algae or modifications in the experimental setup were possible, resulting in the slightly higher TR in the endpoint Repro. VOL. 43, NO. 17, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 1. Comparison of EC50 values of the reference compounds 3-nitroaniline, diuron, NPPB, and norflurazon (for details see SI Table S1) with fluoxetine and its metabolites in the combined algae test ( *, 2 h IPAM; 0, 24 h IPAM; b, 24 h growth rate, due to logarithmic scale error bars could not be plotted).

FIGURE 2. Comparison of EC50 values and TRRepro of the reference compounds 3-nitroaniline, irgarol, diuron, Sea-Nine, TBT and norflurazon (data taken from (21)) with fluoxetine and its metabolites in the synchronous algae toxicity test (b, Repro; 0, PSII; ×, CVG; ] CD, due to logarithmic scale error bars could not be plotted).

Mode of Action Analysis In Figure 1 the time and effect pattern of four reference compounds and fluoxetine and its metabolites in the combined algae test is depicted. SI Figure S7 shows the effect as a function of hydrophobicity and graphically depicts the TRs listed in Figure 1. We chose 3-nitroaniline as a reference compound for baseline toxicity. It showed its strongest effect on growth rate followed by 24 h IPAM and 2 h IPAM (19). This effect pattern is consistent with the pattern observed for p-TFMP, which confirms the assignment as baseline toxicant after the TR-analysis. The second reference compound, the herbicide diuron, specifically interrupts the electron transfer at PSII (37), and therefore it had its most pronounced effect already after 2 h IPAM. Growth rate was here clearly less affected than both photosynthesis endpoints 6834

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(19). From comparison with the effect pattern of diuron, we can conclude that fluoxetine and norfluoxetine do not act specifically on the photosystem II of algae. The reference compound NPPB (5-nitro-2-(3-phenylpropylamino)benzoic acid) is known as a specific inhibitor of anion channels (38). It was chosen because fluoxetine as an ion channel inhibitor has a somewhat similar therapeutic mode of action (1, 39, 40) despite the fact that NPPB is a carboxylic acid. The analysis was expected to be more complicated because of multiple specific modes of action of NPPB. However, the TR24 h IPAM and the TR24 h growth rate were both below 1 (Figure 1 and SI Figure S7) indicating baseline toxicity in algae. In addition, there was a highly sensitive effect on photosynthesis after 2 h that disappears after prolonged incubation. Note that NPPB, despite its acid function, is a relatively hydrophobic chemical and various studies have shown that the more hydrophobic a chemical gets, the more likely its specific mode of action is masked by nonspecific effects (41). Norflurazon, a specific carotenoid-biosynthesis inhibitor (42, 43), was chosen as a reference compound because of structural similarity with fluoxetine including the CF3-group on the aromatic ring as well as a secondary amine group. The inhibition of the carotenoid biosynthesis by norflurazon leads to a deficiency of proper functioning chloroplasts and therefore a lack of energy. Norflurazon has in common with fluoxetine and norfluoxetine that it did not show any effect on the photosynthesis efficiency after 2 h, but in contrast to fluoxetine and norfluoxetine, after 24 h photosynthesis was more affected than growth rate. This analysis does not allow any final conclusion but narrows down the search to two hypotheses: (a) fluoxetine and norfluoxetine target a different but functionally similar receptor as norflurazon; or (b) fluoxetine and norfluoxetine bind to the same receptor as norflurazon but binding is less strong and consequently the effect is less specific. Additionally, the compounds are so hydrophobic that nonspecific partitioning to the membrane adds to the overall effect. Hypothesis (b) would be supported by the relatively low TR 24 h IPAM of fluoxetine and norfluoxetine. To further investigate these hypotheses, we used the synchronous algae toxicity test, for which a mode-of-action classification flow-chart was developed in an earlier study (21). Information on the physiological modes of action of a set of reference compounds with known mechanism was used to define rules for mode-of-action classification. Briefly, the classification works as follows: Compounds with TR e 10 are classified as baseline toxicants. For those compounds with TR g 10, if the endpoint PSII is more sensitive than Repro, the investigated compound is classified as an inhibitor of photosynthesis (example irgarol and diuron in Figure 2 and SI Figure S7). Compounds with Repro > PSII, if the three endpoints Repro, CD, and CVG are more or less equally affected, the energy production is impacted, e.g., by uncoupling or ATPase inhibition (example TBT in Figure 2 and SI Figure S7). If only Repro and CD are equally affected and CVG is significantly less influenced, then cell division is directly interrupted or biosynthesis pathways directly related to cell division, e.g., the biosynthesis of proteins or fatty acids, are disturbed (example Sea-Nine in Figure 2 and SI Figure S7). Last but not least, if Repro is more sensitive than CVG, and CD is not affected, then biosynthesis pathways related to energy production are likely to be the targets (example norflurazon in Figure 2 and SI Figure S7). With a TR e 10 and a very similar effect pattern to the reference baseline toxicant 3-nitroaniline, p-TFMP was again confirmed as baseline toxicant (Figure 2 and SI Figure S7). The pharmacologically active metabolite norfluoxetine could be classified as a compound whose mode of action is related to the energy production of the algal cells since Repro is

FIGURE 3. Isobologram of the binary mixtures of fluoxetine and norfluoxetine in the combined algae test for the endpoint growth inhibition (9s, line of concentration addition; b, binary mixtures) and the endpoint 24 h IPAM (0---, line of concentration addition; O, binary mixtures). Error bars indicate 95% confidence intervals. more affected than CVG, and CD is not affected. Our hypothesis drawn from the analysis of the combined algae test could therefore be confirmed here. For fluoxetine, the classification is not straightforward since CVG is somewhat more affected than Repro but the 95% confidence intervals are overlapping. This is an indication that fluoxetine also possesses the same mode of action as norfluoxetine. For both algae tests, the effect pattern of fluoxetine and norfluoxetine is most similar to baseline toxicity. This is puzzling given the TR > 10, which assigns these compounds to a specific mode of action. The similarity is more pronounced for norfluoxetine than for fluoxetine, consistent with a TR of norfluoxetine smaller by a factor of 2 than of fluoxetine. This difference in intrinsic potency may be explained by both hypotheses (a) and (b) above. Because of their high Dlipw (pH 7), fluoxetine and norfluoxetine can well interact with membranes exerting baseline toxicity and disturbing the membrane-protein interfaces in a nonspecific way.

Mixture Experiments to Elucidate the Contribution of Specific Effects and Baseline Toxicity Mixture toxicity experiments have been successfully used in the past as a diagnostic tool to confirm mode of action classification (25). If compounds act according to the same mode of action, their mixture toxicity is concentrationadditive (CA), if they act on different target sites, their mixture effect is called independent action (IA) and both models can be easily calculated and predictions compared with experimental mixture data (44). Since the time and effect patterns of fluoxetine and norfluoxetine are very similar, we hypothesized that either the two compounds possess the same mode of action and that the binary mixture of fluoxetine and norfluoxetine will act according to CA or the modes of action are different and therefore, depending on the specificity of the endpoint, CA is expected for the nonspecific endpoint (24 h growth rate) and IA is expected for the specific endpoint (24 h IPAM). In the combined algae test three mixtures were tested with different ratios of fluoxetine and norfluoxetine (Table 2). All three mixtures showed the same effect pattern as the single compounds and for the endpoint growth rate all three mixtures directly lie on the theoretical line of CA in an isobologram (Figure 3), while for the endpoint 24 h IPAM all mixtures lie above the line of CA indicating a

smaller effect than predicted for CA. The difference can be explained by IA (see SI Figure S8). The good agreement with CA for the nonspecific endpoint 24 h growth rate is consistent with our hypothesis that the nonspecific effect is influenced by hydrophobicity driven baseline toxicity. The deviation from CA for the more specific endpoint 24 h IPAM confirms the difference in effect pattern observed indicating that fluoxetine and norfluoxetine do have a slightly different target protein or different binding affinity to the target protein. Tertiary mixtures with fluoxetine, norfluoxetine and p-TFMP were again consistent with predictions of CA for the endpoint growth rate, whereas the specific endpoint photosynthesis inhibition appeared more variable with a tendency toward IA (SI Figure S9). Finally, binary mixture experiments with the synchronous algae test yielded consistent results with the combined algae test (SI Figure S10): the integrative endpoint Repro just like the growth rate endpoint in the combined algae test could be explained by CA, while the more specific endpoint CVG showed lower effects than predicted by both, CA and IA (for more background information on the mixture experiments see SI). Given the nearly concentration-additive effect of fluoxetine and its human metabolites, it is important not to neglect the contribution of the metabolites to the risk assessment, in particular for drugs like fluoxetine where certain metabolites are as abundant and toxic as the parent compound. The environmental concentrations of fluoxetine are about 2 orders of magnitude smaller than toxic concentration in algae. Nevertheless, given that fluoxetine acts additively together with its metabolites, not to mention potential mixture effects with other pharmaceuticals and environmental pollutants, and that the 24 h algal test is an acute test, requiring an assessment factor of 1000 for the derivation of the predicted no-effect concentration PNEC, a case-by-case environmental risk assessment is warranted. This study is also a nice example of a compound of high therapeutic potency in humans that has only baseline toxic effects in aquatic invertebrates like daphnia and in fish (17), but does pose an unexpected specific hazard to algae. Therefore, for future applications in risk assessment of pharmaceuticals we recommend to always follow two pathways: (a) to read across from the therapeutic mode of action as was recommended by Ankley et al. (45), and, (b) to do a TR-analysis and in case of indications for specific effects to attempt a thorough mode of action analysis.

Acknowledgments This study was supported by the Swiss Federal Office of the Environment within the framework of the project “KoMet” and partially supported by the European Union under the 6th framework program in the STREP ERAPharm (SSPI-CT2003-511135). We thank Roman Ashauer, Nadine Bramaz, Anja Coors, Ditte B. Hansen, Susanne Kern, Holger Nestler, Pamela Quayle, Sybille Rutishauser, Etie¨nne Vermeirssen, and Thomas Wu ¨ thrich for experimental support and helpful discussions and Leisa-Maree Toms for reviewing the manuscript.

Supporting Information Available Metabolism of fluoxetine, more detailed information on the experiments, concentration-effect curves of all compounds, detailed information on the reference compounds in the combined algae test, additional information on the TRanalysis, development of a new prediction model for Dlipw (pH 7) for bases, and additional mixture studies. This material is available free of charge via the Internet at http:// pubs.acs.org. VOL. 43, NO. 17, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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