Feeding Activity and Xenobiotics Modulate Oxidative Status inDaphnia magna: Implications for Ecotoxicological TestingSara Furuhagen,* Birgitta Liewenborg, Magnus Breitholtz, and Elena Gorokhova
Department of Applied Environmental Science, Stockholm University, Svante Arrhenius vag̈ 8, SE-106 91 Stockholm, Sweden
*S Supporting Information
ABSTRACT: To apply biomarkers of oxidative stress in laboratory and field settings,an understanding of their responses to changes in physiological rates is important. Theevidence is accumulating that caloric intake can increase production of reactive oxygenspecies and thus affect background variability of oxidative stress biomarkers inecotoxicological testing. This study aimed to delineate effects of food intake andxenobiotics on oxidative biomarkers in Daphnia magna. Antioxidant capacity measuredas oxygen radical absorbance capacity (ORAC) and lipid peroxidation assayed asthiobarbituric acid reactive substances (TBARS) were measured. Food intake wasmanipulated by varying food densities or by exposing the animals to chemicalsinhibiting feeding rate (pharmaceutical haloperidol and pesticide lindane). Feedingrate proved to affect both protein, ORAC, and TBARS in unexposed daphnids.However, there was no significant effect of feeding rate on the protein-specific ORACvalues. Both substances affected individual protein and ORAC levels and changed theirrelationship to feeding rate. Our results show that inhibition of feeding rate influencedthe interpretation of biomarker response and further emphasize the importance of understanding (1) baseline variability inpotential biomarkers due to variations in metabolic state and (2) the contribution of feeding rate on toxic response ofbiomarkers.
■ INTRODUCTION
To counteract pro-oxidative processes in aerobic organisms,homeostasis is maintained between the cellular production ofreactive oxygen species (ROS) and the endogenous antioxidantdefense. The balance between ROS production and theantioxidant defense can be affected by physiological factors,such as age and disease,1 as well as by environmental factors,such as hypoxia2 and pollutants.3 Caloric restriction (CR) hasbeen identified as an important factor affecting the cellularproduction of ROS as low-calorie diets hamper ROSproduction.4 Studies on isolated rat mitochondria showedthat CR results in decreased substrate oxidation activity, leadingto lowered mitochondrial membrane potential and increasedproton leakage and thus a diminished generation of ROS.5 Thiseffect appears to be a general mechanism as the effects of CRhave been shown for a variety of species.6 As an excess of ROScan be harmful to DNA, lipids, and proteins,7 the levels ofoxidative damages on these biomolecules have been found tobe lower in animals given a CR diet.6
Chemical substances can affect cellular ROS concentrationsthrough different mechanisms. Pro-oxidative substances canincrease generation of ROS and other radicals by enteringredox cycles,8 but ROS production can be also induced byincreasing metabolic rate as a response to stress or throughinduction of enzymes involved in xenobiotic metabolism, suchas CYP450 and NAD(P)H.9 Moreover, the oxidative homeo-stasis can be disrupted by depletion of antioxidative substancesin xenobiotic metabolism.7,9 Consequently, biomarkers of
oxidative stress are widely used in ecotoxicology and ecologyas indicators of stressful conditions,10 although specific causesof the observed biochemical alterations are not alwaysidentifiable because of the plethora of factors that may affectthe oxidative status of organisms. Therefore, to facilitatebiomarker application and interpretation of measured responsesto stress factors, we need to understand the magnitude andcauses of background variability for the biomarker of interest.11
In particular, variability in feeding rate has a high potential toaffect biomarkers of oxidative stress, because of the effect ofcaloric intake on the production of ROS. Feeding rate is asensitive and ecologically relevant end point in ecotoxicologicalassays as exposure to a wide range of substances has beenreported to cause feeding inhibition in various test species.12,13
In stress assessment, feeding inhibition assay proved to beabout 50-fold more sensitive than standardized acuteecotoxicological assays employing survival as an end point.14
Moreover, although effects of ad libitum feeding on many endpoints have been identified as a serious methodological issue intests with vertebrates,15−17 no attempt has been made so far tostudy the effects of feeding rate and xenobiotic exposure onoxidative biomarkers in invertebrates. The objectives of thisstudy were to (1) establish relationships between feeding rateand oxidative biomarkers in Daphnia magna and (2) under-
Received: February 22, 2014Accepted: September 23, 2014
stand the contribution of variation in feeding rate to toxicresponse.Two model substances, haloperidol and lindane, were used
to address these objectives. Haloperidol is a dopamine receptorantagonist that has been found to cause feeding inhibition inrats by blocking hunger perception,18 and it has indeed beenfound to cause feeding inhibition in D. magna (Furuhagen,unpublished data). Lindane is a neurotoxic insecticide19 thathas been shown to inhibit feeding in daphnids by reducing themovement of filtering limbs.12,20,21 In our study, wemanipulated feeding activity in daphnids by exposing them toeither varying food levels in the absence of a toxic compound orto varying substance concentrations at a constant food level. Asproxies for antioxidant capacity and oxidative damage, weassayed oxygen radical absorbance capacity (ORAC) and lipidperoxidation levels measured as thiobarbituric acid reactivesubstances (TBARS). Both biomarkers have been used beforeto assess oxidative stress in microcrustaceans, includingdaphnids.22,23 Two sets of hypotheses were tested with regardto the effects of food intake and chemical exposure in thisstudy. We hypothesized that individual protein content will bepositively related to feeding rate in the unexposed daphnids(hypothesis 1). Moreover, the oxidative biomarkers will bepositively related to the increase in protein content of animalsfeeding at higher rates and thus having higher ROS production(hypothesis 2). In addition to feeding inhibition andcorresponding effects on the biomarker response, the exposureto toxicants was hypothesized to have effects on therelationships between feeding rate and protein allocation andbetween protein content and oxidative biomarkers. Inparticular, a negative effect on individual protein content wasexpected in the haloperidol-exposed daphnids, whereas lindanewas hypothesized to have a positive effect on the proteincontent. The rationale for this expectation was based on thereported negative effect of haloperidol on the expression of heatshock proteins (hsp)24 and the induction of hsp after lindaneexposure25 (hypothesis 3). An increase in oxidative damage,independent of feeding rates, was expected in exposeddaphnids, whereas the antioxidant capacity could be bothpositively and negatively affected by xenobiotics depending onthe stress levels (hypothesis 4).
■ METHODS
Test Organism. The daphnids originated from a singleclone (environmental pollution test strain Klon 5, the Stateoffice for nature, environment, and customer protection North-Rhine Westfalia, Bonn, Germany; originally from the FederalEnvironment Agency, Berlin, Germany). They were cultured in2 L of M7 medium (OECD standards 202 and 211) at a stockdensity of ∼20 individuals in each beaker and fed three times aweek with a mixture of Pseudokirchneriella subcapitata andScenedesmus subspicatus.
Functional Response Experiments. Using varyingdensities of algal suspension, we manipulated the daphnidfeeding rate. The individuals feeding at varying rates were alsoused to measure individual protein content, ORAC (experi-ments I and II), and TBARS (experiment II) (Table 1). Thefeeding rate of juvenile daphnids (96 h old) as a function offood density was measured in M7 medium with five daphnidsin each replicate. Fluorescence of the algae (P. subcapitata) wasmeasured using a Turner designs 10-AU fluorometer at thestart of the test and after 24 h to assess the feeding rate of thedaphnids. All experiments were conducted in darkness at 20 °Cto minimize algal growth during the incubation. An additionalreplicate without daphnids served as a control to assess algalgrowth. Incubation for ORAC and TBARS measurements(experiment II) was done using starved animals and thoseincubated at the intermediate food concentration (1.5 μg CmL−1) and at the near-saturation concentration (7 μg C mL−1).
Feeding Inhibition Tests. Feeding inhibition tests(haloperidol: experiment III; lindane: experiment V; testconditions as in experiment I) were performed according toBarata et al.26 with minor modifications. In these experiments,the feeding rate was measured at a constant food concentration(1.5 μg C mL−1), and the animals were used for measurementsof individual protein content and ORAC. Exposure for TBARSand ORAC (experiments IV and VI for haloperidol and lindane,respectively) were conducted at a food concentration of 1.5 μgC mL−1 and using the same test conditions as in experiment II(Table 1) and P. subcapitata as a food source. Both haloperidoland lindane were dissolved in dimethyl sulfoxide (DMSO) foruse in the bioassays. Solvent control with a DMSOconcentration corresponding to a volume of 0.1‰ of thetotal incubation volume was used in all exposure tests.
Biochemical Analyses. At the termination of eachexperiment, live daphnids were pooled within replicates, rinsed
Table 1. Summary of the Experiments, Specific Conditions, and Measured Biomarkersa
in potassium phosphate buffer (PPB), and transferred toEppendorf tubes. All samples were snap frozen and stored at−80 °C until analysis.Protein Quantification. Samples for protein and ORAC
measurements were homogenized in 150 μL of PPB buffer (3.1mM, pH 7.4). Protein content (μg ind−1) was determined bythe bicinchoninic acid method27 using a Pierce BCA ProteinAssay kit (Thermo Scientific) according to the microplateprocedure with some modifications. A transparent microplatewas used, and the total volume in the wells was 150 μL, with 10μL of homogenate, 10 μL of PPB, and 130 μL of workingsolution. Absorbance was measured at 540 nm using a FluoStarOptima plate reader (BMG Lab Technologies, Germany).Oxygen Radical Absorbance Capacity. Total antioxidant
capacity was assayed as ORAC according to Ou et al.,28 withminor modifications. Fluorescein was used as a fluorescentprobe (106 nM) and 2,2- azobis(2-amidinopropane) dihydro-chloride (AAPH) (152.66 mM) as a source of peroxyl radicals.Trolox (218 μM, Sigma−Aldrich) was used as the standard. Ineach assay, 20 μL of sample was added to each well and mixedwith 30 μL of AAPH and 150 μL of fluorescein. ORAC levelswere expressed as ORAC per individual. Additionally, ORACvalues were normalized to protein content (ORACp) beforebeing related to feeding rate because of the high contribution ofproteins to ORAC values.29
Lipid Peroxidation. Two exposures were performed forunexposed and exposed daphnids for TBARS analysis (experi-ments II, IV, VI; Table 1) with high (A) and low (B)population density, respectively. Daphnids were assayed forlipid peroxidation by a modified TBARS method for measuringthe aldehydic lipid peroxidation decomposition derivatives,which form fluorescent products after reacting with thiobarbi-turic acid (TBA).30 Daphnids were homogenized in 200 μL ofPPB, sonicated 3 × 10 s, and aliquoted. Subsamples of 125 μLof tissue homogenate were treated with 125 μL of 10%trichloroacetic acid. The samples were further mixed with 150μL of TBA (2 mM) and incubated at 100 °C for 1 h. Aftercooling to room temperature, 220 μL of a butanol/pyridine(volume ratio 15:1) mixture was added, and the samples werevortexed (2 × 10 s) and centrifuged for 5 min at 4000g. Theorganic phase was used for fluorometric determination (540nm/590 nm) of malondialdehyde (MDA) concentration (μMMDA equivalents ind−1). The MDA concentrations wereexpressed as TBARS per individual. Following the commonprocedure for biochemical end point, TBARS were normalizedto protein content (TBARSp) before being related to feedingrate.Data Analysis and Statistics. Feeding rate was calculated
according to Bam̊stedt et al.31 The functional response ofunexposed daphnids was fitted to a sigmoid function:32,33
= + − −F F e/(1 )k C Cmax
( )m (1)
where F is feeding rate (μg C h−1 ind−1), Fmax is the theoreticalmaximum feeding rate, e is Euler’s number, k is a constant, C isfood concentration (μg C mL−1), and Cm is the half-saturationconstant.To test hypotheses 1 and 2, the relationships between
feeding rate and biomarkers were analyzed by linear regressionanalysis. The effect of chemical exposure on feeding rate wasevaluated using the Hill equation:
= + − × +F F F F C C( ( ) )/( EC )n n nmin max min 50 (2)
where F is the feeding rate (μg C h−1 ind−1), Fmin is theminimum feeding rate (μg C h−1 ind−1), Fmax is the maximumfeeding rate (μg C h−1 ind−1), C is the logarithm of thesubstance concentration (mg L−1) +1, and n is the Hillconstant.34 The substance concentration (logarithmic value)that causes 50% feeding inhibition is represented by EC50 (mgL−1).Hypotheses 3 and 4 were addressed using general linear
models to test the impact of substance exposure on therelationships between feeding and protein allocation andbetween protein content and oxidative biomarkers; anexperimental run (A and B) was used as a covariable toaccount for the differences in experimental design. All valueswere normalized to the mean value of the control group foreach treatment. To facilitate statistical comparisons andinterpretation, the independent variables were centered bytheir respective mean values using response interval coveringboth exposed and unexposed daphnids. Centering inputvariables removes the collinearity between the main effectsand the interaction predictors, therefore allowing theinterpretation of main effects.35 The interactions betweenexplanatory variables were removed from the model whennonsignificant. Assumptions of normality and homoscedasticitywere fulfilled for all data as confirmed by residual plot analysis.Significant level was less than 0.05 for all tests, and all analyseswere carried out in R 2.13.2.Projection to latent structures by means of partial least-
squares (PLS) was applied to visualize directions in amultivariate space for maximum separation of observations(biomarkers and physiological variables across an individual)belonging to different groups (treatments). The amount ofvariation attributed to each explanatory variable was deter-mined by regressing each explanatory variable against theresponse variable (treatment as a categorical variable) in theabsence of the other explanatory variables36 as implemented inSTATISTICA 8 (StatSoft, Inc. 2013).
■ RESULTSFeeding and Biomarker Responses in Unexposed
Animals. Feeding rate increased with increasing foodconcentration, reaching saturation at ∼6.7 μg C mL−1 (Figure1). Moreover, the individual protein content was significantlypositively related to the feeding rate (Table 2; Figure 3). Also,there was a significant positive relationship between individualORAC and protein values. However, no significant relationshipbetween ORACp and feeding rate was found. Finally, individualprotein content and TBARS as well as TBARSp and feedingrate were positively related to each other (Table 2; Figure 3).
Feeding and Biomarker Responses in ExposedDaphnids. Neither haloperidol nor lindane caused mortalitywithin the tested concentration range. However, bothsubstances had an inhibitory effect on the feeding rate,following a sigmoid dose−response and resulting in nearlycomplete feeding inhibition in the highest concentrations ofboth substances. Haloperidol EC50 was 1.62 mg L−1 (95%confidence interval: 1.37−1.90 mg L−1) and lindane EC50 was1.27 mg L−1 (95% confidence interval: 1.03−1.55 mg L−1)(Figure 2).Similar to the unexposed daphnids, individual protein
content was significantly positively related to feeding rate inexposed daphnids. Moreover, haloperidol had a significantnegative effect on the baseline protein content and a positiveeffect on the slope on the relationship between protein and
feeding as indicated by the significant interaction term offeeding rate and treatment. By contrast, lindane had nosignificant effect on the individual protein content (Table 3Aand Figure 3).Again, similar to the unexposed daphnids, ORAC was
positively related to protein content in both haloperidol- andlindane-exposed daphnids. Moreover, haloperidol had a positive
effect on the ORAC−protein relationship, as indicated by thesignificant interaction between treatment and protein content.Lindane significantly decreased the baseline ORAC values asindicated by the significantly different intercept (Table 3B).In contrast to the unexposed daphnids, a significant positive
relationship between ORACp and feeding rate was observed inthe animals exposed to haloperidol or lindane. Moreover, bothsubstances had significant negative effects on the ORACpbaseline as indicated by the significant treatment effect (Table3C).Haloperidol had no significant effect on the relationship
between TBARS and protein content. However, the significantinteraction for lindane and protein indicates a significantlynegative effect on the TBARS−protein relationship due tolindane exposure (Table 3D). Neither haloperidol nor lindanehad any significant effect on the relationship between TBARSpand feeding rate (Table 3E).The PLS analysis showed a clear pattern related to the
differences between the lindane-exposed and unexposeddaphnids revealing relevant ORACp, feeding rate, and TBARSpin this separation. The two PLS components accounted for69% of the total variance. No clear separation between thehaloperidol-exposed and unexposed animals or animals exposedto low lindane concentrations was observed, with variability inboth haloperidol-exposed and unexposed groups being largelyaffected by variations in feeding and individual protein content(Figure 3).
■ DISCUSSION
In D. magna, biomarkers of oxidative status changed in concertwith feeding rate, which thus was established as a confoundingfactor for oxidative biomarkers in this standard test species. Inaddition to inducing feeding inhibition, exposure to our modelsubstances, haloperidol and lindane, altered the relationshipbetween feeding rate, protein, and oxidative biomarkers,emphasizing the complexity of the biomarker responses.Hypothesis 1, linking protein content to feeding rate, was
confirmed by the significant positive relationship betweenfeeding rate and protein content, indicating that proteinsynthesis increases as more resources become available forprotein production.37 Since protein content is commonly usedto normalize enzyme activities and other biochemicalconstituents used as biomarkers in ecology and ecotoxicology,this response is important for biomarker applications in general.
Figure 1. Functional response of juvenile D. magna fed P. subcapitata.The horizontal broken line represents the maximum feeding rate, andthe vertical line represents saturation level 6.7 μg C/ml, calculatedusing the lower 95% confidence interval for the theoretical Fmax.
Table 2. Linear Regression for Unexposed Daphnidsa
aLinear regressions (y = ax + b) for the relationships between feedingrate and biomarker responses and between biomarkers and individualprotein content. Asterisks indicate level of significance for the slope(a): p ≤ 0.05 (*); p ≤ 0.01 (**); p ≤ 0.001 (***). FR, feeding rate;ORAC, oxygen radical absorbance capacity; ORACp, protein-specificORAC; TBARS, thiobarbituric acid reactive substances; TBARSp,protein-specific TBARS.
Figure 2. Feeding inhibition in D. magna exposed to (A) haloperidol and (B) lindane. The vertical lines represent EC50 values, and the gray, brokenlines represent upper and lower confidence intervals (95%).
Hypothesis 2, linking oxidative biomarkers to individualprotein content, was also supported. In both exposed and
unexposed daphnids, individual ORAC values were positivelyrelated to protein content, most probably due to increasedproduction and intake of low-molecular compounds andproteins with antioxidative properties. The antioxidant defenseconsists of enzymes as well as other proteins and low-molecular-mass agents, such as ascorbic acid, reducedglutathione, methionine, and uric acid.7 The antioxidativeactivity of the water-soluble fraction of these compounds ismeasured in the ORAC assay.28 The lack of correlationbetween ORACp and feeding rate in the unexposed daphnidssuggests that the allocation of proteins to the antioxidantdefense did not increase in response to increased caloric intake,which is in agreement with previous findings.38 A baselinerelationship between the feeding rate and alterations inantioxidant defense has thus been established, which alsofacilitates application of ORACp as a biomarker in ecologicaland ecotoxicological studies.11
Even though EC50 values for feeding inhibition were similarbetween haloperidol and lindane as evidenced by theoverlapping confidence intervals, their effects on protein andORAC differed, which may be related to differences in theirmode of action.18,20 By including protein and substanceexposure in the statistical models, we could confirm hypothesis3 and show that haloperidol had a positive effect on therelationship between individual protein content and feedingrate. This was likely due to decreased protein synthesis withincreasing haloperidol concentration.39 By contrast to haloper-idol, lindane did not have any effect on protein content. Hence,any difference in protein content in response to increasinglindane concentration was solely due to the decrease in filteringactivity and thus feeding rate in the exposed animals. Withoutincluding feeding rate as an explanatory variable to the model,this effect would have been missed, and observed alterations inprotein content and in the biomarkers normalized to protein
Table 3. General Linear Models Testing Effects of the Xenobiotics and Feeding Rate on the Individual Protein Content, ORAC,ORACp, TBARS, and TBARSpa
aTreatment group was set as a reference. Asterisks indicate level of significance: p ≤ 0.05 (*); p ≤ 0.01 (**); p ≤ 0.001 (***). FR, feeding rate;ORAC, oxygen radical absorbance capacity; ORACp, protein-specific ORAC; TBARS, thiobarbituric acid reactive substances; TBARSp, protein-specific TBARS.
Figure 3. Standardized biplot visualizing PLS model by scatter plotstermed scores or loadings plots and showing how predictors form thespace of the latent variables and how they are combined with theobservations. Each point on the score plot represents an individualDaphnia sample projected in the bivariate space and loading scoresprovide the correlation between the original variables and the newcomponent variables. The model is for treatment as a response variableand feeding rate (FR), individual protein content (protein), protein-specific ORAC and TBARS values (ORACp and TBARSp,respectively) as explanatory variables. The structure of the multivariatepoint cloud is represented by the shaded areas in the bagplot,analogous to a box-and-whiskers plot but also visualizing the spread,correlation, skewness, and tails of the data.45 The small square coloredaccording to the treatment represents the depth median (the deepestlocation), the dark area corresponds to 50% of the data set, and thelight area is a fence augmented by a default factor of 1.5. Sample pointsoutside the shaded areas are outliers.
content may erroneously have been attributed direct toxicmechanisms on protein metabolism.Hypothesis 4 also found support as both haloperidol and
lindane affected the relationship between protein and ORAC.Exposure to haloperidol resulted in lower allocation ofresources to the antioxidant defense in relation to proteincontent, which is consistent with a general response tostarvation, whereas lindane caused a significant decrease inthe baseline ORAC values. Because of the effects of haloperidoland lindane on protein allocation and ORAC, there weresignificant positive effects on the relationship between ORACpand feeding rate in the exposed daphnids. The altered ORAC−protein relationship and the positive relation between ORACpand feeding rate indicate reduced resource allocation toantioxidant defense and/or a depletion of antioxidativecompounds due to the chemical exposure. One can speculatethat these effects may be related to detoxification as someagents contributing to the antioxidant defense are also involvedin xenobiotic metabolism. One of these, glutathione (GSH), isa cofactor in the detoxification of ROS,7 and depletion of GSHis used as a biomarker of oxidative stress due its involvement inantioxidative reactions.40 Both haloperidol and lindane havebeen shown to cause GSH depletion due to its involvement inROS detoxification and xenobiotic metabolism.41−43 Hence,depletion of GSH may partly explain the decrease in ORAC inrelation to protein content observed for exposed daphnids.Contrary to hypothesis 4, predicting that lipid peroxidation
levels would increase in response to xenobiotic exposure,haloperidol did not altered the relationship between proteincontent and TBARS, thus indicating that lipid peroxidationlevels were only affected by feeding rate (Figure 3). Theseresults contradict reported effects of this drug on lipidperoxidation in humans that had been administrated haloper-idol (10 mg day−1) for 2 weeks.41 However, the testedconcentrations in our study may have been too low to induceoxidative damages during the 24 h exposure, and theantioxidant defense could have successfully counteracted ROSeffects with nondetectable effects on lipid peroxidation levels.The high survival rate in this study could be indicative of suchresponses, albeit high survivorship does not necessarily meanthat an oxidative stress response is absent.23 Lindanesignificantly lowered the TBARS levels at increasing proteincontent compared to the unexposed daphnids. Because of thepositive effect of lindane on hsp, and thus proteincomposition,25 normalizing TBARS to the total proteinconcentrations in the sample could introduce additionaluncertainty and even be misleading for understanding ofchemical exposure effects. Assessment of normalizationstrategies for oxidative stress biomarkers is needed to facilitateinterpretation of these responses in the field and laboratorysettings.The observed effects of calorie intake on TBARS levels
(Table 2 and Figure 3) raise questions about optimal testingdesign for studies employing oxidative stress biomarkers toevaluate effects of various stressors. The ad libitum feedingregime used in many ecotoxicological tests may lead to highlipid peroxidation levels in actively feeding nonstressedindividuals and further to erroneous interpretation of theresults. Hence, bioassays with D. magna should be performed atmoderate food levels to avoid effects on biochemical markersthat are solely a consequence of ad libitum feeding. Moderatedietary restriction has also been shown to increase thesensitivity and response to toxic substances in both rodents15
and rotifers,44 and our results indicate that this is also the casefor oxidative biomarkers in D. magna.In conclusion, our results indicate that alterations in oxidative
biomarker response due to xenobiotic exposure may not onlybe a consequence of direct interactions with oxidative processesbut can also be a result of indirect response via feedinginhibition. Since protein content, ORAC, and TBARS werepositively correlated with food intake, it is necessary to accountfor inhibitory effects of xenobiotics on feeding rate wheninterpreting responses of these biomarkers. Without consider-ing confounding factors representing nutritional status andmetabolism when evaluating biomarker response to toxicexposure, there is a risk of making erroneous conclusionsabout toxicity effects and mechanisms. To further increase thevalue of biomarkers in general and oxidative biomarkers inparticular, the importance of confounding factors forinterpretation of biomarker responses needs to be addressedroutinely in biomarker validation.
■ ASSOCIATED CONTENT
*S Supporting InformationTables of protein content in exposed D. magna and feedinginhibition test with D. magna for haloperidol; a plot of feedinginhibition of D. magna exposed to haloperidol. This material isavailable free of charge via the Internet at http://pubs.acs.org.
NotesThe authors declare no competing financial interest.
■ ACKNOWLEDGMENTSThis study was supported by the Swedish Research Council forEnvironment, Agricultural Science and Spatial Planning(FORMAS), Stockholm University’s strategic marine environ-mental research program “Baltic Ecosystem Adaptive Manage-ment”, and the Swedish Foundation for Strategic Environ-mental Research (MISTRA; MistraPharma).
■ REFERENCES(1) Yu, B. P. Aging and oxidative stress: Modulation by dietaryrestriction. Free Radical Biol. Med. 1996, 21 (5), 651−668.(2) Valko, M.; Leibfritz, D.; Moncol, J.; Cronin, M. T. D.; Mazur, M.;Telser, J. Free radicals and antioxidants in normal physiologicalfunctions and human disease. Int. J. Biochem. Cell Biol. 2007, 39 (1),44−84.(3) Mustafa, S. A.; Al-Subiai, S. N.; Davies, S. J.; Jha, A. N. Hypoxia-induced oxidative DNA damage links with higher level biologicaleffects including specific growth rate in common carp, Cyprinus carpioL. Ecotoxicology 2011, 20 (6), 1455−1466.(4) Speakman, J. R.; Mitchell, S. E. Caloric restriction. Mol. AspectsMed. 2011, 32 (3), 159−221.(5) Lambert, A. J.; Merry, B. J. Effect of caloric restriction onmitochondrial reactive oxygen species production and bioenergetics:reversal by insulin. Am J. Physiol.: Regul., Integr. Comp. Physiol. 2004,286 (1), R71−9.(6) Sohal, R. S.; Weindruch, R. Oxidative stress, caloric restriction,and aging. Science 1996, 273 (5271), 59−63.(7) Halliwell, B.; Gutteridge, J. M. C. Free Radicals in Biology andMedicine, 4th ed.; Oxford University Press: New York, 2007.(8) Lushchak, V. I. Environmentally induced oxidative stress inaquatic animals. Aquat. Toxicol. 2011, 101 (1), 13−30.
(9) Livingstone, D. R. Contaminant-stimulated reactive oxygenspecies production and oxidative damage in aquatic organisms. Mar.Pollut. Bull. 2001, 42 (8), 656−666.(10) Valavanidis, A.; Vlahogianni, T.; Dassenakis, M.; Scoullos, M.Molecular biomarkers of oxidative stress in aquatic organisms inrelation to toxic environmental pollutants. Ecotoxicol. Environ. Saf.2006, 64 (2), 178−189.(11) van der Oost, R.; Beyer, J.; Vermeulen, N. P. E. Fishbioaccumulation and biomarkers in environmental risk assessment:A review. Environ. Toxicol. Pharmacol. 2003, 13 (2), 57−149.(12) McWilliam, R. A.; Baird, D. J. Postexposure feeding depression:A new toxicity endpoint for use in laboratory studies with Daphniamagna. Environ. Toxicol. Chem. 2002, 21 (6), 1198−1205.(13) Domene, X.; Natal-da-Luz, T.; Alcaniz, J. M.; Andres, P.; Sousa,J. P. Feeding inhibition in the soil collembolan Folsomia candida as anendpoint for the estimation of organic waste ecotoxicity. Environ.Toxicol. Chem. 2007, 26 (7), 1538−1544.(14) Barata, C.; Alanon, P.; Gutierrez-Alonso, S.; Riva, M. C.;Fernandez, C.; Tarazona, J. V. A Daphnia magna feeding bioassay as acost effective and ecological relevant sublethal toxicity test forEnvironmental Risk Assessment of toxic effluents. Sci. Total Environ.2008, 405 (1−3), 78−86.(15) Hart, R. W.; Keenan, K.; Turturro, A.; Abdo, K. M.; Leakey, J.;Lyncook, B. Caloric restriction and toxicity. Fundam. Appl. Toxicol.1995, 25 (2), 184−195.(16) Keenan, K. P.; Ballam, G. C.; Soper, K. A.; Laroque, P.;Coleman, J. B.; Dixit, R. Diet, caloric restriction, and the rodentbioassay. Toxicol. Sci. 1999, 52 (2), 24−34.(17) Pugh, T. D.; Klopp, R. G.; Weindruch, R. Controlling caloricconsumption: Protocols for rodents and rhesus monkeys. Neurobiol.Aging 1999, 20 (2), 157−165.(18) Ninan, I.; Kulkarni, S. K. Dopamine receptor sensitive effect ofdizocilpine on feeding behaviour. Brain Res. 1998, 812 (1−2), 157−163.(19) Videla, L. A.; Barros, S. B. M.; Junqueira, V. B. C. Lindane-induced liver oxidative stress. Free Radical Biol. Med. 1990, 9 (2), 169−179.(20) Gliwicz, M. Z.; Sieniawska, A. Filtering activity of Daphnia inlow concentrations of a pesticide. Limnol. Oceanogr. 1986, 31 (5),1132−1138.(21) Hartgers, E. M.; Heugens, E. H. W.; Deneer, J. W. Effect oflindane on the clearance rate of Daphnia magna. Arch. Environ.Contam. Toxicol. 1999, 36 (4), 399−404.(22) Vehmaa, A.; Hogfors, H.; Gorokhova, E.; Brutemark, A.;Holmborn, T.; Engstrom-Ost, J. Projected marine climate change:Effects on copepod oxidative status and reproduction. Ecol. Evol. 2013,3 (13), 4548−4557.(23) Barata, C.; Varo, I.; Navarro, J. C.; Arun, S.; Porte, C.Antioxidant enzyme activities and lipid peroxidation in the freshwatercladoceran Daphnia magna exposed to redox cycling compounds.Comp. Biochem. Physiol., Part C: Toxicol. Pharmacol. 2005, 140 (2),175−186.(24) Nakki, R.; Nickolenko, J.; Chang, J. M.; Sagar, S. M.; Sharp, F.R. Haloperidol prevents ketamine- and phencyclidine-induced HSP70protein expression but not microglial activation. Exp. Neurol. 1996,137 (2), 234−241.(25) Saradha, B.; Vaithinathan, S.; Mathur, P. P. Lindane alters thelevels of HSP70 and clusterin in adult rat testis. Toxicology 2008, 243(1−2), 116−123.(26) Barata, C.; Baird, D. J.; Minarro, A.; Soares, A. Do genotyperesponses always converge from lethal to nonlethal toxicant exposurelevels? Hypothesis tested using clones of Daphnia magna straus.Environ. Toxicol. Chem. 2000, 19 (9), 2314−2322.(27) Smith, P. K.; Krohn, R. I.; Hermanson, G. T.; Mallia, A. K.;Gartner, F. H.; Provenzano, M. D.; Fujimoto, E. K.; Goeke, N. M.;Olson, B. J.; Klenk, D. C. Measurement of protein using bicinchonicacid. Anal. Biochem. 1985, 150 (1), 76−85.(28) Ou, B. X.; Hampsch-Woodill, M.; Prior, R. L. Development andvalidation of an improved oxygen radical absorbance capacity assay
using fluorescein as the fluorescent probe. J. Agric. Food Chem. 2001,49 (10), 4619−4626.(29) Cao, G. H.; Prior, R. L. Comparison of different analyticalmethods for assessing total antioxidant capacity of human serum. Clin.Chem. 1998, 44 (6), 1309−1315.(30) Hodges, D. M.; DeLong, J. M.; Forney, C. F.; Prange, R. K.Improving the thiobarbituric acid-reactive-substances assay forestimating lipid peroxidation in plant tissues containing anthocyaninand other interfering compounds. Planta 1999, 207 (4), 604−611.(31) Bam̊stedt, U.; Gifford, D. J.; Irigoien, X.; Atkinson, A.; Roman,M. 8 − Feeding. In ICES Zooplankton Methodology Manual; Harris, R.,Wiebe, P., Lenz, J., Skjoldal, H. R., Huntley, M., Eds.; Academic Press:London, 2000; pp 297−399.(32) Jeschke, J. M.; Kopp, M.; Tollrian, R. Consumer-food systems:Why type I functional responses are exclusive to filter feeders. Biol.Rev. 2004, 79 (2), 337−349.(33) Sarnelle, O.; Wilson, A. E. Type III functional response inDaphnia. Ecology 2008, 89 (6), 1723−1732.(34) Barton, H. A.; Andersen, M. E.; Allen, B. C. Dose-responsecharacteristics of uterine responses in rats exposed to estrogenagonists. Regul. Toxicol. Pharmacol. 1998, 28 (2), 133−149.(35) Schielzeth, H. Simple means to improve the interpretability ofregression coefficients. Methods Ecol. Evol. 2010, 1 (2), 103−113.(36) Wold, S.; Sjostrom, M.; Eriksson, L. PLS-regression: A basic toolof chemometrics. Chemom. Intell. Lab. Syst. 2001, 58 (2), 109−130.(37) Hoppe, S.; Bierhoff, H.; Cado, I.; Weber, A.; Tiebe, M.;Grummt, I.; Voit, R. AMP-activated protein kinase adapts rRNAsynthesis to cellular energy supply. Proc. Natl. Acad. Sci. U.S.A. 2009,106 (42), 17781−17786.(38) Sohal, R. S.; Ku, H. H.; Agarwal, S.; Forster, M. J.; Lal, H.Oxidative damage, mitochondrial oxidant generation and antioxidantdefense during aging and in response to food restriction in the mouse.Mech. Ageing Dev. 1994, 74 (1−2), 121−133.(39) Barrientos, A.; Marin, C.; Miro, O.; Casademont, J.; Gomez, M.;Nunes, V.; Tolosa, E.; Urbano-Marquez, A.; Cardellach, F.Biochemical and molecular effects of chronic haloperidol admin-istration on brain and muscle mitochondria of rats. J. Neurosci. Res.1998, 53 (4), 475−481.(40) Doyotte, A.; Cossu, C.; Jacquin, M. C.; Babut, M.; Vasseur, P.Antioxidant enzymes, glutathione and lipid peroxidation as relevantbiomarkers of experimental or field exposure in the gills and thedigestive gland of the freshwater bivalve Unio tumidus. Aquat. Toxicol.1997, 39 (2), 93−110.(41) Pai, B. N.; Janakiramaiah, N.; Gangadhar, B. N.; Ravindranath,V. Depletion of glutathione and enhanced lipid-peroxidation in theCSF of acute psychotic following haloperidol administration. Biol.Psychiatry 1994, 36 (7), 489−491.(42) Tanaka, K.; Kurihara, N.; Nakajima, M. Metabolism of lindanein house-flies: Metabolic desaturation, dehydrogenation and dehydro-chlorination, and conjugation with glutathione. Pestic. Biochem. Physiol.1976, 6 (4), 392−399.(43) Anguiano, O. L.; de Castro, A. C.; de D’Angelo, A. M. P. Therole of glutathion conjugation in the regulation of early toad embryos’tolerance to pesticides. Comp. Biochem. Physiol., Part C: Toxicol.Pharmacol. 2001, 128 (1), 35−43.(44) Kailasam, M.; Kaneko, G.; Oo, A. K. S.; Ozaki, Y.;Thirunavukkarasu, A. R.; Watabe, S. Effects of calorie restriction onthe expression of manganese superoxide dismutase and catalase underoxidative stress conditions in the rotifer Brachionus plicatilis. Fish. Sci.2011, 77 (3), 403−409.(45) Rousseeuw, P. J.; Ruts, I.; Tukey, J. W. The bagplot: A bivariateboxplot. Am. Stat. 1999, 53 (4), 382−387.
