ARTICLE pubs.acs.org/est
Differential Effects in Mammalian Cells Induced by Chemical Mixtures in Environmental Biota As Profiled Using Infrared Spectroscopy Valon Llabjani,† John D. Crosse,‡ Abdullah A. Ahmadzai,† Imran I. Patel,† Weiyi Pang,† Julio Trevisan,†,§ Kevin C. Jones,† Richard F. Shore,‡ and Francis L. Martin†,* †
Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Bailrigg, Lancaster LA1 4YQ, U.K. NERC Centre for Ecology and Hydrology, Lancaster Environment Centre, Library Avenue, Bailrigg, Lancaster LA1 4AP, U.K. § Department of Communication Systems, Lancaster University, Lancaster LA1 4WA, U.K. ‡
bS Supporting Information ABSTRACT: Environmental contaminants accumulate in many organisms and induce a number of adverse effects. As contaminants mostly occur in the environment as mixtures, it remains to be fully understood which chemical interactions induce the most important toxic responses. In this study, we set out to determine the effects of chemical contaminants extracted from Northern Gannet (Morus bassanus) eggs (collected from the UK coast from three sampling years (1987, 1990, and 1992) on cell cultures using infrared (IR) spectroscopy with computational data handling approaches. Gannet extracts were chemically analyzed for different contaminants, and MCF-7 cell lines were treated for 24 h in a dose-related manner with individual-year extracts varying in their polybrominated diphenyl ether (PBDE) to polychlorinated biphenyl (PCB) ratios. Treated cellular material was then fixed and interrogated using attenuated total reflection Fourier-transform IR (ATR-FTIR) spectroscopy; resultant IR spectra were computationally analyzed to derive dose-response relationships and to identify biomarkers associated with each contaminant mixture treatment. The results show distinct biomarkers of effect are related to each contamination scenario, with an inverse relationship with dose observed. This study suggests that specific contaminant mixtures induce cellular alterations in the DNA/RNA spectral region that are most pronounced at low doses. It also suggests alterations in the “biochemical-cell fingerprint” of IR spectra can be indicative of mixture exposures.
’ INTRODUCTION Environmental contaminants of concern such as persistent organic pollutants (POPs) include the legacy organochlorine (OC) substances dichloro-diphenyl-trichloroethanes (DDTs), polychlorinated biphenyls (PCBs), and emerging polybrominated diphenyl ether (PBDE) flame retardants.1 Although the production of DDT and PCBs was banned in most countries during the 1970s and exposure levels in the environment have decreased, these compounds are still found all over the world, and there is still a concern that these chemicals or their metabolites, combine with other substances and induce adverse effects in humans and wildlife.2 4 PBDE production started in large quantities during 1980s as a result of fire regulations. Production of some brominated diphenyl ether (BDE) congener mixtures (penta-BDE and octa-BDE) ceased in the European Union and America by 2004 due to the concerns over toxic effects similar to those associated with PCBs.5 Decabromodiphenyl ether (decaBDE) mixtures has been regulated in some states in the U.S. but is currently being used without restriction for non-electronic/electrical uses in the E.U. region.6 Many of these contaminants bioaccumulate in biota due to their lipophilic r 2011 American Chemical Society
nature and reach their highest concentrations in high trophic levels species.7 Predatory birds are good bioindicators of environmental contamination because they are at the top of the food chain, accumulate a wide range of contaminants, and are susceptible to the effects of pollution.8,9 Birds’ eggs are a favorable matrix for analyzing contaminant concentrations as they are easily collected and reflect local pollution levels at the time of laying.10 12 POPs, individually or in combination, induce various adverse effects in most species, including mammals, birds, reptiles, and amphibians;13 15 they are mainly thought to alter the endocrine system, but immunosuppressive, genotoxic, and neurological effects have also been observed.16 18 POPs may disrupt the endocrine system by binding to estrogen, androgen, or thyroid receptors and mimic the function of that hormone,19 as well as by altering hormone metabolism via binding to the aryl hydrocarbon Received: July 25, 2011 Accepted: October 31, 2011 Revised: October 31, 2011 Published: October 31, 2011 10706
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Environmental Science & Technology receptor (AhR) and activating the cytochrome P450 family of enzymes (e.g., CYP1A1 and CYP1B1).20 The AhR complex is found in most mammals, birds, reptiles, amphibians, fish, and invertebrates,21 and its activation is viewed as a critical step required for toxic substances such as dioxin (2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) to induce biological effects.22 In vitro cell cultures possessing AhR activity have been used to predict the toxicity of newly emerging chemical contaminants, and explain how toxic substances impinge on different species. For instance, it was shown that PBDE congeners produce a similar rank order of relative potencies (REPs) to AhR in cells of human, rat, chick and rainbow trout, when assessed by the EROD (ethoxyresorufin-O-deethylase) assay.23 Similarly, PCB-induced hormetic effects (estrogenic and antiestrogenic) have been observed in vitro in cell lines (MCF-7 cells and primary cultures of rainbow trout),24 as well as in in vivo rat studies.25 Because chemical-induced characteristics in vitro reflect some processes that occur in vivo, cell culture techniques have been successfully applied to toxicity testing and provide some mechanistic understanding of chemical actions.26 MCF-7 cells have been used in many studies for chemical testing because they are well established, hormonally responsive and metabolically active.27 Laboratory experiments showing biological responses to toxic substances based on adverse effects induced by high concentrations may not reflect how a biological organism responds to low concentrations.28 We have previously used infrared (IR) spectroscopy as a novel tool to examine how MCF-7 cells respond to environmental levels (10 12 M) of chemical pollutants individually or in a binary mixture, and to fingerprint specific exposure patterns.29 32 IR spectroscopy works on the basis that biomolecules absorb mid-IR (λ = 2 25 μm), and when a biological sample is interrogated a signature fingerprint in the form of an absorbance spectrum correlating with structure and function can be derived. Different biomolecules absorb different regions of IR and a biochemical-cell fingerprint region (1800 900 cm 1) can be approximately divided into regions associated mostly with lipids (1800 1700 cm 1), proteins (1690 1480 cm 1) and DNA/RNA (1425 900 cm1).33 In particular, secondary structure protein conformations are detected at 1650 cm 1 (Amide I), 1550 cm 1 (Amide II) or 1250 cm 1 (Amide III), DNA/RNA alterations at 1225 cm 1 (asymmetric phosphate; νasPO2 ) and 1080 cm 1 (symmetric phosphate; νsPO2 ), peaks for glycogen content (1030 cm 1), and protein phosphorylation (940 cm 1).33 Interrogation of cellular material with attenuated total reflection Fourier-transform IR (ATR-FTIR) spectroscopy leads to the generation of large data sets with hundreds of variables that are best analyzed with a multivariate analysis technique such as linear discriminant analysis (LDA).34 In this study, we set out to examine biochemical alterations induced by real-world environmental contaminant scenarios in MCF-7 cells using IR spectroscopy coupled with multivariate analysis. Particularly, our aim was to investigate if different concentration ratios of environmentally relevant contaminants (PCB-to-BDE) produce distinct effects that can be detected using ATR-FTIR spectroscopy combined with LDA. To investigate this, Northern gannet (Morus bassanus) eggs from different years that varied in their BDE-to-PCB ratio were chemically extracted and MCF-7 cells were treated with these extracts in a dose-related manner. In addition, we compared the biochemical alterations induced by these chemical mixtures with those observed following treatment with BDE and PCB analytical standard treatment, in order to determine whether effects associated with gannet egg extracts are driven by these compounds.
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’ EXPERIMENTAL SECTION Cell Culture. The human MCF-7 cell line was grown in Dulbecco’s modified essential medium supplemented with 10% heat-inactivated fetal calf serum (FCS), penicillin (100 U/mL) and streptomycin (100 μg/mL). Cells were grown in 5% CO2 in air at 37°C in a humidified atmosphere and were disaggregated with trypsin (0.05%)/EDTA (0.02%) solution before incorporation into experiments. Cell culture consumables were obtained from Invitrogen Life Technologies (Paisley, UK), unless otherwise stated. Extracts and Analysis. Fresh gannet eggs were taken from nests in each sampling year (1987, 1990, and 1992) at a Scottish colony Ailsa Craig (OS Grid Reference NX019997) by licensed egg collectors. The egg contents were homogenized and stored in glass jars at 20°C until use. A subgroup of five eggs from each sampling year for each colony was selected and analyzed for PBDE, PCB, mercury (Hg), DDE, and diedrin (HEOD) concentrations. The analytical methods for OCs, PCBs, and Hg were conducted as previously described.35 For PBDEs briefly, a 0.5 g subsample of each egg homogenate was thawed, weighed accurately, dried with anhydrous sodium sulfate and sochlet-extracted for 16 h in dichloromethane. Lipid content was determined gravimetrically and samples were cleaned by using an alumina glass column packed with 15 g acidified silica eluted with 300 mL hexane and then by gel permeation chromatography, before being evaporated under nitrogen. The extract was analyzed by gas chromatography mass spectrometry (GC-MS, ThermoFinnigan Trace) fitted with a ThermoQuest AS2000 autosampler and using a 30 m CPSIL-8 CB pesticide column (0.25 mm diameter, 0.12 μm internal diameter), as previously described.36 Stock solutions of gannet egg extracts in hexane were solvent exchanged, first in ethanol and then dimethyl sulfoxide (DMSO) to minimize any sample loss (no fluctuation of PBDE concentrations were apparent after solvent exchange). Serial dilutions in DMSO were added to cell incubates. The maximum DMSO concentration per incubate was 1% (v/v). Egg extract controls (EC) consisted of solvent only and were run at the same time as egg extracts and DMSO controls consisting of the same amount of DMSO as in treatments. Cell Treatments and ATR-FTIR Spectroscopy. Egg extracts from these years (1987, 1990, and 1992) were chosen to treat cell cultures because they varied in their BDE-to-PCB concentration ratios. The years selected were defined based on their BDE-toPCB levels: 1987 as medium in BDE and medium in PCB (MM); 1990 as low in BDE and high in PCB (LH); and 1992 as high in BDE and low in PCB (HL). Five chicken egg (CH) extracts (no BDE and PCB were detected) were used as controls. Mean concentrations of BDE and PCBs for MM extracts were 18.26 and 1260 ng/g Wwt (1:68), whereas in LH extracts they were 11.96 and 2280 ng/g Wwt (1:190) and for HL extract were 47.33 and 577.59 ng/g Wwt (1:12), respectively. Chemical concentrations for individual PBDE congeners, Hg, DDE, and HEOD are shown in Supporting Information (SI) Tables S1 and S2. MCF-7 cells were disaggregated, resuspended in complete medium and then seeded in T25 flasks, whereupon they were concentrated in S-phase (grown for 24 h) prior to treatment with or without egg extracts for a further 24 h. Five eggs per year were analyzed. MCF-7 cells were treated separately in triplicate with each individual egg extract in a dose-related manner, at 5 mg, 10 mg, or 25 mg equivalents, as well as with DMSO and EC. Following treatment, cells were disaggregated and the cell 10707
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Environmental Science & Technology suspensions were immediately fixed with 70% ethanol and stored at 4°C until analyzed. Cellular material was then applied to IRreflective “Low E” glass slides (Kevley Technologies, Chesterland, OH), allowed to air-dry and then desiccated. IR spectra were obtained using a Bruker Vector 27 FTIR spectrometer with Helios ATR attachment containing a diamond crystal (Bruker Optics Ltd., Coventry, U.K.). For each experimental condition (i.e., each slide), 10 spectra were acquired (32 coadditions, ≈3.85 cm 1 wavenumber spacing, 2.2 kHz mirror speed). The ATR crystal was cleaned with sodium dodecyl sulfate (SDS; Sigma Chemical Co.) and a new background spectrum was collected prior to analysis of a new sample. Computational Analysis for Chemical Data. Principal component analysis (PCA) was employed in order to determine if the three selected sampling years differed in their chemical profiles. The data were first log-transformed and then PCA was carried out using total BDE, PCB, DDT, HEOD, and Hg chemical concentrations (ng/g Wwt) as input variables from each year (n = 15, 5 samples per year). In PCA, each variable (e.g., chemical) becomes a single point in n-dimensional space and, using PCs 1, 2, and 3 as coordinates, the data were analyzed for clustering. Spectra Processing and Multivariate Data Analysis. Raw IR spectra obtained from interrogated samples were preprocessed prior to computational analysis. Spectra were cut at the “biochemical-cell fingerprint” region (1800 900 cm 1), baseline-corrected (rubberband) using OPUS software and normalized to the Amide I peak (1650 cm 1). Spectra from five individual extract treatments were combined into separate groups (MM, LH, HL, or CH) and each treatment contained: n = 150 spectra, 10 spectra per experiment slide triplicate experiments 5 extracts per group. Variables in spectral data were reduced from 235 to 117 absorption intensities at different wavenumbers by averaging every two wavenumbers in order to ensure that the rate between number of spectra and number of variables is >5.33 Following on, LDA was applied. LDA is a linear transformation and thus generates new variables as linear combinations (i.e., weighted sums) of the original absorption intensities. Each new variable is called a “factor”. The weights for each factor are represented by a vector called a “loadings vector”. The loadings vectors are successive orthogonal solutions to the problem stated as “maximize the between-class variance over the within-class variance of the factor”.37 Each scalar value of each factor is called a “score”, which may be visualized through 1-, 2-, or 3-dimensional scatter plots—called “scores plots”—where clusters may be identified. LDA allows for a visualization called “cluster vectors plots” which may be used to identify biomarkers (i.e., wavenumbers) associated to specific treatment conditions. A cluster vector is a geometric construction whereby a vector is drawn from the center of a reference class (i.e., the “Control” group) to the center of a treatment class in the vector space spanned by the LDA loadings vectors.30 Thus, each cluster vector is a linear combination of the loadings vectors and it can be plotted as y-values having the wavenumbers as x-values. We applied a peak detection algorithm to identify the ten most prominent peaks from each cluster vector and plotted the location of the detected peaks along the wavenumber line using marker symbols whose size are proportional to the height of their corresponding peaks. Absolute values were used to measure the height of the peaks from cluster vector plots in order include both the negative and positive values. Repeated-measures one-way analysis of variance (ANOVA) with Dunnett’s post hoc tests were used to examine whether the
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Figure 1. Scores plots from principal component analysis (PCA) of chemical data using concentrations (ng/g Wwt) of contaminants in gannet eggs from different years collected from Ailsa Craig as input variables (n = 15, 5 per year); MM (Medium BDE, Medium PCB), LH (Low BDE, High PCB), and HL (High BDE, Low PCB). Principal components 1, 2, and 3 account for 92.7%, 6.4%, and 0.75% of variance, respectively.
mixture-induced effects observed in LD1 space differed significantly between treated vs control cell populations; there was no need to transform data to meet the underlying assumptions of homogeneity of variance between groups and normality of residuals. Apart from baseline correction (conducted using OPUS software) and ANOVA (conducted using GraphPad Prism), all data handling and visualization was performed in MATLAB r2009b using our in-house IRTools toolbox, which is freely available for download at http://biophotonics.lancs.ac.uk/software/irtools.
’ RESULTS AND DISCUSSION PCA using chemical contaminant concentrations as inputting variables showed a good separation in chemical concentrations between years, indicating differences in their chemical mixture content (Figure 1). When LDA was carried out for the MCF-7 cells treated with gannet egg extracts on the spectral data grouped by year with each year containing all the treatment concentrations (combination of 5 mg, 10 mg, and 25 mg equivalents), there was good separation between years and control cell populations [DMSO, EC or CH (Figure 2A)]. Separation of data based on different mg-equivalent treatments indicated that segregation between the controls and years was greater. When the effects of 5 mg equivalent treatments were compared to the controls there was a clear segregation between 5 mg equivalents treatments and all control cell population including DMSO (Figure 2B), CH (Figure 2C) and EC (Figure 2D). Similarly, good separation from controls was also apparent when MCF-7 cells were treated with 10 or 25 mg equivalent extracts (see SI Figures S1 and S2). Data analysis indicated that lowest-dose treatment (5 mg equivalent extracts) produced greater effects on MCF-7 cells compared to 10 or 25 mg equivalent extracts in all treatment years (Figure 4 for MM extracts; SI Figures S3 and S4 for LH and HL extracts, respectively); hence, we examined the 5 mg equivalents to compare the effects on cells between different years. The effects of 5 mg equivalent MM, LH or HL extracts were compared by measuring the distance in LD1 space from the mean of CH control extracts (Figure 3; for 10 or 25 mg equivalents see SI Figure S5 and S6, respectively). Distance in LDA enables one to determine which treatment produces the most alterations in overall cellular structures compared to the 10708
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Figure 2. LDA scores plots of infrared (IR) spectra derived from MCF-7 cells treated with gannet egg extracts compared to control cell populations. (A) Effects of all concentrations combined vs control cell populations. IR spectra from different concentration treatments were combined based on class and each class contained the following number of spectra; for MM (Medium BDE, Medium PCB), LH (Low BDE, High PCB), and HL (High BDE, Low PCB), and chicken egg extract (CH) [n = 450 spectra (10 spectra per experiment slide triplicate experiments 5 extracts per year 3 concentrations)] and for corresponding controls combined DMSO or EC (extract control) (n = 600 spectra); (B) Effects of 5 mg equivalent extracts (n = 150 spectra, 10 spectra per experiment slide triplicate experiments 5 extracts per year) vs DMSO combined (n = 600 spectra); (C) EC combined (n = 600 spectra); or, (D) 5 mg equivalent CH extracts (n = 150 spectra, 10 spectra per experiment slide triplicate experiments 5 extracts).
control egg matrix, and cluster vectors plots identify which biomolecules are altered with different treatments.30 The highest distance from control in 5 mg equivalent extracts was observed for MM extracts, followed by LH and HL extracts, and ANOVA showed that the effects induced by these contaminants resulted in spectral alterations in treated-cell populations that were significantly different (P e0.01) compared to those exposed to CH control extracts. Cluster vector plots (Figure 3B) showed that all of the mixtures induced their main effects in the DNA/ RNA region (1425 900 cm 1), but some protein conformational changes were also evident. MM extracts in general produced the most pronounced effects compared to LH or HL extracts in all spectral regions. Specific alterations associated with MM extracts included secondary protein structure conformation alterations in Amide I and Amide II (≈1650 and ≈1550 cm 1), glycogen content (≈1000 cm 1), protein phosphorylation (≈940 cm 1) and, in the νasPO2 and νsPO2 (≈1225 cm 1 and ≈1080 cm 1). LH effects were associated with Amide II (≈1550 cm 1), CdO stretching of proteins (≈1400 cm 1), Amide III (≈1280 cm 1), carbohydrate (≈1180 cm 1), νasPO2 (≈1225 cm 1), and glycogen content (≈1025 cm 1). Less distinct biochemical changes were induced by HL extracts, although alterations in 1400 cm 1 (proteins), carbohydrate (≈1180 cm1), νsPO2 (≈1080 cm 1) and glycogen content (≈1030 cm 1) were observed. Given that MM extracts induced the most pronounced effects on MCF-7 cultures, we tested how cells responded with this
extract in a dose response manner. An inverse dose-response relationship was apparent that gave rise to spectral alterations that were significant at all concentrations (P e0.01), where the highest effect was observed when cells were treated with 5 mg equivalent extracts and the lowest effect was seen following treatment with 25 mg equivalent extract (Figure 4A). Examination of differences in signatures (Figure 4B) associated with each dose (5 mg, 10 mg, or 25 mg equivalent) also showed that all doses induced their main alterations in the DNA/RNA region (1425 900 cm 1); however, the lowest concentration produced no alterations in the lipid or protein region (1800 1480 cm 1) and the bands associated with νsPO2 (1080 cm 1) are predominantly altered following exposure to 5 mg equivalent extracts but not with 10 or 25 mg equivalent extracts. The results suggest that these chemical mixtures produced effects in cells by genotoxic-associated mechanisms that were most pronounced with low doses. The end points observed in the current study we believe, rather than reflecting the amount of induced damage, indicate the cellular responses following contaminant-mediated effects at environmentally relevant concentrations. Environmentally relevant concentrations of POP mixtures can induce negative effects in hightrophic-level avian species; for instance, glaucous gulls (Larus hyperboreus) breeding in highly OC-polluted sites have been shown to have lower levels of thyroid hormones compared to birds from less exposed colonies.38 However, adverse effects may not necessarily be associated with the highest POP 10709
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Figure 3. LDA comparing the effects of gannet eggs extracts between different years. (A) LD1 scores plot following LDA of infrared (IR) spectra derived from MCF-7 cells treated with 5 mg equivalent gannet egg extracts; MM (Medium BDE, Medium PCB), LH (Low BDE, High PCB), and HL (High BDE, Low PCB), and 5 mg equivalent CH (chicken) egg extracts (n = 150 spectra per class, 10 spectra per experiment slide triplicate experiments 5 extracts per year); and, (B) Corresponding cluster vector plots showing wavenumbers discriminating classes. The sizes of marker symbols in cluster vector plots are proportional to the height of their corresponding peaks. The dashed line represents a typical IR spectrum of the biochemical-fingerprint region (1800 900 cm 1). ANOVA with Dunnett’s post hoc test was used to test significance between contaminant-exposed vs cell populations treated with CH extracts (**, P e0.01).
concentration. A study comparing sex hormones (testosterone and 17β-estradiol) levels in glaucous gull from three contaminated sites that varied in their POP concentrations showed an association between pollution and alteration of hormone levels, but only at the least polluted site.39 Whereas PCB-induced effects such as endocrine and immune disruptions have been well documented in predatory birds such as the American kestrel (Falco sparverius),18,40,41 it has also been shown that exposure of these species to PBDEs induced endocrine-related effects, egg thinning and histopathological end points with diminished reproductive success.42,43 Given that organisms are continuously and variously exposed to low levels of different agents, interactions between chemical mixtures that induce adverse effects are likely to be complex and elusive. In the current study, the choice of eggs was based on existing knowledge of PCB and PBDE concentrations. However, gannets are exposed to a mixture of chemical pollutants and it is difficult to identify which compounds in the egg extracts are responsible for biochemical alterations noted in MCF-7 cells. In previous studies, we treated MCF-7 cells with endocrine active (e.g., 17βestradiol or lindane) and DNA-reactive substances [e.g., benzo[a]pyrene (B[a]P) or 2-amino-1-methyl-6-phenylimidazo[4,5b]pyridine (PHIP)] and used ATR-FTIR spectroscopy to fingerprint these specific exposures, as well as obtain biomarkers
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Figure 4. Dose-response effects of MM (Medium BDE, Medium PCB) gannet egg extracts on MCF-7 cells. (A) LD1 scores plot following LDA of infrared (IR) spectra derived from MCF-7 cells treated with egg extracts (n = 150 spectra per treatment, 10 spectra per experiment slide triplicate experiments 5 extracts per treatment group) and EC (extract control) combined (n = 600 spectra); and (B) Corresponding cluster vector plots showing wavenumbers responsible for discriminating of discriminating effects at doses tested. The sizes of marker symbols in cluster vector plots are proportional to the height of their corresponding peaks. The dashed line represents a typical IR spectrum of the biochemical-fingerprint region (1800 900 cm 1). ANOVA with Dunnett’s post hoc test was used to test significance between contaminantexposed vs EC-treated cell populations (**, P e0.01).
associated with technical mixtures of PCBs and PBDEs.29 32 We showed that BDE and PCB congeners, individually or in combination, induce alterations of cellular structures that are most apparent at low doses (10 12 M to 10 9 M). In particular an inverse dose-response relationship was observed with BDE-47, which is one of the most abundant congeners in environment.44 When we compared the biomarkers of effects observed in the current study with those noted in previous studies, we can identify some similarity in the fingerprint to that of PCB- and BDE-induced effects, as well as some DNA/RNA effects similar to B[a]P treatment. However, most of the effects observed in the present study are distinct and mainly found in the DNA/RNA region, indicating an effect that is mainly driven by genotoxic-associated mechanisms. In particular, it is interesting to note that these mixtures alter the lipid or Amide I regions (1800 1650 cm 1) minimally, and they induce their most pronounced effects in the DNA/RNA region (1400 900 cm 1). These results indicate that effects are likely to be driven via a specific combination of contaminants rather than one chemical compound or constituent present at the highest level. This response is clearest when MCF-7 cells are treated with MM extracts where it is evident that the lowest concentration gives rise to the largest effect. In this study, ATR-FTIR spectroscopy was employed to identify if real world contamination scenarios induce cellular alterations in 10710
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Environmental Science & Technology MCF-7 cells and to obtain biomarkers of effect associated with representative chemical mixtures that may be found in the environment. We showed that ATR-FTIR spectroscopy distinguished effects associated with different contaminant mixtures and fingerprinted real environmental pollution scenarios. Comparison of biomarkers previously identified using the same techniques showed that there may be some contribution of BDEs and PCBs to total observed effects. However, chemical mixtures in this study seem to produce “new” signatures of effects, most apparent at low doses, and of a genotoxic nature. This may be as a result of specific combination-driven effects of known contaminants or some uncharacterized pollution. Whether these mixtures are able to induce such effects in vivo remains to be validated and stresses that there is a need of future monitoring of chemical pollutants and their effects in predatory birds.
’ ASSOCIATED CONTENT
bS
Supporting Information. Contaminant concentrations and additional dose-related effects of gannet egg extracts from Ailsa Craig, Scotland. This material is available free of charge via the Internet at http://pubs.acs.org.
’ AUTHOR INFORMATION Corresponding Author
*Phone: +44 1524 510206; e-mail:
[email protected].
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