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Jun 12, 2014 - located in the Huelva province (SW Spain). Mus spretus mice attain a high population in DNP and has been used as a bioindicator in many...
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Use of Metallomics and Metabolomics to Assess Metal Pollution in Doñana National Park (SW Spain) M. A. García-Sevillano,† T. García-Barrera,*,† F. Navarro,‡ N. Abril,§ C. Pueyo,§ J. López-Barea,§ and J. L. Gómez-Ariza*,† †

Department of Chemistry and Materials Science, Experimental Sciences Faculty, Research Center on Health and Environment (CYSMA), International Campus of Excellence on Agrofood (CEIA3), Huelva University, El Carmen Campus, 21007 Huelva, Spain ‡ Department of Environmental Biology and Public Health, Cell Biology Area, Experimental Sciences Faculty, Huelva University, El Carmen Campus, 21007 Huelva, Spain § Department of Biochemistry and Molecular Biology, International Campus of Excellence on Agrofood (CEIA3), University of Córdoba, Rabanales Campus, 14071 Córdoba, Spain S Supporting Information *

ABSTRACT: Monitoring organism exposure to heavy metals has acquired increased importance in the last decades. The mouse Mus spretus has been used to assess the biological response to contaminants in the relevant ecological area of Doñana National Park (DNP) and surrounding areas (SW Spain), where many migrating birds land for breeding and feeding every year. A metallomics approach, based on the characterization of metal biomolecules using size exclusion chromatography coupled with inductively coupled plasma-mass spectrometry (SEC-ICP-MS) and a metabolomics approach based on direct infusion to a mass spectrometer (DI-ESI-QTOF-MS) followed by a partial linear square-discriminant analysis (PLS-DA), were used to compare the biological responses of M. spretus living in three areas of DNP (the reference) and surrounding areas (El Partido and El Matochal). The activities of key antioxidant enzymes, such as Cu/Zn-SOD, Mn-SOD, CAT, GR, and guaiacol peroxidase, were also determined in connection with environmental contamination issues. The results show differences caused by the presence of metals in the ecosystem that affected to the levels of metals and metalloproteins, such as MT, Cu/Zn-SOD, or MnCA, the breakdown of membrane phospholipids, perturbations in metabolic pathways, related to energy metabolism, and oxidative stress.

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INTRODUCTION

analysis of M. spretus changes in the expression of biomolecules (genes, proteins, or metabolites) due to pollution.8−12 Doñana National Park (DNP) is a 50 000 Ha wildlife reserve located in the Huelva province (SW Spain). Mus spretus mice attain a high population in DNP and has been used as a bioindicator in many studies5,8,9,13,14 because of its ecological importance.15 Yet, this area is threatened by adjacent agricultural, mining, and industrial activities that are responsible for the presence of metal species in its surroundings.5,10,11,13,15−19 In 1998, a 360 Ha tailings dam of the Aznalcóllar pyrite mine 60 km North of DNP collapsed, releasing 4 Hm3 of acidic water and 2 Hm3 of mud into Guadiamar stream, a tributary of the Guadalquivir River that feeds the Doñana marshland. Consequently, the high toxic metal content of this mud threatened DNP and the Guadalquivir Estuary.15

Natural and anthropogenic activities may increase contaminant levels in terrestrial and aquatic ecosystems. Environmental monitoring is conventionally performed using a chemical analysis of toxic elements (e.g., Cd, Cr, As, Pb, and Hg) and their chemical species, organic contaminants, emerging pollutants, and recently, nanoparticles. A more interesting approach to assess environmental pollution is to use sentinel organisms (bioindicators), such as mice, in terrestrial ecosystems1−4 because they can provide useful information for making a risk assessment of the pollutants to humans. In addition, free-living organisms can reflect the effects of the contaminants on metabolism and homeostasis using stress-related biomolecules (biomarkers), such as metalloproteins,5 antioxidative enzymes,6 and metabolites7 The free-living mouse Mus spretus has proven to be an excellent bioindicator since it is a nonprotected species, highly prolific and relatively easy to capture. Additionally, its phylogenetic proximity to the fully sequenced laboratory mouse Mus musculus,8 allows the use of M. musculus databases for the © 2014 American Chemical Society

Received: Revised: Accepted: Published: 7747

January 6, 2014 June 11, 2014 June 12, 2014 June 12, 2014 dx.doi.org/10.1021/es4057938 | Environ. Sci. Technol. 2014, 48, 7747−7755

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Because metal-binding biomolecules represent a substantial part of metabolism-involved molecules, the presence of a metal cofactor in a protein can help trace metalloproteins and metallometabolites overexpression or inhibition in living organisms triggered by contamination.22−29 Metallomics uses metals or metalloids as heteroatomic markers or tags to track these molecules in complex biological matrices, provides a good alternative to deep insight into the fate of elements in exposed organisms, and gives information about metals trafficking, interactions and homeostasis.5 In metallomic approaches, the use of high sensitivity and multielemental atomic detectors, mainly ICP-MS,5 generally coupled to a chromatographic module (in single or multidimensional arrangements), and mass spectrometry for parallel biomolecule identification in an integrated workflow is fundamental.20 Environmental metabolomics is an emerging field involving the application of metabolomics to characterize the interactions of living organisms with their environment. This information is of great value for several issues, such as the risk assessment of chemicals in the environment, the study of the mode of action (MOA) of toxicants and the discovery of indicators for the health of animals. In metabolomics, we study molecules with a molecular mass less than 1000 Da that are usually intermediate metabolites and end products of cellular functions and whose levels can be considered to be the response of biological systems to environmental or genetic manipulation.21 Metabolomics has previously been used for environmental studies22 because this multiparametric approach can determine the metabolic response to chemical exposure. MS and nuclear magnetic resonance (NMR) spectroscopy are the major analytical tools used in metabolomics studies.23,24 Metal-induced toxicity and its immunological effects are well described in the literature.25,26 Metals modulate gene expression by interfering in signal transduction pathways with key roles in cell growth and development.27 One of the major mechanisms behind metal toxicity has been attributed to oxidative stress.28 The generation of free radicals in living systems is closely linked with the participation of redox-active metals, such as iron, copper, chromium, and cobalt,29,30 which may undergo cycling reactions involving the transfer of electrons between metals and substrates and, therefore, playing an important role in the maintenance of metal-homeostasis.31 Metals are also involved in biological processes that entail metalloproteins (and enzymes) or metabolic pathways. Thus, in mammals, Cd is mainly bound to metallothioneins,32 inhibits carbonic anhydrase activity,33 causes lipid peroxidation and alters glutamate metabolism.34,35 Thus, the use of massive information approaches, -omics, such as metallomics and metabolomics may provide valuable information about the effects of metals on free-living organisms and help to identify useful molecular biomarkers for environmental biomonitoring. In the present work, M. spretus mice were used to assess mammalian responses to the contaminants present in DNP and its surroundings. A metallomics approach, based on SEC-ICPMS, combined with a metabolomic study with DI-ESI-QTOFMS followed by statistical discriminant analysis (PLS-DA), were used to compare the biological response of M. spretus from three DNP areas. The study was complemented by the analysis of oxidative stress-related enzymatic activities, including Cu/Znsuperoxide dismutase (Cu/Zn-SOD), Mn-superoxide dismutase (Mn-SOD), catalase (CAT), glutathione reductase (GOR), and guaiacol peroxidase (GP), in connection to the potential contamination of this area.

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EXPERIMENTAL SECTION

Standard Solutions and Reagents. Total element determination in soils, sediments and kidneys were carried out as previously described.36 The standards used for the mass calibration of analytical SEC columns (mass range 70−3 kDa, Superdex-75) were from Sigma-Aldrich (Steinheim, Germany). The mobile phase used in SEC was 20 mM ammonium acetate (Suprapure grade) from Merck (Darmstadt, Germany) prepared daily with ultrapure water (18 MΩcm) from a Milli-Q system (Millipore, Watford, UK). For metabolomic studies, all solvents used for sample preparation were of optimal quality grade for mass spectrometry. Methanol and chloroform were from Fisher Chemical (Geel, Belgium), while formic acid was from SigmaAldrich (Steinheim, Germany). Instrumentation. Trace metals and metal-bound biomolecules were analyzed with an inductively coupled plasma mass spectrometer (ICP-MS) Thermo XSeries2 (Thermo Scientific, Bremen, Germany) equipped with a collision cell. Chromatographic separations were made using a HPLC pump Agilent Model 1100 (Agilent, Wilmington, DE, USA) as the delivery system. A quartz cyclonic spray chambers model ESI (Omaha, USA) and a Teflon microflow nebulizer model ESI (Omaha, USA) were used in the HPLC-ICP-MS coupling. The operating conditions are shown in Supporting Information Table 1. The metabolomics experiments were performed in a mass spectrometer QSTAR XL Hybrid system (Applied Biosystems, Foster City, CA, USA) using an electrospray ionization (ESI) source. The parameters for the QqQ-TOF system are shown in Supporting Information Table 2. Sampling Area and Animals. Mice were collected from September−October 2011 in three DNP areas with differing metal levels (see Supporting Information Figure 1): (i) “Lucio del Palacio” (LDP, green), at the core of the Doñana Biological Reserve (DRB), is a reference area with a low a priori contamination level; (ii) “El Partido” (PAR, orange), upstream of El Partido stream, is under the influence of citrus and grape fields; and (iii) “El Matochal” (MAT, blue), close to the Guadiamar stream, is affected by rice fields. Detailed information about the pollutant presence in these sites located around Doñana and about their biological effects is reviewed in ref 37. Animals were captured with live-traps9 and taken alive to the nearest laboratory (Huelva University or Doñana), where their sex and weight were determined. Ten male mice, of 11−12 g, considered adults on the basis of body weight and color, were used per sampling site. The mice were anesthetized using isoflurane inhalation, exsanguinated using cardiac puncture, and dissected. The organs were rapidly excised, cleaned with a 0.9% (w/v) NaCl, frozen in liquid nitrogen and stored at −80 °C until being used. The investigation was approved by the Ethical Committee of the University of Huelva (Spain). Sediment and soil samples were collected using a polypropylene spatula and transferred to acid-rinsed polypropylene bottles. The samples were air-dried, ground, and sieved to select the 2 ↑ PAR ↑↑ MAT 303 2.14 ↑ PAR ↑↑ MAT 281 2.37 ↑ PAR ↑↑ MAT 130 2.21 ↑ PAR ↑↑ MAT 103 2.19 ↑ PAR ↑ MAT 105 2.51 ↑ PAR ↑ MAT mitochondrial fatty acid import for energy production by β oxidation 162 2.48 ↓ PAR ↓ MAT

glutathione glutamic acid taurine creatinine phosphatidylcholine lysophosphatidylcholine arachidonic acid oleic acid pipecolic acid choline

L-carnitine

a

effecta

VIP

acquisition mode

polar polar polar

ESI+ ESI− ESI−

polar

ESI+

polar and lipophilic polar and lipophilic lipophilic lipophilic lipophilic polar polar

ESI+ ESI+ ESI+ ESI− ESI+ ESI− ESI+

lipophilic

ESI+

Variations compared to reference mice (LDP): ↓, increasing signal intensity, ↓, decreasing signal intensity.

Table 2. Antioxidative Enzymes in Kidneys of M. spretus from DNP and Surroundingsa absolute activity in M spretus kidney LDP

PAR

MAT

enzyme

mean ± SD

mean ± SD

fold-change

mean ± SD

fold-change

catalase Mn-SOD Cu, Zn-SOD total SOD GOR peroxidases

94 ± 6.9 0.97 ± 0.27 7.9 ± 0.54 8.8 ± 0.47 20 ± 1.9 10 ± 1.1

184 ± 6.7 0.90 ± 0.24 18 ± 0.48 19 ± 0.42 25 ± 1.2 4.5 ± 0.40

1.95*** 0.93ns 2.29*** 2.14*** 1.22*** 0.44***

254 ± 8.8 2.5 ± 1.3 11 ± 2.1 14 ± 1.7 35 ± 6.0 5.7 ± 0.10

2.69*** 2.6* 1.46** 1.58*** 1.73*** 0.55***

Data show means ± SEM of some enzymatic activities assayed in animals (n = 8) collected at LPD, PAR and MAT. UNITS: ô l/min/mg protein. For SOD activities are μU SOD/mg protein. Asterisks (*) denote statistical significance compared to the LPD values (p < 0.05; all other differences are not significant). a

Metabolomic Study of M. spretus Kidneys Using DI-ESIQqQ-TOF/MS. When polar and nonpolar extracts of kidney cellfree extracts were analyzed in the positive (ESI+) and negative (ESI-) ion modes, the profiles differed in a wide spectral range (m/z 50−1000) (Figure 3). Polar extracts had many signals of different intensities at an m/z range of 50−320 in both the positive and the negative modes (Figure 3A and 3C, respectively). However, several peak clusters are also visible in the positive mode for polar metabolites in the m/z 700−900 range. In contrast, lipophilic extracts gave different profiles in the positive and negative modes (Figure 3B and 3D) because in positive mode (Figure 3B), low sensitivity signals were visible in the m/z 100−350 range and high molecular mass metabolites with very high sensitivity can be observed at m/z 700−900. However, in the negative mode, peaks with different intensities appear in the m/z range of 50 to 600 (Figure 3D). In conclusion, these results confirm the complementarity of the kidney extraction procedures and molecule ionization mode to obtain a high diversity of signals for metabolomic studies based on DIESI(±)-QTOF-MS. To discriminate between responses of the groups based on the different contamination sites, a partial least-squares discriminant analysis (PLS-DA) was carried out with the intensities of the signals of all experiments. The models built with polar and lipophilic metabolites using positive and negative mode allowed for a good classification of samples from the three studied areas of DNP and its surroundings. Supporting Information Figure 4

shows the respective score plots. To identify the variables responsible for this separation, the parameter variable influence on the projection (VIP) was used. VIP is a weighted sum of the squares of the PLS-DA analysis that indicates the importance of the variable to the whole model. VIP coefficients reflect the relative importance of each X variable for each X variate in the prediction model. VIP coefficients thus represent the importance of each X variable in fitting both the X- and Y-variates because the Y-variates are predicted from the X-variates. VIP allows us to classify the X-variables according to their explanatory power of Y. Predictors with a VIP larger than 1 are the most relevant for explaining Y. This strict criterion was set because of the large number of variables or metabolites in the mass spectra (Figure 3). A t test was performed in succession, and the variables without significant differences (p > 0.01) were eliminated. Goodness of the model was measured through the R2Y and Q2 values provided by the software (indicative of class separation and predictive power of the model, respectively). These parameters ranged from 0 to 1 and indicate the variance explained by the model for all the data analyzed (R2) and this variance in a test set by cross-validation (Q2). In particular, for all of the analyses performed, the values of R2Y (cumulative) and Q2 (cumulative) of the combined model are 0.90−0.99 and 0.8− 0.95, respectively, indicating that a combination of data sets between the groups provides the best classification and prediction. The model allows us to evaluate the effects of the elements on different studied areas. Only variables with VIP 7751

dx.doi.org/10.1021/es4057938 | Environ. Sci. Technol. 2014, 48, 7747−7755

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MS. The most interesting results were found with Mn, Cu, Zn, and Cd. Renal extracts had one Mn-traced peak of 32−35 kDa, most likely because of Mn-superoxide dismutase (Mn-SOD). Nevertheless, this metalloprotein is exclusively mitochondrial,45 and this organelle should not be disrupted by our extraction procedure. Alternatively, this Mn-peak could be due to the replacement of Zn with Mn in the active site of Zn-carbonic anhydrase to yield a Mn-substituted carbonic anhydrase with peroxidase activity and Mr = 29−54 kDa, depending on the isoforms.46 This assumption could explain the increased intensity of this peak with Mn concentrations in the kidney in the following order: MAT > PAR > LDP, also in agreement with the total Mn concentration in the soils and sediments. However, further studies should be performed to confirm this point. A 7-kDa Cu/Cd-traced peak, attributed to metallothionein(MT), was also found in kidneys from MAT site, where this element is present at the highest concentration. The Cu-MT peak was higher in PAR than in MAT animals, while the situation was reversed for the Cd-MT peak, most likely due to the higher Cd content in MAT soil and sediment. Cd has a higher affinity than Cu for MT thiols; therefore, the increased Cd levels of MAT could drive the replacement of Cu by Cd in MT. Cd and Zn-MT are induced in Mus musculus exposed to industrial dust rich in metals, confirming strong interactions between Cu−Zn−Cd.47 Another Cu-traced peak, ∼32 kDa Mr, was very intense in samples from PAR and MAT but very faint in the reference LDP site. This fraction was purified and MS-identified in a previous metallomics-based work,5 confirming that this SOD-attributed Cu-peak is an excellent oxidative-stress biomarker.5,13,19 Three Zn-traced peaks are present at the void volume (>70 kDa) and coelute with bovine serum albumin (Zn/Cu-BSA, 67 kDa) and SOD (Cu/Zn-SOD 32 kDa) standards. Their intensity was enhanced in the MAT and PAR samples. The high concentration of Zn and Cu in the surroundings of DNP could be related to the intensity of the peaks above 67 kDa in these areas, associated with standards of carrier proteins such as Zn/Cu-BSA and transferrin (Cu-Tf and Zn-Tf). Metabolomic changes analysis in these M. spretus samples might help improve our understanding of metal toxicity. Metabolomic analysis of the mouse kidney using DI-ESI-QqQTOF-MS with polar and lipophilic extracts measures the alterations in metabolic pathways promoted by toxic elements in relation to (i) antioxidative activity, (ii) membrane damage, and (iii) energy metabolism. Reduced glutathione (GSH) is the main cytosolic antioxidant that detoxifies reactive oxygen species and keeps key protein thiols reduced. GSH also binds to reactive electrophilic xenobiotics and endogenous metabolites that are later excreted. Both GSH roles decrease the glutathione pool, explaining the lower GSH content found in mice from the PAR and MAT metal-contaminated sites. A diminished GSH level should be compensated by its de novo synthesis from Lglutamate, L-cysteine, and glycine, explaining the increase in glutamate found in PAR and MAT mice. Taurine, an L-cysteinederived antioxidant also active in osmoregulation, membrane stabilization and Ca2+ signaling modulation,48,49 was also increased in mice from metal-contaminated sites. The opposite trends of taurine and GSH, already observed in M. musculus under arsenic exposure,38 could be due to higher taurine synthesis when GSH synthesis is blocked by As exposure. The simultaneous alterations of GSH, taurine, and glutamate shown by metabolomics confirm the oxidative stress caused by metal contamination.

values >2.0 were selected and used to identify altered metabolites in M. spretus kidneys by searching in a variety of open access metabolomic databases (HMDB, METLIN, MassBank, and LipidBank). Table 1 summarizes 11 clearly altered metabolites in the kidney. Their functional activities related to renal damage (creatinine), oxidative stress (glutathione, taurine, glutamic acid), membrane phospholipid degradation (choline, lyso- and phosphatidyl choline, and pipecolic, arachidonic, and oleic acids) and fatty acid mitochondrial import (L-carnitine). These results showed a remarkable complementarity of both ionization modes for polar and lipophilic metabolites (Table 1). Redox Enzymes in Kidney Extracts of M. spretus from DNP and Its Surroundings. The oxidative stress related to metal pollutants was confirmed by assessing the activity of representative antioxidative enzymes in mouse kidney homogenates. Table 2 shows that metal-exposed animals displayed clear increases in several ROS-metabolizing enzymes, including CAT, Mn-, Cu/Zn-, and total SOD, but only a moderate increase in GOR and a clear decrease in total peroxidases. The increases in several key antioxidative enzymes and the parallel rise of antioxidant capacity can be considered a defensive response to the oxidative stress promoted by the redox-active metals detected in mice collected at contaminated sites of DNP and surrounding areas.

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DISCUSSION The kidney is an important organ for the excretion/ detoxification of water-soluble metabolites, including metals and xenobiotics, because of the strong interaction between kidneys and blood.39−41 The element contents of kidneys from M. spretus living in PAR and MAT were compared with those of reference LDP mice. Essential metals, including Cu, Zn, Mn, and Fe, were very abundant in the kidneys from all mice, independently of their site of capture. In contrast, toxic elements, including Cd, As, Ni, Cr and Pb, were quite scarce, although significantly higher in PAR and, particularly, in MAT mice. This observation confirmed previous results showing that El Matochal rice-growing areas were more contaminated by metals than any other area of the DNP surroundings, probably due to the extensive use of metals as algaecides.5,6,9−13,19,36,42 The models built using total kidney metal contents allowed for the good classification of samples from the three groups, as shown by their corresponding scores plots, with animals from the reference LDP site clustered apart from PAR and MAT mice (Supporting Information Figure 4). Notice that the evaluation of VIP parameters also revealed that PAR and MAT samples are distinct from those from LDP because of their higher concentrations of Mn, Fe, Zn, Cu, As, Cd, and Pb in the kidney. The metal contents in the soils, sediments and organisms informed about their movement through the environment, accumulation and potential toxicological effects.43 Rogival et al.44 demonstrated that soil metals correlated positively to those in the diet (plants) and organs of Apodemus sylvaticus captured at five sites of a metal pollution gradient in a smelter area. In our study, a correlation was demonstrated between metals in soils/sediments and their levels in M. spretus kidneys from DNP and surrounding areas. Toxic metals, such as Cd, Pb, and As, were more abundant in the kidneys of MAT mice than in those from the LDP (reference site) and PAR sites; the results in soils and sediments had the same trend. The present study compares the biological response of M. spretus from contaminated (PAR, MAT) and reference DNP sites, tracing the levels of metal-biomolecules using SEC-ICP7752

dx.doi.org/10.1021/es4057938 | Environ. Sci. Technol. 2014, 48, 7747−7755

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LPC, FFA, choline, energy metabolism (L-carnitine), and some metabolites related with oxidative stress (GSH, glutamic acid, creatinine, and taurine). Therefore, the potential of these approaches in the assessment and understanding of the health risks and toxicological effects in contaminated areas has been demonstrated.

Membranes are primary targets of oxidative damage due to the high levels of O2 and metals present in the proximity to these barriers. The damage begins with the peroxidation of the unsaturated fatty acids (FA) of phospholipids (PL) and oxidized PLs are then degraded. This pathway acts via the sequential activity of phospholipase A2 and lysophospholipase, which release FAs converting phosphatidylcholine (PC) to lysophosphatidylcholine (LPC) and glycerophosphocholine; afterward, alkaline phosphatase releases glycerol, choline, and the phosphate. The metabolomic study of mouse kidneys confirmed the membranes as preferential targets of oxidative damages. All changes pointed to damaged PL degradation in metal-exposed mice: (1) phosphatidylcholine decreased in PAR and, especially, in MAT mice; (2) in contrast, the concentration of all degradation products of phosphatidylcholine, including LPC, three fatty acids, arachidonic, oleic, and pipecolic acids, and choline, which forms PC polar head, were markedly increased in animals from the metal-contaminated sites, PAR and especially MAT. Two additional metabolites, creatinine and L-carnitine, were also found to be altered in the metabolomics study. Creatinine, a well-known biomarker of renal damage,50 increased in the metal-contaminated mice, further confirming the membrane oxidative damage promoted by metal toxicity. LCarnitine transports fatty acids from the cytosol to the mitochondrial matrix for energy production via the β-oxidation pathway.51 Consequently, an L-carnitine decrease would diminish the energy status of metal-exposed animals, most likely reflecting the damaging effects of metal toxicity. The intensities in the MS spectra of different phosphatidylcholine-related compounds were altered in the m/z range of 700−850 (Supporting Information Figure 3), in polar extracts using positive ionization mode (ESI+) in M. spretus from DNP sites with different metal contamination levels. The intensities of the phosphatidylcholine peaks were high in the kidneys of animals from the LPD reference area (Supporting Information Figure 3a) and diminished in animals from the contaminated areas, PAR (Supporting Information Figure 3b) and MAT (Supporting Information Figure 3c). Notice that the metabolite patterns were quite similar, but the peak heights diminished clearly, as observed by comparing their respective intensity scales. In contrast, an increase in lysophosphatidylcholine compounds (m/z 450−600) was observed in mice from both metal contaminated areas, PAR (Supporting Information Figure 3e) and MAT (Supporting Information Figure 3f) compared with the results obtained in LDP mice (Supporting Information Figure 3d). These results point to the degradation of membrane phospholipids, further corroborated by increased levels of free fatty acids, such as pipecolic, arachidonic and oleic acids, as a consequence of PC breakdown. In summary and in agreement with previous results, the combined application of metallomic approaches based on SECICP-MS and metabolomic approaches based on direct infusion to a mass spectrometer (DI-ESI-QTOF-MS) followed by discriminant analysis (PLS-DA) allowed us to compare the biological responses of mice living in environmental areas differentially affected by contamination, as is the case of the LDP, PAR, and MAT. These results show differences in the levels of metals and metalloproteins, such as MTs, Cu/Zn-SOD, or MnCA, in the kidneys of mice from these areas and suggest perturbations in various metabolic pathways due to the presence of metals in the ecosystem, such as the breakdown of the membrane phospholipids producing changes in the levels of PC,

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ASSOCIATED CONTENT

S Supporting Information *

Sampling sites, element content in soils and sediments, ESI(+) mass spectra of pooled polar extracts of mice collected in DNP surroundings, mice from LDP, mice from PAR, and mice from MAT, scores plots of PLS-DA for ESI+ and ESI− ionization modes of polar and lipophilic kidney extracts from M. spretus from the three studied sites, operating conditions for ICP-MS and SEC, operating conditions for DI-ESI-QqQ-TOF-MS, and element concentrations (μg g−1) in M. spretus kidney. This material is available free of charge via the Internet at http://pubs. acs.org.

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AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected]. *E-mail: [email protected]. Author Contributions

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. Funding

The authors thank the projects CTM2012-38720-C03-01 and CTM2012-38720-C03-02 (Ministerio de Economia y Competitividad-Spain) and P08-FQM-03554 and P09-FQM-04659 (Consejeriá de Innovación, Andalusian government). M.A.G.-S. thanks to Ministerio de Educación for a predoctoral grant. Notes

The authors declare no competing financial interest.

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REFERENCES

(1) Damek-Poprawa, M.; Sawicka-Kapusta, K. Histopathological changes in the liver, kidneys, and testes of bank voles environmentally exposed to heavy metal emissions from the steelworks and zinc smelter in Poland. Environ. Res. 2004, 96 (1), 72−8. (2) Sanchez-Chardi, A.; Penarroja-Matutano, C.; Ribeiro, C. A.; Nadal, J. Bioaccumulation of metals and effects of a landfill in small mammals. Part II. The wood mouse, Apodemus sylvaticus. Chemosphere 2007, 70 (1), 101−9. (3) Sanchez-Chardi, A.; Ribeiro, C. A.; Nadal, J. Metals in liver and kidneys and the effects of chronic exposure to pyrite mine pollution in the shrew Crocidura russula inhabiting the protected wetland of Donana. Chemosphere 2009, 76 (3), 387−94. ́ (4) Sawicka-Kapusta, K.; Swiergosz, R.; Zakrzewska, M. Bank voles as monitors of environmental contamination by heavy metals. A remote wilderness area in Poland imperilled. Environ. Pollut. 1990, 67 (4), 315− 324. (5) Garcia-Sevillano, M. A.; Gonzalez-Fernandez, M.; Jara-Biedma, R.; Garcia-Barrera, T.; Lopez-Barea, J.; Pueyo, C.; Gomez-Ariza, J. L. Biological response of free-living mouse Mus spretus from Donana National Park under environmental stress based on assessment of metalbinding biomolecules by SEC-ICP-MS. Anal. Bioanal. Chem. 2012, 404 (6−7), 1967−81. (6) Vioque-Fernandez, A.; de Almeida, E. A.; Ballesteros, J.; GarciaBarrera, T.; Gomez-Ariza, J. L.; Lopez-Barea, J. Donana National Park survey using crayfish (Procambarus clarkii) as bioindicator: Esterase inhibition and pollutant levels. Toxicol. Lett. 2007, 168 (3), 260−8. 7753

dx.doi.org/10.1021/es4057938 | Environ. Sci. Technol. 2014, 48, 7747−7755

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(7) Griffin, J. L.; Walker, L.; Shore, R. F.; Nicholson, J. K. Highresolution magic angle spinning 1H-NMR spectroscopy studies on the renal biochemistry in the bank vole (Clethrionomys glareolus) and the effects of arsenic (As3+) toxicity. Xenobiotica 2001, 31 (6), 377−85. (8) Ruiz-Laguna, J.; Abril, N.; Garcia-Barrera, T.; Gomez-Ariza, J. L.; Lopez-Barea, J.; Pueyo, C. Absolute transcript expression signatures of Cyp and Gst genes in Mus spretus to detect environmental contamination. Environ. Sci. Technol. 2006, 40 (11), 3646−3652. (9) Montes-Nieto, R.; Fuentes-Almagro, C. A.; Bonilla-Valverde, D.; Prieto-Alamo, M. J.; Jurado, J.; Carrascal, M.; Gomez-Ariza, J. L.; LopezBarea, J.; Pueyo, C. Proteomics in free-living Mus spretus to monitor terrestrial ecosystems. Proteomics 2007, 7 (23), 4376−4387. (10) Gonzalez-Fernandez, M.; Angel Garcia-Sevillano, M.; JaraBiedma, R.; Navarro- Roldán, F.; Garcia-Barrera, T.; Lopez-Barea, J.; Pueyo, C.; L. Gomez-Ariza, J. Use of metallomics in environmental pollution assessment using mice Mus musculus/Mus spretus as bioindicators. Curr. Anal. Chem. 2013, 9 (2), 229−243. (11) Gonzalez-Fernandez, M.; Garcia-Sevillano, M. A.; Jara-Biedma, R.; Garcia-Barrera, T.; Vioque, A.; Lopez-Barea, J.; Pueyo, C.; GomezAriza, J. L. Size characterization of metal species in liver and brain from free-living (Mus spretus) and laboratory (Mus musculus) mice by SECICP-MS: Application to environmental contamination assessment. J. Anal. At. Spectrom. 2011, 26 (1), 141−149. (12) García-Sevillano, M.; González-Fernández, M.; Jara-Biedma, R.; García-Barrera, T.; Vioque-Fernández, A.; López-Barea, J.; Pueyo, C.; Gómez-Ariza, J. Speciation of arsenic metabolites in the free-living mouse Mus spretus from Doñana National Park used as a bio-indicator for environmental pollution monitoring. Chem. Pap. 2012, 66 (10), 914−924. (13) Bonilla-Valverde, D.; Ruiz-Laguna, J.; Munoz, A.; Ballesteros, J.; Lorenzo, F.; Gomez-Ariza, J. L.; Lopez-Barea, J. Evolution of biological effects of Aznalcollar mining spill in the Algerian mouse (Mus spretus) using biochemical biomarkers. Toxicology 2004, 197 (2), 123−38. (14) Garcia-Sevillano, M. A.; Garcia-Barrera, T.; Abril, N.; Pueyo, C.; Lopez-Barea, J.; Gomez-Ariza, J. L. Omics technologies and their applications to evaluate metal toxicity in mice M. spretus as a bioindicator. J. Proteomics 2014, 104, 4−23. (15) Grimalt, J. O.; Ferrer, M.; Macpherson, E. The mine tailing accident in Aznalcollar. Sci. Total Environ. 1999, 242 (1−3), 3−11. (16) Gonzalez-Fernandez, M.; Garcia-Barrera, T.; Gomez-Ariza, J. L. Molecular mass spectrometric identification of superoxide dismutase in the liver of mice Mus musculus and Mus spretus using a metallomics analytical approach. Anal. Bioanal. Chem. 2011, 401 (9), 2779−83. (17) Montes-Nieto, R.; Garcia-Barrera, T.; Gomez-Ariza, J. L.; LopezBarea, J. Environmental monitoring of Domingo Rubio stream (Huelva Estuary, SW Spain) by combining conventional biomarkers and proteomic analysis in Carcinus maenas. Environ. Pollut. 2010, 158 (2), 401−8. (18) Romero-Ruiz, A.; Alhama, J.; Blasco, J.; Gomez-Ariza, J. L.; LopezBarea, J. New metallothionein assay in Scrobicularia plana: heating effect and correlation with other biomarkers. Environ. Pollut. 2008, 156 (3), 1340−7. (19) Vioque-Fernández, A.; Alves de Almeida, E.; López-Barea, J. Assessment of Doñana National Park contamination in Procambarus clarkii: Integration of conventional biomarkers and proteomic approaches. Sci. Total Environ. 2009, 407 (5), 1784−1797. (20) Gómez-Ariza, J. L.; García-Barrera, T.; Lorenzo, F.; Bernal, V.; Villegas, M. J.; Oliveira, V. Use of mass spectrometry techniques for the characterization of metal bound to proteins (metallomics) in biological systems. Anal. Chim. Acta 2004, 524 (1−2)), 15−22. (21) Bowen, B. P.; Northen, T. R. Dealing with the unknown: Metabolomics and metabolite atlases. J. Am. Soc. Mass Spectrom. 2010, 21 (9), 1471−6. (22) Erry, B. V.; Macnair, M. R.; Meharg, A. A.; Shore, R. F. Arsenic contamination in wood mice (Apodemus sylvaticus) and bank voles (Clethrionomys glareolus) on abandoned mine sites in southwest Britain. Environ. Pollut. 2000, 110 (1), 179−187. (23) Dettmer, K.; Aronov, P. A.; Hammock, B. D. Mass spectrometrybased metabolomics. Mass Spectrom. Rev. 2007, 26 (1), 51−78.

(24) Goldsmith, P.; Fenton, H.; Morris-Stiff, G.; Ahmad, N.; Fisher, J.; Prasad, K. R. Metabonomics: A useful tool for the future surgeon. J. Surg. Res. 2010, 160 (1), 122−32. (25) Booth, S. C.; Workentine, M. L.; Weljie, A. M.; Turner, R. J. Metabolomics and its application to studying metal toxicity. Metallomics 2011, 3 (11), 1142−52. (26) Tersago, K.; De Coen, W.; Scheirs, J.; Vermeulen, K.; Blust, R.; Van Bockstaele, D.; Verhagen, R. Immunotoxicology in wood mice along a heavy metal pollution gradient. Environ. Pollut. 2004, 132 (3), 385−94. (27) Valko, M.; Rhodes, C. J.; Moncol, J.; Izakovic, M.; Mazur, M. Free radicals, metals and antioxidants in oxidative stress-induced cancer. Chem.−Biol. Interact. 2006, 160 (1), 1−40. (28) Flora, S. J.; Mittal, M.; Mehta, A. Heavy metal induced oxidative stress & its possible reversal by chelation therapy. Indian J. Med. Res. 2008, 128 (4), 501−23. (29) Mates, J. M.; Perez-Gomez, C.; Nunez de Castro, I.; Asenjo, M.; Marquez, J. Glutamine and its relationship with intracellular redox status, oxidative stress and cell proliferation/death. Int. J. Biochem. Cell Biol. 2002, 34 (5), 439−58. (30) Rahman, K. Studies on free radicals, antioxidants, and co-factors. Clin. Interventions Aging 2007, 2 (2), 219−36. (31) Lindeque, J. Z.; Levanets, O.; Louw, R.; van der Westhuizen, F. H. The involvement of metallothioneins in mitochondrial function and disease. Curr. Protein Pept. Sci. 2010, 11 (4), 292−309. (32) Hamer, D. H. Metallothionein. Annu. Rev. Biochem. 1986, 55, 913−51. (33) Alsen, C.; Kopcke, C.; Ohnesorge, F. K.; Schneider, J. Effects of cadmium on carbonic anhydrase activity and hemoglobin content of rat testes. Arch. Toxicol. 1976, 37 (1), 39−46. (34) Griffin, J. L.; Troke, J.; Walker, L. A.; Shore, R. F.; Lindon, J. C.; Nicholson, J. K. The biochemical profile of rat testicular tissue as measured by magic angle spinning 1H NMR spectroscopy. FEBS Lett. 2000, 486 (3), 225−229. (35) Sarkar, S.; Yadav, P.; Trivedi, R.; Bansal, A. K.; Bhatnagar, D. Cadmium-induced lipid peroxidation and the status of the antioxidant system in rat tissues. J. Trace Elem. Med. Biol. 1995, 9 (3), 144−9. (36) Garcia-Sevillano, M. A.; Garcia-Barrera, T.; Navarro, F.; GomezAriza, J. L. Inorganic mass spectrometry-based metallomics for environmental monitoring of terrestrial ecosystems affected by metal pollution using Mus spretus as bioindicator. J. Int. OMICS 2013, 3 (2), 88−98. (37) Pueyo, C.; Gómez-Ariza, J.-L.; Bello-López, M.-A.; FernándezTorrez, R.; Abril, N.; Alhama, J.; García-Barrera, T.; López-Barea, J., New methodologies for assessing the presence and ecological effects of pesticides in Doñana National Park (SW Spain). In Pesticides in the Modern WorldTrends in Pesticides Analysis; Stoytcheva, M., Ed.; InTech: Rijeka, Croatia, 2011; pp 167−196. (38) Garciá-Sevillano, M. A.; Garciá-Barrera, T.; Navarro, F.; GómezAriza, J. L. Analysis of the biological response of mouse liver (Mus musculus) exposed to As2O2 based on integrated -omics approaches. Metallomics 2013, 5, 1644−1655. (39) Timbrell, J., Factors affecting metabolism and distribution. In Principles of Biochemical Toxicology; Taylor & Francis Ltd: London, UK, 1982; pp 113−172. (40) Phipps, A. N.; Stewart, J.; Wright, B.; Wilson, I. D. Effect of diet on the urinary excretion of hippuric acid and other dietary-derived aromatics in rat. A complex interaction between diet, gut microflora and substrate specificity. Xenobiotica 1998, 28 (5), 527−37. (41) Bell, J. D.; Sadler, P. J.; Morris, V. C.; Levander, O. A. Effect of aging and diet on proton NMR spectra of rat urine. Magn. Reson. Med. 1991, 17 (2), 414−22. (42) García-Sevillano, M. A.; Jara-Biedma, R.; González-Fernández, M.; García-Barrera, T.; Gómez-Ariza, J. L. Metal interactions in mice under environmental stress. Biometals 2013, 26 (4), 651−666. (43) Torres, K. C.; Johnson, M. L. Bioaccumulation of metals in plants, arthropods, and mice at a seasonal wetland. Environ. Toxicol. Chem. 2001, 20 (11), 2617−2626. 7754

dx.doi.org/10.1021/es4057938 | Environ. Sci. Technol. 2014, 48, 7747−7755

Environmental Science & Technology

Article

(44) Rogival, D.; Scheirs, J.; Blust, R. Transfer and accumulation of metals in a soil−diet−wood mouse food chain along a metal pollution gradient. Environ. Pollut. 2007, 145 (2), 516−28. (45) Fridovich, I. Superoxide radical and superoxide dismutases. Annu. Rev. Biochem. 1995, 64, 97−112. (46) Okrasa, K.; Kazlauskas, R. J. Manganese-substituted carbonic anhydrase as a new peroxidase. Chem.Eur. J. 2006, 12 (6), 1587− 1596. (47) Teodorova, S.; Metcheva, R.; Topashka-Ancheva, M. Bioaccumulation and damaging action of polymetal industrial dust on laboratory mice Mus musculus alba. I. Analysis of Zn, Cu, Pb, and Cd disposition and mathematical model for Zn and Cd bioaccumulations. Environ. Res. 2003, 91 (2), 85−94. (48) Gurer, H.; Ozgunes, H.; Saygin, E.; Ercal, N. Antioxidant effect of taurine against lead-induced oxidative stress. Arch. Environ. Contam. Toxicol. 2001, 41 (4), 397−402. (49) Sinha, M.; Manna, P.; Sil, P. C. Taurine protects the antioxidant defense system in the erythrocytes of cadmium treated mice. BMB Rep. 2008, 41 (9), 657−63. (50) Yaqoob, M.; Bell, G. M.; Stevenson, A.; Mason, H.; Percy, D. F. Renal impairment with chronic hydrocarbon exposure. Q. J. Med. 1993, 86 (3), 165−74. (51) Kerner, J.; Hoppel, C. Fatty acid import into mitochondria. Biochim. Biophys. Acta, Mol. Cell Biol. Lipids 2000, 1486 (1), 1−17.

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