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Metabolomic investigation of Mytilus galloprovincialis (Lamarck 1819) caged in aquatic environments
Ecotoxicology and Environmental Safety 84 (2012) 139–146
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Ecotoxicology and Environmental Safety journal homepage: www.elsevier.com/locate/ecoenv
Metabolomic investigation of Mytilus galloprovincialis (Lamarck 1819) caged in aquatic environments Salvatore Fasulo a,b, Francesco Iacono c, Tiziana Cappello c, Carmelo Corsaro d, Maria Maisano a, Alessia D’Agata a, Alessia Giannetto a, Elena De Domenico a, Vincenzo Parrino a, Giuseppe Lo Paro a, Angela Mauceri a,b,n a
Department of Animal Biology and Marine Ecology, University of Messina, Viale F. Stagno D’Alcontres 31, 98166 Messina, Italy Centro Universitario CUTGANA, Via Terzora 8, 95027 San Gregorio di Catania, Italy c Ph.D. in Biology and Cellular Biotechnologies, Department of Animal Biology and Marine Ecology, University of Messina, Viale F. Stagno D’Alcontres 31, 98166 Messina, Italy d Department of Physics, University of Messina, Viale F. Stagno D’Alcontres 31, 98166 Messina, Italy b
a r t i c l e i n f o
abstract
Article history: Received 28 December 2011 Received in revised form 29 June 2012 Accepted 2 July 2012 Available online 20 July 2012
Environmental metabolomics was applied to assess the metabolic responses in transplanted mussels to environmental pollution. Specimens of Mytilus galloprovincialis, sedentary filter-feeders, were caged in anthropogenic-impacted and reference sites along the Augusta coastline (Sicily, Italy). Chemical analysis revealed increased levels of PAHs in the digestive gland of mussels from the industrial area compared with control, and marked morphological changes were also observed. Digestive gland metabolic profiles, obtained by 1H NMR spectroscopy and analyzed by multivariate statistics, showed changes in metabolites involved in energy metabolism. Specifically, changes in lactate and acetoacetate could indicate increased anaerobic fermentation and alteration in lipid metabolism, respectively, suggesting that the mussels transplanted to the contaminated field site were suffering from adverse environmental condition. The NMR-based environmental metabolomics applied in this study results thus in it being a useful and effective tool for assessing environmental influences on the health status of aquatic organisms. & 2012 Elsevier Inc. All rights reserved.
Keywords: Caged mussels Mytilus galloprovincialis Digestive gland PAHs Metabolomics 1 H NMR
1. Introduction Metabolomics is an emerging approach to assessing the health status of organisms based on the identification of low molecular weight metabolites, whose production and levels vary with the physiological, developmental, or pathological state of cells, tissues, organs or whole organisms (Lin et al., 2006). Proton nuclear magnetic resonance (1H NMR) spectroscopy-based metabolomics, when linked with pattern recognition techniques and data mining tools, can detect differences in the profile of metabolites (metabolic biomarkers) in response to environmental stressors, diseases or exposure to toxicants (Fiehn, 2002; Hines et al., 2007; Tuffnail et al., 2009; Viant et al., 2003), thus providing an overview of the metabolic status of a biological system. Metabolite profiling, originally developed for human biomedical applications (Nicholson et al., 1988) has now been increasingly employed in several research areas, including plant science (Kim et al., 2010), n Corresponding author at: Department of Animal Biology and Marine Ecology, University of Messina, Viale F. Stagno D’Alcontres 31, 98166 Messina, Italy. Fax: þ 39 090 6765556. E-mail address: [email protected] (A. Mauceri).
0147-6513/$ - see front matter & 2012 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ecoenv.2012.07.001
food quality (Tarachiwin et al., 2008), microbial metabolomics (Boroujerdi et al., 2009) and environmental metabolomics (Viant, 2009). Because metabolomics can provide valuable information on how xenobiotics influence physiological functions, this technique has also been applied to experimental studies of selective exposure on various aquatic organisms, both invertebrates (Wu and Wang, 2010) and fish (Iacono et al., 2010; Santos et al., 2010). Pollution of coastal areas may arise from various industrial and urban sources, such as shipping, loading and bunkering operations, shipyards, accidental spills, wastewater emissions (Bocchetti et al., 2008). This may result in elevated concentrations of toxicants in the water column and sediments. In particular, harbours are generally enclosed areas characterized by poor water quality, due to a low flushing rate and human activities within or adjacent to the harbour (Yin et al., 2000). There are concerns about risk to aquatic organisms residing in inner harbours, because these organisms are exposed to high concentrations of environmental contaminants due to low hydrodynamism and intense anthropogenic impact. In this regard, the ‘‘Augusta-Melilli-Priolo’’ industrial area has been considered for this study. It extends approximately 20 km along the Augusta coastal area (eastern Sicily, Italy) and is one of the largest and
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most complex petrochemical sites in Europe, because many industrial installations can be found there, including oil refineries, chemical plants, mineral deposits, a military base and many other industrial installations (Ausili et al., 2008). Mercury (Hg) and polycyclic aromatic hydrocarbons (PAHs) are found in excessive concentrations (ICRAM, 2005). Levels of these contaminants exceed national and international regulatory guidelines, as reported in recent studies on sediments collected from the coastal zone of Augusta (Di Leonardo et al., 2008, 2007). Such pollutant mixtures (heavy metals, drugs, PAHs, polychlorinated biphenyls PCBs) can induce toxic effects at different biological levels (e.g. molecular, cellular, biochemical, physiological). Because changes at the organism level lead to changes at the population and community levels, a number of biomarkers are frequently used as early warning signals of environmental disturbance (Walker et al., 2006). In environmental monitoring studies mussels, particularly the genus Mytilus, are widely used as sentinel organisms (Fasulo et al., 2008; Hellou and Law, 2003; Viarengo et al., 2007). This is because of their wide geographical distribution, ability to tolerate a range of environmental conditions and accumulate toxic chemicals, and suitability for caging experiments at field sites (Andral et al., 2004; Romeo et al., 2003; Tsangaris et al., 2010; Viarengo et al., 2007; Wu and Shin, 1998). The use of transplanted mussels originating from a clean area allows comparison of control organisms with those caged in potentially polluted sites, and allows more control over the experiment than collection of native individuals. In addition, using caged mussels from a single population minimizes confounding factors such as the age and reproductive status of the organisms that influence both contaminant bioaccumulation and biomarker responses. Thus, a more accurate assessment of the real biological effects of pollutant exposure is possible, providing an early sign of impaired health of the ecosystem (Andral et al., 2004; Regoli, 2000; Tsangaris et al., 2010; Viarengo et al., 2007). The digestive gland is a target organ widely used in environmental toxicology because it accumulates pollutants and participates actively in the xenobiotic metabolism (Rajalakshmi and Mohandas, 2005). It is also involved in immune defense, detoxification and in homeostatic regulation (Marigomez et al., 2002; Moore and Allen, 2002), and therefore exposure to contaminants may lead to its histopathological alterations (Garmendia et al., 2011). Histopathology is a biomarker of effect for an overall assessment of the general health status of animals, and provides valuable information concerning changes in the cellular as well as sub-cellular structures of an organ or tissue much earlier than the external manifestations (Auffret, 1988; Fasulo et al., 2010a, 2010b; Ferrando et al., 2005; Livingstone and Pipe, 1992; Mauceri et al., 2002). The aim of this study was to assess biological effects of environmental pollution, mainly related to the presence of PAHs, in the caged mussel Mytilus galloprovincialis, through the use of morphological and metabolite assays. In fact, although in recent years several reports have suggested that NMR-based environmental metabolomics is a powerful tool in environmental toxicology (Viant et al., 2003), there are few studies dealing with assessment of aquatic organism health through a metabolomics based approach.
2. Materials and methods 2.1. Sites and experimental design The ‘‘Augusta-Melilli-Priolo’’ industrial area, chosen as polluted site for this study, has been declared a ‘‘site of national interest’’ by the Italian Ministry of Environment (Law No. 426/98; Ministerial Decree of 10.01.2000) owing to the high level of pollution and subsequent risk for human health. By contrast, the natural reserve of Vendicari, established in 1984 and representing a wildlife
Fig. 1. Map depicting location of the mussel caging sites.
Table 1 Mean (7 S.D.) of water physico-chemical parameters of Vendicari and Priolo. Sampling area
Vendicari
Priolo
Temperature (1C) Salinity (PSU) pH Oxygen (mg/l)
23.4 70.5 37.6 70.1 8.0 70.1 4.8 70.2
22.5 70.6 38.2 70.2 7.9 70.1 3.7 70.3
reserve in the southernmost part of the east coast of Sicily, was chosen as a nonimpacted reference site. It covers an area of 1512 ha (575 ha of a integral reserve and 937 ha of a pre-reserve) and its biological importance is due to the presence of different biotopes, e.g. rocky and sandy coastlines, Mediterranean scrub, both salt and fresh water marshes (Fig. 1). At both sampling sites, water physico-chemical parameters (temperature, salinity, pH, dissolved oxygen) were measured by a portable instrument (Multi 340i/SET, WTW Wissenschaftlich, Weilheim, Germany), as reported in Table 1. Mussels M. galloprovincialis (6.1 70.54 cm shell length) were purchased in October 2009 from a consortium of fishermen in Goro (Ferrara, Italy), a reference site in which physico-chemical parameters have been previously reported (Fasulo et al., 2008). Mussels were maintained 1 week in aerated seawater in the laboratory, and then transplanted in the two selected sites for 30 days in stainless steel cages (about 200 specimens per cage) covered with a net to guarantee free seawater circulation and protect mussels from fish predation. Cages were deployed by scuba-diving at 8 m depth below the surface both in Priolo (371120 1000 N; 151130 4400 E) and Vendicari (361 470 3500 N; 151 080 5200 E). The mussels were retrieved after 4 weeks by diving and immediately conditioned after collection on board of the experimental vessel. Fifteen male individuals from each area were selected randomly and sacrificed. Body length and mass were recorded, and digestive gland samples were rapidly excised and flash-frozen in liquid nitrogen for chemical and metabolic measurements, then transferred to the laboratory and stored at 80 1C prior to analysis. In addition, small pieces of each dissected tissue were taken for histological analysis. This study was conducted according to the guidelines for the protection of animal welfare, in compliance with the Italian National Bioethics Committee (INBC).
2.2. PAH concentration in digestive gland For PAH analysis, the following solvents and reagents were used: acetonitrile ACN (Romil), water and cyclohexane (Chromanorm BDH), acetone (Pestinorm BDH), KOH, ethanol and exane (Carlo Erba), all of HPLC grade. The digestive glands dissected from fifteen individuals were pooled in three samples (each with tissues of five specimens) per each sampling area. Approximately 3 g of each pooled sample were weighted with an analytical balance Mettler Toledo AT 104 and homogenized in a glass vial using an Ultra-TURRAX IKA T10 basic. The homogenized samples were saponified with 10 ml of 1 M KOH in an ethanol solution for
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3 h at 80 1C in a water bath. Then, 20 ml of cyclohexane was added and samples mixed by an orbital agitator for 10 min using dark glassware (Dafflon et al., 1995). The hexanic phase was recovered and the polar mixture washed once with cyclohexane and then discharged. The extracts were filtered, concentrated under a nitrogen gas stream to about 1 ml, and the concentrated extract was removed with a pasteur pipette and loaded into a Varian Bond Elut C18 cartridge 12 ml, previously conditioned. The eluates were dried under nitrogen flow and dissolved with 1 ml of acetonitrile before the analysis. The concentrations of the following sixteen PAHs identified by the EPA as priority pollutants, naphthalene (NA), acenaphthylene (ACY), acenaphthene (AC), fluorene (FL), phenanthrene (PHE), anthracene (AN), fluoranthene (FA), pyrene (PY), benzo(a)anthracene (BaA), chrysene (CH), benzo(b)fluoranthene (BbF), benzo(k)fluoranthene (BkF), benzo(a)pyrene (BaP), dibenz(a,h)anthracene (DahA), benzo(g,h,i)perylene (Bghi) and indeno(1,2,3-cd)pyrene (IP), were determined. Quantitative analysis of PAHs was carried out with a high-performance liquid chromatography (HPLC) apparatus Pro-Star 363 (Varian, Palo Alto, CA) equipped with a 20 ml loop and a fluorescence detector (FLD Pro-Star 363). The software used was Star Chromatography Workstation version 5.2 (Varian, Palo Alto, CA). The chromatographic separation was carried out using a Chromspher three PAH Varian (100 4.6 mm2) coupled with a guard column ChromSep SS 10 2 mm2, Varian. The analytical method involved a mobile phase consisting of H2O/ACN 50 percent for 5 min, which achieved 100 percent ACN in 5 min with a flow of 1 ml/min. The UV determination was performed at 255 nm, while the FL detection was conducted with six different excitation/emission wavelengths. The National Institute of Standards and Technology (NIST) Standard Reference Material SRM 1647c, consisting of an acetonitrile solution of sixteen PAHs (target compounds), was used as a calibration mixture. Percent recovery and matrix interference was assessed with reference to M. galloprovincialis tissue. The external standard multipoint calibration technique was used to determine the linear response interval of the detector and in all cases, regression coefficients were higher than 0.996 for all the analytes detected by UV, and higher than 0.989 for all the analytes detected in FL.
(Wishart, 2007) and by use of Chenomx NMR Suite (version 5.1; Chenomx Inc., Edmonton, Canada) software.
2.3. Histological analysis
3.1. PAH concentration
Digestive gland tissues of fifteen mussels from each sampling site were fixed in four percent paraformaldehyde (Immunofix, Bio-Optica Milano, Italy) in 0.1 M phosphate buffered solution (pH 7.4) at 4 1C for 3 h, dehydrated in a graded series of ethanol and embedded in Paraplast (Bio-Optica Milano, Italy), according to standard protocols (Mauceri et al., 1999). Histological sections, 5 mm thick, were cut with a rotary automatic microtome (Leica Microsystems, Wetzlar, Germany), mounted on glass slides and stained with Hematoxylin/Eosin (Bio-Optica Milano, Italy) to assess morphological features. All observations were made with a motorized Zeiss Axio Imager Z1 microscope equipped with an AxioCam digital camera (Zeiss).
For PAHs molecules containing from two to five condensed rings (NA, ACY, AC, FL, PHE, AN, FA, PY, BaA, CH, BbF, BkF, BaP, DahA) recovery was from 90 to 97 percent, while for the remaining (Bghi, IP), recovery was from 99 to 100 percent. PAH concentrations in the digestive gland samples from the reference site were lower than the instrument detection limit. By contrast, the samples from Priolo had elevated levels of PAHs, especially naphthalene and fluoranthene among light PAHs, benzo(a)pyrene and dibenzo(a,b)anthracene among high molecular weight PAHs (Table 2).
2.4. Tissue metabolite extraction Polar metabolites were extracted from the digestive gland tissues of fifteen mussels from each sampling site using a ‘‘two-step’’ methanol/chloroform procedure (Wu et al., 2008). Briefly, a 100 mg subsample of each frozen gland was homogenized in 4 ml/g of cold methanol and 0.85 ml/g of cold water by using an Ultraturrax homogenizer. The homogenates were transferred to glass vials, and 4 ml/g chloroform and 2 ml/g water were added. Samples were vortexed for 60 s, left on ice for 10 min for phase separation, and then centrifuged for 5 min at 2000g at 4 1C. Four hundred microliter of the upper methanol layer with polar metabolites were transferred to glass vials, dried in fume hood overnight and stored at 80 1C. Immediately prior to NMR analysis, the dried polar extracts were ¨ resuspended in 100 ml of D2O (Armar AG, Dottingen, Switzerland) buffered in 240 mM sodium phosphate, pH 7.0, containing 12.5 mM 2,2-dimethyl-2-silapentane-5-sulfonate (DSS) (Sigma-Aldrich Co) and vortexed. The DSS acts as an internal standard and also provides a chemical shift reference (d ¼ 0.0 ppm) for the NMR spectra, while the D2O provides a deuterium lock for the NMR spectrometer. Fifty microliter of each resuspended sample were then pipetted into a 4 mm-diameter zirconia rotors with a spherical insert and a Kel-F cap. 2.5. High resolution magic Angle spinning (HR-MAS) 1H NMR spectroscopy Extracts of digestive gland tissue from mussels were analyzed on a Bruker Avance-700 NMR spectrometer operated at a spin rate of 4000 Hz (at 300 K). Onedimensional (1-D) 1H NMR spectra were obtained using a 7.0 ms (901) pulse, 11 kHz spectral width (15.94 ppm) and 2.0 s relaxation delay with pre-saturation of the residual water resonance, with 128 transients collected into 32.768 data points requiring a 10.5 min acquisition time. Exponential line-broadenings of 0.5 Hz were applied before Fourier transformation. All 1H NMR spectra were manually phased, baseline-corrected, and calibrated (DSS at 0.0 ppm) using XWIN-NMR (version 3.5; Bruker) software. Peaks within the 1H NMR spectra were assigned with reference to known chemical shifts and peak multiplicities
2.6. Spectral processing and multivariate data analysis NMR spectra were converted to a format for multivariate analysis using custom-written ProMetab 3.3 software (Viant, 2003) in MATLAB (version R2009b; The MathWorks, Natick, MA). Each spectrum was segmented into 0.005 ppm chemical shift bins between 0.7 and 10.0 ppm, with bins from 1.12 to 1.22 and 3.62 to 3.67 ppm (ethanol for rotor cleaning), 4.70 to 5.15 ppm (water) and 7.19 to 7.28 ppm (chloroform) excluded from all the NMR spectra. Because some peaks shifted due to slight variations of the sample pH, nine groups of bins (2.382–2.457, 2.612–2.657, 3.247–3.297, 3.537–3.557, 3.867–3.907, 4.342–4.367, 4.622–4.627, 5.212–5.217 and 8.887–8.927 ppm) were each compressed into single bins. The area for each segmented region was calculated and normalized to the total integrated area of the spectra. All the NMR spectra were generalized by log transformation (with a transformation parameter, l ¼ 3.6 10 6) to stabilize the variance across the spectral bins and to increase the weightings of the less intense peaks (Wu and Wang, 2010). Data were mean-centered before Principal Components Analysis (PCA) using the Unscrambler X package (version 10.0.1; Camo Software AS, Oslo, NO) and the singular value decomposition (SVD) algorithm was applied to perform a PCA with cross validation. PCA, an unsupervised pattern recognition technique, allowed the differences and similarities between NMR metabolic fingerprints to be visualized in a score plot, where samples that are metabolically similar cluster together. The corresponding PCA loadings plot was used to identify the metabolic basis of the clustering. Representative proton peaks were normalized to total spectral area, and Student’s t tests were used to indicate the significant metabolic changes between mussel groups (Microsoft Excel).
3. Results
3.2. Histological analysis The digestive gland of M. galloprovincialis caged in the reference site (Fig. 2A) showed the typical organization of the digestive
Table 2 PAH concentrations (mean7 S.D.) in the digestive gland (mg/g). n.d.¼ not detectable. PAHs
Priolo
Vendicari
Naphthalene Acenaphthylene Acenaphtehene Fluorene Phenanthrene Anthracene Fluranthene Pyrene Benz(a)anthracene Chrysene Benzo(b)fluoranthene Benzo(k)fluoranthene Benzo(a)pyrene Dibenz(a,b)anthracene Benzo(g,h,i)perylene Indeno(1,2,3-cd)pyrene
0.912 70.038 0.011 7 0.007 0.007 70.002 0.009 70.005 o0.006 o0.006 0.187 70.012 0.008 70.004 o0.006 n.d. 0.012 7 0.007 0.008 70.002 0.060 70.017 0.925 70.028 o0.006 o0.006
n.d n.d n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
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Fig. 2. Hematoxylin and Eosin (H&E) staining in the digestive gland of Mytilus galloprovincialis caged in the reference site (A) compared with those transferred to the polluted area (B), which displayed severe histopathological alterations and relevant aggregations of haemocytes (arrow) among digestive tubules. Scale bars, 20 mm.
diverticula of bivalves, as described by Owen (1970). On the contrary, a rather irregular digestive gland morphology of mussels from the polluted area was noted (Fig. 2B). The tissue was remarkably modified and damaged, and massive haemocytic infiltration was observed among digestive tubules. 3.3. Metabolomics analysis 3.3.1. 1H NMR spectroscopy of digestive gland tissue extracts Fig. 3 shows a representative 1H NMR spectrum of the mussel digestive gland tissue extracts. Although several metabolites were identified, all spectra were found to be dominated by betaine, taurine, homarine and glycine, known to act as osmolytes. Other prominent classes of compounds included amino acids (e.g. leucine, alanine, valine), carbohydrates (e.g. glucose), tricarboxylic acid cycle intermediates (e.g. succinate), organic compounds (e.g. acetoacetate) and nucleotides (e.g. uracil). 3.3.2. Pattern recognition analysis of 1H NMR spectra The PCA scores plot of the 1H NMR metabolic fingerprints of M. galloprovincialis digestive gland (Fig. 4A) shows a clear separation between the two mussel groups caged in the selected sites along PC2 (explaining seven percent of variance). The corresponding PC2 loadings plot, depicted in Fig. 4B, was used to determine which metabolites were important in the separation of the two groups and the direction of their changes. In particular, peaks with positive loadings correspond to metabolites that have higher concentrations in ‘‘stressed’’ (specimens transplanted in the polluted area) than in the control mussels, whereas negative loadings correspond to metabolites whose concentration is decreased in the stressed group relative to the control. From the PC2 loadings plot, the metabolic profiles of digestive gland extracts from stressed individuals were characterized by significantly elevated levels (metabolite changes were calculated via the ratio between the averages of the stressed and control peak areas, Po0.05) of valine, lysine, phenylalanine, acetoacetate, nucleotides such as thymidine and adenine, and an unidentified metabolite at 4.15 ppm, together with a decreased concentration (not significant) of glucose, glutamine and glutamate, as reported in Table 3.
4. Discussion The use of caged mussels has been demonstrated to be an effective and useful tool for assessing the environmental quality status and the real biological effects induced by xenobiotics
(Andral et al., 2004; Nigro et al., 2006; Regoli, 2000; Romeo et al., 2003). In the present study, digestive glands of mussels caged for 30 days in Priolo displayed relevant histological lesions such as altered diverticula morphology and conspicuous haemocytic infiltration. This might result in impairment of its metabolic activities. Previous studies have provided evidence of haemocytic infiltration in response to exposure to hydrocarbons (Cajaraville et al., 1990) that could be interpreted as a repair process following tissue damage (Garmendia et al., 2011). While water physico-chemical parameters showed no significant difference between the two investigated areas, chemical analysis revealed high concentrations of naphthalene and fluoranthene, indicative of pyrolytic origin of the PAHs, and benzo(a)pyrene and dibenzo(a,b)anthracene, which are commonly the constituents of urban and industrial contamination, in digestive gland tissue of mussels from the polluted site. These findings are consistent with the presence of PAHs in the industrial area of Priolo. The environmental metabolomics approach here reported, based on 1HNMR spectroscopy, allows the successful investigation of the metabolic changes in response to various environmental insults (Tikunov et al., 2010). PCA analysis indicated that the mussels caged in the natural reserve of Vendicari clustered separately from those transplanted in the industrial area of Priolo, suggesting a differential metabolic profile between organisms. Specifically, the PC2 loadings plot indicated the key metabolic changes occurring in individuals acclimatized in the industrial area (relative to the control). This metabolic fingerprint is characterized by increased concentrations of branched chain amino acids (BCCA) such as valine, free amino acids, energetic metabolites, nucleotides and an unidentified metabolite, and depletion (not significant) of glucose and glutamate. Amino acid levels were markedly increased in the mussels caged at Priolo. Free amino acids represent a large fraction of the metabolome of marine invertebrates (Henry et al., 1980). It has been reported that free amino acids and their catabolites are used in marine molluscs, as well as in other marine invertebrates, as the major osmolytes to balance their intracellular osmolarity with the environment (Yancey et al., 1982). Hence, the noticeably elevated concentration of amino acids is consistent with perturbations in osmoregulatory mechanism due to exposure to toxic compounds. In addition, these pools of amino acids, except for glycine, glutamine and aspartic acid that are necessary in the biosynthesis of nitrogenous bases, are also extensively involved in cellular energy metabolism. In fact, a metabolomic study on M. edulis exposed to high dose of herbicide reported increases in leucine and isoleucine (Tuffnail et al., 2009), and this
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Fig. 3. Representative 1-D 700 MHz 1H NMR spectrum of digestive gland from mussel (Mytilus galloprovincialis) caged in the reference site, with (A) representing the aliphatic region and (B) a vertical expansion of the aromatic region. Keys: (1) DSS, (2) isoleucine, (3) leucine, (4) valine, (5) lactate, (6) alanine, (7) arginine, (8) lysine, (9) glutamate, (10) glutamine, (11) acetocetate, (12) succinate, (13) hypotaurine, (14) aspartate, (15) malonate, (16) choline, (17) taurine, (18) betaine, (19) glucose, (20) glycine, (21) homarine, (22) glycogen, (23) uracil, (24) inosine, (25) fumarate, (26) tyrosine, and (27) phenylalanine.
observation was consistent with the stimulation of metabolic activity. Changes in metabolites involved in energy metabolism were also observed. Specifically, levels of lactate increased in mussels transferred to the industrial area, indicating inhibition of aerobic metabolism (Wu and Wang, 2010). The observed depletion in glucose accompanied by the concomitant increase in lactate indicates then an enhancement in anaerobic metabolism. In addition to the metabolic changes associated with energetic pathways, increases in acetoacetate were found in digestive gland of mussels caged in Priolo. Acetoacetate is a compound categorized as ketone body, and synthesized from three molecules of
acetyl-coenzyme A (acetyl-CoA) as end product of fatty acid oxidation. The increase in acetoacetate is then consistent with an alteration in lipid metabolism. Alternatively, some amino acids, such as phenylalanine, lysine, isoleucine, leucine and tyrosine, under certain metabolic conditions can be converted to ketone bodies. As a matter of fact, acetoacetate reacts with succinil-CoA to form succinate and acetoacetyl-CoA. The reported increase of succinate and fumarate allows thus to hypothesize that the Krebs cycle would proceed towards oxaloacetate, which can be used as precursor to biosynthesize amino acids, purines and pyrimidines. This was consistent with the observed significant increase of the nitrogenous bases (adenine and thymidine).
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Fig. 4. (A) PCA score plot from analysis of mussel digestive gland 1H NMR spectra showing separation of mussels (Mytilus galloprovincialis) caged in the reference site (blue square) from those transferred to the polluted area (red triangle). The ellipse represents the 95 percent confidence limit (Hotelling T2). (B) PC2 loadings plot showing the metabolic differences between individuals acclimatized for 30 days in the selected sites. Keys: (1) isoleucine, (2) leucine, (3) valine, (4) lactate, (5) arginine, (6) lysine, (7) glutamate, (8) glutamine, (9) acetoacetate, (10) succinate, (11) aspartate, (12) malonate, (13) glucose, (14) glycine, (15) unknown metabolite, (16) uracil, (17) thymidine, (18) fumarate, (19) tyrosine, (20) phenylalanine, and (21) adenine. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
In particular, mussels caged at Priolo exhibited an elevated amount of adenine in association with presence of arginine. Arginine is the end product of the reaction between phosphoarginine and ADP, in which phosphoarginine is the primary high energy phosphagen used for ATP regeneration in invertebrates (Fan et al., 1991). Thus, these data are also consistent with an alteration in ATP metabolism. Furthermore, decreased concentrations of glutamate were noticeable in mussels caged in the industrial area of Priolo, and this is consistent with the increased glycolytic metabolism. Glutamate serves as the precursor for the synthesis of glutamine, and is a constituent of some oligopeptides such as glutathione, which plays a central role in protective mechanisms against oxidative insult (Storey, 1996). Glutamate is involved in multiple metabolic pathways and plays a key role in cellular metabolism (Newsholme et al., 2003). Therefore, changes in glutamate levels may be correlative with response to environmental disturbances, suggesting glutamate as suitable metabolic biomarker.
5. Conclusions Data reported in this study revealed that the highly contaminated ‘‘Augusta-Melilli-Priolo’’ industrial area induces
marked changes in the digestive gland morphology, as well as metabolic disturbance, in caged M. galloprovincialis individuals. Therefore, the use of caged organisms and the novel NMR-based environmental metabolomics approach demonstrated to be sensitive and effective tools for site-specific assessment of pollutant toxicological mechanisms on mussel digestive gland, which has been re-confirmed as target organ for bioaccumulation of toxicants. Indeed, the metabolic biomarkers detected in this study provide evidence of the effects of environmental pollution on mussels at the cellular level. Specifically, the digestive gland metabolic profile was characterized by changes in the metabolites involved in energy metabolism that may indicate anaerobic fermentation and be related to the reduced use of metabolites in the citric acid cycle. Moreover, the increase in acetoacetate is consistent with alteration in lipid metabolism. Overall, results from this work demonstrate the effectiveness and sensitivity of metabolomics in ecotoxicological studies in assessing environmental influences on the health status of aquatic organisms. Hence, further metabolomic investigation on the selected sentinel organism is needed to gain a better understanding of how environmental pollution influences other organs.
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Table 3 Key up- or down-regulated metabolites in Mytilus galloprovincialis digestive gland identified by PCA analysis and presented together with their significance (Student’s t test). Metabolites
Chemical shift and peak shape (ppm)
Amino acids Isoleucine Leucine Valine Arginine Lysine Glutamate Glutamine Aspartate Glycine Tyrosine Phenylalanine
0.92 0.94 0.98 1.68 1.48 2.08 2.12 2.66 3.54 6.89 3.13
(t), 1.00 (d), 1.26 (m), 1.44 (m), 1.96 (m), 3.66 (d) (d), 0.96 (d), 1.66 (m), 3.71 (t) (d), 1.03 (d), 2.25 (m), 3.59 (d) (m), 1.90 (m), 3.23 (t), 3.74 (t) (m), 1.73 (m), 1.91 (m), 3.03 (t), 3.76 (t) (m), 2.34 (m), 3.74 (t) (m), 2.44 (m), 3.75 (t) (dd), 2.79 (dd), 3.87 (dd) (s) (d), 7.19 (d) (m), 3.28 (m), 3.98 (m), 7.31 (d), 7.36 (t), 7.41 (m)
m m m m m k k k k m m
0.104 0.136 0.0203 0.951 0.012 0.226 0.206 0.103 0.693 0.692 0.038
(d), 4.12 (q) (s), 3.41 (m) (s) (s) (m), 3.40 (m), 3.45 (m), 3.52 (dd), 3.73 (m), 3.82 (m), (dd), 4.63 (d), 5.22 (d) (s)
m m m k k
0.286 0.006 0.803 0.203 0.505
Fumarate
1.33 2.22 2.41 3.13 3.23 3.88 6.51
m
0.494
Osmolytes Choline Taurine Betaine Homarine
3.21 3.25 3.25 4.35
(s), (s), (s), (s),
0.847 0.504 0.709 0.922
(d), 7.54 (d) (s), 2.36 (m), 3.76 (dd), 3.83 (dd), 4.01 (q), (q), 6.28 (t), 7.63 (s) (s), 8.21 (s)
m m
0.304 2.61E 06
Adenine
5.81 1.88 4.46 8.18
m
0.047
Unknown resonances Unknown
4.15 (s)
m
0.0034
Energy metabolites Lactate Acetoacetate Succinate Malonate Glucose
Nucleotides Uracil Thymidine
3.52 3.41 3.89 7.95
(s), 4.07 (m) (t) (s) (dd), 8.02 (d), 8.53 (dd), 8.71 (d)
Acknowledgments The authors gratefully acknowledge Prof. Mark Viant (University of Birmingham, UK) for reading the manuscript and his useful suggestions. This research was supported by a National Interest Research Project (PRIN 2007-20079FELYB).
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Contents lists available at SciVerse ScienceDirect
Ecotoxicology and Environmental Safety journal homepage: www.elsevier.com/locate/ecoenv
Metabolomic investigation of Mytilus galloprovincialis (Lamarck 1819) caged in aquatic environments Salvatore Fasulo a,b, Francesco Iacono c, Tiziana Cappello c, Carmelo Corsaro d, Maria Maisano a, Alessia D’Agata a, Alessia Giannetto a, Elena De Domenico a, Vincenzo Parrino a, Giuseppe Lo Paro a, Angela Mauceri a,b,n a
Department of Animal Biology and Marine Ecology, University of Messina, Viale F. Stagno D’Alcontres 31, 98166 Messina, Italy Centro Universitario CUTGANA, Via Terzora 8, 95027 San Gregorio di Catania, Italy c Ph.D. in Biology and Cellular Biotechnologies, Department of Animal Biology and Marine Ecology, University of Messina, Viale F. Stagno D’Alcontres 31, 98166 Messina, Italy d Department of Physics, University of Messina, Viale F. Stagno D’Alcontres 31, 98166 Messina, Italy b
a r t i c l e i n f o
abstract
Article history: Received 28 December 2011 Received in revised form 29 June 2012 Accepted 2 July 2012 Available online 20 July 2012
Environmental metabolomics was applied to assess the metabolic responses in transplanted mussels to environmental pollution. Specimens of Mytilus galloprovincialis, sedentary filter-feeders, were caged in anthropogenic-impacted and reference sites along the Augusta coastline (Sicily, Italy). Chemical analysis revealed increased levels of PAHs in the digestive gland of mussels from the industrial area compared with control, and marked morphological changes were also observed. Digestive gland metabolic profiles, obtained by 1H NMR spectroscopy and analyzed by multivariate statistics, showed changes in metabolites involved in energy metabolism. Specifically, changes in lactate and acetoacetate could indicate increased anaerobic fermentation and alteration in lipid metabolism, respectively, suggesting that the mussels transplanted to the contaminated field site were suffering from adverse environmental condition. The NMR-based environmental metabolomics applied in this study results thus in it being a useful and effective tool for assessing environmental influences on the health status of aquatic organisms. & 2012 Elsevier Inc. All rights reserved.
Keywords: Caged mussels Mytilus galloprovincialis Digestive gland PAHs Metabolomics 1 H NMR
1. Introduction Metabolomics is an emerging approach to assessing the health status of organisms based on the identification of low molecular weight metabolites, whose production and levels vary with the physiological, developmental, or pathological state of cells, tissues, organs or whole organisms (Lin et al., 2006). Proton nuclear magnetic resonance (1H NMR) spectroscopy-based metabolomics, when linked with pattern recognition techniques and data mining tools, can detect differences in the profile of metabolites (metabolic biomarkers) in response to environmental stressors, diseases or exposure to toxicants (Fiehn, 2002; Hines et al., 2007; Tuffnail et al., 2009; Viant et al., 2003), thus providing an overview of the metabolic status of a biological system. Metabolite profiling, originally developed for human biomedical applications (Nicholson et al., 1988) has now been increasingly employed in several research areas, including plant science (Kim et al., 2010), n Corresponding author at: Department of Animal Biology and Marine Ecology, University of Messina, Viale F. Stagno D’Alcontres 31, 98166 Messina, Italy. Fax: þ 39 090 6765556. E-mail address: [email protected] (A. Mauceri).
0147-6513/$ - see front matter & 2012 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ecoenv.2012.07.001
food quality (Tarachiwin et al., 2008), microbial metabolomics (Boroujerdi et al., 2009) and environmental metabolomics (Viant, 2009). Because metabolomics can provide valuable information on how xenobiotics influence physiological functions, this technique has also been applied to experimental studies of selective exposure on various aquatic organisms, both invertebrates (Wu and Wang, 2010) and fish (Iacono et al., 2010; Santos et al., 2010). Pollution of coastal areas may arise from various industrial and urban sources, such as shipping, loading and bunkering operations, shipyards, accidental spills, wastewater emissions (Bocchetti et al., 2008). This may result in elevated concentrations of toxicants in the water column and sediments. In particular, harbours are generally enclosed areas characterized by poor water quality, due to a low flushing rate and human activities within or adjacent to the harbour (Yin et al., 2000). There are concerns about risk to aquatic organisms residing in inner harbours, because these organisms are exposed to high concentrations of environmental contaminants due to low hydrodynamism and intense anthropogenic impact. In this regard, the ‘‘Augusta-Melilli-Priolo’’ industrial area has been considered for this study. It extends approximately 20 km along the Augusta coastal area (eastern Sicily, Italy) and is one of the largest and
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most complex petrochemical sites in Europe, because many industrial installations can be found there, including oil refineries, chemical plants, mineral deposits, a military base and many other industrial installations (Ausili et al., 2008). Mercury (Hg) and polycyclic aromatic hydrocarbons (PAHs) are found in excessive concentrations (ICRAM, 2005). Levels of these contaminants exceed national and international regulatory guidelines, as reported in recent studies on sediments collected from the coastal zone of Augusta (Di Leonardo et al., 2008, 2007). Such pollutant mixtures (heavy metals, drugs, PAHs, polychlorinated biphenyls PCBs) can induce toxic effects at different biological levels (e.g. molecular, cellular, biochemical, physiological). Because changes at the organism level lead to changes at the population and community levels, a number of biomarkers are frequently used as early warning signals of environmental disturbance (Walker et al., 2006). In environmental monitoring studies mussels, particularly the genus Mytilus, are widely used as sentinel organisms (Fasulo et al., 2008; Hellou and Law, 2003; Viarengo et al., 2007). This is because of their wide geographical distribution, ability to tolerate a range of environmental conditions and accumulate toxic chemicals, and suitability for caging experiments at field sites (Andral et al., 2004; Romeo et al., 2003; Tsangaris et al., 2010; Viarengo et al., 2007; Wu and Shin, 1998). The use of transplanted mussels originating from a clean area allows comparison of control organisms with those caged in potentially polluted sites, and allows more control over the experiment than collection of native individuals. In addition, using caged mussels from a single population minimizes confounding factors such as the age and reproductive status of the organisms that influence both contaminant bioaccumulation and biomarker responses. Thus, a more accurate assessment of the real biological effects of pollutant exposure is possible, providing an early sign of impaired health of the ecosystem (Andral et al., 2004; Regoli, 2000; Tsangaris et al., 2010; Viarengo et al., 2007). The digestive gland is a target organ widely used in environmental toxicology because it accumulates pollutants and participates actively in the xenobiotic metabolism (Rajalakshmi and Mohandas, 2005). It is also involved in immune defense, detoxification and in homeostatic regulation (Marigomez et al., 2002; Moore and Allen, 2002), and therefore exposure to contaminants may lead to its histopathological alterations (Garmendia et al., 2011). Histopathology is a biomarker of effect for an overall assessment of the general health status of animals, and provides valuable information concerning changes in the cellular as well as sub-cellular structures of an organ or tissue much earlier than the external manifestations (Auffret, 1988; Fasulo et al., 2010a, 2010b; Ferrando et al., 2005; Livingstone and Pipe, 1992; Mauceri et al., 2002). The aim of this study was to assess biological effects of environmental pollution, mainly related to the presence of PAHs, in the caged mussel Mytilus galloprovincialis, through the use of morphological and metabolite assays. In fact, although in recent years several reports have suggested that NMR-based environmental metabolomics is a powerful tool in environmental toxicology (Viant et al., 2003), there are few studies dealing with assessment of aquatic organism health through a metabolomics based approach.
2. Materials and methods 2.1. Sites and experimental design The ‘‘Augusta-Melilli-Priolo’’ industrial area, chosen as polluted site for this study, has been declared a ‘‘site of national interest’’ by the Italian Ministry of Environment (Law No. 426/98; Ministerial Decree of 10.01.2000) owing to the high level of pollution and subsequent risk for human health. By contrast, the natural reserve of Vendicari, established in 1984 and representing a wildlife
Fig. 1. Map depicting location of the mussel caging sites.
Table 1 Mean (7 S.D.) of water physico-chemical parameters of Vendicari and Priolo. Sampling area
Vendicari
Priolo
Temperature (1C) Salinity (PSU) pH Oxygen (mg/l)
23.4 70.5 37.6 70.1 8.0 70.1 4.8 70.2
22.5 70.6 38.2 70.2 7.9 70.1 3.7 70.3
reserve in the southernmost part of the east coast of Sicily, was chosen as a nonimpacted reference site. It covers an area of 1512 ha (575 ha of a integral reserve and 937 ha of a pre-reserve) and its biological importance is due to the presence of different biotopes, e.g. rocky and sandy coastlines, Mediterranean scrub, both salt and fresh water marshes (Fig. 1). At both sampling sites, water physico-chemical parameters (temperature, salinity, pH, dissolved oxygen) were measured by a portable instrument (Multi 340i/SET, WTW Wissenschaftlich, Weilheim, Germany), as reported in Table 1. Mussels M. galloprovincialis (6.1 70.54 cm shell length) were purchased in October 2009 from a consortium of fishermen in Goro (Ferrara, Italy), a reference site in which physico-chemical parameters have been previously reported (Fasulo et al., 2008). Mussels were maintained 1 week in aerated seawater in the laboratory, and then transplanted in the two selected sites for 30 days in stainless steel cages (about 200 specimens per cage) covered with a net to guarantee free seawater circulation and protect mussels from fish predation. Cages were deployed by scuba-diving at 8 m depth below the surface both in Priolo (371120 1000 N; 151130 4400 E) and Vendicari (361 470 3500 N; 151 080 5200 E). The mussels were retrieved after 4 weeks by diving and immediately conditioned after collection on board of the experimental vessel. Fifteen male individuals from each area were selected randomly and sacrificed. Body length and mass were recorded, and digestive gland samples were rapidly excised and flash-frozen in liquid nitrogen for chemical and metabolic measurements, then transferred to the laboratory and stored at 80 1C prior to analysis. In addition, small pieces of each dissected tissue were taken for histological analysis. This study was conducted according to the guidelines for the protection of animal welfare, in compliance with the Italian National Bioethics Committee (INBC).
2.2. PAH concentration in digestive gland For PAH analysis, the following solvents and reagents were used: acetonitrile ACN (Romil), water and cyclohexane (Chromanorm BDH), acetone (Pestinorm BDH), KOH, ethanol and exane (Carlo Erba), all of HPLC grade. The digestive glands dissected from fifteen individuals were pooled in three samples (each with tissues of five specimens) per each sampling area. Approximately 3 g of each pooled sample were weighted with an analytical balance Mettler Toledo AT 104 and homogenized in a glass vial using an Ultra-TURRAX IKA T10 basic. The homogenized samples were saponified with 10 ml of 1 M KOH in an ethanol solution for
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3 h at 80 1C in a water bath. Then, 20 ml of cyclohexane was added and samples mixed by an orbital agitator for 10 min using dark glassware (Dafflon et al., 1995). The hexanic phase was recovered and the polar mixture washed once with cyclohexane and then discharged. The extracts were filtered, concentrated under a nitrogen gas stream to about 1 ml, and the concentrated extract was removed with a pasteur pipette and loaded into a Varian Bond Elut C18 cartridge 12 ml, previously conditioned. The eluates were dried under nitrogen flow and dissolved with 1 ml of acetonitrile before the analysis. The concentrations of the following sixteen PAHs identified by the EPA as priority pollutants, naphthalene (NA), acenaphthylene (ACY), acenaphthene (AC), fluorene (FL), phenanthrene (PHE), anthracene (AN), fluoranthene (FA), pyrene (PY), benzo(a)anthracene (BaA), chrysene (CH), benzo(b)fluoranthene (BbF), benzo(k)fluoranthene (BkF), benzo(a)pyrene (BaP), dibenz(a,h)anthracene (DahA), benzo(g,h,i)perylene (Bghi) and indeno(1,2,3-cd)pyrene (IP), were determined. Quantitative analysis of PAHs was carried out with a high-performance liquid chromatography (HPLC) apparatus Pro-Star 363 (Varian, Palo Alto, CA) equipped with a 20 ml loop and a fluorescence detector (FLD Pro-Star 363). The software used was Star Chromatography Workstation version 5.2 (Varian, Palo Alto, CA). The chromatographic separation was carried out using a Chromspher three PAH Varian (100 4.6 mm2) coupled with a guard column ChromSep SS 10 2 mm2, Varian. The analytical method involved a mobile phase consisting of H2O/ACN 50 percent for 5 min, which achieved 100 percent ACN in 5 min with a flow of 1 ml/min. The UV determination was performed at 255 nm, while the FL detection was conducted with six different excitation/emission wavelengths. The National Institute of Standards and Technology (NIST) Standard Reference Material SRM 1647c, consisting of an acetonitrile solution of sixteen PAHs (target compounds), was used as a calibration mixture. Percent recovery and matrix interference was assessed with reference to M. galloprovincialis tissue. The external standard multipoint calibration technique was used to determine the linear response interval of the detector and in all cases, regression coefficients were higher than 0.996 for all the analytes detected by UV, and higher than 0.989 for all the analytes detected in FL.
(Wishart, 2007) and by use of Chenomx NMR Suite (version 5.1; Chenomx Inc., Edmonton, Canada) software.
2.3. Histological analysis
3.1. PAH concentration
Digestive gland tissues of fifteen mussels from each sampling site were fixed in four percent paraformaldehyde (Immunofix, Bio-Optica Milano, Italy) in 0.1 M phosphate buffered solution (pH 7.4) at 4 1C for 3 h, dehydrated in a graded series of ethanol and embedded in Paraplast (Bio-Optica Milano, Italy), according to standard protocols (Mauceri et al., 1999). Histological sections, 5 mm thick, were cut with a rotary automatic microtome (Leica Microsystems, Wetzlar, Germany), mounted on glass slides and stained with Hematoxylin/Eosin (Bio-Optica Milano, Italy) to assess morphological features. All observations were made with a motorized Zeiss Axio Imager Z1 microscope equipped with an AxioCam digital camera (Zeiss).
For PAHs molecules containing from two to five condensed rings (NA, ACY, AC, FL, PHE, AN, FA, PY, BaA, CH, BbF, BkF, BaP, DahA) recovery was from 90 to 97 percent, while for the remaining (Bghi, IP), recovery was from 99 to 100 percent. PAH concentrations in the digestive gland samples from the reference site were lower than the instrument detection limit. By contrast, the samples from Priolo had elevated levels of PAHs, especially naphthalene and fluoranthene among light PAHs, benzo(a)pyrene and dibenzo(a,b)anthracene among high molecular weight PAHs (Table 2).
2.4. Tissue metabolite extraction Polar metabolites were extracted from the digestive gland tissues of fifteen mussels from each sampling site using a ‘‘two-step’’ methanol/chloroform procedure (Wu et al., 2008). Briefly, a 100 mg subsample of each frozen gland was homogenized in 4 ml/g of cold methanol and 0.85 ml/g of cold water by using an Ultraturrax homogenizer. The homogenates were transferred to glass vials, and 4 ml/g chloroform and 2 ml/g water were added. Samples were vortexed for 60 s, left on ice for 10 min for phase separation, and then centrifuged for 5 min at 2000g at 4 1C. Four hundred microliter of the upper methanol layer with polar metabolites were transferred to glass vials, dried in fume hood overnight and stored at 80 1C. Immediately prior to NMR analysis, the dried polar extracts were ¨ resuspended in 100 ml of D2O (Armar AG, Dottingen, Switzerland) buffered in 240 mM sodium phosphate, pH 7.0, containing 12.5 mM 2,2-dimethyl-2-silapentane-5-sulfonate (DSS) (Sigma-Aldrich Co) and vortexed. The DSS acts as an internal standard and also provides a chemical shift reference (d ¼ 0.0 ppm) for the NMR spectra, while the D2O provides a deuterium lock for the NMR spectrometer. Fifty microliter of each resuspended sample were then pipetted into a 4 mm-diameter zirconia rotors with a spherical insert and a Kel-F cap. 2.5. High resolution magic Angle spinning (HR-MAS) 1H NMR spectroscopy Extracts of digestive gland tissue from mussels were analyzed on a Bruker Avance-700 NMR spectrometer operated at a spin rate of 4000 Hz (at 300 K). Onedimensional (1-D) 1H NMR spectra were obtained using a 7.0 ms (901) pulse, 11 kHz spectral width (15.94 ppm) and 2.0 s relaxation delay with pre-saturation of the residual water resonance, with 128 transients collected into 32.768 data points requiring a 10.5 min acquisition time. Exponential line-broadenings of 0.5 Hz were applied before Fourier transformation. All 1H NMR spectra were manually phased, baseline-corrected, and calibrated (DSS at 0.0 ppm) using XWIN-NMR (version 3.5; Bruker) software. Peaks within the 1H NMR spectra were assigned with reference to known chemical shifts and peak multiplicities
2.6. Spectral processing and multivariate data analysis NMR spectra were converted to a format for multivariate analysis using custom-written ProMetab 3.3 software (Viant, 2003) in MATLAB (version R2009b; The MathWorks, Natick, MA). Each spectrum was segmented into 0.005 ppm chemical shift bins between 0.7 and 10.0 ppm, with bins from 1.12 to 1.22 and 3.62 to 3.67 ppm (ethanol for rotor cleaning), 4.70 to 5.15 ppm (water) and 7.19 to 7.28 ppm (chloroform) excluded from all the NMR spectra. Because some peaks shifted due to slight variations of the sample pH, nine groups of bins (2.382–2.457, 2.612–2.657, 3.247–3.297, 3.537–3.557, 3.867–3.907, 4.342–4.367, 4.622–4.627, 5.212–5.217 and 8.887–8.927 ppm) were each compressed into single bins. The area for each segmented region was calculated and normalized to the total integrated area of the spectra. All the NMR spectra were generalized by log transformation (with a transformation parameter, l ¼ 3.6 10 6) to stabilize the variance across the spectral bins and to increase the weightings of the less intense peaks (Wu and Wang, 2010). Data were mean-centered before Principal Components Analysis (PCA) using the Unscrambler X package (version 10.0.1; Camo Software AS, Oslo, NO) and the singular value decomposition (SVD) algorithm was applied to perform a PCA with cross validation. PCA, an unsupervised pattern recognition technique, allowed the differences and similarities between NMR metabolic fingerprints to be visualized in a score plot, where samples that are metabolically similar cluster together. The corresponding PCA loadings plot was used to identify the metabolic basis of the clustering. Representative proton peaks were normalized to total spectral area, and Student’s t tests were used to indicate the significant metabolic changes between mussel groups (Microsoft Excel).
3. Results
3.2. Histological analysis The digestive gland of M. galloprovincialis caged in the reference site (Fig. 2A) showed the typical organization of the digestive
Table 2 PAH concentrations (mean7 S.D.) in the digestive gland (mg/g). n.d.¼ not detectable. PAHs
Priolo
Vendicari
Naphthalene Acenaphthylene Acenaphtehene Fluorene Phenanthrene Anthracene Fluranthene Pyrene Benz(a)anthracene Chrysene Benzo(b)fluoranthene Benzo(k)fluoranthene Benzo(a)pyrene Dibenz(a,b)anthracene Benzo(g,h,i)perylene Indeno(1,2,3-cd)pyrene
0.912 70.038 0.011 7 0.007 0.007 70.002 0.009 70.005 o0.006 o0.006 0.187 70.012 0.008 70.004 o0.006 n.d. 0.012 7 0.007 0.008 70.002 0.060 70.017 0.925 70.028 o0.006 o0.006
n.d n.d n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
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Fig. 2. Hematoxylin and Eosin (H&E) staining in the digestive gland of Mytilus galloprovincialis caged in the reference site (A) compared with those transferred to the polluted area (B), which displayed severe histopathological alterations and relevant aggregations of haemocytes (arrow) among digestive tubules. Scale bars, 20 mm.
diverticula of bivalves, as described by Owen (1970). On the contrary, a rather irregular digestive gland morphology of mussels from the polluted area was noted (Fig. 2B). The tissue was remarkably modified and damaged, and massive haemocytic infiltration was observed among digestive tubules. 3.3. Metabolomics analysis 3.3.1. 1H NMR spectroscopy of digestive gland tissue extracts Fig. 3 shows a representative 1H NMR spectrum of the mussel digestive gland tissue extracts. Although several metabolites were identified, all spectra were found to be dominated by betaine, taurine, homarine and glycine, known to act as osmolytes. Other prominent classes of compounds included amino acids (e.g. leucine, alanine, valine), carbohydrates (e.g. glucose), tricarboxylic acid cycle intermediates (e.g. succinate), organic compounds (e.g. acetoacetate) and nucleotides (e.g. uracil). 3.3.2. Pattern recognition analysis of 1H NMR spectra The PCA scores plot of the 1H NMR metabolic fingerprints of M. galloprovincialis digestive gland (Fig. 4A) shows a clear separation between the two mussel groups caged in the selected sites along PC2 (explaining seven percent of variance). The corresponding PC2 loadings plot, depicted in Fig. 4B, was used to determine which metabolites were important in the separation of the two groups and the direction of their changes. In particular, peaks with positive loadings correspond to metabolites that have higher concentrations in ‘‘stressed’’ (specimens transplanted in the polluted area) than in the control mussels, whereas negative loadings correspond to metabolites whose concentration is decreased in the stressed group relative to the control. From the PC2 loadings plot, the metabolic profiles of digestive gland extracts from stressed individuals were characterized by significantly elevated levels (metabolite changes were calculated via the ratio between the averages of the stressed and control peak areas, Po0.05) of valine, lysine, phenylalanine, acetoacetate, nucleotides such as thymidine and adenine, and an unidentified metabolite at 4.15 ppm, together with a decreased concentration (not significant) of glucose, glutamine and glutamate, as reported in Table 3.
4. Discussion The use of caged mussels has been demonstrated to be an effective and useful tool for assessing the environmental quality status and the real biological effects induced by xenobiotics
(Andral et al., 2004; Nigro et al., 2006; Regoli, 2000; Romeo et al., 2003). In the present study, digestive glands of mussels caged for 30 days in Priolo displayed relevant histological lesions such as altered diverticula morphology and conspicuous haemocytic infiltration. This might result in impairment of its metabolic activities. Previous studies have provided evidence of haemocytic infiltration in response to exposure to hydrocarbons (Cajaraville et al., 1990) that could be interpreted as a repair process following tissue damage (Garmendia et al., 2011). While water physico-chemical parameters showed no significant difference between the two investigated areas, chemical analysis revealed high concentrations of naphthalene and fluoranthene, indicative of pyrolytic origin of the PAHs, and benzo(a)pyrene and dibenzo(a,b)anthracene, which are commonly the constituents of urban and industrial contamination, in digestive gland tissue of mussels from the polluted site. These findings are consistent with the presence of PAHs in the industrial area of Priolo. The environmental metabolomics approach here reported, based on 1HNMR spectroscopy, allows the successful investigation of the metabolic changes in response to various environmental insults (Tikunov et al., 2010). PCA analysis indicated that the mussels caged in the natural reserve of Vendicari clustered separately from those transplanted in the industrial area of Priolo, suggesting a differential metabolic profile between organisms. Specifically, the PC2 loadings plot indicated the key metabolic changes occurring in individuals acclimatized in the industrial area (relative to the control). This metabolic fingerprint is characterized by increased concentrations of branched chain amino acids (BCCA) such as valine, free amino acids, energetic metabolites, nucleotides and an unidentified metabolite, and depletion (not significant) of glucose and glutamate. Amino acid levels were markedly increased in the mussels caged at Priolo. Free amino acids represent a large fraction of the metabolome of marine invertebrates (Henry et al., 1980). It has been reported that free amino acids and their catabolites are used in marine molluscs, as well as in other marine invertebrates, as the major osmolytes to balance their intracellular osmolarity with the environment (Yancey et al., 1982). Hence, the noticeably elevated concentration of amino acids is consistent with perturbations in osmoregulatory mechanism due to exposure to toxic compounds. In addition, these pools of amino acids, except for glycine, glutamine and aspartic acid that are necessary in the biosynthesis of nitrogenous bases, are also extensively involved in cellular energy metabolism. In fact, a metabolomic study on M. edulis exposed to high dose of herbicide reported increases in leucine and isoleucine (Tuffnail et al., 2009), and this
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Fig. 3. Representative 1-D 700 MHz 1H NMR spectrum of digestive gland from mussel (Mytilus galloprovincialis) caged in the reference site, with (A) representing the aliphatic region and (B) a vertical expansion of the aromatic region. Keys: (1) DSS, (2) isoleucine, (3) leucine, (4) valine, (5) lactate, (6) alanine, (7) arginine, (8) lysine, (9) glutamate, (10) glutamine, (11) acetocetate, (12) succinate, (13) hypotaurine, (14) aspartate, (15) malonate, (16) choline, (17) taurine, (18) betaine, (19) glucose, (20) glycine, (21) homarine, (22) glycogen, (23) uracil, (24) inosine, (25) fumarate, (26) tyrosine, and (27) phenylalanine.
observation was consistent with the stimulation of metabolic activity. Changes in metabolites involved in energy metabolism were also observed. Specifically, levels of lactate increased in mussels transferred to the industrial area, indicating inhibition of aerobic metabolism (Wu and Wang, 2010). The observed depletion in glucose accompanied by the concomitant increase in lactate indicates then an enhancement in anaerobic metabolism. In addition to the metabolic changes associated with energetic pathways, increases in acetoacetate were found in digestive gland of mussels caged in Priolo. Acetoacetate is a compound categorized as ketone body, and synthesized from three molecules of
acetyl-coenzyme A (acetyl-CoA) as end product of fatty acid oxidation. The increase in acetoacetate is then consistent with an alteration in lipid metabolism. Alternatively, some amino acids, such as phenylalanine, lysine, isoleucine, leucine and tyrosine, under certain metabolic conditions can be converted to ketone bodies. As a matter of fact, acetoacetate reacts with succinil-CoA to form succinate and acetoacetyl-CoA. The reported increase of succinate and fumarate allows thus to hypothesize that the Krebs cycle would proceed towards oxaloacetate, which can be used as precursor to biosynthesize amino acids, purines and pyrimidines. This was consistent with the observed significant increase of the nitrogenous bases (adenine and thymidine).
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Fig. 4. (A) PCA score plot from analysis of mussel digestive gland 1H NMR spectra showing separation of mussels (Mytilus galloprovincialis) caged in the reference site (blue square) from those transferred to the polluted area (red triangle). The ellipse represents the 95 percent confidence limit (Hotelling T2). (B) PC2 loadings plot showing the metabolic differences between individuals acclimatized for 30 days in the selected sites. Keys: (1) isoleucine, (2) leucine, (3) valine, (4) lactate, (5) arginine, (6) lysine, (7) glutamate, (8) glutamine, (9) acetoacetate, (10) succinate, (11) aspartate, (12) malonate, (13) glucose, (14) glycine, (15) unknown metabolite, (16) uracil, (17) thymidine, (18) fumarate, (19) tyrosine, (20) phenylalanine, and (21) adenine. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
In particular, mussels caged at Priolo exhibited an elevated amount of adenine in association with presence of arginine. Arginine is the end product of the reaction between phosphoarginine and ADP, in which phosphoarginine is the primary high energy phosphagen used for ATP regeneration in invertebrates (Fan et al., 1991). Thus, these data are also consistent with an alteration in ATP metabolism. Furthermore, decreased concentrations of glutamate were noticeable in mussels caged in the industrial area of Priolo, and this is consistent with the increased glycolytic metabolism. Glutamate serves as the precursor for the synthesis of glutamine, and is a constituent of some oligopeptides such as glutathione, which plays a central role in protective mechanisms against oxidative insult (Storey, 1996). Glutamate is involved in multiple metabolic pathways and plays a key role in cellular metabolism (Newsholme et al., 2003). Therefore, changes in glutamate levels may be correlative with response to environmental disturbances, suggesting glutamate as suitable metabolic biomarker.
5. Conclusions Data reported in this study revealed that the highly contaminated ‘‘Augusta-Melilli-Priolo’’ industrial area induces
marked changes in the digestive gland morphology, as well as metabolic disturbance, in caged M. galloprovincialis individuals. Therefore, the use of caged organisms and the novel NMR-based environmental metabolomics approach demonstrated to be sensitive and effective tools for site-specific assessment of pollutant toxicological mechanisms on mussel digestive gland, which has been re-confirmed as target organ for bioaccumulation of toxicants. Indeed, the metabolic biomarkers detected in this study provide evidence of the effects of environmental pollution on mussels at the cellular level. Specifically, the digestive gland metabolic profile was characterized by changes in the metabolites involved in energy metabolism that may indicate anaerobic fermentation and be related to the reduced use of metabolites in the citric acid cycle. Moreover, the increase in acetoacetate is consistent with alteration in lipid metabolism. Overall, results from this work demonstrate the effectiveness and sensitivity of metabolomics in ecotoxicological studies in assessing environmental influences on the health status of aquatic organisms. Hence, further metabolomic investigation on the selected sentinel organism is needed to gain a better understanding of how environmental pollution influences other organs.
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Table 3 Key up- or down-regulated metabolites in Mytilus galloprovincialis digestive gland identified by PCA analysis and presented together with their significance (Student’s t test). Metabolites
Chemical shift and peak shape (ppm)
Amino acids Isoleucine Leucine Valine Arginine Lysine Glutamate Glutamine Aspartate Glycine Tyrosine Phenylalanine
0.92 0.94 0.98 1.68 1.48 2.08 2.12 2.66 3.54 6.89 3.13
(t), 1.00 (d), 1.26 (m), 1.44 (m), 1.96 (m), 3.66 (d) (d), 0.96 (d), 1.66 (m), 3.71 (t) (d), 1.03 (d), 2.25 (m), 3.59 (d) (m), 1.90 (m), 3.23 (t), 3.74 (t) (m), 1.73 (m), 1.91 (m), 3.03 (t), 3.76 (t) (m), 2.34 (m), 3.74 (t) (m), 2.44 (m), 3.75 (t) (dd), 2.79 (dd), 3.87 (dd) (s) (d), 7.19 (d) (m), 3.28 (m), 3.98 (m), 7.31 (d), 7.36 (t), 7.41 (m)
m m m m m k k k k m m
0.104 0.136 0.0203 0.951 0.012 0.226 0.206 0.103 0.693 0.692 0.038
(d), 4.12 (q) (s), 3.41 (m) (s) (s) (m), 3.40 (m), 3.45 (m), 3.52 (dd), 3.73 (m), 3.82 (m), (dd), 4.63 (d), 5.22 (d) (s)
m m m k k
0.286 0.006 0.803 0.203 0.505
Fumarate
1.33 2.22 2.41 3.13 3.23 3.88 6.51
m
0.494
Osmolytes Choline Taurine Betaine Homarine
3.21 3.25 3.25 4.35
(s), (s), (s), (s),
0.847 0.504 0.709 0.922
(d), 7.54 (d) (s), 2.36 (m), 3.76 (dd), 3.83 (dd), 4.01 (q), (q), 6.28 (t), 7.63 (s) (s), 8.21 (s)
m m
0.304 2.61E 06
Adenine
5.81 1.88 4.46 8.18
m
0.047
Unknown resonances Unknown
4.15 (s)
m
0.0034
Energy metabolites Lactate Acetoacetate Succinate Malonate Glucose
Nucleotides Uracil Thymidine
3.52 3.41 3.89 7.95
(s), 4.07 (m) (t) (s) (dd), 8.02 (d), 8.53 (dd), 8.71 (d)
Acknowledgments The authors gratefully acknowledge Prof. Mark Viant (University of Birmingham, UK) for reading the manuscript and his useful suggestions. This research was supported by a National Interest Research Project (PRIN 2007-20079FELYB).
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