Metabolomic investigation of Mytilus galloprovincialis (Lamarck 1819) caged in aquatic environments
-
Upload
independent -
Category
Documents
-
view
0 -
download
0
Transcript of Metabolomic investigation of Mytilus galloprovincialis (Lamarck 1819) caged in aquatic environments
Ecotoxicology and Environmental Safety 84 (2012) 139–146
Contents lists available at SciVerse ScienceDirect
Ecotoxicology and Environmental Safety
0147-65
http://d
n Corr
Univers
Fax: þ3
E-m
journal homepage: www.elsevier.com/locate/ecoenv
Metabolomic investigation of Mytilus galloprovincialis (Lamarck 1819) cagedin 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, Italyb Centro Universitario CUTGANA, Via Terzora 8, 95027 San Gregorio di Catania, Italyc 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, Italyd Department of Physics, University of Messina, Viale F. Stagno D’Alcontres 31, 98166 Messina, Italy
a r t i c l e i n f o
Article history:
Received 28 December 2011
Received in revised form
29 June 2012
Accepted 2 July 2012Available online 20 July 2012
Keywords:
Caged mussels
Mytilus galloprovincialis
Digestive gland
PAHs
Metabolomics1H NMR
13/$ - see front matter & 2012 Elsevier Inc. A
x.doi.org/10.1016/j.ecoenv.2012.07.001
esponding author at: Department of Animal
ity of Messina, Viale F. Stagno D’Alcontre
9 090 6765556.
ail address: [email protected] (A. Mau
a b s t r a c t
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.
1. Introduction
Metabolomics is an emerging approach to assessing the healthstatus of organisms based on the identification of low molecularweight metabolites, whose production and levels vary with thephysiological, developmental, or pathological state of cells, tis-sues, organs or whole organisms (Lin et al., 2006). Proton nuclearmagnetic resonance (1H NMR) spectroscopy-based metabolomics,when linked with pattern recognition techniques and data miningtools, can detect differences in the profile of metabolites (meta-bolic biomarkers) in response to environmental stressors, dis-eases or exposure to toxicants (Fiehn, 2002; Hines et al., 2007;Tuffnail et al., 2009; Viant et al., 2003), thus providing an over-view of the metabolic status of a biological system. Metaboliteprofiling, originally developed for human biomedical applications(Nicholson et al., 1988) has now been increasingly employed inseveral research areas, including plant science (Kim et al., 2010),
ll rights reserved.
Biology and Marine Ecology,
s 31, 98166 Messina, Italy.
ceri).
food quality (Tarachiwin et al., 2008), microbial metabolomics(Boroujerdi et al., 2009) and environmental metabolomics (Viant,2009). Because metabolomics can provide valuable informationon how xenobiotics influence physiological functions, this tech-nique has also been applied to experimental studies of selectiveexposure on various aquatic organisms, both invertebrates (Wuand Wang, 2010) and fish (Iacono et al., 2010; Santos et al., 2010).
Pollution of coastal areas may arise from various industrialand urban sources, such as shipping, loading and bunkeringoperations, shipyards, accidental spills, wastewater emissions(Bocchetti et al., 2008). This may result in elevated concentrationsof toxicants in the water column and sediments. In particular,harbours are generally enclosed areas characterized by poorwater quality, due to a low flushing rate and human activitieswithin or adjacent to the harbour (Yin et al., 2000). There areconcerns about risk to aquatic organisms residing in innerharbours, because these organisms are exposed to high concen-trations of environmental contaminants due to low hydrodyna-mism and intense anthropogenic impact. In this regard, the‘‘Augusta-Melilli-Priolo’’ industrial area has been considered forthis study. It extends approximately 20 km along the Augustacoastal area (eastern Sicily, Italy) and is one of the largest and
Fig. 1. Map depicting location of the mussel caging sites.
Table 1Mean (7S.D.) of water physico-chemical parameters of Vendicari and Priolo.
Sampling area Vendicari Priolo
Temperature (1C) 23.470.5 22.570.6
Salinity (PSU) 37.670.1 38.270.2
pH 8.070.1 7.970.1
Oxygen (mg/l) 4.870.2 3.770.3
S. Fasulo et al. / Ecotoxicology and Environmental Safety 84 (2012) 139–146140
most complex petrochemical sites in Europe, because manyindustrial installations can be found there, including oil refineries,chemical plants, mineral deposits, a military base and many otherindustrial installations (Ausili et al., 2008). Mercury (Hg) andpolycyclic aromatic hydrocarbons (PAHs) are found in excessiveconcentrations (ICRAM, 2005). Levels of these contaminantsexceed national and international regulatory guidelines, asreported in recent studies on sediments collected from the coastalzone of Augusta (Di Leonardo et al., 2008, 2007).
Such pollutant mixtures (heavy metals, drugs, PAHs, poly-chlorinated biphenyls PCBs) can induce toxic effects at differentbiological levels (e.g. molecular, cellular, biochemical, physiologi-cal). Because changes at the organism level lead to changes at thepopulation and community levels, a number of biomarkers arefrequently used as early warning signals of environmental dis-turbance (Walker et al., 2006).
In environmental monitoring studies mussels, particularly thegenus Mytilus, are widely used as sentinel organisms (Fasulo et al.,2008; Hellou and Law, 2003; Viarengo et al., 2007). This is becauseof their wide geographical distribution, ability to tolerate a range ofenvironmental conditions and accumulate toxic chemicals, andsuitability for caging experiments at field sites (Andral et al., 2004;Romeo et al., 2003; Tsangaris et al., 2010; Viarengo et al., 2007; Wuand Shin, 1998). The use of transplanted mussels originating from aclean area allows comparison of control organisms with those cagedin potentially polluted sites, and allows more control over theexperiment than collection of native individuals. In addition, usingcaged mussels from a single population minimizes confoundingfactors such as the age and reproductive status of the organisms thatinfluence both contaminant bioaccumulation and biomarkerresponses. Thus, a more accurate assessment of the real biologicaleffects of pollutant exposure is possible, providing an early sign ofimpaired 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 environ-mental toxicology because it accumulates pollutants and partici-pates actively in the xenobiotic metabolism (Rajalakshmi andMohandas, 2005). It is also involved in immune defense, detoxifica-tion and in homeostatic regulation (Marigomez et al., 2002; Mooreand Allen, 2002), and therefore exposure to contaminants may leadto its histopathological alterations (Garmendia et al., 2011).
Histopathology is a biomarker of effect for an overall assessmentof the general health status of animals, and provides valuableinformation concerning changes in the cellular as well as sub-cellularstructures of an organ or tissue much earlier than the externalmanifestations (Auffret, 1988; Fasulo et al., 2010a, 2010b; Ferrandoet al., 2005; Livingstone and Pipe, 1992; Mauceri et al., 2002).
The aim of this study was to assess biological effects ofenvironmental pollution, mainly related to the presence of PAHs,in the caged mussel Mytilus galloprovincialis, through the use ofmorphological and metabolite assays. In fact, although in recentyears several reports have suggested that NMR-based environ-mental metabolomics is a powerful tool in environmental tox-icology (Viant et al., 2003), there are few studies dealing withassessment of aquatic organism health through a metabolomicsbased 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
reserve in the southernmost part of the east coast of Sicily, was chosen as a non-
impacted 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 (6.170.54 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
(3711201000N; 1511304400E) 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 homo-
genized samples were saponified with 10 ml of 1 M KOH in an ethanol solution for
Table 2PAH concentrations (mean7S.D.) in the digestive gland (mg/g). n.d.¼not
detectable.
PAHs Priolo Vendicari
Naphthalene 0.91270.038 n.d
Acenaphthylene 0.01170.007 n.d
Acenaphtehene 0.00770.002 n.d.
Fluorene 0.00970.005 n.d.
Phenanthrene o0.006 n.d.
Anthracene o0.006 n.d.
Fluranthene 0.18770.012 n.d.
Pyrene 0.00870.004 n.d.
Benz(a)anthracene o0.006 n.d.
Chrysene n.d. n.d.
Benzo(b)fluoranthene 0.01270.007 n.d.
Benzo(k)fluoranthene 0.00870.002 n.d.
Benzo(a)pyrene 0.06070.017 n.d.
Dibenz(a,b)anthracene 0.92570.028 n.d.
Benzo(g,h,i)perylene o0.006 n.d.
Indeno(1,2,3-cd)pyrene o0.006 n.d.
S. Fasulo et al. / Ecotoxicology and Environmental Safety 84 (2012) 139–146 141
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 Mate-
rial 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.
2.3. Histological analysis
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).
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 proce-
dure (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-silapen-
tane-5-sulfonate (DSS) (Sigma-Aldrich Co) and vortexed. The DSS acts as an
internal standard and also provides a chemical shift reference (d¼0.0 ppm) for
the NMR spectra, while the D2O provides a deuterium lock for the NMR spectro-
meter. 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). One-
dimensional (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
(Wishart, 2007) and by use of Chenomx NMR Suite (version 5.1; Chenomx Inc.,
Edmonton, Canada) software.
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, l¼3.6�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 Compo-
nents 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
3.1. PAH concentration
For PAHs molecules containing from two to five condensedrings (NA, ACY, AC, FL, PHE, AN, FA, PY, BaA, CH, BbF, BkF, BaP,DahA) recovery was from 90 to 97 percent, while for theremaining (Bghi, IP), recovery was from 99 to 100 percent.
PAH concentrations in the digestive gland samples from thereference site were lower than the instrument detection limit. Bycontrast, 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 molecu-lar weight PAHs (Table 2).
3.2. Histological analysis
The digestive gland of M. galloprovincialis caged in the refer-ence site (Fig. 2A) showed the typical organization of the digestive
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.
S. Fasulo et al. / Ecotoxicology and Environmental Safety 84 (2012) 139–146142
diverticula of bivalves, as described by Owen (1970). On thecontrary, a rather irregular digestive gland morphology of mus-sels from the polluted area was noted (Fig. 2B). The tissue wasremarkably modified and damaged, and massive haemocyticinfiltration 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 musseldigestive gland tissue extracts. Although several metaboliteswere identified, all spectra were found to be dominated bybetaine, taurine, homarine and glycine, known to act as osmo-lytes. Other prominent classes of compounds included aminoacids (e.g. leucine, alanine, valine), carbohydrates (e.g. glucose),tricarboxylic acid cycle intermediates (e.g. succinate), organiccompounds (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 ofM. galloprovincialis digestive gland (Fig. 4A) shows a clear separa-tion between the two mussel groups caged in the selected sitesalong PC2 (explaining seven percent of variance). The correspond-ing PC2 loadings plot, depicted in Fig. 4B, was used to determinewhich metabolites were important in the separation of thetwo groups and the direction of their changes. In particular,peaks with positive loadings correspond to metabolites that havehigher concentrations in ‘‘stressed’’ (specimens transplanted inthe polluted area) than in the control mussels, whereas negativeloadings correspond to metabolites whose concentration isdecreased in the stressed group relative to the control. From thePC2 loadings plot, the metabolic profiles of digestive glandextracts from stressed individuals were characterized by signifi-cantly elevated levels (metabolite changes were calculated via theratio between the averages of the stressed and control peak areas,Po0.05) of valine, lysine, phenylalanine, acetoacetate, nucleo-tides such as thymidine and adenine, and an unidentified meta-bolite at 4.15 ppm, together with a decreased concentration(not significant) of glucose, glutamine and glutamate, as reportedin Table 3.
4. Discussion
The use of caged mussels has been demonstrated to be aneffective and useful tool for assessing the environmental qualitystatus and the real biological effects induced by xenobiotics
(Andral et al., 2004; Nigro et al., 2006; Regoli, 2000; Romeoet al., 2003).
In the present study, digestive glands of mussels caged for30 days in Priolo displayed relevant histological lesions such asaltered diverticula morphology and conspicuous haemocyticinfiltration. This might result in impairment of its metabolicactivities. Previous studies have provided evidence of haemocyticinfiltration in response to exposure to hydrocarbons (Cajaravilleet al., 1990) that could be interpreted as a repair process followingtissue damage (Garmendia et al., 2011).
While water physico-chemical parameters showed no signifi-cant difference between the two investigated areas, chemicalanalysis revealed high concentrations of naphthalene and fluor-anthene, indicative of pyrolytic origin of the PAHs, and benzo(a)-pyrene and dibenzo(a,b)anthracene, which are commonly theconstituents of urban and industrial contamination, in digestivegland tissue of mussels from the polluted site. These findings areconsistent with the presence of PAHs in the industrial area ofPriolo.
The environmental metabolomics approach here reported,based on 1HNMR spectroscopy, allows the successful investiga-tion of the metabolic changes in response to various environ-mental insults (Tikunov et al., 2010). PCA analysis indicated thatthe mussels caged in the natural reserve of Vendicari clusteredseparately from those transplanted in the industrial area of Priolo,suggesting a differential metabolic profile between organisms.Specifically, the PC2 loadings plot indicated the key metabolicchanges occurring in individuals acclimatized in the industrialarea (relative to the control). This metabolic fingerprint is char-acterized by increased concentrations of branched chain aminoacids (BCCA) such as valine, free amino acids, energetic metabo-lites, nucleotides and an unidentified metabolite, and depletion(not significant) of glucose and glutamate.
Amino acid levels were markedly increased in the musselscaged at Priolo. Free amino acids represent a large fraction of themetabolome of marine invertebrates (Henry et al., 1980). It hasbeen reported that free amino acids and their catabolites are usedin marine molluscs, as well as in other marine invertebrates,as the major osmolytes to balance their intracellular osmolaritywith the environment (Yancey et al., 1982). Hence, the noticeablyelevated concentration of amino acids is consistent withperturbations in osmoregulatory mechanism due to exposure totoxic compounds. In addition, these pools of amino acids, exceptfor glycine, glutamine and aspartic acid that are necessaryin the biosynthesis of nitrogenous bases, are also extensivelyinvolved in cellular energy metabolism. In fact, a metabolomicstudy on M. edulis exposed to high dose of herbicide reportedincreases in leucine and isoleucine (Tuffnail et al., 2009), and this
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.
S. Fasulo et al. / Ecotoxicology and Environmental Safety 84 (2012) 139–146 143
observation was consistent with the stimulation of metabolicactivity.
Changes in metabolites involved in energy metabolism werealso observed. Specifically, levels of lactate increased in musselstransferred to the industrial area, indicating inhibition of aerobicmetabolism (Wu and Wang, 2010). The observed depletion inglucose accompanied by the concomitant increase in lactateindicates then an enhancement in anaerobic metabolism.
In addition to the metabolic changes associated with energeticpathways, increases in acetoacetate were found in digestive glandof mussels caged in Priolo. Acetoacetate is a compound categor-ized as ketone body, and synthesized from three molecules of
acetyl-coenzyme A (acetyl-CoA) as end product of fatty acidoxidation. The increase in acetoacetate is then consistent withan alteration in lipid metabolism. Alternatively, some aminoacids, such as phenylalanine, lysine, isoleucine, leucine andtyrosine, under certain metabolic conditions can be converted toketone bodies. As a matter of fact, acetoacetate reacts withsuccinil-CoA to form succinate and acetoacetyl-CoA. The reportedincrease of succinate and fumarate allows thus to hypothesizethat the Krebs cycle would proceed towards oxaloacetate, whichcan be used as precursor to biosynthesize amino acids, purinesand pyrimidines. This was consistent with the observed signifi-cant increase of the nitrogenous bases (adenine and thymidine).
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.)
S. Fasulo et al. / Ecotoxicology and Environmental Safety 84 (2012) 139–146144
In particular, mussels caged at Priolo exhibited an elevatedamount of adenine in association with presence of arginine.Arginine is the end product of the reaction between phosphoar-ginine and ADP, in which phosphoarginine is the primary highenergy phosphagen used for ATP regeneration in invertebrates(Fan et al., 1991). Thus, these data are also consistent with analteration in ATP metabolism.
Furthermore, decreased concentrations of glutamate werenoticeable in mussels caged in the industrial area of Priolo, andthis 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 againstoxidative insult (Storey, 1996). Glutamate is involved in multiplemetabolic pathways and plays a key role in cellular metabolism(Newsholme et al., 2003). Therefore, changes in glutamate levelsmay be correlative with response to environmental disturbances,suggesting glutamate as suitable metabolic biomarker.
5. Conclusions
Data reported in this study revealed that the highlycontaminated ‘‘Augusta-Melilli-Priolo’’ industrial area induces
marked changes in the digestive gland morphology, as wellas metabolic disturbance, in caged M. galloprovincialis individuals.Therefore, the use of caged organisms and the novelNMR-based environmental metabolomics approach demon-strated to be sensitive and effective tools for site-specificassessment of pollutant toxicological mechanisms on musseldigestive gland, which has been re-confirmed as targetorgan for bioaccumulation of toxicants. Indeed, the metabolicbiomarkers detected in this study provide evidence of theeffects of environmental pollution on mussels at the cellularlevel.
Specifically, the digestive gland metabolic profile was char-acterized by changes in the metabolites involved in energymetabolism that may indicate anaerobic fermentation and berelated to the reduced use of metabolites in the citric acid cycle.Moreover, the increase in acetoacetate is consistent with altera-tion in lipid metabolism.
Overall, results from this work demonstrate the effectivenessand sensitivity of metabolomics in ecotoxicological studies inassessing environmental influences on the health status ofaquatic organisms. Hence, further metabolomic investigationon the selected sentinel organism is needed to gain a betterunderstanding of how environmental pollution influences otherorgans.
Table 3Key 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) p-Value
Amino acids
Isoleucine 0.92 (t), 1.00 (d), 1.26 (m), 1.44 (m), 1.96 (m), 3.66 (d) m 0.104
Leucine 0.94 (d), 0.96 (d), 1.66 (m), 3.71 (t) m 0.136
Valine 0.98 (d), 1.03 (d), 2.25 (m), 3.59 (d) m 0.0203
Arginine 1.68 (m), 1.90 (m), 3.23 (t), 3.74 (t) m 0.951
Lysine 1.48 (m), 1.73 (m), 1.91 (m), 3.03 (t), 3.76 (t) m 0.012
Glutamate 2.08 (m), 2.34 (m), 3.74 (t) k 0.226
Glutamine 2.12 (m), 2.44 (m), 3.75 (t) k 0.206
Aspartate 2.66 (dd), 2.79 (dd), 3.87 (dd) k 0.103
Glycine 3.54 (s) k 0.693
Tyrosine 6.89 (d), 7.19 (d) m 0.692
Phenylalanine 3.13 (m), 3.28 (m), 3.98 (m), 7.31 (d), 7.36 (t), 7.41 (m) m 0.038
Energy metabolites
Lactate 1.33 (d), 4.12 (q) m 0.286
Acetoacetate 2.22 (s), 3.41 (m) m 0.006
Succinate 2.41 (s) m 0.803
Malonate 3.13 (s) k 0.203
Glucose 3.23 (m), 3.40 (m), 3.45 (m), 3.52 (dd), 3.73 (m), 3.82 (m),
3.88 (dd), 4.63 (d), 5.22 (d)
k 0.505
Fumarate 6.51 (s) m 0.494
Osmolytes
Choline 3.21 (s), 3.52 (s), 4.07 (m) � 0.847
Taurine 3.25 (s), 3.41 (t) � 0.504
Betaine 3.25 (s), 3.89 (s) � 0.709
Homarine 4.35 (s), 7.95 (dd), 8.02 (d), 8.53 (dd), 8.71 (d) � 0.922
Nucleotides
Uracil 5.81 (d), 7.54 (d) m 0.304
Thymidine 1.88 (s), 2.36 (m), 3.76 (dd), 3.83 (dd), 4.01 (q),
4.46 (q), 6.28 (t), 7.63 (s)
m 2.61E�06
Adenine 8.18 (s), 8.21 (s) m 0.047
Unknown resonances
Unknown 4.15 (s) m 0.0034
S. Fasulo et al. / Ecotoxicology and Environmental Safety 84 (2012) 139–146 145
Acknowledgments
The authors gratefully acknowledge Prof. Mark Viant (Univer-sity of Birmingham, UK) for reading the manuscript and his usefulsuggestions. This research was supported by a National InterestResearch Project (PRIN 2007-20079FELYB).
References
Andral, B., Stanisiere, J.Y., Sauzade, D., Damier, E., Thebault, H., Galgani, F., Boissery,P., 2004. Monitoring chemical contamination levels in the Mediterraneanbased on the use of mussel caging. Mar. Pollut. Bull. 49, 704–712.
Auffret, M., 1988. Histopathological changes related to chemical contamination inMytilus edulis from field and experimental conditions. Mar. Ecol.-Prog. Ser. 46,101–107.
Ausili, A., Gabellini, M., Cammarata, G., Fattorini, D., Benedetti, M., Pisanelli, B.,Gorbi, S., Regoli, F., 2008. Ecotoxicological and human health risk in apetrochemical district of southern Italy. Mar. Environ. Res. 66, 217–219.
Bocchetti, R., Fattorini, D., Pisanelli, B., Macchia, S., Oliviero, L., Pilato, F., Pellegrini,D., Regoli, F., 2008. Contaminant accumulation and biomarker responses incaged mussels, Mytilus galloprovincialis, to evaluate bioavailability and tox-icological effects of remobilized chemicals during dredging and disposaloperations in harbour areas. Aquat. Toxicol. 89, 257–266.
Boroujerdi, A.F., Vizcaino, M.I., Meyers, A., Pollock, E.C., Huynh, S.L., Schock, T.B.,Morris, P.J., Bearden, D.W., 2009. NMR-based microbial metabolomics and thetemperature-dependent coral pathogen Vibrio coralliilyticus. Environ. Sci.Technol. 43, 7658–7664.
Cajaraville, M.P., Diez, G., Marigomez, I., Angulo, E., 1990. Responses of thebasophlic cells of the digestive land of mussels to petroleum hydrocarbonexposure. Dis. Aquat. Org. 9, 221–228.
Dafflon, O., Gobet, H., Koch, H., Bosset, J.O., 1995. Le dosage des hydrocarburesaromatiques polycycliques dans le poisson, les produites carne�s et le fromagepar chromatographie liquide a’haute performance. Trav. Chim. Aliment Hyg.86, 534–555.
Di Leonardo, R., Bellanca, A., Angelone, M., Leonardi, M., Neri, R., 2008. Impact of
human activities on the central Mediterranean offshore: evidence from Hg
distribution in box-core sediments from the Ionian Sea. Appl. Geochem. 23,
3756–3766.Di Leonardo, R., Bellanca, A., Capotondi, L., Cundy, A., Neri, R., 2007. Possible
impacts of Hg and PAH contamination on benthic foraminiferal assemblages:
an example from the Sicilian coast, central Mediterranean. Sci. Total Environ.
388, 168–183.Fan, T.W.M., Higashi, R.M., Macdonald, J.M., 1991. Emergence and recovery
response of phosphate metabolites and intracellular Ph in intact Mytilus
edulis as examined insitu by invivo P-31-NMR. Biochim. Biophys. Acta 1092,
39–47.Fasulo, S., Marino, S., Mauceri, A., Maisano, M., Giannetto, A., D’Agata, A., Parrino,
V., Minutoli, R., De Domenico, E., 2010a. A multibiomarker approach in Coris
julis living in a natural environment. Ecotoxicol. Environ. Safe. 73, 1565–1573.Fasulo, S., Mauceri, A., Giannetto, A., Maisano, M., Bianchi, N., Parrino, V., 2008.
Expression of metallothionein mRNAs by in situ hybridization in the gills of
Mytilus galloprovincialis, from natural polluted environments. Aquat. Toxicol.
88, 62–68.Fasulo, S., Mauceri, A., Maisano, M., Giannetto, A., Parrino, V., Gennuso, F., D’Agata,
A., 2010b. Immunohistochemical and molecular biomarkers in Coris julis
exposed to environmental contaminants. Ecotoxicol. Environ. Saf. 73,
873–882.Ferrando, S., Ferrando, T., Girosi, L., Mauceri, A., Fasulo, S., Tagliafierro, G., 2005.
Apoptosis, cell proliferation and serotonin immunoreactivity in gut of Liza
aurata from natural heavy metal polluted environments: preliminary observa-
tions. Eur. J. Histochem. 49, 331–340.Fiehn, O., 2002. Metabolomics—the link between genotypes and phenotypes. Plant
Mol. Biol. 48, 155–171.Garmendia, L., Soto, M., Vicario, U., Kim, Y., Cajaraville, M.P., Marigomez, I., 2011.
Application of a battery of biomarkers in mussel digestive gland to assess
long-term effects of the Prestige oil spill in Galicia and Bay of Biscay: tissue-
level biomarkers and histopathology. J. Environ. Monit. 13, 915–932.Hellou, J., Law, R.J., 2003. Stress on stress response of wild mussels, Mytilus edulis
and Mytilus trossulus, as an indicator of ecosystem health. Environ. Pollut. 126,
407–416.
S. Fasulo et al. / Ecotoxicology and Environmental Safety 84 (2012) 139–146146
Henry, R.P., Mangum, C.P., Webb, K.L., 1980. Salt and water balance in theoligohaline clam, Rangia cuneata II. Accumulation of intracellular free aminoacids during high salinity adaptation. J. Exp. Zool. 211, 11–24.
Hines, A., Oladiran, G.S., Bignell, J.P., Stentiford, G.D., Viant, M.R., 2007. Directsampling of organisms from the field and knowledge of their phenotype: keyrecommendations for environmental metabolomics. Environ. Sci. Technol. 41,3375–3381.
Iacono, F., Cappello, T., Corsaro, C., Branca, C., Maisano, M., Gioffre, G., DeDomenico, E., Mauceri, A., Fasulo, S., 2010. Environmental metabolomics andmultibiomarker approaches on biomonitoring of aquatic habitats. Comp.Biochem. Physiol. A 157, S50-S50.
Istituto Centrale per la Ricerca scientifica e tecnologica Applicata al Mare (ICRAM),2005. Valutazione preliminare dei dati della caratterizzazione ambientaledella Rada di Augusta - aree prioritarie ai fini della messa in sicurezza diemergenza. Sito di bonifica di interesse nazionale di Priolo. BoIPr-SI-GP-Radadi Augusta-01.02. Roma, 33.
Kim, H.K., Choi, Y.H., Verpoorte, R., 2010. NMR-based metabolomic analysis ofplants. Nat. Protoc. 5, 536–549.
Law No. 426 of 9.12.1998. Nuovi interventi in campo ambientale. G.U. n. 291,14.12.1998.
Lin, C.Y., Viant, M.R., Tjeerdema, R.S., 2006. Metabolomics: methodologies andapplications in the environmental sciences. J. Pestic. Sci. 31, 245–251.
Livingstone, D.R., Pipe, R.K., 1992. Mussels and environmental contaminants:molecular and cellular aspects. In: Gossling, E. (Ed.), Development in Aqua-culture and Fishery Science. Elsevier Pub. Co., Amsterdam, pp. 425–456.
Marigomez, I., Soto, M., Cajaraville, M.P., Angulo, E., Giamberini, L., 2002. Cellularand subcellular distribution of metals in molluscs. Microsc. Res. Tech. 56,358–392.
Mauceri, A., Fasulo, S., Ainis, L., Licata, A., Lauriano, E.R., Martinez, A., Mayer, B.,Zaccone, G., 1999. Neuronal nitric oxide synthase (nNOS) expression in theepithelial neuroendocrine cell system and nerve fibers in the gill of the catfish,Heteropneustes fossilis. Acta Histochem. 101, 437–448.
Mauceri, A., Tigano, C., Ferrito, V., Barbaro, B., Calderaro, M., Ainis, L., Fasulo, S.,2002. Effect of natural confinement on the gill cell types and bony elements ofLebias fasciata (Teleostei, Cyprinodontidae): a morphological and immunohis-tochemical analysis. Ital. J. Zool. 69, 195–203.
Ministerial Decree of 10.01.2000. Perimetrazione del sito di interesse nazionale diGela e Priolo. G.U. n. 44, 23.02.2000.
Moore, M.N. and Allen, J.I. 2002. A computational model of the digestive glandepithelial cell of marine mussels and its simulated responses to oil-derivedaromatic.
Newsholme, P., Procopio, J., Lima, M.M., Pithon-Curi, T.C., Curi, R., 2003. Glutamineand glutamate—their central role in cell metabolism and function. CellBiochem. Funct. 21, 1–9.
Nicholson, J.K., Walshe, J.A., Wilson, I.D., 1988. Application of high resolution 1HNMR spectroscopy to the detection of penicillamine and its metabolites inhuman urine. Drug Metab. Drug Interact. 6, 439–446.
Nigro, M., Falleni, A., Barga, I.D., Scarcelli, V., Lucchesi, P., Regoli, F., Frenzilli, G.,2006. Cellular biomarkers for monitoring estuarine environments: trans-planted versus native mussels. Aquat. Toxicol. 77, 339–347.
Owen, G., 1970. The fine structure of the digestive tubules of the marine bivalveCardium edule. Philos. Trans. R. Soc. 258, 245–260.
Rajalakshmi, S., Mohandas, A., 2005. Copper-induced changes in tissue enzymeactivity in a freshwater mussel. Ecotoxicol. Environ. Safe. 62, 140–143.
Regoli, F., 2000. Total oxyradical scavenging capacity (TOSC) in polluted andtranslocated mussels: a predictive biomarker of oxidative stress. Aquat.Toxicol. 50, 351–361.
Romeo, M., Hoarau, P., Garello, G., Gnassia-Barelli, M., Girard, J.P., 2003. Musseltransplantation and biomarkers as useful tools for assessing water quality inthe NW Mediterranean. Environ. Pollut. 122, 369–378.
Santos, E.M., Ball, J.S., Williams, T.D., Wu, H.F., Ortega, F., Van Aerle, R., Katsiadaki,I., Falciani, F., Viant, M.R., Chipman, J.K., Tyler, C.R., 2010. Identifying healthimpacts of exposure to copper using transcriptomics and metabolomics in afish model. Environ. Sci. Technol. 44, 820–826.
Storey, K.B., 1996. Oxidative stress: animal adaptations in nature. Brazilian J. Med.Biol. Res. 29, 1715–1733.
Tarachiwin, L., Masako, O., Fukusaki, E., 2008. Quality evaluation and prediction ofCitrullus lanatus by 1H NMR-based metabolomics and multivariate analysis.J. Agric. Food Chem. 56, 5827–5835.
Tikunov, A.P., Johnson, C.B., Lee, H., Stoskopf, M.K., Macdonald, J.M., 2010.Metabolomic investigations of American oysters using HNMR spectroscopy.Mar. Drugs 8, 2578–2596.
Tsangaris, C., Kormas, K., Strogyloudi, E., Hatzianestis, I., Neofitou, C., Andral, B.,Galgani, F., 2010. Multiple biomarkers of pollution effects in caged mussels onthe Greek coastline. Comp. Biochem. Phys. C 151, 369–378.
Tuffnail, W., Mills, G.A., Cary, P., Greenwood, R., 2009. An environmental H-1 NMRmetabolomic study of the exposure of the marine mussel Mytilus edulis toatrazine, lindane, hypoxia and starvation. Metabolomics 5, 33–43.
Viant, M.R., 2009. Applications of metabolomics to the environmental sciences.Metabolomics 5, 1–2.
Viant, M.R., 2003. Improved methods for the acquisition and interpretation ofNMR metabolomic data. Biochem. Biophys. Res. Commun. 310, 943–948.
Viant, M.R., Rosenblum, E.S., Tjeerdema, R.S., 2003. NMR-based metabolomics: apowerful approach for characterizing the effects of environmental stressors onorganism health. Environ. Sci. Technol. 37, 4982–4989.
Viarengo, A., Lowe, D., Bolognesi, C., Fabbri, E., Koehler, A., 2007. The use ofbiomarkers in biomonitoring: a 2-tier approach assessing the level of pollu-tant-induced stress syndrome in sentinel organisms. Comp. Biochem. Phys. C146, 281–300.
Walker, C.H., Hopkin, S.P., Sibly, R.M., Peakall, D.B., 2006. Principles of Ecotoxicol-ogy. Taylor & Francis Group, Boca Raton.
Wishart, D.S., Tzur, D., Knox, C., Eisner, R., Guo, A.C., Young, N., Cheng, D., Jewell, K.,Arndt, D., Sawhney, S., Fung, C., Nikolai, L., Lewis, M., Coutouly, M.A., Forsythe,I., Tang, P., Shrivastava, S., Jeroncic, K., Stothard, P., Amegbey, G., Block, D., Hau,D.D., Wagner, J., Miniaci, J., Clements, M., Gebremedhin, M., Guo, N., Zhang, Y.,Duggan, G.E., Macinnis, G.D., Weljie, A.M., Dowlatabadi, R., Bamforth, F., Clive,D., Greiner, R., Li, L., Marrie, T., Sykes, B.D., Vogel, H.J., Querengesser, L., 2007.HMDB: the human metabolome database. Nucleic Acids Res. 35, D521–D526.
Wu, H., Southam, A.D., Hines, A., Viant, M.R., 2008. High-throughput tissueextraction protocol for NMR- and MS-based metabolomics. Anal. Biochem.372, 204–212.
Wu, H., Wang, W.X., 2010. NMR-based metabolomic studies on the toxicologicaleffects of cadmium and copper on green mussels Perna viridis. Aquat. Toxicol.100, 339–345.
Wu, R.S.S., Shin, P.K.S., 1998. Transplant experiments on growth and mortality ofthe fan mussel Pinna bicolor. Aquaculture 163, 47–62.
Yancey, P.H., Clark, M.E., Hand, S.C., Bowlus, R.D., Somero, G.N., 1982. Living withwater stress: evolution of osmolyte systems. Science 217, 1214–1222.
Yin, J., Falconer, R.A., Chen, Y., Probert, S.D., 2000. Water and sediment movementsin harbours. Appl. Energy 67, 341–352.