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Airborne pollution-linked thyroid disruption in fish from European Mountain
lakes
Sergio Jarquea,b, Carme Boscha, Joan O. Grimalta, Demetrio Raldúaa, Benjamin Piñaa,*
a) Institute of Environmental Assessment and Water Research (IDAEA-CSIC). Jordi
Girona, 18. 08034 Barcelona, Spain
b) Research Centre for Toxic Compounds in the Environment, RECETOX, Faculty of
Science, Masaryk University, Kamenice 5/753, Brno CZ62500, Czech Republic
ABSTRACT.
The hepatic expression of the enzyme deiodinase 2 (dio2) was used as a biomarker for
thyroid disruption in trout from seven lakes in the Pyrenees (Spain) and the Tatra
Mountains (Slovakia). Highest levels of dio2 gene expression were found in fish from
the two coldest lakes in Pyrenees, whereas relatively low expression levels were found
in the Tatra lakes. Expression of these genes correlated with the presence of PBDE
(polybrominated diphenyl ethers) in the muscle of the same animals, and reflects the
anomalous distribution of these compounds across European mountain ranges. In
contrast, cyp1a expression levels, diagnostic for the presence of dioxin-like pollutants,
followed a strong negative correlation with lake average temperatures in both mountain
ranges, mirroring the distribution of semi-volatile organochlorine compounds. These
data show a first indication for thyroid disruption in remote ecosystems and signal to
organobromide compounds as suitable candidates of triggering this form of endocrine
disruption.
INTRODUCTION
Despite their remoteness and isolation from local pollution sources, high
mountain lakes are excellent models for the evaluation of the toxic effects of airborne
pollution, as they receive significant concentrations of long-range transported persistent
organic pollutants (POPs). This includes polycyclic aromatic hydrocarbons (PAHs),
organochlorine compounds (OCs), and organobrominated compounds, like PBDEs,
which accumulate in their sediments and biota 1-6. Fish, the top predators of these
ecosystems, constitute excellent sentinel organisms for monitoring their pollution status
7
, as they exhibit significant accumulations of OCs, depending on the
altitudinal/temperature features of their habitat lakes 2,3,5. However, the current
information on the physiological consequences of the accumulation of POPs in
mountain lake fish is still scarce, although some reports revealed different physiological
responses in high mountain fish associated to the presence of specific airborne
pollutants 8-11. Expression levels of Cytochrome P450 1A (cyp1a) is an established
biomarker of exposure to different environmental pollutants in many animal species,
including fish 8,11,12. Hepatic Cyp1A gene expression levels in trout populations from
European mountain lakes has been investigated in a previous study 11, showing
statistically significant correlations between levels of this marker in liver trout and
concentrations of several POPs in lake sediments were the animals were captured11.
Endocrine disruption is a particularly pervasive form of pollution that affects
reproductive and metabolic systems at very low concentrations. In its most usual
form, endocrine disruption is mediated by the binding of exogenous substances to
natural hormone receptors that regulate the endocrine system 13 14. Whereas the term
typically relates to sex-related signalling mechanisms (estrogens, androgens, etc.). In
addition, there are several lines of evidence indicating the existence in the environment
of disruptors for other cellular receptors, like the thyroid hormone receptors (TR),
among others. There is very little knowledge on environmentally relevant pollutants that
may act as thyroid disruptors. Given the nature of the active thyroid hormone (T3, see
below), obvious candidates include different organochlorinated (OC) and
organobrominated compounds, like PCB, dioxins and PBDE 15.
The thyroid system is regulated mainly by thyroid hormone receptors (TR), which
includes different isoforms and subfamilies, with distinct and sometimes contradictory
functions depending on the species and on the tissue. Thyroid function is regulated by
the Hypothalamus-Pituitary-Thyroid axis, a multi-loop feedback mechanism present in
all higher vertebrates, in which the thyroid synthetizes thyroxine, or T4. In fish, like in
terrestrial vertebrates, T4 is considered a pro-hormone, and must first be metabolized to
T3 (3,5,3'-triiodothyronine ) in peripheral tissues by the selenocysteine containing
enzymes deiodinases in order to bind to TRs 16 17 18. Deiodinases are also implicated in
the synthesis of inactive thyroid hormone forms, like the the reverse-T3 (rT3, 3,3',5'-
triiodothyronine) or the 3,3'-diiodothyronine (T2) 18. The hepatic isoform 2 (deiodinase
2, dio2) plays a major role in the control of the intracellular concentration of T3 in
teleostei, and its expression in fish liver is regulated by circulating thyroid hormones 19.
Therefore, this hepatic isoform was selected as a suitable candidate for a thyroid
disruption biomarker in trout. In this work we compared expression levels of dio2 and
cyp1a to assess the environmental impact of airborne pollution in two different
regulatory systems that are controlled by two evolutionary distant receptors, the TR and
the AhR, both showing high affinity for hydrophobic, non-steroid ligands. Our intention
is to link alterations on their respective mRNA levels to the presence of longtransported persistent pollutants arriving in these lakes by atmospheric deposition and to
identify potential sources of airborne thyroid disrupters which up-to-now is a poorly
characterized form of pollution.
MATERIALS AND METHODS
Fish sampling.
The study includes fish from two European mountain ranges, an
altitudinal transect of five lakes in the Pyrenees (at the French-Spanish border) and two
lakes in the Tatra Mountains (Poland-Slovakian border), which configure a range of
average annual temperatures from 6.2 to -0.7ºC. Lake characteristics have been
published elsewhere
2,11
; a complete set of data is presented as supplementary material
(Table S1).
Fish (Salmo trutta, brown trout) were sampled by net fishing. They were killed by
cervical dislocation, weighed, measured and dissected in the sampling site, reducing any
stress or undue suffering 5. Fish from two local altitudinal gradients (Pyrenees and
Tatras) were sampled in a single campaign coinciding with the maximal productivity
period (July in the Pyrenees and September in the Tatras, both in 2004). They were
selected de visu to discard aged or very young fish, keeping an age range between 5 and
10 years for most of them (Table 1), calculated by otolith analysis as described 20. Liver
samples (50-100 mg) were preserved in RNAlater (Sigma-Aldrich, St. Louis, MO,
USA) as previously described
21
and kept at -80ºC. Muscle fillets (skinless) for
chemical analysis were wrapped in pre-cleaned aluminium foil and stored at -20ºC.
Hepatic mRNA analysis by RT-qPCR. Liver samples were homogenised in TRIzol
Reagent (Gibco, Paisley, UK). Total RNA was extracted and analyzed as previously
described
8,11
. Quantitation of specific mRNA molecules was performed by Reverse-
Transcription quantitative a Abi Prism 7000 Sequence Detection System (Applied
Biosystems, Foster City, CA, USA) by the SYBR GREEN method (Applied
Biosystems)
8,11
, using ß-Actin as reference gene8,22. Sequences for dio2, cyp1a, and ß-
Actin primers used in this work were the following:
ß-Actin Forward: 5'- CTGTCTTCCCCTCCATCGTC-3'
ß-Actin Reverse: 5'- TCTTGCTCTGAGCCTCGTCTC-3'
dio2 Forward: 5'-GAGGCACACCCCTCGGACGGCT-3'
dio2 Reverse: 5'-ACCACCCTCTCCTCCAGTGAT-3'
cyp1a Forward: 5'-CACTGACTCCCTCATTGACCAC-3'
cyp1a Reverse: 5'-ACAGATCATTGACAATGCCCAC-3'
Amplified PCR products were purified using GFX PCR Purification Kit
(Amersham Biosciences, Backinghamshire, UK), inserted into the pTZ57R/T plasmid
(InsT/Aclone PCR Product Cloning Kit, Fermentas, Burlington, Canada) and sequenced
using Applied Biosystems 3730 DNA Analyzer (Applied Biosystems). Amplified
sequences were compared to previously reported sequences of homologous genes from
different salmonids using ClustalW from Bioedit Sequence Alignment Editor (BioEdit
v7.0.5, Ibis Therapeutics, Carlsbad, CA). A detailed protocol of the mRNA preparation,
RT-qPCR method and associated calculations is shown as supplementary material.
PCBs and PBDE analysis. Muscle tissues were analyzed as described elsewhere5.
Muscle samples were ground with activated sodium sulphate to fine powder and
extracted with Soxhlet in n-hexane:dichloromethane (4:1) for 18 h, cleaned with
sulfuric acid, concentrated, evaporated and finally redissolved in 50µl of isooctane.
Samples were analyzed for PCBs by GC-ECD (Hewlett-Packard 5890 series II)
operated in splitless mode. PBDE were analyzed by negative ion chemical ionization
mass spectrometry coupled to gas chromatography (GC-MS-NICI). A detailed protocol
of the extraction and analytical procedures is included as supplementary material.
Statistics. All statistical calculations were performed using the SPSS v. 19 package
(SPSS Inc., Chicago, Ill.). Non-parametric methods were preferred to compare data
from very different analytical and measurement procedures (Physical measurements,
chemical analysis, gene expression data, etc.). Missing values in partial correlation
analysis were eliminated pairwise. Unless otherwise noted, significance levels were set
at p<0.05.
RESULTS AND DISCUSSION
POP concentrations in muscle samples. The analyses were focussed on the
pollutants with adequate physical-chemical properties for long-range transport. Variable
concentrations of these compounds were found in fish muscle samples. Among
organochlorine compounds, 4,4’-DDE showed the highest concentrations in all lakes
considered for study, followed by PCB153, PCB138 and, in slightly lower
concentration, PCB180. This pattern was observed in both mountain regions, Pyrenees
and Tatras, and was consistent with the higher bioaccumulation potential of the more
chlorinated PCBs than the less chlorinated congeners3 (Supplementary Table 1). A
different trend was observed for the PBDEs. The congener PBDE47 was the most
abundant in the samples from Pyrenean lakes, followed in second place by PBDE99
(Supplementary Table 1). These results agree with lab studies with perch (Perca
fluiviatilis), pike (Esox lucius) and roach (Rutilus rutilus) 23, and juvenile carp
(Cyprinus carpio) 24, in which PBDE47 showed higher concentrations than the rest of
PBDE congeners. However, the samples from the two Tatra lakes showed a different
distribution in which PBDE99 was in higher concentration than PBDE47
(Supplementary Table 1). Despite of this divergence, all fish populations considered in
the present were consistent with a general trend in which, among the compounds found
above limit of detection, congeners with higher bromine content were found in lower
concentrations than those with higher degree of bromination. These results are
consistent with the inverse relationship between degree of bioaccumulation and number
of bromine atoms in these compounds generally observed in other studies 25. However,
there are some studies in which no clear relationship between bioaccumulation ratio and
bromine content was found26. These discrepant results could be explained in part by the
effects of biotransformation and bioformation reactions27,28. Both processes vary among
species, and may affect congener half-lives, and, consequently, concentrations in
samples.
Expression levels of dio2 and cyp1a in natural S. trutta populations. dio2 and
cyp1a expression levels varied several orders of magnitude among S. trutta specimens
from different high mountain lakes (Figure 1, see values in Supplementary Table S2). A
substantial fraction of this variability occurred within each lake population; when
average values from each fish population were considered, these differences were
reduced at about 25 fold for dio2 and around 5 fold for cyp1a expression (Figure 1).
The Llebreta lake, the lowest and warmest sampled point in the Pyrenees whose fish
contain low concentrations of PCBs and PBDEs, showed the lowest levels of expression
for both genes (Supplementary Table 2, orange dots in the graphs from Figure 1), which
is consistent with the well known accumulation of POPs in cold environments relative
to warmer ones2. Consistently with this model, the fish population showing the highest
cyp1a expression level corresponded to Veľké Hinçovo, the coldest site in this survey,
and already identified by containing fish with high concentrations of PCBs2,8,11
(Supplementary Table 1, Figure 1). In contrast, dio2 expression levels were relatively
low in this lake, the maximal values were observed in the two highest lakes in the
Pyrenees, Xic de Colomina and Vidal d'Amunt (Supplementary Tables 1 and 2, Figure
1). These data suggest that putative thyroid disrupters arriving to high mountain lakes
by atmospheric deposition are distributed differently from those of dioxine-like
pollutants.
Correlation of gene expression data with pollution burden. Correlation
analysis of gene expression and chemical burden data show different dependences
between the hepatic cyp1a and dio2 mRNA levels and POPs in muscle (Table 1). Cyp1a
expression shows a high correlation with the concentration of the more chlorinated
PCB, 4,4'DDT and 4,4'DDE (Table 1). This correlation has been already reported 8,11
and is also related with the strong inverse correlation between bioaccumulative POPs
and temperature in fish from European lakes 2,3,5. Thus, cyp1a expression is also
strongly correlated with the inverse of temperature (Table 1), as previously described 11.
This result is described graphically in the rightmost panel of Figure 1 (discontinuous
line). On the contrary, dio2 expression levels correlated with the concentration of the
highly brominated PBDE congeners, and only marginally with PCB118 and 4,4'DDT
(Table 1). On the contrary, dio2 mRNA levels are correlated with the concentrations of
the most brominated BDE and follow a different pattern (Figure 1; left and center
panels).
PBDEs are unable to activate AhR signalling in higher vertebrates. Indeed,
PBDE47 and PBDE99 inhibit, rather than activate, induction of AhR target genes by
exogenous ligands 29. For example, studies in feral barbels showed that most PBDE
congeners may inhibit EROD activities in natural populations and in laboratory
experiments 30. These studies agree with our observation that the concentrations of
PBDEs in fish muscle showed no correlation with cyp1a gene expression (Table 1). In
contrast, PBDEs, due to their structural similarity to T4, may be debrominated in a
similar manner to the deiodination of T4 to T3. Deiodinases, especially dio2, may play a
key role in this process 26, which may influence negatively thyroid homeostasis, as some
PBDE congeners may compete for transporters and promote hormone excretion 31. The
present results suggests that PBDE may have a metabolic role equivalent to T4 and their
occurrence in fish may induce dio2 expression. These results are consistent with
observed increases in total T3 hormone in humans at higher exposure to BDE47 in the
first years of life32. We consider these results a first indication of thyroid disruption in
fish in remote lakes due to atmospheric deposition.
Acknowledgments
We are grateful to the groups of E. Stuchlik (Charles University Prague, Czeck
Republic). This work has been supported by the EU Project EUROLIMPACS (GOCECT-2003-505540) and the Spanish Ministery of Econoly and Competitiveness project
TEA-PARTICLE (CGL2011-29621). Technical assistance from M. Casado, R. Chaler,
D. Fanjul and R. Mas is acknowledged
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FIGURE LEGENDS
Figure 1. Correlation between dio2 mRNA levels in trout liver and the content in
PBDE 153 (left) and PBDE 154 (center) in muscle, and of cyp1a mRNA level and
PCB153 (right). Dots indicate average values, brackets correspond to SEM values.
Pyrenees and Tatra Mountains samples are indicated by orange and blue dots. mRNA
levels are shown as dual logarithms of the number of mRNA copies per 1000 copies of
ß-actin mRNA (Y-axis); PBDEs and PCB153 values represent pg/g or ng/g of wet
tissue weight, respectively (X-axis). Discontinuous lines correspond to the correlation
between PBDE or PCB153 average contents and average annual temperature for each
like (ºC, right Y-axis, see also Supplementary Table S1). Numbers indicate the different
lakes: 1-Llebreta; 2-Cavallers; 3-Llong; 4-Xic de Colomina: 5-Vidal d'Amunt; 6Morske Oko; 7- Veľké Hinçovo. Llong lake (lake number 3) PBDE153 and 154 data is
lacking.