Ecotoxicology and Environmental Safety 108 (2014) 95–105

Contents lists available at ScienceDirect

Ecotoxicology and Environmental Safety
journal homepage: www.elsevier.com/locate/ecoenv

Effects of persistent organochlorine exposure on the livertranscriptome of the common minke whale (Balaenoptera
acutorostrata) from the North Paciﬁc
Satoko Niimi a, Mai Imoto a, Tatsuya Kunisue a, Michio X. Watanabe a, Eun-Young Kim b,
Kei Nakayama a, Genta Yasunaga c, Yoshihiro Fujise c, Shinsuke Tanabe a, Hisato Iwata a,naCenter for Marine Environmental Studies (CMES), Ehime University, Bunkyo-cho 2-5, Matsuyama 790-8577, Japan
Department of Life and Nanopharmaceutical Science and Department of Biology, Kyung Hee University, Hoegi-Dong, Dongdaemun-Gu,
Seoul 130-701, Republic of Koreac
The Institute of Cetacean Research, Toyomi-cho 4-5, Chuo-ku, Tokyo 104-0055, Japanbar t ic l e i nf o

a b s t r a c t

Article history:
Received 18 March 2014
Received in revised form
20 June 2014
Accepted 20 June 2014

Hepatic concentrations of persistent organochlorines (OCs) were determined in the common minke
whale (Balaenoptera acutorostrata) from the North Paciﬁc. To investigate the effects of OCs on thetranscriptome in the minke whale, the present study constructed a hepatic oligo array of this species
where 985 unique oligonucleotides were spotted and further analyzed the relationship between the OC
levels and gene expression proﬁles of liver tissues. The stepwise multiple linear regression analysis
identiﬁed 32 genes that correlated with hepatic OC levels. The mRNA expression levels of sevencytochrome P450 (CYP) genes, CYP1A1, 1A2, 2C78, 2E1, 3A72, 4A35, and 4V6 showed no clear correlations
with the concentration of each OC, suggesting that the accumulated OCs in the liver did not reach levels
that could alter CYP expression. Among the genes screened by the custom oligo array analysis, hepatic
mRNA expression levels of 16 genes were further measured using quantitative real-time reverse
transcription polymerase chain reaction. The mRNA levels of vitamin D-binding protein (DBP) were
negatively correlated with non-ortho coplanar polychlorinated biphenyl (PCB) levels. Androgen receptorassociated coregulator 70 (ARA70) expression levels showed a signiﬁcant positive correlation withconcentrations of non-ortho coplanar PCB169. These correlations suggest that coplanar PCB-reduced DBP
expression could suppress vitamin D receptor-mediated signaling cascades in peripheral tissues.
Alternatively, the suppression of vitamin D receptor signaling cascade could be enhanced throughcompetition with the androgen receptor signaling pathway for ARA70. In addition, a negative correlation
between kynureninase and PCB169 levels was also observed, which suggest an enhanced accumulationof an endogenous aryl hydrocarbon receptor agonist, kynurenine in the minke whale population. Further
studies are necessary to translate the changes in the transcriptome to toxicological outcomes including
the disruption of the nervous and immune systems.
& 2014 Elsevier Inc. All rights reserved.

Keywords:
Minke whale
Transcriptome
Organochlorines
Dioxins
Kynureninase

1. Introduction
Persistent organochlorine compounds (OCs) such as polychlorinated biphenyls (PCBs), 1,1,1-trichloro-2,2-bis(p-chlorophenyl)
ethane (DDT), and its metabolite, DDE, have been detected in avariety of environmental media (Iwata et al., 1993). Due to theirhigh bioaccumulation and toxic potentials, the contamination of
OCs in wildlife has been of great concern (Tanabe et al., 1994).
The levels of OCs in wild animal populations have been well
documented; however, the information on its effects remainsnCorresponding author.
E-mail address: iwatah@agr.ehime-u.ac.jp (H. Iwata).

http://dx.doi.org/10.1016/j.ecoenv.2014.06.028
0147-6513/& 2014 Elsevier Inc. All rights reserved.

insufﬁcient, especially at the molecular level. Regulatory programsin developed countries have started to incorporate tests andendpoints that capture the effects of chemicals on speciﬁc signaling pathways in animals (Ankley et al., 2010). Hence, 21st century
ecological testing and screening programs for chemicals should behighly comprehensive and promptly implemented (Villeneuve andGarcia-Reyero, 2011). On the other hand, the majority of themethods used for ecological testing virtually relies on wholeanimal exposures that focus on its effects on survival, growth,and reproduction. These types of tests are resource-oriented andtime-intensive; this makes it technically difﬁcult to address wild
species, particularly large-sized animals.
Animals react to chemical exposures by changing the expression patterns of their transcriptome (Van Aggelen et al., 2010;

96

S. Niimi et al. / Ecotoxicology and Environmental Safety 108 (2014) 95–105

Williams et al., 2003; Hirakawa et al., 2011). Thus, comprehensive
monitoring of the transcriptome in animals of concern, also known
as transcriptomics, will identify the critical targets of chemicals
and reveal new mechanisms of action. For gene expression
analysis, particularly at the transcriptome level, the use of the
microarray technique has recently been recognized as the standard methodology and continues to improve in terms of efﬁciency,
data enrichment, and cost (Van Aggelen et al., 2010). In toxicological studies, the microarray has been frequently used to comprehensively determine changes in gene expression proﬁles inorganisms exposed to not only drugs and pharmaceuticals but
also environmental contaminants. Hence, this technique could
play an important role in screening chemicals and in assessing
the health of animals. Molecular responses of murine models to
OC exposure have been detected using microarrays (Zeytun et al.,
2002; Boverhof et al., 2005, 2006; Vezina et al., 2004; Adeeko
et al., 2003; Kopec et al., 2010). Such studies have identiﬁed genes
responsive to OCs, as well as evaluated potential effects byassociating histopathological features with speciﬁc gene expression proﬁles. These observations have thus facilitated the implementation of transcriptomics as a diagnostic tool in ecotoxicology(Van Aggelen et al., 2010). However, most ecotoxicology studies
have used murine mammals that have been propagated in thelaboratory and may thus inaccurately represent the gene expression proﬁles of wild animals that are subjected to chronic and/or
long-term exposure to chemicals (Williams et al., 2003; Nakayama
et al., 2006; Hirakawa et al., 2011), while inbred murine animals
can diminish their genetic diversity which may contribute tosigniﬁcant differences in responses to chemical exposure. Comprehensive monitoring of changes in gene expression in wild
species may lead to the development of molecular markers that
aid in identifying causative chemicals and toxic mechanisms ofaction.
Our previous studies have revealed that common minke whales(Balaenoptera acutorostrata) from the North Paciﬁc accumulateclassical OCs including PCBs (sum of congeners), DDTs (p,p'-DDT, p,p'-DDD, and p,p'-DDE), hexachlorocyclohexanes (HCHs; α-, β-, and
γ-HCH), chlordanes (CHLs; cis-chlordane, trans-chlordane, cisnonachlor, trans-nonachlor, and oxychlordane) and hexachlorobenzene (HCB) in the liver and blubber (Aono et al., 1997; Niimi
et al., 2005). Furthermore, by using a cDNA library generated fromminke whale livers, we have identiﬁed seven cytochrome P450
(CYP) isozymes, including CYP1A1 (Accession no. AB231891),
CYP1A2 (AB231892), CYP2C78 (AB290008), CYP2E1 (AB290010),
CYP3A72 (AB290009), CYP4A35 (AB290011), and CYP4V6(AB290012) that might potentially respond to environmental
contaminants such as OCs at the transcriptional level and be
involved in their metabolism. We then determined their fulllength cDNA sequences and hepatic mRNA expression levels(Kim et al., 2004; Niimi et al., 2005, 2007). In addition, we carriedout correlation analyses between concentrations of each OC andmRNA expression levels of each CYP isozyme in the liver of theminke whale population from the North Paciﬁc. The results
showed no signiﬁcant correlations between the CYP isozyme
expression levels and the OC concentrations, which indicate thatthese CYP enzymes were not induced by OC exposure (Niimi et al.,2007). However, the effects of OCs on the hepatic expression ofgenes other than these CYPs in the common minke whales still
remain unclear. Sequence data from the whale cDNA library could
be potentially employed as a diagnostic tool such as microarray forevaluating chronic exposure of complex mixtures of OCs in thewhale species because it could help to establish sensitive markers
that identify pathways to adverse outcomes before they are
manifested in the population.
In the present study, we constructed an oligo array of thecommon minke whale using sequence data from the hepatic cDNA

library (Niimi et al., 2007) to investigate alterations in the expression of genes other than CYPs that may be associated with OC
accumulation in the body. In addition to chemical analyses of PCBs,
DDTs, HCHs, chlordanes, and HCB that have been so far reported(Niimi et al., 2005), we further analyzed dioxins and related
compounds (DRCs), including polychlorinated dibenzo-p-dioxins(PCDDs) and dibenzofurans (PCDFs) and coplanar (dioxin-like)
PCBs as aryl hydrocarbon receptor (AHR) agonists in the liver ofminke whales. Statistical analyses of correlations between hepatic
OC concentrations and gene expression levels on the custom oligo
array were then executed. Based on the correlation analyses, we
assessed the potential effects of OCs in the whale liver.

2. Materials and methods
2.1. Samples
Liver samples of the common minke whale employed in the present study were
the same as those used in our previous studies (Niimi et al., 2005, 2007). In brief,
nineteen male common minke whales (nine immature and ten mature) werecollected from an area of the western North Paciﬁc (35–451N, 140–1501E) by JARPN
II (Japanese Whale Research Program under Special Permit in the Western North
Paciﬁc-Phase II) in 2001. Livers of common minke whales were immediately
removed on board the research vessel after capture. Only male liver samples wereused to rule out the effect of sex on gene expression proﬁles. The livers wrappedwith aluminum foil were frozen in liquid nitrogen and subsequently stored at
 80 1C in the laboratory of Ehime University until total RNA preparation. The
subsamples of the livers were stored at –20 1C until DRC analysis.

2.2. Construction of custom microarray
Hepatic cDNA library of the common minke whale was prepared for theconstruction of an oligo array (Niimi et al., 2005). A total of 6930 clones randomly
selected from the library were screened, and 1991 cDNA clones with high sequence
identities with genes deposited in GenBank were obtained. Unique 70-mer
oligonucleotides for 985 genes were designed and spotted in duplicate onto a
TaKaRa-Hubble slide glass (Takara Bio, Inc.). Spotted genes on the oligo array werecategorized according to the gene annotation presented in Table 1.
Table 1
List of genes spotted onto our custom minke whale
oligo array.
Gene speciesnOncogene
Transcriptional factor
Translation initiation factor
Elongation factor
Receptor
Transporter
Immune system
Synthetase
KinasePhosphatase
Xenobiotic metabolizing enzyme
Antioxidant enzyme
Other enzymes
Homeobox
Growth factor
Heat shock protein
Ribosomal protein
Glycoprotein
KIAA
RIKEN
MGC
ATP-related protein
Haptoglobin
Selenoprotein
Cathepsin
Others

6
19
12
8
45
23
15
42
43
19
29
4
288
1
7
6
13
14
31
33
50
18
2
2
5
250

Total

985

S. Niimi et al. / Ecotoxicology and Environmental Safety 108 (2014) 95–105

2.3. Oligo array analysis
Total RNAs from nineteen liver samples were individually extracted using
TRIzols reagent (Invitrogen), and the quality of each RNA sample was checked bydenaturing agarose gel electrophoresis. RNA samples from three specimens that
contained relatively low OC levels were pooled for use as a common reference forthe following analysis. The preparation of antisense RNA (aRNA) probe, hybridization, washing, and scanning for oligo array analyses were performed according to
the method of Nakayama et al. (2006) and Hirakawa et al. (2011). For the
preparation of RNA probes, amino allyl antisense aRNA was ampliﬁed using 5 mgof total RNA with an Amino Allyl MessageAmp aRNA kit (Ambion), and 5 mg ofaRNA was labeled with either Cy3 (data) or Cy5 (reference) (Amersham Biosciences). Excess amounts of the Cy dye were then removed using a QIAquick PCR
puriﬁcation kit (Qiagen K.K.). Cy3- and Cy5-labeled aRNAs were mixed andfragmented with a 5  fragmentation buffer [0.5 M of potassium acetate, 0.15 M
of magnesium acetate in 0.2 M Trisacetate (pH 8.1)]. Labeled aRNA was puriﬁed andconcentrated using Microcon YM-10 ﬁlters (Millipore) for subsequent hybridization. For hybridization, a Cy dye-labeled aRNA solution was prepared using 6  SSC,
0.2 percent SDS, 5  Denhardt's solution (Eppendorf), and 0.1 mg/mL human Cot-I
DNAs (Invitrogen). The aRNA solution was heated at 95 1C for 2 min to denature
aRNA, cooled on ice, and then incubated at 65 1C for 5 min. After incubation, theaRNA solution was placed on a glass slide, and the aRNA probes were hybridized
with oligonucleotides spotted on the glass slide at 65 1C for 17 h. Following
hybridization, the slides were washed twice with 0.2 percent SDS in 2  SSC at
55 1C and once with 0.2 percent SDS in 2  SSC at 65 1C, rinsed twice with 0.2 
SSC at room temperature, and then dried by centrifugation at 800 rpm for 3 min.
The washed slides were then scanned using a ﬂuor-image analyzer (FLA-8000, Fuji
Photo Film Co., Ltd.) at a wavelength of 532 nm for Cy3 and at 635 nm for Cy5.
Fluorescence intensities derived from the Cy dye-labeled aRNA probes were
quantiﬁed by Array Gauge Ver 2.0 (Fuji Photo Film Co., Ltd.) in triplicate for eachsample. The intensity on the surrounding area of each spot was used as a
background signal. The ﬂuorescence intensity of each spot was corrected using
the background signal intensity. Expression levels of each gene were represented asdata (Cy3)/reference (Cy5) ratios. The ratios were normalized using the Locﬁt(LOWESS) function in TIGR MIDAS (version 2.19). Data showing less than twenty
percent of inter-slide variation in the gene expression levels in triplicate were
subjected to the following correlation analyses with OC levels.

97

PCDD/Fs and coplanar PCBs, was collected, concentrated, and passed through a 3.0g activated silica gel-packed glass column (Wako-gel S-1, Wako Pure Chemical
Industries Ltd.). PCDD/Fs and coplanar PCBs were eluted with 220 mL of hexane.
After the concentration of eluate, the extract was spiked into a 10-g activatedalumina-packed glass column (aluminum oxide 90, Brockman activity I, 70–230
mesh, Merck). The ﬁrst fraction eluted with hexane contained most of the PCB
isomers, including a large portion of mono-ortho coplanar congeners, and thesecond fraction eluted with 50 percent of DCM in hexane contained the remaining
mono-ortho coplanar PCBs, non-ortho coplanar PCBs, and PCDD/Fs. The second
fraction eluted from the activated alumina column was treated with a 1.0-g
activated carbon-dispersed silica gel-packed glass column (1 cm i.d., Kanto Chemical Co. Inc.). The ﬁrst fraction was collected with 25 percent of DCM in hexane formono-ortho coplanar PCBs and combined with the ﬁrst fraction obtained from thealumina column. The second fraction eluted with 220 mL of toluene contained nonortho coplanar PCBs and PCDD/Fs. Both fractions were concentrated to neardryness, and 13C12-labeled CB-105, CB-157, and CB-180 prepared in decane wereadded to the combined ﬁrst fraction, and 13C12-labeled 1,2,3,4-T4CDD and
1,2,3,7,8,9-H6CDD to the second fraction. The identiﬁcation and quantiﬁcation of
mono-ortho coplanar PCBs were performed using a gas chromatograph (GC)
(Agilent 6890 series, Agilent Technology) with a benchtop double-focusing mass
selective detector (MSD) (JEOL GC-MateII, JEOL Ltd.). The GC column used was a
DB-1 fused silica capillary (60 m length, 0.25 mm i.d., 0.25-mm ﬁlm thickness, J&W
Scientiﬁc, Inc.). The identiﬁcation and quantiﬁcation of non-ortho coplanar PCBs
and PCDD/Fs were performed using a GC (Agilent 6890 series) with a highresolution MSD (JEOL JMS-700D). Chromatographic separation was accomplishedby using a DB5ms fused silica capillary column (60 m length, 0.25 mm i.d., 0.1-mm
ﬁlm thickness, Varian, Inc.). The ﬁrst and second highest ions were monitored forthe identiﬁcation of individual congeners, except for P5CDD at ions of [M] þ and[M þ 2] þ .
All the congeners were quantiﬁed using an isotope dilution method for thecorresponding 13C12-congeners when the isotope ratio was within ﬁfteen percent of
the theoretical ratio and the peak area was more than ﬁve times the noise orprocedure blank level. Recoveries for the 13C12-labeled PCDD/Fs and coplanar PCBs,
which were added prior to gel permeation chromatography, were within 60–120
percent. The 2,3,7,8-T4CDD toxic equivalents (TEQs) were calculated using toxic
equivalency factors determined for mammalian species (Van den Berg et al., 2006).

2.6. Statistical analyses
2.4. Quantitative assessment of array-screened gene mRNAs by real-time RT-PCR
Total RNA extracted from each liver sample was treated with DNase prior tomRNA quantiﬁcation to avoid DNA contamination. The mRNA expression levels ofgenes, which have been associated with hepatic residue levels of OCs through an
initial screening using oligo array analysis, were further measured by quantitative
real-time RT-PCR. An ABI PRISM 7700 Sequence Detection System (Applied
Biosystems) was utilized for real-time PCR with a TaqMan One-Step RT-PCR Master
Mix Reagent Kit (Applied Biosystems). A set of speciﬁc primers and probe for eachgene of interest was designed using the cDNA sequence and the Primer Express™
ver. 1.05 software program (Applied Biosystems). The ﬁnal concentrations of theprimers and probes in the reaction mixture and annealing temperature for realtime RT-PCR are summarized in Table 2. FAM was used as a reporter dye at the 50 end of the probe and TAMRA was used as a quencher dye at the 30 -end. Eachreaction mixture contained 50 ng or 100 ng of total RNA as template. Conditions forreal-time RT-PCR were as follows: 30 min at 48 1C, 10 min at 95 1C, and 40 cycles of
15 s at 95 1C and 1 min at the corresponding annealing temperature for each set ofprimers (Table 2). The primers and a VIC-labeled probe for the endogenous control
ribosomal RNA (rRNA) were purchased from PE Applied Biosystems. Quantitativevalues were obtained from the threshold PCR cycle number (Ct) at which theincrease in signals associated with an exponential growth of PCR products was
detected. The standard curve of PCR products was obtained using a serially diluted
total RNA solution. The relative mRNA level of each sample was normalized to its
rRNA content and was expressed as the ratio relative to the highest expression level
among the analyzed samples.

2.5. Chemical analysis of DRCs
DRCs, including PCDD/Fs and coplanar PCBs, were analyzed following themethod described by Iwata et al. (2004). Ten to twenty grams of liver samples wereextracted in a Soxhlet apparatus for more than 8 h with dichloromethane (DCM).
The extract was concentrated, and an aliquot was used for lipid determination.
13
C12-labeled PCDD/Fs and coplanar PCBs (2,3,7,8-T4CDD/F, 1,2,3,7,8-P5CDD/F,
1,2,3,6,7,8-H6CDD/F, 1,2,3,7,8,9-H6CDF, 1,2,3,4,6,7,8-H7CDD/F, O8CDD/F, PCB-77, -81,
-118, -126, -156, -167, -169, and -189) were spiked into the remaining extract as a
mixture of internal standards. Lipid and biogenic materials in this solution were
removed by a gel permeation chromatography using a Bio-Bead S-X 3 packed glasscolumn (50 cm  2 cm i.d., Bio-Rad Laboratories). A mixture of 50 percent hexanein DCM was used as mobile phase, at a ﬂow rate of 5 mL/min. The ﬁrst 120 mL ofeluted solvent was discarded, and the following 100-mL fraction, which contained

The Mann–Whitney U test was employed to detect differences in DRC
concentrations between immature and mature animals. Correlations among OC
concentrations were analyzed by using Pearson's correlation test. Correlations ofconcentrations of a single or mixture of OCs with mRNA expression levels were
examined by using stepwise multiple linear regression analyses. Correlations of the
microarray data with the real-time RT-PCR data for each gene, and the relationships
between mRNA expression levels measured by the real-time RT-PCR and OC
concentrations were analyzed by using Spearman's rank correlation test. All
statistical analyses were performed using StatView 5 (SAS Institute Inc., Cary, NC)
and SPSS 12.0J (SPSS, Tokyo, Japan). A p value of o 0.05 was regarded as statisticallysigniﬁcant.

3. Results
3.1. Concentrations of DRCs in the liver of the common minke whale
DRCs were detected in all liver samples of the common minke
whales analyzed in this study (Table 3). Hepatic residue levels ofother OCs in this population have been previously reported indetail (Niimi et al., 2005). While only a few PCDD/F congeners(O8CDD, 2,3,7,8-T4CDF, 2,3,4,7,8-P5CDF, and 2,3,4,6,7,8-H6CDF)
were detected at trace levels (o0.01–0.70 pg/g wet wt), the concentrations of total coplanar PCBs were relatively high (690–
8900 pg/g wet wt). The residue levels of non-ortho coplanar
PCB169 and mono-ortho coplanar PCBs, except for PCB105, 114,
and 123, in mature male whales were signiﬁcantly higher thanthose in immature male whales (po 0.05). Hepatic total TEQ levels
were within the range of 0.54–3.2 pg TEQ/g wet wt. The contribution of TEQs derived from non-ortho coplanar PCBs to total TEQs
was the most dominant (Table 3).
Signiﬁcant positive correlations among residue levels of OCs
were detected in all the analyzed samples (Table 4). The intercorrelations of OC levels indicated concurrent exposure of thisNorth Paciﬁc whale population. This is probably due to similarities

98

S. Niimi et al. / Ecotoxicology and Environmental Safety 108 (2014) 95–105

Table 2
List of primer pairs and probes designed for the quantiﬁcation of the mRNA expression levels of genes by real-time RT-PCR.
Gene namePrimer and probe sequences 50 to 30

Amplicon(bp)

Primer and probe
concentration(nM)

Anealing
temperature(1C)

Total RNAas template(ng)

CYP1A1F
CCGTATCCGGGACATCACAGRCGACATTAACGATCTTCTCATCTGA
Probe CTGTCAGGGCAAGAGACTGGACGAGAA

104

300
300
250

53

50

CYP1A2F
GGTGCCCTGTTCAAGCACTACGAR
AGATGGCTGTTGTGATTGGATCAAAC
Probe CAACCTTGTCAACGACATCTTCGCAGCC

126

900
900
250

57

100

CYP2C78F
AGTTTCTGGTGGAGGAGCTCAGGARGTTGAAGAGGATGGAGCAGATCACA
Probe TTCACCCTCTCCTGTGCTTCCTGCAA

103

900
900
250

56

100

CYP2E1FCTACAACGTCATCTCCGACATCCTCR
GCTACTGAGCAGGTAGAAGTTCTCATTG
Probe CGACTACAATGACAAGACGGCTCTG

108

900
900
250

55

100

CYP3A72F
GCTGGCTACGAGACCACTAGCAATR
AAGTTGCATCAATCTCCTCCTGC
Probe AATTGGCCACTCACCCTGATGTCCAG

102

900
900
250

54

100

CYP4A35FGGAGCAGCTTGTCTGACGTGGAR
GTGGGAGGCCAGAGCATAGAGGAT
Probe CCGAAGTGGATACGTTCATGTTCGAGGGTC

112

900
900
250

57

100

CYP4V6F
CCTATGCACTGCACAGAGATCAAAGG
R
ACATATGCGTATGAATGACGTCCTTTC
Probe CCTGAGGAATTCAAGCCAGAACGGTTCTT

105

900
900
250

57

100

2',5'-Oligoadenylate synthetase (OAS1)F
AGTGCGTGGAGTTTGATGTCCTR
CTCTCGGATAAGCTGGACGTAGA
Probe TTGACCAGAGGCTACAGACCTGACCCTAAA

101

900
900
250

53

50

ATP synthase gamma subunit precursor (ATP5C1) F
GGCTGATATTAAGGTGCCTGAAGARCGAGGAATGAATAGCACCACAA
Probe ACATCTCCTTATTGGTGTGTCCTCAGACCG

91

900
900
250

53

50

Solute carrier family 27, member 5 (SLC27A5)F
GCATGGTGTGACTGTGATCCAR
TTGCCAGGCGGACTTTATGTProbe TCCTGCGGTACCTGTGCAACACTCC

101

900
900
250

57

50

Acetyl-CoA C-acetyltransferase (ACAT1)FGAACACCCATTGGATCCTTTCTARTGGAATCCCTGCCTTTTCAA
Probe CTTTCCTCTCTGCCAGCCACTAAACTTGGTT

101

900
900
250

57

50

Histamine N-metyltransferase (HNMT)F
TTGGTTTCTGACCACAGCAGATR
GGCAGCTTCTCGTCCATGA
Probe TTGAATCTTTCCGGAGGTTTCTCGACAATTC

101

900
900
250

57

50

Urate oxidase precursor (UOX)

F
GTGCAACTTACTCTGAGCTCCAAA
R
TTTGCCAGGACATGAACTGTGT
Probe TTCAGACCTCATCCCTACAGACACCATCAA

101

900
900
250

58

100

Lactate dehydrogenase A (LDHA)F
TCCAACATGGCAGCCTTTTC
101
R
TGCTCCAGCTGTGATAATAACCA
Probe TTAAAACACCAAAAATCGTCTCTGGCAAAGACT

900
900
250

58

100

Paraoxonase 2 (PON2)F
ACCTTCCAAACTGCCACCTG
R
CCCACACTAAAGAAGGCCGAC
Probe CGAAGCTGGCTCTGAAGATATTGACATACTTCC

91

300
300
250

59

100

Caspase 6 (CASP6)FGCTCACGGTGCAGGTGAAC
R
GTACGTTTCTGCCGGATCAAA
Probe CATGACAGAAACAGATGCCTTCCCTATGAGA

81

900
900
250

59

50

Cysteine dioxygenase 1 (CDO1)F
AGGACATGGCAGCAGTATCCA
R
CCAGGCAAATAACGTCTCCTTT
Probe ATCACACTGACTCCCACTGCTTTCTGAAGATG

91

300
300
250

58

50

Androgen receptor-associated protein 70 (ARA70) F
GCACCACATCTGTCCCTCTCAR
GAGCCAGTCCTGCAGATTGG
Probe CAGCGGTCGCCAGGCTCCTTACATAC

101

900
900
250

58

50

Vitamin D binding protein (DBP)

F
CCACTCTGGGAATGACATCTGAR
GAGGCTCTTGCAGCTGATAACA
Probe AGCCTAACCCAAGCAAAACCAGAGTTCCT

101

300
300
250

58

50

Kynureninase (KYNU)

F
GTCCGACGCATCGCATCTRTGAAGTGCCTCAGCTTATCTTCCT
Probe AACAGATGAGAGAGTTGCCCTCCGCC

91

900
900
250

58

50

S3 ribosomal protein (RPS3)F
AATCCATGAAGTTCGTGGATGG
R
CACACCCTGTCTGAGCAGCA
Probe TAACTACTATGTTGATACTGCCGTGCGCCA

101

900
900
250

58

50

S. Niimi et al. / Ecotoxicology and Environmental Safety 108 (2014) 95–105

99

Table 2 (continued )Gene namePrimer and probe sequences 50 to 30

Amplicon(bp)

Primer and probe
concentration(nM)

Anealing
temperature(1C)

Total RNAas template(ng)

Ribosomal protein L13a (RPL13a)

F
GATCCCGCCACCCTATGACRGTAGGCAAACTTCCGTGTAGGCTProbe ATGGTGGTTCCTGCCGCCCTC

91

300
300
250

58

50

Acidic ribosomal phosphoprotein P0 (RPLP0)F
ACAGTGCCTGCCCAGAACACR
TGGTGCCCCTGGAGATTTTAG
Probe AGACCTCCTTCTTCCAGGCTTTAGGCATCA

91

300
300
250

58

50

F: forward primer.
R: reverse primer.

in sources, physicochemical characteristics, and/or toxicokinetics
among these environmental pollutants. Based on the results ofintercorrelation analyses of OC levels, it may be difﬁcult to identify
the causative OC compound that is responsible for the altered gene
expression levels, even when the accumulation level of a single
compound exhibited a signiﬁcant correlation with the expression
level of a certain gene. Hence, the most plausible approach is totreat all the tested OCs as potential candidates that induce changes
in expression levels of a particular gene in case that a signiﬁcantcorrelation is obtained.

Although the CYP isozymes including CYP1A1, CYP1A2,
CYP2C78, CYP2E1, CYP3A72, CYP4A35, and CYP4V6 were spotted
onto our whale oligo array, no correlations were establishedbetween these enzymes and OC levels. Similar ﬁndings wereobtained from real-time RT-PCR analysis.

3.2. Gene expression analysis

The detected levels of DRCs in the liver of minke whales fromthe North Paciﬁc were in the following decreasing order: monoortho PCBs 4non-ortho PCBs 4PCDFs 4PCDDs (Table 3). Thisaccumulation pattern, particularly characterized by traceablelevels of PCDDs in the whales, was apparently similar to thatobserved in other oceanic vertebrate species (Kunisue et al., 2006;
Kubota et al., 2010). Previous investigations have reported higher
concentration ratios of PCDFs/PCDDs in oceanic animals than thatin animals inhabiting terrestrial and coastal areas, indicating that
selective exposure to PCDFs occurs in the open seas (Kunisue et al.,2006). The high PCDFs/PCDDs ratio in oceanic animals may be
attributable to higher atmospheric transport potential of PCDFs
than PCDDs, which is reﬂected by the higher vapor pressure (PL)and lower octanol-air partition coefﬁcient (KOA) in PCDFs than in
PCDDs, and/or to the release of PCDFs as impurities from technical
PCB formulations used as antifouling paints in commercial vessels(Kunisue et al., 2006). The residue levels of non-ortho coplanar
PCB169 and mono-ortho coplanar PCB118, 156, 157, 167, and 189 inmature whales were signiﬁcantly higher than those in immatureindividuals (Table 3). This observation suggests that these congeners are constantly supplied through the oceanic food web andpersist in the liver of minke whales.
TEQ levels detected in the liver of minke whales were compared to those of other vertebrate species inhabiting oceanic
ecosystems. Data on DRC concentrations in cetaceans were mostly
derived from blubber analysis, and TEQ levels were thus based on
lipid weight analysis. Hence, the minke whale wet weight-based
TEQ data of this study were converted to lipid weight basis inorder to compare these with the blubber data of other cetaceans(Table 3). TEQ levels of the minke whales (16–85 pg TEQ/g lipid wt) were lower than those detected in the blubber of cetaceans, which include Stejneger's beaked whale (120–230 pg TEQ/
g lipid wt) and the killer whale (110–440 pg TEQ/g lipid wt) fromJapanese coastal waters (Kajiwara et al., 2004, 2006). This may be
attributable to differences in prey species and trophic position in
the ecosystem; the prey species of the western North Paciﬁc
common minke whale population consists of pelagic zooplankton
and schools of small ﬁshes (Tamura and Fujise, 2002), whereas
Stejneger's beaked whale mostly feeds on herring, mackerel, andcephalopods. The killer whale is a real apex predator in the

Stepwise multiple linear regression analysis using oligo arraydata identiﬁed 21 genes showing associations between expression
patterns and TEQ levels, and twelve genes presenting relationships
with other OCs in the liver of common minke whales (Tables 5 and
6). The mRNA expression levels of paraoxonase 2 were correlatedwith both of non-ortho coplanar PCB-derived TEQ and HCB levels.
The total 32 genes were classiﬁed into functional categories, which
include receptors, ribosomal proteins, synthetases, phosphatases,
and other enzymes, as well as speciﬁc cellular activities such as
apoptosis, immune function, ATP synthesis, citric acid cycle, andfatty acid metabolism.
Among the genes screened by our oligo array analysis, mRNA
expression levels of 16 genes, including androgen receptorassociated coregulator 70 (ARA70), ATP synthase gamma chain(ATP5C1), paraoxonase 2 (PON2), ribosomal protein S3 (RPS3),
ribosomal protein L13a (RPL13A), acidic ribosomal phosphoprotein
P0 (RPLP0), kynureninase (KYNU), histamine N-methyltransferase(HNMT), vitamin D binding protein (DBP), 20 ,50 -oligoadenylate
synthetase 1 (OAS1), solute carrier family 27 (fatty acid transporter) member 5 (SLC27A5), urate oxidase precursor (UOX), cysteine
dioxygenase type 1 (CDO1), acetyl-coenzyme A acetyltransferase 1(ACAT1), lactate dehydrogenase A (LDHA), and caspase 6 (CASP6)
were further measured using quantitative real-time RT-PCR. Signiﬁcantly positive correlations in expression levels between theoligo array and real-time RT-PCR analyses were observed in sevenout of the sixteen genes, which included ARA70, RPS3, KYNU,
HNMT, CDO1, LDHA, and CASP6 (Table 7). Signiﬁcant correlations
were also observed between some of OC levels and DBP, ARA70,
KYNU, RPS3, OAS1, LDHA, and CASP6 mRNA expression levels thatwere measured using both the oligo array and real-time RT-PCR
analyses. The mRNA levels of DBP and KYNU measured by realtime RT-PCR were negatively correlated with TEQ levels from nonortho coplanar PCBs, particularly with PCB126 (Fig. 1A and B). As
for ARA70 levels quantiﬁed with real-time RT-PCR, a signiﬁcant
positive correlation with PCB169 levels was detected (Fig. 1C).
Positive correlations were detected between the expression levelsof RPS3, OAS1, LDHA, and CASP6 and γ-HCH levels (data notshown).

4. Discussion
4.1. Levels of DRC residue

100

S. Niimi et al. / Ecotoxicology and Environmental Safety 108 (2014) 95–105

Table 3
Arithmetic mean and range of hepatic concentrations of dioxins and related compounds and other organochlorines in the common minke whale from the North Paciﬁc.
Immature

MatureImmature

MatureSample number
Dioxins and related compounds

9
Concentration (pg/g wet wt)

10

9Concentration (pg/g lipid wt)

10

PCDDs
2,3,7,8-T4CDD
1,2,3,7,8-P5CDD
1,2,3,4,7,8-H6CDD
1,2,3,6,7,8-H6CDD
1,2,3,7,8,9-H6CDD
1,2,3,4,6,7,8-H7CDD
O8CDD

o0.01
o0.01
o0.03
o0.03
o0.03
o0.05
0.24

o 0.01o 0.01o 0.01o 0.03o 0.03o 0.03
0.18

o0.20
o0.20
o0.60
o0.60
o0.60
o1.0
6.7

o 0.20o 0.20o 0.60o 0.60o 0.60
o 1.0
4.8

PCDFs
2,3,7,8-T4CDF
1,2,3,7,8-P5CDF
2,3,4,7,8-P5CDF
1,2,3,4,7,8-H6CDF
1,2,3,6,7,8-H6CDF
1,2,3,7,8,9-H6CDF
2,3,4,6,7,8-H6CDF
1,2,3,4,6,7,8-H7CDF
1,2,3,4,7,8,9-H7CDF
O8CDF

0.12
o0.01
0.3
o0.03
o0.03
o0.03
0.1
o0.05
o0.05
o0.10

ΣPCDDsb
ΣPCDFsb
Σ PCDD/Fs( o 0.10–0.70)( o 0.01–0.48)(0.12–0.61)( o 0.03–0.20)

0.087
o 0.010.25
o 0.03o 0.03o 0.030.12
o 0.05o 0.05o 0.10( o 0.10–0.66)( o 0.10–0.19)(0.15–0.39)( o 0.03–0.29)

3.4
o0.20
8.7
o0.60
o0.60
o0.60
2.8
o1.0
o1.0
o2.0

(o 2.0–21)(o 0.20–13)(3.6–16)(o 0.6–5.3)

2.1
o 0.206.3
o 0.60o 0.60o 0.60
2.7
o 1.0
o 1.0
o 2.0

( o 2.0–20)( o 0.2–4.6)(4.3–9.8)( o 0.6–6.0)

0.31( o 0.13–0.78)

0.26( o 0.13–0.74)

8.3(o 2.6–23)

6.4( o 2.6–22)

0.68(0.33–1.4)

0.60(0.32–0.94)

18(8.1–36)14(8.0–19)0.99(0.50–1.8)

0.87(0.52–1.3)

26(12–46)20(13–30)Non-ortho co-PCBs
3,30 ,4,4'-T4CB (77)
3,4,40 ,5-T4CB (81)3,3',4,4',5-P5CB (126)3,3',4,4',5,50 -H6CB (169)

1.5
1.5
11
2.0

(0.86–3.2)(0.73–4.0)(4.1–27)(0.91–4.5)

1.3
1.6
12
4.2

(0.96–1.6)(0.88–2.8)(7.0–25)(1.3–10)

44
44
310
56

(25–86)(22–110)(120–720)(27–120)

33
41
310
100

(23–41)(22–86)(190–550)(37–210)

Mono-ortho co-PCBs
2,3,30 ,4,4'-P5CB (105)
2,3,4,40 ,5-P5CB (114)
2,30 ,4,40 ,5-P5CB (118)
20 ,3,4,4',5-P5CB (123)
2,3,30 ,4,40 ,5-H6CB (156)
2,3,30 ,4,40 ,50 -H6CB (157)
2,30 ,4,40 ,5,50 -H6CB (167)
2,3,30 ,4,40 ,5,50 -H7CB (189)

180
29
1200
16
97
45
65
22

(53–430)(10–54)(450–2200)(8.3–31)(51–160)(23–86)(33–110)(10–29)

130
63
3000
27
350
140
260
54

(62–300)(14–140)(500–6600)(11–59)(49–760)(27–340)(30–590)(22–100)

5100
850
3300
480
2900
1400
1900
680

(1700–12,000)(390–1500)(1500–59,000)(270–830)(1400–4900)(640–2700)(910–3400)(260–960)

3100
1500
71,000
660
8400
3300
6300
1400

(1900–5500)(390–2600)(14,000–130,000)(300–1200)(1400–16,000)(750–6100)(930–13,000)(510–3100)

Σnon-ortho co-PCBs
Σmono-ortho co-PCBs
Σco-PCBs
TEQs

16(6.6–38)20(11–38)450(190–1000)

490(300–810)

1600(680–3100)

4000(730–8900)

47,000(21,000–83,000)

96,000(20,000–180,000)

1600(690–3100)

4000(740–8900)

47,000(22,000–84,000)

96,000(21,000–180,000)aΣPCDDs-TEQs
ΣPCDFs-TEQs
ΣPCDD/Fs TEQs
Σnon-ortho co-PCBs-TEQs
Σmono-ortho co-PCBs-TEQs
Σco-PCBs-TEQs
Σ TEQs

0.015

0.015

0.30

0.30

0.12

(0.055–0.25)

0.10(0.052–0.16)

3.3(1.6–6.6)

2.5(1.5–3.5)

0.13(0.070–0.27)

0.12(0.067–0.18)

3.6(1.9–6.9)

2.8(1.8–3.8)

1.1(0.44–2.8)

1.4(0.74–2.8)

33(13–76)34(21–59)0.048(0.020–0.092)

0.12(0.022–0.27)

1.4(0.63–2.5)

2.9(0.61–5.3)

1.2(0.47–2.9)

1.5(0.76–3.0)

34(14–78)37(23–63)

1.3(0.54–3.2)

1.6(0.90–3.2)

38(16–85)40(25–66)

950
1600
790
540
430

(190–1900)(190–4300)(480–1300)(92–1400)(120–1200)

Other OCsb

concentration (ng/g wet wt)

PCBs
DDTs
HCHs
CHLs
HCB

13
14
24
7.4
11

(5.5–22)(4.1–31)(16–30)(3.2–13)(6.3–15)

concentration (ng/g lipid wt)
35
62
28
20
16

(5.6–93)(5.7–210)(14–48)(2.7–67)(3.5–57)

400
450
750
240
330

(210–660)(160–960)(560–930)(120–380)(190–460)

Body length of the immature and mature minke whales used in this study was 5.8 m on average (range: 4.4–7.0 m) and 7.3 m (range: 6.9–7.7 m), respectively.
Lipid content of the liver samples of the immature and mature minke whales used in this study was 3.4 percent on average (range: 2.6–4.4 percent) and 4.0 percent (range:
3.2–5.5 percent), respectively.
For the calculation of arithmetic mean of concentrations and TEQ values, the concentrations below detection limit were regarded to be the half of the detection limit.
ab

TEQs were calculated using TEFs for mammals reported by Van den Berg et al. (2006).
Data on concentrations of other OCs were cited from Niimi et al. (2005).

oceanic ecosystem. A recent report has described the hepatic TEQ
levels in oceanic vertebrates (Moon et al., 2010). The hepatic TEQ
levels in minke whales and common dolphins from Korean coastal

waters are within the range of 4.6–66 pg TEQ/g lipid wt and 13–
122 pg TEQ/g lipid wt, respectively, which are similar to those of
the common minke whales from the North Paciﬁc.

S. Niimi et al. / Ecotoxicology and Environmental Safety 108 (2014) 95–105

4.2. Analysis of gene expression
To investigate whether OC accumulation in the liver results inchanges in the gene expression proﬁle of the common minke
whale from the North Paciﬁc, our previous study initially examined the relationships between hepatic residue levels of OCs (PCBs,
DDTs, CHLs, HCHs, and HCB) other than DRCs and the expression
levels of seven CYP (CYP1A1, 1A2, 2C78, 2E1, 3A72, 4A35, and 4V6)
isozymes (Niimi et al., 2007). The results indicated no clear
correlation between any of the CYPs with a speciﬁc OC. In thepresent study, the relationship between DRC concentration and
CYP levels, including that of CYP1A1 and 1A2, were further
examined; however, no correlation was detected at any
statistically signiﬁcant level (data not shown). Supportingthese results were the observation that the liver TEQ levels (range:
0.54–3.2 pg/g wet wt) of the common minke whales were markedly lower than the EC50 values for CYP1A or EROD induction by
TCDD in the human hepatoblastoma cell line, HepG2 (220 pg/mL)
and rat hepatoma cell line, H4IIE (16 pg/mL) (Zeiger et al., 2001).
In an aquatic mammalian species, the Baikal seal (Pusa sibirica),

Table 4
Results (correlation coefﬁcients) of Pearson's correlation test between concentrations of OCs detected in the liver of common minke whales (n ¼19).
TEQs
PCBs
DDTs
HCHs
CHLs
HCB
n

PCBs

DDTs

HCHs

CHLs

0.976nnn
0.691n0.984nnn
0.714nn0.669n0.970nnn
0.690n0.709nn
0.850nnn

0.772nn

nnn

0.797
0.725nn
0.584n0.800nnn
0.717nn

po 0.01.
p o0.001.
p o 0.0001.

nn

nnn

101

the wild population had a signiﬁcant positive correlation between
hepatic total TEQ and CYP1A protein expression levels, showing
65 pg/g wet wt of total TEQ-EC50 estimated from the sigmoidal
curve of the correlation (Hirakawa et al., 2007). Our recent study
evaluated the sensitivity of CYP1A1 transactivation via AHR to
TCDD in the Baikal seal by constructing an in vitro reporter geneassay system (Kim et al., 2011). The Baikal seal AHR (bsAHR)
expression plasmid and a reporter plasmid containing CYP1A1
promoter were transfected to COS-7 cells, and the cells weretreated with TCDD. The EC50 of TCDD was 0.021 nM (6.8 pg/mL).
Comparison with the total TEQ-EC50 in the wild seal population
and TCDD-EC50 for bsAHR-mediated transactivation indicates thatthe hepatic total TEQs in North Paciﬁc whales were relatively low.
These results thus suggest that the hepatic TEQs in this population
may not reach a level that is sufﬁcient enough to induce CYP1A.
Nonetheless, a signiﬁcant positive correlation (rs ¼0.64; po 0.01)
between CYP1A1 and CYP1A2 mRNA levels was observed (Niimi
et al., 2007), which suggests that certain exogenous/endogenous
AHR ligands might be regulating the expression of both CYPs and/or there might be a common mechanism that controls theconstitutive expression of these CYP1A genes in the whale liver.
Apart from the correlation analysis with CYP expression levels,
the results of the present study using a customized oligo arraysuggest that the hepatic expression levels of multiple genes might
have been altered by the accumulation of OCs in common minke
whales. Consequently, we identiﬁed 32 genes whose expression
levels might have been potentially affected by DRCs and other OCs(Tables 5 and 6). Of these genes, seven (DBP, ARA70, KYNU, RPS3,
OAS1, LDHA, and CASP6) mRNA expression levels as determinedusing the oligo array and real-time RT-PCR approaches showed
positive correlations with any of the OC levels.
DBP mRNA expression levels measured using the real-time RTPCR were negatively correlated (rs ¼  0.59; p ¼0.013) with theconcentrations of non-ortho coplanar PCB126 (Fig. 1A). DBP is a

Table 5
List of genes of which the mRNA expression levels were correlated with hepatic TEQs of PCDD/Fs and coplanar PCBs in common minke whales (n¼ 19).
Gene name

Gene symbol

Compound

R2

Slope

p-Value

Receptor
Androgen receptor-associated coregulator 70; nuclear receptor coactivator 4
Asialoglycoprotein receptor 2

ARA70
ASGPR 2Non-ortho co-PCBs
PCDFs

0.43
0.37

1.1
1.0

0.00560.013

Synthetase
ATP synthase gamma chain

ATP5C1

Mono-ortho co-PCBs

0.38

 0.700.011

PhosphataseParaoxonase 2

PON 2

Non-ortho co-PCBs

0.39

 1.0

0.0095

Ribosomal protein
Ribosomal protein S3
Ribosomal protein L13a
Acidic ribosomal phosphoprotein P0

RPS3
RPL13A
RPLP0

Non-ortho co-PCBs
Non-ortho co-PCBs
Mono-ortho co-PCBs

0.48
0.30
0.34

1.3
1.4
0.53

0.00280.029
0.018

Other enzymes
Sorbitol dehydrogenase
Homogentisate 1,2-dioxygenase (Homogentisate oxidase)
Kynureninase (L-kynurenine hydrolase)
L-arginine:glycine amidinotransferase
Histamine N-methyltransferase
Peptidylprolyl isomerase C
N-acylsphingosine amidohydrolase (Acid ceramidase)-like (Predicted) [Rattus norvegicus ]

SORD
HGD
KYNU
LAGA
HNMT
PPIC
ASAH1-like

PCDFs
Non-ortho co-PCBs
Non-ortho co-PCBs
Mono-ortho co-PCBs
Mono-ortho co-PCBs
Non-ortho co-PCBs
Non-ortho co-PCBs

0.37
0.51
0.33
0.26
0.34
0.31
0.34

 0.76
 1.4
 1.3
1.4
 3.1
 2.0
1.0

0.013
0.0018
0.020
0.046
0.018
0.025
0.018

OthersVitamin D binding protein
T-cell activation protein (PGR1 protein) (Mof4 family associated protein 1)
RER1 protein
Small EDRK-rich factor 2
PlasminogenThioredoxin domain containing 4
HSPC176 (Trafﬁcking protein particle complex 2-like)

DBP
PGR1
RER1
SERF2
PLG
TXNDC4
HSPC176

Non-ortho co-PCBs
Non-ortho co-PCBs
Non-ortho co-PCBs
Non-ortho co-PCBs
Non-ortho co-PCBs
Mono-ortho co-PCBs
Non-ortho co-PCBs

0.31
0.27
0.34
0.27
0.26
0.36
0.31

 1.3
 0.680.61
1.1
1.0
 0.68
1.6

0.025
0.038
0.018
0.042
0.043
0.014
0.026

Correlations were examined by stepwise multiple linear regression analysis using data on the mRNA expression levels of each gene from oligo array analyses and TEQ levels.

102

S. Niimi et al. / Ecotoxicology and Environmental Safety 108 (2014) 95–105

Table 6
List of genes of which the mRNA expression levels were correlated with hepatic concentrations of OCs other than PCDD/Fs and coplanar PCBs in common minke whales(n¼19).
Gene name

Gene symbol

Compound

R2

Slope

p-ValueSynthetase
20 ,50 -oligoadenylate synthetase 1
Solute carrier family 27 (fatty acid transporter), member 5

OAS1
SLC27A5

HCB
PCBs

0.33
0.53

1.3
0.85

0.019
0.0013

EnzymeUrate oxidase
Cysteine dioxygenase type I
Acetyl-Coenzyme A acetyltransferase 1
Fumarate hydratase
Lactate dehydrogenase A
Caspase 6
Paraoxonase 2

UOX
CDO1
ACAT1
FH
LDHA
CASP6
PON2

PCBs
HCHs
PCBs
PCBs
PCBs
PCBs
HCB

0.41
0.29
0.27
0.26
0.30
0.26
0.30

 0.60
 2.0
 0.75
 0.64
 0.99
 0.44
 0.620.0080
0.032
0.040
0.044
0.029
0.044
0.028

PCBs

0.30

1.0

0.029

HCHs
PCBs

0.38

 2.3

0.011

0.31

0.91

0.027

MGC
Unknown (protein for MGC:37838)
OthersAnnexin A5

ANXA5Actin-interacting protein 1

AIP1

Correlations were examined by stepwise multiple linear regression analysis using data on the mRNA expression levels of each gene from oligo array analyses and OC levels.

Table 7
Results of Spearman's rank correlation test between hepatic gene expression levels
measured using oligo array and real-time RT-PCR analyses.
Gene symbol

rs- Value

p-Value

ARA70
ATP5C1PON2
RPS3
RPL13A
RPLP0
KYNU
HNMT
DBP
OAS1
SLC27A5
UOX
CDO1
ACAT1
LDHA
CASP6

0.95
0.34
0.45
0.95
 0.27
0.23
0.81
0.97
0.39
0.42
0.18
0.27
0.65
0.49
0.80
0.51

0.015
0.19
0.079
0.018
0.30
0.37
0.00180.00020
0.13
0.10
0.49
0.31
0.012
0.060
0.00190.048

See Tables 5 and 6 for the gene name of each gene symbol used in this Table.

blood transporter of vitamin D3 and its active metabolites, 25hydroxy vitamin D3 (25-OH-D3) and 1,25-dihydroxy vitamin D3(1α, 25-(OH)2-D3), and vitamin D receptor (VDR) is activated by
1α, 25-(OH)2-D3 (Safadi et al., 1999; Christakos et al., 2003; Ting
et al., 2005). Considering that DBP mRNA levels decrease withhigher dioxin-like PCB concentrations, the AHR agonist could
prevent the distribution of the biologically active form of vitamin
D3 through the blood stream and result in the reduction of VDR
activation in peripheral tissues. Consistent with our results,
Lilienthal et al. (2000) has reported that exposure to PCB mixtures,
which were reconstituted based on the PCB congener proﬁle inhuman breast milk, dose-dependently reduced serum concentrations of 1α, 25-(OH)2-D3 in the dam and offspring of Long-Evansrats. Another study has also demonstrated that 25-(OH)-D3 levelsin the plasma of Long-Evans rats decreased after TCDD treatment(Fletcher et al., 2005). In addition, 1α,25-(OH)2-D3 has been
associated with the anti-proliferative effects on human cancer
cells through VDR (Caputo et al., 2003), as well as with the controlof physiological conditions such as the immune system andcalcium homeostasis (Holick, 2003). Thus, the accumulation of
the coplanar PCB may lead to cancer promotion and physiologicaldisturbances through the reduced circulation of hydroxylated
vitamin D3 in minke whales. Besides, it has also been reported

that the circulatory reduction of hydroxylated vitamin D3 forms
could reduce CYP2C and CYP3A expression through VDR because
the ligand-activated VDR regulates the expression of multiple
target genes, including CYP2C and CYP3A (Pascussi et al., 2003).
This earlier ﬁnding is consistent with the result of the current
study in which DBP expression was positively correlated with bothCYP2C78 and CYP3A72 in the liver of minke whales (Fig. 2A and B).
ARA70 mRNA levels quantiﬁed by the real-time RT-PCR analysis
showed a signiﬁcant positive correlation with PCB169 levels(Fig. 1C). ARA70, which is also known as nuclear receptor coactivator 4 (NCOA4), is a co-regulator of the androgen receptor (AR)and is involved in the stability of AR (Hu et al., 2004). Ting et al.
(2005) suggested that AR shares ARA70 with VDR in both
receptor-mediated signaling cascades, and the crosstalk between
these two receptors is hence mediated by competing for ARA70.
Following the increased expression of ARA70 as induced bycoplanar PCB169, the enhancement of AR-mediated signaling
could induce the suppression of VDR-mediated signaling in acompetitive manner, together with the decreased delivery ofvitamin D as previously described.
KYNU mRNA levels and PCB126 concentrations showed asigniﬁcant negative correlation (Fig. 1B). KYNU participates inthe tryptophan metabolic pathway (Dale et al., 2000; Allegri
et al., 2004; Stone and Darlington 2002) and plays an importantrole in the biosynthesis of the nicotinamide adenine dinucleotide[NAD(H)] and its phosphorylated form, NADP(H). In this pathway,
KYNU catalyzes the hydrolysis of kynurenine to anthranilic acidand of 3-hydroxykynurenin to 3-hydroxyanthranilic acid (Daleet al., 2000; Allegri et al., 2004). Mostafa et al. (1983) investigatedthe effects of a technical PCB mixture, Aroclor 1254, on thetryptophan metabolic pathway, in which PCB-treated mice
showed a reduction of KYNU and kynurenine aminotransferase
activities in the liver. These observations may eventually lead tothe accumulation of kynurenines, thus affecting the nervous andimmune systems because kynurenines are involved in a wide
range of physiological and pathological processes (Opitz et al.,2011). More recently, some investigations have revealed thatkynurenine is an endogenous AHR ligand that alters the generation of regulatory T cells and IL-17-producing helper T cells(Nguyen et al., 2010; Mezrich et al., 2010).
Using data on mRNA expression levels of RPS3, OAS1, LDHA, and
CASP6 determined by real-time RT-PCR, an upregulation of OAS1,
RPS3, CASP6, and LDHA with increasing concentrations of γ-HCH

S. Niimi et al. / Ecotoxicology and Environmental Safety 108 (2014) 95–105

103

Fig. 2. Relationship between the expression level of DBP and (A) CYP2C78 or (B)
CYP3A72 in the liver of common minke whales. The mRNA levels of these genes
were quantiﬁed using real-time RT-PCR and expressed as the ratio relative to thehighest expression level observed among all analyzed samples. The relationships
were statistically examined using Spearman's rank correlation test.

alterations in the expression proﬁle of the minke whale liver cells
due to chemical exposure could result in apoptosis induction.

5. Conclusions

Fig. 1. Relationship between coplanar PCB concentrations and (A) DBP, (B) KYNU, or(C) ARA70 expression levels in the liver of the common minke whale. The mRNAlevels of these genes were quantiﬁed using real-time RT-PCR and expressed as theratio relative to the highest expression level observed among all analyzed
samples. The relationships were statistically examined using Spearman's rankcorrelation test.

was suggested (data not shown). Because these genes are associated with apoptosis (Cohen, 1997; Shim et al., 1998; ChawlaSarkar et al., 2003; Jang et al., 2004), it is thus possible that

The present study indicated that hepatic expression levels ofmultiple genes are associated with the accumulation of OCs in thecommon minke whale from the North Paciﬁc. The OC levels
analyzed in this study appeared not to reach the levels that
directly alter the expression of CYP1, 2, 3, and 4 isozymes. Nevertheless, some genes other than CYPs were signiﬁcantly correlatedwith OC concentrations. This suggests that these OC concentrations may be of concern in terms of effects. We imply that
exposure to coplanar PCBs resulted in a suppression of VDRmediated signaling cascades in peripheral tissues by reducing
DBP expression, and led to a downregulation of the transcriptionof hepatic CYP2C and 3A genes. The suppression of VDR signaling
pathway might have been induced by competing with the ARmediated signaling pathway for ARA70, which was upregulated by
the accumulation of coplanar PCBs. In addition, a decrease inhepatic KYNU expression due to the exposure to coplanar PCBs
might result in the enhanced accumulation of an endogenous aryl

104

S. Niimi et al. / Ecotoxicology and Environmental Safety 108 (2014) 95–105

hydrocarbon receptor, kynurenine, which might consequently
disrupt the nervous and immune systems. On the other hand,confounding factors such as physiological parameters (age, lipid,
and diet) other than chemical exposure may also be involved inaltered expression levels of these genes. In conclusion, this study
demonstrates that the minke whale oligo array may serve as a
useful tool in screening for potential genes that could have been
affected by the exposure to various environmental chemicals.
Since this study does not provide physiological and biochemical
validation, further research is necessary to evaluate the toxicological effects associated with the altered gene expressions.

Acknowledgments
The authors thank Prof. A. Subramanian (CMES, Ehime University) for critical reading of the manuscript. This work was
supported by the Grants-in-Aid for Scientiﬁc Research (S)(21221004 and 26220103) to H.I. and (S) (20221003) to S.T., andJoint Research Project under the Japan-Korea Basic Scientiﬁc
Cooperation Program for FY 2012 from the Japan Society for the
Promotion of Science. Financial assistance was also provided by
Global COE Program from the Ministry of Education, Culture,
Sports, Science and Technology, Japan. Funding support was also
given to E-Y.K. from the Basic Science Research Program throughthe National Research Foundation of Korea (NRF) funded by
the Ministry of Education, Science and Technology, Korea(2013R1A1A2A10010043 and 2012K2A2A4021504).

References
Adeeko, A., Li, D., Doucet, J., Cooke, G.M., Trasler, J.M., Robaire, B., Hales, B.F., 2003.
Gestational exposure to persistent organic pollutants: maternal liver residues,
pregnancy outcome, and effects on hepatic gene expression proﬁles in the dam
and fetus. Toxicol. Sci. 72, 242–252.
Allegri, G., Ragazzi, E., Costa, C.V., Caparrotta, L., Biasiolo, M., Comai, S., Bertazzo, A.,
2004. Tryptophan metabolism along the kynurenine pathway in diet-induced
and genetic hypercholesterolemic rabbits. Clin. Chim. Acta 350, 41–49.
Ankley, G.T., Bennett, R.S., Erickson, R.J., Hoff, D.J., Hornung, M.W., Johnson, R.D.,
Mount, D.R., Nichols, J.W., Russom, C.L., Schmieder, P.K., Serrrano, J.A.,
Tietge, J.E., Villeneuve, D.L., 2010. Adverse outcome pathways: a conceptual
framework to support ecotoxicology research and risk assessment. Environ.
Toxicol. Chem. 29 (3), 730–741.
Aono, S., Tanabe, S., Fujise, Y., Kato, H., Tatsukawa, R., 1997. Persistent organochlorines in minke whale (Balaenoptera acutorostrata) and their prey species
from the Antarctic and the North Paciﬁc. Environ. Pollut. 1, 81–89.
Boverhof, D.R., Burgoon, L.D., Tashiro, C., Chittim, B., Harkema, J.R., Jump, D.B.,
Zacharewski, T.R., 2005. Temporal and dose-dependent hepatic gene expression
patterns in mice provide new insights into TCDD-mediated hepatotoxicity.
Toxicol. Sci. 85, 1048–1063.
Boverhof, D.R., Burgoon, L.D., Tashiro, C., Sharratt, B., Chittim, B., Harkema, J.R.,
Mendrick, D.L., Zacharewski, T.R., 2006. Comparative toxicogenomic analysis of
the hepatotoxic effects of TCDD in Sprague Dawley rats and C57BL/6 mice.
Toxicol. Sci. 94, 398–416.
Caputo, A., Pourgholami, M.H., Akhter, J., Morris, D.L., 2003. 1,25-Dihydroxyvitamin
D(3) induced cell cycle arrest in the human primary liver cancer cell line
HepG2. Hepatol. Res. 26, 34–39.
Chawla-Sarkar, M., Lindner, D.J., Liu, Y.-F., Williams, B.R., Sen, G.C., Silverman, R.H.,
Borden, E.C., 2003. Apoptosis and interferons: role of interferon-stimulated
genes as mediators of apoptosis. Apoptosis 8, 237–249.
Christakos, S., Dhawan, P., Liu, Y., Peng, X., Porta, A., 2003. New insights into themechanisms of vitamin D action. J. Cell. Biochem. 88, 695–705.
Cohen, G.M., 1997. Caspases: the executionsers of apoptosis. Biochem. J. 326, 1–16.
Dale, W.E., Dang, Y., Brown, O.R., 2000. Tryptophan metabolism through thekynurenine pathway in rat brain and liver slices. Free Radic. Biol. Med. 29,
191–198.
Fletcher, N., Giese, N., Schmidt, C., Stern, N., Lind, P.M., Viluksela, M., Tuomisto, J.T.,
Tuomisto, J., Nau, H., Hakansson, H., 2005. Altered retinoid metabolism infemale Long-Evans and Han/Wistar rats following long-term 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)-treatment. Toxicol. Sci. 86, 264–272.
Hirakawa, S., Iwata, S., Takeshita, Y., Kim, E.Y., Sakamoto, T., Okajima, Y., Amano, M.,
Miyazaki, N., Petrov, E.A., Batoev, V.B., Tanabe, S., 2007. Molecular characterization of cytochrome P4501A1, 1A2, and 1B1, and effects of polychlorinateddibenzo-p-dioxin, dibenzofuran, and biphenyl congeners on their hepatic
expression in Baikal seal (Pusa sibrica). Toxicol. Sci. 97, 318–335.

Hirakawa, S., Imaeda, D., Nakayama, K., Udaka, M., Kim, E.Y., Kunisue, T., Ogawa, M.,
Matsuda, T., Matsui, S., Petrov, E.A., Batoev, V.B., Tanabe, S., Iwata, H., 2011.
Integrative assessment of potential effects of dioxins and related compounds inwild Baikal seals (Pusa sibirica): application of microarray and biochemical
analyses. Aquat. Toxicol. 105, 89–99.
Holick, M.F., 2003. Vitamin D: a millenium perspective. J. Cell. Biochem. 88 (2),296–307.
Hu, Y.C., Yeh, S., Yeh, S.D., Sampson, E.R., Huang, J., Li, P., Hsu, C.L., Ting, H.J., Lin, H.K.,
Wang, L., Kim, E., Ni, J., Chang, C., 2004. Functional domain and motif analysesof androgen receptor coregulator ARA70 and its differential expression in
prostate cancer. J. Biol. Chem. 279, 33438–33446.
Iwata, H., Tanabe, S., Sakai, N., Tatsukawa, R., 1993. Distribution of persistentorganochlorines in the oceanic air and surface seawater and the role of ocean
on their global transport and fate. Environ. Sci. Technol. 27 (6), 1080–1098.
Iwata, H., Watanabe, M., Okajima, Y., Tanabe, S., Amano, M., Miyazaki, N., Petrov, E.
A., 2004. Toxicokinetics of PCDD, PCDF, and coplanar PCB congeners in Baikal
seals, Pusa sibirica: age-related accumulation, maternal transfer, and hepatic
sequestration. Environ. Sci. Technol. 38, 3505–3513.
Jang, C.Y., Lee, J.Y., Kim, J., 2004. RpS3, a DNA repair endonuclease and ribosomal
protein, is involved in apoptosis. FEBS Lett. 56, 81–85.
Kajiwara, N., Watanabe, M., Amano, M., Yamada, T., Tanabe, S., 2004. Speciesspeciﬁc accumuration of dioxin related compounds in cetaceans collected fromJapanease coastal waters. Organohalogen Compd. 66, 1554–1558.
Kajiwara, N., Kunisue, T., Kamikawa, S., Ochi, Y., Yano, S., Tanabe, S., 2006.
Organohalogen and organotin compounds in killer whales mass-stranded in
the Shiretoko Peninsula, Hokkaido, Japan. Mar. Pollut. Bull. 52, 1066–1076.
Kim, E.Y., Iwata, H., Fujise, Y., Tanabe, S., 2004. Searching for novel CYP members
using cDNA library from a minke whale liver. Mar. Environ. Res. 58, 495–498.
Kim, E.Y., Suda, T., Tanabe, S., Batoev, V.B., Petrov, E.A., Iwata, H., 2011. Evaluation ofrelative potencies for in vitro transactivation of the Baikal Seal aryl hydrocarbon
receptor by dioxin-like compounds. Environ. Sci. Technol. 45, 1652–1658.
Kopec, A.K., Burgoon, L.D., Ibrahim-Aibo, D., Burg, A.R., Lee, A.W., Tashiro, C.,
Potter, D., Sharratt, B., Harkema, J.R., Rowlands, J.C., Budinsky, R.A., Zacharewski, T.R., 2010. Automated dose–response analysis and comparative toxicogenomic evaluation of the hepatic effects elicited by TCDD, TCDF, and PCB126 in
C57BL/6 mice. Toxicol. Sci. 118, 286–297.
Kubota, A., Watanabe, M., Kunisue, T., Kim, E.Y., Tanabe, S., Iwata, H., 2010. Hepatic
CYP1A induction by chlorinated dioxins and related compounds in theendangered black-footed albatross from the North Paciﬁc. Environ. Sci. Technol.
44, 3559–3565.
Kunisue, T., Nakanishi, S., Oka, N., Sato, F., Tsurumi, M., Tanabe, S., 2006. Dioxins andrelated compounds in albatrosses from the Torishima Island, Japan: accumulation features by growth stage and toxicological implications. Environ. Sci.
Technol., 40; , pp. 6919–6927.
Lilienthal, H., Fastabend, A., Hany, J., Kaya, H., Roth-Harer, A., Dunemann, L., Winneke, G.,2000. Reduced levels of 1,25-dihydroxyvitamin D(3) in rat dams and offspring after
exposure to a reconstituted PCB mixture. Toxicol. Sci. 57, 292–301.
Mezrich, J.D., Fechner, J.H., Zhang, X., Johnson, B.P., Burlingham, W.J., Bradﬁeld, C.A.,
2010. An interaction between kynurenine and the aryl hydrocarbon receptor
can generate regulatory T cells. J. Immunol. 185, 3190–3198.
Moon, H.B., Kannan, K., Choi, H.G., An, Y.R., Choi, S.G., Park, J.Y., Kim, Z.G., 2010.
Concentrations and accumulation features of PCDDs, PCDFs and dioxin-like
PCBs in cetaceans from Korean coastal waters. Chemosphere 79 (9),733–739.
Mostafa, M.H., El-Bassiouni, E.A., El-Sewedy, S.M., El-Zoghby, S.M., Ramadan, M.,
Abdel-Tawab, G.A., El-Sebae, A.H., 1983. Effect of some xenobiotics on kynurenine hydrolase and kynurenine aminotransferase of mouse liver. J. Environ.
Sci. Health B 18, 393–399.
Nakayama, K., Iwata, H., Kim, E.Y., Tashiro, K., Tanabe, S., 2006. Gene expression
proﬁling in common cormorant liver with an oligo array: assessing thepotential toxic effects of environmental contaminants. Environ. Sci. Technol.
40, 1076–1083.
Nguyen, N.T., Kimura, A., Nakahama, T., Chinen, I., Masuda, K., Nohara, K., FujiiKuriyama, Y., Kishimoto, T., 2010. Aryl hydrocarbon receptor negatively regulates dendritic cell immunogenicity via a kynurenine-dependent mechanism.
Proc. Natl. Acad. Sci. USA 107, 19961–19966.
Niimi, S., Watanabe, M.X., Kim, E.Y., Iwata, H., Yasunaga, G., Fujise, Y., Tanabe, S.,
2005. Molecular cloning and mRNA expression of cytochrome P4501A1 and
1A2 in the liver of common minke whales (Balaenoptera acutorostrata). Mar.
Pollut. Bull. 51, 784–793.
Niimi, S., Kim, E.Y., Iwata, H., Watanabe, M.X., Yasunaga, G., Fujise, Y., Tanabe, S.,
2007. Identiﬁcation and hepatic expression proﬁles of cytochrome P450 1-4
isozymes in common minke whales (Balaenoptera acutorostrata). Comp. Biochem. Physiol. B Biochem. Mol. Biol. 147, 667–681.
Opitz, C.A., Litzenburger, U.M., Sahm, F., Ott, M., Tritschler, I., Trump, S., Schumacher, T., Jestaedt, L., Schrenk, D., Weller, M., Jugold, M., Guillemin, G.J., Miller, C.
L., Lutz, C., Radlwimmer, B., Lehmann, I., von Deimling, A., Wick, W., Platten, M.,
2011. An endogenous tumour-promoting ligand of the human aryl hydrocarbon
receptor. Nature 478 (7368), 197–203.
Pascussi, J.M., Gerbal-Chaloin, S., Drocourt, L., Maurel, P., Vilarem, M.J., 2003. The
expression of CYP2B6, CYP2C9 and CYP3A4 genes: a tangle of networks ofnuclear and steroid receptors. Biochim. Biophys. Acta 1619, 243–253.
Safadi, F.F., Thornton, P., Magiera, H., Hollis, B.W., Gentile, M., Haddad, J.G.,
Liebhaber, S.A., Cooke, N.E., 1999. Osteopathy and resistance to vitamin D
toxicity in mice null for vitamin D binding protein. J. Clin. Investig. 103,
239–251.

S. Niimi et al. / Ecotoxicology and Environmental Safety 108 (2014) 95–105

Shim, H., Chun, Y.S., Lewis, B.C., Dang, C.V., 1998. A unique glucose-dependent
apoptotic pathway induced by c-Myc. Proc. Natl. Acad. Sci. USA 95, 1511–1516.
Stone, T.W., Darlington, L.G., 2002. Endogenous kynurenines as targets for drug
discovery and development. Nat. Rev. Drug Discov. 1 (8), 609–620.
Tamura, T., Fujise, Y., 2002. Geographical and seasonal changes of the prey speciesof minke whale in the Northwestern Paciﬁc. J. Mar. Sci. 59, 516–528.
Tanabe, S., Iwata, H., Tatsukawa, R., 1994. Global contamination by persistentorganochlorines and their ecotoxicological impact on marine mammals. Sci.
Total Environ. 154, 163–177.
Ting, H.J., Bao, B.Y., Hsu, C.L., Lee, Y.F., 2005. Androgen-receptor coregulators
mediate the suppressive effect of androgen signals on vitamin D receptor
activity. Endocrine 26 (1), 1–9.
Van Aggelen, G., Ankley, G.T., Baldwin, W.S., Bearden, D.W., Benson, W.H., Chipman,
J.K., Collette, T.W., Craft, J.A., Denslow, N.D., Embry, M.R., Falciani, F., George, S.
G., Helbing, C.C., Hoekstra, P.F., Iguchi, T., Kagami, Y., Katsiadaki, I., Kille, P., Liu,
L., Lord, P.G., McIntyre, T., O'Neill, A., Osachoff, H., Perkins, E.J., Santos, E.M.,
Skirrow, R.C., Snape, J.R., Tyler, C.R., Versteeg, D., Viant, M.R., Volz, D.C.,
Williams, T.D., Yu, L., 2010. Integrating omic technologies into aquatic ecologicalrisk assessment and environmental monitoring: hurdles, achievements, andfuture outlook. Environ. Health Perspect. 118, 1–5.

105

Van den Berg, M., Birnbaum, L.S., Denison, M., De Vito, M., Farland, W., Feeley, M.,
Fiedler, H., Hakansson, H., Hanberg, A., Haws, L., Rose, M., Safe, S., Schrenk, D.,
Tohyama, C., Tritscher, A., Tuomisto, J., Tysklind, M., Walker, N., Peterson, R.E.,
2006. The 2005 World Health Organization re-evaluation of human andmammalian toxic equivalency factors for dioxins and dioxin-like compounds.
Toxicol. Sci. 93, 223–241.
Vezina, C.M., Walker, N.J., Olson, J.R., 2004. Subchronic exposure of TCDD, PeCDF,
PCB126, and PCB153: effect on hepatic gene expression. Environ. Health
Perspect. 112, 1636–1644.
Villeneuve, D.L., Garcia-Reyero, N., 2011. Vision & strategy: predictive ecotoxicology
in the 21st century. Environ. Toxicol. Chem. 30 (1), 1–8.
Williams, T.D., Gensberg, K., Minchin, S.D., Chipman, J.K., 2003. A DNA expression
array to detect toxic stress response in European ﬂounder (Platichthys ﬂesus).
Aquat. Toxicol. 65, 141–157.
Zeiger, M., Haag, R., Hockel, J., Schrenk, D., Schmitz, H.J., 2001. Inducing effects ofdioxin-like polychlorinated biphenyls on CYP1A in the human hepatoblastoma
cell line HepG2, the rat hepatoma cell line H4IIE, and rat primary hepatocytes:
comparison of relative potencies. Toxicol. Sci. 63, 65–73.
Zeytun, A., McKallip, R.J., Fisher, M., Camacho, I., Nagarkatti, M., Nagarkatti, P.S.,
2002. Analysis of 2,3,7,8-tetrachlorodibenzo-p-dioxin-induced gene expression
proﬁle in vivo using pathway-speciﬁc cDNA arrays. Toxicology 178, 241–260.