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Keywords:

  • Oyster;
  • Crassostrea brasiliana;
  • Gene transcription;
  • Suppressive subtractive hybridization;
  • Diesel fuel

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. Acknowledgements
  7. REFERENCES

Diesel fuel can cause adverse effects in marine invertebrates by mechanisms that are not clearly understood. The authors used suppressive subtractive hybridization to identify genes up- and downregulated in Crassostrea brasiliana exposed to diesel fuel. Genes putatively involved in protein regulation, innate immune, and stress response, were altered by diesel challenge. Three genes regulated by diesel were validated by quantitative real-time polymerase chain reaction. This study sheds light on transcriptomic responses of oysters to diesel pollution. Environ. Toxicol. Chem. 2012;31:1249–1253. © 2012 SETAC


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. Acknowledgements
  7. REFERENCES

Petroleum by-products often occur in the marine environment as a complex mixture of compounds with the potential to cause harmful effects to aquatic biota. Thus, evaluating and predicting the toxic effects of petrochemicals on aquatic organisms have become important issues for implementing risk assessment studies 1. Biomonitoring surveys usually employ a combination of chemical analysis with the measurement of biochemical biomarkers in bivalve tissues. However, some studies have yielded inconsistent results 2, perhaps because many of these biomarkers have their origins in human toxicology 3 and are not appropriate for mollusk studies.

To identify novel bivalve-specific biomarkers in response to exposure to petroleum-related compounds, we used the suppressive subtractive hybridization (SSH) assay to construct normalized cDNA libraries of up- and downregulated genes from the digestive gland of the mangrove oyster, Crassostrea brasiliana, following short-term exposure to a complex mixture of diesel fuel water-accommodated fraction (WAF). In addition, the relative transcription of genes of interest was analyzed by using quantitative real-time polymerase chain reaction (qPCR). The current results will serve as a basis for future studies on the molecular mechanisms behind diesel toxicity in an ecologically and economically important oyster species.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. Acknowledgements
  7. REFERENCES

Adult oysters, C. brasiliana, of similar shell length (6.0–8.0 cm) were supplied by the oyster culture facility from the Federal University of Santa Catarina, Florianópolis, southern Brazil. They were acclimatized for 7 d prior to chemical exposure in aerated tanks with 0.45-µm-filtered seawater at 21°C and salinity of 25 ppt. Oysters were fed twice per day on microalgae (Chaetoceros muelleri and Isochrysis sp.) at a density of 3.3 × 106 cells mL−1 and 2.2 × 106 cells mL−1, respectively, and water was changed daily. Diesel fuel WAF was prepared as described previously 4 with a 10% diesel WAF (v/v) chosen based on previous results from biochemical biomarker experiments in our laboratory using C. brasiliana5. Oysters were exposed to 10% WAF for 24 h, in addition to a separate nonexposed control group. The experiment was carried out in duplicate, and the animals were not fed during the exposure period.

Suppressive subtractive hybridization was used to identify diesel-regulated genes in oysters. After 24 h of exposure, total RNA was extracted from the digestive gland (∼500 mg) of six controls and six exposed animals using TRIzol reagent (Invitrogen) and subsequently pooled into two corresponding groups. The SSH method was employed twice on different occasions. For the initial experiment, poly-A+ RNA (mRNA) was isolated from each pool of total RNA using the Poly(A)Purist Kit (Ambion), whereas the second experiment was performed using the MicroPoly(A)Purist Kit (Ambion), following the manufacturer's instructions. The integrity of the purified mRNA was assessed by using formaldehyde agarose gel electrophoresis, and quantity was determined by using a NanoDrop ND-1000 Spectrophotometer (Thermo Scientific).

Subtractive hybridizations were performed in both directions to obtain both up- and downregulated genes. The forward libraries contained cDNA fragments of genes more highly transcribed in the digestive gland of the diesel-challenged oysters, in which the exposed animals are referred to as “tester” and the control animals are called “driver.” The reverse libraries contained those genes that were down regulated by diesel WAF, in which the tester and driver designations for the groups are switched. Briefly, both SSH libraries were constructed with 2 µg mRNA each, using the PCR Select cDNA Subtraction Kit (Clontech), then amplified with the Advantage cDNA PCR Kit (Clontech), following the manufacturer's instructions. The differentially expressed PCR products were cloned into the pGEM-T vector (Promega) and transformed into competent JM-109 cells (Promega), and colonies were then grown in liquid ampicillin-LB medium. Plasmids were then extracted and purified using the Perfectprep Plasmid Mini Kit (Eppendorf). Clones from four SSH libraries, two forward and two reverse, were sequenced using the MegaBACE 1000 DNA Analysis System (GE Healthcare). Sequences were visually checked for possible sequencing errors, and vector and adaptor sequences were removed using VecScreen (www.ncbi.nlm.nih.gov/VecScreen). The trimmed sequences from each SSH were assembled by CAP3 using default parameters 6. After assembly, contigs and singletons were aligned against the NCBI nonredundant (nr) protein database using the BlastX algorithm (E value threshold of 10−6). Resulting BlastX hits were fed into the Blast2GO v.2.5.0 platform to retrieve associated gene ontology terms 7.

Eight candidate genes potentially regulated by diesel WAF were selected for validation of SSH results by quantitative real-time PCR (qPCR; Table 1). Among them, vdg3-like was used as an endogenous reference gene, because it can be regarded as a digestive gland-specific marker 8 (Table 1). The qPCR analyses were carried out on the same total RNA samples used for subtractions. Total RNA (1 µg) from both control and exposed oysters was DNase treated then reverse transcribed using the QuantiTect Reverse Transcription Kit (Qiagen) with a mixture of oligo-dT and random primers. After cDNA synthesis, qPCR using the Rotor-Gene SYBR Green PCR Kit (Qiagen) and a Rotor-Gene 6000 real-time qPCR system (Qiagen) was applied to quantify gene transcription levels in diesel-challenged and control oysters. The PCR amplification was performed using the fast two-step cycling program as follows: 5 min at 95°C, and 40 cycles of 5 s at 95°C and 10 s at 60°C, as recommended by the manufacturer. Polymerase chain reaction products were subjected to melt curve analysis to ensure that nonspecific priming was absent in samples. Each primer pair amplified a single PCR fragment, and the vdg3 was used as an endogenous reference gene. The relative mRNA expression ratio for each gene was analyzed using an efficiency-corrected ΔΔCt method, normalizing to the endogenous reference gene 9. The p values were obtained using a pairwise fixed reallocation randomization test (2,000 iterations) using the relative expression software tool (REST 2009) 9. Differences were considered statistically significant at p < 0.01.

Table 1. Primer sequences used for qPCR for the amplification of genes of interest from both forward and reverse libraries with putative gene name and amplicon size (bp)
Gene namePrimer sequence 5′–3′Amplicon size (bp)
  1. qPCR = quantitative real-time polymerase chain reaction; ERG = endogenous reference gene.

Forward library  
 vdg3 (ERG)F - TTCACTGGTGGCGAGGTTGGATGGT142
 R - CCGAGGTCCAATGTGAACATGAATGCCACG 
 Beta-tubulinF - GGGCTAAGGGACACTACACAGAAGGAGC146
 R - TGTTCCCATACCAGATCCGGTGCCA 
 Alpha-tubulinF - TGAGGCCCGTGAAGATCTTGCTGC91
 R - ACCACCCTCCTCTTCAGCTTCACCT 
 Ubiquitin specific peptidase 25F - CAGGAGGAAGTCATGGGCAAGGAGATGG135
 R - TCTCTGCATGCTGAACAGGGAGGTTTGA 
Reverse library 140
 Dominin precursorF - GCAGCAAGCGATGATGGAGGTATGGC 
 R - ATGACGACGAGCACGGAGAGGTGA 
 Universal stress proteinF - CTGACCCATCAGTTGCGGCCTTGA92
 R - AAATCCGGACTCCATCACCCACGC 
 Serine protease CFSP2F - TCGCTGGTGGTTTAGCCTCGGTCT83
 R - TGTGGAGGCCATCCGTAAAGCTGC 
 Nucleoside diphosphate kinase BF - TCCAGTGGGTTGGTGGCTCCTAACAT120
 R - GGGTTTCTTTGCTGGTCTGGTCGCA 

RESULTS AND DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. Acknowledgements
  7. REFERENCES

In total, 252 clones were processed and 208 sequences (82.5% of the total) were obtained, with 66 unique genes identified from 20 contigs and 46 singletons (Table 2). BlastX analysis of expressed sequence tags revealed that 23 (34.85%) matched known genes in the NCBI nr protein database, which is consistent with previous studies carried out with mollusks exposed to different environmental contaminants 10–12. Among the 23 annotated sequences, 20 (87.96%) were assigned with one or more gene ontology terms, which are summarized in Tables 3 and 4. For the forward libraries, in total, 430 gene ontology assignments were obtained, with 259 for biological processes, 88 for molecular functions, and 83 for cellular components. The reverse libraries accounted for 203 assignments in biological processes, 63 for molecular functions, and 49 for cellular components, totaling 315 gene ontology terms. Genes involved in catalytic activity, binding, protein binding, and metabolic processes constituted the majority of the transcripts in the digestive glands of oysters.

Table 2. General characteristics of suppressive subtractive hybridization libraries and expressed sequence tags obtained from digestive gland of Crassostrea brasilianaa
 Forward SSH1Forward SSH2Reverse SSH1Reverse SSH2
  • a

    Forward library: enriched for genes expressed by diesel-challenged oysters. Reverse library: enriched for genes expressed by control oysters.

    SSH = suppressive subtractive hybridization; SSH1 = sequences obtained from the first SSH; SSH2 = sequences obtained from the second SSH.

Total no. clones sequenced96726024
Total no. clones analyzed82595116
Contigs12242
Singletons1413181
Total no. sequences with BlastX match10373
Total no. sequences with no BlastX match161215
Table 3. List of identified suppressive subtractive hybridization up-regulated genes in the digestive gland of Crassostrea brasiliana exposed to diesel fuel water-accommodated fraction
Putative match; BlastX e valueSSHaGenBank No.Gene ontology termGene ontology description
  • a

    Origin of the sequences: 1 = SSH library 1; 2 = SSH library 2.

  • SSH = suppressive subtractive hybridization; ATP = adenosine triphosphate.

Cytoskeleton (30.77%)    
 Helcion pellucidus actin; 3e-711AAS20338GO:0005856; GO:0005737; GO:0005524Cytoskeleton; cytoplasm; ATP binding
 Sepia officinalis beta actin; 2e-402AEE87267GO:0005829; GO:0005200; GO:0030048Cytosol; structural constituent of cytoskeleton; actin filament-based movement
 Drosophila yakuba alpha tubulin; 6e-1241AAR09810GO:0005874; GO:0007018; GO:0005198Microtubule; microtubule-based movement; structural molecule activity
 Hydractinia echinata beta tubulin; 3e-161AAX47550GO:0005874; GO:0007018; GO:0005198Microtubule; microtubule-based movement; structural molecule activity
Translation machinery (23.08%)    
 Argopecten irradians ribosomal protein L9; 3e-562AAN05606GO:0022625; GO:0003735; GO:0006412Cytosolic large ribosomal subunit; structural constituent of ribosome; translation
 Crassostrea gigas ribosomal protein S3; 2e-1122CAD91420GO:0022627; GO:0006413; GO:0006414Cytosolic small ribosomal subunit; translational initiation; translational elongation
 Pongo abelii translation elongation factor 3δ; 2e-281XP_002831114GO:0005852; GO:0001732; GO:0003743Eukaryotic translation initiation factor 3 complex; formation of translation initiation complex; translation initiation factor activity
Respiratory chain (15.38%)    
 Crassostrea gigas cytochrome c oxidase subunit III; e-671AAF20042GO:0006123; GO:0004129; GO:0016021Mitochondrial electron transport, cytochrome c to oxygen; cytochrome-c oxidase activity; integral to membrane
 Crassostrea virginica NADH dehydrogenase subunit 5; 9e-411YP_254656GO:0005739; GO:0008137; GO:0042773Mitochondrion; NADH dehydrogenase (ubiquinone) activity; ATP synthesis coupled electron transport
Protein regulation (7.69%)    
 Xenopus laevis ubiquitin specific peptidase 25; e-251NP_001086746GO:0008233; GO:0019538Peptidase activity; protein metabolic process
Immune response (7.69%)    
 Mytilus galloprovincialis C1q domain-containing protein 1; e-101CBX41678  
Energetic metabolism (7.69%)    
 Mytilus edulis vdg3; 7e-061ABB76764  
Predicted protein (7.69%)    
 Nematostella vectensis predicted protein; 8e-191XP_001625243  
Table 4. List of identified suppressive subtractive hybridization downregulated genes in the digestive gland of Crassostrea brasiliana exposed to diesel fuel water-accommodated fraction
Putative match; BlastZ e valueSSHaGenBank No.Gene ontology termGene ontology description
  • a

    Origin of the sequences: 1 = SSH library 1; 2 = SSH library 2.

    SSH = suppressive subtractive hybridization; GTP = γ-glutamyltranspeptidase; USP = universal stress protein.

Translation machinery (60%)
 Crassostrea gigas ribosomal protein S23; 6e-561AAX47435GO:0022627; GO:0003735; GO:0006417Cytosolic small ribosomal subunit; structural constituent of ribosome; regulation of translation
 Arenicola marina ribosomal protein L4; e-081ABW23158GO:0022625; GO:0005886; GO:0005730Cytosolic large ribosomal subunit; plasma membrane; nucleolus
 Crassostrea gigas ribosomal protein L19; 8e-301CAD91441GO:0022625; GO:0003735; GO:0006412Cytosolic large ribosomal subunit; structural constituent of ribosome; translation
 Crassostrea ariakensis elongation factor 1-α; 3e-1551ABS30425GO:0005737; GO:0003746; GO:0006414Cytoplasm; translation elongation factor activity; translational elongation
 Amblyomma maculatum eukaryotic translation initiation factor 1b; e-412AEO34903GO:0006417; GO:0003743; GO:0006413Regulation of translation; translation initiation factor activity; translational initiation
 Crassostrea ariakensis bifunctional aminoacyl-trna synthetase; 6e-361ABV44793GO:0006461; GO:0004827; GO:0004818Protein complex assembly; proline-tRNA ligase activity; glutamate-tRNA ligase activity
Immune response (10%)
 Crassostrea virginica dominin precursor; 8e-202BAF30874GO:0004784; GO:0006801; GO:0055114Superoxide dismutase activity; superoxide metabolic process; oxidation reduction
Stress response (10%)    
 Clonorchis sinensis universal stress protein (USP); 2e-121GAA35932GO:0006950Response to stress
Protein regulation (10%)    
 Chlamys farreri serine protease CFSP2; 2e-232ABB89131GO:0008236Serine-type peptidase activity
Nucleic acid regulation (10%)    
 Haliotis discus discus nucleoside diphosphate kinase B; 2e-501ABO26651GO:0006165; GO:0004550; GO:0006183Nucleoside diphosphate phosphorylation; nucleoside diphosphate kinase activity; GTP biosynthetic process

Following the BlastX annotation, our data showed that different pathways of oyster metabolism were changed in both forward (Table 3) and reverse (Table 4) directions after diesel exposure. The most abundant upregulated transcripts identified were associated with the cytoskeleton (30.77%), followed by translation (23.08%) and respiratory processes (15.38%). Genes encoding proteins of the cytoskeleton have also been identified in forward SSH libraries obtained from oysters (Crassostrea gigas) and copepods (Calanus finmarchicus) exposed to hydrocarbons and environmental stressors, respectively 10, 13. In a previous study, however, mussels (Mytilus spp.) showed reduced mRNA levels of an actin gene in the digestive gland following exposure to crude oil 14, indicating that the regulation of cytoskeleton-related genes differs between mollusk species. In fact, our qPCR data showed an unexpected result, in that neither of the cytoskeleton genes (alpha and beta-tubulin-like) of C. brasiliana chosen from the forward library seems to be regulated by diesel (Fig. 1). Moreover, this finding might represent a limitation of the SSH technique, as previously suggested 15.

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Figure 1. Relative gene transcription of putative up- and downregulated genes identified in suppressive subtractive hybridization (SSH) libraries from the digestive gland of oysters Crassostrea brasiliana exposed for 24 h to 10% diesel fuel water-accommodated fraction (WAF). The gene transcript levels were assessed by quantitative real-time polymerase chain reaction (qPCR) and transcription of tester genes are relative to the driver group in both SSH directions as follows: the forward library refers to expected upregulation genes in treated animals, where the diesel-challenged oysters are referred as “tester” and the control animals are called “driver”; the reverse library represents those genes in which downregulation by diesel WAF is expected, where the tester and driver designations for the groups are reversed. Note that the y axis is logarithmic to base 2 (n = 6 animals per group). Statistical analysis was performed using a pairwise fixed reallocation randomization test. *Significant (p < 0.01) transcription change (REST 2009 software from Qiagen). USP25 = ubiquitin-specific peptidase 25; CFSP2 = serine protease CFSP2; USP = universal stress protein; NDPK-B = nucleoside diphosphate kinase B.

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Genes encoding proteins putatively involved in translation were well represented in the reverse libraries (60%), which is consistent with previous findings obtained for C. gigas exposed to pesticides 16. In our study, the downregulated genes associated with translation machinery differed from those identified in the forward libraries, suggesting that the toxic effects of diesel WAF on downregulated genes might be compensated by the upregulation of other translation genes, maintaining the protein synthesis machinery. Therefore, our results further suggest that diesel differentially modulates the translation-related genes in the oyster. With regard to the regulation of protein synthesis, a gene encoding a deubiquitinating enzyme (ubiquitin-specific peptidase 25 [USP25]-like) was identified in the forward library. However, our qPCR results showed that USP25-like was down- and not upregulated as indicated by the SSH outcome (Fig. 1), suggesting a false-positive SSH result. On the other hand, the significant decrease of USP25-like transcription further suggests lower cellular levels of this protein in exposed oysters, resulting in an elevated rate of protein degradation 17.

With regard to the reverse libraries obtained in this study, three of the four genes selected for validation by qPCR confirmed the SSH results. Genes putatively encoding dominin precursor, universal stress protein (USP), and nucleoside diphosphate kinase B (NDPK-B) proteins were significantly downregulated after diesel exposure (Fig. 1). Dominin is considered the major plasma protein of oysters, playing an important role in the immune defense system 18. We have found that dominin precursor-like was significantly downregulated in exposed oysters, indicating that the diesel exposure elicited an impairment of the innate immune system. Surprisingly, the mRNA levels of CFSP2-like, a gene encoding protein that has recently been reported to participate in the innate immune responses in the pearl oyster, Pinctada fucata19, remained unchanged when evaluated by qPCR (Fig. 1). On the other hand, another immune system-related gene (C1q domain-containing protein 1-like) was identified in the forward libraries. Thus, based on the differences seen in the modulation of genes involved in the oysters' immune system, we can suggest a compensatory response to the diesel exposure, resulting in molecular mechanisms to keep up the animals' resistance against inflammatory or infectious processes.

Another important outcome derived from this study relates to the inhibition of the transcription of one gene related to the stress response by diesel treatment. The decrease in the USP-like mRNA levels indicates that the toxic response is being suppressed, possibly failing to protect the oysters from the toxic effects caused by diesel. This is consistent with a recent study in which environmental toxicants significantly inhibited the transcription of genes related to stress proteins in abalone, Haliotis rufescens11. Therefore, USP-like seems to be a good indicator of digestive gland tissue injuries in C. brasiliana following chemical challenge. Interestingly, a gene putatively involved in the maintenance of cellular levels of nucleoside triphosphates (NDPK-B-like) was downregulated by diesel. Although the reason for this remains unclear, it might suggest lower adenosine triphosphate levels in diesel-challenged animals.

In conclusion, novel early-warning molecular responses were studied for the first time in C. brasiliana exposed to diesel WAF. Suppressive subtractive hybridization allowed a comprehensive approach, demonstrating that protein regulation, immune response, and stress response systems seem to be compromised after diesel exposure. In this respect, changes in the transcription of USP25-like, dominin precursor-like, USP-like, and NDPK-B-like genes are potentially effective biomarkers of environmental contamination by petroleum by-products, thus acting as early-warning indicators. However, our results showed only partial success of the efficiency of the SSH technique, with only three of eight expressed sequence tags found to be differentially transcribed between diesel-challenged and control oysters. These findings highlight the need for using qPCR as a validation tool to confirm the transcriptomic data derived from SSH approaches in mollusks.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. Acknowledgements
  7. REFERENCES

This work was supported by grant 550706/2005-4 from CNPq-CTPetro to A.C.D. Bainy. The Brazilian agencies Capes (K.H. Lüchmann, J.J. Mattos, M.N. Siebert, G. Toledo-Silva, and P.H. Stoco) and CNPq (T.S. Dorrington) fellowships are acknowledged. A.C.D. Bainy and E.C. Grisard are recipients of CNPq productivity fellowships.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. Acknowledgements
  7. REFERENCES
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