ORIGINAL RESEARCH article

Front. Physiol., 01 February 2017

Sec. Aquatic Physiology

Volume 8 - 2017 | https://doi.org/10.3389/fphys.2017.00034

Skin Mucus of Gilthead Sea Bream (Sparus aurata L.). Protein Mapping and Regulation in Chronically Stressed Fish

  • 1. Nutrigenomics and Fish Growth Endocrinology Group, Biology, Culture and Pathology of Marine Species, Institute of Aquaculture Torre de la Sal (IATS-CSIC) Castellón, Spain

  • 2. Department of Biotechnology and Life Sciences, University of Insubria Varese, Italy

  • 3. Inter-University Centre for Research in Protein Biotechnologies “The Protein Factory” Polytechnic University of Milan and University of Insubria Varese, Italy

  • 4. Institute of Marine Research Matre Matredal, Norway

  • 5. Department of Biology, Norwegian University for Science and Technology Trondheim, Norway

  • 6. Fish Pathology Group Group, Biology, Culture and Pathology of Marine Species, Institute of Aquaculture Torre de la Sal (IATS-CSIC) Castellón, Spain

Abstract

The skin mucus of gilthead sea bream was mapped by one-dimensional gel electrophoresis followed by liquid chromatography coupled to high resolution mass spectrometry using a quadrupole time-of-flight mass analyzer. More than 2,000 proteins were identified with a protein score filter of 30. The identified proteins were represented in 418 canonical pathways of the Ingenuity Pathway software. After filtering by canonical pathway overlapping, the retained proteins were clustered in three groups. The mitochondrial cluster contained 59 proteins related to oxidative phosphorylation and mitochondrial dysfunction. The second cluster contained 79 proteins related to antigen presentation and protein ubiquitination pathways. The third cluster contained 257 proteins where proteins related to protein synthesis, cellular assembly, and epithelial integrity were over-represented. The latter group also included acute phase response signaling. In parallel, two-dimensional gel electrophoresis methodology identified six proteins spots of different protein abundance when comparing unstressed fish with chronically stressed fish in an experimental model that mimicked daily farming activities. The major changes were associated with a higher abundance of cytokeratin 8 in the skin mucus proteome of stressed fish, which was confirmed by immunoblotting. Thus, the increased abundance of markers of skin epithelial turnover results in a promising indicator of chronic stress in fish.

Introduction

A keratinized multi-sheet cellular layer (stratum corneum) covers the epidermis of amphibian adults, reptiles, birds and mammals, whereas skin mucus constitutes the outermost epidermal barrier in fish and aquatic amphibian larvae (Schempp et al., 2009). Cutaneous or skin mucus is thus considered a metabolically active tissue with important roles in respiration, ionic and osmotic regulation, excretion, locomotion, communication, sensory perception, thermal regulation and immunological defense (Negus, 1963; Shephard, 1994; Cone, 2009; Esteban, 2012). Several cell types are involved in regulating the composition of the skin mucus layer, although it is mainly shaped by Goblet cells that release mucous granules containing high molecular weight glycoproteins called mucins (Dharmani et al., 2009). These O-glycosylated glycoproteins are present on the apex of all wet-surfaced epithelia with a well-defined expression pattern, which can be disrupted in response to a wide range of injuries or challenges. For instance, recent experiments in gilthead sea bream (Sparus aurata L.) indicate that the gene expression pattern of gut mucins is altered by dietary oils and parasitic enteritis (Pérez-Sánchez et al., 2013b). In addition to glycoproteins, glycosaminoglycans, immunoglobulins, lectins, pheromones, and proteolytic enzymes have been identified in the mucus of different fish species (Fletcher and Grant, 1969; Hjelmeland et al., 1983; van de Winkel et al., 1986; Shiomi et al., 1988; Shephard, 1994; Subramanian et al., 2008; Guardiola et al., 2014; Ren et al., 2015). Most of these molecules are involved in fish innate immunity and skin mucus is considered a key component of fish immune responses (Ellis, 2001; Salinas et al., 2011; Esteban, 2012). This is certainly the result of the evolutionary adaptation of fish to survive in a variety of aquatic environments which are rich in pathogenic organisms. However, immune response can be depleted by stressful conditions, such as those resulting from high density or inappropriate aquaculture husbandry. Thus, limiting stress is now considered a key issue to reduce the economic losses due to opportunistic pathogens in intensive fish farming (Mancuso, 2012).

In teleost fish, stress activates the hypothalamus-pituitary-interrenal axis, leading to a rapid release of the glucocorticoid hormone cortisol by the interrenal tissue, the tissue analogous to the adrenal cortex of mammals (Pottinger, 2008; Pankhurst, 2011). Thus, high circulating levels of cortisol are commonly used as indicators of fish acute stress, though there is no consensus on the endocrine profile for chronically stressed animals or how to assess it without invoking further stress (Pankhurst, 2011; Dickens and Romero, 2013). This notion applies to gilthead sea bream exposed to chronic and acute stress (Arends et al., 1999; Rotllant et al., 2000; Calduch-Giner et al., 2010; Fanouraki et al., 2011), even in a higher manner when intermittent and repetitive stressors are considered (Tort et al., 2001; Ibarz et al., 2007). Hence, expression profiling of stress-responsive genes in different target tissues is envisaged as a complementary tool for assessing nutritional and environmental stress in fish (Terova et al., 2005, 2009; Rimoldi et al., 2012, 2016; Montero et al., 2015a,b), and gilthead sea bream in particular (Pérez-Sánchez et al., 2013a; Benedito-Palos et al., 2014; Bermejo-Nogales et al., 2014). However, this type of approach often requires sacrificing specimens, and the use of a biological sample collected in a minimally invasive manner is more advisable. Skin mucus fulfills such specifications, especially taking into account that one of the most apparent responses of fish to stress is the production of a copious amount of skin mucus (Vatsos et al., 2010). Thus, stress associated with live transport increased the production of sulfated and sialyated skin mucins in channel catfish (Tacchi et al., 2015). Ai-Jun et al. (2013) identified lectins and cytokeratins of skin mucus as bioindicators of thermal stress in turbot. Sea lice infestation increased the abundance of lectins in the skin mucus of Atlantic salmon (Easy and Ross, 2009), while transcriptional and proteomic approaches revealed differentially expressed proteins in the skin mucus of Atlantic cod upon natural infection with Vibrio anguillarum (Rajan et al., 2013). Likewise, metabolite profiling of fish skin mucus has been successfully applied as a novel approach for the monitoring and surveillance of wild fish health (Ekman et al., 2015; Dzul-Caamal et al., 2016).

Recently, important research efforts have also been invested in mapping the skin mucus proteome of warm-water marine fish, such as gilthead sea bream (Jurado et al., 2015; Sanahuja and Ibarz, 2015; Cordero et al., 2016) and European sea bass (Cordero et al., 2015), which are the two most important species in Mediterranean aquaculture. These studies have made important advances in defining the composition of fish mucus, also highlighting that both probiotics and overcrowding stress induce proteomic changes mostly involved in immune processes. However, so far, very little is known about the effects of other types of stressors that are closely related to daily farming activities, such as people walking alongside tanks, removal of dead fish, and changes in noise and/or light level that potentially provoke a wide variety of stimuli that are difficult to evaluate in a non-invasive and easy manner (Bratland et al., 2010; Nilsson et al., 2012). Thus, the goal of the present study was to gain new insights into the mucus composition of gilthead sea bream, contributing to identify robust and non-invasive biomarkers in a chronic stress model of daily farming activities, which have been previously characterized by means of more conventional stress biomarkers of fish performance at hormonal and liver transcriptional levels (Bermejo-Nogales et al., 2014). To pursue this issue, one-dimensional and two-dimensional proteomic approaches followed by mass spectrometry were combined, taking advantage of a homologous protein database derived from the IATS-CSIC gilthead sea bream transcriptome (Calduch-Giner et al., 2013) for consistent and reliable protein matches.

Materials and methods

Animals and mucus collection

Two-year old gilthead sea bream (average body weight of 320 g) coming from the study of Bermejo-Nogales et al. (2014) comprised a control unstressed group (CTRL) and a group of fish exposed to a model of chronic stress that consisted in a fast series of automated stressors (multiple sensorial stressed fish, M-ST): tank shaking, sounds, moving objects into water, water reverse flow and light flashes in random order for 30 min three times a day (9:30 h, 14:30 h, and 18:30 h) for a period of 21 days. At the end of experimental period, eight fish per group were randomly sampled and anesthetized with 100 mg/L MS-222 (Sigma, Saint Louis, MO, USA). Mucus was gently scraped off the normal skin surface of the left side of fish from operculum to tail with sterile microslides, avoiding collection of blood, urine, and feces along with mucus. Skin mucus was then transferred into Eppendorf tubes and immediately frozen at −80°C until analyzed. All procedures were performed wearing gloves to avoid human contaminations and according to the Norwegian National Ethics Board for experimentation with animals (ID No. 4007) and EU legislation (2010/63/EU) on the handling of experimental animals.

One-dimensional electrophoresis

The protein composition of mucus was first analyzed by one-dimensional electrophoresis (1-DE). Initially, mucus samples from all animals (CTRL and M-ST fish) were pooled, and triplicate samples (54-56 μg) were separated by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) using a TGX Any kD precast gel (Bio-Rad, Hercules, CA, USA) run at 200V for 25 min and stained overnight with colloidal Coomassie (Bio-Rad). The gel was then divided into 10 slices (0.65 cm) that were analyzed independently. Proteins in the gel were digested with protein-grade trypsin (Promega, Madison, WI, USA) and concentrated by speed vacuum at a final volume of 12 μL for mass spectrometry.

Two-dimensional electrophoresis

Individual samples of CTRL and M-ST fish (n = 8 for each group) were precipitated by means of the 2-D Clean-Up kit (GE HealthCare Life Sciences, Buckinghamshire, UK), and then solubilized in labeling buffer (7 M urea, 2 M thiourea, 4% w/v CHAPS, 20 mM Tris). The N-hydroxysuccinimide ester dyes Cy2/3/5 were used for minimal labeling following the mixed internal standard methodology of Alban et al. (2003) according to the manufacturer's protocol (GE HealthCare Life Sciences). Briefly, 50 μg of each experimental sample were individually labeled with 400 pmol of either Cy3 or Cy5. In parallel, a mixed internal standard was generated by combining equal amounts of each experimental sample, which were then labeled with 400 pmol of Cy2. Labeling was performed for 60 min on ice in the dark after which the reaction was quenched by adding 10 nM lysine for 10 min.

About 150 μg of protein (incubated in 65 mM DTT and 1% ampholytes) were loaded into Immobiline DryStrips (pH 3-11 NL, 24 cm), rehydrated overnight in 8 M urea, 4% w/v CHAPS, 12 μL/mL DeStreak reagent, 1% ampholytes. After focusing at 32 kVh at 20°C, strips were equilibrated first for 15 min in reducing solution (6 M urea, 50 mM Tris-HCl, 30% v/v glycerol, 2% w/v SDS, 2% w/v DTT) and then in alkylating solution (6 M urea, 50 mM Tris-HCl, 30% v/v glycerol, 2% w/v SDS, 2.5% w/v iodoacetamide) for 15 min. The second dimension (12.5% polyacrylamide, 25 × 21 cm) was run at 20°C at a constant power of 2 W for 60 min followed by 15 W until the bromophenol blue tracking front had run off the end of the gel (6 h). Fluorescence images were obtained on a Typhoon 9,400 scanner (GE HealthCare Life Sciences). Cy2, Cy3, and Cy5 images were scanned at excitation/emission wavelengths of 488/520 nm, 532/580 nm, and 633/670 nm, respectively, at a resolution of 100 μm. Image analysis was performed using DeCyder v.6.5 software (GE HealthCare Life Sciences). Protein spots displaying a statistically significant difference between groups were manually excised from analytical gels and digested with sequencing-grade trypsin prior to mass spectrometry analysis.

Mass spectrometry

Samples (5 μl) from 1-DE and two-dimensional electrophoresis (2-DE) were analyzed by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) using a quadrupole time-of-flight mass analyzer (qQTOF). Briefly, samples were loaded onto a trap column (NanoLC Column, 3 μ C18-CL, 350 μm × 0.5 mm, Nikkyo Technos Co. Ltd., Tokyo, Japan) desalted with 0.1% TFA at 3 μL/min for 10 min. Peptide mixtures were then loaded onto an analytical column (LC Column, 3 μ C18-CL, 75 μm × 12 cm, Nikkyo Technos Co. Ltd.) equilibrated in 5% acetonitrile and 0.1% formic acid. Separation was carried out with a linear gradient of 5–40% acetonitrile gradient with 0.1% formic acid at a flow rate of 300 nL/min. Peptides were analyzed in a high resolution nanoESI (qQ) TOF mass spectrometer (AB SCIEX TripleTOF 5,600 System, Applied Biosystems/MDS Sciex, Foster City, CA). The (qQ) TOF was operated in information-dependent acquisition mode, in which a 0.25-s TOF MS scan from 350 to 1,250 m/z, was performed, followed by 0.05 s product-ion scans from 100 to 1,500 m/z on the 50 most intensely 2–5 charged ions. The MS proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD004115 and PXD004116.

Protein identity was determined using ProteinPilot v4.5 (AB SCIEX, Applied Biosystems/MDS Sciex), which incorporated the Mascot search algorithm (v2.2, Matrix Science, London, UK). ProteinPilot default parameters were used to generate peak list directly from 5600 TripleTOF wiff files. Mascot was used to search the Expasy protein database or the IATS-CSIC gilthead sea bream database (www.nutrigroup-iats.org/seabreamdb) according to the following parameters: trypsin specificity, carbamidomethyl C to fix modification, deamidated (NQ), Gln->pyro-Glu (N-term Q), Glu->pyro-Glu (N-term E), oxidation (M) to variable modification, 75 ppm as peptide mass tolerance and 0.6 Da as fragment mass tolerance. Proteins with a ProteinPilot score higher than 1.3 were identified with a confidence interval ≥95%. Functional analysis of identified proteins was performed by means of the Ingenuity Pathway Analysis (IPA) software (www.ingenuity.com). For each protein in the analysis, the Uniprot accession equivalent for one of the three higher vertebrates model species in IPA (human, rat, or mouse) was searched as previously reported for the transcriptome-encoding proteins of gilthead sea bream (Calduch-Giner et al., 2013).

Western blot

In order to validate the results of 2-DE analysis, the increased abundance of keratin type II cytoskeletal 8 in M-ST compared to CTRL group was assessed by means of a Western blot analysis using an antibody directed to human cytokeratin 8. Total protein concentration from mucus samples of CTRL and M-ST fish was determined using the Bradford protein assay (Bio-Rad). The quantified protein analyzed remained almost equal in both experimental groups (1 μg/μl) and equal amounts from the two different groups were mixed with 2 × SDS sample buffer (1.5 M Tris, pH 8.8, 0.2% glycerol, 0.4% SDS, 0.1% 2-mercaptoethanol and 0.05% bromophenol blue), heated for 5 min at 50°C and separated by SDS-PAGE. After electrophoresis, proteins were transferred to polyvinylidenedifluoride (PVDF) membranes (Invitrogen, Gaithersburg, MD, USA) at 15 V for 1 h at room temperature. The membranes were then blocked in 5% nonfat dry milk prepared in TBS (20 Mm Tris pH 7.5, 500 mM NaCl) overnight at 4°C. After blocking, membranes were incubated with rabbit anti-human cytokeratin 8 antibody (PA5-29607, Thermo Scientific, Wilgminton, DE, USA) in antibody buffer (0.1% Tween 20, 1% bovine serum albumin), using a 1:2000 dilution of the supplied antibody concentration. The peptide immunogen (252 amino acids in length) of this primary antibody shared 81% identity (93% homology) with the gilthead sea bream sequence of cytokeratin 8. After primary antibody incubation, membranes were washed four times for 10 min each in T-TBS (TBS with 0.1% Tween 20), incubated with HRP-conjugated goat anti-rabbit IgG at 1:9000 dilution in antibody buffer for 2 h at room temperature, and washed four times for 10 min each in T-TBS. Immunodetection was performed using a chemiluminescent system (Western Blotting Luminol Reagent, Santa Cruz Biotechnologies, CA, USA) and the image on the membrane was captured by VersaDoc Imaging system model 5,000.

Statistical analyses

Quantification of relative protein levels in 2-DE electrophoresis was performed using Decyder v.6.5 software. Statistical significance was assessed using Student's t-test (p < 0.05) applying the false discovery rate (FDR) to minimize the number of false positive results. Western blot band intensity was quantified using Quantity One 1-D Analysis Software 4.5 (Bio-Rad) and results were compared by means of Student's t-test. The significance threshold was set at p < 0.05.

Results and discussion

Skin mucus proteins in gilthead sea bream

The current study analyzed the skin mucus of gilthead sea bream, combining 1-DE and 2-DE MS-based proteomic approaches. The primary finding was the large number of proteins that were identified by 1-DE followed by LC-HRMS in comparison to previous proteomic studies in this fish species, in which attention was focused on the most abundant proteins with an over-representation of structural and immune-related proteins. Hence, in the first reference proteome map of gilthead sea bream epidermal mucus (Sanahuja and Ibarz, 2015), up to 92 proteins were identified, and the Gene Ontology enrichment process resulted in 12 functional groups of proteins further classified as structural, metabolic and protection-related proteins. Likewise, a limited set of proteins clustered on structural (23), metabolic (25), stress-response proteins (2) and signal transduction (2) were already reported by Jurado et al. (2015). In Atlantic salmon, up to 521 proteins were identified and classified into nine main groups based on their putative biological processes (Provan et al., 2013). In the present study, 1,595 HRMS spectra were identified by comparing the results of the ProteinPilot with the Expasy protein database when the protein score filter was set up at 1.3. However, by using our gilthead sea bream protein database we identified 2,466 spectra with a much higher protein score (≥20). This number was significantly reduced to 2,060 when a protein score filter of 30 was applied (Table S1), but even in this case, the number of identified proteins was relatively high compared to the proteins that compose other mucosal tissues and body fluids in humans (de Souza et al., 2006; Lee et al., 2009; Marimuthu et al., 2011) and other animal models (Sánchez-Juanes et al., 2013; Bennike et al., 2014; Winiarczyk et al., 2015). Certainly, this was favored by the use of a homologous protein database derived from a reference transcriptome with a high coverage of protein-codifying sequences (more than 15,000 unique sequences in Swissprot database), which first increased the consistency of annotation in parallel with the number of protein isoforms or subunits of a given enzyme or protein complex represented in the analyzed samples (e.g., enzyme subunits of the mitochondrial respiratory chain; protein subunits of the eukaryotic translation initiation factor; ribosomal proteins; proteasome subunits, etc.). Alternatively, we cannot exclude differences in fish species regarding turnover of epidermal cells, which might trigger an enhanced flux of proteins from the cutaneous epithelium toward the skin mucus layer as a result of a normal mucus secretion and/or tissue repair and cell desquamation and renewal. This is perhaps more common than initially expected, as the results of our experimental stress model points out.

Protein characterization and function

Among the final number of mucus proteins (2,060), more than 89% (1,848 proteins) were eligible for functional pathway analysis using the IPA software. These proteins were represented in 418 canonical pathways out of 644. To easy identify the more relevant pathways and biological processes, an overlapping analysis was performed with a filter of six common proteins among related pathways. From this integrative approach, 17 canonical pathways with significant p-values lower than 1E-08 were clustered in three distinct clusters (Figure 1). The first cluster was composed of 60 proteins comprising the canonical pathways “oxidative phosphorylation” and “mitochondrial dysfunction” with a high representation of enzyme subunits of the mitochondrial respiratory chain (NADH dehydrogenase, Complex I; succinate dehydrogenase, Complex II; ubiquinol-cytochrome c reductase, Complex III; cytochrome c oxidase, Complex IV; ATP synthase, Complex V) and mitochondrial cell death and disease factors with both apoptotic (apoptosis-inducing factor 1, caspase 3) and anti-apoptotic (peroxiredoxin 3, PRDX3; peroxiredoxin 5, PRDX5; superoxide dismutase 2, SOD2; Parkinson protein 7, PARK7; nicastrin, NCSTN) roles due to their mediated effects on cell proteolysis, redox sensing, and cell differentiation and proliferation (Table 1).

Figure 1

Table 1

Protein accessionProtein nameProtein symbolCanonical pathway(s)
C2_18809Aconitase 2, mitochondrialACO21
C2_6260Apoptosis-inducing factor 1, mitochondrialAIFM11
C2_1751ATP synthase subunit alpha, mitochondrialATP5A11,2
C2_1973ATP synthase subunit beta, mitochondrialATP5B1,2
C2_18579ATP synthase subunit gamma, mitochondrialATP5C11,2
C2_6419ATP synthase subunit delta, mitochondrialATP5D1,2
C2_24277ATP synthase subunit epsilon, mitochondrialATP5E1,2
C2_176ATP synthase subunit b, mitochondrialATP5F11,2
C2_958ATP synthase lipid-binding protein, mitochondrialATP5G11,2
C2_6236ATP synthase subunit d, mitochondrialATP5H1,2
C2_7051ATP synthase subunit e, mitochondrialATP5I1,2
C2_1188ATP synthase subunit f, mitochondrialATP5J21,2
C2_1627ATP synthase subunit g, mitochondrialATP5L1,2
C2_123ATP synthase subunit O, mitochondrialATP5O1,2
C2_3535Caspase 3CASP31
C2_270Cytochrome c oxidase subunit 4 isoform 1, mitochondrialCOX4I11,2
C2_462Cytochrome c oxidase subunit 4 isoform 2, mitochondrialCOX4I21,2
C2_238Cytochrome c oxidase subunit 5A, mitochondrialCOX5A1,2
C2_132Cytochrome c oxidase subunit 6A, mitochondrialCOX6A11,2
C2_1197Cytochrome c oxidase subunit 6B1COX6B11,2
C2_3512Cytochrome c oxidase subunit 7B, mitochondrialCOX7B1,2
C2_4920Carnitine O-palmitoyltransferase 1, liver isoformCPT1A1
C2_568NADH-cytochrome b5 reductase 3CYB5R31
C2_785Cytochrome c1, heme protein, mitochondrialCYC11,2
C2_198Mitochondrial fission 1 proteinFIS11
C2_19719Glutathione reductase, mitochondrialGSR1
C2_14163-hydroxyacyl-CoA dehydratase 2HSD17B101
C2_106937ATP synthase subunit aMT-ATP61,2
C2_5715Cytochrome c oxidase subunit 3MT-CO31,2
C2_5958NicastrinNCSTN1
C2_8082NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 1NDUFA11,2
C2_110117NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 12NDUFA121,2
C2_1985NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 2NDUFA21,2
C2_3631NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 4NDUFA41,2
C2_9313NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 6NDUFA61,2
C2_332NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 9, mitochondrialNDUFA91,2
C2_11239Acyl carrier protein, mitochondrialNDUFAB11,2
C2_497NADH dehydrogenase [ubiquinone] 1 beta subcomplex subunit 10NDUFB101,2
C2_3428NADH dehydrogenase [ubiquinone] 1 beta subcomplex subunit 4NDUFB41,2
C2_3928NADH dehydrogenase [ubiquinone] 1 beta subcomplex subunit 6NDUFB61,2
C2_1170NADH dehydrogenase [ubiquinone] 1 beta subcomplex subunit 7NDUFB71,2
C2_1488NADH-ubiquinone oxidoreductase 75 kDa subunit, mitochondrialNDUFS11,2
C2_1740NADH dehydrogenase [ubiquinone] iron-sulfur protein 3, mitochondrialNDUFS31,2
C2_10276NADH dehydrogenase [ubiquinone] iron-sulfur protein 6, mitochondrialNDUFS61,2
C2_1860NADH dehydrogenase [ubiquinone] iron-sulfur protein 7, mitochondrialNDUFS71,2
C2_62722NADH dehydrogenase [ubiquinone] iron-sulfur protein 8, mitochondrialNDUFS81,2
C2_3103NADH dehydrogenase [ubiquinone] flavoprotein 2, mitochondrialNDUFV21,2
C2_229Parkinson protein 7PARK71
C2_2292Pyruvate dehydrogenase E1 component subunit alpha, somatic form, mitochondrialPDHA11
C2_2010Peroxiredoxin 3PRDX31
C2_4821Peroxiredoxin 5PRDX51
C2_1571Succinate dehydrogenase [ubiquinone] flavoprotein subunit, mitochondrialSDHA1,2
C2_791Succinate dehydrogenase [ubiquinone] iron-sulfur subunit, mitochondrialSDHB1,2
C2_1642Superoxide dismutase 2, mitochondrialSOD21
C2_1166Ubiquinol-cytochrome c reductase, complex III subunit XUQCR101,2
C2_516Ubiquinol-cytochrome c reductase binding proteinUQCRB1,2
C2_507Ubiquinol-cytochrome c reductase, Rieske iron-sulfur polypeptide 1UQCRFS11,2
C2_2118Ubiquinol-cytochrome c reductase hinge proteinUQCRH1,2
C2_12420Ubiquinol-cytochrome c reductase, complex III subunit VII, 9.5kDaUQCRQ1,2
C2_318Voltage-dependent anion-selective channel protein 1VDAC11

Proteins mapped in the overlapping pathways of oxidative phosphorylation and mitochondrial dysfunction.

Canonical pathways are indicated by number: (1) Mitochondrial dysfunction; (2) Oxidative phosphorylation.

As pointed out by Sanahuja and Ibarz (2015), it is still not clear whether the mucus release of glycolytic or mitochondrial enzymes is related to Goblet cell activity or directly to high metabolic activity in the cells of epithelial layers. In any case, increased glycolytic activity has been reported during epidermal infection in Atlantic salmon (Provan et al., 2013) or parental care and mouth-brooding of cichlids (Chong et al., 2006; Iq and Shu-Chien, 2011). Meanwhile, caspase 1 and 6 have been identified in the skin mucus of European sea bass, and it has been suggested that secretion of these cysteine proteases is activated upon danger signals to amplify the inflammatory response (Cordero et al., 2015). The presence of these two caspases was also found in the present study, in addition to a third caspase that was identified as caspase 3. Importantly the caspase 3 cascade is activated by pro-apoptotic mitochondrial molecules such as cytochrome c, and restrained by cellular inhibitors of apoptosis proteins (Srinivasula and Ashwell, 2008). Indeed, elevated levels of caspase 3 in the bloodstream of human patients are considered a symptom of recent myocardial infarction (Agosto et al., 2011). Likewise, PRDXs represent a family of antioxidant proteins with a ubiquitous and differentially regulated abundance in tissues, mucosal surfaces and body fluids (Leyens et al., 2003; Perkins et al., 2015). In the present study, up to four PRDXs (PRDX 1, 4, 5, and 6) were detected in the skin mucus of gilthead sea bream, although only the PRDX5 was represented in the mitochondrial cluster after filtering by canonical pathway overlapping. As reported below, no changes in the abundance of PRDX5 were found in our chronic stress model, although it is noteworthy that this mitochondrial PRDX is highly regulated at the transcriptional level by a wide range of nutritional and environmental stressors (dietary oils, high rearing density and parasitic infections) in the head kidney of gilthead sea bream (Pérez-Sánchez et al., 2011). Additionally, PARK7 is a redox-sensitive chaperone, acting as a sensor of oxidative stress that apparently protects neurons against oxidative stress and cell death, and defects in this gene are the cause of autosomal recessive early-onset Parkinson disease 7 (Bonifati et al., 2003). The presence of this protein in the skin mucus of gilthead sea bream could be viewed, therefore, as part of the antioxidant defense system role of epithelial layers. In this regard, NCSTN might represent another important protein, because in humans it plays a pivotal role in chronic inflammatory skin disease, affecting keratinocyte proliferation, cell-cycle control, and apoptosis (Xiao et al., 2016).

The second node of interconnected skin proteins was composed of 79 proteins involved in protein ubiquitination and antigen presentation pathways with a high representation of major histocompatibility complex, proteasome subunits, ubiquitin enzymes and molecular chaperones, including calnexin, calreticulin and heat shock proteins representative of the six major HSP families based on molecular mass (small HSPs, HSP40, HSP60, HSP70, HSP90 and HSP100) with either cytoplasmic, nuclear plasma membrane or extracellular locations (Table 2). This agrees with the observations made in a previous proteomic gilthead sea bream study, in which more than 1,300 spots were recorded in the skin mucus, but the 100 most abundant were among others ubiquitin/proteasome-related proteins and HSPs (Sanahuja and Ibarz, 2015). Furthermore, in Atlantic cod, changes in proteasome proteins abundance have been reported in response to V. anguillarum infection (Rajan et al., 2013) and to challenges with formalin-killed Aeromonas salmonicida (Bricknell et al., 2006). Another protein of interest in this cluster was the beta-2-microglobulin, which is now emerging as a consistent marker of immune system activation (Li et al., 2016). This small membrane protein is associated with the heavy chains of class I major histocompatibility complex proteins and serum concentrations are elevated in humans during chronic inflammation, liver disease, renal dysfunction, some acute viral infections, and a number of malignancies associated with the B-lymphocyte lineage (Drüeke and Massy, 2009; Shi et al., 2009). However, to our knowledge no previous reports have addressed the presence and regulation of beta-2-microglobulin in the skin mucus of fish.

Table 2

Protein accessionProtein nameProtein symbolCanonical pathway(s)
C2_3233E3 ubiquitin-protein ligase AMFRAMFR4
C2_17008Anaphase-promoting complex subunit 11ANAPC114
C2_9282Anaphase-promoting complex subunit 4ANAPC44
C2_6Beta-2-microglobulinB2M3,4
C2_1023CalreticulinCALR3
C2_19770CalnexinCANX3
C2_213DnaJ homolog subfamily A member 1DNAJA14
C2_5322DnaJ homolog subfamily C member 17DNAJC174
C2_8665DnaJ homolog subfamily C member 22DNAJC224
C2_121377HLA class II histocompatibility antigen, DP beta 1 chainHLA-DPB13
C2_104432H-2 class II histocompatibility antigen, A-R alpha chainHLA-DQA13
C2_728DLA class II histocompatibility antigen, DR-1 beta chainHLA-DR13
C2_105193H-2 class II histocompatibility antigen, E-D alpha chainHLA-DRA3
C2_113147HLA class II histocompatibility antigen, DRB1-4 beta chainHLA-DRB43
C2_4132Heat shock protein HSP 90-alpha 1HSP90AA14
C2_42Heat shock protein HSP 90-betaHSP90AB14
C2_1490Endoplasmin (GRP-94)HSP90B14
C2_6720Heat shock 70 kDa protein 4HSPA44
C2_2502778 kDa glucose-regulated proteinHSPA54
C2_4763Heat shock cognate 71 kDa proteinHSPA84
C2_82883Stress-70 protein, mitochondrialHSPA94
C2_10046Heat shock protein beta-11HSPB114
C2_522260 kDa heat shock protein, mitochondrialHSPD14
C2_402310 kDa heat shock protein, mitochondrialHSPE14
C2_2116Heat shock protein 105 kDaHSPH14
C2_121640Major histocompatibility complex class I-related gene proteinMR13
C2_251Protein disulfide-isomerase A3PDIA33
C2_276Proteasome subunit alpha type-1PSMA14
C2_39253Proteasome subunit alpha type-2PSMA24
C2_667Proteasome subunit alpha type-3PSMA34
C2_89Proteasome subunit alpha type-5PSMA54
C2_979Proteasome subunit alpha type-6PSMA64
C2_486Proteasome subunit alpha type-7PSMA74
C2_303Proteasome subunit beta type-1-BPSMB14
C2_53426Proteasome subunit beta type-10PSMB104
C2_4220Proteasome subunit beta type-2PSMB24
C2_1113Proteasome subunit beta type-3PSMB34
C2_1989Proteasome subunit beta type-4 (Fragment)PSMB44
C2_2719Proteasome subunit beta type-5PSMB53,4
C2_104936Proteasome subunit beta type-6-B like proteinPSMB63,4
C2_4274Proteasome subunit beta type-9PSMB93,4
C2_426426S protease regulatory subunit 4PSMC14
C2_300226S protease regulatory subunit 7PSMC24
C2_166626S protease regulatory subunit 6APSMC34
C2_48226S protease regulatory subunit 6BPSMC44
C2_51426S protease regulatory subunit 8PSMC54
C2_152026S protease regulatory subunit 10BPSMC64
C2_272826S proteasome non-ATPase regulatory subunit 1PSMD14
C2_310226S proteasome non-ATPase regulatory subunit 11PSMD114
C2_139226S proteasome non-ATPase regulatory subunit 12PSMD124
C2_79026S proteasome non-ATPase regulatory subunit 13PSMD134
C2_80726S proteasome non-ATPase regulatory subunit 14PSMD144
C2_455626S proteasome non-ATPase regulatory subunit 2PSMD24
C2_100626S proteasome non-ATPase regulatory subunit 3PSMD34
C2_803226S proteasome non-ATPase regulatory subunit 6PSMD64
C2_36426S proteasome non-ATPase regulatory subunit 7PSMD74
C2_184326S proteasome non-ATPase regulatory subunit 8PSMD84
C2_19056Proteasome activator complex subunit 1PSME14
C2_52053Proteasome activator complex subunit 2PSME24
C2_159S-phase kinase-associated protein 1SKP14
C2_6616Antigen peptide transporter 1TAP13,4
C2_8891Antigen peptide transporter 2TAP23,4
C2_27605TapasinTAPBP3
C2_529Transcription elongation factor B polypeptide 1TCEB14
C2_558Transcription elongation factor B polypeptide 2TCEB24
C2_15542Thimet oligopeptidaseTHOP14
C2_8231Ubiquitin-like modifier-activating enzyme 1UBA14
C2_5227Ubiquitin-conjugating enzyme E2 D2UBE2D24
C2_187Ubiquitin-conjugating enzyme E2 D3UBE2D34
C2_17030Ubiquitin-conjugating enzyme E2 NUBE2N4
C2_23677Ubiquitin-conjugating enzyme E2 variant 1CUBE2V14
C2_9398Ubiquitin-protein ligase E3AUBE3A4
C2_5640Ubiquitin carboxyl-terminal hydrolase isozyme L1UCHL14
C2_660Ubiquitin carboxyl-terminal hydrolase isozyme L3UCHL34
C2_1964Ubiquitin carboxyl-terminal hydrolase 14USP144
C2_11890Ubiquitin carboxyl-terminal hydrolase 22USP224
C2_18121Ubiquitin carboxyl-terminal hydrolase 37USP374
C2_66335Ubiquitin carboxyl-terminal hydrolase 8USP84
C2_19855Probable ubiquitin carboxyl-terminal hydrolase FAF-XUSP9X4

Proteins mapped in the overlapping pathways of protein ubiquitination and antigen presentation.

Canonical pathways are indicated by number: (3) Antigen presentation pathway; (4) Protein ubiquitination pathway.

The third cluster was the most populated one with 257 proteins in 13 interconnected canonical pathways (Table 3). Many of them are involved in protein synthesis (EIF2 signaling, mTOR signaling) and the maintenance of epithelial integrity (remodeling of epithelial adherens junctions, regulation of actin-based motility by Rho, epithelial adherens junction signaling, etc.) with also an important representation of proteins of acute phase response signaling. This set of proteins included among others, alpha-2-HS-glycoprotein, alpha-2-macroglobulin, amyloid P component, apolipoprotein A-I, angiotensinogen, ceruloplasmin, complement component 2, 3, 5, and 9, complement factor B, ferritin, fibrinogen, hemopexin, inter-alpha-trypsin inhibitor heavy chain H2 and H3, serpin peptidase inhibitor, transthyretin and transferrin. Most of them have been reported in other proteomic studies of mucosal surfaces, being this finding consistent with a key role of mucosal immunity during the course of most fish infections, probably due to the fact that aquatic environment favors a more intimate contact with pathogens (Salinas et al., 2011; Esteban, 2012). We are still far from fully exploiting this information on a routine basis, but our study will contribute to enlarge the list of immune-relevant proteins that are susceptible to be included in protein arrays or more targeted immune kits.

Table 3

Protein accessionProtein nameProtein symbolCanonical pathway(s)
s_flp0005a11_f_1Alpha-2-macroglobulinA2M6
C2_2Actin, cytoplasmic 1ACTB5,7,9,10,12,14,15,16,17
C2_1387Actin, alpha cardiacACTC15,7,9,10,12,14,15,16,17
C2_102126Actin, cytoplasmic 2ACTG15,7,9,10,14,15,16,17
C2_1801Alpha-actinin-3ACTN35,9,10,16
C2_26557Alpha-actinin-4ACTN45,9,10,16
C2_3453Actin-related protein 2-AACTR25,7,9,10,12,14,15,16,17
C2_1771Actin-related protein 3ACTR35,7,9,10,12,14,15,16,17
C2_5961Protein argonaute-2AGO28,13
C2_17965AngiotensinogenAGT6
C2_22548Alpha-2-HS-glycoproteinAHSG6
C2_2100Protein AMBPAMBP6
C2_37278AP-1 complex subunit beta-1AP1B17
C2_5784AP-2 complex subunit betaAP2B17
C2_1474AP-2 complex subunit mu-1-AAP2M17
C2_14608Serum amyloid P-componentAPCS6
C2_1042Apolipoprotein A-IAPOA16,7
s_rl0001e11_f_1Apolipoprotein B-100APOB7
C2_5591Apolipoprotein EbAPOE7
C2_487ADP-ribosylation factor 1-like 2ARF110
C2_2038ADP-ribosylation factor 4ARF410
C2_3418ADP-ribosylation factor 6ARF67,10,16
C2_1604Rho GDP-dissociation inhibitor 1ARHGDIA12,15
C2_22184Rho guanine nucleotide exchange factor 5ARHGEF515,17
C2_18222Actin-related protein 2/3 complex subunit 1AARPC1A5,7,9,10,12,14,15,16,17
C2_4212Actin-related protein 2/3 complex subunit 1BARPC1B5,7,9,10,12,14,15,16,17
C2_22529Actin-related protein 2/3 complex subunit 2ARPC25,7,9,10,12,14,15,16,17
C2_4166Actin-related protein 2/3 complex subunit 3ARPC35,7,9,10,12,14,15,16,17
C2_427Actin-related protein 2/3 complex subunit 4ARPC45,7,9,10,12,14,15,16,17
C2_503Actin-related protein 2/3 complex subunit 5ARPC55,7,9,10,12,14,15,16,17
FM156976Arf-GAP with SH3 domain, ANK repeat and PH domain-containing protein 1ASAP110
FP333165Complement C2C26
C2_1398Complement C3C36
s_flp0005d01_f_1Complement C5C56
s_rl0001d01_f_1Complement component C9C96
C2_15607Calpain-1 catalytic subunitCAPN110
C2_55335Calpain-5CAPN510
C2_44459Calpain-8CAPN810
C2_5497Calpain small subunit 1CAPNS110
C2_9606CD2-associated proteinCD2AP7
C2_16241Cdc42 effector protein 2CDC42EP214,17
C2_2045Cadherin-1CDH19,15,16,17
C2_11775Cadherin-2CDH29,15,17
C2_9760Complement factor BCFB6
C2_1192Cofilin-2CFL25,14,15,17
C2_1929Calcium-binding protein p22CHP17
C2_9111CAP-Gly domain-containing linker protein 1CLIP19,16,17
C2_39986CeruloplasminCP6
C2_540Casein kinase II subunit alphaCSNK2A17
C2_8203Casein kinase II subunit betaCSNK2B7
C2_13521Catenin alpha-2CTNNA29,16
C2_23957Catenin delta-1CTNND19,16
C2_33608Cytoplasmic FMR1-interacting protein 2CYFIP25
C2_6275Dynamin-2DNM27,16
C2_25618Eukaryotic translation initiation factor 1A, X-chromosomalEIF1AX8,13
C2_4011Eukaryotic translation initiation factor 2 subunit 1EIF2S18,13
C2_5966Eukaryotic translation initiation factor 2 subunit 2EIF2S28,13
C2_1614Eukaryotic translation initiation factor 2 subunit 3EIF2S38,13
C2_533Eukaryotic translation initiation factor 3 subunit AEIF3A8,11,13
C2_630Eukaryotic translation initiation factor 3 subunit BEIF3B8,11,13
C2_114Eukaryotic translation initiation factor 3 subunit EEIF3E8,11,13
C2_92Eukaryotic translation initiation factor 3 subunit FEIF3F8,11,13
C2_1542Eukaryotic translation initiation factor 3 subunit GEIF3G8,11,13
C2_312Eukaryotic translation initiation factor 3 subunit IEIF3I8,11,13
C2_5501Eukaryotic translation initiation factor 3 subunit KEIF3K8,11,13
C2_372Eukaryotic translation initiation factor 3 subunit LEIF3L8,11,13
C2_68Eukaryotic translation initiation factor 3 subunit MEIF3M8,11,13
C2_406Eukaryotic initiation factor 4A-IEIF4A18,11,13
C2_746Eukaryotic initiation factor 4A-IIEIF4A28,11,13
C2_1414Eukaryotic initiation factor 4A-IIIEIF4A38,11,13
C2_1810Eukaryotic translation initiation factor 4EEIF4E8,11,13
C2_2581Eukaryotic translation initiation factor 4E-binding protein 2EIF4EBP213
C2_2506Eukaryotic translation initiation factor 4 gamma 1EIF4G18,11,13
C2_31468ProthrombinF25,6,7
FP332283Fibrinogen beta chainFGB6
C2_38689Fibrinogen gamma chainFGG6
C2_49308Formin-binding protein 1 homologFNBP110,11,12,15,17
C2_105435Ferritin light chain, oocyte isoformFTL6
C2_32560Rab GDP dissociation inhibitor alphaGDI115
C2_455Rab GDP dissociation inhibitor betaGDI215
C2_75053Guanine nucleotide-binding protein subunit alpha-11GNA1115,17
C2_5820Guanine nucleotide-binding protein subunit alpha-13GNA135,14,15,17
C2_3738Guanine nucleotide-binding protein G(i) subunit alpha-1GNAI115,17
C2_6805Guanine nucleotide-binding protein G(k) subunit alphaGNAI315,17
C2_35672Guanine nucleotide-binding protein G(t) subunit alpha-2GNAT215,17
C2_8162Guanine nucleotide-binding protein G(I)/G(S)/G(T) subunit beta-1GNB115,17
C2_41327Guanine nucleotide-binding protein G(I)/G(S)/G(T) subunit beta-2GNB215,17
C2_45Guanine nucleotide-binding protein subunit beta-2-like 1GNB2L115,17
C2_3160Guanine nucleotide-binding protein subunit beta-4GNB415,17
C2_64382Guanine nucleotide-binding protein G(I)/G(S)/G(O) subunit gamma-12GNG121,15,17
C2_7512Guanine nucleotide-binding protein G(I)/G(S)/G(O) subunit gamma-2GNG215,17
C2_4717Growth factor receptor-bound protein 2GRB25,6,7,8,10,13
C2_265GelsolinGSN5,12
C2_2149Heme oxygenaseHMOX16,11
C2_61488Heterogeneous nuclear ribonucleoprotein KHNRNPK6
C2_27397HemopexinHPX6
C2_4763Heat shock cognate 71 kDa proteinHSPA87
C2_23533Inhibitor of nuclear factor kappa-B kinase subunit epsilonIKBKE6
C2_757Interleukin-6 receptor subunit alphaIL6R6
C2_5031Ras GTPase-activating-like protein IQGAP1IQGAP15,9,16,17
C2_7014Ras GTPase-activating-like protein IQGAP2IQGAP25
FP333792Inter-alpha-trypsin inhibitor heavy chain H2ITIH26
C2_12615Inter-alpha-trypsin inhibitor heavy chain H3ITIH36
C2_23019Junction plakoglobinJUP9
C2_29495Kininogen (Fragments)KNG15
C2_2112GTPase KRasKRAS5,6,8,9,10,11,13
C2_24867Dual specificity mitogen-activated protein kinase kinase 6MAP2K66
C2_10488Mitogen-activated protein kinase 1MAPK15,6,8,10,11,13,17
C2_15543Microtubule-associated protein RP/EB family member 1MAPRE116
C2_86MoesinMSN5,14,15,17
C2_29145Myosin-11MYH115,9
C2_14197Myosin-6MYH65,9
C2_515Myosin-9MYH95,9
C2_179Myosin light chain 1, skeletal muscle isoformMYL15,9,12,14,15,17
C2_2556Myosin light chain 3, skeletal muscle isoformMYL35,9,12,14,15,17
C2_3500Myosin light polypeptide 6MYL65,9,12,14,15,17
C2_2090Myosin regulatory light polypeptide 9MYL95,9,10,12,14,15,17
C2_2234Myosin regulatory light chain 2, smooth muscle minor isoformMYLPF5,12,14,15,17
C2_59686Myosin-IeMYO1E7
C2_62194Myosin-VIMYO67
C2_82048Nuclear factor NF-kappa-B p105 subunitNFKB16,17
C2_24789Ephexin-1NGEF14
C2_113264Nucleoside diphosphate kinase A1NME116
C2_4961Glucocorticoid receptorNR3C16
C2_3168Polyadenylate-binding protein 1PABPC18,13
C2_3226Serine/threonine-protein kinase PAK 2PAK25,10,12,15,17
C2_25053-phosphoinositide-dependent protein kinase 1PDPK16,8,11,13
C2_22976Profilin-1PFN15,12,14
C2_47781-phosphatidylinositol-3-phosphate 5-kinasePIKFYVE5,12,14,15,17
C2_700061-phosphatidylinositol-4,5-bisphosphate phosphodiesterase gamma-1PLCG110
C2_44121-phosphatidylinositol-4,5-bisphosphate phosphodiesterase gamma-2PLCG210
C2_1167Serine/threonine-protein phosphatase PP1-beta catalytic subunitPPP1CB5,8,10,12,14
C2_553Serine/threonine-protein phosphatase PP1-gamma catalytic subunitPPP1CC8
C2_11251Serine/threonine-protein phosphatase 2A catalytic subunit alpha isoformPPP2CA11,13
C2_7368Serine/threonine-protein phosphatase 2A catalytic subunit beta isoformPPP2CB11,13
C2_7698Serine/threonine-protein phosphatase 2A 65 kDa regulatory subunit A beta isoformPPP2R1B11,13
C2_22338Serine/threonine-protein phosphatase 2B catalytic subunit alpha isoformPPP3CA7
C2_6942Calcineurin subunit B type 1PPP3R17
C2_9126Protein kinase C beta typePRKCB11
C2_3156Ras-related protein Rab-11ARAB11A7
C2_452Ras-related protein Rab-11BRAB11B7
C2_9276Ras-related protein Rab-4BRAB4B7
C2_4291Ras-related protein Rab-5ARAB5A7,16
C2_6579Ras-related protein Rab-5BRAB5B7,16
C2_7828Ras-related protein Rab-5CRAB5C7,16
C2_53708Ras-related protein Rab7RAB7A7,16
C2_1097Ras-related C3 botulinum toxin substrate 1RAC15,7,9,10,11,12,15,17
C2_121610Ras-related C3 botulinum toxin substrate 2RAC25,10,12
C2_935Ras-related protein Ral-BRALB10
C2_879Ras-related protein Rap-1bRAP1B9,1
C2_16564RadixinRDX5,14,15,17
C2_131Transforming protein RhoARHOA5,9,10,11,12,14,15,17
C2_30428Rho-related GTP-binding protein RhoCRHOC10,11,12,15,17
C2_11478Rho-related GTP-binding protein RhoGRHOG10,11,12,15,17
C2_9607260S ribosomal protein L10RPL108
C2_6760S ribosomal protein L10aRPL10A8
C2_23660S ribosomal protein L11RPL118
C2_58760S ribosomal protein L12RPL128
C2_45360S ribosomal protein L13RPL138
C2_44160S ribosomal protein L13aRPL13A8
C2_14260S ribosomal protein L14RPL148
C2_27960S ribosomal protein L15RPL158
C2_124460S ribosomal protein L17RPL178
C2_2404060S ribosomal protein L18RPL188
C2_1235860S ribosomal protein L18aRPL18A8
C2_70060S ribosomal protein L19RPL198
C2_9433660S ribosomal protein L21RPL218
C2_3965660S ribosomal protein L22RPL228
C2_11555260S ribosomal protein L22-like 1RPL22L18
C2_37360S ribosomal protein L23RPL238
C2_100760S ribosomal protein L23aRPL23A8
C2_11996960S ribosomal protein L24RPL248
C2_39260S ribosomal protein L26RPL268
C2_10211760S ribosomal protein L27RPL278
C2_34360S ribosomal protein L27aRPL27A8
C2_138360S ribosomal protein L28RPL288
C2_1260S ribosomal protein L3RPL38
C2_1712660S ribosomal protein L30RPL308
C2_112760S ribosomal protein L31RPL318
C2_7259860S ribosomal protein L34RPL348
C2_8983560S ribosomal protein L35RPL358
C2_1157460S ribosomal protein L35aRPL35A8
C2_201960S ribosomal protein L36RPL368
C2_178860S ribosomal protein L36aRpl36a8
C2_79660S ribosomal protein L37RPL378
C2_6432360S ribosomal protein L38RPL388
C2_2560S ribosomal protein L4RPL48
C2_14360S ribosomal protein L5RPL58
C2_82760S ribosomal protein L6RPL68
C2_43460S ribosomal protein L7RPL78
C2_9860S ribosomal protein L7aRPL7A8
C2_17460S ribosomal protein L8RPL88
C2_15660S ribosomal protein L9RPL98
C2_4760S acidic ribosomal protein P0RPLP08
C2_4632360S acidic ribosomal protein P1RPLP18
C2_692360S acidic ribosomal protein P2RPLP28
C2_880540S ribosomal protein S10RPS108,11,13
C2_36740S ribosomal protein S11RPS118,11,13
C2_58340S ribosomal protein S12RPS128,11,13
C2_2070840S ribosomal protein S14RPS148,11,13
C2_1057040S ribosomal protein S15RPS158,11,13
C2_41440S ribosomal protein S15aRPS15A8,11,13
C2_733740S ribosomal protein S16RPS168,11,13
C2_97140S ribosomal protein S17RPS178,11,13
C2_1733940S ribosomal protein S18RPS188,11,13
C2_95540S ribosomal protein S19RPS198,11,13
C2_6258140S ribosomal protein S2RPS28,11,13
C2_23240S ribosomal protein S20RPS208,11,13
C2_1191740S ribosomal protein S21RPS218,11,13
C2_124340S ribosomal protein S23RPS238,11,13
C2_127140S ribosomal protein S24RPS248,11,13
C2_31040S ribosomal protein S25RPS258,11,13
C2_69840S ribosomal protein S26RPS268,11,13
C2_33738Ubiquitin-40S ribosomal protein S27aRPS27A8,11,13
C2_5074940S ribosomal protein S28RPS288,11,13
C2_2347940S ribosomal protein S29RPS298,11,13
C2_1787340S ribosomal protein S3RPS38,11,13
C2_59340S ribosomal protein S4RPS48,11,13
C2_43340S ribosomal protein S5RPS58,11,13
C2_16440S ribosomal protein S6RPS68,11,13
C2_2840Ribosomal protein S6 kinase 2 alphaRPS6KA111
C2_38170Ribosomal protein S6 kinase alpha-3RPS6KA311
C2_13340S ribosomal protein S7RPS78,11,13
C2_1367140S ribosomal protein S8RPS88,11,13
C2_25240S ribosomal protein S9RPS98,11,13
C2_1640S ribosomal protein SARPSA8,11,13
C2_23094Ras-related protein R-RasRRAS5,6,8,9,10,11,13
C2_7026Ras-related protein R-Ras2RRAS25,6,8,9,10,11,13
C2_16505Septin-10SEPT1014,17
C2_5603Septin-2SEPT214,17
C2_22270Septin-6SEPT614,17
C2_8875Septin-7SEPT714,17
C2_9888Septin-8-ASEPT814,17
C2_14294Serpin peptidase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 1SERPINA16,7
C2_9982Serpin peptidase inhibitor, clade F (alpha-2 antiplasmin, pigment epithelium derived factor), member 2SERPINF26
C2_9305Endophilin-A1SH3GL27
C2_4801SHC-transforming protein 1SHC15,6,8,10,13
C2_1642Superoxide dismutase [Mn], mitochondrialSOD26
C2_4186Protein phosphatase Slingshot homologSSH15
C2_2871Signal transducer and activator of transcription 3STAT36
C2_15171Transcription factor 7-like 2TCF7L29
C2_7158TransferrinTF6,7
C2_83924Talin-1TLN15,1
C2_1309Tumor necrosis factor receptor superfamily member 1BTNFRSF1B6
C2_45863Activated CDC42 kinase 1TNK210
C2_2326Tumor necrosis factor receptor type 1-associated DEATH domain proteinTRADD6
C2_1557TitinTTN5,10,14
C2_75383TransthyretinTTR6
C2_38179Tubulin alpha-1A chainTUBA1A9,16
C2_20113Tubulin alpha-4A chainTUBA4A9,16
C2_905Tubulin beta chainTUBB9,16
C2_90Tubulin beta-1 chainTUBB19,16
C2_14202Tubulin beta-2C chainTUBB4B9,16
C2_6783Ubiquitin-60S ribosomal protein L40UBA528
C2_19855Probable ubiquitin carboxyl-terminal hydrolase FAF-XUSP9X7
C2_9594VinculinVCL5,9,10,16
C2_3381VimentinVIM17

Proteins mapped in the overlapping pathways of protein synthesis, cellular assembly and remodeling and non-humoral immune response.

Canonical pathways are indicated by number: (5) Actin cytoskeleton signaling; (6) Acute phase response signaling; (7) Clathrin-mediated endocytosis signaling; (8) EIF2 signaling; (9) Epithelial adherens junction signaling; (10) Integrin signaling; (11) mTOR signaling; (12) Regulation of actin based motility by Rho; (13) Regulation of eIF4 and p70S6K signaling; (14) RhoA signaling; (15) RhoGDI signaling; (16) Remodeling of epithelial adherens junctions; (17) Signaling by Rho family GTPase.

Stress-regulated proteins

Principal components analysis from image processing of 2-DE of the mucus proteins from control CTRL vs. M-ST did not clearly separate individuals from both groups (Figure S1). Thus, only six spots were found to show a different significant (p-value < 0.03) abundance in stressed fish, with three upregulated (fold-change 1.6–2.7) and three down-regulated (0.6–0.7) proteins. The six protein spots were unequivocally identified by comparing the LC-MS/MS data with the gilthead sea bream transcriptome database, with a 100% of identity for all peptide sequences with the corresponding accession (Table 4). Down-regulated spots were elongation factor 2 (spot 743; GenBank accession KY388506) and cytoplasmic actin (spots 1,549 and 1,816; GenBank accession KY388507). Spot 2,181 (fold-change 1.64) was identified as the mitochondrial protein cytochrome c1 heme (GenBank accession KC217621), whereas the two most upregulated spots (spots 815, 1,321) were both recognized as keratin type II cytoskeletal 8 (GenBank accession KY388508). The higher abundance of immunoreactive cytokeratin 8 proteins in the mucus of M-ST fish was confirmed by Western blot (Figure 2), where the most abundant band was that of lower molecular weight (38–40 kDa). Cytokeratin 8 is a highly modified protein, but our working hypothesis is that this band was a proteolytically cleaved form. Protein spots, representing type I or type II keratin fragments, have also been reported at different stages of development in amphibians (Domanski and Helbing, 2007) and Atlantic cod larvae (Sveinsdóttir et al., 2008). Likewise, different fragments of cytokeratin 8 were detected by immunoblotting in colorectal biopsies of human cancer patients (Khan et al., 2011). Of note, gilthead sea bream cytokeratine 8 has a high identity (61%) and homology (69%) with the same protein of human origin, but the identified peptide sequences matched exactly with the gilthead sea bream protein sequence and not with that of human, so the risk of potential handling contamination was discarded.

Table 4

Spot numberAccession numberProtein namep-valueAverage ratio (M-ST/CTRL)Identified peptide sequences
743C2_534Elongation factor 20.0260.71APLMVYISK/CDLLYEGPPDDEAAMGIK/EGVLCEENMR/FSVSPVVR/GGG
QIIPTAR/GGGQIIPTARR/NCDSKAPLMVYISK/RVLYACELTAEPR/SDPVVS
YR/TILMMGR/VAVEAKNPADLPK/VFSGSVSTGLK/VFSGSVSTGLKVR/VLYACEL
TAEPR/VMKFSVSPVVR
815C2_1442Keratin type II cytoskeletal 80.0142.71ANLEAQIAEAEER/AQYEDIANR/FASFIDKVR/IRDLEDALQR/NLDMDSIVAEVK
1,321C2_1442Keratin type II cytoskeletal 80.0241.78DTSVIVEMDNSR/FASFIDKVR/FLEQQNK/IRDLEDALQR/LALDIEIATYRK/NM
QGLVEDFK/YEDEINK/YEDEINKR
1,549C2_2Actin, cytoplasmic 10.0190.71AGFAGDDAPR/AVFPSIVGRPR/DLTDYLMK/IIAPPERK/LAPSTMKIK/SYELP
DGQVITIGNER
1,816C2_2Actin, cytoplasmic 10.0260.63DLYANTVLSGGTTMYPGIADR/GYSFTTTAER/SYELPDGQVITIGNER/VAPEE
HPVLLTEAPLNPK/VAPEEHPVLLTEAPLNPKANR
2,181C2_785Cytochrome c1, heme protein mitochondrial0.0181.64LSDYFPKPYPNPESAR/NLVGVSHTEAEVK

Protein spots identified as differentially expressed in gilthead sea bream skin mucus after multiple sensorial stress.

Figure 2

Clear evidence for the prominent mechanical function of keratins comes from multiple human diseases and murine knockouts. However, distinct keratins emerge as highly dynamic scaffolds contributing to cell size determination, translation control, proliferation, malignant transformation and various stress responses (Magin et al., 2007; Loschke et al., 2015). Importantly, this also applies to fish and different reports show that keratins from skin mucus possess anti-bacterial activity owing to their pore-forming properties (Molle et al., 2008; Rajan et al., 2011). Relatively little is known about the precise mechanisms responsible for assembly and pathology, although it has been suggested that keratins can act as a “phosphate sponge” absorbing the stress-activated phosphate kinases, thereby, reducing their adverse effect and protecting cells from injury (Ku and Omary, 2006). Indeed, differential regulation of keratin phosphorylation is related to intricate functional properties of specific epithelial cell types (Tao et al., 2006; Busch et al., 2012; Majumdar et al., 2012). In our case, changes in the abundance of cytokeratin 8 in the skin mucus of gilthead sea bream would support some type of epithelia damage in fish diagnosed as chronically stressed, showing reduced growth and feed conversion efficiency, strong-down regulation of markers of mitochondrial activity and biogenesis in combination with a high variable and non-significant increase of plasma cortisol levels (Bermejo-Nogales et al., 2014). Since aerobic metabolism is the most important source of reactive oxygen species (ROS), this mitochondrial metabolic feature was considered as part of the adaptive stress response that reduced ROS production when fish face an increased risk of oxidative stress in our stress model that mimicked daily farming activities. The magnitude of the changes observed in the skin mucus proteome was, however, lower than expected. It can be argued that this fact might reflect the high allostatic capacity of our fish strain to cope with chronic stress. Indeed, in other less intrusive models of chronic stress, fish were intensively chased for 5 min 2 times per day after lowering water level and data on growth parameters evidenced a real stress adaptation with a switch from aerobic to more anaerobic metabolism without changes in plasma cortisol levels (Bermejo-Nogales et al., 2014). Additionally, other factors including season, age and nutritional background should be considered in an holistic manner to ultimately understand the extent to which the skin mucus proteome of gilthead sea bream is regulated by environmental and nutritional stressors, helping to understand how stress condition can be fine evaluated at the farm scale level without evoking further stress.

Conclusions

A high resolution mass spectrometry-based proteomic approach was able to identify 2,062 proteins in the skin mucus of gilthead bream after matching in a homologous protein database. Three major clusters with more than 350 proteins were retained after filtering by canonical pathway overlapping. Among them, proteins of oxidative phosphorylation, mitochondrial dysfunction, protein ubiquitination, immune response, epithelial remodeling, and cellular assembly were highly represented. This was reinforced by the observation that major changes related to the abundance of cytokeratin 8 in the skin mucus of stressed fish under our experimental model of chronic stress were found by means of 2-DE methodology and confirmed by immunoblotting. All this information will be useful in developing more targeted approaches that address specific changes in the skin mucus proteome of farmed fish, with special emphasis on markers of skin epithelial cell turnover.

Funding

This study was funded by the European Union (AQUAEXCEL, FP7/2007/2013; grant agreement No. 262336, Aquaculture infrastructures for excellence in European fish research) project. The views expressed in this work are the sole responsibility of the authors and do not necessarily reflect the views of the European Commission. Additional funding was obtained from the Spanish Ministerio de Economía y Competitividad (MI2-Fish, AGL2013-48560) and from Generalitat Valenciana (PROMETEO FASE II-2014/085). Proteomics study was done at Proteomics laboratory of University of Valencia, Spain (SCSIE). This laboratory is a member of Proteored, PRB2-ISCIII and is supported by grant PT13/0001, of the PE I+D+i 2013–2016, funded by Instituto de Salud Carlos III and Fondo Europeo de Desarrollo Regional (FEDER).

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Statements

Author contributions

JP, RO, and AS conceived and designed the study. OF supervised animal handling and sampling. JP, GT, PS, SR, and JC performed protein identification and functional characterization of mucus proteome and stress-regulated proteins. JP and PS conducted Western blot analysis. JP, GT, AS, and JC wrote the manuscript. All authors read and approved the final manuscript.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Supplementary material

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fphys.2017.00034/full#supplementary-material

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Summary

Keywords

chronic stress, cytokeratins, gilthead sea bream, proteome, skin mucus

Citation

Pérez-Sánchez J, Terova G, Simó-Mirabet P, Rimoldi S, Folkedal O, Calduch-Giner JA, Olsen RE and Sitjà-Bobadilla A (2017) Skin Mucus of Gilthead Sea Bream (Sparus aurata L.). Protein Mapping and Regulation in Chronically Stressed Fish. Front. Physiol. 8:34. doi: 10.3389/fphys.2017.00034

Received

05 October 2016

Accepted

13 January 2017

Published

01 February 2017

Volume

8 - 2017

Edited by

Pung P. Hwang, Academia Sinica, Taiwan

Reviewed by

Alberto Cuesta, University of Murcia, Spain; Mathilakath Vijayan, University of Calgary, Canada

Updates

Copyright

© 2017 Pérez-Sánchez, Terova, Simó-Mirabet, Rimoldi, Folkedal, Calduch-Giner, Olsen and Sitjà-Bobadilla.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Jaume Pérez-Sánchez

This article was submitted to Aquatic Physiology, a section of the journal Frontiers in Physiology

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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