Research Article Open Access Modulation of the Intestinal ... · Citation: Tapia-Paniagua ST, Reyes-Becerril M, Ascencio-Valle F, Esteban MÁ, Clavijo E, et al. (2011) Modulation

Open Access

ISSN: 2155-9546 JARD, an open access journalJ Aquac Res Development

Research Article Open Access

Tapia-Paniagua, et al. J Aquac Res Development 2011, S1http://dx.doi.org/10.4172/2155-9546.S1-012

Research Article Open Access

AquacultureResearch & Development

Probiotic & Prebiotic Applications in Aquaculture

IntroductionAccording to the FAO, at present, 52% of the wild 600 fish species with

economic value are heavily depleted, 17% over fished and 7% fully exploited. Supply from capture fisheries will be static over the next 30 years. Growing percentages of world aquatic production derives from aquaculture, whose importance is increasing dramatically as a result of overfishing of the world waters and increasing demands for seafood [1].

In large scale production facilities, where farmed animals are exposed to stressful conditions, problems related to diseases and deterioration of environmental conditions often result in economic losses [2,3]. Control of pathogens in fish farms has been routinely achieved by the administration of antimicrobial agents, but the excessive use of these agents has produced the emergence of resistant bacteria making the treatments less successful [4]. One the main challenges to achieve productive, feasible and sustainable aquaculture is to develop alternative preventive practises that may help to maintain high animal welfare standards as well as healthy environment, resulting in a better production and higher profits. In view of the increasing interest in the environmental and nutritional control of diseases [5], application of probiotics, prebiotics and synbiotics for aquatic animals is increasing to improve welfare and promote growth [6-9].

Probiotics are often defined for aquatic organisms as applications of entire or components of a microorganism which are beneficial to the health of the host [10]. Yeasts are commonly used in aquaculture [11], either alive as a feed ingredient [12,13], or as source of inmunostimulants [14-16]. In this context, Debaryomyces hansenii has been proposed as probiotic due to its beneficial effects on the enzymatic antioxidative status of farmed fish such as sea bass

(Dicentrarchus labrax) larvae [17] and juvenile leopard grouper (Mycteroperca rosacea) [18] and in the immune response of Sparus aurata [19, 20].

Prebiotics are defined as food ingredients non-digestible by the host which beneficially affects by selectively stimulating the growth and the activity of bacterial groups that improve the host health [21]. Several prebiotics have been assayed in farmed fish [17,22-24], the inulin being one of them [25]. This fructooligosaccharide has shown some prebiotic properties for fish, such as an improvement of the feed efficiency and energy retention [26], and weight [22,27]. However, it does not seem to exert an immunostimulant effect for gilthead seabream [28], and this prebiotic is not appropriate for supplementation of the diet of beluga (Huso huso, Linnaeus 1758), due to negative effects with some performance indices [29].

Fish gastrointestinal tract is one of the most important sites of interaction

*Corresponding author: Miguel Angel Moriñigo, Department of Microbiology, Faculty of Sciences, University of Malaga, 29071-Málaga, Spain, Tel: 34952131862; Fax: 34952136645; E-mail: [email protected]

Received June 30, 2011; Accepted November 05, 2011; Published November 15, 2011

Citation: Tapia-Paniagua ST, Reyes-Becerril M, Ascencio-Valle F, Esteban MÁ, Clavijo E, et al. (2011) Modulation of the Intestinal Microbiota and Immune System of Farmed Sparus aurata by the Administration of the Yeast Debaryomyces hansenii L2 in Conjunction with Inulin. J Aquac Res Development S1:012. doi:10.4172/2155-9546.S1-012

Copyright: © 2011 Tapia-Paniagua ST, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

AbstractFish gastrointestinal tract is one of the most important sites of interaction with the external world. Interactions

between the intestinal microbiota and the host modulate the functionality of the intestinal mucosa and gene expression. Application of probiotics, prebiotics and synbiotics for aquatic animals is increasing to improve welfare and promote growth. However, data about the use of probiotics in conjunction with prebiotics, in farmed marine organisms are scarce. The objective of this work is to study the modulation ability of the intestinal microbiota and the immune system of gilthead seabream exerted by the probiotic yeast Debaromycess hansonii L2 in conjunction with the prebiotic inulin. Fish were fed a commercial diet (control diet I), and with the same diet supplemented with 1.1% D. hansenii strain L2 (106 CFU g-1) plus inulin (3%) (diet II) for 4 weeks. The whole intestines of healthy fish from each group were aseptically removed at 2 and 4 weeks after starting the experiment and they were analysed by PCR-Denaturing Gradient Gel Electrophoresis (DGGE). Samples of blood and head kidney were obtained for humoral and cellular immune parameters determination. The expression of 12 selected genes related to the immune response (IgM, MHCIα, MHCIIα, C3, IL-1β,TLR, TNFα, CSF-1R, NCCRP-1, Hep, TCRβ y CD8) were analyzed by real-time PCR from skin, intestine, liver and head-kidney tissue.

In this study, relevant changes in the intestinal microbiota of gilthead seabream specimens fed the diets assayed has been demonstrated. An important effect on the intestinal microbiota by the dietary administration of a synbiotic mixture has also been detected, especially in fish receiving the supplemented diet for 4 weeks. These changes coincided in the same time with an up-regulation of the expression of immunological genes in skin and head kidney of gilthead seabream at 2 and 4 weeks, respectively.

Modulation of the Intestinal Microbiota and Immune System of Farmed Sparus aurata by the Administration of the Yeast Debaryomyces hansenii L2 in Conjunction with InulinSilvana Teresa Tapia-Paniagua1, Martha Reyes-Becerril2,3, Felipe Ascencio-Valle2, María Ángeles Esteban3, E. Clavijo4, Mª Carmen Balebona1 and Miguel Angel Moriñigo1*1Group of Prophylaxis and Biocontrol of Fish Diseases, Department of Microbiology, Faculty of Sciences, University of Malaga, 29071-Málaga, Spain2Centro de Investigaciones Biológicas del Noroeste (CIBNOR), Mar Bermejo 195, Col. Playa Palo de Santa Rita, La Paz, B.C.S. 23090, México3Fish Innate Immune System Group, Department of Cell Biology and Histology, Faculty of Biology, University of Murcia, 30100 Murcia, Spain4Department of Microbiology, Faculty of Medicine, University of Malaga, 29071-Málaga, Spain

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ISSN: 2155-9546 JARD, an open access journalJ Aquac Res Development Probiotic & Prebiotic Applications in Aquaculture

with the external world [9], and it is considered one of the major portals for pathogenic invasion in fish [30]. Interactions between the intestinal microbiota and the host modulate the functionality of the intestinal mucosa and gene expression [31-33]. An imbalanced microbiota may contribute to the development of diseases or reduced functionality [34]. Establishment of a healthy microbiota plays an important role in the generation of immune-physiologic regulation by providing crucial signals for the development and maintenance of the immune system [35]. Some yeasts have activities, such as the production of siderophores and proteases [36], which can have antibacterial properties [9], and which can effects on the bacteria comprising the fish intestinal microbiota. In addition, effects of inulin on the intestinal microbiota of artic charr (Salvelinus alpinus, L.) and hybrid stripped bass (Morone chrysops x Morone saxatilis) have been demonstrated [37-39]. However, data about the use of probiotics in conjunction with prebiotics, in farmed marine organisms [40] are scarce, although this possibility could have a high priority in future studies [25].

In short, the objective of this work is to study the modulation ability of the intestinal microbiota and the immune system of gilthead seabream exerted by the probiotic yeast Debaryomyces hansonii L2 in conjunction with the prebiotic inulin.

Materials and Methods Debaryomyces hansenii strain L2

The live yeast Debaryomyces hansenii strains L2 was provided by Centro de Investigaciones Biológicas del Noroeste (CIBNOR, México) and belongs to the yeast collection of CIBNOR. Briefly, the yeast was isolated from the surface of lemon fruit and cultures by across-streak on YPD-agar (containing 2.0% glucose, 2.0% peptone, 1.0% yeast extract and 1.5% agar prepared with distilled water and supplemented with 0.05% chloramphenicol) at 30°C. Yeast cells were removed with a bacteriological loop and suspended them in YPD-medium (100-ml or 1,000-ml in Erlenmeyer flasks) following a new incubation on a rotary shaker at 30°C for 48 h with constant aeration until the early stationary phase. Yeast cells were then removed from the growth medium by centrifugation (5 min, 1000g, 4°C) and the pellet was recovered the final cell concentration being adjusted accordingly.

Fish and experimental design

Sixty specimens (80g mean weight) of the hermaphroditic protandrous seawater teleost gilthead seabream (Sparus aurata L.) obtained from Culmarex S.A. (Murcia, Spain) were randomly placed in four running seawater tanks (10 fish per tank) (flow rate 1500 l h-1|) at 20°C with a 12 h dark/12 h light photoperiod. Seabream were confirmed bacterial-free by standard microbiological techniques [41] and by a PCR technique using the primers combination strategy described by Vazquez-Juarez et al. [42] to determine the presence or absence of allochthonous A. hydrophila. Fish in three. Fish in two aquaria were fed a non-supplemented commercial diet (ProAqua, Spain) (control diet I), while the fish of the other three tanks were fed the same diet supplemented with 1.1% D. hansenii strain L2 (106 CFU g-1) plus inulin (3%) (diet II) for four weeks. Briefly, the commercial pelleted diet was crushed, mixed with tap water (to which the yeast suspensions were added inulin (3%) and made again into pellets. The re-made pellets were allowed to dry and stored at 4°C until use. The control diet was put under the same process that the experimental diet but without yeast. The viability of the yeast after incorporation in the feed was determined by means of colony counts on YPD-agar. Briefly, one gram quantities of food were homogenized in 9 ml volumes of saline, and serial dilutions prepared to 10-5 the colony counts being determined after incubation for 24 h at 30°C.

The control diet was administered to all fish during two weeks conditioning period. The biomass in each aquarium was measured before the experiment and the daily ration was adjusted accordingly after each sampling. The fish were fed twice daily at 2% of their biomass.

Fish sample collection

The studies presented in this manuscript were approved by the Bioethical Committee of the University of Murcia. Five fish from each aquarium (15 fish/treatment) were randomly sampled at weeks 2 or 4 of the feeding assay. Before sampling, the fish were starved for 24 h. The whole intestines from sampled fish were aseptically removed and stored at -80ºC intestinal microbiota analysis. Tissue fragments from skin, intestine, liver and head-kidney were obtained and immediately stored at -80ºC in TRIzol reagent (Invitrogen) for RNA extraction. Samples of blood and head kidney were obtained for immunological assays as described below.

Intestinal microbiota analysis

The intestinal contents of four fish from each treatment were sampled on days 14 and 28 after starting the experiment. The whole intestines were aseptically removed and stored at -80ºC until further analysis.

Total DNA was extracted from samples as described by Martínez et al. [43]. Agarose gel (1% [wt/vol]) electrophoresis in the presence of ethidium bromide was used to visually check for DNA quality and yield.

In order to compare DGGE patterns of the intestinal microbiota of gilthead seabream specimens receiving the different diets, the DNA was amplified using the 16S rDNA bacterial domain-specific primers 677R-GC (5’ CGGGGCGGGGGCACGGGGGGATMTCTACGCATTTCACCGCTAC-3’) and 309-F (5’ACTCCTACGGGAGGCWGCAG-3’). PCR mixtures (50µl) contained 1U Robust Taq polymerase (KapaBiosystem, Spain), 20mM Tris-HCl (pH 8.5), 50mM KCl, 3mM MgCl2, 200 µM of each deoxynucleoside triphosphate, 5 pmol of the primers, 1 µl of DNA template, and UV-sterilized water. The PCR was performed in a T1 thermocycler (Whatman Biometra, Göttingen, Germany) using one cycle of 94ºC for 2 min, 35 cycles of 94ºC for 30 s, 56ºC for 30 s and 68ºC for 30 min, followed by one cycle of 68ºC for 5 min. Aliquots (5µl) were analyzed by electrophoresis on 1% (wt/vol) agarose gels containing ethidium bromide to check for product size and quantity.

The amplicons obtained from the intestinal lumen-extracted DNA and the probiotic strain were separated by Denaturing Gradient Gel Electrophoresis (DGGE) [44] using a Dcode TM system (Bio-Rad Laboratories, Hercules, CA). Electrophoresis was performed in 8% polyacrylamide gels (37.5:1 acrylamide-bisacrylamide; dimensions, 20 X 20cm x 1mm). The gels contained a 30 to 55% gradient of urea and formamide increasing in the direction of the electrophoresis. A 100% denaturing solution contained 7M urea and 40% (vol/vol) deionized formamide. PCR samples were applied to gels in aliquots of 13µl per lane. The gels were electrophoresed for 16 h at 85 V in 0.5 X TAE (20mM Tris acetate [pH 7.4], 10mM sodium acetate, 0.5mM Na2-EDTA) buffer at a constant temperature of 60ºC [45] and subsequently stained with AgNO3 [46]. The number of DGGE bands and similarity indices were calculated from the densitometric curves of the scanned DGGE profiles with the software FPQuest 4.5 (Applied Maths BVBA, Sint-Martens-Latem, Belgium). Similarity between DGGE profiles was determined by calculating a band similarity coefficient Pearson. The position tolerance used in the band comparison was 1.00%. Clustering of DGGE patterns was achieved by construction of dendrograms using the Unweighted Pair Groups Method using Arithmetic Averages (UPGMA).

In order to determine the structural diversity of the microbial community corresponding to the DGGE banding patterns several parameters were calculated: (1) Range-weighted richness (Rr) [47] calculated as the total number of bands multiplied by the percentage of denaturing gradient needed to describe the total diversity of the sample analysed, according to the following formula: Rr = (N2 x Dg), where N represents the total number of bands in the pattern, and Dg the denaturing gradient comprised between the first and the last band of the pattern. The Rr defines the carrying capacity of the system, and it is related to the amount and localisation of the DGGE bands in the gel [47]; (2) the Shannon

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index (H’) was calculated following the function: H’ =−Σ Pi ln Pi, where Pi is defined as (ni/N), ni is the peak surface of each band, and N is the sum of all the peak surfaces of all bands, and its value rangs from 1 to 5 indicating a low and high diversity, respectively; (3) the specific richness (R) was calculated based on the total number of bands; and (4) the Simpsom’s index was calculated in base on the function D=Σpi2, and its value rangs from 0 to 1 indicating a low and high dominance, respectively.

Cloning of the PCR-amplified products

16S rRNA gene-targeted PCR amplicons (500 bp) were generated with the same set of primers used for DGGE and were purified with NucloeSpin Extract II (Macherey-Nagel, The Netherlands) according to the manufacturer’s instructions. PCR products were cloned into Escherichia coli XL1-Blue competent cells (Stratagene) using the Promega pGEM-T easy vector system (Promega, Madison, WI). Ligation and transformation reactions were performed according to the protocol described by the manufacturer. PCR was performed on cell lysates of ampicillin-resistant transformants using vector specific primers T7 (TAATACGACTCACTATAGG) and Sp6 (GATTTAGGTGACACTATAG) to confirm the size of the inserts. A total of 96 amplicons of the correct size (per sample) were subjected to amplified ribosomal DNA restriction analysis (ARDRA) using the restriction enzymes MspI, CfoI, and AluI. From each sample, clones corresponding to a unique RFLP pattern were used to amplify V6–V8 regions of 16S rRNA genes with the primers 309-F and 677-CG as described previously, and they were selected for subsequent sequence analysis according to their migration position in the DGGE gel compared to the amplicons of the original DGGE profile of the sample.

Sequence analysis

PCR amplicons (0.5 kb) of transformants selected by the above-described ARDRA/DGGE screening procedure were purified with NucloeSpin Extract II (Macherey-Nagel, The Netherlands) according to the manufacturer’s instructions.

The samples were subjected to DNA sequence analysis with the primers SP6 and T7. Sequences were analyzed for similarity with sequences deposited in public databases using the BLAST tool at the National Center for Biotechnology Information database (http://www.ncbi.nlm.nih.gov/BLAST).

Blood serum and head kidney leucocytes

Blood was collected from the caudal vein with a 27-gauge needle and 1 ml syringe and allowed to clot at 4ºC for 4 h. Serum was obtained by centrifugation (10 min, 200g, 4ºC) and stored at -80ºC until used for humoral immune parameters determination (peroxidise level, natural haemolytic complement activity and Ig M level). Head kidney (HK) was dissected out sterilely by a ventral incision, cut into small fragments and transferred to 8 ml of sRPM (RPMI-1640, Gibco, culture medium containing P/S, 2% FCS and 0.35% NaCl). Head-kidney leucocytes (HKLs) were isolated from each fish under sterile conditions [48]. Briefly, leucocytes were washed, counted in a Z2 Coulter Particle Counter (Beckman Coulter, Spain) and adjusted to 107 cells ml-1 to determine cellular immune parameters (leucocyte peroxidase, phagocytosis and respiratory burst activity).

Immunological assays

Peroxidase: The peroxidase activity was measured as an indicator of leucocyte activation by a colorimetric method [49]. Briefly, 5 µl of serum were diluted with 50 µl of HBSS in flat- bottomed 96-well plates. HKLs (105) were dispensed into flat-bottomed 96-well plates and lysed with 50 µl of 0.02% cetyltrimethylammonium bromide (Sigma). Serum or HKL samples were mixed with the peroxidase substrate (80 µM 3,3’,5,5’-tetramethylbenzidine hydrochloride (TMB; Sigma) and 2.5mM H2O2). The colour-change reaction was stopped after 2 min by adding 50 µ1 of 2M sulphuric acid and the optical

density was read at 450 nm in a plate reader (BMG, Fluoro Star Galaxy). Standard samples without serum or leucocytes were used as blanks. The peroxidase activity was determined defining as one unit the peroxidase that produces an absorbance change of 1 OD.

Phagocytic activity: The phagocytosis was studied by flow cytometry [50]. Heat-killed yeast cells were labeled with fluorescein isothiocyanate (FITC, Sigma), washed and adjusted to 5x107 cells ml-1 of sRPMI. Phagocytosis samples consisted of labelled-yeast cells and leucocytes. Samples were mixed, centrifuged (5 min, 400g, 22ºC), resuspended in sRPMI and incubated (22ºC, 30 min). At the end of the incubation time, the samples were placed on ice and 400 ml ice-cold PBS was added to each sample to stop phagocytosis. The fluorescence of the extracellular yeasts was quenched by adding 40 ml ice-cold trypan blue (0.4% in PBS). Standard samples of FITC-labelled S. cerevisiae or leucocytes were included in each phagocytosis assay. All samples were analysed in a flow cytometer set to analyse the phagocytic cells. Phagocytic ability was defined as the percentage of cells with ingested yeast cells (green-FITC fluorescent cells, FL1+) within the phagocyte cell population. The relative number of ingested yeasts per cell (phagocytic capacity) was assessed in arbitrary units from the mean fluorescence intensity of the phagocytic cells.

Respiratory burst activity: The respiratory burst activity of gilthead seabream HKLs, measured as the production of reactive oxygen intermediates, was studied by a chemiluminescence [51]. Briefly, samples of 106 leucocytes in sRPMI were placed in the wells of a flat-bottomed 96-well microtiter plate, to which was added 100 µl of HBSS containing 1 µg ml-1 phorbol myristate acetate (PMA, Sigma) and 10-4M luminol (Sigma). The plate was shaken and immediately read in a plate reader over a period of 1 h at 2 min intervals. The reaction kinetic was analyzed and the maximum slope of each curve was calculated. Backgrounds of luminescence were calculated using reagent solutions containing luminol but not PMA.

Natural haemolytic complement activity: The activity of the serum alternative complement pathway was assayed using sheep red blood cells (SRBC, Biomedics) as targets [52]. Equal volumes of SRBC suspension (6%) in phenol red-free Hank’s buffer (HBSS) containing Mg+2 and EGTA were mixed with serially diluted serum to give final concentrations ranging from 10% to 0.078%. After incubation for 90 min at 22ºC, the samples were centrifuged (400g, 5 min, 4°C) to avoid unlysed erythrocytes. The relative haemoglobin content of the supernatants was assessed by measuring their optical density at 550 nm in a plate reader. The values of maximum (100%) and minimum (spontaneous) haemolysis were obtained by adding 100 µl of distilled water or HBSS to 100 µl samples of SRBC, respectively.

The degree of haemolysis (Y) was estimated and the lysis curve for each specimen was obtained by plotting Y/(1-Y) against the volume of serum added (ml) on a log-log scaled graph. The volume of serum producing 50% haemolysis (ACH50) was determined and the number of ACH50 units ml-1 was obtained for each specimen.

Serum IgM level: Total serum IgM levels were analyzed according using the enzyme-linked immunosorbent assay (ELISA) [53], serial dilutions of gilthead seabream serum (from 1/1 to 1/1000) and the commercial monoclonal antibody as indicated by the manufacturer’s instructions. The 1/100 serum dilution gave an OD in the linear range of the serum dilution versus absorbance curve and was chosen to compare the total IgM level in different serum samples. Thus, 20 ml per well of 1/100 diluted serum were placed in flat-bottomed 96-well plates in triplicate and the proteins were coated by overnight incubation at 4ºC with 200 ml of carbonate-bicarbonate buffer (35mM NaHCO3 and 15mM Na2CO3, pH 9.6). After three rinses with PBT (20mM Tris-HCl, 150mM NaCl and 0.05% Tween 20, pH 7.3) the plates were blocked for 2 h at room temperature with blocking buffer containing 3% bovine serum albumin (BSA) in PBS, followed by three rinses with PBT. The plates were then incubated for 1 h with 100ml

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per well of mouse anti-gilthead seabream IgM monoclonal antibody (Aquatic Diagnostics Ltd.) (1/100 in blocking buffer), washed and incubated with the secondary antibody anti-mouse IgG-HRP (1/1000 in blocking buffer). After exhaustive rinsing with PBT the plates were developed using 100 ml of a 0.42mMTMB solution, prepared daily in a 100mMcitric acid/sodium acetate buffer, pH 5.4, containing 0.01% H2O2. The reaction was allowed to proceed for 10 min and stopped by the addition of 50 ml of 2M H2SO4 and the plates were read at 450 nm. Negative controls consisted of samples without serum or without primary antibody, whose OD values were subtracted for each sample value.

RNA purification: Total RNA was extracted from 0.5g of gilthead seabream skin, intestine, liver and head-kidney tissue, using Trizol RNA isolation reagent (Invitrogen). It was then quantified and the purity assessed by spectrophotometry; 260:280 ratios were 1.8–2.0, and treated with DNase (Promega, USA) to remove DNA contamination. Complementary DNA (cDNA) was synthesized from total RNA using the SuperScriptTM III reverse transcriptase (Invitrogen) and using 1μg of total RNA with oligo-dT18 primer.

Real-time PCR: The expression of 12 selected genes (IgM, MHCIα, MHCIIα, C3, IL-1β, TLR, TNFα, CSF-1R, NCCRP-1, Hep, TCRβ y CD8) were analysed by real-time PCR using the SYBR Green PCR Core Reagents dye detection (Applied Biosystems). The amplification was performed in a 96-well plate in a 20 μl reaction volume containing 10 μl of 2xSYBR Green supermix, 5 μl of concentration primers, and 5 μl of cDNA template. The thermal profile for SYBR Green real-time PCR was 95°C for 10 min followed by 40 cycles of denaturation (95°C for 15 S), annealing (60°C for 60 S) and extension (95°C for 15 S). For each mRNA, gene expression was corrected against the endogenous level of the house keeping gene 18S content in each sample in order to standardize the results by eliminating variation in mRNA and cDNA quantity and quality [19] No amplification product was observed in negative controls and no primer-dimer formations were observed in the control templates. In all cases, each PCR was performed with triplicate samples and repeated at least twice. The primers

used are detailed in Table 1. The results are expressed as the fold change in the yeast-group compared with the control group.

Statistical analysis

All bioassays were made in triplicate and all measurements were performed on three replicates; the mean ± standard error (SE) for each immune parameter was calculated. One-way ANOVA was performed to determine the effects of dietary live yeast plus inulin on different parameters after checking for normality and homogeneity of variance by the Kolgomorov-Smirnov and Levene tests (P < 0.05), respectively. All statistical tests were conducted using the computerized software Statistical Package for Social Sciences (SPSS) v.15.0 software. Differences were considered significant at P < 0.05. The intestinal microbiota analysis data were processed by analysis of variance using the program STATGRAFICS Plus 5.0 (Statgraphics Corporation, Rockville, MD, USA). For Real time PCR, gene expression was normalized to the ribosomal protein S18 content in each sample using the comparative Ct method (2-∆∆Ct) (fold), where the ∆Ct value is determined by subtracting the average 18S Ct value from the average of each gen Ct. The results are expressed as the fold change in the yeast group compared with the control group.

ResultsThe number of bands in the PCR-DGGE patterns ranging from 4-6 until

20-25 depending on the diet and the weeks supplied is summarized in Table 2. DGGE patterns from fish fed the diet supplemented with Debaryomyces hansenii strain L2 and inulin (diet II) for 4 weeks showed a significant (p


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not statistically different (2.07 and 2.23, respectively). On the contrary, values of the Shannon’s index significantly (p30) [47]. On the contrary, this value drastically was reduced from fish receiving the diet II for 4 weeks (13.4). These results correspond to environments with a medium range-weighted richness (Rr between 10 and 30) [47].

Tables 3 and 4 summarize the bacterial species identified from the cloned sequences from intestines of fish fed the diets I and II for two and four weeks. The phylogenetic affiliations of those sequences which were not clearly related to members of bacterial genera were determined (Figure 2), being the majority of these cloned sequences related to Pseudomonas genus. Majority of cloned sequences from intestines of fish fed with diet I for 2 weeks days were identified or phylogenetically related to Pseudomonas and Serratia genera. The cloned sequences related to Serratia sp GIST-WP4w1 (control 1), Pseudomonas fluorescens strain XXPFMDU1 (control 6), Pseudomonas sp VS05_112 (control 12) and γ-proteobacterium 6.1.12_I (control 14), phylogenetically related to Pseudomonas fluorescens, corresponded to one of the most predominant bands in the PCR-DGGE profiles. Other cloned sequences related to uncultured bacterium clone 2B (control 17) and clone nbt36b09 (control 18) also corresponded to predominant bands of the PCR-DGGE patterns. The last cloned sequence was phylogenetically related to species of Serratia genus. Remaining cloned sequences also corresponded to one of the bands detected in the PCR-DGGE profiles, although the intensity of these bands was lower than those previously mentioned. Other clones sequences showed a high similarity to Stenotrophomonas, Ewingella, Yersinia and Vibrionaceae genera, whilst other were phylogenetically related to Aeromonas and Chlorobibacterium genera. When the diet I was supplied for 4 weeks, 15 different cloned sequences were characterized, and sequences control 24, 26 and 32 showed a very high similarity with members of Pseudomonas genus. Other sequences such as control 23 and 29 were phylogenetically related to Pseudomonas. Other cloned sequences showed a high similarity to Lactobacillus (control 22 and 35) and Ralstonia (control 21 and 25) genera. All these sequences corresponding with some of the predominant bands detected in the PCR-DGGE patterns. Cloned sequences related to Serratia genus were not identified. Although the majority of cloned sequenced were related to γ–Proteobacteria, three cloned sequences (control 22, 25 and 30) corresponded to β-Proteobacteria related to Ralstonia and Pelomonas genera, which were not detected in samples from fish fed with the diet I for 2 weeks.

Twenty two different cloned sequences were characterized from intestines of fish fed diet II for 2 weeks. Thirteen of them showed a very high similarity (L2+I_4, L2+I_11, L2+I_18 and L2+I_19), or were phylogenetically related (L2+I_1, L2+I_5 L2+I_7, L2+I_9, L2+I_12, L2+I_15, L2+I_16, L2+I_17 and L2+I_21) to Pseudomonas genus. All these sequences corresponded to some of the predominant bands detected in PCR-DGGE profiles, and the cloned sequence L2+I_5 corresponded to one of the most intensive bands. Remaining cloned sequences showed a high similarity or were phylogenetically related to Serratia, Pseudoalteromonas, Vibrio and Enterobacteriaceae genera. Some of the cloned sequences did not correspond to some of the predominant bands of the PCR-DGGE profiles. After 4 weeks receiving the diet II, sixteen cloned sequences were characterized, but the majority of these cloned sequences did not correspond to some of the predominant bands of the PCR-DGGE. Two sequences (L2+I_23 and L2+I_35) showed high similarity or were phylogenetically related (L2+I_34) with species of Pseudomonas genus. Other sequences were identified or related to Vibrio harveyi, Shewanella alga, Enterobacter, Ralstonia and Psychrobacter

Figure 2: Phylogenetic tree of clusters based on 16S rRNA sequences showing the relationships of the cloned sequences obtained from intestinal samples of Sparus aurata specimens with their closest relatives bacteria.

weeks drastically increased their similarity index (about 100%), indicating a lower intragroup variability of the intestinal microbiota of the specimens in comparison with the intestinal microbiota of fish fed with control diet.

The Shannon index obtained for fish receiving diets I and II for 2 weeks were

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Closest relative Similarity (%) GenBank accession number TaxonDiet I Control 1 Serratia sp. GIST-WP4w1 99 EF428994 g-ProteobacteriaControl 2 Stenotrophomonas sp. Bt-45 99 GU564359 BacteriaControl 3 Pseudomonas putida 5IIANH 99 AF307869 g-ProteobacteriaControl 4 Serratia proteamaculans 2Sm39 97 AM268219 g-Proteobacteria Control 5 Vibrionaceae bacterium clone HE_C4 100 FJ178090 g-ProteobacteriaControl 6 Pseudomonas fluorescens strain XXPFMDU1 100 GU048851 g-ProteobacteriaControl 7 Uncultured organism clone OTUI167 99 EU332816 g-ProteobacteriaControl 8 Pseudomonas putida strain CH-22 99 GU060497 g-ProteobacteriaControl 9 Uncultured archaeon AEXO15n.4 97 FM242736 ArchaeaeControl 10 Serratia sp. I-111-21 99 FJ786072 g-ProteobacteriaControl 11 Uncultured g-proteobacterium RBE1CI-38 96 EF111061 g-ProteobacteriaControl 12 Pseudomonas sp. VS05_112 99 FJ662898 g-ProteobacteriaControl 13 Yersinia massiliensis CCUG 53444 98 EF179120 g-ProteobacteriaControl 14 g-proteobacterium 6.1.12_I 98 GU352683 g-ProteobacteriaControl 15 Ewingella americana 99 AB428447 g-ProteobacteriaControl 16 g-proteobacterium 7.1.14_S 99 GU352879 g-ProteobacteriaControl 17 Uncultured bacterium clone 2B 99 FN396941Control 18 Uncultured bacterium clone nbt36b09 99 FJ893837 g-ProteobacteriaControl 19 Pseudomonas putida 5IIANH 97 AF307869 g-ProteobacteriaControl 20 Uncultured bacterium S01_E08 99 AB374478 g-ProteobacteriaDiet IIL2+I_1 g-proteobacterium clone P_C1 100 FJ178095 g-ProteobacteriaL2+I_2 Uncultured bacterium clone 50p7_2505 96 FJ935499L2+I_3 Uncultured bacterium clone 2B 97 FN396941L2+I_4 Pseudomonas fluorescens strain XXPFMDU1 99 GU048851 g-ProteobacteriaL2+I_5 g-proteobacterium 6.1.12_I 99 GU352683 g-ProteobacteriaL2+I_6 Uncultured planctomycete Mu2MO16E2.2 98 AM941034L2+I_7 Uncultured bacterium clone 50p15_611 99 FJ935397 g-ProteobacteriaL2+I_8 Enterobacteriaceae bacterium GGC-D12 100 FJ348020 g-ProteobacteriaL2+I_9 Uncultured bacterium clone 0p15_414 85 FJ933826 g-ProteobacteriaL2+I_10 Vibrio parahaemolyticus K5030 98 ACKB01000119 g-ProteobacteriaL2+I_11 Uncultured Pseudomonas sp. clone K13 96 AM947012 g-ProteobacteriaL2+I_12 Uncultured bacterium clone 50p12_408 100 FJ935181 g-ProteobacteriaL2+I_13 Serratia proteamaculans strain 94 99 EU327084 g-ProteobacteriaL2+I_14 Enterobacteriaceae bacterium GGC-D12 99 FJ348020 g-ProteobacteriaL2+I_15 Uncultured bacterium clone 50p15_108 99 FJ935228 g-ProteobacteriaL2+I_16 Uncultured bacterium clone 50p15_512 98 FJ935383 g-ProteobacteriaL2+I_17 Uncultured bacterium clone 50p8_610 97 FJ935723 g-ProteobacteriaL2+I_18 Pseudomonas fluorescens SBW25 100 NC_012660 g-ProteobacteriaL2+I_19 Pseudomonas entomophila 99 NC_008027 g-ProteobacteriaL2+I_20 Uncultured cyanobacterium clone O7 97 FJ178040 CyanobacteriaeL2+I_21 g-proteobacterium 2.1.12_I 98 GU352593 g-ProteobacteriaL2+I_22 Uncultured archaeon isolate AEXO15n.4 100 FM242736 Archaeae

Table 3: 16S rRNA sequence similarities to closest relatives obtained from BLAST search, of DNA corresponding to Sparus aurata specimens fed with the different diets assayed for two weeks. Diet I is a commercial diet, and diet II, is a commercial diet supplemented with the symbiotic mixture.

genera which were not detected from intestinal samples from fish fed diet II for 2 weeks. The majority of cloned sequenced were related to γ–Proteobacteria, but three cloned sequences corresponded to β-Proteobacteria, two of them related to Ralstonia (L2+I_29) genus. β-Proteobacteria were not detected from cloned sequences from fish fed with the diet I for 2.

The phylogenetic analysis based on 16S rRNA gene showed that, P. fluorescens was in the majority of cases the species more frequently characterized corresponding from the cloned sequences identified as members of Pseudomonas genus.

On the other hand, about the humoral and cellular immunological parameters, this study show a significant effect on peroxidase activity in serum in fish fed diet II at week 4. The highest values in the haematological parameters

were recorded from the groups fed diet II (Figure 3), although they were not significant.

A quantitative RT-PCR was used to estimate the regulation of immune gene expression in gilthead seabream fed diet II, and in this study the number of mRNA transcripts of 12 selected immune-related genes was generally higher at week 2 in skin and intestine (Figure 4). The maximum transcript levels were found in the intestine for the major histocompatibility complex (MHC) genes, MHCI and MHCII, which were significantly up-regulated more than 241- and 127-fold respectively. On the other hand, after 4 weeks (Figure 5), a relatively lower expression of genes was recorded in the skin, intestine and liver but not in the head-kidney, where they were up-regulated, except MHC I, TLR and CD8. Interestingly, the C3 transcript was significantly increased more than 244-fold in the intestine.

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Closest relative Similarity (%) GenBank accession number TaxonDiet I Control 21 Uncultured β-proteobacterium clone R64LS 100 FM863753 β-ProteobacteriaControl 22 Uncultured Lactobacillus clone 4EV10 100 AM117146 FirmicutesControl 23 Uncultured bacterium isolate w90 99 FN432022 g-ProteobacteriaControl 24 Uncultured Pseudomonas sp. clone L6B-537 98 GU000370 g-ProteobacteriaControl 25 Uncultured Ralstonia sp. clone 3P-3-2-P01 98 EU705953 β-Proteobacteria Control 26 Pseudomonas saccharophila 98 AF368755 g-ProteobacteriaControlo 27 Leptolyngbya valderiana BDU 20041 100 AAZV01000073 CyanobacteriaControl 28 Uncultured bacterium clone V20-13 98 GQ487980Control 29 Uncultured Pseudomonadaceae LW9m-3-63 98 EU641589 g-ProteobacteriaControl 30 Uncultured Pelomonas sp. clone GI7-8-K21 99 FJ193845 β-ProteobacteriaControl 31 Thermoproteus neutrophilus JCM 9278 98 AB009618 ArchaeaControl 32 Pseudomonas fluorescens strain Pfa7B 99 GQ334362 g-ProteobacteriaControl 33 Unidentified marine bacterium gel fragment 99 AF007939 g-ProteobacteriaControl 34 Uncultured gamma proteobacterium cloneNL1BD-03-E04a 100 FM252424 g-ProteobacteriaControl 35 Lactococcus lactis subsp. lactis strain MD 99 EU337106 FirmicutesDiet IIL2+I_23 Uncultured Pseudomonas sp. clone KJ 97 AM947011 g-ProteobacteriaL2+I_24 Uncultured beta proteobacterium clone R64LS 99 FM863753 β-proteobacteriaL2+I_25 Uncultured bacterium clone 2 97 FN396941

L2+I_26 Uncultured planctomycete Mu2MO16E2.2 100 AM941034 Planctomycetes

L2+I_27 Uncultured bacterium S01_H01 99 AB374505L2+I_28 Uncultured cyanobacterium clone O7 97 FJ178040 CyanobacteriaL2+I_29 Uncultured Ralstonia sp. clone 1P-2-N13 98 EU705153 β-proteobacteriaL2+I_30 Vibrio harveyi strain NH87-72 99 FJ447524 g-ProteobacteriaL2+I_31 Shewanella alga ATCC 8073 99 AF005250 g-ProteobacteriaL2+I_32 Uncultured bacterium isolate w16 99 FN432004 BacteriaL2+I_33 g-proteobacterium enrichment culture clone P_C1 100 FJ178095 g-ProteobacteriaL2+I_34 Uncultured bacterium isolate w90 99 FN432022 BacteriaL2+I_35 Uncultured Pseudomonas sp. clone Eis3 99 FM252498 g-ProteobacteriaL2+I_36 Enterobacter sp. 2J-3 16S 100 FJ493047 g-ProteobacteriaL2+I_38 Psychrobacter sp. BSw20879 96 GU166130 g-ProteobacteriaL2+I_39 Uncultured bacterium clone nbw424h10c 97 GQ093780 Bacteria

Table 4: 16S rRNA sequence similarities to closest relatives obtained from BLAST search, of DNA corresponding to Sparus aurata specimens fed the different diets as-sayed for four weeks. Diet I is a commercial diet, and diet II, is a commercial diet supplemented with the symbiotic mixture.

0

0,04

0,08

0,12

0,16

0,2

2 4

Weeks of treatments

Pero

xida

se a

ctivi

ty (U

nits

10

-7 le

ucoc

yes)

*

05

101520253035

2 4

Weeks of treatments

Pero

xida

se a

ctiv

ity

(U/m

l)

02040

6080

100

2 4

Weeks of treatments

% o

f p

hag

ocit

yc c

ells

050000

100000150000200000250000

2 4

Weeks of treatments

Res

pira

tory

bur

st a

ctiv

ity

(Slo

pe m

in-1

)

0

5

10

15

20

25

2 4

Weeks of treatments

AC

H50

uni

ts m

l-1

00,050,1

0,150,2

0,250,3

2 4

Weeks of treatments

Tot

al I

gM l

evel

(O

D 45

0)

A B

C D

E F Figure 3: Effect of Debaryomyces hansenii L2 in conjunction with inulin on gilthead seabream immune parameters. A, B: peroxidase activity. C: Phagocytic ability. D: Respiratory burst. E: Natural complement activity. F: Total IgM level. Bars show the mean SE. Asterisk denotes statistically significant differences between control and D. hansenii L2 plus inulin groups (p ≤ 0.05).

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0.1

1.0

10.0

Skin Week 4

Fold

cha

nge

IgMMHC-Iα

MHC-IIα

C3IL-Iβ

TLRTNF-α

CSF-1RNCCR-1HepTCR-β

CD8

0

1

10

1

Liver Week 4

Fol

d ch

ange

IgMMHC-Iα

MHC-IIα

C3IL-Iβ

TLRTNF-α


CD8

0

1

10

1

Head kidney Week 4

Fol

d ch

ange

IgMMHC-Iα

MHC-IIα

C3IL-Iβ

TLRTNF-α


CD8

0

1

10

100

1000

Intestine Week 4

Fol

d ch

ange

IgMMHC-Iα

MHC-IIα

C3IL-Iβ

TLRTNF-α


CD8

Figure 5: Expression of immune-relevant genes determined by real-time polymerase chain reaction (PCR) in seabream following a diet with Debaryomy-ces hansenii L2 plus inulin at week 4. Fold change in gene expression compared with the control fish is expressed. All the genes were considered to be up-regulated if the relative value was above 1 and down-regulated with a relative value below 1. Each bar represents the mean SD of triplicate samples.

0

1

10

100

1000

Skin Week 2

Fold

cha

nge

IgMMHC-Iα

MHC-IIα

C3IL-Iβ

TLRTNF-α


CD8

0

1

10

100

1000

IntestineWeek 2

Fold

cha

nge

IgMMHC-Iα

MHC-IIα

C3IL-Iβ

TLRTNF-α


CD8

0

1

10

100

Liver Week 2

Fo

ld c

han

ge

IgMMHC-Iα

MHC-IIα

C3IL-Iβ

TLRTNF-α


CD8

0

1

10

1

Head-kidney Week 2

Fold

cha

nge

IgMMHC-Iα

MHC-IIα

C3IL-Iβ

TLRTNF-α


CD8

Figure 4: Expression of immune-relevant genes determined by real-time polymerase chain reaction (PCR) in seabream following a diet with Debaryomy-ces hansenii L2 plus inulin at week 2. Fold change in gene expression compared with the control fish is expressed. All the genes were considered to be up-regulated if the relative value was above 1 and down-regulated with a relative value below 1. Each bar represents the mean SD of triplicate samples.

DiscussionThe demonstration that the gut microbiota is an important component of

the mucosal barrier has resulted in the promotion of its manipulation through the use of probiotics [54] and synbiotic [40]. Results obtained in this study suggest the ability of the yeast Debaryomyces hansenii strain L2 in conjunction with the prebiotic inulin to modify the status of the intestinal microbiota of gilthead seabream. In this context, the evaluation of the results derived from the

analyses of the PCR DGGE patterns suggests that the intragroup variability in the intestinal bacterial communities of Sparus aurata specimens was higher than in those fish receiving the diet supplemented with the synbiotic. Similar results have been reported for to the intestinal microbiota of other farmed fish such as Senegalese sole (Solea senegalensis) [55]. This intragroup variability also was observed for the intestinal microbiota of Sparus aurata specimens fed the diet II for 2 weeks. On the contrary, the PCR-DGGE profiles corresponding to fish receiving for 4 weeks the diet supplemented with the synbiotic mixture showed

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a very low intragroup variability and a very important reduction of the number of bands. These results suggest that the addition of the synbiotic mixture to the feed could exert an important influence on bacterial intestinal groups and yield a faster homogenization of the intestinal microbial community. This ability to modulate the intestinal microbiota by the synbiotics has also been reported in humans and other animals [13,40].

The interpretation of the molecular fingerprints in terms of mean Rr values obtained fish fed with diet I for 2 and 4 weeks and 2 weeks for fish receiving diet II showed that these were higher than 30. They are associated with very habitable environments characterized by a high microbial diversity with a high range-weighted richness, and they can host a lot of different microorganisms and genetic variability [47]. Bacterial diversity plays an important role in the functioning of microbial ecosystems [56]. Biodiversity protects ecosystems against declines in their functionality and allows for adaptation to changing conditions providing a greater guarantee that some will back up a given function when other fail [57,58]. On the contrary, the fish received the diet II for 4 weeks showed mean values of Rr ranging from 10 to 30, and they are considered as a medium range-weighted richness [47], which is a less habitable environment than the intestine of fish fed with the diets previously mentioned.

The intestinal microbiota of fish play an important role as a defensive barrier against pathogens [25], and it can regulate the expression of great numbers of genes in the digestive tract implied in the epithelial proliferation, promotion of nutrient, metabolism and immune response [31]. In a previous study, a stimulatory effect on the immunological system induced by the supplementation of feed with has Debaryomyces hansenii strain L2 been detected [20]. However, the different imnunostimulatory effect on the expression of genes in different organs was different depending on the time that fish were receiving the diet supplemented with the microorganism.

In this study, a reduction of the number of predominant PCR-DGGE bands was detected from fish fed diet II for 2 and especially 4 weeks, in comparison with those detected from fish receiving the diet I. It could indicate a reduction of the diversity of the predominant microbial species of the intestinal microbiota. It is assumed that the reduction of the diversity could suggest a negative effect because the diversity protects ecosystem against declines in their functionality and allows for adaptation to changing conditions [47,56,57]. However, in this study an important number of cloned sequences identified from intestinal samples from fish fed diet II for 4 weeks did not correspond to visible bands in the PCR-DGGE patterns. Similar results have been reported by other authors studying complex bacterial communities [59] and the effect of fermentable carbohydrates on piglet faecal bacterial communities [60]. It could indicate a higher diversity of that detected only from the number of visible bands of PCR-DGGE profiles. The absence of these bands in fish fed with the other diets may not exclude the presence of the same bacterial species in the samples, since they could be below the detection limit of the DGGE technique which has an abundance limit of 1% [61], although some of them can be selected using a cloning approach [60,62]. However, some authors suggest that those less abundant taxons could be less relevant for the functioning of the microbial community [63], but this point must be demonstrated.

Different microbial species were detected in fish fed for 2 and 4 weeks, and sequences related to Serratia genus were frequently detected from intestinal samples from fish fed both diets for 2 weeks, but they were not detected from samples recovered at 4 weeks. On the other hand, cloned sequences related to β-Proteobacteria were not detected from fish fed with the diets for 2 weeks although they were detected at 4 weeks. Pseudomonas was the only one genus detected from all intestinal samples of fish fed both diets for 2 and 4 weeks, although its frequency of detection was lower from fish receiving the diet II for 4 weeks. Ps. fluorecens was the most frequent species identified from cloned sequences. Several species of Pseudomonas genus have been described

as pathogenic for different farmed fish [64-69], Ps. fluorescens being one of them [70]. However Pseudomonas species have been identified as members of autochtonous microbiota of farmed fish [71-74], and several authors have reported the potential probiotic role play for strains of Pseudomonas genus [8,71,75,76].

Hematological parameters are typically used to asses the health status and detect physiological changes in a number of fish species [77]. It is known that inulin, particularly long chain molecules thereof, stimulates the human immune system by binding to specific lectin-like receptors on leucocytes and increasing macrophage proliferation [78]. In this work, cellular immunological parameters did not differ from the activity of fish fed the control diet at any time during the experiment, although there was a slight non-significant stimulation in these parameters in gilthead seabream. About the humoral parameters, serum peroxidase activity from individuals fed diet II was significantly enhanced at week 4 compared with the control group, which suggests that an enhanced leucocyte microbe-killing capacity is a key factor in increased resistance to disease. It has become readily evident that the microbiota affected by prebiotics plays integral roles in numerous processes including growth, digestion, immunity and disease resistance of the hot organism [21,79]. However, the relationship between the changes produced in the intestinal microbiota of fish receiving the synbiotic diet and the enhanced immunological response needs to be more studied. Cerezuela et al. [28] have studied the effect of inulin in seabream; however, immunostimulant effect of inulin on the innate immune system of gilthead seabream was not detected [28]. On the other hand, Reyes et al. [20] have observed that D. hansenii L2 is an effective immunostimulant in juveniles seabream.

Real-time PCR was performed to analyse the expression of IgM, MHCIα, MHCIIα, C3, IL-1β, TLR, TNFα, CSF-1R, NCCRP-1, Hep, TCRβ y CD8 in different tissues, including skin, intestine, liver and head-kidney. The present work demonstrates for the first time in fish that yeast-supplemented diets plus inulin (3%) up-regulated the expression of genes in skin and head-kidney of gilthead seabream, at week 2 and 4, respectively. In contrast, only the expression of MHCIIα was up-regulated in skin at week 4, the up-regulation of C3 being the most pronounced at week 4. Similar effect were observed in our laboratory where yeast D. hansenii L2 diets up-regulated the expression of several genes principally in skin and head-kidney [20]. Fish have a well-developed complement system that plays an important role in their innate immune response, including membrane attack complex (which lyses bacteria), opsonization and phagocytosis [80]. On the other hand, the mRNA transcript levels of MHC I, MHC II and TNF-α showed a tendency to increase in the intestine at 2 weeks, suggesting the importance of the intestinal tract as a site of immune activity. However, immunostimulant effect of inulin on the innate immune system of gilthead seabream was not detected [28]. These results suggest that Debaryomyces hansenii L2 could stimulate the immune system by itself. TNF-a is a key cytokine in acquired cell-mediated immunity to intracellular bacteria and tissue injury and it can stimulate immune responses by activating lymphocytes, or by inducing the release of other cytokines capable of triggering macrophages, NK cells and lymphocytes [81]. Genes of the MHC encode two classes of structurally similar, but functionally distinct, glycoproteins, MHC class I and class II, both of which are involved in the immune response at various levels [82]. These results suggest that D. hansenii L2 in conjunction with inulin could stimulate the expression of genes related of immune system. Reyes et al. [20] observed that this strain L2 by itself can induce immune responses in gilthead seabream Sparus aurata.

In this study, relevant changes in the intestinal microbiota of gilthead seabream specimens fed with the diets assayed have been demonstrated, and an important effect on the intestinal microbiota by the dietary administration of a probiotic mixture has also been detected, especially in fish receiving the diet supplemented with a synbiotic mixture for 4 weeks. These microbial

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changes coincided in the same time with a up-regulation the expression of immunological genes in skin and head kidney of gilthead seabream at 2 and 4 weeks, respectively. It would be very suggestive to think that this up-regulation expression of genes could be related with the changes produced on the fish intestinal microbiota. Looking at the molecular level, it is clear from our study that the yeast D. hansenii L2 in conjunction with inulin enhanced the immune response in terms of immune gene expressions in seabream. However, more studies are necessary to understand the potential effects of the intestinal microorganisms on the immune system of fish.

Acknowledgments

Tapia-Paniagua wishes to thank the Ministerio Español de Educación y Ciencia for a F.P.U. scholarship. M.Reyes-Becerril received postdoctoral scholarships from Consejo Nacional de Ciencia y Tecnología of México (CONACYT Grant 164653). This work was partially funded by the Ministerio de Ciencia e Innovación (AGL2008-05119-C02-01 and AGL2008-05119-C02-02, Spain) and Fundación Séneca de la Región de Murcia (06232/GERM/07).

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This article was originally published in a special issue, Probiotic & Prebiotic Applications in Aquaculture handled by Editor(s). Dr. Daniel L. Merrifield, University of Plymouth, UK; Prof. Zhigang Zhou, Chinese Academy of Agri-cultural Sciences, China

http://dx.doi.org/10.4172/2155-9546.S1-012http://journals.tubitak.gov.tr/veterinary/issues/vet-03-27-5/vet-27-5-25-0211-16.pdfhttp://www.ncbi.nlm.nih.gov/pubmed/12710484http://www.ncbi.nlm.nih.gov/pubmed/15950490http://www.ncbi.nlm.nih.gov/pubmed/17045337http://www.sciencedirect.com/science/article/pii/S0044848604003965

TitleAbstractIntroduction*Corresponding authorMaterials and MethodsDebaryomyces hansenii strain L2Fish and experimental designFish sample collectionIntestinal microbiota analysisCloning of the PCR-amplified productsSequence analysisBlood serum and head kidney leucocytesImmunological assaysStatistical analysis

ResultsDiscussionAcknowledgmentsTable 1Table 2Table 3Table 4Figure 1Figure 2Figure 3Figure 4Figure 5References

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