Field data and preliminary biogeochemical descriptors Sampling sites are grouped

Field data and preliminary biogeochemical descriptors. Sampling sites are grouped according to their lithology and listed in a north-to-south order.SampleLithologyLat UTM ED50Long UTM ED50Elevation (m a.s.l.)Eh (mV)T (°C)pHDO (mg L−1)EC (μS cm−1)Total coliforms (MPN/100 mL)E. coli (MPN/100 mL)M24Volcanites281559466041216521018.37.78.58594<1<1M37Volcanites276689465666412124017.76.916.663596<1M23Volcanites28310846562809922518.76.865.4557435<1M42Volcanites279295465457710020516.66.657.45146<1M44Volcanites27648746543345921516.17.69.026094356M43Volcanites277667465418564243178.149.3454419423M45Volcanites27862246526948919016.56.819.15357<1<1M15Volcanites2815974649236101260137.428.71448<1<1M14Volcanites27801946472739423015.97.449.12494<1<1M09Volcanites27733746421167127412.67.59.1583<1<1M29Alluvial27394246454023111517.37.012.61123<1<1M47Alluvial28107346441944918916.36.965.331168<1<1M18Alluvial27765046437566030516.87.136.14735<1<1M36Alluvial284816464309967−3018.37.425.95728<1<1M13Alluvial28034246427563251147.372.47757135<1M04Alluvial285548463896241240157.668.8753<1<1M34Alluvial278710463847026−8016.37.380.036915<1Full-size tableTable optionsView in workspaceDownload as CSVFig. 2. Box-plots of the chemical major components and trace elements measured in volcanic and alluvial aquifer portions. Lines within the boxes, boundaries, whiskers and dots mark the median, 25th–75th percentiles, 10th–90th percentiles, and outliers, respectively. The Cleveland linear interpolation method was used to compute the percentile values.Figure optionsDownload full-size imageDownload high-quality image (386 K)Download as PowerPoint slide3.2. Microbial community structure in volcanic and alluvial watersThe occurrence of total coliforms was higher in the volcanic sampling sites rather than in the alluvial ones. An indication of fecal contamination (i.e. E. coli occurrence >1 MPN/100 mL) was detected only in two samples collected from the volcanic area ( Table 1).The prokaryotic abundance was significantly lower in volcanic waters (median value = 3.3 × 104 cells mL−1) than in alluvial waters (27.4 × 104 cells mL−1). The contributions of LNA and HNA cells to the total abundance were statistically different in volcanic waters (35.7% and 64.4% as median values, respectively; U test p < 0.05) but not in the alluvial ones (52.1% and 47.9%, respectively; p > 0.05). The percentage of dead cells was higher in volcanic waters (8.9% of the total cells) comparing to alluvial waters (4.6% of the total cells). Most of the dead cells were associated with the LNA fraction in either volcanic (59.4%) or alluvial waters (68.5%) ( Fig. 3).Fig. 3. Microbial community composition as assessed by flow cytometry (upper box-plot) and CARD-FISH (lower box-plot) in the groundwaters collected from the volcanic and the alluvial part of the aquifer.Figure optionsDownload full-size imageDownload high-quality image (300 K)Download as PowerPoint slideFrom a phylogenetic point of view, Bacteria (51.1 ± 13.0% of the total prokaryotes) largely dominated over Paclitaxel (18.6 ± 7.4%). Despite the highest percentages were found in alluvial waters (up to 72.4 ± 0.8% for Bacteria and 29.7 ± 1.8% for Archaea), the relative occurrence of the two prokaryotic domains was not significantly different between the two groups of waters (U test, p > 0.05). The four phylogenetic classes of Proteobacteria, representing on average the 63% of the total Bacteria, were differently structured in the two aquifer portions. In volcanic waters, Alpha-Proteobacteria represented the most abundant group (median value = 11.2%), while Beta-, Gamma- and Delta-Proteobacteria accounted for about 5% of the total cells. In alluvial waters, Alpha- (17.4%) and Beta-Proteobacteria (15.8%) were the dominant groups. Interestingly, only Beta- and Delta-Proteobacteria accounted for a significant different fraction of total cells between the two groups of waters (U test, p < 0.05) ( Fig. 3). The quantitative tracking of microbial cytometric and phylogenetic groups at a single cell level showed significant changes in cell numbers along the flow path, with the exception of the dead cells, which were not statistically different between the two groups of waters (U test, p > 0.05).3.3. Biogeochemical evolution along the aquifer flow pathThe principal component analysis allowed recognizing the variation patterns of major water chemical determinants passing from volcanic to the alluvial deposits (Fig. 4). The first component explained most of the variance within the dataset (56.5%), thus discriminating between the two groups of waters. The V, SiO2, Sb and PO4 were relatively more concentrated in volcanic waters, showing a negative correlation with the PC1 axis. They progressively declined moving southward to the alluvial aquifer portion, but other elements significantly increased. Among those, salinity and major ions (e.g. HCO3, Ca, Na, Cl) and also some metals (e.g. Fe, Mn, Zn). According to the vector-fitting procedure on the NMDS representation of the chemical selected parameters, specific microbiological features appeared relatively more related to the overall chemical variability. The percentages of Beta- and Delta-Proteobacteria increased in the alluvial waters together with the abundance of viable cells. Those microbiological variables correlated positively with the NMDS axis 1, largely the most explicative of the dataset variability ( Fig. 4).Fig. 4. Principal Components Analysis biplot and Nonmetric MultiDimensional Scaling ordination plot representing the typifying chemical composition (a, b) and the related distribution of the microbial community subpopulations (c, d) in the transition from volcanic to alluvial portions of the aquifer. Stress value indicates the significant concordance between the distance among samples in the NMDS plot and the actual Bray–Curtis distance among samples. The microbiological parameters were incorporated in the NMDS analysis with a vector-fitting procedure. Length of arrows represents the correlation between corresponding parameters and PCA/NMDS axis 1 and 2. Histogram plots (b, d) show the contribution of each variable (vector projection values) expressed as the correlation with the x-axis, explaining most of the variance of the dataset.Figure optionsDownload full-size imageDownload high-quality image (364 K)Download as PowerPoint slideWith an approximated distance of 13 Km between the centroids of the recharge and discharge areas, we estimated a theoretical groundwater travel time of approximately 60–90 years, based on the average hydrodynamical properties of the geological formations in the study area. Comparatively, a theoretical travel time of 56 years was estimated according to the first order equation used to model the O2 reduction rates. The estimation of the propagation rates and generation times for each cytometric and phylogenetic microbial groups over a reasonable travel time of 60 years was then resumed in Table 2. The percentage increase of the HNA viable cells was higher than that of the total and of the LNA viable cells. All phylogenetic groups showed a cell increase higher than that of the total viable cells (>90%), except for the Gamma-Proteobacteria. Archaea appeared to propagate as quickly as Bacteria. The cell increase of Beta- and Delta-Proteobacteria were the highest among those of the retrieved Proteobacteria, thus reflecting higher propagation rates ( Table 2).Table 2.

The putative TLR protein sequences used for

The putative TLR2 protein sequences used for multiple alignments and phylogenetic analysis.SpeciesCommon nameFull length identity (%)TIR domain identity (%)GenBank Accession no.Miichthys miiuymiiuy croaker9595AFG21856.1Oplegnathus fasciatusJapanese parrotfish7986AFZ81806.1Epinephelus coioidesOrange-spotted grouper7583AEB32453.1Oreochromis niloticusTilapia7082XP_005460222.1Paralichthys olivaceusJapanese flounder7283BAD01044.1Trematomus bernacchiiTrematomus bernacchii7182ACT64128.1Takifugu rubripesfugu rubripes6678AAW69370.1Chionodraco hamatuscrocodile icefish7080ACT64127.1Oncorhynchus mykissrainbow trout5669CCK73195.1Cyprinus carpiocommon carp4557ACP20793.1Ctenopharyngodon idellagrass carp4657ACT68333.1Ictalurus punctatuschannel catfish4559AEI59663.1Labeo rohitarohu4457ADQ74644.1Danio reriozebra fish4455NP_997977.1Anas platyrhynchosduck3655ADO39962.1Felis catuscat3754XP_003984979.1Equus caballushorse3754NP_001075265.1Loxodonta africanaAfrican elephant3755XP_003417572.1Oryctolagus cuniculusrabbit3855NP_001076250.1Homo sapienshuman3855AAY85647.1Gallus galluschicken3655ACR26424.1Bos taurusbovine3755NP_776622Mus musculusmouse3654AAH14693Full-size tableTable optionsView in workspaceDownload as CSV2.5. Cell culture and LcTLR2 subcellular localizationLarge yellow croaker kidney cell line (LCK) was cultured in Gibco MEM (41500-034, Invitrogen, USA) medium at 25 °C. The cDNA of LcTLR2 was used as template and PCR amplifications were performed with EcoR? and BamHI 5′-tailed primers, TLR2-pEGFP-F1 and TLR2-pEGFP-R1 ( Table 1), at annealing temperature of 57 °C. After restriction digestion with EcoR ? and BamH ?, the PCR product was ligated with an identically predigested pEGFP-n1 vector (Clontech Laboratories) to create LcTLR2-pEGFP. Briefly, 3 × 105 LCK cells were seeded in 6-wells plates and cultured at 25 °C for overnight and were transfected with 4 μg of either pEGFP or LcTLR2-pEGFP plasmid and 10 μl Lipofectamine 2000 (Life Technologies, USA). Cells expression of the EGFP or LcTLR2-pEGFP fusion proteins was visualized at the 24 h using Leica fluorescence microscopy (DMI3000B, Germany). Cell nuclear was stained with Hoechst 33342 (Life Technologies, USA).2.6. Immune challenge in LCKFive × 106 LCK cells were incubated with 30 μg/ml LPS (L2880, Sigma, USA) [24], 1 μg/ml Salmonella Typhimurium flagellin (12B06-MM, InvivoGen, USA) [25], 15 μg/ml PNG (77140, Sigma, USA) [26] and 10 μg/ml polyI:C (27472901, GE, USA) [24] respectively. The cells were incubated with same volume PBS as negative control. For each stimulant, cells from three replicate wells were sampled at 6, 12, 24 and 48 h and were stored at −80 °C for RNA extraction (n = 3).2.7. Real-time PCR analysis of LcTLR2 mRNA expressionThe expression of LcTLR2 mRNA in the different tissues including the kidney, head-kidney, intestine, spleen, liver, gill, brain, skin, muscle, heart, stomach and blood cells, the temporal expression in the spleen, head-kidney and liver challenged with V. parahaemolyticus, polyI:C and LPS, and the temporal expression in LCK challenged with LPS, flagellin, PGN and polyI:C were assessed using qRT-PCR in an ABI 7500 Real-time Detection System (Applied Biosystems, USA). The housekeeping gene β-actin was used as an internal control for cDNA normalization. The primers β-actin-F and β-actin-R ( Table 1) were used to amplify a 107-bp β-actin gene fragment and gene-specific primers TLR2QF and TLR2QR were used to amplify a 160-bp LcTLR2 cDNA fragment ( Table 1). The PCR product was sequenced to verify the specificity of RT-PCR. The amplification was performed as previous report [20] and [27]. Dissociation analysis of amplification products was performed at the end of each PCR reaction to confirm that only the special PCR product was amplified and detected. After the PCR program, data were analyzed with ABI 7500 SDS software. To maintain consistency, the baseline was set automatically by the software. The comparative CT method (2−ΔΔCT method) was used to analyze the expression level of LcTLR2 [28]. All data were given in terms of relative mRNA expression as means ± SE. The data obtained from six or three independent biological replicates were subjected to statistical analysis.2.8. Statistical analysisThe data were analyzed by one-way analysis of variance (one-way ANOVA) using SPSS 19.0 for Windows (SPSS Inc.). A value of p < 0.05 was considered as statistically significant difference. The results were plotted by Origin 8.0 software (Origin Lab Corporation, MS, USA). Asterisks denote statistically significant differences between experimental treatments and the control.3. Results3.1. Characterization of the full-length cDNA of LcTLR2BLASTX search indicated that a 162-bp cDNA fragment from our EST database had 82% identity with the TLR2 of orange-spotted grouper. Then, a fragment of 1961-bp was obtained by 3′ RACE PCR. Subsequently, a 1041-bp fragment was obtained by 5′ RACE PCR, which contained an initial start codon for Met. As a result, a 2802-bp nucleotide sequence representing the full-length cDNA of LcTLR2 was obtained. BLASTX analysis suggested that LcTLR2 had high homology to other fish TLR2.The full-length cDNA sequence of LcTLR2 was deposited to GenBank (KJ820743) which contained an ORF of 2451 bp encoding a polypeptide of 816 amino acids residues, a 5′-UTR of 135 bp, and a 3′-UTR of 216 bp, which included an RNA instability motif (ATTTA), a canonical polyadenylation signal (ATTAAA) and a 21-bp poly (A) tail ( Fig. 1).Fig. 1. Nucleotide sequence and deduced amino Mifepristone sequence of LcTLR2 cDNA. The start codon (ATG) is boxed and the stop codon (TGA) is represented with an asterisk. The polyadenylation signal motif (AATAAA) is in bold. In the deduced amino acid sequence, signal peptide is marked by dot underline (1–22aa). The LRR motifs are shown as underscore (82–104aa, 105–128aa, 154–177aa, 178–201aa, 365–386aa, 394–413aa, 420–443aa, 444–463aa, 464–483aa, 484–507aa, 541–595aa). The transmembrane domain is shown as double-underline (597–619aa). The TIR domain is shaded (657–812aa).Figure optionsDownload full-size imageDownload as PowerPoint slide3.2. Putative protein structure of LcTLR2Prediction of protein domains by SMART program revealed that LcTLR2 consisted of a signal peptide in the first 22 amino acids at the N-terminal, followed by 9 LRRs, an LRR typicals (LRRTYP) and an LRR C-terminal (LRRCT) domain (82–595 amino acids), a transmembrane region at amino acid positions 597–619, and a TIR domain at the positions 597–619 ( Fig. 1). The putative molecular weight (Mw) of LcTLR2 mature peptide was 90.73 kDa and the isoelectric point was 6.15.LcTLR2 shows the highest amino acid identity of 95% with TLR2 from miiuy croaker, Miichthys miiuy and the lowest amino acid identity of 44% with zebrafish and Indian major carp (Labeo rohita) ( Table 2). And LcTLR2 shared highly conservative LRR domains and TIR domain with TLR2 from other fish, birds and mammals ( Fig. 2).Fig. 2. The putative protein structures of TLR2 from fish, birds and mammals. (A) Schematic representation of the structures of the predicted TLR2 proteins. Domains in the proteins were predicted by the SMART program. Signal peptide, LRR, LRRCT, transmembrane region, and TIR domain are indicated in the picture. Large yellow croaker TLR molecules include 11 LRR repeats in the N-terminal region, followed by a transmembrane region and the conserved TIR domain at the C-terminal end. (B) Alignment of the amino acid sequences of TIR domain of TLR2. Alignments were performed using the ClustalW. Three typical Box in TIR domain (boxes 1, 2, and 3) are conserved from fish to mammals. GenBank Accession numbers were listed in Table 2.Figure optionsDownload full-size imageDownload as PowerPoint slide3.3. Phylogenetic analysis of LcTLR2The results of phylogenetic analysis revealed that the deduced amino acid sequence of the LcTLR2 was in the same subgroup with the TLR2 from other teleost. The closest relationship of LcTLR2 was found with TLR2 from miiuy croaker. TLR2 from birds and mammals were also clustered into their corresponding subgroups. The observed relationships within this cluster reflected the taxonomic positions of the species ( Fig. 3).Fig. 3. Phylogenetic tree of TLR2 sequences. Complete amino acids sequences were aligned by using ClustalW, and the tree was constructed with NJ method in MEGA 5.05 and a bootstrap analysis was performed using 1000 replicates to test the relative support for particular clades. GenBank accession numbers of these genes were listed in Table 2.Figure optionsDownload full-size imageDownload as PowerPoint slide3.4. Subcellular localization of LcTLR2 in PCK cell linesThe expression of the fused LcTLR2-EGFP specific protein in transfected LCK is shown in Fig. 4. The subcellular localization results showed that pEGFP protein was mainly localized in both cell nucleus and cytoplasm. However, the LcTLR2-pEGFP fusion protein was mainly expressed in cytoplasm.Fig. 4. The subcellular localization of LcTLR2 in LCK cell line. The expression of internal control (EGFP) and LcTLR2-EGFP in LCK cells. Bar = 20 μm.Figure optionsDownload full-size imageDownload as PowerPoint slide3.5. Expression of LcTLR2 transcripts in tissuesThe tissue expression of LcTLR2 gene results showed that it expressed in most examined tissues, with the most predominant expression levels in blood, followed by spleen. The expression level of LcTLR2 in gill was very weak ( Fig. 5).Fig. 5. Expression of LcTLR2 in different tissues of large yellow croaker relative to β-actin, the tissues include kidney, liver, stomach, spleen, head-kidney, intestine, brain, skin, gill, heart, muscle and blood, respectively (n = 6).Figure optionsDownload full-size imageDownload as PowerPoint slide3.6. Expression profiles of LcTLR2 mRNA in spleen, head-kidney and liver after immune injectionTranscriptional changing of LcTLR2 after immune-stimulation in spleen is shown in Fig. 6A. Significant up-regulation of LcTLR2 transcripts was detected from 3 h to 6 h after V. parahaemolyticus injection (p < 0.05), reaching a peak value 23-fold that of the control group at 6 h. However, it returned to the control level from 12 h to 72 h post-injection. After injection with polyI:C, significant up-regulation of LcTLR2 transcripts appeared at 6 h and 12 h (p < 0.05), and the highest expression was 2.54-fold as much as the control at 6 h. However, it recovered to the control level from 24 to 72 h post-injection. LcTLR2 expression levels increased significantly at 3 h and 6 h after LPS stimulation, with the highest expression reaching 5 times that of the control group at 6 h (p < 0.05). Then it recovered to the control level from 12 to 72 h.Fig. 6. Analysis of LcTLR2 expression relative to control in spleen (A), head-kidney (B) and liver (C) after V. parahaemolyticus, polyI:C and LPS challenge. Error bars represented the mean ± SE, and significant difference (p < 0.05) between the experimental group and the control group at the corresponding point was indicated with asterisks (n = 6).Figure optionsDownload full-size imageDownload as PowerPoint slideExpression profiles of LcTLR2 in head-kidney after immune stimulation are shown in Fig. 6B. LcTLR2 transcripts showed significant increase from 12 to 72 h after V. parahaemolyticus injection (p < 0.05), with the peak value reaching 32-fold that of the control group at 72 h (p < 0.05). After polyI:C stimulation, LcTLR2 transcripts showed significant up-regulation at 12 h (p < 0.05), however, it did not show significant change at other time points. After LPS stimulation, LcTLR2 transcripts showed significant increase from 3 to 6 h (p < 0.05), then it returned to the control level after 6 h post-injection.LcTLR2 transcripts in liver after immune stimulation are shown in Fig. 6C. After V. parahaemolyticus injection, LcTLR2 transcripts increased gradually from 3 h to 24 h, with the peak value reaching 40-fold that of the control at 6 h (p < 0.05). Then LcTLR2 transcripts returned to the control levels from 48 to 72 h post-injection. After injection with polyI:C, LcTLR2 transcripts showed significant increase from 3 to 48 h (p < 0.05), with the highest value reaching 17.5-fold that of the control at 12 h, and it returned to the control level at 72 h. After stimulation with LPS, LcTLR2 expression levels showed significant increase from 6 h to 12 h (p < 0.05), with the highest expression reaching 5 times higher than that of the control at 12 h. Then it returned to the control level from 24 h to 72 h.3.7. Expression profiles of LcTLR2 in PCK cell line after immune challengeExpression profiles of LcTLR2 in LCK cell line after immune challenge are shown in Fig. 7. After flagellin stimulation, LcTLR2 transcripts showed a gradual increase, reaching a peak value 22.5-fold that of the control at 24 h (p < 0.05). After polyI:C challenge, LcTLR2 transcripts did not show significant change at most time points. However, after PGN stimulation, the expression levels of LcTLR2 increased significantly from 12 h to 48 h, the peak value reaching 17.5-fold that of the control at 24 h (p < 0.05). LcTLR2 transcripts showed a moderate increase after LPS stimulation, with the significant high expression appeared at 12 and 24 h (p < 0.05).Fig. 7. Expression levels of LcTLR2 relative to β-actin in LCK cell line of large yellow croaker after incubation with flagellin, polyI:C, peptidoglycan and LPS. Significant difference (p < 0.05) between the challenge group and the control group at the corresponding time were indicated with asterisk (n = 3).Figure optionsDownload full-size imageDownload as PowerPoint slide4. DiscussionIn the present study, LcTLR2 was cloned and characterized. The full-length cDNA of LcTLR2 was 2802 bp, including an ORF of 2451 bp encoding a polypeptide of 816 amino acids. The theoretical ectodomain of LcTLR2 contained 11 LRRs, including 9 conserved LRRs, an LRRTYP and an LRRCT ( Fig. 1 and Fig. 2). LcTLR2 shared similar structure characterization with TLR2 from zebrafish, Japanese flounder, orange-spotted grouper and miiuy croaker, which contained 7 LRRs, 8 LRRs, 10 LRRs and 9 LRRs, respectively [10], [12], [15] and [29]. TIR domain in LcTLR2 shared high identities with TIR in other invertebrate TLRs ( Table 2, Fig. 3), suggesting that LcTLR2 has similar recognition domain and conservative adapter binding domain with its counterparts in other fish and might have similar signal transduction function upon ligand stimulation in immune response.The subcellular localization of LcTLR2 in LCK cell lines ( Fig. 4) showed that it mainly expressed in cytoplasm. It was demonstrated that human TLR2 was mainly expressed on the cell membrane and in the cytoplasm in cultured biliary epithelial cells [30], indicating that LcTLR2 might have the similar expression pattern with its mammalian counterparts.LcTLR2 transcripts were broadly expressed in most examined tissues of large yellow croaker. Similar results were reported in zebrafish, Japanese flounder, orange-spotted grouper and miiuy croaker [10], [12], [15] and [29]. The most predominant expression of LcTLR2 was found in blood and then followed by spleen, and high expression levels of LcTLR2 were also detected in head-kidney and liver, suggesting that LcTLR2 mainly expressed in the immune tissues ( Fig. 5). Our results agreed closely with previous investigations from zebrafish [10], Japanese flounder [12] and catfish [14], suggesting that LcTLR2 was mainly expressed in immune tissues and might play important roles in fish immune response.The function of TLR2 in immune responses is complicated and varied in different species. Previous studies showed that TLR2 transcripts increased after viral [15] and [17] and bacterial [10], [11], [15], [31] and [32] stimulation. In the present study, significant up-regulations of LcTLR2 transcripts were also detected in spleen, head-kidney and liver after V. parahaemolyticus and LPS injection (p < 0.05) ( Fig. 6A–C), indicating that LcTLR2 could be induced after bacterial challenge in main immune tissues of large yellow croaker. Similar results were found in catfish and zebrafish after G+ and G− bacterial injection [13] and [14]. A moderate up-regulations of LcTLR2 were also induced by polyI:C stimulation in all examined tissues ( Fig. 6A–C). Similarly, significant up-regulations of TLR2 were reported in Japanese flounder and orange-spotted grouper after polyI:C challenge [12] and [15], suggesting that TLR2 expression also could be induced by viral infection. However, compared with V. parahaemolyticus injection group, the greatest values of LcTLR2 expression in LPS and polyI:C injection group were much lower in the three examined tissues ( Fig. 6A–C), demonstrating that TLR2 might play a more important role in large yellow croaker response to infectious bacteria, V. parahaemolyticus.In order to understand the detailed immune response characterizations of LcTLR2 in large yellow croaker, we investigated the expression of LcTLR2 in LCK cells after different PAMPs challenge ( Fig. 7). Our results showed that LcTLR2 transcripts were induced significantly in LCK after stimulation with flagellin, PGN and LPS (p < 0.05). However, compared with LPS challenge group, higher expression levels of LcTLR2 were induced after flagellin and PGN stimulation. Our findings indicated that LcTLR2 might play an important role by recognizing flagellin and PGN to respond bacterial infection in large yellow croaker. Similar results were observed in the miiuy croaker [29] and Indian major carp [32]. According to the evolution relationship of TLR family, TLR2 and TLR1 belonged to the TLR1 subfamily [6] and [33]. However, Wang and colleagues demonstrated that TLR1 transcripts obviously increased in the anterior kidney cells of large yellow croaker [34], suggesting that TLR2 might have the different function with TLR1. However, incubation with polyI:C did not induce LcTLR2 response in LCK, suggesting that TLR2 might be more important in recognizing bacterial infection in large yellow croaker. Our previous investigation demonstrated that LcTLR3 expression was induced obviously after polyI:C stimulation [20], indicating that the main function of TLR2 was not recognition of polyI:C. Nevertheless, significant increases of LcTLR2 transcripts were detected in spleen, head-kidney and liver after the polyI:C challenge in vivo ( Fig. 6A–C), suggesting that LcTLR2 might be induced by other immune factors.In conclusion, the full-length cDNA of LcTLR2 was cloned from large yellow croaker, which belonged to the conserved TLR2 family. LcTLR2 transcripts were broadly expressed in most examined tissues with high levels in the immune related tissues and very weak in the gill tissue. Subcellular location revealed that LcTLR2 mainly expressed in the cytoplasm and on cell membrane. The expression levels of LcTLR2 could be induced significantly in most immune tissues after V. parahaemolyticus, LPS and polyI:C stimulation. However, compared with polyI:C, LcTLR2 might play a more important role in large yellow croaker defense against bacterial infection through recognition flagellin and PGN.AcknowledgmentsThis research was supported by National Natural Science Foundation of China (31101882; 41276178) and the National Basic Research Program of China (2011CB111604) to C.L.Y.

Energy of the lowest conduction

Energy of Cobicistat lowest conduction band and highest valence band for majority and minority spin along with band gaps for minority spin and half metallic band gaps.CompoundMethod of calculationE↑C (eV)E↑V (eV)Eg-HM (eV)E↓C (eV)E↓V (eV)EgΓ–Γ (eV)Zn1−xCrxSPBE-GGA0.3950.220.1750.56−1.642.2mBJ-LSDA1.6850.1421.5431.748−2.0643.812Zn1−xMnxSPBE-GGA0.265−0.8401.1050.40−1.6852.085mBJ-LSDA2.732−0.2823.0142.748−0.8433.591Zn1–2xCrxMnxSPBE-GGA−0.370−0.6150.245−0.18−2.82.62mBJ-LSDA−0.084−0.9950.911−0.112−3.4313.319Zn1–2xMnxCrxSPBE-GGA0.5750.210.570.78−1.952.525mBJ-LSDA1.3950.1371.2581.325−2.3153.640Full-size tableTable optionsView in workspaceDownload as CSVThe calculated values of ΔEc, ΔEv, N0α and N0β are listed in the Table 3 and roots is obvious that the values of p-d exchange splitting N0α and p-d exchange constants N0β are consistent with respect to their negative signs. The opposite signs of N0α and N0β indicates the FM character as this reveals that the conduction and valence Cobicistat states are behaving in an opposite mode during the exchange splitting process. N0α and N0β have opposite sign for all the compounds in PBE-GGA while in mBJ-LSDA, N0α and N0β have same sign for ZnMnCrS and ZnCrMnS and opposite sign for ZnCrS and ZnMnS.Table 3.