TY - JOUR
AU - Araus, José Luis
AB - Abstract Mercury (Hg) is a toxic metal that affects plant growth. Here the effect of Hg exposure on plant growth and leaf gas-exchange together with gene expression in roots is reported for barley. Hg was mainly accumulated in roots and only very small amounts were found in the shoots. Chlorophyll fluorescence and net photosynthesis were not affected by Hg. Nevertheless exposure to Hg reduced shoot and root growth, the shoot to root ratio, stomatal conductance, carbon isotope discrimination and expression of an aquaporin transcript, whereas abscisic acid related transcripts were over-expressed. These results suggested some degree of limitation to water uptake causing a moderate water stress when plants are exposed to Hg. Microarray (MapMan) analysis revealed changes in the transcription of genes involved in nitrogen metabolism, which were accompanied by decreased nitrogen concentrations in the shoots, together with an increase in transcripts associated with secondary metabolism, stress, inhibition of DNA synthesis/chromatin structure and cell organization elements. Moreover, Hg induced the expression of many transcripts known to be involved in the uptake, accumulation, transport and general responses to other heavy metals. It is concluded that barley is able to accumulate high amounts of Hg in roots through several transcriptional, metabolic and physiological adjustments. Graphical Abstract Open in new tabDownload slide Mercury (Hg) is a toxic metal that affects plant growth. 1 Introduction Mercury (Hg) is considered an environmental pollutant that can pose a serious threat to human health and development, in addition to it being highly persistent in nature.1–3 Natural sources of Hg include sediments arising from volcanic action and their erosion. Other sources of contamination include human inputs through mining, namely the transportation and processing of Hg ores; the dumping of industrial waste into rivers and lakes; the combustion of fossil fuels (e.g. Hg in coal is about 1 ppm4), pulp and paper production; seed dressings used in agriculture; and exhausts of metal smelters.5 Mercury concentrations as high as 200 ppm were measured in an abandoned stampmill site near Atlanta, USA.6 Like lead (Pb) and cadmium (Cd), Hg can have a deleterious effect on plants. Mercury has been shown to reduce cell proliferation and inhibit the growth of both roots and shoots in a number of different species.7–10 Metabolic alterations form part of the tolerance mechanisms of roots against toxic ions.11 Hg blocks essential functional groups (e.g. sulfhydryl groups) in biomolecules12–14 and induces the production of reactive oxygen species.7,8,10,13,15 In Medicago sativa, Hg not only severely compromises cellular redox homeostasis but also causes cell necrosis, with root hairs showing clear plasmolysis and loss of cytosolic content.8 A microarray survey of genes induced by Hg in Arabidopsis leaves showed that proteins encoding the photosynthetic apparatus and the anti-oxidative system were all induced by this element.15,16 The induction of these genes was hypothesized to compensate for damage to the photosynthetic apparatus caused by Hg and to protect the plant from oxidative stress, respectively.15 Other genes encoding cell wall-localized proteins, cytochrome P450, and an indole-3-glycerol phosphate synthetase gene participating in the tryptophan biosynthetic pathway are also induced by Hg.15 In maize, a group of leaf genes associated with aerial exposure to Hg encode for glycine-rich protein, pathogenesis-related proteins, chaperones and membrane proteins.17 In fact, a preliminary evaluation in sunflower leaves of metal-ion stress tolerance has been carried out through proteomic changes.18 However, besides the identification of a limited number of proteins, no membrane transporters have been identified so far. While these studies have been conducted in plant leaves, there is little information available on the mechanisms used by roots to adapt to Hg stress. On contaminated soil sites the stress is permanent, therefore, the study of long term molecular responses rather than short term exposure responses is needed. Moreover, the precise ways in which plants respond to Hg phytotoxicity are poorly understood, especially the gene expression profiles of roots exposed to this toxic element and their consequences for plant photosynthesis and growth. Another specific objective of this work was to evaluate the pattern of Hg accumulation in barley roots and shoots and identify the expression of genes associated with transport and accumulation in roots. To that end, an experiment was conducted where the transcriptomic profiles of roots, growth of both roots and shoots, and photosynthetic traits (gas exchange and carbon isotope discrimination) in shoots of barley plants exposed to different levels of Hg were studied. We chose barley since this crop is a fast growing crop species that is well adapted to marginal areas exposed to abiotic stresses such as drought or salinity,19,20 which makes barley a potential candidate for heavy metal bioremediation.21 Nonetheless, the potential risks for human health and animal feed from barley grown in Hg contaminated soils have been recently studied.22 Furthermore, barley has been proposed as a model plant for studying the increasing prevalence of iron (Fe) and zinc (Zn) deficiencies in human populations worldwide, with the need for more information about the distribution and chemical speciation of these elements in cereal products.23 2 Results Plant growth, photosynthesis, water status, N content and Hg accumulation Shoot biomass was 35 and 55% smaller in M1 and M2 plants compared to control plants (Table 1), respectively. However, significant decreases (30%) of root dry weight were only observed in M2, but not in M1 (Table 1). These results indicated greater decreases in shoot DW than root DW due to Hg exposure. As a consequence the shoot to root ratio was significantly decreased under both Hg concentrations (Table 1). Besides changes in total biomass and root to shoot partitioning, Hg exposure also induced root browning (Fig. 1). The Hg concentration in shoots ranged from 3.1 to 130 μg g−1 between M1 and M2, whereas in roots it ranged from 4000 to 7000 μg g−1 (Table 1). Table 1 Root dry weight (root DW), shoot dry weight (shoot DW), total plant dry weight (total DW), shoot to root ratio (shoot : root), mercury concentration in roots and shoots, light-saturated net CO2 assimilation rate (Asat), stomatal conductance (gs), maximum quantum yield of PSII (Fv/Fm), relative quantum yield of PSII (ΦPSII), relative efficiency of open PSII reaction centres (Fv′/Fm′) and photochemical quenching (qp), N content in roots and leaves (N and C leaf, N and C root) and leaf C isotope discrimination (leaf Δ13C) in barley grown under control conditions, and with Hg treatments M1 and M2. Means and standard deviations (Std) are shown. Means followed by different letters are significantly different at probabilities (P) using the LSD test. Ns, non-significant . Control . M1 . M2 . LSD . P . Mean . Std . Mean . Std . Mean . Std . Root DW (mg) 29.5a 5.0 30.5a 5.2 17.7b 4.3 7.8 <0.01 Shoot DW (mg) 78.2a 9.6 50.7b 16.4 35.0b 6.8 18.7 <0.005 Total DW (mg) 107.7a 14.1 81.2b 18.7 52.7c 12.9 23.9 <0.005 Shoot : root 2.8a 0.4 1.8b 0.5 1.8b 0.3 0.5 <0.01 Shoot Hg (μg Hg gDW−1) 1.8a 0.4 3.1a 0.2 130b 8 10.5 <0.0001 Root Hg (μg Hg gDW−1) 0.15a 0.02 3765b 355 6950b 356 662 <0.0001 Asat 17.5a 2.4 17.6a 1.2 15.9a 0.9 3.3 Ns gs 0.31a 0.04 0.28a,b 0.01 0.23b 0.02 0.06 <0.10 Fv/Fm 0.798a 0.005 0.800a 0.004 0.801a 0.001 0.007 Ns ΦPSII 0.229a 0.021 0.230a 0.023 0.213a 0.009 0.04 Ns Fv′/Fm′ 0.458a 0.012 0.451a 0.009 0.447a 0.007 0.03 Ns qp 0.499a 0.035 0.509a 0.044 0.476a 0.007 0.08 Ns Nleaf (%) 2.97a 0.17 1.47b 0.22 1.75b 0.13 0.4 <0.005 Nroot (%) 1.15a 0.15 1.50a 0.16 1.4a 0.25 0.43 Ns Cleaf (%) 40.5a 1.9 39.2a 1.8 38.3a 3.4 5.9 Ns Croot (%) 29.5b 2.9 34.5a 1.0 35.2a 1.2 2.3 <0.05 Leaf Δ13C (‰) 19.1a 0.5 16.5b 0.5 17.2a,b 0.7 1.5 <0.05 . Control . M1 . M2 . LSD . P . Mean . Std . Mean . Std . Mean . Std . Root DW (mg) 29.5a 5.0 30.5a 5.2 17.7b 4.3 7.8 <0.01 Shoot DW (mg) 78.2a 9.6 50.7b 16.4 35.0b 6.8 18.7 <0.005 Total DW (mg) 107.7a 14.1 81.2b 18.7 52.7c 12.9 23.9 <0.005 Shoot : root 2.8a 0.4 1.8b 0.5 1.8b 0.3 0.5 <0.01 Shoot Hg (μg Hg gDW−1) 1.8a 0.4 3.1a 0.2 130b 8 10.5 <0.0001 Root Hg (μg Hg gDW−1) 0.15a 0.02 3765b 355 6950b 356 662 <0.0001 Asat 17.5a 2.4 17.6a 1.2 15.9a 0.9 3.3 Ns gs 0.31a 0.04 0.28a,b 0.01 0.23b 0.02 0.06 <0.10 Fv/Fm 0.798a 0.005 0.800a 0.004 0.801a 0.001 0.007 Ns ΦPSII 0.229a 0.021 0.230a 0.023 0.213a 0.009 0.04 Ns Fv′/Fm′ 0.458a 0.012 0.451a 0.009 0.447a 0.007 0.03 Ns qp 0.499a 0.035 0.509a 0.044 0.476a 0.007 0.08 Ns Nleaf (%) 2.97a 0.17 1.47b 0.22 1.75b 0.13 0.4 <0.005 Nroot (%) 1.15a 0.15 1.50a 0.16 1.4a 0.25 0.43 Ns Cleaf (%) 40.5a 1.9 39.2a 1.8 38.3a 3.4 5.9 Ns Croot (%) 29.5b 2.9 34.5a 1.0 35.2a 1.2 2.3 <0.05 Leaf Δ13C (‰) 19.1a 0.5 16.5b 0.5 17.2a,b 0.7 1.5 <0.05 Open in new tab Table 1 Root dry weight (root DW), shoot dry weight (shoot DW), total plant dry weight (total DW), shoot to root ratio (shoot : root), mercury concentration in roots and shoots, light-saturated net CO2 assimilation rate (Asat), stomatal conductance (gs), maximum quantum yield of PSII (Fv/Fm), relative quantum yield of PSII (ΦPSII), relative efficiency of open PSII reaction centres (Fv′/Fm′) and photochemical quenching (qp), N content in roots and leaves (N and C leaf, N and C root) and leaf C isotope discrimination (leaf Δ13C) in barley grown under control conditions, and with Hg treatments M1 and M2. Means and standard deviations (Std) are shown. Means followed by different letters are significantly different at probabilities (P) using the LSD test. Ns, non-significant . Control . M1 . M2 . LSD . P . Mean . Std . Mean . Std . Mean . Std . Root DW (mg) 29.5a 5.0 30.5a 5.2 17.7b 4.3 7.8 <0.01 Shoot DW (mg) 78.2a 9.6 50.7b 16.4 35.0b 6.8 18.7 <0.005 Total DW (mg) 107.7a 14.1 81.2b 18.7 52.7c 12.9 23.9 <0.005 Shoot : root 2.8a 0.4 1.8b 0.5 1.8b 0.3 0.5 <0.01 Shoot Hg (μg Hg gDW−1) 1.8a 0.4 3.1a 0.2 130b 8 10.5 <0.0001 Root Hg (μg Hg gDW−1) 0.15a 0.02 3765b 355 6950b 356 662 <0.0001 Asat 17.5a 2.4 17.6a 1.2 15.9a 0.9 3.3 Ns gs 0.31a 0.04 0.28a,b 0.01 0.23b 0.02 0.06 <0.10 Fv/Fm 0.798a 0.005 0.800a 0.004 0.801a 0.001 0.007 Ns ΦPSII 0.229a 0.021 0.230a 0.023 0.213a 0.009 0.04 Ns Fv′/Fm′ 0.458a 0.012 0.451a 0.009 0.447a 0.007 0.03 Ns qp 0.499a 0.035 0.509a 0.044 0.476a 0.007 0.08 Ns Nleaf (%) 2.97a 0.17 1.47b 0.22 1.75b 0.13 0.4 <0.005 Nroot (%) 1.15a 0.15 1.50a 0.16 1.4a 0.25 0.43 Ns Cleaf (%) 40.5a 1.9 39.2a 1.8 38.3a 3.4 5.9 Ns Croot (%) 29.5b 2.9 34.5a 1.0 35.2a 1.2 2.3 <0.05 Leaf Δ13C (‰) 19.1a 0.5 16.5b 0.5 17.2a,b 0.7 1.5 <0.05 . Control . M1 . M2 . LSD . P . Mean . Std . Mean . Std . Mean . Std . Root DW (mg) 29.5a 5.0 30.5a 5.2 17.7b 4.3 7.8 <0.01 Shoot DW (mg) 78.2a 9.6 50.7b 16.4 35.0b 6.8 18.7 <0.005 Total DW (mg) 107.7a 14.1 81.2b 18.7 52.7c 12.9 23.9 <0.005 Shoot : root 2.8a 0.4 1.8b 0.5 1.8b 0.3 0.5 <0.01 Shoot Hg (μg Hg gDW−1) 1.8a 0.4 3.1a 0.2 130b 8 10.5 <0.0001 Root Hg (μg Hg gDW−1) 0.15a 0.02 3765b 355 6950b 356 662 <0.0001 Asat 17.5a 2.4 17.6a 1.2 15.9a 0.9 3.3 Ns gs 0.31a 0.04 0.28a,b 0.01 0.23b 0.02 0.06 <0.10 Fv/Fm 0.798a 0.005 0.800a 0.004 0.801a 0.001 0.007 Ns ΦPSII 0.229a 0.021 0.230a 0.023 0.213a 0.009 0.04 Ns Fv′/Fm′ 0.458a 0.012 0.451a 0.009 0.447a 0.007 0.03 Ns qp 0.499a 0.035 0.509a 0.044 0.476a 0.007 0.08 Ns Nleaf (%) 2.97a 0.17 1.47b 0.22 1.75b 0.13 0.4 <0.005 Nroot (%) 1.15a 0.15 1.50a 0.16 1.4a 0.25 0.43 Ns Cleaf (%) 40.5a 1.9 39.2a 1.8 38.3a 3.4 5.9 Ns Croot (%) 29.5b 2.9 34.5a 1.0 35.2a 1.2 2.3 <0.05 Leaf Δ13C (‰) 19.1a 0.5 16.5b 0.5 17.2a,b 0.7 1.5 <0.05 Open in new tab Fig. 1 Open in new tabDownload slide Details of roots grown in the absence (a) and presence (b) of Hg (M2) showing root browning. Root exposure to Hg did not have a significant effect on photosynthesis (Asat) measured by gas exchange techniques (Table 1). Photosynthesis performance was further estimated with chlorophyll fluorescence (Fv/Fm, Fv′/Fm′, ΦPSII and qp) and these parameters were similar in controls and Hg treatments (Table 1). Also C content (%) in the leaves was similar in controls and Hg treatments. However, stomatal conductance (gs) and leaf carbon isotope discrimination (Δ13C) were significantly decreased in plants exposed to Hg (Table 1). Shoots from barley plants exposed to Hg showed a sharp decrease in total N content (on a dry matter basis) compared to shoots of control plants (Table 1). In roots, the total N content was similar in all treatments. The down-regulation of transcripts encoding key enzymes of N metabolism, namely Fd-GOGAT protein, NADH-dependent glutamate synthase, glutamine synthetase, ferredoxin-nitrite reductase (EC 1.7.7.1) and nitrate transporters, was shown in our microarray analysis of roots grown in Hg. In Fig. 2, transcripts of down regulated enzymes are shown in red, whereas transcripts of up regulated enzymes are shown in blue. Fig. 2 Open in new tabDownload slide MapMan metabolism overview maps showing differences in transcript levels between Hg-treated barley roots and controls. log2 ratios for average transcript abundance on the basis of 3 independent replicates of Affymetrix Barley1 GeneChip normalized gene expression data of Hg-treated barley roots versus control roots were calculated. The resulting file was loaded into MapMan Image Annotator module to generate the metabolism overview map. On the logarithmic color scale ranging from −4.5 to 4.5, dark blue represents at least a 6-fold higher gene expression and red at least a 6-fold lower expression in Hg-exposed roots. In the microarray technique only transcripts are revealed (shown in Table S1, ESI†), and thus squares, which correspond to transcripts (RNA) appear colored. Gray circles are shown in the absence of metabolite information. General microarray analysis of roots exposed to Hg and controls We studied the expression of 22 840 genes present in the Affymetrix Barley Microchip in roots of barley seedlings grown in the absence of Hg (control) and under the highest of the two Hg concentrations (M2) assayed. Around 47 and 49% of all genes were detected in Hg-exposed roots and in control plants, respectively. Hg-treated roots showed a total of 1466 genes (Table S1, ESI†) with altered expression signals in comparison to controls (P < 0.05). Cluster analysis (Fig. 3) of expression signals from all probes showing significant differences between treated and control plants clearly separated all three biological replicates of the Hg treatment (M2) from the three biological replicates of control roots. This is a good indicator of the reproducibility of our microchips (Fig. 3). Fig. 3 Open in new tabDownload slide Agglomerative cluster of microarray data obtained in several Hg treatments. Cluster includes control (Control 1–3) and Hg-exposed roots (Hg 1–3) in three replicates using genes with significant altered expression in the comparison of both treatments. The number of significant clusters is indicated (1, 2 and 3). Changes in gene expression often indicate coordinated changes in the expression of genes involved in a particular function. We applied MapMan to our results and found that the following eight hierarchical categories of genes (‘BINs’) showed significantly altered gene expression based on the Wilcoxon rank sum test (Table 2) when comparing roots exposed to Hg with control roots: cell wall (13 genes); nitrogen metabolism (4 genes); amino acid metabolism (55 genes); secondary metabolism (55 genes); biotic and abiotic stresses (74 genes); miscellaneous enzyme families (135); DNA synthesis/chromatin structure, repair and unspecified (17 genes); and cell organization, division, cycle and vesicle transport (21 genes). A general overview of the transcripts involved in the main metabolic pathways showing altered gene expression in roots exposed to Hg is given in Fig. 2, while stress response genes are shown in Fig. 4. Moreover, several transcripts involved in ion transport and binding showed differential expression (Table 3). In order to validate the results of the microarrays, five genes showing altered expression in the microarray were also tested using RT-PCR (Table 4). Only one gene (asparaginase) was not correctly detected by both techniques. This gene demonstrated increased expression in Hg by both RT-PCR and microarray, but differences between the control and Hg treated roots only gave a statistically significant result in the microarray analysis (Table 4). Table 2 BINs (hierarchical categories of genes) and number of corresponding elements showing significant changes in microarray expression signals by the Wilcoxon rank sum test of roots exposed to HgCl2 as compared to controls. Significance corresponds to p values for the Wilcoxon test (*P < 0.05, **P < 0.005, ***P < 0.0005) Bin . Name . Significance . 10 Cell wall 13*** 12 Nitrogen metabolism 4* 13 Amino acid metabolism 55** 16 Secondary metabolism 55* 20 Stress 74*** 26 Misc. 135*** 28 DNA: synthesis/chromatin structure, repair and unspecified 21*** 31 Cell: organization, division, cycle and vesicle transport 21*** Bin . Name . Significance . 10 Cell wall 13*** 12 Nitrogen metabolism 4* 13 Amino acid metabolism 55** 16 Secondary metabolism 55* 20 Stress 74*** 26 Misc. 135*** 28 DNA: synthesis/chromatin structure, repair and unspecified 21*** 31 Cell: organization, division, cycle and vesicle transport 21*** Open in new tab Table 2 BINs (hierarchical categories of genes) and number of corresponding elements showing significant changes in microarray expression signals by the Wilcoxon rank sum test of roots exposed to HgCl2 as compared to controls. Significance corresponds to p values for the Wilcoxon test (*P < 0.05, **P < 0.005, ***P < 0.0005) Bin . Name . Significance . 10 Cell wall 13*** 12 Nitrogen metabolism 4* 13 Amino acid metabolism 55** 16 Secondary metabolism 55* 20 Stress 74*** 26 Misc. 135*** 28 DNA: synthesis/chromatin structure, repair and unspecified 21*** 31 Cell: organization, division, cycle and vesicle transport 21*** Bin . Name . Significance . 10 Cell wall 13*** 12 Nitrogen metabolism 4* 13 Amino acid metabolism 55** 16 Secondary metabolism 55* 20 Stress 74*** 26 Misc. 135*** 28 DNA: synthesis/chromatin structure, repair and unspecified 21*** 31 Cell: organization, division, cycle and vesicle transport 21*** Open in new tab Fig. 4 Open in new tabDownload slide MapMan metabolism overview maps showing differences in transcript levels of stress response genes between Hg-treated roots and controls. For further details, see the legend to Fig. 2. Table 3 Expression of transcripts related to Hg uptake, transport and accumulation in barley roots. Expression increase was calculated against controls (plants grown without Hg). Signal log ratios (SLR) are shown, using control plants as the baseline. Increased expression was identified by analysis of variance with P < 0.05 Transcript . SLR . Multidrug resistance-associated protein MRP1 [Triticum aestivum] 0.71 ABC transporter family protein 0.92 Putative potential cadmium/zinc-transporting ATPase 4 0.98 Putative ABC transporter [Arabidopsis thaliana] 1.00 ABC transporter family protein 1.04 ABC transporter family protein 1.14 ABC transporter, putative [Arabidopsis thaliana] 1.28 Putative multidrug resistance protein 1 homolog 1.50 ZIP-like zinc transporter [Thlaspi caerulescens] 1.56 Putative ABC transporter protein [Oryza sativa] 2.52 Putative MRP-like ABC transporter 2.53 Putative ABC transporter protein [Oryza sativa] 2.76 Multidrug resistance protein 1 homolog [Triticum aestivum] 4.74 Putative selenium binding protein [Oryza sativa] 4.74 Putative selenium binding protein [Oryza sativa] 4.75 Dehydrin; DHN10 [Hordeum vulgare] 4.84 Putative ABC transporter [Oryza sativa] 5.10 Dehydrin 10 [Hordeum vulgare] 5.38 Dehydrin; DHN4 [Hordeum vulgare] 5.98 ABC transporter family protein 6.19 Dehydrin 3 [Hordeum vulgare] 6.44 Dehydrin 8 – barley 6.90 Transcript . SLR . Multidrug resistance-associated protein MRP1 [Triticum aestivum] 0.71 ABC transporter family protein 0.92 Putative potential cadmium/zinc-transporting ATPase 4 0.98 Putative ABC transporter [Arabidopsis thaliana] 1.00 ABC transporter family protein 1.04 ABC transporter family protein 1.14 ABC transporter, putative [Arabidopsis thaliana] 1.28 Putative multidrug resistance protein 1 homolog 1.50 ZIP-like zinc transporter [Thlaspi caerulescens] 1.56 Putative ABC transporter protein [Oryza sativa] 2.52 Putative MRP-like ABC transporter 2.53 Putative ABC transporter protein [Oryza sativa] 2.76 Multidrug resistance protein 1 homolog [Triticum aestivum] 4.74 Putative selenium binding protein [Oryza sativa] 4.74 Putative selenium binding protein [Oryza sativa] 4.75 Dehydrin; DHN10 [Hordeum vulgare] 4.84 Putative ABC transporter [Oryza sativa] 5.10 Dehydrin 10 [Hordeum vulgare] 5.38 Dehydrin; DHN4 [Hordeum vulgare] 5.98 ABC transporter family protein 6.19 Dehydrin 3 [Hordeum vulgare] 6.44 Dehydrin 8 – barley 6.90 Open in new tab Table 3 Expression of transcripts related to Hg uptake, transport and accumulation in barley roots. Expression increase was calculated against controls (plants grown without Hg). Signal log ratios (SLR) are shown, using control plants as the baseline. Increased expression was identified by analysis of variance with P < 0.05 Transcript . SLR . Multidrug resistance-associated protein MRP1 [Triticum aestivum] 0.71 ABC transporter family protein 0.92 Putative potential cadmium/zinc-transporting ATPase 4 0.98 Putative ABC transporter [Arabidopsis thaliana] 1.00 ABC transporter family protein 1.04 ABC transporter family protein 1.14 ABC transporter, putative [Arabidopsis thaliana] 1.28 Putative multidrug resistance protein 1 homolog 1.50 ZIP-like zinc transporter [Thlaspi caerulescens] 1.56 Putative ABC transporter protein [Oryza sativa] 2.52 Putative MRP-like ABC transporter 2.53 Putative ABC transporter protein [Oryza sativa] 2.76 Multidrug resistance protein 1 homolog [Triticum aestivum] 4.74 Putative selenium binding protein [Oryza sativa] 4.74 Putative selenium binding protein [Oryza sativa] 4.75 Dehydrin; DHN10 [Hordeum vulgare] 4.84 Putative ABC transporter [Oryza sativa] 5.10 Dehydrin 10 [Hordeum vulgare] 5.38 Dehydrin; DHN4 [Hordeum vulgare] 5.98 ABC transporter family protein 6.19 Dehydrin 3 [Hordeum vulgare] 6.44 Dehydrin 8 – barley 6.90 Transcript . SLR . Multidrug resistance-associated protein MRP1 [Triticum aestivum] 0.71 ABC transporter family protein 0.92 Putative potential cadmium/zinc-transporting ATPase 4 0.98 Putative ABC transporter [Arabidopsis thaliana] 1.00 ABC transporter family protein 1.04 ABC transporter family protein 1.14 ABC transporter, putative [Arabidopsis thaliana] 1.28 Putative multidrug resistance protein 1 homolog 1.50 ZIP-like zinc transporter [Thlaspi caerulescens] 1.56 Putative ABC transporter protein [Oryza sativa] 2.52 Putative MRP-like ABC transporter 2.53 Putative ABC transporter protein [Oryza sativa] 2.76 Multidrug resistance protein 1 homolog [Triticum aestivum] 4.74 Putative selenium binding protein [Oryza sativa] 4.74 Putative selenium binding protein [Oryza sativa] 4.75 Dehydrin; DHN10 [Hordeum vulgare] 4.84 Putative ABC transporter [Oryza sativa] 5.10 Dehydrin 10 [Hordeum vulgare] 5.38 Dehydrin; DHN4 [Hordeum vulgare] 5.98 ABC transporter family protein 6.19 Dehydrin 3 [Hordeum vulgare] 6.44 Dehydrin 8 – barley 6.90 Open in new tab Table 4 Signal Log Ratios (SLR) of real time PCR and microarray data for 5 selected genes showing differential expression in the microarray data. bCEP_CB (cysteine endopeptidase precursor, CONTIG5626_S_AT); bNTF_SLN1 (nuclear transcription factor SLN1 CONTIG3135_AT); bCY_P450 (putative cytochrome P450, HV_CEb0004J20f_s_at); bGlu-Cla47 (glutathione S-transferase Cla47, CONTIG21968_AT); and bAspar (asparaginase, CONTIG8739_AT). Significant differences between each comparison were determined by analysis of variance. *(P < 0.05) and Ns (non-significant). SLRs were calculated using expression signals from the control treatment as the baseline Gene name . SLR HgCl2vs. Control . SLR (microarray) . bCEP_CB −4.16* −3.11* bNTF_SLN1 −2.60* −0.60* bCY_P450 1.52* 1.90* bGlu-Cla47 4.41* 5.05* bAspar 1.02(Ns) 1.40* Gene name . SLR HgCl2vs. Control . SLR (microarray) . bCEP_CB −4.16* −3.11* bNTF_SLN1 −2.60* −0.60* bCY_P450 1.52* 1.90* bGlu-Cla47 4.41* 5.05* bAspar 1.02(Ns) 1.40* Open in new tab Table 4 Signal Log Ratios (SLR) of real time PCR and microarray data for 5 selected genes showing differential expression in the microarray data. bCEP_CB (cysteine endopeptidase precursor, CONTIG5626_S_AT); bNTF_SLN1 (nuclear transcription factor SLN1 CONTIG3135_AT); bCY_P450 (putative cytochrome P450, HV_CEb0004J20f_s_at); bGlu-Cla47 (glutathione S-transferase Cla47, CONTIG21968_AT); and bAspar (asparaginase, CONTIG8739_AT). Significant differences between each comparison were determined by analysis of variance. *(P < 0.05) and Ns (non-significant). SLRs were calculated using expression signals from the control treatment as the baseline Gene name . SLR HgCl2vs. Control . SLR (microarray) . bCEP_CB −4.16* −3.11* bNTF_SLN1 −2.60* −0.60* bCY_P450 1.52* 1.90* bGlu-Cla47 4.41* 5.05* bAspar 1.02(Ns) 1.40* Gene name . SLR HgCl2vs. Control . SLR (microarray) . bCEP_CB −4.16* −3.11* bNTF_SLN1 −2.60* −0.60* bCY_P450 1.52* 1.90* bGlu-Cla47 4.41* 5.05* bAspar 1.02(Ns) 1.40* Open in new tab Stress response and cell protection mechanisms The microarray analysis of barley roots exposed to Hg showed that around 20% (74 probes) of the transcripts present in the genechip with altered expression were related to the ‘BIN’ category of stress (Fig. 4). 3 Discussion Plant growth, photosynthesis and water status Reduction in both shoot and root growth due to Hg exposure has been widely reported in the literature.7–10 However, the effect of Hg reducing plant growth does not seem primarily associated with a reduction in photosynthetic capacity. Thus net assimilation rates and chlorophyll fluorescence parameters indicated that the photosynthetic machinery was not affected by root exposure to Hg. This was in spite of the fact that N concentration in shoots decreased in response to Hg exposure. Previous studies have shown that Hg inhibits photosynthesis mainly through direct exposure of leaves to volatile Hg (reviewed in ref. 24 and 25). In our study, photosynthesis was not affected by Hg application to the substrate, probably because its concentration in the shoots was much lower than in the roots (Table 1). In fact, the availability of soil Hg to plants is low and there is a tendency for Hg to accumulate in roots, indicating that the roots serve as a barrier to Hg uptake.24 Therefore other factors may account for the negative effect of Hg on plant growth. The decrease in gs and Δ13C in response to Hg suggests that this treatment affects plant water status. These are all well-known responses to water stress.26,27 Even a mild water stress may lead to decreased intercellular CO2 due to stomatal closure, consequently increasing the proportion of the 13C isotope in plant tissues.27 A decrease in gs in response to Hg has been reported before28 but to the best of our knowledge there are no reports in the literature of a decrease in Δ13C in response to Hg in the substrate as shown in this work. In addition to the decreased gs and Δ13C of leaves, we also observed a reduced expression of an aquaporin gene (see Affymetrix probe set ID named Contig1216_s_at, in Table S1, ESI†) in the roots of plants exposed to Hg, which suggests some degree of water uptake limitation by roots.28 Mercury is recognized as a potent aquaporin (water channel) blocker.29–33 Further, the up-regulation of five transcripts related to the abscisic acid (ABA) biosynthesis pathway in response to Hg (Fig. 4) was observed. ABA is normally produced in roots in response to soil drying and moves to the shoot through the xylem stream to induce stomatal closure.34,35 In conclusion, decreased gs and Δ13C in shoots of plants exposed to Hg in addition to the down-regulation of an aquaporin gene and increased expression of ABA-related genes all provide evidence for a limitation of water uptake and transport. The decrease in the ratio of shoot to root biomass in response to Hg also agrees with a water stress effect. Furthermore, root suberization (as discussed below) may also play a role in decreasing the transport of water in the plant when exposed to Hg. Overall, moderate changes in water status triggered by root exposition to Hg may have major effects limiting plant growth. Water stress affects plant growth through reduced tissue expansion, cell number and carbon assimilation.36–38 Tissue expansion is loosely co-ordinated with cell division and carbon accumulation, which may have limited direct effects on growth under water deficit,38 confirming that plant growth is already affected at mild levels of water stress where photosynthesis is unaffected. Moreover, water stress strongly affects N metabolism,39 which also agrees with the lower leaf N content of plants exposed to Hg. In summary, this work shows a simultaneous reduction in stomatal conductance of leaves and their Δ13C in dry matter, a well-known and well-established relationship found in plants.27 In addition, aquaporins reduced expression in roots (limiting water uptake28) and ABA up-regulation in roots (inducing stomatal closure in leaves34,35) are further evidence of stress induced by the presence of Hg. Nitrogen and secondary metabolism A decrease in leaf N content can be due not only to the down-regulation of N assimilation transcripts in the roots but also to decreased expression of nitrate transporters and water uptake limitations. Our study agrees with previous work where nitrate reductase activity was inhibited by exposure to Hg.40 Our results also showed that several transcripts involved in amino acid degradation were up-regulated (Fig. 2). This is in accordance with ref. 41 who demonstrated that genes encoding the catabolic enzymes of amino acids responded faster to abiotic stress than those encoding biosynthetic pathways, and hence they play major regulatory roles in amino acid metabolism upon exposure to these forms of stress. Hg-induced root browning may have several possible causes. Root suberization, cell wall thickening and increased phenolic compound content are possible explanations but root browning can also be a consequence of cell death. All seem to be related one way or the other to secondary metabolism. Our microarray analysis showed that the phenylpropanoid and phenolic pathways were considerably up-regulated, particularly the lignin biosynthesis pathway, which showed several up-regulated genes under Hg treatment. Lignification of cortical cells, together with increased lignin biosynthesis, is known to occur in plants exposed to toxic concentrations of other heavy metals42–44 and also in response to Hg.45,46 Lignin is substantially hydrophobic and effectively ‘water-proofs’ the vessel walls47 and may therefore boost water uptake limitations of roots exposed to Hg. Stress response and cell protection In our study, the ‘BIN’ clustering stress responses included transcripts associated with hormone signalling (with special emphasis on ethylene and ABA), cell wall precursor synthesis and degradation, proteolysis, glutathione s-transferases, heat shock proteins, secondary metabolites and abiotic stress in general (Fig. 4). Ethylene influences a diverse array of plant growth and developmental processes, and responses to a wide variety of stress factors,34,48 and here we show an association with Hg. Transcripts involved in cell wall modification and degradation were also down-regulated in roots in the Hg treatment. Common pathways for the detoxification of xenobiotic compounds have been identified in most organisms, mediated by a group of enzymes, including: cytochrome P450, monoxygenases, UDP:glucosyltransferases, glutathione s-transferases and ATP-dependent membrane pumps. This group of genes has been recognized to be involved in transferring conjugates across membranes for excretion or sequestration generally.49–51 The genes we found to respond to Hg included at least one probe set encoding for each of these types of proteins involved in detoxification systems. The up-regulation of aldehyde dehydrogenase (ALDH) transcripts in roots exposed to Hg may also contribute to the detoxification of certain compounds induced by the presence of Hg. The ALDH superfamily metabolizes a wide variety of endogenous and exogenous aldehydes. Increased expression of ALDHs is known to improve tolerance to diverse forms of environmental stresses.52,53 Transcripts for pathogenesis-related proteins showed increased expression in Hg-exposed roots (Fig. 4). In maize leaves, pathogenesis-related proteins have been associated with aerial exposure to Hg17 but not with root exposure in Arabidopsis thaliana.15,16 These results should be compared with caution because of the different experimental and environmental conditions used. In summary, high amounts of Hg were found in roots of barley plants ‘switching on’ the expression of genes known to be associated with acclimation to several types of abiotic and biotic stresses. Mechanisms of Hg accumulation and tolerance As shown above the Hg concentration was much higher in roots compared with shoots of plants grown in the presence of Hg (Table 1). Given the amounts of Hg assayed in our experiment it seems acceptable to assume that barley can accumulate considerably high amounts of Hg in the roots. In fact, some authors have suggested barley as a potential high-biomass species for phytoremediation of heavy metals21 although in the case of Hg our results have suggested more a role of barley immobilizing Hg belowground. Increased Hg accumulation in the roots as compared to the shoots has been observed in other work; however, this is highly dependent on soil type, Hg mobility, and the degree of Hg volatilization.54,55 The presence of small but detectable amounts of Hg in the shoots can be explained by: (i) foliar absorption due to evaporation from the pots; (ii) through some degree of transportation in the xylem or (iii) both together. Moreover, Hg was found in small amounts in leaves of control plants (Table 1) suggesting that Hg may be present as a pollutant in the atmosphere and that foliar absorption can be an important process for Hg accumulation in the above-ground parts of barley. The pathway by which plants accumulate high amounts of toxic metals without major penalties in growth involves: uptake into cells, metal vacuolar sequestration, metal remobilization from the vacuole, xylem loading/unloading of metal/ligands/metal–ligand complexes and synthesis of metal ligands.56 The expression of several genes has been associated with metal accumulation by plants, but most of them are related to responses to other heavy metals rather than Hg.63 Two full-length cDNAs coding for a putative metallothionein and an auxin responsive protein were isolated and characterized in Sesbania drummondii plants57 in response to Hg exposure, suggesting that up-regulated expression of the former is likely to be involved in alleviation of Hg toxicity, whereas up-regulated expression of the latter may contribute to the survival of Sesbania plants under mercury stress. Phytochelatins associated with Hg exposure were identified in Brassica napus and considered to be involved in the cellular detoxification mechanism due to their ability to form stable metal–phytochelatin complexes,58 and in vivo phytochelatins (PCs) and their corresponding Hg–PC complexes were characterized in the roots of Hg-stressed Brassica chinensis L. plants.59 More recently it has been shown that complexation of Hg with phytochelatins is important for plant Hg tolerance in alfalfa, barley and maize.60 We have no evidence in our microarray analysis for the over expression of phytochelatin synthetase in response to Hg. The lack of conclusive results concerning over expression of phytochelatin synthetase leaves open other alternatives for Hg accumulation and detoxification. In fact, several transcripts associated with ion and metal transport were over expressed in Hg exposed roots (Table 3). For example, the over-expression of a zinc transporter transcript and a potential cadmium/zinc-transporting ATPase 4 were observed in barley roots exposed to Hg (Table 3). Zinc transporters like ZNT1 have been identified in Thlaspi arvense, known as a hyperaccumulating species,61,62 whereas cadmium/zinc-transporting ATPases have been associated with Zn and Cd detoxification.63 Metal transporting ATPases interact with metallochaperones and function in transmembrane transport of metals.64 A great number of transcripts encoding for ABC transporters (a family of transmembrane proteins that utilize the energy of adenosine triphosphate (ATP) hydrolysis) and multidrug resistance like proteins were up regulated in roots exposed to Hg as shown in Table 3. ABC proteins have important roles in the efflux pumping of Cd2+ or Cd conjugates and are possibly involved in hyperaccumulation and metal sequestration in the vacuoles.63,65 The multidrug resistance-associated protein subfamily has been shown to be involved in the intracellular sequestration of glutathione-conjugated toxins or metabolites.66,67 Increased production of PCs after exposure of plants to various heavy metals is primarily due to the enzyme's requirement for glutathione-like peptides containing blocked thiol groups for activity.68 Two transcripts for putative selenium binding proteins were highly expressed in roots exposed to Hg (see Table 3). The over expression of selenium binding proteins has been associated with Cd tolerance.69 Selenium binding proteins have been shown to bind with Cd and increase Cd accumulation in Arabidopsis.69 Many dehydrin transcripts were highly over-expressed in roots of barley plants exposed to Hg (see Table 3). Dehydrins are hydrophilic proteins that are responsive to several stresses in plants and have been associated with plant species capable of withstanding extremely high levels of dehydration.70 Although dehydrins have been hypothesized to stabilize macromolecules in stressed cells, their functions are not fully understood.71 However, there are examples in the literature that show the metal binding property of dehydrins with Fe, Co, Ni, Cu and Zn.71 The same authors also concluded that since dehydrin is a radical-scavenging protein, it might reduce metal toxicity in plant cells. Other tolerance mechanisms have been described through the expression of plant heme oxygenases (HOs) that regulate biosynthesis of phytochrome and which, in turn, influences photo-acceptance and photo-morphogenesis.72 The same study has also demonstrated that plant HOs also regulate many other physiological processes including responses to environmental stimuli. In summary, while several transcripts in our transcriptome analysis of roots exposed to Hg were associated with metal transport, this transport seems to occur only within the root tissues because very small concentrations of Hg were found in barley shoots (Table 3). Hg immobilization was also suggested by the over expression of transcripts involved in detoxification, metal sequestration in the vacuoles (ABC and multidrug resistance proteins) and transcripts for proteins with metal binding properties (dehydrins). Moreover, limitations to water uptake and transport may prevent Hg transport across the plant. Even when this is not the main mechanism of excluding Hg, it may help to prevent Hg accumulation in leaves and stems and further damage to the photosynthetic apparatus. Another important conclusion refers to the similarities of gene expression between plant responses to Hg and other heavy metals (e.g. Zn). We may take advantage of these similarities when pyramiding genes to improve bioaccumulation of several heavy metals at the same time. 4 Conclusion This study provides a comprehensive (physiological and molecular) assessment of how barley seedlings may react when exposed to high levels of Hg in the substrate. Barley can accumulate substantial amounts of Hg in the roots, whereas very small amounts are transported to the aerial part of the plant. This pattern of accumulation prevents damage to the leaf photosynthetic machinery, but still affects plant growth, particularly of shoots. Low Hg transport to the shoots can be at least partially explained by limitations of water uptake and transport preventing the further transport of Hg to the aboveground parts of the plant. Evidence for such limitations is shown by: (i) decreased leaf stomatal conductance and carbon isotope discrimination; (ii) down regulation of an aquaporin transcript and (iii) increased expression of ABA related transcripts. Hg immobilization in the roots was further evidenced by the over expression of several transcripts involved in metal sequestration in the vacuoles (ABC proteins and multidrug resistance proteins) and transcripts for proteins with metal binding properties (dehydrins). This small mobility of Hg to the aboveground parts of the plant prevents the use of barley for bioremediation proposes, but still, barley can be considered as an important Hg bioaccumulator, eventually immobilizing soil Hg in the roots. Overall, this study illustrates the complexity of mechanisms involved in plant responses to Hg exposure of the roots. 5 Experimental Plant material and growth conditions Barley (Hordeum vulgare L. cv. Graphic) seeds with similar weight, shape and size were germinated in Petri dishes for two days in the dark, and later transferred to a hydroponic system where the plants were grown for 15 days under different levels of Hg. The experimental design consisted of three levels of Hg with three replicates each, and fully randomized. Each replicate consisted of a two-pot system: a bottom pot, containing 300 mL of half-strength Hoagland solution with either 0 μM, 500 μM or 1000 μM HgCl2, and a top 1 L pot filled with sand where three barley seedlings were planted. A cotton string was hanging from the top into the bottom pots, allowing the solutions to be absorbed by the plant as needed. The total amount of HgCl2 available (w/w; HgCl2/sand) to the plant roots was 0 μg g−1 (control), 20 μg g−1 (M1) or 40 μg g−1 (M2). Nevertheless, actual concentrations were probably somewhat lower due to Hg volatilization. According to ref. 73 estimated losses in soils can be around 711 ng m−2 h−1, which in our experiment would represent around 3 μg per pot. The electrical conductivity was similar in both Hg and control solutions (1.1 ± 0.3 dS m−1), showing that an osmotic effect due to the addition of HgCl2 in the concentration range used here was negligible. Daily means of temperature, relative humidity and maximum irradiance in the greenhouse throughout the experiment were 16 °C, 45% and 378 W m−2, respectively. At harvest, one plantlet per pot (i.e. three plantlets per treatment) was sampled, immediately frozen in liquid nitrogen, lyophilized, shoot and roots dry weight recorded and the shoot to root ratio calculated. These samples were further used to analyze total N and C contents and carbon isotope discrimination. The rest of the plantlets were sampled and the entire root systems were separated from leaves, both washed with de-ionized water and immediately frozen in liquid N and kept at −80 °C until use for RNA extractions and Hg analysis. Leaf gas exchange and chlorophyll fluorescence Before harvesting, a portable infrared gas analyzer (LI-6400 system, Li-Cor Inc., Lincoln, NB, USA) fitted with a Leaf Chamber Fluorometer (6400-40) was used to simultaneously measure leaf gas exchange and chlorophyll fluorescence in plants from the three treatments. Measurements were performed on the last fully expanded leaf of three biological replicates per treatment. The gas exchange parameters measured were: light saturated net CO2 assimilation rate (Asat) and stomatal conductance (gs). These measurements were performed at 1200 μmol photons m−2 s−1 of PPFD (with 10% blue light), at a temperature of 25 °C and at 360 μmol mol−1 of CO2. Modulated chlorophyll fluorescence measurements allowed estimation of the relative quantum yield of photosystem II (ΦPSII), given by (Fm′ − Fs)/Fm′, the efficiency of excitation energy of capture by open PSII reaction centres (Fv′/Fm′) and the photochemical quenching (qp). The maximum quantum yield of PSII (Fv/Fm), given by [(Fm − F0)/Fm], was determined in dark-adapted leaves for 30 min.74 Mercury content Shoot and root samples were ground in liquid nitrogen. Then, approximately 200 mg of fresh weight per sample was digested overnight at 90 °C in tightly closed Teflon reactors using a mixture of HNO3 and H2O2 1 : 1 vol. The next day, 20 mL of Milli-Q deionized water was then added together with a concentration of 2% rhodium. Digestions were diluted when necessary in 1% HNO3. Mercury content was determined in duplicate by Inductively Coupled Plasma Mass Spectrometry(ICP-MS) using a Perkin Elmer apparatus model Elan-6000 (Waltham, Massachusetts, USA). Results were expressed as μg Hg per g of dry weight. C/N contents and C isotope analyses Lyophilized samples of root and shoots from control and Hg-exposed plants were ground into a fine powder and total N and C contents (% dry matter) were measured by elemental analysis (EA1108, Series 1, Carlo Erba Strumentazione, Milan, Italy). Three different plants per treatment were analyzed. The same elemental analyzer coupled to an isotope ratio mass spectrometer (Delta C, Finnigan Mat, Bremen, Germany), operating in a continuous flow mode, was used to determine the 13C/12C ratios (R) of leaf samples. Results were expressed as δ13C values, using secondary standards (polyethylene (IAEA C7), graphite (USGS24) and sucrose (IAEA-C6) calibrated against Vienna Pee Dee Belemnite calcium carbonate (VPDB)) with an analytical precision of 0.1‰ as: δ13C = (RsampleRstandard)−11 The carbon isotope discrimination (Δ13C) of leaves was then calculated from δ13Ca and δ13Cp27 as: Δ13C = (δ13Ca−δ13Cp)/[1 + (δ13Cp/1000)]2 where δ13Ca and δ13Cp refer to air and the plant carbon isotope compositions, respectively. δ13C of CO2 air within the greenhouse was −11.3‰.75 C/N content analysis and C isotope measurements of both plant material and CO2 air were performed at the facilities of the University of Barcelona. Microarray processing and analysis For all experiments, Affymetrix Genechips from the Barley Genome Array were used (Affymetrix, Santa Clara, CA, USA). These represented 22 840 genes.76 Total RNA was extracted from entire roots of control and M2 plants with Trizol reagent (Invitrogen Life Technologies, Paisley, UK) in three biological replicates (i.e. individual plants) per treatment and further purified with the RNeasy Mini Kit (Qiagen GmbH, Hilden, Germany) following the instructions provided by the supplier (Affymetrix, Santa Clara, CA, USA). All procedures were developed in the Progenika, SA Medplant Genetics facilities (Derio, Spain). After visual observation of each chip, the quality of the hybridization mixes was evaluated on the basis of the spike controls and the relationship 3′/5′ of housekeeping genes. The spike controls applied consisted of BioB, BioC, BioD and Cre. Housekeeping controls were probes for constitutively expressed genes, namely glyceraldehyde-3-phosphate dehydrogenase, α-tubulin and actin. The 3′ and 5′ regions were used to check for the integrity of the synthesized cRNA. Details of the procedures are included in S1 (ESI†). Using the Affymetrix GCOS 1.1 (Affymetrix, Santa Clara, CA, USA), all the arrays were scaled using an average intensity of 200. All signals recorded in each chip were used to calculate the 50 percentile, and the signal intensity of each sequence was then divided by the 50 percentile of all measures in that specific chip. The median of each set of probes in the 3 replicates of each experimental unit was calculated. The signals of each set of probes in all chips were then divided by the median. Normalized data in each chip were subsequently filtered to avoid control sequences and sequences with hybridization signals near the average background. Present (P) sequences were then selected only when they were detected as P in at least 2 of the 3 arrays in each experimental unit. Changes in expression between two experimental units were calculated and their magnitudes expressed as the fold change (FC). To calculate FC, all the data in each comparison between two experimental units were normalized using the mean of the 3 arrays assigned to the baseline experimental conditions. The normal distribution of gene expression corresponding to all treatment comparisons was graphically evaluated, thereby showing the expected bell-shaped layout. Differences in transcript abundance were expressed as FCs, which were calculated as the ratio of signal values in different treatments. Signal Log Ratio (SLR) corresponds to log2 FC. Analysis of variance was performed with GeneSpring v7.1 software (Agilent Technologies, Orlando, FL, USA) and significant changes between the two experimental units were accepted with P < 0.05. MapMan was used here to display all expression data on the diagrams of metabolic pathways or other processes.77 The program MapMan was originally developed to display Arabidopsis thaliana gene expression in a functional context by classifying genes into hierarchical categories (called ‘BINs’). Barley genes included in the Barley1 Gene Chips76 were recently included in MapMan (for details see ref. 78) thereby allowing the application of this software to our results. The data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus79 and are accessible through GEO Series accession number GSE15295 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE15295). Real time RT-PCR The same RNA samples were used in the microarray and real time RT-PCR. Five genes showing differential expression were selected from the microarray data (Table S2, ESI†): one involved in protein fate, cysteine endopeptidase precursor (CONTIG5626_S_AT); a nuclear transcription factor SLN1 (CONTIG3135_AT); two genes involved in cellular detoxification: putative cytochrome P450 (HVSMEA0013F14R2_AT), and glutathione s-transferase Cla47 (CONTIG21968_AT); and an asparaginase, (CONTIG8739_AT) involved in N metabolism. Further details on Blast and the sequences of these five targeted genes are provided in S2 (ESI†). Real-Time RT-PCR assays were performed with the 7900HT Fast Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) using Power SYBR Green PCR Master Mix (Applied Biosystems). For all amplifications using SYBR green, the melting curve consisted of only one peak. The relative expression of target genes from the samples was calculated using the absolute quantitation method, which included normalization to the expression of 14-3-3-LIKE PROTEIN B (14-3-3B) pirT04406 14-3-3b protein – barley gene (endogenous control gene), and showed similar expression for all treatments in the microarray analysis. In this study, efficiency values were measured using the CT slope method (following Applied Biosystems specifications). CT values are fractional cycle numbers where amplification fluorescence levels reach a fixed threshold, i.e. exceeds the background level. Specific primers were designed using Primer Express Software v2.5 (Applied Biosystems) and details are shown in Table S2 (ESI†). Additional details of the results and procedures for the qPCR are provided in S3 and S4 (ESI†). Primer sequences and sizes are described in S5 (ESI†). Other statistical analysis Analysis of variance was performed following the generalized linear model procedure (SAS, 2004 Institute Inc., Cary, NC, USA) to calculate the effects of the Hg treatment using a fully randomized design. Acknowledgements We thank Cristina Caldelas for sampling and handling materials contaminated with Hg. We acknowledge the University of California San Diego, Center for AIDS Research Genomics Core Laboratory (Director, Dr Christopher Woelk; Grant number, 5P30 AI36214) and the San Diego Veterans Medical Research Foundation in this work for generating the RT-PCR data. We also acknowledge support from MERCURY, a research project funded by the Directorate-General for Research of the European Commission. References G. Kelman Environ. Pract. , 2004 , 6 , 101 – 104 . Crossref Search ADS N. E. Selin and H. Selin Rev. Eur. Int. Environ. Law , 2006 , 15 , 258 – 269 . Crossref Search ADS I. Devai , R. D. Delaune, G. Devai, C. Aradi, S. Gori, A. S. Nagy and Z. Talas J. 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Lash Nucleic Acids Res. , 2002 , 30 , 207 – 210 . Crossref Search ADS PubMed Footnotes † Electronic supplementary information (ESI) available. See DOI: 10.1039/c3mt00084b © The Royal Society of Chemistry 2013 This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) © The Royal Society of Chemistry 2013
TI - Molecular and physiological mechanisms associated with root exposure to mercury in barley
JF - Metallomics
DO - 10.1039/c3mt00084b
DA - 2013-08-21
UR - https://www.deepdyve.com/lp/oxford-university-press/molecular-and-physiological-mechanisms-associated-with-root-exposure-BY6SGXeiSp
SP - 1305
EP - 1315
VL - 5
IS - 9
DP - DeepDyve
ER -