Gene expression and sensitivity in response to copper stress in rice leaves*

Gene expression in response to Cu stress in rice leaves was quantified using DNA microarray (Agilent 22K Rice Oligo Microarray) and real-time PCR technology. Rice plants were grown in hydroponic solutions containing 0.3 (control), 10, 45, or 130 μM of CuCl2, and Cu accumulation and photosynthesis inhibition were observed in leaves within 1 d of the start of treatment. Microarray analysis flagged 305 Cu-responsive genes, and their expression profile showed that a large proportion of general and defence stress response genes are up-regulated under excess Cu conditions, whereas photosynthesis and transport-related genes are down-regulated. The Cu sensitivity of each Cu-responsive gene was estimated by the median effective concentration value (EC50) and the range of fold-changes (F) under the highest (130 μM) Cu conditions (|log2F|130). Our results indicate that defence-related genes involved in phytoalexin and lignin biosynthesis were the most sensitive to Cu, and that plant management of abiotic and pathogen stresses has overlapping components, possibly including signal transduction

Boxplots of (left panel) and log (right panel) in each functional category

The empty box indicates the interquartile (25–75%) range. Bars across the boxes represent the median value. Whiskers below and above the box indicate the range of values within 1.5 times the value of the upper or lower edge of the box. Circles represent outliers. The statistical significance of differences was tested by Dunnett's multiple comparison tests. Asterisks indicate significant differences with average values of all Cu-responsive genes (* <p><b>Copyright information:</b></p><p>Taken from "Gene expression and sensitivity in response to copper stress in rice leaves"</p><p></p><p>Journal of Experimental Botany 2008;59(12):3465-3474.</p><p>Published online 1 Aug 2008</p><p>PMCID:PMC2529235.</p><p></p

Strigolactones Modulate Cellular Antioxidant Defense Mechanisms to Mitigate Arsenate Toxicity in Rice Shoots

Metalloid contamination, such as arsenic poisoning, poses a significant environmental problem, reducing plant productivity and putting human health at risk. Phytohormones are known to regulate arsenic stress; however, the function of strigolactones (SLs) in arsenic stress tolerance in rice is rarely investigated. Here, we investigated shoot responses of wild-type (WT) and SL-deficient d10 and d17 rice mutants under arsenate stress to elucidate SLs’ roles in rice adaptation to arsenic. Under arsenate stress, the d10 and d17 mutants displayed severe growth abnormalities, including phenotypic aberrations, chlorosis and biomass loss, relative to WT. Arsenate stress activated the SL-biosynthetic pathway by enhancing the expression of SL-biosynthetic genes D10 and D17 in WT shoots. No differences in arsenic levels between WT and SL-biosynthetic mutants were found from Inductively Coupled Plasma-Mass Spectrometry analysis, demonstrating that the greater growth defects of mutant plants did not result from accumulated arsenic in shoots. The d10 and d17 plants had higher levels of reactive oxygen species, water loss, electrolyte leakage and membrane damage but lower activities of superoxide dismutase, ascorbate peroxidase, glutathione peroxidase and glutathione S-transferase than did the WT, implying that arsenate caused substantial oxidative stress in the SL mutants. Furthermore, WT plants had higher glutathione (GSH) contents and transcript levels of OsGSH1, OsGSH2, OsPCS1 and OsABCC1 in their shoots, indicating an upregulation of GSH-assisted arsenic sequestration into vacuoles. We conclude that arsenate stress activated SL biosynthesis, which led to enhanced arsenate tolerance through the stimulation of cellular antioxidant defense systems and vacuolar sequestration of arsenic, suggesting a novel role for SLs in rice adaptation to arsenic stress. Our findings have significant implications in the development of arsenic-resistant rice varieties for safe and sustainable rice production in arsenic-polluted soils

Protonema of the moss <i>Funaria hygrometrica</i> can function as a lead (Pb) adsorbent

<div><p>Water contamination by heavy metals from industrial activities is a serious environmental concern. To mitigate heavy metal toxicity and to recover heavy metals for recycling, biomaterials used in phytoremediation and bio-sorbent filtration have recently drawn renewed attention. The filamentous protonemal cells of the moss <i>Funaria hygrometrica</i> can hyperaccumulate lead (Pb) up to 74% of their dry weight when exposed to solutions containing divalent Pb. Energy-dispersive X-ray spectroscopy revealed that Pb is localized to the cell walls, endoplasmic reticulum-like membrane structures, and chloroplast thylakoids, suggesting that multiple Pb retention mechanisms are operating in living <i>F</i>. <i>hygrometrica</i>. The main Pb-accumulating compartment was the cell wall, and prepared cell-wall fractions could also adsorb Pb. Nuclear magnetic resonance analysis showed that polysaccharides composed of polygalacturonic acid and cellulose probably serve as the most effective Pb-binding components. The adsorption abilities were retained throughout a wide range of pH values, and bound Pb was not desorbed under conditions of high ionic strength. In addition, the moss is highly tolerant to Pb. These results suggest that the moss <i>F</i>. <i>hygrometrica</i> could be a useful tool for the mitigation of Pb-toxicity in wastewater.</p></div

TEM-EDX analysis of <i>F</i>. <i>hygrometrica</i> protonemal cells.

<p>(A) Control cell. (B to E) Cells treated with 0.1 mM PbCl₂. The thickness of (A) and (B) is 80 nm, and that of (C) to (E) is 150 nm. (C), (D), and (E) are views focusing on the cell wall, endoplasmic reticulum (plasmodesmata), and chloroplast, respectively. Arrows indicate the X-ray analytical areas. Magnified views of the analyzed areas are shown in the inset. cw, cell wall, ch, chloroplast, er, endoplasmic reticulum, mt, mitochondrion. Scale bars: 1 μm. (F, G, H) Energy-disperse spectroscopic spectra. (F), (G), and (H) show results of the analyses of (C), (D), and (E), respectively. Peaks marked by closed arrowheads were used for Pb identification: 2.35(Mα), 10.55(Lα1) and 10.45(Lα2), and 12.61(Lβ1) and 12.62(Lβ2) keV. Peaks highlighted by open arrowheads originated from the Cu in the sample-holding grid (8.05(Kα1) and 8.91(Kβ) keV).</p

Effects of pH on metal adsorption.

<p><i>F</i>. <i>hygrometrica</i> protonemal cells were incubated with the metal solutions at the indicated pH values, and the unbound metals in the filtrates were quantified. Adsorption rate (%) = (initial concentration − final concentration) / initial concentration × 100.</p

Adsorption of Pb to prepared a cell-wall fraction of <i>F</i>. <i>hygrometrica</i>.

<p>Aliquots of a cell-wall (CW) fraction were suspended in MQW (Mock), 1 mM PbCl₂, or 1 mM Pb(NO₃)₂. After washing with MQW, Pb was detected with rhodizonic acid staining and X-ray analysis. (A) Precipitated CW fractions in bottles after treatment. (B) Autiofluorescence image of rhodizonic acid-stained CW fraction observed with Bio Imaging Navigator with a fluorescence filter (FSX100/U-MNUA2, OLYMPUS, Japan). (C) Observation with bright field mode. (D) Spectra of X-ray analysis with an X-ray analyzer. Background peaks in mock treatment are derived from rhodizonic acid. Scale bars, 3 mm in (A), 100 μm in (B) and (C).</p