47 research outputs found

    Knockdown of Glutamate Cysteine Ligase Catalytic Subunit by siRNA Causes the Gold Nanoparticles-Induced Cytotoxicity in Lung Cancer Cells

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    <div><p>Gold nanoparticles (GNPs) have shown promising medical applications in cancer treatment involved in the regulation of intracellular redox balance. Previously, we have reported that GNPs can trigger apoptosis and necrosis in human lung cancer cells (A549) when L-buthionine-sulfoximine (BSO) was used to decrease the expression of intracellular glutathione (GSH). Herein, we investigated the cytotoxicity of GNPs toward lung cancer cells under the glutamate cysteine ligase catalytic subunit (GCLC) was silenced by siRNA. Our results showed that GNPs cause apoptosis and necrosis in cells transfected with GCLC siRNA by elevating intracellular reactive oxygen species (ROS). These findings demonstrated that the regulation of glutathione synthesis by GCLC siRNA in A549 cells can initiate the gold nanoparticles-induced cytotoxicity.</p></div

    Flow cytometry analysis of mitochondrial membrane potential in GNPs-treated cells.

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    <p>After transfected with negative control siRNA or GCLC siRNA-1, cells were treated with GNPs (20μM) for additional 72 hours then collected and stained with JC-1 in darkness at 37°C, rinsed by PBS. The fluorescence shift (red to green) of samples was measured by flow cytometry. Each bar represents the mean (±SD n = 4) of triplicate determinations. *<i>p</i><0.05, compared with negative control group.</p

    Effect of GCLC siRNA on intracellular GSH levels.

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    <p>Cytosol was isolated from cells transfected with negative control siRNA, GCLC siRNA-1, GCLC siRNA-2 and GCLC siRNA-3. The intracellular GSH levels were determined at 412 nm absorbance with a multiwell plate reader. Data represent the mean percentage of negative control (n = 3) ±SD for 4 independent experiments. *p<0.05, ** P<0.01, compared to negative control.</p

    Knockdown of glutamate cysteine ligase catalytic subunit by siRNA.

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    <p>(A) GCLC mRNA levels in A549 cells following 24 hours transfected with negative control siRNA, GCLC siRNA-1, GCLC siRNA-2 and GCLC siRNA-3. GCLC siRNA significantly decreased the GCLC mRNA levels in A549 cells. (B) Representative Western blot gel documents for GCLC and summarized data showing that efficiency of gene silencing of GCLC by siRNA. Cytosolic proteins were isolated from transfected cells. GCLC protein levels in cell extracts were measured by Western blot analysis and were normalised to β-actin expression levels. *** P<0.001, compared to negative control.</p

    Effect of GNPs on intracellular ROS levels in GCLC siRNA pretreated cells.

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    <p>Exponentially growing cells were transfected with negative control and GCLC siRNA-1 for 24 hours, following treated with GNPs (20μM), GNPs (20μM) and GSH (1mM), GNPs (20μM) and NAC (1mM). ROS levels were measured. Graphs indicate ROS (as determined by DCF) levels (%) compared with negative control cells. Each bar represents the mean (±SD n = 4) of triplicate determinations. **p<0.01</p

    GNPs induce apoptosis and necrosis in cells transfected with GCLC siRNA.

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    <p>Cells were transfected with either non-target control siRNA or GCLC-specific siRNA-1. One day later, cells were treated with GNPs (20μM), GNPs (20μM)﹢GSH (1mM) and GNPs (20μM)+NAC(1mM) for additional 72 hours. AnnexinV-FITC and PI cells were measured with flow cytometry. (A) The fluorescence pattern of AnnexinV-FITC and PI-stained A549 cells after treatment. (B) Percentages of Annexin V positive or PI positive cells for different treatments. Each bar represents the mean (±SD n = 3). **p<0.01, ***P<0.001, versus control.</p

    GNPs induce caspase activation in cells transfected with GCLC siRNA.

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    <p>Activation of caspase-3 was measured using specific antibodies by flow cytometry. Intracellular GSH was depleted by GCLC siRNA-1, after approximately 72 hours of GNPs treatment, the cells were collected, treated with 0.1% Triton X-100 and blocked with 1% BSA, then incubated with cleaved caspase-3 (Asp175) antibody (Alexa fluor 488 conjugate) for 30 minutes. The fluorescence intensity was measured by flow cytometry. Each bar represents the mean (±SD n = 4) of triplicate determinations. *<i>p</i><0.05, compared with negative control group.</p

    Real-time PCR validation of differentially expressed miRNAs supported by both Solexa sequencing and microarray.

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    <p>NA, non-aestivation; DA, deep-aestivation (n = 3 for NA and DA respectively). The RT-PCR was performed in triplicate wells for each individual sample. Bars show means ± standard deviation. “*” p<0.05; “**” p<0.01.</p

    High-Throughput Sequencing Reveals Differential Expression of miRNAs in Intestine from Sea Cucumber during Aestivation

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    <div><p>The regulatory role of miRNA in gene expression is an emerging hot new topic in the control of hypometabolism. Sea cucumber aestivation is a complicated physiological process that includes obvious hypometabolism as evidenced by a decrease in the rates of oxygen consumption and ammonia nitrogen excretion, as well as a serious degeneration of the intestine into a very tiny filament. To determine whether miRNAs play regulatory roles in this process, the present study analyzed profiles of miRNA expression in the intestine of the sea cucumber (<i>Apostichopus japonicus</i>), using Solexa deep sequencing technology. We identified 308 sea cucumber miRNAs, including 18 novel miRNAs specific to sea cucumber. Animals sampled during deep aestivation (DA) after at least 15 days of continuous torpor, were compared with animals from a non-aestivation (NA) state (animals that had passed through aestivation and returned to the active state). We identified 42 differentially expressed miRNAs [RPM (reads per million) >10, |FC| (|fold change|) ≥1, FDR (false discovery rate) <0.01] during aestivation, which were validated by two other miRNA profiling methods: miRNA microarray and real-time PCR. Among the most prominent miRNA species, miR-200-3p, miR-2004, miR-2010, miR-22, miR-252a, miR-252a-3p and miR-92 were significantly over-expressed during deep aestivation compared with non-aestivation animals. Preliminary analyses of their putative target genes and GO analysis suggest that these miRNAs could play important roles in global transcriptional depression and cell differentiation during aestivation. High-throughput sequencing data and microarray data have been submitted to GEO database.</p></div

    Common and specific sequences summary of unique sRNAs between non-aestivation (NA) and DA (deep-aestivation) states.

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    <p>Three groups are shown: those specific to NA, those specific to DA, and those that are common to both. The percentage distribution of sequences between these three groups is shown along with the number of sRNA sequences in brackets.</p