15 research outputs found

    MicroRNA Dysregulation in the Spinal Cord following Traumatic Injury

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    Spinal cord injury (SCI) triggers a multitude of pathophysiological events that are tightly regulated by the expression levels of specific genes. Recent studies suggest that changes in gene expression following neural injury can result from the dysregulation of microRNAs, short non-coding RNA molecules that repress the translation of target mRNA. To understand the mechanisms underlying gene alterations following SCI, we analyzed the microRNA expression patterns at different time points following rat spinal cord injury

    Interleukin 15 expression in the CNS: blockade of its activity prevents glial activation after an inflammatory injury.

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    Although reactive glia formation after neuronal degeneration or traumatic damage is one of the hallmarks of central nervous system (CNS) injury, we have little information on the signals that direct activation of resting glia. IL-15, a pro-inflammatory cytokine involved in regulating the response of T and B cells, may be also key for the regulation of early inflammatory events in the nervous system. IL-15 was expressed in the CNS, most abundantly in cerebellum and hippocampus, mainly in astrocytes and in some projection neurons. Using a rodent model of acute inflammatory injury [lipopolysaccharide (LPS) injection], we found enhanced expression of IL-15 in both reactive astroglia and microglia, soon after CNS injury. Blockade of IL-15 activity with an antibody to the cytokine, reversed activation of both glial types, suggesting that IL-15 has a major role in the generation of gliotic tissue and in the regulation of neuroimmune responses. Because IL-15 appears to modulate the inflammatory environment acutely generated after CNS injury, regulating IL-15 expression seems a clear antiinflammatory therapy to improve the outcome of neurodegenerative diseases and CNS trauma

    Apoptosis-related microRNAs with significant changes in expression in the present study.

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    <p>Expression changes, targets and references for the pro-apoptotic and anti-apoptotic microRNAs and those exhibiting dual roles are detailed. For each microRNA, the expression changes in the present study are detailed in column EC (expression changes; D corresponds to downregulation and U to upregulation at the indicated dpo).</p

    Negative correlation between microRNA and mRNA expression changes.

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    <p>Graph illustrating the relationship between the changes in microRNA and mRNA expression 7 days after injury. It clearly shows that mRNA upregulation parallels decreased microRNA expression. Numbers of upregulated and downregulated microRNA data according to the t-tests comparing the injured and sham animals at 7 days after SCI. The mRNA data correspond to the equivalent comparisons (mild plus moderately injured vs. sham at 7 dpo) from DeBiase <i>et al. </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034534#pone.0034534-DeBiase1" target="_blank">[7]</a>.</p

    Biological effects of the microRNA expression changes.

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    <p>List of the 10 Gene Ontology biological function terms that were most significantly enriched according to the targets of microRNAs with significant expression changes, according to the t-test analyses. The GSEA values were obtained using DAVID (<a href="http://david.abcc.ncifcrf.gov" target="_blank">http://david.abcc.ncifcrf.gov</a>) algorithms. Comparisons are as follow: <b>C1</b>) Comparison between CT and LS1; <b>C2</b>) CT vs LS3; <b>C3</b>) SH3 vs LS3; <b>C4</b>) CT vs LS7; <b>C5</b>) SH7 vs LS7; and <b>C6</b>) LS1 vs LS7.</p

    MicroRNAs detected at the spinal cord of different vertebrates in previous studies [6], [17], [18], [19], [20], [21], [22] but not in the present study.

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    <p>Note that no data from Liu <i>et al.</i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034534#pone.0034534-Liu1" target="_blank">[6]</a> are included in the table because some disagreements were observed among microRNAs with low expression but not among those with high expression (see supplementary <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034534#pone-0034534-t001" target="_blank">table 1</a> from Liu <i>et al.</i>).</p

    Temporal expression profiles of selected microRNAs.

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    <p>The expression levels of selected microRNAs were assessed using quantitative PCR (left columns) and compared with the corresponding microarray data (right columns) using a correlation analysis (c.c: correlation coefficient). The fold changes in the sham and injured experimental groups are with respect to the control group. The Q-PCR data were analyzed using a one-way ANOVA followed by a Tukey post-test. * = p<0.05; ** = p<0.01; *** = p<0.001.</p

    Number of microRNA expression changes following spinal cord injury.

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    <p>(A) Table showing the number of expression changes detected for the different pair comparisons performed. For each comparison, the first number (in bold type) corresponds to the number of significant changes according to t-test analyses after FDR adjustment; the second number (in regular type) corresponds to the number of significant changes according to the non-parametric Rank Product test; the third number (between brackets) corresponds to the changes found to be significant by both tests. (B) Scatterplot illustrating the changes in microRNA expression after SCI. The y-axis indicates the number of up-regulated (positive axis) and down-regulated (negative axis) microRNAs. Values were derived from the t-test analyses comparing microRNA expression levels at different times after SCI to the corresponding sham or control data.</p

    MicroRNA expression profiles after spinal cord injury.

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    <p>(A) Hierarchical cluster analysis and heat map, Euclidean distance and average linkage clustering of data from individual replicates. This analysis provides a visual ordination of the samples and genes according to their overall similarity. The colors of the heat map indicate microRNA upregulation (red) and downregulation (green). (B) PCA and scatterplot of the first two components, showing the separation of the LS7 individuals. (C) Scatterplot of the first and third components of the PCA, showing a group of LS3 samples. All analyses were based on data from the 463 microRNAs showing variable expression (IQR>0.5). PC1, PC2, and PC3 correspond to the axis determined by the first, second and third principal components of the PCA, respectively. These components are lineal combinations of the expression values for each gene optimized to capture the maximum variation of the matrix. Each consecutive component is orthonormal to the previous ones and absorbes the maximum amount of the remaining gene expression variation (AV, absorbed variation). Ls7, Ls3, Ls1, Sh1, Sh3 and Ct indicate sample type and correspond to Lesion (Ls), Sham (Sh) and control, while the numbers 1, 3, 7 indicate the sampling time after surgery.</p
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