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Identification of microRNA-mRNA functional interactions in UVB-induced senescence of human diploid fibroblasts.

Greussing R, Hackl M, Charoentong P, Pauck A, Monteforte R, Cavinato M, Hofer E, Scheideler M, Neuhaus M, Micutkova L, Mueck C, Trajanoski Z, Grillari J, Jansen-Dürr P - BMC Genomics (2013)

Bottom Line: In parallel, a comprehensive screen for microRNAs regulated during UVB-induced senescence was performed which identified five microRNAs that are significantly regulated during the process.We performed a comprehensive screen for UVB-regulated microRNAs in human diploid fibroblasts, and identified a network of miRNA-mRNA interactions mediating UVB-induced senescence.In addition, miR-101 and Ezh2 were identified as key players in UVB-induced senescence of HDF.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute for Biomedical Aging Research, Austrian Academy of Sciences, Rennweg 10, Innsbruck 6020, Austria. Pidder.Jansen-Duerr@uibk.ac.at.

ABSTRACT

Background: Cellular senescence can be induced by a variety of extrinsic stimuli, and sustained exposure to sunlight is a key factor in photoaging of the skin. Accordingly, irradiation of skin fibroblasts by UVB light triggers cellular senescence, which is thought to contribute to extrinsic skin aging, although molecular mechanisms are incompletely understood. Here, we addressed molecular mechanisms underlying UVB induced senescence of human diploid fibroblasts.

Results: We observed a parallel activation of the p53/p21(WAF1) and p16(INK4a)/pRb pathways. Using genome-wide transcriptome analysis, we identified a transcriptional signature of UVB-induced senescence that was conserved in three independent strains of human diploid fibroblasts (HDF) from skin. In parallel, a comprehensive screen for microRNAs regulated during UVB-induced senescence was performed which identified five microRNAs that are significantly regulated during the process. Bioinformatic analysis of miRNA-mRNA networks was performed to identify new functional mRNA targets with high confidence for miR-15a, miR-20a, miR-20b, miR-93, and miR-101. Already known targets of these miRNAs were identified in each case, validating the approach. Several new targets were identified for all of these miRNAs, with the potential to provide new insight in the process of UVB-induced senescence at a genome-wide level. Subsequent analysis was focused on miR-101 and its putative target gene Ezh2. We confirmed that Ezh2 is regulated by miR-101 in human fibroblasts, and found that both overexpression of miR-101 and downregulation of Ezh2 independently induce senescence in the absence of UVB irradiation. However, the downregulation of miR-101 was not sufficient to block the phenotype of UVB-induced senescence, suggesting that other UVB-induced processes induce the senescence response in a pathway redundant with upregulation of miR-101.

Conclusion: We performed a comprehensive screen for UVB-regulated microRNAs in human diploid fibroblasts, and identified a network of miRNA-mRNA interactions mediating UVB-induced senescence. In addition, miR-101 and Ezh2 were identified as key players in UVB-induced senescence of HDF.

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Correlation network of miR-20a/b and their high confidence target genes. We used 10 prediction tools to obtain, based on public data, candidate miRNA-mRNA target interactions and we identified high confidence targets by mRNA and miRNA expression. In positive cases, miRNA expression should show a negative correlation with the respective target gene mRNA level. We calculated Pearson correlation coefficients between miRNAs and their targets. Results of the analysis are presented here for miR-20a (A), and miR-20b (B). The color and shape of nodes are based on different node attributes available for the analyzed dataset. The red triangles, purple circles and orange diamonds in the network are indicating miRNAs, target genes, and transcription factors, respectively. Edges represent correlation between miRNAs and mRNAs, the color of the edges designate the type of interaction. Red is for positive and green is for negative correlation. Protein was isolated from UVB irradiated and control cells at the indicated time points. Protein levels were analyzed by standard Western blot for Cyclin D1 (C). Experiments were performed in triplicates, one representative experiment is shown.
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Figure 4: Correlation network of miR-20a/b and their high confidence target genes. We used 10 prediction tools to obtain, based on public data, candidate miRNA-mRNA target interactions and we identified high confidence targets by mRNA and miRNA expression. In positive cases, miRNA expression should show a negative correlation with the respective target gene mRNA level. We calculated Pearson correlation coefficients between miRNAs and their targets. Results of the analysis are presented here for miR-20a (A), and miR-20b (B). The color and shape of nodes are based on different node attributes available for the analyzed dataset. The red triangles, purple circles and orange diamonds in the network are indicating miRNAs, target genes, and transcription factors, respectively. Edges represent correlation between miRNAs and mRNAs, the color of the edges designate the type of interaction. Red is for positive and green is for negative correlation. Protein was isolated from UVB irradiated and control cells at the indicated time points. Protein levels were analyzed by standard Western blot for Cyclin D1 (C). Experiments were performed in triplicates, one representative experiment is shown.

Mentions: High confidence targets were identified for miR-20a and miR-20b encoded by the miR-17-92 cluster which is known to synergize with Myc in cancer development [26], probably through repression of p21WAF1 expression at the post-transcriptional level [27]. However, there is also evidence that miR-17-92 blocks E2F-dependent steps in the regulation of angiogenesis [28]. Our analysis confirmed a high confidence interaction between both miR-20a and miR-20b with p21WAF1 (CDKN1A), p15INK4B (CDKN2B), RUNX1, and vEGF-A (Figure 4A,B), thereby validating the analytical procedure. E2F1 and Cyclin D1 are predicted targets for both miR-20a and miR-20b. Whereas decreased expression of miR-20a/b was not correlated with altered mRNA levels of E2F1 and Cyclin D1 (Figure 4A,B), upregulation of Cyclin D1 gene expression during UVB-induced senescence was observed at the protein level (Figure 4C). Results of the bioinformatic analysis suggested several so far unreported potential targets for miR-20a and miR-20b in the context of UVB-induced senescence. Thus, DRAM, IDS, NFAT5, EGR2, CCND2, and RARB were identified as potential high confidence interactions for both miR-20a and miR-20b (Figure 4A,B). In addition, the data suggest TIMP3, ETV1, B2M, IGFBP-3, and RRAS2 as potential targets for miR-20a (Figure 4A), and TGM2, CPE, RHOJ, and SERPING1 as potential targets for miR-20b (Figure 4B).


Identification of microRNA-mRNA functional interactions in UVB-induced senescence of human diploid fibroblasts.

Greussing R, Hackl M, Charoentong P, Pauck A, Monteforte R, Cavinato M, Hofer E, Scheideler M, Neuhaus M, Micutkova L, Mueck C, Trajanoski Z, Grillari J, Jansen-Dürr P - BMC Genomics (2013)

Correlation network of miR-20a/b and their high confidence target genes. We used 10 prediction tools to obtain, based on public data, candidate miRNA-mRNA target interactions and we identified high confidence targets by mRNA and miRNA expression. In positive cases, miRNA expression should show a negative correlation with the respective target gene mRNA level. We calculated Pearson correlation coefficients between miRNAs and their targets. Results of the analysis are presented here for miR-20a (A), and miR-20b (B). The color and shape of nodes are based on different node attributes available for the analyzed dataset. The red triangles, purple circles and orange diamonds in the network are indicating miRNAs, target genes, and transcription factors, respectively. Edges represent correlation between miRNAs and mRNAs, the color of the edges designate the type of interaction. Red is for positive and green is for negative correlation. Protein was isolated from UVB irradiated and control cells at the indicated time points. Protein levels were analyzed by standard Western blot for Cyclin D1 (C). Experiments were performed in triplicates, one representative experiment is shown.
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Related In: Results  -  Collection

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Figure 4: Correlation network of miR-20a/b and their high confidence target genes. We used 10 prediction tools to obtain, based on public data, candidate miRNA-mRNA target interactions and we identified high confidence targets by mRNA and miRNA expression. In positive cases, miRNA expression should show a negative correlation with the respective target gene mRNA level. We calculated Pearson correlation coefficients between miRNAs and their targets. Results of the analysis are presented here for miR-20a (A), and miR-20b (B). The color and shape of nodes are based on different node attributes available for the analyzed dataset. The red triangles, purple circles and orange diamonds in the network are indicating miRNAs, target genes, and transcription factors, respectively. Edges represent correlation between miRNAs and mRNAs, the color of the edges designate the type of interaction. Red is for positive and green is for negative correlation. Protein was isolated from UVB irradiated and control cells at the indicated time points. Protein levels were analyzed by standard Western blot for Cyclin D1 (C). Experiments were performed in triplicates, one representative experiment is shown.
Mentions: High confidence targets were identified for miR-20a and miR-20b encoded by the miR-17-92 cluster which is known to synergize with Myc in cancer development [26], probably through repression of p21WAF1 expression at the post-transcriptional level [27]. However, there is also evidence that miR-17-92 blocks E2F-dependent steps in the regulation of angiogenesis [28]. Our analysis confirmed a high confidence interaction between both miR-20a and miR-20b with p21WAF1 (CDKN1A), p15INK4B (CDKN2B), RUNX1, and vEGF-A (Figure 4A,B), thereby validating the analytical procedure. E2F1 and Cyclin D1 are predicted targets for both miR-20a and miR-20b. Whereas decreased expression of miR-20a/b was not correlated with altered mRNA levels of E2F1 and Cyclin D1 (Figure 4A,B), upregulation of Cyclin D1 gene expression during UVB-induced senescence was observed at the protein level (Figure 4C). Results of the bioinformatic analysis suggested several so far unreported potential targets for miR-20a and miR-20b in the context of UVB-induced senescence. Thus, DRAM, IDS, NFAT5, EGR2, CCND2, and RARB were identified as potential high confidence interactions for both miR-20a and miR-20b (Figure 4A,B). In addition, the data suggest TIMP3, ETV1, B2M, IGFBP-3, and RRAS2 as potential targets for miR-20a (Figure 4A), and TGM2, CPE, RHOJ, and SERPING1 as potential targets for miR-20b (Figure 4B).

Bottom Line: In parallel, a comprehensive screen for microRNAs regulated during UVB-induced senescence was performed which identified five microRNAs that are significantly regulated during the process.We performed a comprehensive screen for UVB-regulated microRNAs in human diploid fibroblasts, and identified a network of miRNA-mRNA interactions mediating UVB-induced senescence.In addition, miR-101 and Ezh2 were identified as key players in UVB-induced senescence of HDF.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute for Biomedical Aging Research, Austrian Academy of Sciences, Rennweg 10, Innsbruck 6020, Austria. Pidder.Jansen-Duerr@uibk.ac.at.

ABSTRACT

Background: Cellular senescence can be induced by a variety of extrinsic stimuli, and sustained exposure to sunlight is a key factor in photoaging of the skin. Accordingly, irradiation of skin fibroblasts by UVB light triggers cellular senescence, which is thought to contribute to extrinsic skin aging, although molecular mechanisms are incompletely understood. Here, we addressed molecular mechanisms underlying UVB induced senescence of human diploid fibroblasts.

Results: We observed a parallel activation of the p53/p21(WAF1) and p16(INK4a)/pRb pathways. Using genome-wide transcriptome analysis, we identified a transcriptional signature of UVB-induced senescence that was conserved in three independent strains of human diploid fibroblasts (HDF) from skin. In parallel, a comprehensive screen for microRNAs regulated during UVB-induced senescence was performed which identified five microRNAs that are significantly regulated during the process. Bioinformatic analysis of miRNA-mRNA networks was performed to identify new functional mRNA targets with high confidence for miR-15a, miR-20a, miR-20b, miR-93, and miR-101. Already known targets of these miRNAs were identified in each case, validating the approach. Several new targets were identified for all of these miRNAs, with the potential to provide new insight in the process of UVB-induced senescence at a genome-wide level. Subsequent analysis was focused on miR-101 and its putative target gene Ezh2. We confirmed that Ezh2 is regulated by miR-101 in human fibroblasts, and found that both overexpression of miR-101 and downregulation of Ezh2 independently induce senescence in the absence of UVB irradiation. However, the downregulation of miR-101 was not sufficient to block the phenotype of UVB-induced senescence, suggesting that other UVB-induced processes induce the senescence response in a pathway redundant with upregulation of miR-101.

Conclusion: We performed a comprehensive screen for UVB-regulated microRNAs in human diploid fibroblasts, and identified a network of miRNA-mRNA interactions mediating UVB-induced senescence. In addition, miR-101 and Ezh2 were identified as key players in UVB-induced senescence of HDF.

Show MeSH
Related in: MedlinePlus