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The transcriptional response in human umbilical vein endothelial cells exposed to insulin: a dynamic gene expression approach.

Di Camillo B, Sanavia T, Iori E, Bronte V, Roncaglia E, Maran A, Avogaro A, Toffolo G, Cobelli C - PLoS ONE (2010)

Bottom Line: Pathway-based enrichment analysis revealed "Electron Transport Chain" significantly enriched.Results were validated on genes belonging to "Electron Transport Chain" pathway, using quantitative RT-PCR.As far as we know, this is the first systematic study in the literature monitoring transcriptional response to insulin in endothelial cells, in a time series microarray experiment.

View Article: PubMed Central - PubMed

Affiliation: Information Engineering Department, University of Padova, Padova, Italy.

ABSTRACT

Background: In diabetes chronic hyperinsulinemia contributes to the instability of the atherosclerotic plaque and stimulates cellular proliferation through the activation of the MAP kinases, which in turn regulate cellular proliferation. However, it is not known whether insulin itself could increase the transcription of specific genes for cellular proliferation in the endothelium. Hence, the characterization of transcriptional modifications in endothelium is an important step for a better understanding of the mechanism of insulin action and the relationship between endothelial cell dysfunction and insulin resistance.

Methodology and principal findings: The transcriptional response of endothelial cells in the 440 minutes following insulin stimulation was monitored using microarrays and compared to a control condition. About 1700 genes were selected as differentially expressed based on their treated minus control profile, thus allowing the detection of even small but systematic changes in gene expression. Genes were clustered in 7 groups according to their time expression profile and classified into 15 functional categories that can support the biological effects of insulin, based on Gene Ontology enrichment analysis. In terms of endothelial function, the most prominent processes affected were NADH dehydrogenase activity, N-terminal myristoylation domain binding, nitric-oxide synthase regulator activity and growth factor binding. Pathway-based enrichment analysis revealed "Electron Transport Chain" significantly enriched. Results were validated on genes belonging to "Electron Transport Chain" pathway, using quantitative RT-PCR.

Conclusions: As far as we know, this is the first systematic study in the literature monitoring transcriptional response to insulin in endothelial cells, in a time series microarray experiment. Since chronic hyperinsulinemia contributes to the instability of the atherosclerotic plaque and stimulates cellular proliferation, some of the genes identified in the present work are potential novel candidates in diabetes complications related to endothelial dysfunction.

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Related in: MedlinePlus

Comparison between Affymetrix and qRT-PCR.Contingency table that compares the lists of selected/not selected genes belonging to Electron Transport Chain pathway for both Affymetrix and qRT-PCR experiments. 21 of the 32 genes monitored by qRT-PCR were selected as differentially expressed from Affymetrix measurements, while 28 were selected from qRT-PCR measurements. In particular, 20 of the 21 genes selected as differentially expressed by using Affymetrix chips are also selected by qRT-PCR. However, 8 genes selected using qRT-PCR are not selected using Affymetrix chips, probably due to the better precision of qRT-PCR technology to measure low RNA concentration with respect to Affymetrix chips.
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pone-0014390-g004: Comparison between Affymetrix and qRT-PCR.Contingency table that compares the lists of selected/not selected genes belonging to Electron Transport Chain pathway for both Affymetrix and qRT-PCR experiments. 21 of the 32 genes monitored by qRT-PCR were selected as differentially expressed from Affymetrix measurements, while 28 were selected from qRT-PCR measurements. In particular, 20 of the 21 genes selected as differentially expressed by using Affymetrix chips are also selected by qRT-PCR. However, 8 genes selected using qRT-PCR are not selected using Affymetrix chips, probably due to the better precision of qRT-PCR technology to measure low RNA concentration with respect to Affymetrix chips.

Mentions: To validate Affymetrix measurements, 32 genes related to “Electron Transport Chain” pathway were monitored using qRT-PCR, as explained in Methods. As shown in Table 2, 21 of these genes were selected as differentially expressed from Affymetrix measurements, while 28 were selected from qRT-PCR measurements. The overall overlap (Figure 4) is 72%, indicating a good agreement between the two techniques. In particular, 20 of the 21 genes selected as differentially expressed by using Affymetrix chip are also selected by qRT-PCR, showing an overlap of 95%. However, 8 genes selected using qRT-PCR are not selected using Affymetrix chips, probably due to the better precision of qRT-PCR technology to measure low RNA concentration with respect to Affymetrix chips.


The transcriptional response in human umbilical vein endothelial cells exposed to insulin: a dynamic gene expression approach.

Di Camillo B, Sanavia T, Iori E, Bronte V, Roncaglia E, Maran A, Avogaro A, Toffolo G, Cobelli C - PLoS ONE (2010)

Comparison between Affymetrix and qRT-PCR.Contingency table that compares the lists of selected/not selected genes belonging to Electron Transport Chain pathway for both Affymetrix and qRT-PCR experiments. 21 of the 32 genes monitored by qRT-PCR were selected as differentially expressed from Affymetrix measurements, while 28 were selected from qRT-PCR measurements. In particular, 20 of the 21 genes selected as differentially expressed by using Affymetrix chips are also selected by qRT-PCR. However, 8 genes selected using qRT-PCR are not selected using Affymetrix chips, probably due to the better precision of qRT-PCR technology to measure low RNA concentration with respect to Affymetrix chips.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3008714&req=5

pone-0014390-g004: Comparison between Affymetrix and qRT-PCR.Contingency table that compares the lists of selected/not selected genes belonging to Electron Transport Chain pathway for both Affymetrix and qRT-PCR experiments. 21 of the 32 genes monitored by qRT-PCR were selected as differentially expressed from Affymetrix measurements, while 28 were selected from qRT-PCR measurements. In particular, 20 of the 21 genes selected as differentially expressed by using Affymetrix chips are also selected by qRT-PCR. However, 8 genes selected using qRT-PCR are not selected using Affymetrix chips, probably due to the better precision of qRT-PCR technology to measure low RNA concentration with respect to Affymetrix chips.
Mentions: To validate Affymetrix measurements, 32 genes related to “Electron Transport Chain” pathway were monitored using qRT-PCR, as explained in Methods. As shown in Table 2, 21 of these genes were selected as differentially expressed from Affymetrix measurements, while 28 were selected from qRT-PCR measurements. The overall overlap (Figure 4) is 72%, indicating a good agreement between the two techniques. In particular, 20 of the 21 genes selected as differentially expressed by using Affymetrix chip are also selected by qRT-PCR, showing an overlap of 95%. However, 8 genes selected using qRT-PCR are not selected using Affymetrix chips, probably due to the better precision of qRT-PCR technology to measure low RNA concentration with respect to Affymetrix chips.

Bottom Line: Pathway-based enrichment analysis revealed "Electron Transport Chain" significantly enriched.Results were validated on genes belonging to "Electron Transport Chain" pathway, using quantitative RT-PCR.As far as we know, this is the first systematic study in the literature monitoring transcriptional response to insulin in endothelial cells, in a time series microarray experiment.

View Article: PubMed Central - PubMed

Affiliation: Information Engineering Department, University of Padova, Padova, Italy.

ABSTRACT

Background: In diabetes chronic hyperinsulinemia contributes to the instability of the atherosclerotic plaque and stimulates cellular proliferation through the activation of the MAP kinases, which in turn regulate cellular proliferation. However, it is not known whether insulin itself could increase the transcription of specific genes for cellular proliferation in the endothelium. Hence, the characterization of transcriptional modifications in endothelium is an important step for a better understanding of the mechanism of insulin action and the relationship between endothelial cell dysfunction and insulin resistance.

Methodology and principal findings: The transcriptional response of endothelial cells in the 440 minutes following insulin stimulation was monitored using microarrays and compared to a control condition. About 1700 genes were selected as differentially expressed based on their treated minus control profile, thus allowing the detection of even small but systematic changes in gene expression. Genes were clustered in 7 groups according to their time expression profile and classified into 15 functional categories that can support the biological effects of insulin, based on Gene Ontology enrichment analysis. In terms of endothelial function, the most prominent processes affected were NADH dehydrogenase activity, N-terminal myristoylation domain binding, nitric-oxide synthase regulator activity and growth factor binding. Pathway-based enrichment analysis revealed "Electron Transport Chain" significantly enriched. Results were validated on genes belonging to "Electron Transport Chain" pathway, using quantitative RT-PCR.

Conclusions: As far as we know, this is the first systematic study in the literature monitoring transcriptional response to insulin in endothelial cells, in a time series microarray experiment. Since chronic hyperinsulinemia contributes to the instability of the atherosclerotic plaque and stimulates cellular proliferation, some of the genes identified in the present work are potential novel candidates in diabetes complications related to endothelial dysfunction.

Show MeSH
Related in: MedlinePlus