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An algorithm for identifying novel targets of transcription factor families: application to hypoxia-inducible factor 1 targets.

Jiang Y, Cukic B, Adjeroh DA, Skinner HD, Lin J, Shen QJ, Jiang BH - Cancer Inform (2009)

Bottom Line: Efficient and effective analysis of the growing genomic databases requires the development of adequate computational tools.We further studied one of the potential targets, COX-2, in the biological lab; and showed that it was a biologically relevant HIF-1 target.These results demonstrate that our methodology is an effective computational approach for identifying novel HIF-1 targets.

View Article: PubMed Central - PubMed

Affiliation: Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA. yue@csee.wvu.edu

ABSTRACT
Efficient and effective analysis of the growing genomic databases requires the development of adequate computational tools. We introduce a fast method based on the suffix tree data structure for predicting novel targets of hypoxia-inducible factor 1 (HIF-1) from huge genome databases. The suffix tree data structure has two powerful applications here: one is to extract unknown patterns from multiple strings/sequences in linear time; the other is to search multiple strings/sequences using multiple patterns in linear time. Using 15 known HIF-1 target gene sequences as a training set, we extracted 105 common patterns that all occur in the 15 training genes using suffix trees. Using these 105 common patterns along with known subsequences surrounding HIF-1 binding sites from the literature, the algorithm searches a genome database that contains 2,078,786 DNA sequences. It reported 258 potentially novel HIF-1 targets including 25 known HIF-1 targets. Based on microarray studies from the literature, 17 putative genes were confirmed to be upregulated by HIF-1 or hypoxia inside these 258 genes. We further studied one of the potential targets, COX-2, in the biological lab; and showed that it was a biologically relevant HIF-1 target. These results demonstrate that our methodology is an effective computational approach for identifying novel HIF-1 targets.

No MeSH data available.


Related in: MedlinePlus

Effect of HIF-1 expression on COX-2 transcriptional activation. PC-3 prostate cancer cells were seeded into 6 well plates a day before the transfection. a) To determine whether HIF-1 activity is required for COX-2 transcriptional activation, the cells were co-transfected with COX-2 promoter luciferase reporter (PXP4/COX-2), pCMV-β-gal, and pcDNA3 vector or pcDNA3-HIF-1 dominant negative plasmid. b) To determine whether HIF-1 expression is sufficient to induce COX-2 transcriptional activation, the cells were co-transfected with the COX-2 promoter reporter, pCMV-β-gal, and pcDNA3 vector or pcDNA3-HIF-1α wild type expression plasmid. The cells were cultured for 36 h after transfection. The relative luciferase activity was determined by the ratio of luciferase/β-gal activity, and normalized to the vector control (100%). *Indicates the significant difference when the value is compared to the control (p < 0.01).
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f4-cin-07-75: Effect of HIF-1 expression on COX-2 transcriptional activation. PC-3 prostate cancer cells were seeded into 6 well plates a day before the transfection. a) To determine whether HIF-1 activity is required for COX-2 transcriptional activation, the cells were co-transfected with COX-2 promoter luciferase reporter (PXP4/COX-2), pCMV-β-gal, and pcDNA3 vector or pcDNA3-HIF-1 dominant negative plasmid. b) To determine whether HIF-1 expression is sufficient to induce COX-2 transcriptional activation, the cells were co-transfected with the COX-2 promoter reporter, pCMV-β-gal, and pcDNA3 vector or pcDNA3-HIF-1α wild type expression plasmid. The cells were cultured for 36 h after transfection. The relative luciferase activity was determined by the ratio of luciferase/β-gal activity, and normalized to the vector control (100%). *Indicates the significant difference when the value is compared to the control (p < 0.01).

Mentions: It is known that HIF-1 target genes are regulated at the transcriptional level by triggering their promoter activity. Therefore, to determine whether HIF-1 expression plays a role in COX-2 transcriptional activation, PC-3 prostate cancer cells were transfected with a COX-2 promoter reporter containing a 960-bp human COX-2 promoter with the potential HIF-1 binding site. Expression of HIF-1 dominant negative construct specifically inhibited HIF-1 activity, and inhibited the COX-2 reporter activity in a dose-dependent manner (Fig. 4a). This result indicates that HIF-1 activity is required for COX-2 transcriptional activation. In order to determine whether HIF-1 is sufficient to induce COX-2 transcriptional activation, HIF-1α expression plasmid was co-transfected with the COX-2 reporter. The expression of HIF-1α in PC-3 cells induced HIF-1 expression and COX-2 reporter activity in a dose-dependent manner (Fig. 4b). Thus, HIF-1α is also sufficient to induce COX-2 transcriptional activation. This data demonstrates that COX-2 is a functional HIF-1 target. These result further shows that our methodology is effective in identifying HIF-1 novel targets. Lab verification indicates that HIF-1 is essential in regulating COX-2 transcriptional activation.


An algorithm for identifying novel targets of transcription factor families: application to hypoxia-inducible factor 1 targets.

Jiang Y, Cukic B, Adjeroh DA, Skinner HD, Lin J, Shen QJ, Jiang BH - Cancer Inform (2009)

Effect of HIF-1 expression on COX-2 transcriptional activation. PC-3 prostate cancer cells were seeded into 6 well plates a day before the transfection. a) To determine whether HIF-1 activity is required for COX-2 transcriptional activation, the cells were co-transfected with COX-2 promoter luciferase reporter (PXP4/COX-2), pCMV-β-gal, and pcDNA3 vector or pcDNA3-HIF-1 dominant negative plasmid. b) To determine whether HIF-1 expression is sufficient to induce COX-2 transcriptional activation, the cells were co-transfected with the COX-2 promoter reporter, pCMV-β-gal, and pcDNA3 vector or pcDNA3-HIF-1α wild type expression plasmid. The cells were cultured for 36 h after transfection. The relative luciferase activity was determined by the ratio of luciferase/β-gal activity, and normalized to the vector control (100%). *Indicates the significant difference when the value is compared to the control (p < 0.01).
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC2664698&req=5

f4-cin-07-75: Effect of HIF-1 expression on COX-2 transcriptional activation. PC-3 prostate cancer cells were seeded into 6 well plates a day before the transfection. a) To determine whether HIF-1 activity is required for COX-2 transcriptional activation, the cells were co-transfected with COX-2 promoter luciferase reporter (PXP4/COX-2), pCMV-β-gal, and pcDNA3 vector or pcDNA3-HIF-1 dominant negative plasmid. b) To determine whether HIF-1 expression is sufficient to induce COX-2 transcriptional activation, the cells were co-transfected with the COX-2 promoter reporter, pCMV-β-gal, and pcDNA3 vector or pcDNA3-HIF-1α wild type expression plasmid. The cells were cultured for 36 h after transfection. The relative luciferase activity was determined by the ratio of luciferase/β-gal activity, and normalized to the vector control (100%). *Indicates the significant difference when the value is compared to the control (p < 0.01).
Mentions: It is known that HIF-1 target genes are regulated at the transcriptional level by triggering their promoter activity. Therefore, to determine whether HIF-1 expression plays a role in COX-2 transcriptional activation, PC-3 prostate cancer cells were transfected with a COX-2 promoter reporter containing a 960-bp human COX-2 promoter with the potential HIF-1 binding site. Expression of HIF-1 dominant negative construct specifically inhibited HIF-1 activity, and inhibited the COX-2 reporter activity in a dose-dependent manner (Fig. 4a). This result indicates that HIF-1 activity is required for COX-2 transcriptional activation. In order to determine whether HIF-1 is sufficient to induce COX-2 transcriptional activation, HIF-1α expression plasmid was co-transfected with the COX-2 reporter. The expression of HIF-1α in PC-3 cells induced HIF-1 expression and COX-2 reporter activity in a dose-dependent manner (Fig. 4b). Thus, HIF-1α is also sufficient to induce COX-2 transcriptional activation. This data demonstrates that COX-2 is a functional HIF-1 target. These result further shows that our methodology is effective in identifying HIF-1 novel targets. Lab verification indicates that HIF-1 is essential in regulating COX-2 transcriptional activation.

Bottom Line: Efficient and effective analysis of the growing genomic databases requires the development of adequate computational tools.We further studied one of the potential targets, COX-2, in the biological lab; and showed that it was a biologically relevant HIF-1 target.These results demonstrate that our methodology is an effective computational approach for identifying novel HIF-1 targets.

View Article: PubMed Central - PubMed

Affiliation: Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA. yue@csee.wvu.edu

ABSTRACT
Efficient and effective analysis of the growing genomic databases requires the development of adequate computational tools. We introduce a fast method based on the suffix tree data structure for predicting novel targets of hypoxia-inducible factor 1 (HIF-1) from huge genome databases. The suffix tree data structure has two powerful applications here: one is to extract unknown patterns from multiple strings/sequences in linear time; the other is to search multiple strings/sequences using multiple patterns in linear time. Using 15 known HIF-1 target gene sequences as a training set, we extracted 105 common patterns that all occur in the 15 training genes using suffix trees. Using these 105 common patterns along with known subsequences surrounding HIF-1 binding sites from the literature, the algorithm searches a genome database that contains 2,078,786 DNA sequences. It reported 258 potentially novel HIF-1 targets including 25 known HIF-1 targets. Based on microarray studies from the literature, 17 putative genes were confirmed to be upregulated by HIF-1 or hypoxia inside these 258 genes. We further studied one of the potential targets, COX-2, in the biological lab; and showed that it was a biologically relevant HIF-1 target. These results demonstrate that our methodology is an effective computational approach for identifying novel HIF-1 targets.

No MeSH data available.


Related in: MedlinePlus