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Chemical Inhibitors-I Transcriptome PCR Array

 
Chemical Inhibitors-I Transcriptome PCR Array

The Chemical Inhibitors-I Transcriptome PCR Array is an innovative tool for identifying which pathways regulate the expression of any gene. In each well of a Transcriptome PCR Array, is a unique "transcriptome" or cDNA sample that was synthesized from a cell sample treated with a unique chemical inhibitor. Therefore, the user will screen 90 different chemical inhibitor treatments with a single qPCR reaction. The real-time PCR assay can be for any gene. Only mRNAs that can be converted to cDNA via random hexamers and oligo-dT primed reverse transcription will be tested. A change in expression of the tested gene in a specific sample reveals that the corresponding pathway activity is a regulator of that gene. This array is a collection of cDNAs derived from HeLa , HEK293 or MCF-7 cells treated with 90 chemical inhibitors.

 

Array Description Research Example How It Works Manuals & Data Analysis
 

Chemical Inhibitors-I Transcriptome PCR Array contains 90 experimental cDNA samples and 6 control samples. Each experimental cDNA sample is derived from HeLa , HEK293 or MCF-7 cells treated with a different chemical inhibitors. View the Gene Table to see the chemical inhibitors tested with this Transcriptome PCR Array.

Gene Table

 

Array Description Research Example How It Works Manuals & Data Analysis
 

Overview of Transcriptome PCR Array Protocol.

 

The Transcriptome PCR Array is comprised of a single PCR plate (chosen based on user's machine type) and data analysis software.

The user of a Transcriptome PCR Array must supply a qPCR assay that is specific for their gene-of-interest. The user may use either a SYBR® green or Probe-based assay with the Transcriptome PCR Arrays. To perform the assay the user must add qPCR Master mix and the assay specific for their gene to every well in the Transcriptome PCR Array. The user then runs the Transcriptome PCR Array through a cycling program specific for the selected gene-specific assay. The Ct values obtained from the instrument are then imported into the data analysis software so the user can identify regulators of the slected gene's expression.

The Excel-based data analysis software for Transcriptome PCR Arrays performs the ΔΔCt based fold-change calculations from uploaded raw threshold cycle data from the gene-specific real time-PCR assay. The spreadsheet delivers results in a tabular format and assists in hit selection.

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Array Description Research Example How It Works Manuals & Data Analysis
 

Identification of cellular pathways that regulate the expression of PAI-1 using SureFIND Transcriptome PCR Arrays

Introduction
Currently, research-based identification of upstream signaling events that regulate the expression of the target gene mainly involves extensive literature searches of known signal transduction networks or relies on bioinformatics predictive algorithms to identify probable regulators. Chemical Inhibitors Transcriptome PCR Arrays provide a novel experimental approach for identifying signal transduction networks that potentially regulate the endogenous level of the target gene.

Plasminogen activator inhibitor 1 (PAI-1), also called Serpin E1, is a circulating single-chain glycoprotein that belongs to the family of serine protease inhibitors called SERPINs [1]. Physiologically, PAI-1 is the major inhibitor of plasminogen activation, and its activity is tightly regulated at the transcriptional level largely by transforming growth factor (TGF)-β [1]. We employed Chemical Inhibitors Transcriptome PCR Array to perform a focused and fast screening experiment to simultaneously analyzing the contribution of multiple signaling pathways kinases, and other regulating enzymes toward PAI-1 transcriptional regulation in MCF-7 cells.

Materials and Methods

In this study we used Chemical Inhibitors SureFind Transcriptome PCR Array to identify potential regulators of PAI-1 expression in MCF-7 cells. SYBR Green qPCR assay was performed to quantify the expression of PAI-1 (gene of interest) and GAPDH (house-keeping control). Fold change in PAI-1 gene expression as a result of each specific chemical inhibitor treatment relative to DMSO treated control were calculated and normalized to GAPDH. Fold changes were converted to log2 and subjected to MAD analysis for positive hits selection.

Figure1: Cellular targets involved in regulation of PAI-1 gene expression.
Chemical Inhibitor-1 Transcriptome PCR Array was used to run SYBR Green-based qPCR assays for PAI-1 and GAPDH. PAI-1 gene expression level is expressed as Log2 fold change based on Ct calculation using GAPDH as house-keeping gene and DMSO treated sample well (VTC) as negative control.

Results

Our results show that TGF-β positively regulates PAI-1 gene expression in MCF-7 cells, validating previous findings regarding the strong connection between PAI-1 and the action of TGF-β (Fig. 1). Inhibition of TGF-β signaling by an ALK5 inhibitor VII, which specifically targets TGF-β type I receptor kinase, resulted in greater than 5-fold reduction in the level of PAI-1 mRNA. In addition to TGF-β, inhibition of Notch signaling by DAPT, which targets gamma-secretase, showed the strongest effect on PAI-1 expression, resulting in nearly 9-fold reduction in the level of PAI-1 mRNA. These findings serve as a confirmation of a previously suspected convergence of TGF-β and Notch signaling pathways [2] in a novel cellular background.

Conclusions
Chemical Inhibitors Transcriptome PCR Array identified several signaling pathways that negatively regulate PAI-1 expression including TGF-β and Notch signaling pathways, validating previous knowledge and confirming novel findings.

References

1. Binder BR, Christ G, Gruber F, Grubic N, Hufnagl P, Krebs M, Mihaly J, Prager GW. Plasminogen activator inhibitor 1: physiological and pathophysiological roles. News Physiol Sci. 2002 Apr;17:56-61.
2. Blokzijl A, Dahlqvist C, Reissmann E, Falk A, Moliner A, Lendahl U, Ibáńez CF. Cross-talk between the Notch and TGF-beta signaling pathways mediated by interaction of the Notch intracellular domain with Smad3. J Cell Biol. 2003 Nov 24;163(4):723-8.

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Array Description Research Example How It Works Manuals & Data Analysis
 

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