Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Synergistic effects of TOR and proteasome pathways on the yeast transcriptome and cell growth

ABSTRACT: The experiments were designed to interrogate the genetic interaction relationship between the TOR signalling pathway and the UPS-proteasome pathway in gene expression and cell growth. Yeast cells (BY4742pdr5delta) were treated with the drug vehicle, MG132 (50uM), rapamycin (200ng/ml) or both drugs. Samples in triplicates were taken at 0, 1, 2 and 3hours after treatment. Transcriptome were assayed using Affimetrixs genechips (Yeast 2).

ORGANISM(S): Saccharomyces cerevisiae

SUBMITTER: Nianshu Zhang

PROVIDER: E-MTAB-1550 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Synergistic effects of TOR and proteasome pathways on the yeast transcriptome and cell growth.

Zhang Nianshu N Quan Zhenzhen Z Rash Bharat B Oliver Stephen G SG

Open biology 20130522 5

The proteasome has been implicated in gene transcription through a variety of mechanisms. How the proteasome regulates genome-wide transcription in relation to nutrient signalling pathways is largely unknown. Using chemical inhibitors to compromise the functions of the proteasome and/or TORC1, we reveal that the proteasome and TORC1 synergistically promote the expression of de novo purine and amino acid biosynthetic genes, and restrict the transcription of those associated with proteolysis, star ...[more]

PMID: 23697803

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Project description:Background: The combination of Proteasome inhibitor with Glucocorticoid is one of the most promising antileukemic treatments. Both agents act through pluripotent signal mediators. The two types of agents inhibit key signals that are considered crucial to their effects on malignant cells. Methodology/Principal Findings: Combined use of the two reagents on the lymphoblastic leukemia cell line CCRF-CEM has a range of effects on the viability that depend on the dose and the time used. Even though both reagents are capable of enhancing cell death on the CEM cell line, no combinatorial increase in cell death is detectable, until after the first 120 hours of treatment. In contrast, there are a number of combinatorial effects on the cell cycle phase distribution of treated cells, which indicates a potential for mutual signal disruption between glucocorticoid and proteasome inhibitor at multiple levels. Microarray analysis indicates that Prednisolone and MG132 elicit highly divergent, early-response molecular signatures on this cell line. We assayed levels of the antiapoptotic protein Mcl-1 as a potential model of late, downstream target regulation by both glucocorticoid and proteasome. Synchronized use of Prednisolone with MG132 results in temporary stabilization of Mcl-1 in CEM cells. Stabilization is not the result of a common mechanism of action on the genome, as Prednisolone and MG132 elicit nonreduntant molecular signatures, and it occurs also when the cells are treated at different timepoints with either agent. Conclusions/Significance: Our results show that this glucocorticoid-resistant ALL lymphoblast line is highly sensitive to proteasome inhibitor, and suggest that the proteasome inhibitor and the glucocorticoid regulate different direct target genes. This difference in immediate targets, when the two agents are applied in combination, may lead to negative or positive interference with mechanisms regulating viability of the leukemic lymphoblast. Signal interference between glucocorticoid Prednisolone and the proteasome inhibitor MG132 is expected to occur at more than one level, resulting in complex effects on intracellular signal transduction pathways. The net result depends on the development of individual downstream effects and interactions between key signal mediators. Elucidation of the conditions of interference between glucocorticoid and proteasome targets on leukemic cell fate is expected to improve effects of applied treatment combinations. Experimental setups consisted of the three following samples obtained after 4 h treatment: control, 10nM prednisolone, 1uM prednisolone, 10uM prednisolone, 100M-NM-<M prednisolone, 700M-NM-<M prednisolone, 200nM MG132, 2M-NM-<M MG132 and 20M-NM-<M MG132. Untreated cells were used as reference.

Dataset Information

Synergistic effects of TOR and proteasome pathways on the yeast transcriptome and cell growth

Publications

Synergistic effects of TOR and proteasome pathways on the yeast transcriptome and cell growth.

Similar Datasets

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