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Convergence of ubiquitylation and phosphorylation signaling in rapamycin-treated yeast cells.

Iesmantavicius V, Weinert BT, Choudhary C - Mol. Cell Proteomics (2014)

Bottom Line: We found that proteome, phosphorylation, and ubiquitylation changes converged on the Rsp5-ubiquitin ligase, Rsp5 adaptor proteins, and Rsp5 targets.Furthermore, we found that permeases and transporters, which are often ubiquitylated by Rsp5, were biased for reduced ubiquitylation and reduced protein abundance.Collectively, these data reveal new insights into the global proteome dynamics in response to rapamycin treatment and provide a first detailed view of the co-regulation of phosphorylation- and ubiquitylation-dependent signaling networks by this compound.

View Article: PubMed Central - PubMed

Affiliation: From the ‡Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3, 2200 Copenhagen, Denmark.

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The rapamycin-regulated proteome.A, identification of significantly regulated proteins. The column chart shows the distribution of SILAC ratios comparing rapamycin-treated cells (1 h) to control cells. A cutoff for significantly up- or down-regulated proteins was determined using two standard deviations from the median of the distribution. Proteins that were significantly up- or down-regulated are marked in red and blue, respectively. B, functional annotation of the rapamycin-regulated proteome. The bar chart shows the fraction of regulated proteins that were associated with GO terms that were significantly overrepresented among the down-regulated (blue) or up-regulated (red) proteins. Significance (p) was calculated with hypergeometric test.
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Figure 2: The rapamycin-regulated proteome.A, identification of significantly regulated proteins. The column chart shows the distribution of SILAC ratios comparing rapamycin-treated cells (1 h) to control cells. A cutoff for significantly up- or down-regulated proteins was determined using two standard deviations from the median of the distribution. Proteins that were significantly up- or down-regulated are marked in red and blue, respectively. B, functional annotation of the rapamycin-regulated proteome. The bar chart shows the fraction of regulated proteins that were associated with GO terms that were significantly overrepresented among the down-regulated (blue) or up-regulated (red) proteins. Significance (p) was calculated with hypergeometric test.

Mentions: In order to provide an in-depth proteomic analysis of rapamycin-treated yeast cells, we sought to quantify changes in protein abundance. Furthermore, by determining the protein abundance in rapamycin-treated yeast, we were able to more accurately quantify changes occurring at PTM levels by correcting changes in PTM abundance for changes in protein abundance. In total, 3590 proteins were quantified with at least two ratio counts, of which 2578 were observed in all three biological replicates (Fig. 1B and supplemental Table S2). PTM changes were corrected for changes in protein abundance if possible; otherwise the uncorrected PTM changes were used for further analysis. SILAC ratio changes were significantly correlated between experimental replicates at both time points, and the correlation increased at the 3-h time point when the proteome was more substantially regulated (supplemental Figs. S1A and S1B). Proteins whose SILAC ratios deviated more than two standard deviations (δ) from the median at the 1-h time point were considered as significantly regulated upon rapamycin treatment. Applying these criteria, we found that 77 and 253 proteins were significantly up-regulated and 69 and 147 proteins were significantly down-regulated after 1 h and 3 h of rapamycin treatment, respectively (Fig. 2A and supplemental Table S2). To further validate the quantitative MS findings, we verified protein abundance changes in three proteins via immunoblot analysis (supplemental Fig. S1C). Protein abundance was significantly increased for proteins encoded by genes that were previously shown (46) to be up-regulated by rapamycin treatment (supplemental Fig. S1D). However, down-regulated gene expression was not associated with decreased protein abundance, suggesting that the reduced protein abundances observed in our study might have been resulted through a post-transcriptional mechanism. GO enrichment analysis (Fig. 2B) showed enrichment for terms that were consistent with the ability of rapamycin to mimic nutrient deprivation. Proteins with increased abundance were associated with the terms “cellular response to stress” and “cellular amino acid biosynthetic process.” Nearly one-third of the proteins with decreased abundance were associated with the term “integral to membrane,” suggesting a specific reduction in membrane-associated proteins.


Convergence of ubiquitylation and phosphorylation signaling in rapamycin-treated yeast cells.

Iesmantavicius V, Weinert BT, Choudhary C - Mol. Cell Proteomics (2014)

The rapamycin-regulated proteome.A, identification of significantly regulated proteins. The column chart shows the distribution of SILAC ratios comparing rapamycin-treated cells (1 h) to control cells. A cutoff for significantly up- or down-regulated proteins was determined using two standard deviations from the median of the distribution. Proteins that were significantly up- or down-regulated are marked in red and blue, respectively. B, functional annotation of the rapamycin-regulated proteome. The bar chart shows the fraction of regulated proteins that were associated with GO terms that were significantly overrepresented among the down-regulated (blue) or up-regulated (red) proteins. Significance (p) was calculated with hypergeometric test.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4125731&req=5

Figure 2: The rapamycin-regulated proteome.A, identification of significantly regulated proteins. The column chart shows the distribution of SILAC ratios comparing rapamycin-treated cells (1 h) to control cells. A cutoff for significantly up- or down-regulated proteins was determined using two standard deviations from the median of the distribution. Proteins that were significantly up- or down-regulated are marked in red and blue, respectively. B, functional annotation of the rapamycin-regulated proteome. The bar chart shows the fraction of regulated proteins that were associated with GO terms that were significantly overrepresented among the down-regulated (blue) or up-regulated (red) proteins. Significance (p) was calculated with hypergeometric test.
Mentions: In order to provide an in-depth proteomic analysis of rapamycin-treated yeast cells, we sought to quantify changes in protein abundance. Furthermore, by determining the protein abundance in rapamycin-treated yeast, we were able to more accurately quantify changes occurring at PTM levels by correcting changes in PTM abundance for changes in protein abundance. In total, 3590 proteins were quantified with at least two ratio counts, of which 2578 were observed in all three biological replicates (Fig. 1B and supplemental Table S2). PTM changes were corrected for changes in protein abundance if possible; otherwise the uncorrected PTM changes were used for further analysis. SILAC ratio changes were significantly correlated between experimental replicates at both time points, and the correlation increased at the 3-h time point when the proteome was more substantially regulated (supplemental Figs. S1A and S1B). Proteins whose SILAC ratios deviated more than two standard deviations (δ) from the median at the 1-h time point were considered as significantly regulated upon rapamycin treatment. Applying these criteria, we found that 77 and 253 proteins were significantly up-regulated and 69 and 147 proteins were significantly down-regulated after 1 h and 3 h of rapamycin treatment, respectively (Fig. 2A and supplemental Table S2). To further validate the quantitative MS findings, we verified protein abundance changes in three proteins via immunoblot analysis (supplemental Fig. S1C). Protein abundance was significantly increased for proteins encoded by genes that were previously shown (46) to be up-regulated by rapamycin treatment (supplemental Fig. S1D). However, down-regulated gene expression was not associated with decreased protein abundance, suggesting that the reduced protein abundances observed in our study might have been resulted through a post-transcriptional mechanism. GO enrichment analysis (Fig. 2B) showed enrichment for terms that were consistent with the ability of rapamycin to mimic nutrient deprivation. Proteins with increased abundance were associated with the terms “cellular response to stress” and “cellular amino acid biosynthetic process.” Nearly one-third of the proteins with decreased abundance were associated with the term “integral to membrane,” suggesting a specific reduction in membrane-associated proteins.

Bottom Line: We found that proteome, phosphorylation, and ubiquitylation changes converged on the Rsp5-ubiquitin ligase, Rsp5 adaptor proteins, and Rsp5 targets.Furthermore, we found that permeases and transporters, which are often ubiquitylated by Rsp5, were biased for reduced ubiquitylation and reduced protein abundance.Collectively, these data reveal new insights into the global proteome dynamics in response to rapamycin treatment and provide a first detailed view of the co-regulation of phosphorylation- and ubiquitylation-dependent signaling networks by this compound.

View Article: PubMed Central - PubMed

Affiliation: From the ‡Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3, 2200 Copenhagen, Denmark.

Show MeSH
Related in: MedlinePlus