Lated residueMembershipEnrichmentFIG. 3. Dynamics on the rapamycin-regulated phosphoproteome. A, identification of drastically
Lated residueMembershipEnrichmentFIG. 3. Dynamics of your rapamycin-regulated phosphoproteome. A, identification of significantly regulated phosphorylation sites. The histogram shows the distribution of phosphorylation web site SILAC ratios for 1h rapamycincontrol (1hctrl) and the distribution of unmodified peptide SILAC ratios (red). The cutoff for regulated phosphorylation web sites was determined based on two regular deviations in the median for unmodified peptides. Unregulated web sites are shown in black, and regulated internet sites are shown in blue. The numbers of down-regulated and up-regulated phosphorylation web pages is indicated. B, the bar chart shows the distribution of phosphorylation websites into seven clusters, whereMolecular Cellular Proteomics 13.-7 -6 -5 -4 -3 -2 -1 0 1 2 3 four 5 6494Phosphorylation and Ubiquitylation Dynamics in TOR Signalingbehavior applying a fuzzy c-means algorithm (Figs. 3B and 3C) (40, 48). Regulated phosphorylation internet sites had been clustered into six distinct profiles based on the temporal behavior of these web-sites. Distinct associations of GO terms inside each and every cluster (Fig. 3D and supplemental Figs. S2H 2M) indicated that phosphorylation websites with specific temporal profiles were involved in the regulation of various biological processes. Cluster 1 incorporated sites that showed decreased phosphorylation over the time period of our GM-CSF Protein Molecular Weight experiment. This cluster integrated GO terms such as “signal transduction,” “ubiquitinprotein ligase activity,” and “positive regulation of gene expression” (supplemental Fig. S2H). Consistent with this, it encompassed recognized regulated phosphorylation sites like Thr142 of the transcriptional activator Msn4, which has been shown to reduce in response to osmotic stress (49), and Ser530 around the deubiquitylase Ubp1, a recognized Cdk1 substrate (50). This cluster also included several other fascinating proteins, like Gcd1, the subunit of the translation initiation aspect eIF2B; Pol1, the catalytic subunit on the DNA polymerase I -primase complex; Swi1, the transcription factor that activates transcription of genes expressed in the MG1 phase of your cell cycle; and Atg13, the regulatory subunit on the Atg1p signaling complicated that stimulates Atg1p kinase activity and is expected for G-CSF Protein Source vesicle formation in the course of autophagy and cytoplasm-to-vacuole targeting. In contrast, cluster six contained web sites at which phosphorylation enhanced over the time period of our experiment. This cluster was enriched in GO terms associated to nutrient deprivation, like “cellular response to amino acid starvation,” “amino acid transport,” “autophagy,” and “autophagic vacuole assembly” (supplemental Fig. S2M). It included phosphorylation sites on proteins including Rph1, Tod6, Dot6, Stb3, and Par32, which have previously been shown to be hyperphosphorylated immediately after rapamycin therapy (51). Clusters four and five showed increases and decreases in phosphorylation, respectively, suggesting that these phosphorylation web-sites are possibly regulated as a consequence of alterations downstream of TOR inhibition, for instance, by regulating the activity of downstream kinases and phosphatases upon rapamycin treatment. Clusters two and three contained web pages at which the directionality of phosphorylation dynamics switched over time, suggesting that these sites may possibly be topic to a feedback regulation or controlled by a complicated regulatory plan. IceLogo (41) was used to analyze sequence motifs within the regulated phosphorylation web page clusters (Fig. 3E). TOR kinase features a.
