Lated residueMembershipEnrichmentFIG. three. Dynamics of the rapamycin-regulated phosphoproteome. A, identification of drastically
Lated residueMembershipEnrichmentFIG. three. Dynamics of the rapamycin-regulated phosphoproteome. A, identification of considerably regulated phosphorylation web pages. The histogram shows the distribution of phosphorylation web page SILAC Traditional Cytotoxic Agents Gene ID ratios for 1h rapamycincontrol (1hctrl) along with 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 sites are shown in black, and regulated internet sites are shown in blue. The numbers of down-regulated and up-regulated phosphorylation sites is indicated. B, the bar chart shows the distribution of phosphorylation internet sites into seven clusters, whereMolecular Cellular PARP3 drug Proteomics 13.-7 -6 -5 -4 -3 -2 -1 0 1 two 3 four five 6494Phosphorylation and Ubiquitylation Dynamics in TOR Signalingbehavior working with a fuzzy c-means algorithm (Figs. 3B and 3C) (40, 48). Regulated phosphorylation sites were clustered into six distinct profiles depending on the temporal behavior of these web sites. Distinct associations of GO terms inside every cluster (Fig. 3D and supplemental Figs. S2H 2M) indicated that phosphorylation internet sites with precise temporal profiles were involved within the regulation of distinct biological processes. Cluster 1 integrated sites that showed decreased phosphorylation more than the time period of our experiment. This cluster included GO terms for example “signal transduction,” “ubiquitinprotein ligase activity,” and “positive regulation of gene expression” (supplemental Fig. S2H). Consistent with this, it encompassed known regulated phosphorylation web-sites which include Thr142 on the transcriptional activator Msn4, which has been shown to decrease in response to osmotic stress (49), and Ser530 on the deubiquitylase Ubp1, a known Cdk1 substrate (50). This cluster also included quite a few other exciting proteins, which include Gcd1, the subunit on the translation initiation factor eIF2B; Pol1, the catalytic subunit with the DNA polymerase I -primase complex; Swi1, the transcription factor that activates transcription of genes expressed at the MG1 phase of the cell cycle; and Atg13, the regulatory subunit on the Atg1p signaling complex that stimulates Atg1p kinase activity and is essential for vesicle formation throughout autophagy and cytoplasm-to-vacuole targeting. In contrast, cluster 6 contained sites at which phosphorylation elevated over the time period of our experiment. This cluster was enriched in GO terms related to nutrient deprivation, including “cellular response to amino acid starvation,” “amino acid transport,” “autophagy,” and “autophagic vacuole assembly” (supplemental Fig. S2M). It integrated phosphorylation websites on proteins like Rph1, Tod6, Dot6, Stb3, and Par32, which have previously been shown to become hyperphosphorylated immediately after rapamycin treatment (51). Clusters four and five showed increases and decreases in phosphorylation, respectively, suggesting that these phosphorylation websites are possibly regulated as a consequence of alterations downstream of TOR inhibition, for example, by regulating the activity of downstream kinases and phosphatases upon rapamycin remedy. Clusters two and 3 contained websites at which the directionality of phosphorylation dynamics switched over time, suggesting that these sites may well be subject to a feedback regulation or controlled by a complicated regulatory program. IceLogo (41) was applied to analyze sequence motifs inside the regulated phosphorylation web-site clusters (Fig. 3E). TOR kinase includes a.
