Degradation of protein translation machinery by amino acid starvation-induced macroautophagy

Abstract

Macroautophagy is regarded as a nonspecific bulk degradation process of cytoplasmic material within the lysosome. However, the process has mainly been studied by nonspecific bulk degradation assays using radiolabeling. In the present study we monitor protein turnover and degradation by global, unbiased approaches relying on quantitative mass spectrometry-based proteomics. Macroautophagy is induced by rapamycin treatment, and by amino acid and glucose starvation in differentially, metabolically labeled cells. Protein dynamics are linked to image-based models of autophagosome turnover. Depending on the inducing stimulus, protein as well as organelle turnover differ. Amino acid starvation-induced macroautophagy leads to selective degradation of proteins important for protein translation. Thus, protein dynamics reflect cellular conditions in the respective treatment indicating stimulus-specific pathways in stress-induced macroautophagy.

Keywords: SILAC; autophagy; degradation; mass spectrometry; protein turnover; proteomics.

Figure 1.

Induction of macroautophagy. (A) Accumulation of autophagosomes. MCF7-eGFP-LC3B cells were left untreated, AA, Glc starved, or treated with Rap (100 nM) for 24 h. Stimulus-dependent accumulation of autophagosomes was visualized by translocation of eGFP-LC3B into dotted structures. Nuclei were stained with DAPI. Scale bar: 10 µm. (B) Quantification of autophagosomes. Autophagosomes were counted in a minimum of 50 cells as shown in (A). Average autophagosome numbers ± SD are depicted. (C) Macroautophagic flux analysis using eGFP-LC3B-II. Cells were treated as in (A) and, in addition, ConA (2 nM) was added as indicated. Samples were normalized to cell number and eGFP-LC3B-II bands of ConA-treated samples were analyzed relative to respective untreated samples by western blot. Right panel depicts quantification (n = 3). (D) Macroautophagic flux analysis using SQSTM1. Samples were treated and analyzed as in (C). (E) Inhibition of MTOR. Phosphorylation levels of RPS6KB1 were monitored using a Thr389 phosphosite-specifc antibody (upper lane). Lower lane shows loading control. Right panel depicts quantification (n = 3). *: p < 0.05; **: p < 0.01; ***: p < 0.001, unpaired T test.

Figure 2.

Autophagosome turnover analyzed by fluorescence microscopy. (A) Original and segmented images. MCF7-mRFP-GFP-LC3B cells were treated as in Figure 1 and images of GFP (green), RFP (red) and DAPI (blue) were acquired after 2, 12 and 24 h. An example of 15 merged z-stacks (100x) is shown (upper panel). The lower panel shows the segmented objects. (B) Principal component analysis. The lines for each condition represent the trajectory connecting the average values at each time point (the open circle indicates the untreated condition). AA starvation had the most pronounced effects, followed by Rap treatment and Glc starvation. (C) Accumulation of GFP. All treatments led to an accumulation of GFP as indicated by object intensity (KS test p < 0.001 with Bonferroni correction). (D) Accumulation of RFP. Whereas AA starvation led to strong accumulation of RFP intensity, Rap had only a moderate effect. Glc starvation did not change RFP intensity (KS test p < 0.001 with Bonferroni correction). (E) Autophagosome turnover. The ratio of GFP:RFP object intensity can be used as a surrogate for autophagosome turnover. AA starvation and Rap treatment led to increased turnover. Glc starvation had no effect (KS test p < 0.001 with Bonferroni correction). (F) Autophagosome localization. Autophagosome localization and turnover T between plasma (pm) and nuclear (nuc) membrane is depicted using GFP:RFP ratios. A 2D histogram of the proportion of LC3B-containing organelles with a given localization and GFP:RFP ratio is shown on a log scale. The Y-axis depicts the distance between nuclear and plasma membrane, 0 being at the nuclear membrane and 1 at the plasma membrane. Color indicates the proportion of organelles, with red indicating a high proportion (see color scale). AU, arbitrary units.

Figure 3.

Protein turnover in macroautophagy. (A) Experimental outline to determine protein turnover changes in macroautophagy. Cells were fully labeled with “heavy” SILAC AA before 7-h or 24-h pulses under different treatments, and control conditions were performed with “light” SILAC AA. Cells were lysed, proteins separated by SDS-PAGE and in-gel digested with trypsin. Resulting peptide mixtures were analyzed by LC-MS/MS. Peptide ratios of light:heavy represent turnover values of respective proteins during 7 h or 24 h and reflect synthesis as well as degradation changes. (B) Histograms of protein turnover rates in 7-h stimulations. SILAC ratios were normalized by cell growth to determine proliferation-independent protein turnover rates. Rates were binned and upper values are indicated. The red line indicates the average turnover rate under control conditions (17%) in 7 h. (C) Histograms of protein turnover rates in 24-h stimulations. Data were analyzed as in (B). The red line indicates the average turnover rate under control conditions (52%) in 24 h. (D) k-means cluster analysis of protein turnover values. SILAC ratios representing turnover rates of 2 biologic replicates each were averaged, log2 transformed and z-score normalized. Clusters are indicated by numbers. Selected, significant enriched GO terms and keywords are indicated (BH corrected p < 0.05). (E) Turnover rates of ribosomal proteins decrease during active macroautophagy. Average turnover rates of 46 proteins of the 60S large ribosomal subunit (RPL) and 27 proteins of the 40S small ribosomal subunit (RPS) are depicted. Error bars indicate standard deviations. *: p < 0.05; **: p < 0.01; ***: p < 0.001, unpaired T test.

Figure 4.

Protein degradation by macroautophagy analyzed by pcSILAC. (A) pcSILAC protein degradation assay. Cells are combined 1:1, lysed, separated by SDS-PAGE and proteins in-gel digested with trypsin. Peptides are analyzed by LC-MS/MS. Relative protein degradation rates are determined by quantifying “medium” to “heavy” signal intensities of corresponding peptides. (B) Correlation of pcSILAC data and western blot analysis. Cells were treated as in (A) and protein synthesis was inhibited with 1 µM cycloheximide. Protein abundance was analyzed by western blot (Fig. S11). SILAC and western blot ratios of treated versus control cells were log2 transformed and plotted. (C-D) Degradation of autophagy marker proteins. pcSILAC data of the 2 autophagy marker proteins MAP1LC3B and SQSTM1 (C) is compared with protein degradation analysis by western blot (D) using cycloheximide-treated cells (n = 4 for LC3 and n = 3 for SQSTM1). The red line indicates degradation under control conditions. 3MA blocks macroautophagy-dependent protein degradation. Error bars represent standard deviations of replicate measurements, or peptide variability in the case of single identifications. (E) k-means cluster analysis of protein degradation values. SILAC ratios representing degradation rates of 2 biologic replicates each were averaged, log2 transformed and z-score normalized. Clusters are indicated by numbers. Selected, significant enriched GO terms and keywords are indicated (BH corrected p < 0.05). *: p < 0.05; **: p < 0.01; ***: p < 0.001, unpaired t test.

Figure 5.

Degradation of protein translation machinery by amino acid-starvation induced macroautophagy. (A) Degradation of the large ribosomal subunit (RPL). Shown is the average degradation value of 39 components of the RPL. Only in the case of AA starvation is 3-MA able to block degradation. Error bars indicate standard deviation. (B) Degradation of the small ribosomal subunit (RPS). Shown is the average degradation value of 27 components of the RPS. Especially in the case of AA starvation 3-MA is able to block degradation. Error bars indicate standard deviation. (C) Degradation of the EIF3 (eukaryotic translation initiation factor 3). Shown is the average degradation value of 11 components of the EIF3 complex. Only in the case of AA starvation is 3-MA able to partially block degradation. Error bars indicate standard deviation. (D) Degradation relative to SQSTM1. Degradation rates (panel A-C, and E) relatively normalized to respective SQSTM1 degradation are depicted. Error bars indicate standard deviation. (E) Degradation of tRNA ligases by AA starvation-induced macroautophagy. Shown are average degradation values of tRNA ligases (n = 2). The amino acid sensor LARS, and to a minor extent IARS, are spared from degradation. Error bars indicate standard deviations. The red line indicates degradation under control conditions. (F) Quantification of protein abundances of LARS and NARS. Protein abundances of LARS and NARS after 24 h of amino acid starvation were quantified relative to untreated control conditions using SILAC-based MS (n = 2) and western blot (WB) analysis (n = 5). Whereas NARS abundance decreases relative to control cells, LARS abundance increases. *: p < 0.05; **: p < 0.01; ***: p < 0.001, unpaired t test.