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Systematic quantitative analysis of ribosome inventory during nutrient stress

Abstract

Mammalian cells reorganize their proteomes in response to nutrient stress through translational suppression and degradative mechanisms using the proteasome and autophagy systems1,2. Ribosomes are central targets of this response, as they are responsible for translation and subject to lysosomal turnover during nutrient stress3,4,5. The abundance of ribosomal (r)-proteins (around 6% of the proteome; 107 copies per cell)6,7 and their high arginine and lysine content has led to the hypothesis that they are selectively used as a source of basic amino acids during nutrient stress through autophagy4,7. However, the relative contributions of translational and degradative mechanisms to the control of r-protein abundance during acute stress responses is poorly understood, as is the extent to which r-proteins are used to generate amino acids when specific building blocks are limited7. Here, we integrate quantitative global translatome and degradome proteomics8 with genetically encoded Ribo–Keima5 and Ribo–Halo reporters to interrogate r-protein homeostasis with and without active autophagy. In conditions of acute nutrient stress, cells strongly suppress the translation of r-proteins, but, notably, r-protein degradation occurs largely through non-autophagic pathways. Simultaneously, the decrease in r-protein abundance is compensated for by a reduced dilution of pre-existing ribosomes and a reduction in cell volume, thereby maintaining the density of ribosomes within single cells. Withdrawal of basic or hydrophobic amino acids induces translational repression without differential induction of ribophagy, indicating that ribophagy is not used to selectively produce basic amino acids during acute nutrient stress. We present a quantitative framework that describes the contributions of biosynthetic and degradative mechanisms to r-protein abundance and proteome remodelling in conditions of nutrient stress.

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Fig. 1: Reduction in r-protein abundance during nutrient stress is largely autophagy-independent.
Fig. 2: Density, synthesis and dilution of r-proteins in single cells using Ribo–Halo.
Fig. 3: Global translatome and degradome analysis during nutrient stress.
Fig. 4: Analysis of r-protein homeostasis in response to single amino acid perturbations.

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Data availability

All the mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE repository (http://www.proteomexchange.org/): dataset 1 (related to Supplementary Table 1; PXD017852, PXD017853); dataset 2 (related to Supplementary Table 2; PXD018252); dataset 3 (related to Supplementary Table 3; PXD017857, PXD018158); dataset 4 (related to Supplementary Table 4; PXD017856, PXD017855); dataset 5 (related to Supplementary Table 5; PXD017858, PXD017851); dataset 6 (related to Supplementary Table 6; PXD017861, PXD017860, PXD017859). Source data are provided with this paper. Full gel data for immunoblots are provided in Supplementary Fig. 1. All datasets generated within this study are available online, and the reagents are available from the corresponding author on request. Source data are provided with this paper.

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Acknowledgements

This work was supported by the National Institutes of Health (grants R37NS083524, RO1AG011085 and RO1GM095567 to J.W.H. and grant RO1GM132129 to J.A.P.). We acknowledge the Nikon Imaging Center (Harvard Medical School) for imaging assistance. We thank S. Gruver and M. Kirschner for providing MoxiGo II access and training.

Author information

Authors and Affiliations

Authors

Contributions

H.A., A.O. and J.W.H. conceived the study. H.A., A.O. and M.K. performed all experiments. J.A.P. provided mass spectrometry expertise. The paper was written by H.A., A.O. and J.W.H.

Corresponding author

Correspondence to J. Wade Harper.

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Competing interests

J.W.H. is a founder and consultant for Caraway Therapeutics and a consultant for X-Chem, Inc.

Additional information

Peer review information Nature thanks Kris Gevaert, Suresh Subramani and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Reduction of r-proteins during nutrient stress is not discernible by immunoblotting methods regardless of autophagy.

a, Schematic of the ribosome analysis pipeline. bd, (top panels) Volcano plots (-Log10 p-value versus Log2 ratio Tor1/UT) for 293T cells (n = 8029 proteins), ATG7−/− (n = 8373 proteins) or RB1CC1−/− (n = 8332 proteins) (b), HEK293 cells (n = 7531 proteins), ATG5−/− (n = 7504 proteins) (c), or HCT116 cells (n = 3779 proteins), ATG5−/− (n = 3761 proteins) or RB1CC1−/− (n = 3671 proteins) (d). n = 3 (UT); 4 (Tor1) biologically independent samples. P values were calculated by two-sided Welch’s t-test (adjusted for multiple comparisons); for parameters, individual P values and q values, see Supplementary Table 1. Green dots represent r-proteins. Data for 293T cells are from ref. 12. Histograms below the individual volcano plots show the mean ± s.d. of relative abundance of autophagy adaptors with or without nutrient deprivation. n = 3 (UT) or n = 4 (−AA and Tor1) biologically independent samples. U, untreated; A, −AA; T, Tor1. Data for 293T cells are from ref. 12. e, The relative abundance changes12 for proteins located in the ER, Golgi, or the ribosome in 293T cells treated as in b are plotted as a violin plot (n = 340, 349, 343, 340, 349, 343, 87, 89, 86, 87, 89, 86, 72, 75, 70, 72, 75, and 70 proteins, from left to right). R-protein abundance change is not affected by autophagy unlike other vesicular organelles. The violin curves represent the distribution and density of the indicated dataset (Centre-line: median; Limits: minima and maxima). f, Plots of relative abundance of individual r-protein in HEK293 cells upon either 10h of amino acid withdrawal (left) or Tor1 treatment (right). 39 r-proteins with less than ± 10% error range for every condition. Mean ± s.d. for n = 3 (UT) or n = 4 (−AA and Tor1) biologically independent samples. g, 293T cells with or without ATG7 or RB1CC1 were either left untreated, subjected to amino acid withdrawal (10h) or treated with Tor1 (10h) and whole cell extracts immunoblotted for the indicated proteins. h, HCT116 cells with or without ATG5 or RB1CC1 were treated as indicated, and whole cell extracts immunoblotted for the indicated proteins. ik, Extracts from the indicated cells (30, 15, 7.5 or 3.75 μg) were immunoblotted with the indicated antibodies (i, j). The signal intensity for the indicated r-proteins as a function of quantity loaded was measured using Odyssey (k), showing no indication of signal saturation and no detectable difference between cells with or without active autophagy. Related to Fig. 1. The experiments shown in gj were repeated more than three times independently and showed similar results. For gel source data, see Supplementary Fig. 1.

Source Data

Extended Data Fig. 2 Generation of Ribo–Halo reporters and extensive titration assays for quantification.

a, The Halotag7 protein (referred to here as ‘Halo’) was endogenously tagged at the C terminus of RPL29 or RPS3 as the indicated r-proteins contain solvent-exposed C termini and are located far from the peptide exit tunnel based on the structure of an 80S complex. (PDB: 5AJ0). b, c, Gene editing of HCT116, HEK293 and 293T cells using CRISPR-Cas9 to fuse Halo with the C termini of RPS3 and RPL29. Homozygous incorporation of Halo was confirmed by genotyping (b). Extracts from the indicated cells were subjected to immunoblotting with RPS3 (c, left) or RPL29 (c, right). Protein translation efficiency of wild-type and Halo knock-in cells were compared using puromycin incorporation assay (c, bottom). d, Immunoblotting of WT or RPS3-Halo 293T cell lysates after nutrient stress, confirming no detectable difference between the two cell lines in response to mTOR inhibition. The full immunoblot is shown in Extended Data Fig. 9i. eg, Halo-ligand titration assays with the indicated incubation time were performed using flow cytometry analysis (e, f) or in-gel fluorescence analysis (g) for the labelling saturation. In f, background signal from free Halo-ligand was measured using WT HCT116 cells in comparison to RPS3-Halo, confirming that the free ligand does not contribute to the observed fluorescence signal. h, HCT116 RPS3-Halo cells were incubated with 250 nM Halo-TMR ligand for 1h, washed for indicated numbers by incubating cells in ligand free medium for 20 min each time, followed by 17-h prolonged incubation in ligand free medium. i, Extracts from the RPS3-Halo HCT116 cells (20, 15, 10 or 5 μg) treated with the indicated Halo ligands were subjected to in-gel fluorescence analysis. The fluorescence signal intensity of each lane was directly proportional to the loading amount. We noted that R110 fluorophore was excited by epi-green excitation (520-545 nm) and detected in 577-613 nm. We subtracted this bleed-through signal for TMR quantification. j, Measurement of the effect of Tor1 on cell size with HCT116 RPS3-Halo (left) and RPL29-Halo (right) using Coulter Principle-based cell measurements. k, Cell proliferation assay. HCT116 RPS3-Halo and RPL29-Halo cells were grown in rich medium or Tor1 (200 nM) containing medium for 12, 16 and 24 h. The data estimates around 16-h cell division rate for untreated cells, and around 24-h cell division rate for Tor1 treated cells. Mean ± s.d. for n = 4 biologically independent experiments. l, Ratio of pre-existing to newly synthesized RPL29-Halo per cell plotted against cell populations as a frequency histogram (left). Average from the triplicate experiments plotted as a bar graph (right). Pre-existing Ribo–Halo proteins in HCT116 RPL29-Halo cells were labelled with TMR ligand (100 nM, 1 h), followed by the thorough washing and addition of 50 nM Green-ligand (also called R110-ligand). The newly synthesized RPL29-Halo was chased for 8, 16, and 24 h before flow cytometry analysis. Error bars represent s.d. See Methods for details. m, Pre-existing RPL29-Halo proteins were labelled with TMR ligand (100 nM, 1 h) in HCT116 cells, and the newly synthesized RPL29-Halo in the presence or absence of Tor1 (200 nM) were labelled with Green-ligand. The ratio of R110 to TMR signals plotted against cell populations (left), and the mean ± s.d. values from the triplicate experiments of 8, 16 and 24-h pulse chase plotted as a bar graph (right) are shown. n, In-gel fluorescence images of the cell extracts treated as in m. The same gels were then transferred to PVDF membranes for immunoblotting measurement of total RPL29 level. n = 3 biologically independent samples. o, In-gel fluorescence images of the cell extracts from 293T RPS3-Halo or HCT116 RPS3-Halo cells using the labelling strategy in m. Relative synthesis of RPS3-Halo with or without Tor1 is plotted on the right. Mean for n = 2 experiments. p, Live-cell imaging of HCT116 RPS3-Halo cells labelled with TMR (for pre-existing r-proteins) and Green (for newly synthesized r-proteins) ligands with or without Tor1 (200 nM, 24 h). Scale bar, 20 μm. q, Live-cell imaging of HCT116 RPL29-Halo cells labelled with TMR (for pre-existing r-proteins) and Green (for newly synthesized r-proteins) ligands with or without Tor1 (200 nM, 14h). Scale bar, 20 μm. r, The indicated cells were left untreated or incubated with Tor1 for 8 h before immunoblotting with the indicated antibodies. Related to Fig. 2. The experiments in d, j and pr were repeated three times independently with similar results, and b, c and ei were performed once. For gel source data, see Supplementary Fig. 1.

Source Data

Extended Data Fig. 3 Minimal contribution of ribophagy to control of r-protein synthesis and dilution by cell division in response to nutrient stress.

a, b, Histogram of normalized TMR signal in RPS3-Halo (a) and RPL29-Halo (b) HCT116 cells with or without ATG8 conjugation (ATG7 for RPS3-Halo and ATG5 for RPL29-Halo) or RB1CC1 incubated with or without 200 nM Tor1 for 14 h, followed by 1 h TMR ligand treatment and flow cytometry analysis. >3x105 and >4x103 cells were analysed, respectively. c, d, Mean ± s.d. of the triplicate data from cells treated as in a, b are plotted, respectively. e, Effect of Tor1 treatment on cell size in HCT116 RPL29-Halo WT, ATG5−/− and RB1CC1−/− cells, as measured using Coulter Principle-based cell measurements. Mean ± s.d. of the triplicate data. f, g, Ratio of pre-existing (red) to newly synthesized (green) r-proteins per cell plotted against cell populations as a frequency histogram for RPS3-Halo (f) or RPL29-Halo (g) HCT116 cells with or without ATG5, ATG7 or RB1CC1 based on the labelling scheme in Fig. 2f. h, Quantification of relative amounts of pre-existing and newly synthesized r-proteins from data in f, g. Mean ± s.d., n = 3 biologically independent experiments. i, j, HCT116 RPS3-Halo cells with or without ATG7 or RB1CC1 were left untreated or treated with Tor1 for 14h (i) and 24h (j) using the Halo tagging scheme in Fig. 2f. Extracts were subjected to SDS–PAGE and in-gel fluorescence analysis, followed by immunoblotting with the indicated antibodies. k, l, Quantification of relative amounts of pre-existing and newly synthesized r-proteins from data in i, j. Mean ± s.d., n = 3 biologically independent experiments. m, Live-cell imaging of HCT116 RPL29-Halo cells with indicated genotypes labelled with TMR (for pre-existing r-proteins) and Green (for newly synthesized r-proteins) ligands with or without Tor1 (200 nM, 14h). Scale bar, 20 μm. n, An example of gating strategy used for flow cytometry analysis. Green and Red only control experiments are shown at the bottom. Experiments in m, n were repeated more than three times independently with similar results. For gel source data, see Supplementary Fig. 1.

Source Data

Extended Data Fig. 4 Global decoding of protein translation during nutrient stress via independent AHA-TMT methods.

a, b, Total AHA incorporation levels with or without prior Methionine starvation (30 min) were compared using 293T cells grown in Met or AHA (250 μM) for the indicated duration, followed by click with TMR alkyne and in-gel fluorescence analysis (a). The quantification of duplicate experiments is shown in b. c, d, 293T cells were grown in medium with Met (250 μM) or the indicated concentration of AHA for the indicated time periods. Extracts were clicked with TMR and subjected to SDS–PAGE before in-gel TMR fluorescence analysis (c). TMR intensity was quantified in d. e, f, 293T cells grown in AHA (250 μM) with or without To1 for the indicated time periods and extracts clicked with TMR before processing as in c. The effect of Tor1 on TMR fluorescence is quantified in f. g, 293T cells were incubated with or without amino acid withdrawal or Tor1-containing medium in the presence of Met or AHA (250 μM each), as in Fig. 3c. Cell extracts were subjected to SDS–PAGE followed by immunoblotting. Three biologically independent samples are shown in the same blot. h, TMR signals in Fig. 3c. were quantified as described in Methods and plotted in top panel, and the relative TMT signal of the total biotinylated proteome in Fig. 3d. is plotted in bottom panel. Centre data are mean ± s.d. n = 1, 3, 3 and 3 biologically independent samples, from left to right for top and bottom panels. i, Translatome analysis. 293T cells were carried through the workflow in Fig. 3b with amino acid withdrawal and extracts clicked with biotin before enrichment on streptavidin and TMT-based proteomics. Plot of -Log10 p-value versus Log2 ratio −AA/untreated is shown for n = 8285 proteins. n = 3 (UT; −AA) biologically independent samples. j, Translatome plot of -Log10 p-value versus Log2 ratio −AA/Tor1 is shown (n = 8285 proteins). r-proteins skewed to the right side of the volcano plot indicates that Tor1 suppresses the translation of r-proteins more strongly than amino acid withdrawal, unlike the majority of the proteome. n = 3 (−AA; Tor1) biologically independent samples. P values in i and j were calculated by two-sided Welch’s t-test (adjusted for multiple comparisons); for parameters, individual P values and q values, see Supplementary Table 2. ko, The relative abundance of all quantified biotinylated proteins are shown in k. Proteins in individual groups are shown in lo. l: representative proteins showing over twofold more reduction in translation than the average translation in both Tor1 and −AA conditions, m: proteins with over twofold less reduction in translation than the average translation in both Tor1 and −AA conditions, n: proteins showing twofold less reduction only in Tor1 condition, with p-value (Supplementary Table 2) between Tor1 and −AA was less than 0.05. o: proteins showing twofold less reduction only in −AA condition, with p-value (Supplementary Table 2) between Tor1 and −AA was less than 0.05. n = 3 biologically independent samples per conditions (UT; −AA; Tor1). Centre data are mean ± S.E.M. pr, 293T cells lacking either ATG7 or RB1CC1 were subjected to amino acid withdrawal or Tor1 treatment for 3 h in the presence of 250 μM Met or AHA. Cell extracts were subjected to SDS–PAGE followed by immunoblotting with the indicated antibodies (p) or clicked with TMR and in-gel fluorescence analysis (q). TMR signals were quantified as described in Methods (r). Centre data are mean ± s.d. n = 1, 3, 3 and 3 biologically independent samples, from left to right. s, Correlation plot (Log2 ratio of treated/untreated) for the translatome upon either Tor1 treatment or amino acid withdrawal. Related to Fig. 3. Experiments in cf were performed once and p was performed three times independently with similar results. For gel source data, see Supplementary Fig. 1.

Source Data

Extended Data Fig. 5 Global decoding of protein degradation during nutrient stress via independent AHA-TMT methods.

a, Extracts from cells as described in Fig. 3g were subjected to immunoblotting with the indicated antibodies to demonstrate suppression of the mTOR activity by Tor1. b, Biotinylated extracts as described in Fig. 3g were subjected to immunoblotting with a fluorescent streptavidin conjugant, showing the pre-existing proteome (Streptavidin-IRdye) versus the total proteome (Revert total protein stain) in the lysates. n = 3 biologically independent samples are shown in a and b. c, Volcano plots (-Log10 p-value versus Log2 Tor1/UT 12h) for 293T WT (n = 8304 proteins), ATG7−/− (n = 8319 proteins), and RB1CC1−/− (n = 8590 proteins) cells as in Fig. 3i, but with pattern 1 proteins in Fig. 3h coloured as red dots, pattern 2 proteins coloured as green dots, and pattern 3 proteins coloured as blue dots. P values were calculated by two-sided Welch’s t-test (adjusted for multiple comparisons); for parameters, individual P values and q values, see Supplementary Table 3. n = 3 (UT; Tor1) biologically independent samples. d, Volcano plots as in c, but with autophagy related proteins coloured as indicated. Autophagy adaptors dramatically degraded upon Tor1 treatment only in WT cells are shown in the circle. e, Plots of individual ratio for AHA-labelled r-proteins using the protocol in Fig. 3g in WT, ATG7−/−, or RB1CC1−/− 293T cells. r-proteins with STDEV <0.3 for every condition are selected (n = 58 r-proteins). Centre data are mean ± s.d. from 3 biologically independent samples for each condition. f, Relative turnover rates for individual r-proteins from e, with or without mTOR inhibition have a correlation of R2~0.7 (n = 58 r-proteins). Grey dotted lines are 95% confidence intervals of the best-fit line (solid black line) result from a simple linear regression analysis. g, Volcano plots as in d, but with ER resident proteins coloured in purple. h, i, Individual ratio for n = 326 AHA-labelled ER membrane resident proteins using the protocol in Fig. 3g in WT, ATG7−/−, or RB1CC1−/− 293T cells (h) and plots for all individual ER resident proteins data points used in h (i). Centre data are mean ± s.e.m. Related to Fig. 3. For gel source data, see Supplementary Fig. 1.

Extended Data Fig. 6 Protein degradation time-course experiment during nutrient stress via AHA-TMT methods.

a, Schematic of AHA-based degradomics time-course to examine r-protein turnover during nutrient stress with or without functional autophagy. b, Lysates from 293T cells treated as in a, were subjected to SDS–PAGE followed by immunoblotting to confirm proper mTOR inhibition. c, Cell extracts were reacted with TMR alkyne for click reaction followed by in-gel fluorescence analysis. d, Click reaction yield across the replicates was confirmed indirectly. In brief, cell extracts treated as in a, were clicked with biotin alkyne followed by streptavidin capture. The proteins in the flow-through was precipitated, resuspended in 2% SDS, then clicked with TMR-alkyne. e, Patterns of protein turnover, as described in the main Fig. 3h, in the time-course experiment. mean ± s.e.m. Proteins analysed (n = 4 top; n = 6 middle and bottom) are shown below. f, Volcano plots for the indicated time (-Log10 p-value versus Log2 Tor1/UT) in 293T WT (n = 3334 proteins), ATG7−/− (n = 3351 proteins), and RB1CC1−/− (n = 3375 proteins) cells. r-proteins, red, green or blue. P values were calculated by two-sided Welch’s t-test (adjusted for multiple comparisons); for parameters, individual P values and q values, see Supplementary Table 3. g, A box plot of the individual ratio for AHA-labelled r-proteins using the protocol in a (centre line, median; box limits correspond to the first and third quartiles; whiskers, 10-90 percentiles range). n = 48 r-proteins that were quantified across WT, ATG7−/− and RB1CC1−/− 293T cells. two-sided t-test, P = 0.1514, 0.2818, 0.0005, 0.000016, 0.000051, 0.0005, 0.000001, 0.000020, 0.0105 from left to right; NS: non-significant, *P < 0.1, ***P < 0.001, ****P < 0.0001. Experiments in bd were replicated twice independently and showed similar results. For gel source data, see Supplementary Fig. 1.

Extended Data Fig. 7 Optimization of nuclear–cytosolic partitioning during nutrient stress.

a, Contribution of cytoplasmic and nuclear partitioning to net ribosome balance upon nutrient stress. b, c, Optimization of the nuclear and cytosolic fraction partitioning method using 293T cells. Side by side comparison of four previously published methods was performed. Surfactant used in method1: 1% Triton, method 2: 0.1% Triton, method 3: 0.1% NP40, method 4: 0.05% NP40. For more details on methods 1-4, see Methods. Methods 2 and 3 were further compared in c. 1: ctrl, 2: Leptomycin B (20 nM, 16h), 3: MgCl2 added in lysis buffer, 4: 2+3, 5: ctrl, 6: Leptomycin B (20 nM, 16h), 7: MgCl2 added in lysis buffer, 8: additional pipetting. d, Effect of the centrifugal velocity and duration on nuclear-cytosol partitioning is shown. 1: 13K rpm, 10sec, 2: 10K rpm, 10sec, 3: 7K rpm, 10sec, 4: 7K rpm, 30sec, 5: 5K rpm, 60sec, 6: 5K rpm, 180sec, 7: 3K rpm, 60sec, 8: 3K rpm, 180sec. e, f, Lysates collected after Tor1 treatment for 0, 1 or 3 h subjected to the optimized nuclear-cytosol partitioning, followed by immunoblotting against the indicated antibodies (e). Quantification measured by Odyssey shown in f. g, Scheme depicting strategy for quantitative analysis of changes in nuclear and cytosolic protein abundance in 293T cells in response to short period (3 h) of amino acid withdrawal. h, i, Biochemical characterization of nuclear and cytosolic 293T cell fractions in response to amino acid withdrawal. Extracts (15 μg of cytosol and nuclei) were separated by SDS–PAGE and immunoblots probed with the indicated antibodies (see Methods). j, k, Volcano plots (-Log10 p-value versus Log2 −AA/UT) for nuclear (j) or cytosolic (k) proteins (n = 9193 proteins) quantified by TMT-based proteomics. P values were calculated by two-sided Welch’s t-test (adjusted for multiple comparisons); for parameters, individual P values and q values, see Supplementary Table 4. Nuclear fraction (j) n = 3 (UT; −AA), cytosolic fraction (k) n = 2 (UT); n = 3 (−AA) biologically independent samples. l, Relative RPS6, FOXK1, FOXK2, and CAD phospho-peptides abundance quantified by TMT-based proteomics confirming strong inhibition of mTOR by Tor1. Centre data are mean ± s.d. n = 2 for UT RPS6 and CAD, and 3 for the rest. m, n, Relative abundance of proteins that translocate either from cytosol to nucleus (m) or from nucleus to cytosol (n) after 3h amino acid withdrawal, including proteins linked with nutrient dependent transcription (TFEB, MITF, TFE3 – accumulating in the nucleus), and proteins involved in ribosome assembly (PWP1, SDAD1, NVL – exported from the nucleus to the cytosol). Centre data are mean ± s.d. n = 3, 2, 3 and 3 biologically independent samples, from left to right for each indicated proteins. o, p, 293T cells were treated with −AA medium for the indicated time period, partitioned into nuclear and cytosolic fractions, followed by immunoblotting against the indicated antibodies (o). Odyssey quantification shown in p. Experiments shown in bd were performed once, e, h, i were performed more than three times independently with similar results, and o was performed twice with similar results. For gel source data, see Supplementary Fig. 1.

Source Data

Extended Data Fig. 8 Contribution of nuclear–cytosolic partitioning to r-protein abundance during nutrient stress and ribophagy flux measurement using the Ribo–Keima system.

a, Relative abundance of individual r-proteins from the 60S subunit (left) or 40S subunit (right) with the cytosol fraction in grey and the nuclear fraction in blue. (less than ± 10% error range for every replicate) Individual r-proteins that are thought to assemble onto the ribosome either late in the assembly process or specifically in the cytosol are indicated in red font. mean ± s.d. n = 2 for cytosolic fraction and 3 for nuclear fraction as shown in Extended Data Fig. 7g. b, c, Abundance of nuclear and cytosolic r-proteins after amino acid withdrawal (3 h). 60S subunits are on top (n = 38), and 40S subunits are at the bottom (n = 26). Right panels indicate the relative r-protein abundance change normalized by UT of cytosolic or nuclear fraction. mean ± s.e.m. d, −AA/UT ratio of individual r-proteins from both nuclear and cytosolic fractions collected after 3 h amino acid starvation indicates heterogenous distribution with RPS7 most strongly down regulated. n = 64, mean ± s.e.m. e, Lysates from HEK293 RPS3-Keima cells after the indicated nutrient stress were immunoblotted against anti-Keima antibody (top). Abundance ratio of the processed Keima to the intact Keima measured by Odyssey is plotted (bottom). f, Flow cytometry analysis of HEK293 RPS3-Keima cells to obtain normalization factors. To achieve a condition in which cells have 0% of the ribosomes in the lysosome, RPS3-Keima cells were treated with SAR405 for 10h and collected in pH7.2 FACS buffer. To achieve a theoretical condition in which 100% ribosomes are present in the lysosome, the cells were incubated in pH4.5 FACS buffer containing 0.1% Triton-X. We used the 561/488 ratio from these two measurements to calculate the % lysosomal ribosomes in g and h. n = 1742 cells for each. g, h, HEK293 RPS3-Keima cells were left untreated or treated with Tor1 (200 nM) in the presence or absence of SAR405 (1 μM) for 12 h. 561 nm ex to 488 nm ex Keima signal was measured by flow cytometry and plotted as either a frequency histogram (g, n = 1742 cells for each) or a bar graph (h, n = 3 biologically independent samples, mean ± s.d.). i, TMT-based quantification of endogenous RPS3 abundance in 293T WT, ATG7−/−, and RB1CC1−/− cells treated and processed as in Fig. 3g. n = 3 biologically independent samples. mean ± s.d. Experiments in e, g, h were repeated three times independently with similar results, and f was repeated once. For gel source data, see Supplementary Fig. 1.

Source Data

Extended Data Fig. 9 NUFIP1 deletion does not affect the ribosome inventory changes with nutrient stress.

a, Extracts from the 293T cells with or without NUFIP1 immunoblotted with the indicated antibodies after 10h of amino acid withdrawal, showing the same level of mTOR inhibition and r-proteins abundance regardless of the NUFIP1 deletion. Three biologically independent samples are blotted except two samples for NUFIP+/+ −AA condition. b, Volcano plot (-Log10 p-value versus Log2 ratio (NUFIP1−/−/WT)) of 293T cells with or without NUFIP1 deletion (n = 7032 proteins). P values were calculated by two-sided Welch’s t-test (adjusted for multiple comparisons); for parameters, individual P values and q values, see Supplementary Table 5. n = 3 biologically independent samples per genotype. c, Normalized TMR signal in HCT116 RPS3-Halo NUFIP1+/+ or −/− cells incubated with or without 200 nM Torin for 24 h, followed by 1 h TMR ligand treatment and flow cytometry analysis. Mean ± s.d. of the triplicate data are plotted. d, Average ratio of pre-existing to newly synthesized RPS3-Halo per cell with or without NUFIP1 plotted as a bar graph. Pre-existing Ribo–Halo proteins were labelled with TMR ligand (100 nM, 1 h), followed by the addition of 50 nM Green-ligand. n = 3 biologically independent samples. mean ± s.d. e, Live-cell imaging of indicated Ribo–Halo cells with or without NUFIP1 labelled with TMR (for pre-existing r-proteins) and Green (for newly synthesized r-proteins) ligands with or without Tor1 (200 nM, 14 h). Scale bar, 20 μm. f, Schematic description of the triple TMT-MS analysis of the whole cell lysates gathered from WT 293T or RPS3-Halo 293T cells with or without NUFIP1 after nutrient stress for 10 h. g, Lysates of cells treated as in f were immunoblotted against the indicated antibodies for quality control, showing that mTOR activity was properly inhibited in all three cell types. h, Volcano plots (-Log10 p-value versus Log2 ratio Nutrient stress/Untreated) of the cells treated as in f (WT n = 2072 proteins; RPS3-Halo n = 2105 proteins; RPS3-Halo and NUFIP1−/− n = 2241 proteins). Introducing HaloTag at the endogenous locus did not alter the mTOR inhibition nor ribosome abundance change after nutrient stress. Deletion of NUFIP1 did not show detectable difference either. P values were calculated by two-sided Welch’s t-test (adjusted for multiple comparisons); for parameters, individual P values and q values, see Supplementary Table 5. n = 3 (UT); 4 (−AA, Tor1) biologically independent samples per cell line. i, Immunoblotting of the cell lysates prepared as in f shows that introducing HaloTag at the endogenous locus did not alter the mTOR inhibition nor ribosome abundance change after nutrient stress. Deletion of NUFIP1 did not show detectable difference either, consistent with the TMT-MS analysis. j, Keima processing assay using the lysates from HEK293 RPS3-Keima WT or NUFIP−/− cells after the indicated nutrient stress. Also see Supplementary Table 5. Experiments in e were repeated twice with similar results, and g, i, j were repeated three times independently with similar results. For gel source data, see Supplementary Fig. 1.

Source Data

Extended Data Fig. 10 Systematic analysis of r-protein homeostasis in response to withdrawal of single amino acids.

a, 293T cells were treated with either Tor1 or 6-MP or were incubated in medium lacking Leu, Arg, or amino acids for the indicated times and cell extracts subjected to immunoblotting with the indicated antibodies. b, Quantification of the WB data in a and c. c, Puromycin incorporation assay after treating 293T cells with the indicated medium and time course. Immunoblotting against anti-puromycin antibody was probed using either infrared fluorophore labelled second antibody coupled with Odyssey or Horseradish peroxidase labelled second antibody coupled with ECL for comparison. d, Quantification of the relative abundance of pre-existing (red) and newly synthesized (green) RPS3-Halo in Fig. 4b. mean, n = 2. e, Cell extracted treated as indicated were analysed for either mTOR inhibition or translatome using AHA incorporation assay coupled with TMR-alkyne click. f, Time-course protein synthesis assay was performed using AHA clicked with TMR-alkyne method after the indicated nutrient stress. g, h, Cells treated as in Fig. 4c were clicked with TMR-alkyne and analysed by in-gel fluorescence signal (g). Immunoblot assays using the indicated antibodies for quality control is shown in h (top), and relative TMR signal is plotted below. Centre data are mean ± s.d. n = 1, 3, 3, 3, 3 and 3 biologically independent samples, from left to right. i, Lysates from HEK293 RPS3-Keima cells after the indicated nutrient stress were immunoblotted against antibodies for Keima or mTOR substrates (top). Abundance ratio of the processed Keima to the intact Keima is plotted (bottom). Related to Fig. 4. Experiments in a, c, g, i were repeated three times independently with similar results, and e, f, i were performed once. For gel source data, see Supplementary Fig. 1.

Source Data

Extended Data Fig. 11 Systematic decoding of r-protein homeostasis in response to purine deficiency.

a, Schematic diagram indicating the points of intersection of nucleotides availability with net ribosome production. 6-MP is an inhibitor of purine biosynthesis and blocks production of rRNAs. b, 293T cells were treated with or without Tor1, 6-MP, or -Arg medium for the indicated time duration. AHA (250 μM) was added 3 h before collecting the cells. Lysates were either immunoblotted against the indicated antibodies for mTOR signalling inhibition (bottom) or processed for TMR-click reaction for in-gel fluorescence analysis (top). c, 293T cells treated with 6-MP for the indicated time points as well as AHA (for the last three hours) were analysed for either mTOR inhibition (middle) or translatome using AHA incorporation assay coupled with TMR-alkyne click (top). Relative translation efficiency is plotted (bottom). Centre data are mean ± s.d. n = 1, 3, 3, 3 and 3 biologically independent samples, from left to right. d, 293T cells were incubated in the presence or absence of 6-MP for the indicated times, and AHA (250 μM) was added 3 h before collecting each lysate. The translatome was analysed by biotinylation of AHA-labelled proteins followed by TMT-based proteomics. A volcano plot (-Log10 p-value versus Log2 6-MP/UT) showing the translatome and individual r-proteins (in red) at three time points. P values were calculated by two-sided Welch’s t-test (adjusted for multiple comparisons); for parameters, individual P values and q values, see Supplementary Table 6. n = 1 (Neg Ctrl); n = 3 (UT, 9h); 2 (6 h, 18 h) biologically independent samples per cell line. e, Pre-existing RPL29 in HCT116 RPL29-Halo cells was labelled with TMR (red), washed and then incubated with medium containing green Halo ligand with or without 6-MP (24h). Live cells were imaged. f, HCT116 RPS3-Halo cells were subjected to 2-colour labelling as in Fig. 2f. Cells were either left untreated or incubated with 6-MP before analysis of pre-existing and newly synthesized RSP3-Halo using in-gel fluorescence signal-based quantification. Histograms show the relative abundance of pre-existing (red) and newly synthesized (green) RPS3-Halo. Centre data are mean ± s.d. n = 2, 3, 3, 3, 3, 3 and 3 biologically independent samples, from left to right for both histograms. g, Total proteome analysis of 293T cells (with or without ATG5) was performed according to the scheme (top). Volcano plots (-Log10 p-value versus Log2 6-MP/UT) for all quantified proteins (n = 8234 proteins), including individual r-proteins marked with a red dot, are shown at the bottom. P values were calculated by two-sided Welch’s t-test (adjusted for multiple comparisons); for parameters, individual P values and q values, see Supplementary Table 6. n = 3 (UT); 2 (6-MP) biologically independent samples per cell line. h, Keima processing assay using the lysates from HEK293 RPS3-Keima WT or ATG5−/− cells after 6-MP treatment (24h). Cells treated with arsenite was also blotted as a positive control, as it was previously reported to induce selective ribophagy. i, j, Analysis of ribosome concentration using biosynthetic, degradative and cell division information is shown as a simple equation in i. j, Change of ribosome concentration in response to nutrient stress using 0.2 as the degradation rate (derived from AHA-degradomics measurements), translation rates (Tr) of 0.35 derived from AHA-translatome analysis, and a cell cycle factor of 1.5 (Y = 1+t/24, t = 12 h) derived from the proliferation assay. We find that the ribosome concentration upon 12 h of Tor1 treatment [0.944*A0/V0} is comparable to the reduction in ribosomes we measured by total proteome analysis (reduction of ribosomes from ~5–8%). Summary of the systematic quantitative analysis of ribosome inventory during nutrient stress. Related to Fig. 4. Experiments in b were performed once, and e, h were repeated three times independently with similar results. For gel source data, see Supplementary Fig. 1.

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Supplementary Figure 1

Original immunoblot gel images.

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Supplementary Table 1

Total proteome for HEK293T, HEK293 and HCT116 cells with or without Tor1 or -AA treatment for 10h. Relevant to Fig. 1 and Extended Data Fig. 1.

Supplementary Table 2

AHA-derived translatome for HEK293T cells with or without Tor1 or –AA treatment for 3h. Relevant to Fig. 3 and Extended Data Fig. 4.

Supplementary Table 3

AHA-derived degradome (pulse chase) for HEK293T cells with or without Tor1 or -AA treatment. Relevant to Fig. 3 and Extended Data Figs. 5 and 6.

Supplementary Table 4

Nuclear and Cytosolic proteome abundance of HEK293T cells with or without -AA treatment for 3h. Relevant to Extended Data Figs.7 and 8.

Supplementary Table 5

Total proteome abundance for HEK293T deleted or not for NUFIP1 with or without Tor1 or -AA treatment for 10h. Relevant to Extended Data Fig. 9.

Supplementary Table 6

AHA-derived translatome for HEK293T cells with or without 3h single AA withdraw or 6-MP time course treatment and total proteome abundance upon 24h 6-MP treatment. Relevant to Extended Data Fig. 11.

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An, H., Ordureau, A., Körner, M. et al. Systematic quantitative analysis of ribosome inventory during nutrient stress. Nature 583, 303–309 (2020). https://doi.org/10.1038/s41586-020-2446-y

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