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Cited by 114Cancer-related Molecular PathwaysPI3K/AKT/mTOR signaling in cancerRNA and protein synthesis mechanisms

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p53 induces transcriptional and translational programs to suppress cell proliferation and growth

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Loayza-Puch, Fabricio, Drost, Jarno, Rooijers, Koos, Lopes, Rui, Elkon, Ran, Agami, Reuven·2013·Genome Biology
DOI 10.1186/gb-2013-14-4-r32PMC PMC4053767
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Abstract

Background: Cell growth and proliferation are tightly connected to ensure that appropriately sized daughter cells are generated following mitosis. Energy stress blocks cell growth and proliferation, a critical response for survival under extreme conditions. Excessive oncogenic stress leads to p53 activation and the induction of senescence, an irreversible state of cell-cycle arrest and a critical component in the suppression of tumorigenesis. Nutrient-sensing and mitogenic cues converge on a major signaling node, which regulates the activity of the mTOR kinase. Although transcriptional responses to energy and oncogenic stresses have been examined by many gene-expression experiments, a global exploration of the modulation of mRNA translation in response to these conditions is lacking. Results: We combine RNA sequencing and ribosomal profiling analyses to systematically delineate modes of transcriptional and translational regulation induced in response to conditions of limited energy, oncogenic stress and cellular transformation. We detect a key role for mTOR and p53 in these distinct physiological states, and provide the first genome-wide demonstration that p53 activation results in mTOR inhibition and a consequent global repression of protein translation. We confirm the role of the direct p53 target genes Sestrin1 and Sestrin2 in this response, as part of the broad modulation of gene expression induced by p53 activation. Conclusions: We delineate a bimodal tumor-suppressive regulatory program activated by p53, in which cell-cycle arrest is imposed mainly at the transcriptional level, whereas cell growth inhibition is enforced by global repression of the translation machinery.

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Figure 1 Wide-scale exploration of patterns of transcriptional and translational regulation in response to energy and oncogenic stresses using RNA-Seq and Ribo-Seq. (A) We profiled gene-expression levels (RNA-Seq) and rates of mRNA translation (Ribo-Seq) in human primary fibroblast BJ cells subjected to serum depletion (energy stress which results in quiescence (Q) or induction of RASG12V (oncogenic stress which results in senescence (S) in the presence of functional p53, and in neoplastic transformation (T) in the absence of functional p53 and p16INK4A). We examined the effect of RASG12V at two time points, 5 days (pre-senescence; preS) and 14 days (senescence; S). (B-D) Transcripts that showed either differential expression or differential translation efficiency (TE) were identified in the combined RNA-Seq and Ribo-Seq dataset and subjected to cluster analysis. Major patterns of RNA induction (B), RNA repression (C) and modulation of TE (D) were detected. Each cluster is represented by the mean pattern of its assigned transcripts (error bars represent ±SD). The first five points (red) represent transcript levels and the subsequent five points (blue) represent mRNA translation levels. Prior to clustering, levels measured for each transcript were standardized to mean = 0 and SD = 1 (so transcripts that are clustered together show similar response pattern in our dataset but might differ in the magnitude of their response). Enriched functional categories (P-value calculated using hypergeometric tail) and selected genes are indicated next to the patterns. C, control.
Figure 1 Wide-scale exploration of patterns of transcriptional and translational regulation in response to energy and oncogenic stresses using RNA-Seq and Ribo-Seq. (A) We profiled gene-expression levels (RNA-Seq) and rates of mRNA translation (Ribo-Seq) in human primary fibroblast BJ cells subjected to serum depletion (energy stress which results in quiescence (Q) or induction of RASG12V (oncogenic stress which results in senescence (S) in the presence of functional p53, and in neoplastic transformation (T) in the absence of functional p53 and p16INK4A). We examined the effect of RASG12V at two time points, 5 days (pre-senescence; preS) and 14 days (senescence; S). (B-D) Transcripts that showed either differential expression or differential translation efficiency (TE) were identified in the combined RNA-Seq and Ribo-Seq dataset and subjected to cluster analysis. Major patterns of RNA induction (B), RNA repression (C) and modulation of TE (D) were detected. Each cluster is represented by the mean pattern of its assigned transcripts (error bars represent ±SD). The first five points (red) represent transcript levels and the subsequent five points (blue) represent mRNA translation levels. Prior to clustering, levels measured for each transcript were standardized to mean = 0 and SD = 1 (so transcripts that are clustered together show similar response pattern in our dataset but might differ in the magnitude of their response). Enriched functional categories (P-value calculated using hypergeometric tail) and selected genes are indicated next to the patterns. C, control.CC BY · PubMed Central
Figure 2 Two modes of regulation of the translation apparatus. (A) We examined changes in transcript levels (top) and in translation efficiency (TE; bottom), in each condition relative to control proliferating cells, of two functional modules of the translational apparatus: ribogenesis genes (left) and ribosomal protein genes (right). P-values were calculated for each condition by comparing changes observed for the test gene-set and for a background set containing all the other transcripts in the dataset; Wilcoxon test. The figure shows that while the ribosomal protein genes were strikingly and exclusively regulated at the layer of mRNA translation, regulation of ribogenesis genes was enforced at the transcriptional level, and to a lesser extent, in some conditions also at the level of translation. (B) A comprehensive map of the translational apparatus generated using the SPIKE knowledgebase of signaling pathways. The map contains five types of nodes (violet nodes represent genes/proteins; green, protein complexes; yellow, gene families; pink, biological functions or states (for example, 'translation elongation'); and orange, signaling molecules (for example, AMP)), and two types of edges (blue edges represent regulatory relationship between nodes; arrow for activation and T-shaped edges for inhibition; green edges represent associations between gene families or protein complexes and their members). Genes that were repressed in response to energy stress (quiescence state) in our dataset at the transcriptional or the translational levels are colored, respectively, by orange or brown bars to the left of their nodes. (Red and green dots within nodes indicate that the nodes have additional regulation and association relationships in the in SPIKE database that are not displayed in the map to reduce clutter).
Figure 2 Two modes of regulation of the translation apparatus. (A) We examined changes in transcript levels (top) and in translation efficiency (TE; bottom), in each condition relative to control proliferating cells, of two functional modules of the translational apparatus: ribogenesis genes (left) and ribosomal protein genes (right). P-values were calculated for each condition by comparing changes observed for the test gene-set and for a background set containing all the other transcripts in the dataset; Wilcoxon test. The figure shows that while the ribosomal protein genes were strikingly and exclusively regulated at the layer of mRNA translation, regulation of ribogenesis genes was enforced at the transcriptional level, and to a lesser extent, in some conditions also at the level of translation. (B) A comprehensive map of the translational apparatus generated using the SPIKE knowledgebase of signaling pathways. The map contains five types of nodes (violet nodes represent genes/proteins; green, protein complexes; yellow, gene families; pink, biological functions or states (for example, 'translation elongation'); and orange, signaling molecules (for example, AMP)), and two types of edges (blue edges represent regulatory relationship between nodes; arrow for activation and T-shaped edges for inhibition; green edges represent associations between gene families or protein complexes and their members). Genes that were repressed in response to energy stress (quiescence state) in our dataset at the transcriptional or the translational levels are colored, respectively, by orange or brown bars to the left of their nodes. (Red and green dots within nodes indicate that the nodes have additional regulation and association relationships in the in SPIKE database that are not displayed in the map to reduce clutter).CC BY · PubMed Central
Figure 3 Bimodal p53-mediated suppression of cell proliferation and growth. (A) Examination of the effect of energy and oncogenic stress, p53 activation by nutlin-3a (6 h and 19 h after treatment) and mTOR inhibition (by PP242 and rapamycin) on the expression level of cell-cycle related transcripts. p53 activation resulted in a very significant attenuation of the expression of cell-cycle genes. P-values were calculated for each condition by comparing the distribution of fold-change measured for cell-cycle and all the other genes in the dataset using Wilcoxon test. We included in this analysis a subset of 298 genes selected from the set of GO cell-cycle genes (GO:007049) which showed a variation of at least 1.5-fold in expression level (either induction or repression) across our entire dataset. (B) Examination of the effect of energy and oncogenic stress, p53 activation by nutlin-3a and mTOR inhibition on the translation efficiency of the ribosomal protein transcripts. p53 activation resulted in a very significant repression of the translation of ribosomal gene transcripts (P-values were calculating as in A). (C) Validation of the effect of p53 activation on translation efficiency of ribosomal gene transcripts measured by their ribosome occupancy. MCF-7 cells were treated with nutlin-3a for 20 h and subjected to isolation of polysome-associated mRNAs (see Methods). Polysomal fractionation followed by RT-PCR for two ribosomal genes (and GAPDH as a control) were used to quantify mRNA levels in the different polysomal fractions.
Figure 3 Bimodal p53-mediated suppression of cell proliferation and growth. (A) Examination of the effect of energy and oncogenic stress, p53 activation by nutlin-3a (6 h and 19 h after treatment) and mTOR inhibition (by PP242 and rapamycin) on the expression level of cell-cycle related transcripts. p53 activation resulted in a very significant attenuation of the expression of cell-cycle genes. P-values were calculated for each condition by comparing the distribution of fold-change measured for cell-cycle and all the other genes in the dataset using Wilcoxon test. We included in this analysis a subset of 298 genes selected from the set of GO cell-cycle genes (GO:007049) which showed a variation of at least 1.5-fold in expression level (either induction or repression) across our entire dataset. (B) Examination of the effect of energy and oncogenic stress, p53 activation by nutlin-3a and mTOR inhibition on the translation efficiency of the ribosomal protein transcripts. p53 activation resulted in a very significant repression of the translation of ribosomal gene transcripts (P-values were calculating as in A). (C) Validation of the effect of p53 activation on translation efficiency of ribosomal gene transcripts measured by their ribosome occupancy. MCF-7 cells were treated with nutlin-3a for 20 h and subjected to isolation of polysome-associated mRNAs (see Methods). Polysomal fractionation followed by RT-PCR for two ribosomal genes (and GAPDH as a control) were used to quantify mRNA levels in the different polysomal fractions.CC BY · PubMed Central
Figure 4 Knocking-down the Sestrin genes significantly compromises the translational repression of the translation machinery upon p53 activation. (A) A table showing fold induction of Sestrin1 and Sestrin2 (SESN1 and SESN2, respectively) in nutlin-3a treated cells for the indicated times compared to control untreated cells. (B) MCF-7 cells were transfected with si-control and si-SESN1 and si-SESN2 siRNA oligos, treated with nutlin-3a for 20 h, and subjected to RNA-Seq and Ribo-Seq analyses. The effect of siRNAs on the RNA level and ribosome occupancy of SESN1 and SESN2 is shown. (C) Comparison between changes in translation efficiency measured for genes encoding the translational machinery (ribosomal proteins and translation initiation/elongation factors) in response to nutlin-3a treatment, in cells knocked-down for Sestrin1 and Sestrin2 (right) or treated with control siRNAs (left). P-values calculated using Wilcoxon test. FPKM, fragments per kilobase of mRNA per million reads; si, small interfering.
Figure 4 Knocking-down the Sestrin genes significantly compromises the translational repression of the translation machinery upon p53 activation. (A) A table showing fold induction of Sestrin1 and Sestrin2 (SESN1 and SESN2, respectively) in nutlin-3a treated cells for the indicated times compared to control untreated cells. (B) MCF-7 cells were transfected with si-control and si-SESN1 and si-SESN2 siRNA oligos, treated with nutlin-3a for 20 h, and subjected to RNA-Seq and Ribo-Seq analyses. The effect of siRNAs on the RNA level and ribosome occupancy of SESN1 and SESN2 is shown. (C) Comparison between changes in translation efficiency measured for genes encoding the translational machinery (ribosomal proteins and translation initiation/elongation factors) in response to nutlin-3a treatment, in cells knocked-down for Sestrin1 and Sestrin2 (right) or treated with control siRNAs (left). P-values calculated using Wilcoxon test. FPKM, fragments per kilobase of mRNA per million reads; si, small interfering.CC BY · PubMed Central
Figure 5 Schematic model for the bimodal regulatory program activated by p53 to suppress cell growth and proliferation.
Figure 5 Schematic model for the bimodal regulatory program activated by p53 to suppress cell growth and proliferation.CC BY · PubMed Central

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Metadata

Authors
Loayza-Puch, F., Drost, J., Rooijers, K., Lopes, R., Elkon, R., & Agami, R.
Affiliations
The Netherlands Cancer Institute (NL)
Corresponding author
  • Elkon, Ran
  • Agami, Reuven
ORCID
Venue
Genome Biology
Publisher
Springer Science and Business Media LLC
Published
2013-04-17
Volume
14
Issue
4
Pages
R32-R32
ISSN
  • 1465-6906 (ISSN-L)
  • 1474-760X
DOI
10.1186/gb-2013-14-4-r32
PMC
PMC4053767
OpenAlex
W2137903553
Cited by
114
References
37
Citations by year
2026: 2 · 2025: 3 · 2024: 7 · 2023: 5 · 2022: 10 · 2021: 9 · 2020: 7 · 2019: 5 · 2018: 8 · 2017: 12 · 2016: 10 · 2015: 11 · 2014: 15 · 2013: 10
FWCI
8.22
Type
journal article
Language
en
Open access
Licence
Locations
  • Genome biology (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Oncology › Cancer-related Molecular Pathways
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › PI3K/AKT/mTOR signaling in cancer
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
Keywords
p53, mTOR, mRNA translation, cell proliferation, cell growth inhibition, oncogenic stress, energy stress, cellular senescence, Sestrin2, cell cycle arrest, tumor suppression, ribosome profiling, nutrient sensing
MeSH terms
Cell Line, Humans, Transcription, Genetic, Protein Biosynthesis, Gene Expression Regulation, Neoplastic, Tumor Suppressor Protein p53, Cellular Senescence, Apoptosis, Proteome, Cell Proliferation, TOR Serine-Threonine Kinases, Transcriptome, Carcinogenesis

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