Fig 1: The NSP, via RPL5 and RPL11, is required to stabilize p53 in response to a broad range of genetic, pharmacological, and pathophysiologic stressesTo identify which candidate genes are required for the canonical NSP, we rescreened a selection of candidates from the primary p53 stabilization screen described in Figure 1 (ribosomal proteins, nucleolar/RiBi candidates, and “other” p53 positive candidates, 232 genes in total) in the presence of non-targeting, RPL5, RPL11, HEATR3, or RPS19 siRNAs in A549 cells (A). From this analysis, we further quantified the number of candidates screened from each group (ribosomal proteins, nucleolar/RiBi, and other) for which their p53 response could be suppressed by =50% when co-depleted with RPL5, RPL11, HEATR3, or RPS19 siRNAs (B). We further tested a panel of pharmacological agents and pathophysiological stressors when A549 cells were depleted of RPL5 and RPL11 for 48 h. Cells were treated for 24 h with pharmacological agents actinomycin D (ACTD, 5 nM), a-amanitin (2.5 µM), doxorubicin (DRB, 500 nM), 5-fluoruracil (5-FU, 50 µM), etoposide (ETO, 50 µM), camptothecin (CPT, 50 nM), leptomycin B (LMB, 10 ng/mL), or MG132 (10 µM). Alternatively, cells were treated with pathophysiological stressors UV (50 J/m2), gamma irradiation (10 Gy), or subjected to heat shock (45°C, 30 min), then incubated at 37°C for 3 h post treatment. At the end of treatment, protein was harvested and subjected to western blot analysis for p53 and p21 protein expression (C). The same panel of stressors (and treatment conditions) was tested on mouse embryonic fibroblasts (MEFs) isolated from either Mdm2 wild-type (WT) or mice homozygous for the Mdm2 C305F mutation (C305F) to determine p53 expression (D). n = 3–4 biological replicates for each condition, and the most representative experiment for each treatment is presented.
Fig 2: mTOR overactivation causes increased translation of 5' terminal oligopyrimidine (5’TOP) transcripts leading to precocious differentiation.(A) Immunostaining of 40-day-old TSC2+/+ and TSC2-/- organoid sections (Rozh-5 background) with anti-TSC2 antibody. Scale bar = 100 µm. (B) Immunostaining of 40-day-old TSC2+/+ and TSC2-/- organoid sections (Rozh-5 background) stained with anti-pS6 and anti-SOX2 antibodies. Zoomed-in image of the inlay on the bottom. Scale bar = 100 µm. (C) Schematic representation of polysome profiling of 37-day-old TSC2+/+ and TSC2-/- organoids (Rozh-5 background) followed by RNA-seq and differential polysome association analysis of 80S monosome, low-polysome and high-polysome fractions. Data was generated from three batches of organoid differentiation for Rozh-5 WT and Rozh-5 TSC2-/- 4G11 clones. (D) Heatmap of hierarchical clustering of genes differentially associated with high-polysome fractions of TSC2+/+ and TSC2-/- organoids (left). Top 10 most significant cellular component gene ontology (GO) terms for TSC2-/- enriched differentially associated genes (DAGs) and TSC2+/+ enriched DAGs (right). (E) MA plot of 5’TOP genes for high-polysome, low-polysome and monosome fractions shows log2 fold change of TSC2-/- over TSC2+/+ versus log2 mean transcript per million (TPM) (expression levels). Significant genes (threshold: log2 fold change = 1, FDR = 0.1) are color coded. (F) Log2 fold change of classical 5’TOP genes associated with high-polysome fractions over monosome fractions of TSC2+/+ and TSC2-/- organoids. Boxplots mark median and interquartile range (IQR. Whiskers extend to 1.5x IQR). p-Value of paired t-test. (G) Quantification of mean z-score normalized fluorescent intensity of RPL5 and RPL11 proteins in the ventricular zones (VZs) of TSC2+/+ and TSC2-/- organoids (Rozh-5 background). Error bars mark standard deviation. p-Values of unpaired t-test are shown. Each dot represents a VZ. Data from three batches of organoid differentiation for each clone. Schematic on the left shows a typical regions of interest (ROI) analyzed for a VZ. Figure 5—source data 1.Differential gene association analysis from polysome profiling results.
Fig 3: Analysis of developing mouse brain tissue.(A) Confocal scans of ventricular zones in E12. 5 Mouse developing cortex stained with anti-EGFP, anti-G3BP1, anti-SOX1 and anti-MAP2 antibodies and DAPI. Zoomed-in images of the boxed areas are shown below. Arrows mark G3BP1 positive punctate structures. Scale bar = 50 µm. (B) Expression scores of 5’TOP genes RPL5 and RPL11 during mouse cortex development. scRNA-seq data from Telley et al. , Science 2019: http://genebrowser.unige.ch/telagirdon/.
Fig 4: High-throughput screening for modifiers of ribosomal stress due to activation of the canonical nucleolar surveillance pathway (NSP) and analysis of the HEAT-repeat containing 3 (HEATR3) protein and its role in ribosome and 5S-RNP biogenesisIn a similar approach (outlined in Figure 1A), we performed a genome-wide RNAi screen to identify modifiers of ribosomal stress by co-depleting RPS19 with every gene in the genome. After conducting the screen, candidates were further triaged using gene expression data from RNA-seq analysis of A549 cells depleted of RPS19 (RPKM cutoff of 0.05 or greater) to yield 14,577 “expressed” screen candidates. The “expressed” screen candidates were then graphed normalized to RPS19 depletion (A); candidates in red are those with a Log2 value of = -1 (total 64 candidates). Ribosomal protein (RP) genes in the screening data are demarcated with blue circles. A selection of these candidates (TP53, RPL5, RPL11, HEATR3, RXRA, and CIRH1A) was then further subjected to candidate-based validation in A549 cells (B), by co-depletion of candidates with siRPS19 for 72 h, and analyzed by western blotting (representative of n = 3 biological experiments). Comparison between C. thermophilium Syo1 (ctSyo1) (PDB: 5AFF) (Kressler et al., 2012) and the predicted human HEATR3 structure was performed (C). HEATR3 secondary structure and domain modeling indicates the presence of an N-terminal Armadillo (ARM, orange), and a C-terminal HEAT-repeat domain (dark gray), similar to the yeast symportin 1 (Syo1) protein. A domain schematic (to scale; top) and a cartoon model (bottom) are shown for each protein. Similar to the ctSyo1 protein, HEATR3 contains four N-terminal Armadillo (ARM) repeats and six C-terminal HEAT repeats. In the case for HEATR3, these regions are connected by a central, long, and unstructured loop, whereas ctSyo1 has an acidic loop with a helical segment (Glu389 to Gly399) likely responsible, at least in part, for the binding of rpL11 (light blue, surface representation) to the protein (Calvino et al., 2015). A conserved N-terminal segment of RPL5 (green, surface representation) may also interact with HEATR3 (similar to Syo1). Co-immunoprecipitation (CoIP) analysis of human myc-tagged HEATR3 (MT-HEATR3) with FLAG-tagged human RPL5 and RPL11 proteins in HEK293 cells (D). Ribosome subunit (E) analysis of A549 cells depleted of RPL5, RPL11, or HEATR3 (and non-targeting siRNA, siNT) for 72 h and quantitation of 40S:60S ratio (F; note that the NT, RPL5, and RPL11 data traces presented here are already presented in Figure 2D and are replicated in this figure to directly compare the effect of HEATR3 depletion with these conditions). A549 cells depleted of HEATR3 for 48 h were pulsed with ~3–5 mCi 32P orthophosphate for 30 min and chased for a further 30 min to examine rRNA processing (G) with quantitation of 28:18S rRNA ratio in (H). Northern blot analysis of the association of MDM2 with 5S rRNA after 48-h HEATR3 depletion in U2OS cells expressing FLAG-MDM2 (I) and quantitation (J). Schematic of the predicted role of HEATR3 in 5S-RNP biogenesis (“Normal”) and the NSP (K). Data presented are the mean -/+ SD. Statistical analysis was performed using unpaired student t test for 40:60S subunit analysis and 5S rRNA binding experiments; one-way ANOVA with Sidak’s multiple comparison test was conducted for 28:18S ratio after 32P rRNA labeling as part of a time series presented in Figure S7F. Minimum n = 3 biological experiments were carried out for each analysis, and representative images are presented; ****p < 0.0001, **p < 0.01.
Fig 5: Expression of most ribosomal protein genes is integral for maintaining cellular p53 homeostasisGiven the enrichment of ribosomal protein (RP) genes in our primary screen dataset, we further investigated this group; depicted is the breakdown of screened RPs that were p53 “positive,” 2-fold or greater increase in p53, and the proportion of which are in the large (60S) or small (40S) ribosome subunit, shown in (A). We further verified the p53 result of approximately 50% of the RP genes (when depleted using siRNAs for 72 h) with quantitative p53 analysis (Alphascreen) in A549 cells (note genes associated with DBA are highlighted in red) (B). We selected candidates that were “p53 positive” (RPS18, RPL21, RPS19) and “p53 low” (RPL5, RPL11, RPL22, RPL28) to confirm knockdown at the protein level, and we determined p53 and p21 protein levels using western blot analysis in A549 cells (C, representative blot of n = 3 experiments). Cells depleted of each RP were then subjected to ribosome subunit analysis (performed under high-salt conditions, D) to determine the effect of depletion on 60S and 40S subunits (quantitation of 40S:60S subunit ratio is presented in E). Comparison of the timing of RP incorporation into the ribosome subunit as tabulated by de la Cruz and colleagues (de la Cruz et al., 2015) with p53 intensity when the RP was depleted using siRNA (F), where red circles indicate 40S subunit RPs, and black circles indicate 60S subunit RPs. Quantitative data presented as mean -/+ SD. Statistical analysis: for quantitation of 40S:60S subunits, one-way ANOVA with Dunnett’s multiple comparison test was conducted; for timing of RP incorporation into ribosome subunit, one-way ANOVA with Tukey’s multiple comparison test was performed. ****p < 0.0001, ***p < 0.001, **p < 0.01, *p < 0.05, ns = not significant. Alphascreen analysis performed n = 3–5 biological experiments; ribosome subunit analysis conducted on a minimum of n = 3 biological experiments per candidate.
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