Title: Queuosine‐modified tRNAs confer nutritional control of protein translation
Abstract: Article9 August 2018Open Access Source DataTransparent process Queuosine-modified tRNAs confer nutritional control of protein translation Francesca Tuorto Corresponding Author Francesca Tuorto [email protected] orcid.org/0000-0003-1625-1181 Division of Epigenetics, DKFZ-ZMBH Alliance, German Cancer Research Center, Heidelberg, Germany Search for more papers by this author Carine Legrand Carine Legrand Division of Epigenetics, DKFZ-ZMBH Alliance, German Cancer Research Center, Heidelberg, Germany Search for more papers by this author Cansu Cirzi Cansu Cirzi Division of Epigenetics, DKFZ-ZMBH Alliance, German Cancer Research Center, Heidelberg, Germany Faculty of Biosciences, University of Heidelberg, Heidelberg, Germany Search for more papers by this author Giuseppina Federico Giuseppina Federico Department of Cellular and Molecular Pathology, German Cancer Research Center, Heidelberg, Germany Search for more papers by this author Reinhard Liebers Reinhard Liebers Division of Epigenetics, DKFZ-ZMBH Alliance, German Cancer Research Center, Heidelberg, Germany Faculty of Biosciences, University of Heidelberg, Heidelberg, Germany Search for more papers by this author Martin Müller Martin Müller Institut für Biologie, Humboldt-Universität zu Berlin, Berlin, Germany Search for more papers by this author Ann E Ehrenhofer-Murray Ann E Ehrenhofer-Murray orcid.org/0000-0001-8709-1942 Institut für Biologie, Humboldt-Universität zu Berlin, Berlin, Germany Search for more papers by this author Gunnar Dittmar Gunnar Dittmar orcid.org/0000-0003-3647-8623 Proteome and Genome Research Unit, Department of Oncology, Luxembourg Institute of Health, Luxembourg, Luxembourg Search for more papers by this author Hermann-Josef Gröne Hermann-Josef Gröne Department of Cellular and Molecular Pathology, German Cancer Research Center, Heidelberg, Germany Search for more papers by this author Frank Lyko Frank Lyko orcid.org/0000-0002-4873-5431 Division of Epigenetics, DKFZ-ZMBH Alliance, German Cancer Research Center, Heidelberg, Germany Search for more papers by this author Francesca Tuorto Corresponding Author Francesca Tuorto [email protected] orcid.org/0000-0003-1625-1181 Division of Epigenetics, DKFZ-ZMBH Alliance, German Cancer Research Center, Heidelberg, Germany Search for more papers by this author Carine Legrand Carine Legrand Division of Epigenetics, DKFZ-ZMBH Alliance, German Cancer Research Center, Heidelberg, Germany Search for more papers by this author Cansu Cirzi Cansu Cirzi Division of Epigenetics, DKFZ-ZMBH Alliance, German Cancer Research Center, Heidelberg, Germany Faculty of Biosciences, University of Heidelberg, Heidelberg, Germany Search for more papers by this author Giuseppina Federico Giuseppina Federico Department of Cellular and Molecular Pathology, German Cancer Research Center, Heidelberg, Germany Search for more papers by this author Reinhard Liebers Reinhard Liebers Division of Epigenetics, DKFZ-ZMBH Alliance, German Cancer Research Center, Heidelberg, Germany Faculty of Biosciences, University of Heidelberg, Heidelberg, Germany Search for more papers by this author Martin Müller Martin Müller Institut für Biologie, Humboldt-Universität zu Berlin, Berlin, Germany Search for more papers by this author Ann E Ehrenhofer-Murray Ann E Ehrenhofer-Murray orcid.org/0000-0001-8709-1942 Institut für Biologie, Humboldt-Universität zu Berlin, Berlin, Germany Search for more papers by this author Gunnar Dittmar Gunnar Dittmar orcid.org/0000-0003-3647-8623 Proteome and Genome Research Unit, Department of Oncology, Luxembourg Institute of Health, Luxembourg, Luxembourg Search for more papers by this author Hermann-Josef Gröne Hermann-Josef Gröne Department of Cellular and Molecular Pathology, German Cancer Research Center, Heidelberg, Germany Search for more papers by this author Frank Lyko Frank Lyko orcid.org/0000-0002-4873-5431 Division of Epigenetics, DKFZ-ZMBH Alliance, German Cancer Research Center, Heidelberg, Germany Search for more papers by this author Author Information Francesca Tuorto *,1, Carine Legrand1, Cansu Cirzi1,2, Giuseppina Federico3, Reinhard Liebers1,2, Martin Müller4, Ann E Ehrenhofer-Murray4, Gunnar Dittmar5, Hermann-Josef Gröne3 and Frank Lyko1 1Division of Epigenetics, DKFZ-ZMBH Alliance, German Cancer Research Center, Heidelberg, Germany 2Faculty of Biosciences, University of Heidelberg, Heidelberg, Germany 3Department of Cellular and Molecular Pathology, German Cancer Research Center, Heidelberg, Germany 4Institut für Biologie, Humboldt-Universität zu Berlin, Berlin, Germany 5Proteome and Genome Research Unit, Department of Oncology, Luxembourg Institute of Health, Luxembourg, Luxembourg *Corresponding author. Tel: +49 6221 423806; Fax: +49 6221 423802; E-mail: [email protected] The EMBO Journal (2018)37:e99777https://doi.org/10.15252/embj.201899777 See also: I Kozlovski & R Agami (September 2018) PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract Global protein translation as well as translation at the codon level can be regulated by tRNA modifications. In eukaryotes, levels of tRNA queuosinylation reflect the bioavailability of the precursor queuine, which is salvaged from the diet and gut microbiota. We show here that nutritionally determined Q-tRNA levels promote Dnmt2-mediated methylation of tRNA Asp and control translational speed of Q-decoded codons as well as at near-cognate codons. Deregulation of translation upon queuine depletion results in unfolded proteins that trigger endoplasmic reticulum stress and activation of the unfolded protein response, both in cultured human cell lines and in germ-free mice fed with a queuosine-deficient diet. Taken together, our findings comprehensively resolve the role of this anticodon tRNA modification in the context of native protein translation and describe a novel mechanism that links nutritionally determined modification levels to effective polypeptide synthesis and cellular homeostasis. Synopsis The modification of certain tRNAs depends on diet-supplied precursor queuine. The queuosinylation of tRNAs affects methylation on neighbouring nucleotides and controls translational speed, illustrating how a nutritionally determined tRNA modification can affect polypeptide synthesis and cellular homeostasis in vivo. Dnmt2-dependent tRNA methylation is dynamically modulated by nutritionally determined queuosine-tRNA levels. Queuosine-tRNA levels control the translation speed of queuosinylated-tRNA decoded codons. Altered translation in the absence of queuosine results in misfolded aggregates, which in turn trigger endoplasmic reticulum stress and the unfolded protein response. Introduction The correct assignment of 20 amino acids to each of the 64 possible codon triplets within the messenger RNA (mRNA)-coding sequence determines accurate protein synthesis. Codon:anticodon recognition is mediated by transfer RNAs (tRNAs), which physically link mRNAs to the amino acid sequence of the nascent polypeptide at the ribosome. The 1st and 2nd base of the codon and the 3rd and 2nd base of the anticodon, respectively, interact according to the Watson–Crick base-pairing rules (A:U, U:A, G:C, and C:G). In contrast, the interaction between the 3rd base of the codon and the 1st base of the anticodon (position 34, so-called wobble base) is less stringent, so that non-standard base pairings are permitted (Crick, 1966). As a result, a given tRNA may read more than one synonymous codon. Post-transcriptional modifications in the anticodon loop of tRNAs are critical for the translation process (Grosjean et al, 2010). In particular, position 34 is subject to various modifications (Agris et al, 2017), depending on the associated tRNA isoacceptor and the organism (Grosjean et al, 2010; El Yacoubi et al, 2012). Some of these modifications have been shown to be important for the fine-tuning of protein translation and for the maintenance of proteome integrity in yeast and in C. elegans (Rezgui et al, 2013; Zinshteyn & Gilbert, 2013; Nedialkova & Leidel, 2015; Chou et al, 2017). Queuosine is a hyper-modified guanosine analog that comprises a 7-deaza-guanine core structure covalently linked to an amino-methyl side chain and a cyclo-pentanediol moiety (Fergus et al, 2015). The corresponding base is termed queuine (q), and the respective nucleotide is called queuosine (Q). Q occurs at the wobble position of tRNAs with GUN anticodons tRNAAspGUC, tRNAHisGUG, tRNATyrGUA, and tRNAAsnGUU (Harada & Nishimura, 1972). In eukaryotes, both NAC/U codons are translated by tRNA genes with GUN anticodons. The translation of NAU is mediated by a non-canonical G:U pairing. In eubacteria, lack of Q affects mRNA translation and reduces the virulence of certain pathogenic strains (Durand et al, 2000). In animal cells, changes in the abundance of Q have been shown to correlate with diverse phenomena including stress tolerance, cell proliferation, and tumor growth (Fergus et al, 2015). Nonetheless, the function of Q in mammals remains poorly understood. Animals obtain Q (or its analogs) as a micronutrient from dietary sources and from the gut microbiota (Farkas, 1980; Fergus et al, 2015). The difficulty of maintaining animals under bacteria-free conditions and/or on Q-deficient diets has severely hampered the study of Q metabolism and function in metazoans. Nevertheless, germ-free mice fed with a Q-free diet have been shown to be deficient in queuosine modifications of tRNA, while exogenous administration of queuine restores Q-tRNA (Reyniers et al, 1981). Cytosine-5 methylation (m5C) is a widely known modification in the context of DNA methylation and epigenetic gene regulation (Jones, 2012). Interestingly, m5C also represents a conserved RNA modification (Gilbert et al, 2016), and several recent studies have provided evidence for a conserved role in the regulation of protein translation (Tuorto & Lyko, 2016). We have previously shown that Dnmt2-mediated tRNA methylation affects the speed and accuracy of protein translation (Tuorto et al, 2015). In higher eukaryotes, m5C-tRNA methylation is found at positions 48, 49, and 72, and in the anticodon loop at positions 34 and 38 (Motorin et al, 2010). The absence of a methyl group at these positions has been suggested to interfere with tRNA folding and stability, codon–anticodon interactions, and reading frame maintenance (Agris, 2004; Grosjean et al, 2010; El Yacoubi et al, 2012; Guy et al, 2014; Hori, 2014). Interestingly, tRNAAsp is modified with both m5C and Q, and it has been shown recently that DNMT2-dependent tRNA methylation is enhanced by queuine in S. pombe and in D. discoideum (Muller et al, 2015). Remarkably, the choice of C- versus U-ending codons of certain developmental genes in Drosophila and the codon usage across Drosophila species at evolutionarily conserved Q codon sites relates to the level of Q-tRNA modification (Zaborske et al, 2014). More specifically, it was observed that the level of Q-modification provides an accuracy-driven selective advantage of C- over U-ending codons. This suggested a “kinetic competition model”, wherein the presence of Q34 leads to more accurate translation of the C-ending codon as a result of increased binding affinity (Zaborske et al, 2014). This indicated that environmental conditions, such as the availability of a micronutrient from the gut microbiota, can influence the decoding of a genome. However, this concept is currently only supported by codon usage analysis in Drosophila, and direct experimental evidence has been lacking. Furthermore, the described preference of Q-tRNAs for C- over U-ending codons is in contrast with earlier findings that either did not detect any Q-dependent changes in protein synthesis (Owenby et al, 1979) or suggested a mild preference for Q:U pairings over Q:C (Meier et al, 1985; Morris et al, 1999). Here, we have obtained translatomes of Q-containing and Q-lacking human cells to comprehensively analyze the role of queuine in the native protein translation context and describe a novel mechanism that links nutritionally determined tRNA modification levels to the effective polypeptide synthesis and cellular homeostasis. Using ribosome profiling and SILAC, we show that nutritionally determined Q-tRNA levels promote C38 methylation and control translational speed at codons decoded by Q-tRNAs and their near-cognate codons. The loss of Q-modification results in pronounced changes in cellular and organismal phenotypes including the induction of the unfolded protein response. Our results establish a novel molecular link between microbial-derived micronutrients and the coordinated decoding of the mammalian transcriptome, thus identifying a central nutrient-controlled mechanism for the fine-tuning of protein translation. Results C38 methylation depends on Q in mammalian cell lines Standard cell culture medium contains 1–2 × 10−8 M q, which is provided through the fetal bovine serum (S) supplement and is sufficient for the quantitative modification of tRNAs (Katze et al, 1982; Fergus et al, 2015). Therefore, to obtain a q-free cell culture system, human HeLa cells were grown in synthetic serum-free medium (SF) (Rakovich et al, 2011), in the absence or presence of chemically synthesized q (Fig 1A). To quantify Q-tRNA modification levels directly from total RNA, we used polyacrylamide gels that are covalently linked with N-acryloyl-3-aminophenylboronic acid (APB; Igloi & Kossel, 1985; Zaborske et al, 2014). In APB gels, the additional ribose moiety of Q slows down Q-tRNA migration compared to G-tRNA, thus producing two bands, corresponding to Q-tRNAHisQUG and G-tRNAHisGUG (Fig 1A). Using APB Northern analysis, we confirmed a continuous reduction in Q-tRNA in our SF cell culture at various time points over a 21-day culture period with a probe specific to tRNAHis (Fig 1A). A similar loss of Q-tRNA was observed using a probe detecting tRNAAsn (Fig EV1A). No separate Q and G bands were detected with tRNAAsp and tRNATyr (Fig EV1A), which is likely due to a secondary mannosyl modification of Q-tRNAAsp and galactosyl modification of Q-tRNATyr (Kasai et al, 1976; Zaborske et al, 2014). Figure 1. m5C38-tRNAAspGUC dependency by Q in human cell culture APB Northern blot using a tRNAHis probe. m5C38 levels of tRNAAspGUC were measured by 454 bisulfite sequencing at the indicated time points. Both queuosinylation and methylation levels could be restored by the addition of queuine. The slower migration of tRNAHis is eliminated by oxidizing the ribose with periodate, producing a single faster migrating band (ox). The addition of queuine to HCT116 cells cultured in serum-free medium resulted in an increase in both queuosinylation and m5C38 levels. The addition of 20 nM queuine to the SF medium is sufficient to restore tRNAHisQUG in HeLa, whereas 200 nM of q is necessary for queuosinylation of tRNAHisGUG in HCT116 cells. Data information: S (standard medium), SF (serum-free medium), q (queuine), Q (queuosine), and G (guanine). Source data are available online for this figure. Source Data for Figure 1 [embj201899777-sup-0006-SDataFig1.pdf] Download figure Download PowerPoint Click here to expand this figure. Figure EV1. m5C38-tRNAAsp GUC dependency on Q in HeLa cell culture and tRNA level quantifications APB Northern blot using tRNAAsn probe shows that SF medium depletes Q-tRNA. No separate Q- and G-tRNAAsp and Tyr bands were detected. m5C38 levels are measured by 454 bisulfite sequencing. A concomitant robust reduction in Q-tRNAHis and m5C38-tRNAAspGUC is observed in HeLa cells cultivated in SF medium. Both queuosinylation and methylation levels could be restored by the addition of queuine to the SF medium for 3 or 8 days after 21 days in SF medium. The differential migration is eliminated by oxidizing the ribose with periodate, producing a single faster migrating band (ox). Bisulfite sequencing maps from a biological replicate culture under S and SF for 3 weeks are depicted. Each row represents one sequence read and each column a cytosine residue. Green boxes represent unmethylated cytosine residues, and red boxes indicate methylated cytosine residues. Sequencing gaps are shown in white. Numbers in the maps indicate the number of reads. The position of specific cytosine residues and level of C38 methylation are indicated at the bottom. APB Northern blot analysis that complete Fig 2B with tRNAAsp, tRNAAsn, tRNATyr, and 5S rRNA as a loading control. Quantitative analysis of signals for tRNAs at the indicated culture conditions. tRNA signal intensities were normalized to 5S rRNA levels for each of the two replicates. Data information: S (standard medium), SF (serum-free medium), q (queuine), Q (queuosine), and G (guanine). Source data are available online for this figure. Download figure Download PowerPoint In further experiments, we used tRNA bisulfite sequencing (Schaefer et al, 2009) to determine whether Dnmt2-mediated tRNA methylation is affected by the presence of q in the medium, as shown previously for tRNAAspGUC in fission yeast (Muller et al, 2015). A reduction in m5C38 tRNAAspGUC from 96 to 57% was observed in SF medium (Fig 1A), while methylation levels of the non-queuosinylated Dnmt2 targets tRNAGlyGCC and tRNAValAAC remained unaffected after culturing for 3 weeks in SF medium (Fig EV1A and B). To confirm that Q is necessary for physiological C38 methylation levels, we added synthetic q in rescue experiments. Indeed, C38 methylation of tRNAAspGUC was completely restored (Figs 1A and EV1A and B). These findings demonstrate that Q enhances DNMT2 activity on tRNAAspGUC in a mammalian cell line. We also addressed the conservation of this mechanism in an additional cell culture model, and SF conditions strongly reduced the queuosinylation of tRNAHis in human colorectal carcinoma cells (HCT116; Fig 1B). When we analyzed tRNAHis queuosinylation at various concentrations of q, we observed that in HeLa cells quantitative queuosinylation was achieved at 20 nM (Fig 1C), which corresponds to the q levels of standard cell culture media (Katze et al, 1982; Fergus et al, 2015). Interestingly, HCT116 cells required higher q concentrations (200 nM) to quantitatively modify G-tRNAHis. This indicates a role of cell-type-specific factors in queuine uptake and salvage (Fergus et al, 2015; Zallot et al, 2017). Taken together, our data thus suggest a conserved post-transcriptional control mechanism of Q-tRNA and m5C38-tRNA modifications. Q accelerates translational speed at Q-decoded codons In subsequent experiments, we aimed to determine how Q and the Q-dependent m5C38 modification influence protein translation. To this end, we compared HeLa cells that were cultured 45 days under SF conditions with cells that were first cultured under SF conditions for 30 days and then received 20 nM queuine for 15 days (SF+qR) to rescue any q-dependent defects (Fig 2A). Furthermore, a parallel control culture (45 days) was established using SF conditions supplemented with 20 nM queuine for the entire duration of the experiment (SF+q) (Fig 2A). HeLa cells grown in standard medium (S) and in standard medium supplemented with 20 nM queuine were included as additional controls (Fig 2A). Under all conditions, levels of Q-tRNAHis and m5C38-tRNA strictly depended on the availability of the supplemented q (Fig 2B). tRNA level measurements excluded an effect due to altered tRNA stability or tRNA availability by Q (Figs 2B and EV1C and D). We then examined genome-wide codon occupancy during translation elongation, in different culture conditions (Fig 2A) using ribosome profiling. In this method, ribosome-protected mRNA fragments are sequenced to obtain ribosomal position-specific information at single-nucleotide resolution (Ingolia et al, 2011). Two independent biological replicates for each culture condition were analyzed and showed a strong correlation (Fig EV2A). Quality controls (Figs 2C and D, and EV2A) suggested the generation of high-quality datasets. Data analysis revealed that q-free culture conditions resulted in a significant (P < 0.05, t-test) increase in ribosome density at specific codons (Figs 3A and EV2B), which included all the queuosine-decoded codons: tRNAAsp, tRNATyr, tRNAHis, and tRNAAsn (Figs 3A and EV2B), suggesting that translation of these codons was slower in the absence of the Q-modification. We also observed reduced translation speed at specific near-cognate Q-decoded codons such as Glu (GAA, GAG), in agreement with earlier results from m5C38-deficient mice (Tuorto et al, 2015). Hierarchical clustering of codons according to translational speed also resulted in the consistent separation of Q-decoded and related near-cognate codons from all the other codons (Fig EV2C). Notably, focusing on synonymous codon pairs, the U-ending codons were slowed down more severely than the C-ending codons, except for tRNAAspGUC, where the concomitant reduction in m5C38 resulted in a slower translation of the GAC codon (Fig 3B). Figure 2. Q-depleted and quantitatively modified cell culture conditions Cell culture timing schedule. Corresponding queuosinylation and methylation levels, as determined by Northern blot using a tRNAHis probe and bisulfite sequencing of tRNAAspGUC. Representative metaplot of SF cells. 25–32 mer ribosome footprint reads were summed across all annotated reading frames with the AUG staring codon at position zero. In-frame 27–30 mer ribosome footprints showing the correct periodicity. Representative metagene plot of 27–30 mer ribosome footprints in S and SF culture conditions for two biological replicates (rep1 and rep2). Data information: S (standard medium), SF (serum-free medium), q (queuine), Q (queuosine), and G (guanine). Source data are available online for this figure. Source Data for Figure 2 [embj201899777-sup-0007-SDataFig2.pdf] Download figure Download PowerPoint Click here to expand this figure. Figure EV2. Translation speed in Q-free cells Correlation between ribosome profiling dataset replicates. Spearman rho, 95% confidence interval for each pair of replicates. Changes in bulk codon occupancy in –Q cells compared to the relative rescue condition. All Q-decoded codons and Glu/Lys codons are highlighted with the indicated colors. Error bars: ± SE of the permutated ratios of bulk codon occupancy for the indicated conditions; (n = 4). For each distribution, the statistical significance calculated using a Kolmogorov–Smirnov test is shown. P-values (t-test, adjusted for multiple testing) relative for each codon occupancy are indicated by a color scale heatmap at the bottom. The heatmap shows codon occupancy correlations between replicates using Ward's maximum distance clustering method. Q-decoded codons are shown in green and Lys and Glu codons in orange. Note that hierarchical clustering grouped all Q-decoded codons together. Data information: S (standard medium), SF (serum-free medium), q (queuine), Q (queuosine), and G (guanine). Download figure Download PowerPoint Figure 3. Effects of Q depletion on translational speed Heatmap showing codon occupancy according to the color scale. Green bars indicate Q-decoded codons. The Asp-GAC codon translated by Q- and m5C38-tRNAAspGUC is shown in yellow and Lys and Glu codons are in orange. Lack of Q reduces ribosome translation speed at all Q-dependent codons and at near-cognate decoded codons. Translational speed of C-ending codons relative to U-ending codons. Error bars: ± SE of the permutated ratios of C-ending codon occupancy relative to U for the indicated conditions; (n = 4). Heatmap displaying an increase or decrease in codon frequencies (‰) in SILAC down-regulated proteins relative to the average frequency of that codon in unchanged proteins. Codons translated by Q-tRNA in both forward and reverse SILAC. § Data information: S (standard medium), SF (serum-free medium), q (queuine), Q (queuosine), and G (guanine). Download figure Download PowerPoint To confirm this finding, we used stable isotope labeling by amino acids (SILAC) in HeLa cell culture in the presence or absence of q for 3 weeks (Fig EV3A–C, Dataset EV1). Codon usage analysis of deregulated proteins confirmed an effect of Q on codons decoded by Q-tRNA and near-cognate codons (Fig 3C). Indeed, codons translated slower by Q-tRNA in the absence of the Q-modification were enriched in down-regulated proteins and depleted in up-regulated proteins in both forward and reverse labeling (Figs 3D and EV3D). These results confirm the ribosome profiling findings with an orthogonal approach and strongly indicate a role of Q and m5C38 in the decoding of the mammalian transcriptome. Click here to expand this figure. Figure EV3. SILAC Labeling culture conditions and numbers of identified proteins. APB Northern blot using tRNAHis probe and C38 methylation of tRNAAsp in SILAC labeled cells. SILAC analysis of deregulated proteins in the absence of Q. The top 10% of down-regulated proteins are indicated in red, the top 10% of up-regulated proteins are indicated in blue, HSPA5/BiP is indicated in orange. Increase or decrease in a codon frequency (‰) in up- or down-regulated proteins relative to the average frequency of that codon in unchanged proteins is displayed as heatmap according to the color scale. Data information: DS (dialyzed medium), q (queuine), Q (queuosine), and G (guanine). Source data are available online for this figure. Download figure Download PowerPoint Q-dependent phenotypes in cultured cell lines To characterize the phenotypic consequences of Q depletion, we performed gene ontology (GO) enrichment analysis on mRNAs that were differentially translated in Q-depleted cells (Figs 4A and EV4A–C, and Dataset EV2). Ingenuity pathway analysis revealed a strong enrichment for genes involved in eIF2 signaling (Fig 4B) a critical point of stress-induced regulation of translation in eukaryotic cells (Bhat et al, 2015). Accordingly, we also identified several pathways related to stress signaling (Fig 4B). Other significantly enriched pathways, such as p70S6K signaling (Fig 4B), provided links between protein translation and a plethora of cellular functions (Holz et al, 2005). Figure 4. Q-dependent phenotypes in cultured cell lines The volcano plot shows differentially translated transcripts against adjusted P-values for SF compared to SF + q. Red dots indicate Padj < 0.1 in multiple tests. Comparative analysis of differentially translated mRNAs of both experimental groups (SF compared to SF + q and SF compared to SF + qR) using ingenuity pathway analysis identified EIF2 signaling as the most significantly affected canonical pathway. Representative polysome profiles of HeLa cells grown in S and SF medium in the absence or presence of q. As a measurement for the global translation rate, the fraction of polysomal ribosomes was quantified; *P < 0.05 (t-test); n = 5. Proliferation analysis of HeLa cells grown under the indicated culture conditions. Population doubling levels of three biological replicates were calculated for each time point. Error bars: ± SD; n = 3. Data information: S (standard medium), SF (serum-free medium), q (queuine), and RO (ribosome occupancy). Download figure Download PowerPoint Click here to expand this figure. Figure EV4. Molecular functions affected by Q Log2 fold changes in transcripts abundance and footprints at the indicated cell culture conditions. Pearson correlation coefficient (r) between footprints and mRNA abundance changes is shown. Volcano plot showing differentially translated mRNAs against adjusted P-values for SF compared with SF + qR. Red dots indicate Padj < 0.1. Venn diagram showing the correlation of mRNA with high and low ribosome occupancy between the two rescue experiments (SF compared to SF + q and SF compared with SF + qR). Ingenuity molecular function analysis of differentially translated mRNAs. The top eight categories according to the ingenuity causal network P-value are shown. Transmission electron microscopy images showing cellular overview with increased cystic vacuoles of the ER upon Q depletion. Arrowheads point to rough endoplasmic reticulum while expansions are indicated by asterisk. N, nucleus. Scale bar 500 nm. Automated quantification of the size of all vacuoles is presented in violin plot between the indicated grown conditions (5 optical fields). Black lines show the medians; white lines represent individual data points; polygons represent the estimated density of the data; *P < 0.05 (t-test). Automated quantification of fluorescence intensity (AU: arbitrary units) relative to the immunofluorescence in Fig 6B. Error bars: ± SD (all cells in n ≥ 3 optical fields); *P < 0.05 (t-test). Western blot showing increased eIF2α phosphorylation upon Q depletion. Actin and global eIF2 levels are used as loading controls. Quantification of the eIF2α phosphorylation signal normalized to β-actin. Each bar represents three independent biological replicates. Error bars: ± SD; *P < 0.05 (t-test). Data information: S (standard medium), SF (serum-free medium), and q (queuine). Source data are available online for this figure. Download figure Download PowerPoint The affected signaling pathways are strictly lin