16 research outputs found

    Aminoacyl-tRNA quality control is required for efficient activation of the TOR pathway regulator Gln3p

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    <p>The aminoacylation status of the cellular tRNA pool regulates both general amino acid control (GAAC) and target of rapamycin (TOR) stress response pathways in yeast. Consequently, fidelity of translation at the level of aminoacyl-tRNA synthesis plays a central role in determining accuracy and sensitivity of stress responses. To investigate effects of translational quality control (QC) on cell physiology under stress conditions, phenotypic microarray analyses were used to identify changes in QC deficient cells. Nitrogen source growth assays showed QC deficient yeast grew differently compared to WT. The QC deficient strain was more tolerant to caffeine treatment than wild type through altered interactions with the TOR and GAAC pathways. Increased caffeine tolerance of the QC deficient strain was consistent with the observation that the activity of Gln3p, a transcription factor controlled by the TOR pathway, is decreased in the QC deficient strain compared to WT. GCN4 translation, which is typically repressed in the absence of nutritional stress, was enhanced in the QC deficient strain through TOR inhibition. QC did not impact cell cycle regulation; however, the chronological lifespan of QC deficient yeast strains decreased compared to wild type, likely due to translational errors and alteration of the TOR-associated regulon. These findings support the idea that changes in translational fidelity provide a mechanism of cellular adaptation by modulating TOR activity. This, in turn, supports a central role for aminoacyl-tRNA synthesis QC in the integrated stress response by maintaining the proper aa-tRNA pools necessary to coordinate the GAAC and TOR.</p

    Data_Sheet_1_Oxidative stress strongly restricts the effect of codon choice on the efficiency of protein synthesis in Escherichia coli.PDF

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    IntroductionThe response of enterobacteria to oxidative stress is usually considered to be regulated by transcription factors such as OxyR and SoxR. Nevertheless, several reports have shown that under oxidative stress the levels, modification and aminoacylation of tRNAs may be altered suggesting a role of codon bias in regulation of gene expression under this condition.MethodsIn order to characterize the effects of oxidative stress on translation elongation we constructed a library of 61 plasmids, each coding for the green fluorescent protein (GFP) translationally fused to a different set of four identical codons.ResultsUsing these reporters, we observed that GFP production levels vary widely (~15 fold) when Escherichia coli K-12 is cultured in minimal media as a consequence of codon choice variations. When bacteria are cultured under oxidative stress caused by paraquat the levels of GFP produced by most clones is reduced and, in contrast to control conditions, the range of GFP levels is restricted to a ~2 fold range. Restricting elongation of particular sequences does not increase the range of GFP production under oxidative stress, but altering translation initiation rates leads to an increase in this range.DiscussionAltogether, our results suggest that under normal conditions the speed of translation elongation is in the range of the speed of initiation and, consequently, codon choice impacts the speed of protein synthesis. In contrast, under oxidative stress translation initiation becomes much slower than elongation, limiting the speed of translation such that codon choice has at most only subtle effects on the overall output of translation.</p

    Changes in gene expression due to the deletion of tRNA<sup>Other</sup>.

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    <p>Expression of genes in <i>B. cereus</i> Δ<i>tRNA<sup>Other</sup></i> reletive to wt grown in rich media (light green) and iron depleted media (dark green) was determined by qRT-PCR. Data presented in log<sub>2</sub>.</p

    Predicted interactions between tRNA<sup>Other</sup>-containing transcripts and putative mRNA targets.

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    <p>Target prediction parameters for <i>nos</i> (<b>A</b> and <b>B</b>) and <i>sod</i> (<b>C</b> and <b>D</b>) included terminator removal, a hybridization seed of 9, G:U basepairs included, and alignment score determined with a P-value set to 0.05 (<b>A</b> and <b>C</b>) or thermodynamic energy (<b>B</b> and <b>D</b>). Vertical lines (|) indicate a Watson-Crick base pair, and dots (<b>:</b>) indicate a G-U wobble base pair. The numbered nucleotide positions are relative to the start and stop codons for <i>sod</i> and <i>nos</i> mRNAs, respectively. Target prediction parameters for <i>cymR</i> included terminator removal, a hybridization seed of 8, and G:U basepairs included. Alignment was focused on the start codon (<b>E</b>), the stop codon (<b>F</b>), or the coding sequence (<b>G</b> and <b>H</b>). Alignment score was determined with a P-value set to 0.01 (<b>C</b>) or thermodynamic energy (<b>E</b>, <b>F</b> and <b>H</b>). Vertical lines (|) indicate a Watson-Crick base pair, and dots (<b>:</b>) indicate a G-U wobble base pair. The numbered nucleotide positions are relative to the start and stop codons for <i>cymR</i> mRNA. Ribosome-binding sites and start codons are underlined (note that <i>sod</i> and <i>cymR</i> homologue sequences are written 3′ to 5′. Targets were predicted using TargetRNA and sRNATarget.</p

    EF-P Dependent Pauses Integrate Proximal and Distal Signals during Translation

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    <div><p>Elongation factor P (EF-P) is required for the efficient synthesis of proteins with stretches of consecutive prolines and other motifs that would otherwise lead to ribosome pausing. However, previous reports also demonstrated that levels of most diprolyl-containing proteins are not altered by the deletion of <i>efp</i>. To define the particular sequences that trigger ribosome stalling at diprolyl (PPX) motifs, we used ribosome profiling to monitor global ribosome occupancy in <i>Escherichia coli</i> strains lacking EF-P. Only 2.8% of PPX motifs caused significant ribosomal pausing in the Δ<i>efp</i> strain, with up to a 45-fold increase in ribosome density observed at the pausing site. The unexpectedly low fraction of PPX motifs that produce a pause in translation led us to investigate the possible role of sequences upstream of PPX. Our data indicate that EF-P dependent pauses are strongly affected by sequences upstream of the PPX pattern. We found that residues as far as 3 codons upstream of the ribosomal peptidyl-tRNA site had a dramatic effect on whether or not a particular PPX motif triggered a ribosomal pause, while internal Shine Dalgarno sequences upstream of the motif had no effect on EF-P dependent translation efficiency. Increased ribosome occupancy at particular stall sites did not reliably correlate with a decrease in total protein levels, suggesting that in many cases other factors compensate for the potentially deleterious effects of stalling on protein synthesis. These findings indicate that the ability of a given PPX motif to initiate an EF-P-alleviated stall is strongly influenced by its local context, and that other indirect post-transcriptional effects determine the influence of such stalls on protein levels within the cell.</p></div

    Mapping of tRNA<sup>Other</sup>.

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    <p><b>A</b>, Putative promoter and Fur binding sites (DBTBS <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041248#pone.0041248-Sierro1" target="_blank">[28]</a>). Thioesterase indicates the ORF immediately 5′ of tRNA<sup>Other</sup>. <b>B</b>, 5′ and 3′ mapping by RACE. Circle with a vertical line at the bottom indicates an intrinsic terminator. Numbers indicate 5′ and 3′ nt relative to the originally predicted 5′-and 3′- ends of <i>tRNA<sup>Other</sup></i>.</p

    Transcript profiles of wt and <i>B. cereus</i> Δ<i>tRNA<sup>Other</sup></i>.

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    <p>Transcript level data is presented as the average of two microarrays. Each dot represents the transcript level for one gene. The three green lines, from top left to bottom right, indicate 2-fold higher, equal, and 2-fold lower transcript levels for Δ<i>tRNA<sup>Other</sup></i> relative to wt <i>B. cereus</i>. White dots represent transcripts with a significant 2-fold change or greater.</p

    EF-P dependent pauses that contain a PPX sequence.

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    *1<p>: Genes with a PPPX pattern are introduced twice to account for the ribosome density at P<sub>1</sub>P<sub>2</sub>P<sub>3</sub> and P<sub>2</sub>P<sub>3</sub>X.</p>*2<p>: Values correspond to averages of two independent samples.</p>*3<p>: Values from SILAC <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004553#pgen.1004553-Peil1" target="_blank">[10]</a>.</p

    Effect of upstream residues on the EF-P dependence of AtpD and AtpA synthesis.

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    <p><b>A</b>) Sequences (<i>Salmonella</i> Typhimurium) of AtpD and AtpA in proximity to their PPG motifs (bold). The relative position when the glycine of PPG occupies the A site is shown above. The amino acid position of the second proline of the PPG motif in each protein is indicated below. <b>B</b>) Fluorescence ratios comparing expression of plasmid-borne AtpD-GFP translational fusions in wild-type (WT) and <i>efp</i> mutant <i>Salmonella</i>. ‘Swap’ constructs indicate swap-in of AtpA sequence for the specified number of amino acids upstream of the PPG motif. LacZ, unmodified (wt), P214L and R279P constructs from <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004553#pgen-1004553-g004" target="_blank">Figure 4</a> are included for comparison. Ratios show WT/Δ<i>efp</i> for GFP fluorescence at 10 hours post-inoculation normalized to optical density (600 nm). The mean of at least three biological replicates is shown and error bars indicate one standard deviation. <b>C</b>) As in <b>B</b>, but with AtpA-GFP translational fusion constructs with swap-in of AtpD upstream sequence.</p

    Changes in transcript levels between wt and <i>B. cereus</i> Δ<i>tRNA<sup>Other</sup></i> during growth under moderate and low iron conditions.

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    *<p>Δ, <i>B. cereus</i> Δ<i>tRNA<sup>Other</sup></i>; wt, wild-type <i>B. cereus</i> ATCC14579.</p>‡<p>Negative control transcript levels were determined with a standard curve.</p
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