18 research outputs found

    Differential Regulation of Two Arms of mTORC1 Pathway Fine-Tunes Global Protein Synthesis in Resting B Lymphocytes

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    Protein synthesis is tightly regulated by both gene-specific and global mechanisms to match the metabolic and proliferative demands of the cell. While the regulation of global protein synthesis in response to mitogen or stress signals is relatively well understood in multiple experimental systems, how different cell types fine-tune their basal protein synthesis rate is not known. In a previous study, we showed that resting B and T lymphocytes exhibit dramatic differences in their metabolic profile, with implications for their post-activation function. Here, we show that resting B cells, despite being quiescent, exhibit increased protein synthesis in vivo as well as ex vivo. The increased protein synthesis in B cells is driven by mTORC1, which exhibits an intermediate level of activation in these cells when compared with resting T cells and activated B cells. A comparative analysis of the transcriptome and translatome of these cells indicates that the genes encoding the MHC Class II molecules and their chaperone CD74 are highly translated in B cells. These data suggest that the translatome of B cells shows enrichment for genes associated with antigen processing and presentation. Even though the B cells exhibit higher mTORC1 levels, they prevent the translational activation of TOP mRNAs, which are mostly constituted by ribosomal proteins and other translation factors, by upregulating 4EBP1 levels. This mechanism may keep the protein synthesis machinery under check while enabling higher levels of translation in B cells

    Factors That Shape Eukaryotic tRNAomes:  Processing, Modification and Anticodon–Codon Use

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    Transfer RNAs (tRNAs) contain sequence diversity beyond their anticodons and the large variety of nucleotide modifications found in all kingdoms of life. Some modifications stabilize structure and fit in the ribosome whereas those to the anticodon loop modulate messenger RNA (mRNA) decoding activity more directly. The identities of tRNAs with some universal anticodon loop modifications vary among distant and parallel species, likely to accommodate fine tuning for their translation systems. This plasticity in positions 34 (wobble) and 37 is reflected in codon use bias. Here, we review convergent evidence that suggest that expansion of the eukaryotic tRNAome was supported by its dedicated RNA polymerase III transcription system and coupling to the precursor‐tRNA chaperone, La protein. We also review aspects of eukaryotic tRNAome evolution involving G34/A34 anticodon‐sparing, relation to A34 modification to inosine, biased codon use and regulatory information in the redundancy (synonymous) component of the genetic code. We then review interdependent anticodon loop modifications involving position 37 in eukaryotes. This includes the eukaryote‐specific tRNA modification, 3‐methylcytidine‐32 (m3C32) and the responsible gene, TRM140 and homologs which were duplicated and subspecialized for isoacceptor‐specific substrates and dependence on i6A37 or t6A37. The genetics of tRNA function is relevant to health directly and as disease modifiers

    Codon optimality has minimal effect on determining translation efficiency in mycobacterium tuberculosis

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    Abstract Mycobacterium tuberculosis (Mtb) is a slow-growing, intracellular pathogen that exhibits a high GC-rich genome. Several factors, including the GC content of the genome, influence the evolution of specific codon usage biases in genomes. As a result, the Mtb genome exhibits strong biases for amino acid usage and codon usage. Codon usage of mRNAs affects several aspects of translation, including accuracy, efficiency, and protein folding. Here we address the effect of codon usage biases in determining the translation efficiency of mRNAs in Mtb. Unlike most commonly studied organisms, Mtb carries a single copy of each tRNA gene. However, we show that the relative levels of tRNAs in the Mtb tRNA pool vary by an order of magnitude. Our results show that the codons decoded by the abundant tRNAs indeed show higher adaptability. Moreover, there is a general positive correlation between genomic codon usage and the tRNA adaptability of codons (TAc). We further estimated the optimality of the codon and mRNAs by considering both the TAc and the tRNA demand. These measures did not show any correlation with mRNA abundance and translation efficiency. There was no correlation between tRNA adaptability and ribosome pausing as well. Taken together, we conclude that the translation machinery, and the tRNA pool of an organism, co-evolve with the codon usage to optimize the translation efficiency of an organism. Thus the deleterious effect of maladapted codons is not pronounced

    RNA Polymerase III Output Is Functionally Linked to tRNA Dimethyl-G26 Modification

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    <div><p>Control of the differential abundance or activity of tRNAs can be important determinants of gene regulation. RNA polymerase (RNAP) III synthesizes all tRNAs in eukaryotes and it derepression is associated with cancer. Maf1 is a conserved general repressor of RNAP III under the control of the target of rapamycin (TOR) that acts to integrate transcriptional output and protein synthetic demand toward metabolic economy. Studies in budding yeast have indicated that the global tRNA gene activation that occurs with derepression of RNAP III via <i>maf1-</i>deletion is accompanied by a paradoxical loss of tRNA-mediated nonsense suppressor activity, manifested as an antisuppression phenotype, by an unknown mechanism. We show that <i>maf1</i>-antisuppression also occurs in the fission yeast <i>S</i>. <i>pombe</i> amidst general activation of RNAP III. We used tRNA-HydroSeq to document that little changes occurred in the relative levels of different tRNAs in <i>maf1Δ</i> cells. By contrast, the efficiency of <i>N2</i>,<i>N2</i>-dimethyl G26 (m<sup><b>2</b></sup><sub><b>2</b></sub>G26) modification on certain tRNAs was decreased in response to <i>maf1</i>-deletion and associated with antisuppression, and was validated by other methods. Over-expression of Trm1, which produces m<sup><b>2</b></sup><sub><b>2</b></sub>G26, reversed <i>maf1-</i>antisuppression. A model that emerges is that competition by increased tRNA levels in <i>maf1Δ</i> cells leads to m<sup><b>2</b></sup><sub><b>2</b></sub>G26 hypomodification due to limiting Trm1, reducing the activity of suppressor-tRNASerUCA and accounting for antisuppression. Consistent with this, we show that RNAP III mutations associated with hypomyelinating leukodystrophy decrease tRNA transcription, increase m<sup><b>2</b></sup><sub><b>2</b></sub>G26 efficiency and reverse antisuppression. Extending this more broadly, we show that a decrease in tRNA synthesis by treatment with rapamycin leads to increased m<sup><b>2</b></sup><sub><b>2</b></sub>G26 modification and that this response is conserved among highly divergent yeasts and human cells.</p></div

    M<sup>2</sup><sub>2</sub>G26 is regulated by nutrient/growth conditions.

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    <p><b>A)</b> Box plot showing G26 misincorporation levels in WT cells grown in minimal (EMM), rich (YES) media, and <i>trm1</i><sup><b><i>+</i></b></sup> over-expression (<i>trm1Δ</i>+<i>trm1</i><sup><b><i>+</i></b></sup>) in EMM as indicated (*paired student t test p value <0.001 relative to WT-EMM). <b>B)</b> Bar graph showing G26 misincorporation levels in WT cells in minimal (EMM) and rich (YES) media and +<i>trm1</i><sup><b><i>+</i></b></sup> over-expression in EMM. <b>C)</b> PHA26 assay for tRNAThrCGT in minimal (EMM) and rich (YES) media. <b>D)</b> Western blot analysis for Trm1 in WT cells in minimal (EMM) and rich (YES) media (lanes 1, 2), and +<i>trm1</i><sup><b><i>+</i></b></sup> over-expression in EMM (lane 3), as well as <i>maf11Δ</i>+<i>trm1</i><sup><b><i>+</i></b></sup> in EMM (lane 4); tubulin serves as a loading control. <b>E)</b> TMS assay for various strains in +/- rapamycin as indicated to the right. <b>F)</b> Western blot analysis for Trm1 in +/- rapamycin as indicated above the lanes; tubulin serves as a loading control. <b>G)</b> PHA26 assay on various strains in +/- rapamycin as indicated above the lanes.</p

    The m<sup>2</sup><sub>2</sub>G26 modification efficiency response is conserved in <i>S</i>. <i>cerevisiae</i> and human cells.

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    <p><b>A)</b> PHA26 assay of <i>S</i>. <i>cerevisiae maf1Δ</i> and WT (<i>MAF1</i>) cells. <b>B)</b> TMS assay shows that over-expression of <i>TRM1</i> reverses antisuppression phenotype of <i>S</i>. <i>cerevisiae maf1Δ</i> cells. <b>C)</b> PHA26 assay of human embryonic kidney (HEK) 293 cells grown for a period of serum starvation or after serum replenishment as indicated above the lanes. <b>D)</b> PHA26 assay of HEK293 cells in the presence or absence of rapamycin. Quantitative modification indices are shown for panels A, C and D, described as for <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005671#pgen.1005671.g004" target="_blank">Fig 4D</a>.</p

    Lack of i6A37 is not responsible for <i>maf1-</i>antisuppression phenotype.

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    <p><b>A)</b> tRNA mediated suppression (TMS) in WT (wild-type, i.e., <i>maf1</i><sup><b><i>+</i></b></sup>), <i>tit1Δ</i> (lacking the tRNA A37-isopentenyltransferase-1 gene, <i>tit1</i><sup><b><i>+</i></b></sup>, see text) and <i>maf1Δ</i> cells in excess or limiting adenine (Ade200 vs. Ade10; 200 vs. 10 mg/L, respectively); transformed with empty vector (+ev) or expression vector for <i>maf1</i><sup><b><i>+</i></b></sup>. <b>B)</b> Midwestern blotting of RNA from <i>maf1</i><sup><b><i>+</i></b></sup> and <i>maf1Δ</i> cells using anti-i6A antibody, and subsequent probing for U5 snRNA as loading control. <b>C)</b> Monitoring <i>in vivo</i> i6A37 level by PHA6 (<u>p</u>ositive <u>h</u>ybridization in the <u>a</u>bsence of i<u>6</u>A modification, see text) assay in sup-tRNASerUCA (sup-tRNA) and other RNA as indicated. 1X, 2X = 5, 10 ug total RNA. <b>D)</b> Graphic plot of quantification efficiencies in the three <i>S</i>. <i>pombe</i> strains: % modification = [1− (ACL<i>tit1</i><sup><b><i>+</i></b></sup>/BP<i>tit1</i><sup><b><i>+</i></b></sup>)/(ACL<i>tit1Δ/</i>BP<i>tit1Δ</i>)] X 100. ACL, anticodon loop probe; BP, body probe. <b>E)</b> Quantification of steady state levels of the sup-tRNASerUCA and tRNASerUGA examined in panel C. <b>D & E:</b> Error bars reflect standard deviations for three experiments.</p
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