Cellular health and growth requires protein synthesis to be both efficient to ensure sufficient production, and accurate to avoid producing defective or unstable proteins. The background of misreading error frequency by individual tRNAs is as low as 2 × 10−6 per codon but is codon-specific with some error frequencies above 10−3 per codon. Here we test the effect on error frequency of blocking post-transcriptional modifications of the anticodon loops of four tRNAs in Escherichia coli. We find two types of responses to removing modification. Blocking modification of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\rm tRNA}_{{\rm UUC}}^{{\rm Glu}}$\end{document} and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\rm tRNA}^{\rm Asp}_{\rm QUC}$\end{document} increases errors, suggesting that the modifications act at least in part to maintain accuracy. Blocking even identical modifications of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\rm tRNA}^{\rm Lys}_{\rm UUU}$\end{document} and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\rm tRNA}^{\rm Tyr}_{\rm QUA}$\end{document} has the opposite effect of decreasing errors. One explanation could be that the modifications play opposite roles in modulating misreading by the two classes of tRNAs. Given available evidence that modifications help preorder the anticodon to allow it to recognize the codons, however, the simpler explanation is that unmodified ‘weak’ tRNAs decode too inefficiently to compete against cognate tRNAs that normally decode target codons, which would reduce the frequency of misreading.
Protein synthesis requires both high speed and accuracy to ensure a healthy cellular environment. Estimates of errors during protein synthesis in Saccharomyces cerevisiae have varied from 10−3 to 10−4 errors per codon. Here, we show that errors made by \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\rm{tRNA}}^{\rm Glu}_{\rm UUC}$\end{document} in yeast can vary 100-fold, from 10−6 to 10−4 errors per codon. The most frequent errors require a G•U mismatch at the second position for the near cognate codon GGA (Gly). We also show, contrary to our previous results, that yeast tRNAs can make errors involving mismatches at the wobble position but with low efficiency. We have also assessed the effect on misreading frequency of post-transcriptional modifications of tRNAs, which are known to regulate cognate codon decoding in yeast. We tested the roles of mcm5s2U34 and t6A37 and show that their effects depend on details of the codon anticodon interaction including the position of the modification with respect to the base mismatch and the nature of that mismatch. Both mcm5 and s2 modification of wobble uridine strongly stabilizes G2•U35 mismatches when \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\rm{tRNA}}^{\rm Glu}_{\rm UUC}$\end{document} misreads the GGA Gly codon but has weaker effects on other mismatches. By contrast, t6A37 destabilizes U1•U36 mismatches when \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\rm{tRNA}}^{\rm Lys}_{\rm UUU}$\end{document} misreads UAA or UAG but stabilizes mismatches at the second and wobble positions.
BackgroundA large number of Saccharomyces cerevisiae cellular factors modulate the movement of the retrovirus-like transposon Ty1. Surprisingly, a significant number of chromosomal genes required for Ty1 transposition encode components of the translational machinery, including ribosomal proteins, ribosomal biogenesis factors, protein trafficking proteins and protein or RNA modification enzymes.ResultsTo assess the mechanistic connection between Ty1 mobility and the translation machinery, we have determined the effect of these mutations on ribosome biogenesis and Ty1 transcriptional and post-transcriptional regulation. Lack of genes encoding ribosomal proteins or ribosome assembly factors causes reduced accumulation of the ribosomal subunit with which they are associated. In addition, these mutations cause decreased Ty1 + 1 programmed translational frameshifting, and reduced Gag protein accumulation despite at least normal levels of Ty1 mRNA. Several ribosome subunit mutations increase the level of both an internally initiated Ty1 transcript and its encoded truncated Gag-p22 protein, which inhibits transposition.ConclusionsTogether, our results suggest that this large class of cellular genes modulate Ty1 transposition through multiple pathways. The effects are largely post-transcriptional acting at a variety of levels that may include translation initiation, protein stability and subcellular protein localization.Electronic supplementary materialThe online version of this article (doi:10.1186/s13100-015-0053-5) contains supplementary material, which is available to authorized users.
Saccharomyces cerevisiae has been an important model for determining the frequency of translational misreading events, those in which a tRNA pairs incorrectly to the mRNA and inserts an amino acid not specified by the codon in the mRNA. Misreading errors have been quantified in vivo using reporter protein systems or mass spectrometry with both approaches converging on a simple model for most misreading. The available data show that misreading tRNAs must form stereotypical base mismatches that correspond to those that can mimic Watson–Crick base pairs when formed in the ribosomal A site. Errors involving other mismatches occur significantly less frequently. This work debunks the idea of an average misreading frequency of 5 × 10−4 per codon that extends across the genetic code. Instead, errors come in two distinct classes—high frequency and low frequency events—with most errors being of the low frequency type. A comparison of misreading errors in S. cerevisiae and Escherichia coli suggests the existence of a mechanism that reduces misreading frequency in yeast; this mechanism may operate in eukaryotes generally.
Background Comprehensive genomic profiling in NSCLC has become increasingly important for clinical management of advanced stage patients. Alteration status of EGFR, ALK, BRAF, and ROS1 are validated biomarkers linked to approved drugs, with many clinical trials enrolling on the basis of additional biomarkers, including Tumor Mutation Burden (TMB). It is therefore important to develop accurate and sensitive tools for tumor profiling, particularly in NSCLC where biopsy materials are limited. Here, we present results from ongoing analytical performance studies with the PGDx elio tissue complete - IUO assay, verifying our capabilities to accurately identify a range of genomic alteration types, comprising SNVs, indels, translocations, and TMB. Methods >300 specimens in NSCLC, comprising FFPE tissue and characterized cell lines were analyzed on our >500-gene targeted panel. Accuracy of the results were compared to orthogonal methods, such as whole exome sequencing (WES), IHC, FISH, and on-market IVD assays. Results were analyzed for the positive percent agreement (PPA) and negative percent agreement (NPA) for all variants assessed. Analytical studies were performed to assess the limit of blank, limit of detection, and repeatability for detection of these variants. Results Clinical FFPE and characterized cell line specimens (representing EGFR and BRAF SNVs, EGFR exon 19 deletions, and ALK and ROS1 translocations) were evaluated and demonstrated high concordance between PGDx elio tissue complete - IUO and orthogonal methods, with high PPA and NPA for SNV, indel, and translocation alterations analyzed. Repeatability studies demonstrated 100% PPA and 100% NPA for all variants assessed across operators, instruments, and days. The accuracy for panel-wide sequence mutations were assessed by comparing the results of >50 clinical samples (representing >500 SNVs and ~40 indels) run on PGDx elio tissue complete IUO and a validated NGS method, resulting in high PPA and NPA across all alterations analyzed. Reported alterations between PGDx elio tissue complete IUO and the independent NGS method displayed high sensitivity for analyzed SNVs (≥4% MAF) and indels (≥6% MAF). Finally, comparison of TMB results to WES data demonstrated TMB can be accurately and consistently reported from this panel, across a range of DNA inputs (50-200 ng) and tumor purities (10-30%). Conclusions The PGDx elio tissue complete - IUO >500-gene assay system, including our proprietary bioinformatics, provides accurate and reproducible results for the detection of clinically relevant genetic alterations in this NSCLC study. Further verification and validation studies of this gene panel are ongoing. The PGDx elio tissue complete assay will employ a decentralized, kitted model, increasing clinical accessibility to NGS and allow for delivery of highly accurate and timely results. Citation Format: Kelly Gerding, Laurel Keefer, Christine McCord, Amy Greer, Shantanu Shewale, Nicole Barkley, Eileen Sagini, Dorhyun Johng, Kenneth Valkenburg, Caitlin Gilley, Colby Ganey, Alvis Hu, Diandra Denier, Lorenzo Jones, Christina Oliveras, Gregory Joseph, Kartikeya Joshi, James Hernandez, Christopher Gault, Eniko Papp, Peibing Qin, Sonya Parpart-Li, James White, Mark Sausen, Siân Jones. Analytical performance of a comprehensive genomic profiling system to detect actionable genetic alterations in NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3534.
Introduction: Genomic analysis using next-generation sequencing (NGS) enables simultaneous detection of targetable alterations and biomarkers with emerging clinical utility in non-small cell lung cancer (NSCLC) patients. Importantly, many of these alterations are mutually exclusive and tumor tissue for molecular testing is often limited. As such, we developed PGDx elioTM tissue complete (ETC) as a comprehensive NGS assay capable of detecting somatic single nucleotide variants (SNVs), insertions and deletions (indels), amplifications, and rearrangements, as well as microsatellite stability (MSI) and tumor mutational burden (TMB). Here, we present the performance of this assay in detecting key clinical variants in NSCLC. Methods: Studies comprising >300 NSCLC specimens (FFPE tissue and characterized cell lines) were analyzed using ETC, a 500+ gene assay (under development), across key clinically relevant variants in NSCLC, including tumor mutation burden (TMB). Accuracy of the results were compared to orthogonal methods (e.g. whole-exome sequencing (WES), IHC, FISH) and analyzed for the overall percent agreement (OPA). Additionally, archival FFPE samples from 46 NSCLC patients previously found to harbor ALK translocations, MET amplifications, MET exon 14 skipping mutations, EGFR mutations, and/or ROS1 translocations were also analyzed. The results were compared to orthogonal methods and the overall genomic landscape evaluated. Results: Clinical FFPE and characterized cell line specimens were evaluated for the following alterations: EGFR mutations (L858R, T790M, and Exon 19 deletions), BRAF V600E mutations, and ALK and ROS1 translocations. Compared to orthogonal methods, the NGS assay demonstrated >93% OPA across all variants. Comparison of TMB results to WES data demonstrated high accuracy and precision, across a range of DNA inputs (50-200 ng) and tumor purities (10-30%). In the 46 retrospective NSCLC cases, the NGS assay identified 15 ALK translocations, 6 MET amplifications, 1 MET exon 14 skipping mutation, and 5 EGFR mutations, with most being mutually exclusive. The majority of cases were confirmed by orthogonal assays, with the few apparent discordances likely due to tumor heterogeneity, assay distinctions, or analyte input. Higher TMB was found in cases without targetable alterations. Conclusions: ETC provides accurate and reproducible results for the detection of clinically relevant alterations in NSCLC. Further verification and validation studies of this gene panel are ongoing. Overall NGS showed excellent concordance with orthogonal variant detection methods. Importantly, ETC demonstrated added value in assessing all genomic alteration types in a single assay, as well as reporting composite genomic scores, suggesting that NGS may offer a comprehensive solution to molecular testing. Citation Format: Elizabeth Weingartner, Kelly M.R. Gerding, Gustavo Cerquiera, Christopher Gault, James Hernandez, Kenneth Valkenburg, Laurel Keefer, Eileen Sagini, Dorhyun Johng, Caitlin Gilley, Colby Ganey, Leila Ettehadieh, Diandra Denier, Christina Oliveras, Kartikeya Joshi, Eric Kong, Eniko Papp, Amy Greer, James R. White, Donna Nichol, John Simmons. Comparison of a comprehensive NGS profiling assay and conventional molecular testing approaches for detection of clinically relevant alterations in NSCLC [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr B029. doi:10.1158/1535-7163.TARG-19-B029
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