Accurate transfer RNA (tRNA) aminoacylation by aminoacyl-tRNA synthetases controls translational fidelity. Although tRNA synthetases are generally highly accurate, recent results show that the methionyl-tRNA synthetase (MetRS) is an exception. MetRS readily misacylates non-methionyl tRNAs at frequencies of up to 10% in mammalian cells; such mismethionylation may serve a beneficial role for cells to protect their own proteins against oxidative damage. The Escherichia coli MetRS mismethionylates two E. coli tRNA species in vitro, and these two tRNAs contain identity elements for mismethionylation. Here we investigate tRNA mismethionylation in Saccharomyces cerevisiae. tRNA mismethionylation occurs at a similar extent in vivo as in mammalian cells. Both cognate and mismethionylated tRNAs have similar turnover kinetics upon cycloheximide treatment. We identify specific arginine/lysine to methionine-substituted peptides in proteomic mass spectrometry, indicating that mismethionylated tRNAs are used in translation. The yeast MetRS is part of a complex containing the anchoring protein Arc1p and the glutamyl-tRNA synthetase (GluRS). The recombinant Arc1p-MetRS-GluRS complex binds and mismethionylates many tRNA species in vitro. Our results indicate that the yeast MetRS is responsible for extensive misacylation of non-methionyl tRNAs, and mismethionylation also occurs in this evolutionary branch.

For cells to function properly the process of translating RNA messengers into proteins needs to be accurate, on the whole. Yet work in HeLa cells now shows that about 1% of methionine residues used in protein synthesis are aminoacylated to 'textbook-incorrect' tRNAs. Surprisingly, the proportion of Met-misacylated tRNAs increases significantly when cells are under stress through viral infection or treatment with viral or bacterial Toll-like receptor ligands. Tests with other amino acids indicate that the phenomenon is limited to Met, and as Met residues are known to protect proteins against damage from reactive oxygen species, one possibility is that Met-misacylation is a natural protective response to cellular stress. Accurate transfer RNA (tRNA) aminoacylation is necessary for translational fidelity; however, the accuracy of tRNA aminoacylation in vivo is uncertain. In mammalian cells, approximately 1% of methionine residues used in protein synthesis are now shown to be aminoacylated to non-methionyl-tRNAs. Furthermore, misacylation of methionine increases up to tenfold upon exposing cells to viruses, toll-like receptor ligands or oxidative stress. Translational fidelity, essential for protein and cell function, requires accurate transfer RNA (tRNA) aminoacylation. Purified aminoacyl-tRNA synthetases exhibit a fidelity of one error per 10,000 to 100,000 couplings1,2. The accuracy of tRNA aminoacylation in vivo is uncertain, however, and might be considerably lower3,4,5,6. Here we show that in mammalian cells, approximately 1% of methionine (Met) residues used in protein synthesis are aminoacylated to non-methionyl-tRNAs. Remarkably, Met-misacylation increases up to tenfold upon exposing cells to live or non-infectious viruses, toll-like receptor ligands or chemically induced oxidative stress. Met is misacylated to specific non-methionyl-tRNA families, and these Met-misacylated tRNAs are used in translation. Met-misacylation is blocked by an inhibitor of cellular oxidases, implicating reactive oxygen species (ROS) as the misacylation trigger. Among six amino acids tested, tRNA misacylation occurs exclusively with Met. As Met residues are known to protect proteins against ROS-mediated damage7, we propose that Met-misacylation functions adaptively to increase Met incorporation into proteins to protect cells against oxidative stress. In demonstrating an unexpected conditional aspect of decoding mRNA, our findings illustrate the importance of considering alternative iterations of the genetic code.

In multiple myeloma (MM), malignant plasma cells produce large amounts of antibodies and have highly active protein translational machinery. It is not known whether regulation of the abundance and aminoacylation (charging) of transfer RNA (tRNA) takes place in myeloma cells to accommodate for the increased amount of protein translation. Using tRNA-specific microarrays, we demonstrate that tRNA levels are significantly elevated in MM cell lines compared to normal bone marrow cells. We furthermore show that the addition of the proteasome inhibitor, bortezomib (Velcade™, PS-341) results in decreased charging levels of tRNAs, in particular those coding for hydrophobic amino acids. These results suggest that tRNA properties are altered in MM to accommodate for its increased need for protein translation, and that proteasome inhibition directly impacts protein synthesis in MM through effects on tRNA charging.

Over 450 transfer RNA (tRNA) genes have been annotated in the human genome. Reliable quantitation of tRNA levels in human samples using microarray methods presents a technical challenge. We have developed a microarray method to quantify tRNAs based on a fluorescent dye-labeling technique. The first-generation tRNA microarray consists of 42 probes for nuclear encoded tRNAs and 21 probes for mitochondrial encoded tRNAs. These probes cover tRNAs for all 20 amino acids and 11 isoacceptor families. Using this array, we report that the amounts of tRNA within the total cellular RNA vary widely among eight different human tissues. The brain expresses higher overall levels of nuclear encoded tRNAs than every tissue examined but one and higher levels of mitochondrial encoded tRNAs than every tissue examined. We found tissue-specific differences in the expression of individual tRNA species, and tRNAs decoding amino acids with similar chemical properties exhibited coordinated expression in distinct tissue types. Relative tRNA abundance exhibits a statistically significant correlation to the codon usage of a collection of highly expressed, tissue-specific genes in a subset of tissues or tRNA isoacceptors. Our findings demonstrate the existence of tissue-specific expression of tRNA species that strongly implicates a role for tRNA heterogeneity in regulating translation and possibly additional processes in vertebrate organisms.

We compare the diversity of chromosomal-encoded transfer RNA (tRNA) genes from 11 eukaryotes as identified by tRNAScan-SE of their respective genomes. They include the budding and fission yeast, worm, fruit fly, fugu, chicken, dog, rat, mouse, chimp and human. The number of tRNA genes are between 170 and 570 and the number of tRNA isoacceptors range from 41 to 55. Unexpectedly, the number of tRNA genes having the same anticodon but different sequences elsewhere in the tRNA body (defined here as tRNA isodecoder genes) varies significantly (10–246). tRNA isodecoder genes allow up to 274 different tRNA species to be produced from 446 genes in humans, but only up to 51 from 275 genes in the budding yeast. The fraction of tRNA isodecoder genes among all tRNA genes increases across the phylogenetic spectrum. A large number of sequence differences in human tRNA isodecoder genes occurs in the internal promoter regions for RNA polymerase III. We also describe a systematic, ligation-based method to detect and quantify tRNA isodecoder molecules in human samples, and show differential expression of three tRNA isodecoders in six human tissues. The large number of tRNA isodecoder genes in eukaryotes suggests that tRNA function may be more diverse than previously appreciated.

Asthma affects nearly 14 million people worldwide and has been steadily increasing in frequency for the past 50 years. Although environmental factors clearly influence the onset, progression, and severity of this disease, family and twin studies indicate that genetic variation also influences susceptibility. Linkage of asthma and related phenotypes to chromosome 6p21 has been reported in seven genome screens, making it the most replicated region of the genome. However, because many genes with individually small effects are likely to contribute to risk, identification of asthma susceptibility loci has been challenging. In this study, we present evidence from four independent samples in support of HLA-G as a novel asthma and bronchial hyperresponsiveness susceptibility gene in the human leukocyte antigen region on chromosome 6p21, and we speculate that this gene might contribute to risk for other inflammatory diseases that show linkage to this region.

Animal GeneticsVolume 35, Issue 2 p. 158-159 Linkage mapping of inhibitor of apoptosis protein-1 (IAP 1) to chicken chromosome 1 J. M. Goodenbour, J. M. Goodenbour Department of Animal Science, Iowa State University, Ames, Iowa 50011-3150, USASearch for more papers by this authorM. G. Kaiser, M. G. Kaiser Department of Animal Science, Iowa State University, Ames, Iowa 50011-3150, USASearch for more papers by this authorS. J. Lamont, S. J. Lamont Department of Animal Science, Iowa State University, Ames, Iowa 50011-3150, USASearch for more papers by this author J. M. Goodenbour, J. M. Goodenbour Department of Animal Science, Iowa State University, Ames, Iowa 50011-3150, USASearch for more papers by this authorM. G. Kaiser, M. G. Kaiser Department of Animal Science, Iowa State University, Ames, Iowa 50011-3150, USASearch for more papers by this authorS. J. Lamont, S. J. Lamont Department of Animal Science, Iowa State University, Ames, Iowa 50011-3150, USASearch for more papers by this author First published: 17 March 2004 https://doi.org/10.1111/j.1365-2052.2004.01111.xCitations: 1 Dr Susan J. Lamont ([email protected]) Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. References 1 Yang Y. L. & Li X. M. (2000) Cell Res. 10, 169–77. 2 Zhou H. et al. (2001) Poult. Sci. 80, 284–8. 3 Crittenden L. B. et al. (1993) Poult. Sci. 72, 334–48. 4 Manly K. F. et al. (2001) Mamm. Genome 12, 930–2. 5 Rajcan-Separovic E. et al. (1996) Genomics 37, 404–6. 6 Liston P. et al. (1997) Genomics 46, 495–503. 7 Liu W. & Lamont S. J. (2003) Anim. Biotech. 14, 61–76. 8 Zhou H. & Lamont S. J. (2003) Poult. Sci. 82, 1118–26. 9 Kaiser M. G. & Lamont S. J. (2002) Poult. Sci. 81, 657–63. 10 Kaiser M. G. et al. (2002) Poult. Sci. 81, 193–201. Citing Literature Volume35, Issue2April 2004Pages 158-159 ReferencesRelatedInformation