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Comparative tRNA sequencing and RNA mass spectrometry for surveying tRNA modifications

Nature Chemical Biology volume 16, pages 964–972 (2020)Cite this article

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Abstract

Chemical modifications of the nucleosides that comprise transfer RNAs are diverse. However, the structure, location and extent of modifications have been systematically charted in very few organisms. Here, we describe an approach in which rapid prediction of modified sites through reverse transcription-derived signatures in high-throughput transfer RNA-sequencing (tRNA-seq) data is coupled with identification of tRNA modifications through RNA mass spectrometry. Comparative tRNA-seq enabled prediction of several Vibrio cholerae modifications that are absent from Escherichia coli and also revealed the effects of various environmental conditions on V. cholerae tRNA modification. Through RNA mass spectrometric analyses, we showed that two of the V. cholerae-specific reverse transcription signatures reflected the presence of a new modification (acetylated acp3U (acacp3U)), while the other results from C-to-Ψ RNA editing, a process not described before. These findings demonstrate the utility of this approach for rapid surveillance of tRNA modification profiles and environmental control of tRNA modification.

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Fig. 1: Profiling tRNA modifications in V. cholerae through tRNA-seq.
Fig. 2: Frequency of acp3U is dependent on growth phase.
Fig. 3: Structure of acacp3U.
Fig. 4: Biogenesis and function of acacp3U.
Fig. 5: Cytidine at position 32 in tRNA-Tyr undergoes C-to-Ψ RNA editing.

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Data availability

All data is available from the corresponding authors upon request. The data reported in this paper have been deposited in the NCBI Gene expression omnibus https://www.ncbi.nlm.nih.gov/geo/ (accession code, GSE147614). Source data for Figs. 1, 2 and 4 and Extended Data Figs. 1–5 are presented with the paper.

Code availability

All codes are available from the corresponding authors upon request.

References

  1. Gingold, H. et al. A dual program for translation regulation in cellular proliferation and differentiation. Cell 158, 1281–1292 (2014).

    CAS  PubMed  Google Scholar 

  2. Goodarzi, H. et al. Modulated expression of specific tRNAs drives gene expression and cancer progression. Cell 165, 1416–1427 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Hanada, T. et al. CLP1 links tRNA metabolism to progressive motor-neuron loss. Nature 495, 474–480 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Machnicka, M. A. et al. MODOMICS: a database of RNA modification pathways–2013 update. Nucleic Acids Res. 41, D262–D267 (2013).

    CAS  PubMed  Google Scholar 

  5. Ontiveros, R. J., Stoute, J. & Liu, K. F. The chemical diversity of RNA modifications. Biochem. J. 476, 1227–1245 (2019).

    CAS  PubMed  Google Scholar 

  6. Cantara, W. A. et al. The RNA modification database, RNAMDB: 2011 update. Nucleic Acids Res. 39, D195–D201 (2011).

    CAS  PubMed  Google Scholar 

  7. Eisenberg, E. & Levanon, E. Y. A-to-I RNA editing—immune protector and transcriptome diversifier. Nat. Rev. Genet. 19, 473–490 (2018).

    CAS  PubMed  Google Scholar 

  8. Bjork, G. R. & Hagervall, T. G. Transfer RNA modification: presence, synthesis, and function. EcoSal Plus 6, https://doi.org/10.1128/ecosalplus.ESP-0007-2013 (2014).

  9. Duechler, M., Leszczynska, G., Sochacka, E. & Nawrot, B. Nucleoside modifications in the regulation of gene expression: focus on tRNA. Cell Mol. Life Sci. 73, 3075–3095 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Kimura, S. & Waldor, M. K. The RNA degradosome promotes tRNA quality control through clearance of hypomodified tRNA. Proc. Natl Acad. Sci. USA 116, 1394–1403 (2019).

    CAS  PubMed  Google Scholar 

  11. Lorenz, C., Lunse, C. E. & Morl, M. tRNA modifications: impact on structure and thermal adaptation. Biomolecules 7, https://doi.org/10.3390/biom7020035 (2017).

  12. Alexandrov, A. et al. Rapid tRNA decay can result from lack of nonessential modifications. Mol. Cell 21, 87–96 (2006).

    CAS  PubMed  Google Scholar 

  13. Vecerek, B., Moll, I. & Blasi, U. Control of fur synthesis by the non-coding RNA RyhB and iron-responsive decoding. EMBO J. 26, 965–975 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Chionh, Y. H. et al. tRNA-mediated codon-biased translation in mycobacterial hypoxic persistence. Nat. Commun. 7, 13302 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Schwartz, M. H. et al. Microbiome characterization by high-throughput transfer RNA sequencing and modification analysis. Nat. Commun. 9, 5353 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Laxman, S. et al. Sulfur amino acids regulate translational capacity and metabolic homeostasis through modulation of tRNA thiolation. Cell 154, 416–429 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Wetzel, C. & Limbach, P. A. Mass spectrometry of modified RNAs: recent developments. Analyst 141, 16–23 (2016).

    CAS  PubMed  Google Scholar 

  18. Antoine, L., Wolff, P., Westhof, E., Romby, P. & Marzi, S. Mapping post-transcriptional modifications in Staphylococcus aureus tRNAs by nanoLC/MSMS. Biochimie 164, 60–69 (2019).

    CAS  PubMed  Google Scholar 

  19. Suzuki, T. & Suzuki, T. A complete landscape of post-transcriptional modifications in mammalian mitochondrial tRNAs. Nucleic Acids Res. 42, 7346–7357 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Cozen, A. E. et al. ARM-seq: AlkB-facilitated RNA methylation sequencing reveals a complex landscape of modified tRNA fragments. Nat. Methods 12, 879–884 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Zheng, G. et al. Efficient and quantitative high-throughput tRNA sequencing. Nat. Methods 12, 835–837 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Richter, U. et al. RNA modification landscape of the human mitochondrial tRNA(Lys) regulates protein synthesis. Nat. Commun. 9, 3966 (2018).

    PubMed  PubMed Central  Google Scholar 

  23. Ryvkin, P. et al. HAMR: high-throughput annotation of modified ribonucleotides. RNA 19, 1684–1692 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Clark, W. C., Evans, M. E., Dominissini, D., Zheng, G. & Pan, T. tRNA base methylation identification and quantification via high-throughput sequencing. RNA 22, 1771–1784 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Helm, M. & Motorin, Y. Detecting RNA modifications in the epitranscriptome: predict and validate. Nat. Rev. Genet. 18, 275–291 (2017).

    CAS  PubMed  Google Scholar 

  26. Marchand, V. et al. AlkAniline-Seq: profiling of m(7) G and m(3) C RNA modifications at single nucleotide resolution. Angew. Chem. Int. Ed. Engl. 57, 16785–16790 (2018).

    CAS  PubMed  Google Scholar 

  27. Juhling, F. et al. tRNAdb 2009: compilation of tRNA sequences and tRNA genes. Nucleic Acids Res. 37, D159–D162 (2009).

    PubMed  Google Scholar 

  28. Roovers, M. et al. The YqfN protein of Bacillus subtilis is the tRNA: m1A22 methyltransferase (TrmK). Nucleic Acids Res. 36, 3252–3262 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Ritchie, J. M., Rui, H., Bronson, R. T. & Waldor, M. K. Back to the future: studying cholera pathogenesis using infant rabbits. mBio 1, https://doi.org/10.1128/mBio.00047-10 (2010).

  30. Patiny, L. & Borel, A. ChemCalc: a building block for tomorrow’s chemical infrastructure. J. Chem. Inf. Model. 53, 1223–1228 (2013).

    CAS  PubMed  Google Scholar 

  31. Galperin, M. Y., Makarova, K. S., Wolf, Y. I. & Koonin, E. V. Expanded microbial genome coverage and improved protein family annotation in the COG database. Nucleic Acids Res. 43, D261–D269 (2015).

    CAS  PubMed  Google Scholar 

  32. Cameron, D. E., Urbach, J. M. & Mekalanos, J. J. A defined transposon mutant library and its use in identifying motility genes in Vibrio cholerae. Proc. Natl Acad. Sci. USA 105, 8736–8741 (2008).

    CAS  PubMed  Google Scholar 

  33. Finn, R. D. et al. The Pfam protein families database: towards a more sustainable future. Nucleic Acids Res. 44, D279–D285 (2016).

    CAS  PubMed  Google Scholar 

  34. Chan, P. P. & Lowe, T. M. GtRNAdb 2.0: an expanded database of transfer RNA genes identified in complete and draft genomes. Nucleic Acids Res. 44, D184–D189 (2016).

    CAS  PubMed  Google Scholar 

  35. Wrzesinski, J., Nurse, K., Bakin, A., Lane, B. G. & Ofengand, J. A dual-specificity pseudouridine synthase: an Escherichia coli synthase purified and cloned on the basis of its specificity for psi 746 in 23S RNA is also specific for psi 32 in tRNA(phe). RNA 1, 437–448 (1995).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Takakura, M., Ishiguro, K., Akichika, S., Miyauchi, K. & Suzuki, T. Biogenesis and functions of aminocarboxypropyluridine in tRNA. Nat. Commun. 10, 5542 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Meyer, B. et al. Identification of the 3-amino-3-carboxypropyl (acp) transferase enzyme responsible for acp3U formation at position 47 in Escherichia coli tRNAs. Nucleic Acids Res. 48, 1435–1450 (2019).

    PubMed Central  Google Scholar 

  38. Nakahama, T. & Kawahara, Y. Adenosine-to-inosine editing in the immune system: friend or foe?. Cell Mol. Life Sci. 661, https://doi.org/10.1007/s00018-020-03466-2 (2020).

  39. Dixit, S., Henderson, J. C. & Alfonzo, J. D. Multi-substrate specificity and the evolutionary basis for interdependence in tRNA editing and methylation enzymes. Front Genet 10, 104 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Lerner, T., Papavasiliou, F. N. & Pecori, R. RNA editors, cofactors, and mRNA targets: an overview of the C-to-U RNA editing machinery and its implication in human disease. Genes 10, https://doi.org/10.3390/genes10010013 (2018).

  41. Small, I. D., Schallenberg-Rudinger, M., Takenaka, M., Mireau, H. & Ostersetzer-Biran, O. Plant organellar RNA editing: what 30 years of research has revealed. Plant J. 101, 1040–1056 (2019).

    PubMed  Google Scholar 

  42. Randau, L. et al. A cytidine deaminase edits C to U in transfer RNAs in archaea. Science 324, 657–659 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Rubio, M. A. et al. Editing and methylation at a single site by functionally interdependent activities. Nature 542, 494–497 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Millet, Y. A. et al. Insights into Vibrio cholerae intestinal colonization from monitoring fluorescently labeled bacteria. PLoS Pathog. 10, e1004405 (2014).

    PubMed  PubMed Central  Google Scholar 

  45. Donnenberg, M. S. & Kaper, J. B. Construction of an eae deletion mutant of enteropathogenic Escherichia coli by using a positive-selection suicide vector. Infect. Immun. 59, 4310–4317 (1991).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009).

    PubMed  PubMed Central  Google Scholar 

  47. Griffey, R. H. et al. 15N-labeled tRNA. Identification of 4-thiouridine in Escherichia coli tRNASer1 and tRNATyr2 by 1H-15N two-dimensional NMR spectroscopy. J. Biol. Chem. 261, 12074–12078 (1986).

    CAS  PubMed  Google Scholar 

  48. Horie, N. et al. Modified nucleosides in the first positions of the anticodons of tRNA(Leu)4 and tRNA(Leu)5 from Escherichia coli. Biochemistry 38, 207–217 (1999).

    CAS  PubMed  Google Scholar 

  49. Salazar, J. C., Ambrogelly, A., Crain, P. F., McCloskey, J. A. & Soll, D. A truncated aminoacyl-tRNA synthetase modifies RNA. Proc. Natl Acad. Sci. USA 101, 7536–7541 (2004).

    CAS  PubMed  Google Scholar 

  50. Bjork, G. R. & Hagervall, T. G. Transfer RNA Modification. EcoSal Plus 1, https://doi.org/10.1128/ecosalplus.4.6.2 (2005).

  51. Miyauchi, K., Kimura, S. & Suzuki, T. A cyclic form of N6-threonylcarbamoyladenosine as a widely distributed tRNA hypermodification. Nat. Chem. Biol. 9, 105–111 (2013).

    CAS  PubMed  Google Scholar 

  52. Rodriguez-Hernandez, A. et al. Structural and mechanistic basis for enhanced translational efficiency by 2-thiouridine at the tRNA anticodon wobble position. J. Mol. Biol. 425, 3888–3906 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Sakai, Y., Miyauchi, K., Kimura, S. & Suzuki, T. Biogenesis and growth phase-dependent alteration of 5-methoxycarbonylmethoxyuridine in tRNA anticodons. Nucleic Acids Res. 44, 509–523 (2016).

    CAS  PubMed  Google Scholar 

  54. Sakai, Y., Kimura, S. & Suzuki, T. Dual pathways of tRNA hydroxylation ensure efficient translation by expanding decoding capability. Nat. Commun. 10, 2858 (2019).

    PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank V. Srisuknimit, B. Davis, T. Hubbard and Waldor laboratory members for helpful comments on the project, the manuscript, the Harvard Medical School East Quad NMR Facility for assistance with nuclear magnetic resonance, the Harvard Medical School Analytical Chemistry Core for use of the QTOF mass spectrometer and the Harvard FAS Science Core Facility for use of the MALDI equipment. This work was supported by NIH R01-AI-042347 (M.K.W.), HHMI (M.K.W.), NIH R01-ES026856 (P.C.D.), R01-ES024615 (P.C.D.) and National Research Foundation of Singapore through the Singapore-MI Alliance for Research and Technology Antimicrobial Resistance Interdisciplinary Research Group (P.C.D.).

Author information

Authors and Affiliations

  1. Division of Infectious Diseases, Brigham and Women’s Hospital, Boston, MA, USA

    Satoshi Kimura & Matthew K. Waldor

  2. Department of Microbiology, Harvard Medical School, Boston, MA, USA

    Satoshi Kimura & Matthew K. Waldor

  3. Howard Hughes Medical Institute, Boston, MA, USA

    Satoshi Kimura & Matthew K. Waldor

  4. Department of Biological Engineering, Massachusetts Institution of Technology, Cambridge, MA, USA

    Peter C. Dedon

  5. Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore, Singapore

    Peter C. Dedon

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Contributions

S.K. and M.K.W. designed the research. S.K. performed all experiments and analyzed data. M.K.W. and P.C.D. discussed the results. S.K. and M.K.W. wrote the paper.

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Correspondence to Satoshi Kimura or Matthew K. Waldor.

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Extended data

Extended Data Fig. 1 tRNA-seq profiling of tRNA modifications in E. coli.

a, Example of the analysis of reverse transcription derived signatures in tRNA-seq data. The bars in the left panel represent mapped read depth with the left side and right side corresponding to the 5′ and 3′ end of tRNAs, respectively. Bars in which the misincorporation frequency is less than 1% are colored in grey; additional colors are shown at sites where there are higher levels of misincorporation (red corresponds to U, blue, C, orange, G and yellow, A). The importance of the misincorporation signal at position 10 is not known. Several drops in depth around sites of known modifications are also apparent (for example DD at positions 16, 17); however, the correspondence between the decrease in read depth and sites of modification is less precise than with nucleotide misincorporation. The right panel shows the secondary structure of tRNA-Lys. The structures of some of the modifications that lead to reverse transcription derived signatures are shown in lower panels. b, Heatmaps of the frequency of misincorporation (left) and stop (termination) of reverse transcription (right) signals in tRNA from stationary phase E. coli. Each row represents an individual tRNA and each column represents a position within tRNAs. The modifications are assigned based on the reference tRNA sequences (Supplementary Data 1 and Supplementary Table 1). The color keys indicated above upper right corners of the heatmaps correspond to the frequencies of misincorporation and termination. Representative data from one replicate is shown.

Source data

Extended Data Fig. 2 Validation of modifications inferred from RT-derived signals by nucleoside analysis.

Nucleosides from purified tRNAs were analyzed by mass spectrometry. The area values of a nucleoside was normalized using the signal of T, which is present in all tRNA species as an internal control. The values relative to the maximum number across the nine tRNA species are shown in the heatmap. Glu-Q was not observed in any tRNAs. The presence of most of the modifications were also confirmed in the fragment analyses except for Q in tRNA-Tyr, s2C and I in tRNA-Arg2A, and Ψ (Supplementary Data 3). This experiment was performed once.

Source data

Extended Data Fig. 3 Validation of modifications inferred from RT-derived signals using mutant V. cholerae strains.

a, Heatmap of misincorporation frequency at position 8 in V. cholerae tRNAs. Most of the misincorporation signals, except for tRNA-Ser1 and tRNA-Gln1A, are eliminated in the ΔthiI strain, consistent with the idea that misincorporation results from the associated modification, s4U. The data for tRNA-Ile2 is not shown (black) because of insufficient read depth (<100 reads). b, Heatmap of misincorporation frequency at position 32 in V. cholerae tRNAs. The signals in tRNAs that are expected to have s2C (tRNA-Arg2A, tRNA-Arg2C, tRNA-Arg3, tRNA-Ser3A, tRNA-Ser3B, and tRNA-Arg4) are eliminated in the ΔttcA strain, whereas the signal in tRNA-Tyr remains due to C to Ψ RNA editing (see Fig 5). The data for tRNA-Ile2 is not shown (black) because of insufficient read depth. c, Heatmap of misincorporation frequency at position 37 in V. cholerae tRNAs. The signals in tRNAs that are expected to have ms2io6A (tRNA-Leu5, tRNA-Phe1, tRNA-Phe2, tRNA-Leu4, tRNA-Trp, tRNA-Cys1, tRNA-Cys2, tRNA-Ser1, and tRNA-Tyr) are eliminated in the ΔmiaA strain, whereas the signals in tRNA species that are predicted to have m1G at position 37 remain. d, Heatmap of misincorporation frequency at position 22 in V. cholerae tRNAs. The signal in tRNA-Tyr was absent in the ΔtrmK strain, suggesting that this signal is derived from m1A. The data for tRNA-Ile2 is not shown (black) because of insufficient read depth. In all panels, representative data from three replicates with similar results for WT and one replicate for knockout strains is shown.

Source data

Extended Data Fig. 4 tRNA-seq profiles of log phase (a) and cecal fluid-derived (b)V. cholerae.

Heatmaps of frequency of misincorporation (left) and termination of reverse transcription (right) signals in indicated samples. Types and positions of modifications that are presumed shared with E. coli are shown in black. Positions of V. cholerae-specific signals are indicated in white letters. Representative data from three replicates with similar results is shown.

Source data

Extended Data Fig. 5 VC0317 is a candidate acetyltransferase required for acacp3U synthesis.

Nucleoside analysis of total tRNAs derived from strains containing transposon insertions in putative acetyltransferases. Relative abundances of acacp3U (a) and acp3U (b), normalized to that of T, are shown. This experiment was performed once.

Source data

Extended Data Fig. 6 Nucleoside analysis of tRNA-Tyr from the Δvc1231 strain RNA cultured with stable isotope labeled cytidine (15N3-C) or unlabeled cytidine (non-SI).

The detecting bases are shown on the left of panels. Representative data from two independent experiments with similar results for G, A, and T is shown. Experiments for other nucleosides were performed once.

Extended Data Fig. 7 RNA mass spectrometric analyses of tRNA-Tyr.

a, Nucleoside analysis detecting D, Ψ, m1A, T, oQ, Q, s4U, ms2io6A. The peak heights between different nucleosides are not comparable. Representative data from two independent experiments with similar results is shown. b, Fragment analyses of RNase T1 (left) and RNase A (right) digests. The fragments with or without modifications are shown in red and black, respectively. Measurement was conducted in positive polarity mode. Representative data from two independent experiments with similar results is shown.

Supplementary information

Supplementary information

Supplementary Figs. 1–9, Tables 1 and 2, Synthetic procedures and references

Reporting Summary

Supplementary Data

Supplementary Datasets. Supplementary Data 1. Reference E. coli tRNA sequences with modifications. tRNA sequences were retrieved from tRNAdb and partial or full sequences were changed or added based on the literature. Bold letters indicate the changes and addition of sequences based on references. Supplementary Data 2. Conservation of tRNA modification enzymes between V. cholerae and E. coli. Supplementary Data 3. Primary sequences of V. cholerae tRNAs with modifications The nucleosides that were detected in the RNase T1 (top rows), RNase A (middle rows) and either RNase (bottom rows) fragment analyses of digests are colored in black. The abbreviation of nucleosides is shown on the right. Supplementary Data 4. Parameters of mass spectrometry for dynamic MRM analyses. Supplementary Data 5. Comparative genomics for narrowing down candidate acetyltransferases required for acacp3U biogenesis. Putative acetyltransferases in V. cholerae are listed with E values calculated by BLAST among homologs between V. cholerae and indicated organisms. n.d. means the E value is higher than 1E-10 or no detectable homologs were found. Supplementary Data 6. Primer list Supplementary Data 7. Reference DNA sequences of tRNAs for mapping

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Kimura, S., Dedon, P.C. & Waldor, M.K. Comparative tRNA sequencing and RNA mass spectrometry for surveying tRNA modifications. Nat Chem Biol 16, 964–972 (2020). https://doi.org/10.1038/s41589-020-0558-1

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