Letter | Published:

Utilization of selenocysteine in early-branching fungal phyla

Nature Microbiology (2019) | Download Citation

Abstract

Selenoproteins are a diverse group of proteins containing selenocysteine (Sec)—the twenty-first amino acid—incorporated during translation via a unique recoding mechanism1,2. Selenoproteins fulfil essential roles in many organisms1, yet are not ubiquitous across the tree of life3,4,5,6,7. In particular, fungi were deemed devoid of selenoproteins4,5,8. However, we show here that Sec is utilized by nine species belonging to diverse early-branching fungal phyla, as evidenced by the genomic presence of both Sec machinery and selenoproteins. Most fungal selenoproteins lack consensus Sec recoding signals (SECIS elements9) but exhibit other RNA structures, suggesting altered mechanisms of Sec insertion in fungi. Phylogenetic analyses support a scenario of vertical inheritance of the Sec trait within eukaryotes and fungi. Sec was then lost in numerous independent events in various fungal lineages. Notably, Sec was lost at the base of Dikarya, resulting in the absence of selenoproteins in Saccharomyces cerevisiae and other well-studied fungi. Our results indicate that, despite scattered occurrence, selenoproteins are found in all kingdoms of life.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Code availability

The latest version of the selenoprotein gene finder software Selenoprofiles is available at https://github.com/marco-mariotti/selenoprofiles. The script ncbi_assembly, used to download NCBI assemblies in batch, is available at https://github.com/marco-mariotti/ncbi_db.

Data availability

A list of the fungal species and corresponding genomes (NCBI assembly accession IDs) used in this study is provided in Supplementary Table 1. Supplementary Data 1 contains the sequences of all of the genes and RNA elements mentioned in this work, as well as their genomic coordinates to derive these sequences from genomes. For each species, coordinates are mapped to GenBank nucleotide entries (contigs or scaffolds) found within their corresponding genome. Our re-annotated open reading frames are in the process of being assigned GenBank IDs.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. 1.

    Labunskyy, V. M., Hatfield, D. L. & Gladyshev, V. N. Selenoproteins: molecular pathways and physiological roles. Physiol. Rev. 94, 739–777 (2014).

  2. 2.

    Xu, X. M. et al. Biosynthesis of selenocysteine on its tRNA in eukaryotes. PLoS Biol. 5, e4 (2007).

  3. 3.

    Zhang, Y., Romero, H., Salinas, G. & Gladyshev, V. Dynamic evolution of selenocysteine utilization in bacteria: a balance between selenoprotein loss and evolution of selenocysteine from redox active cysteine residues. Genome Biol. 7, R94 (2006).

  4. 4.

    Mariotti, M. et al. Evolution of selenophosphate synthetases: emergence and relocation of function through independent duplications and recurrent subfunctionalization. Genome Res. 25, 1256–1267 (2015).

  5. 5.

    Lobanov, A. V., Hatfield, D. L. & Gladyshev, V. N. Eukaryotic selenoproteins and selenoproteomes. Biochim. Biophys. Acta 1790, 1424–1428 (2009).

  6. 6.

    Chapple, C. E. & Guigó, R. Relaxation of selective constraints causes independent selenoprotein extinction in insect genomes.PLoS ONE 13, e2968 (2008).

  7. 7.

    Otero, L. et al. Adjustments, extinction, and remains of selenocysteine incorporation machinery in the nematode lineage. RNA 20, 1023–1034 (2014).

  8. 8.

    Jiang, L. et al. Evolution of selenoproteins in the metazoan. BMC Genomics 13, 446 (2012).

  9. 9.

    Krol, A. Evolutionarily different RNA motifs and RNA–protein complexes to achieve selenoprotein synthesis. Biochimie 84, 765–774 (2002).

  10. 10.

    Gupta, N., DeMong, L. W., Banda, S. & Copeland, P. R. Reconstitution of selenocysteine incorporation reveals intrinsic regulation by SECIS elements. J. Mol. Biol. 425, 2415–2422 (2013).

  11. 11.

    Castellano, S. et al. Low exchangeability of selenocysteine, the 21st amino acid, in vertebrate proteins. Mol. Biol. Evol. 26, 2031–2040 (2009).

  12. 12.

    Reich, H. J. & Hondal, R. J. Why nature chose selenium. ACS Chem. Biol. 11, 821–841 (2016).

  13. 13.

    Lin, J. et al. Comparative genomics reveals new candidate genes involved in selenium metabolism in prokaryotes. Genome Biol. Evol. 7, 664–676 (2015).

  14. 14.

    Mariotti, M. et al. Lokiarchaeota marks the transition between the archaeal and eukaryotic selenocysteine encoding systems. Mol. Biol. Evol. 33, 2441–2453 (2016).

  15. 15.

    Mariotti, M. et al. Composition and evolution of the vertebrate and mammalian selenoproteomes. PLoS ONE 7, e33066 (2012).

  16. 16.

    Lobanov, A. V. et al. Evolutionary dynamics of eukaryotic selenoproteomes: large selenoproteomes may associate with aquatic life and small with terrestrial life. Genome Biol. 8, R198 (2007).

  17. 17.

    Mariotti, M. & Guigó, R. Selenoprofiles: profile-based scanning of eukaryotic genome sequences for selenoprotein genes. Bioinformatics 26, 2656–2663 (2010).

  18. 18.

    Santesmasses, D., Mariotti, M. & Guigó, R. Computational identification of the selenocysteine tRNA (tRNASec) in genomes. PLoS Comput. Biol. 13, e1005383 (2017).

  19. 19.

    Cox, A. G. et al. Selenoprotein H is an essential regulator of redox homeostasis that cooperates with p53 in development and tumorigenesis. Proc. Natl Acad. Sci. USA 113, E5562–E5571 (2016).

  20. 20.

    Castellano, S. et al. Reconsidering the evolution of eukaryotic selenoproteins: a novel nonmammalian family with scattered phylogenetic distribution. EMBO Rep. 5, 71–77 (2004).

  21. 21.

    Mariotti, M., Lobanov, A. V., Guigo, R. & Gladyshev, V. N. SECISearch3 and Seblastian: new tools for prediction of SECIS elements and selenoproteins. Nucleic Acids Res. 41, e149 (2013).

  22. 22.

    Lee, B. C., Dikiy, A., Kim, H.-Y. & Gladyshev, V. N. Functions and evolution of selenoprotein methionine sulfoxide reductases. Biochim. Biophys. Acta 1790, 1471–1477 (2009).

  23. 23.

    Darras, V. M. & Van Herck, S. L. J. Iodothyronine deiodinase structure and function: from ascidians to humans. J. Endocrinol. 215, 189–206 (2012).

  24. 24.

    Arnér, E. S. & Holmgren, A. Physiological functions of thioredoxin and thioredoxin reductase. Eur. J. Biochem. 267, 6102–6109 (2000).

  25. 25.

    Gruber, A. R., Findeiß, S., Washietl, S., Hofacker, I. L. & Stadler, P. F. RNAz 2.0: improved noncoding RNA detection.Pac. Symp. Biocomput. 15, 69–79 (2010).

  26. 26.

    Lorenz, R. et al. ViennaRNA package 2.0. Algorithms Mol. Biol. 6, 26 (2011).

  27. 27.

    Pellegrini, M., Marcotte, E. M., Thompson, M. J., Eisenberg, D. & Yeates, T. O. Assigning protein functions by comparative genome analysis: protein phylogenetic profiles. Proc. Natl Acad. Sci. USA 96, 4285–4288 (1999).

  28. 28.

    Spatafora, J. W. et al. A phylum-level phylogenetic classification of zygomycete fungi based on genome-scale data. Mycologia 108, 1028–1046 (2016).

  29. 29.

    Howard, M. T. et al. Recoding elements located adjacent to a subset of eukaryal selenocysteine-specifying UGA codons. EMBO J. 24, 1596–1607 (2005).

  30. 30.

    Labunskyy, V. M. et al. The insertion Green Monster (iGM) method for expression of multiple exogenous genes in yeast. G3 (Bethesda) 4, 1183–1191 (2014).

  31. 31.

    Slater, G. S. C. & Birney, E. Automated generation of heuristics for biological sequence comparison. BMC Bioinformatics 6, 31 (2005).

  32. 32.

    Birney, E., Clamp, M. & Durbin, R. GeneWise and Genomewise. Genome Res. 14, 988–995 (2004).

  33. 33.

    Gladyshev, V. N. in Selenium 127–139 (Springer International Publishing, New York, 2016).

  34. 34.

    Zhang, Y. in Selenium 141–150 (Springer International Publishing, New York, 2016).

  35. 35.

    Camacho, C. et al. BLAST+: architecture and applications. BMC Bioinformatics 10, 421 (2009).

  36. 36.

    NCBI Resource Coordinators. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 45, D12–D17 (2017).

  37. 37.

    Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 30, 772–780 (2013).

  38. 38.

    Capella-Gutiérrez, S., Silla-Martínez, J. M. & Gabaldón, T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25, 1972–1973 (2009).

  39. 39.

    Huerta-Cepas, J., Serra, F. & Bork, P. ETE 3: reconstruction, analysis, and visualization of phylogenomic data. Mol. Biol. Evol. 33, 1635–1638 (2016).

  40. 40.

    Huerta-Cepas, J., Capella-Gutiérrez, S., Pryszcz, L. P., Marcet-Houben, M. & Gabaldón, T. PhylomeDB v4: zooming into the plurality of evolutionary histories of a genome. Nucleic Acids Res. 42, D897–D902 (2014).

  41. 41.

    Wallace, I. M., O’Sullivan, O., Higgins, D. G. & Notredame, C. M-Coffee: combining multiple sequence alignment methods with T-Coffee. Nucleic Acids Res. 34, 1692–1699 (2006).

  42. 42.

    Guindon, S. et al. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst. Biol. 59, 307–321 (2010).

  43. 43.

    Wang, Y. et al. Comparative genomics reveals the core gene toolbox for the fungus–insect symbiosis.mBio 9, e00636-18 (2018).

  44. 44.

    Nawrocki, E. P., Kolbe, D. L. & Eddy, S. R. Infernal 1.0: inference of RNA alignments. Bioinformatics 25, 1335–1337 (2009).

  45. 45.

    Sievers, F. et al. Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol. Syst. Biol. 7, 539 (2011).

  46. 46.

    Waterhouse, A. M., Procter, J. B., Martin, D. M. A., Clamp, M. & Barton, G. J. Jalview Version 2—a multiple sequence alignment editor and analysis workbench. Bioinformatics 25, 1189–1191 (2009).

  47. 47.

    Griffiths-Jones, S. RALEE—RNA alignment editor in Emacs. Bioinformatics 21, 257–259 (2005).

  48. 48.

    Waterhouse, R. M. et al. BUSCO applications from quality assessments to gene prediction and phylogenomics. Mol. Biol. Evol. 35, 543–548 (2017).

  49. 49.

    Nordberg, H. et al. The genome portal of the Department of Energy Joint Genome Institute: 2014 updates. Nucleic Acids Res. 42, D26–D31 (2014).

  50. 50.

    Laslett, D. & Canback, B. ARAGORN, a program to detect tRNA genes and tmRNA genes in nucleotide sequences. Nucleic Acids Res. 32, 11–16 (2004).

Download references

Acknowledgements

This work was supported by National Institutes of Health grants DK117149, AG021518 and CA080946. Funding for the open access charge was provided by the National Institutes of Health.

Author information

Affiliations

  1. Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    • Marco Mariotti
    •  & Vadim N. Gladyshev
  2. Departamento de Biociencias, Facultad de Química, Universidad de la República, Montevideo, Uruguay

    • Gustavo Salinas
  3. Worm Biology Laboratory, Institut Pasteur de Montevideo, Montevideo, Uruguay

    • Gustavo Salinas
  4. Bioinformatics and Genomics Programme, Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain

    • Toni Gabaldón
  5. Universitat Pompeu Fabra, Barcelona, Spain

    • Toni Gabaldón
  6. Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain

    • Toni Gabaldón

Authors

  1. Search for Marco Mariotti in:

  2. Search for Gustavo Salinas in:

  3. Search for Toni Gabaldón in:

  4. Search for Vadim N. Gladyshev in:

Contributions

G.S. first noted Sec machinery in a fungal genome and initiated this study. M.M. designed and performed the data analyses and wrote the manuscript. G.S., T.G. and V.N.G. participated in critical discussion and revised the manuscript.

Competing interests

The authors declare no competing interests.

Corresponding authors

Correspondence to Marco Mariotti or Vadim N. Gladyshev.

Supplementary information

  1. Supplementary Information

    Supplementary Figures 1–26 and Supplementary Notes.

  2. Reporting Summary

  3. Supplementary Table 1

    Species names, assembly identifiers and taxonomic annotation of all fungal genomes analysed in this study.

  4. Supplementary Table 2

    Results of phylogenetic profiling to detect proteins related to Sec.

  5. Supplementary Data 1 and 2

    Sequences and genomic coordinates of Sec machinery, selenoproteins and RNA structures described in this work, and reconstructed phylogenetic trees of Sec machinery and selenoproteins (the same as in Fig. 3 and in Supplementary Figures 2–10) with branch support values.

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/s41564-018-0354-9