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Accurate and universal delineation of prokaryotic species


The exponentially increasing number of sequenced genomes necessitates fast, accurate, universally applicable and automated approaches for the delineation of prokaryotic species. We developed specI (species identification tool;, a method to group organisms into species clusters based on 40 universal, single-copy phylogenetic marker genes. Applied to 3,496 prokaryotic genomes, specI identified 1,753 species clusters. Of 314 discrepancies with a widely used taxonomic classification, >62% were resolved by literature support.

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Figure 1: Comparative performance assessment of specI.
Figure 2: Phylogenetic trees and species-level clustering of Prochlorococcus displaying discrepancies with the NCBI Taxonomy data.


  1. Rosselló-Mora, R. & Amann, R. FEMS Microbiol. Rev. 25, 39–67 (2001).

    Article  Google Scholar 

  2. Stackebrandt, E. et al. Int. J. Syst. Evol. Microbiol. 52, 1043–1047 (2002).

    CAS  PubMed  Google Scholar 

  3. Kämpfer, P. & Glaeser, S. Environ. Microbiol. 14, 291–317 (2012).

    Article  Google Scholar 

  4. Richter, M. & Rosselló-Móra, R. Proc. Natl. Acad. Sci. USA 106, 19126–19131 (2009).

    Article  CAS  Google Scholar 

  5. Chun, J. et al. Int. J. Syst. Evol. Microbiol. 57, 2259–2261 (2007).

    Article  CAS  Google Scholar 

  6. Stackebrandt, E. & Goebel, B.M. Int. J. Syst. Bacteriol. 44, 846–849 (1994).

    Article  CAS  Google Scholar 

  7. Stackebrandt, E. & Ebers, J. Microbiol. Today 33, 152 (2006).

    Google Scholar 

  8. Konstantinidis, K. & Tiedje, J. Proc. Natl. Acad. Sci. USA 102, 2567–2572 (2005).

    Article  CAS  Google Scholar 

  9. von Mering, C. et al. Science 315, 1126–1130 (2007).

    Article  CAS  Google Scholar 

  10. Wu, M. & Scott, A. Bioinformatics 28, 1033–1034 (2012).

    Article  CAS  Google Scholar 

  11. Ciccarelli, F. et al. Science 311, 1283–1287 (2006).

    Article  CAS  Google Scholar 

  12. Creevey, C.J. et al. PLoS ONE 6, e22099 (2011).

    Article  CAS  Google Scholar 

  13. Powell, S. et al. Nucleic Acids Res. 40, 9 (2012).

    Article  Google Scholar 

  14. Murray, R.G.E. Int. J. Syst. Bacteriol. 46, 831 (1996).

    Article  Google Scholar 

  15. Konstantinidis, K. & Tiedje, J. J. Bacteriol. 187, 6258–6264 (2005).

    Article  CAS  Google Scholar 

  16. Kremer, K. et al. J. Clin. Microbiol. 37, 2607–2618 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. McDonald, D. et al. ISME J. 6, 610–618 (2012).

    Article  CAS  Google Scholar 

  18. Jousselin, E., Desdevises, Y. & Coeur d'acier, A. Proc. Royal Soc. B Biol. Sci. 276, 187–196 (2009).

    Article  Google Scholar 

  19. Chen, X., Li, S. & Aksoy, S. J. Mol. Evol. 48, 49–58 (1999).

    Article  CAS  Google Scholar 

  20. Brenner, D.J. Bergey's Manual of Systematic Bacteriology 1, 408–420 (The Williams & Wilkins Co., 1984).

    Google Scholar 

  21. Chisholm, S.W. et al. Nature. 334, 340–343 (1988).

    Article  Google Scholar 

  22. Moore, L., Rocap, G. & Chisholm, S. Nature 393, 464–467 (1998).

    Article  CAS  Google Scholar 

  23. Cowan, S. J. Gen. Microbiol. 67, 1–8 (1971).

    Article  CAS  Google Scholar 

  24. Sorek, R. et al. Science 318, 1449–1452 (2007).

    Article  CAS  Google Scholar 

  25. Arumugam, M., Harrington, E., Foerstner, K., Raes, J. & Bork, P. Bioinformatics 26, 2977–2978 (2010).

    Article  CAS  Google Scholar 

  26. Altschul, S. et al. Nucleic Acids Res. 25, 3389–3402 (1997).

    Article  CAS  Google Scholar 

  27. Huang, Y., Gilna, P. & Li, W. Bioinformatics 25, 1338–1340 (2009).

    Article  CAS  Google Scholar 

  28. Finn, R., Clements, J. & Eddy, S. Nucleic Acids Res. 39, 37 (2011).

    Article  Google Scholar 

  29. Pruesse, E. et al. Nucleic Acids Res. 35, 7188–7196 (2007).

    Article  CAS  Google Scholar 

  30. Caporaso, J. et al. Bioinformatics 26, 266–267 (2010).

    Article  CAS  Google Scholar 

  31. Jensen, L. et al. Nucleic Acids Res. 36, D250–D254 (2008).

    Article  CAS  Google Scholar 

  32. Pearson, W. & Lipman, D. Proc. Natl. Acad. Sci. USA 85, 2444–2448 (1988).

    Article  CAS  Google Scholar 

  33. Letunic, I. & Bork, P. Nucleic Acids Res. 39, W475–W478 (2011).

    Article  CAS  Google Scholar 

  34. Edgar, R. Bioinformatics 26, 2460–2461 (2010).

    Article  CAS  Google Scholar 

  35. Delcher, A., Salzberg, S. & Phillippy, A. Curr. Protoc. Bioinformatics 10, 10.3 (2003).

    Google Scholar 

  36. Muller, J., Creevey, C., Thompson, J., Arendt, D. & Bork, P. Bioinformatics 26, 263–265 (2010).

    Article  CAS  Google Scholar 

  37. Talavera, G. & Castresana, J. Syst. Biol. 56, 564–577 (2007).

    Article  CAS  Google Scholar 

  38. Stamatakis, A. Bioinformatics 22, 2688–2690 (2006).

    Article  CAS  Google Scholar 

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We thank the members of the Bork group for helpful discussions and Y. Yuan and members of the European Molecular Biology Laboratory information technology core facility for managing the high-performance computing resources. We acknowledge funding provided by the CancerBiome project (European Research Council project reference 268985), the 'METACARDIS' project (FP7-HEALTH-2012-INNOVATION-I-305312) and the International Human Microbiome Standards project (HEALTH-F4-2010-261376).

Author information

Authors and Affiliations



P.B., D.R.M., S.S. and G.Z. designed the study. D.R.M. developed and implemented the program, D.R.M. and G.Z. performed the experiments, D.R.M., S.S. and G.Z. analyzed the data, and D.R.M., S.S., G.Z. and P.B. wrote the manuscript.

Corresponding author

Correspondence to Peer Bork.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–8, Supplementary Tables 1–3, 5–7, 15, 17, 19 and 20, and Supplementary Note (PDF 1573 kb)

Supplementary Table 4

NCBI Taxonomy information of type strains listed on the list of prokaryotic names with standing in nomenclature (LPSN; that could be linked to NCBI, including their sequencing status (XLS 365 kb)

Supplementary Table 8

ANIb values of Prochlorococcusmarinus (XLS 19 kb)

Supplementary Table 9

ANIm values of Prochlorococcusmarinus (XLS 14 kb)

Supplementary Table 10

ANIb values of the Serratia and Rahnella clades (XLS 14 kb)

Supplementary Table 11

ANIm values of the Serratia and Rahnella clades (XLS 14 kb)

Supplementary Table 12

ANIb values of the Buchnera clade (XLS 15 kb)

Supplementary Table 13

ANIm values of the Buchnera clade (XLS 15 kb)

Supplementary Table 14

Cluster assignments for the 3,496 genomes used in this study (XLS 496 kb)

Supplementary Table 16

Literature-based reclassifications of species assignments of NCBI Taxonomy database (XLS 94 kb)

Supplementary Table 18

Assignments of genomes were previously not assigned to a named species to known species using the species clustering strategy presented in this publication (XLS 28 kb)

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Mende, D., Sunagawa, S., Zeller, G. et al. Accurate and universal delineation of prokaryotic species. Nat Methods 10, 881–884 (2013).

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