Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Global spread of three multidrug-resistant lineages of Staphylococcus epidermidis

Abstract

Staphylococcus epidermidis is a conspicuous member of the human microbiome, widely present on healthy skin. Here we show that S. epidermidis has also evolved to become a formidable nosocomial pathogen. Using genomics, we reveal that three multidrug-resistant, hospital-adapted lineages of S. epidermidis (two ST2 and one ST23) have emerged in recent decades and spread globally. These lineages are resistant to rifampicin through acquisition of specific rpoB mutations that have become fixed in the populations. Analysis of isolates from 96 institutions in 24 countries identified dual D471E and I527M RpoB substitutions to be the most common cause of rifampicin resistance in S. epidermidis, accounting for 86.6% of mutations. Furthermore, we reveal that the D471E and I527M combination occurs almost exclusively in isolates from the ST2 and ST23 lineages. By breaching lineage-specific DNA methylation restriction modification barriers and then performing site-specific mutagenesis, we show that these rpoB mutations not only confer rifampicin resistance, but also reduce susceptibility to the last-line glycopeptide antibiotics, vancomycin and teicoplanin. Our study has uncovered the previously unrecognized international spread of a near pan-drug-resistant opportunistic pathogen, identifiable by a rifampicin-resistant phenotype. It is possible that hospital practices, such as antibiotic monotherapy utilizing rifampicin-impregnated medical devices, have driven the evolution of this organism, once trivialized as a contaminant, towards potentially incurable infections.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Increasing prevalence of multidrug-resistant S. epidermidis (MDRSE).
Fig. 2: Clonal expansion of endemic, multidrug-resistant ST2 and ST23 S. epidermidis lineages resulting in clinical disease within a single institution.
Fig. 3: International clonal expansion of endemic, multidrug-resistant ST2 and ST23 S. epidermidis lineages resulting in clinical disease.
Fig. 4: RpoB mutations confer vancomycin heteroresistance in S. epidermidis.
Fig. 5: RpoB D471E and I527M mutations cause vancomycin heteroresistance in four different S. epidermidis backgrounds.
Fig. 6: Mutants containing dual D471E and I527M RpoB substitutions outcompete WT S. epidermidis in the presence of vancomycin.

Similar content being viewed by others

References

  1. Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012).

    Article  CAS  Google Scholar 

  2. Becker, K., Heilmann, C. & Peters, G. Coagulase-negative staphylococci. Clin. Microbiol. Rev. 27, 870–926 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Götz, F. Staphylococcus and biofilms. Mol. Microbiol. 43, 1367–1378 (2002).

    Article  PubMed  Google Scholar 

  4. Sievert, D. M. et al. Antimicrobial-resistant pathogens associated with healthcare-associated infections: summary of data reported to the National Healthcare Safety Network at the Centers for Disease Control and Prevention, 2009–2010. Infect. Control Hosp. Epidemiol. 34, 1–14 (2013).

    Article  PubMed  Google Scholar 

  5. Otto, M. Staphylococcus epidermidis—the ‘accidental’ pathogen. Nat. Rev. Microbiol. 7, 555–567 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Miragaia, M., Thomas, J. C., Couto, I., Enright, M. C. & de Lencastre, H. Inferring a population structure for Staphylococcus epidermidis from multilocus sequence typing data. J. Bacteriol. 189, 2540–2552 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Thomas, J. C., Zhang, L. & Robinson, D. A. Differing lifestyles of Staphylococcus epidermidis as revealed through Bayesian clustering of multilocus sequence types. Infect. Genet. Evol. 22, 257–264 (2014).

    Article  CAS  PubMed  Google Scholar 

  8. Tolo, I. et al. Do Staphylococcus epidermidis genetic clusters predict isolation sources? J. Clin. Microbiol. 54, 1711–1719 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Krediet, T. G. et al. Molecular epidemiology of coagulase-negative Staphylococci causing sepsis in a neonatal intensive care unit over an 11-year period. J. Clin. Microbiol. 42, 992–995 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Conlan, S. et al. Staphylococcus epidermidis pan-genome sequence analysis reveals diversity of skin commensal and hospital infection-associated isolates. Genome Biol. 13, R64 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Mendes, R. E., Deshpande, L. M., Costello, A. J. & Farrell, D. J. Molecular epidemiology of Staphylococcus epidermidis clinical isolates from U.S. hospitals. Antimicrob. Agents Chemother. 56, 4656–4661 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Lee, J. Y. H. et al. Functional analysis of the first complete genome sequence of a multidrug resistant sequence type 2 Staphylococcus epidermidis. Microb. Genom. 2, e000077 (2016).

    PubMed  PubMed Central  Google Scholar 

  13. Gazzola, S. & Cocconcelli, P. S. Vancomycin heteroresistance and biofilm formation in Staphylococcus epidermidis from food. Microbiol. 154, 3224–3231 (2008).

    Article  Google Scholar 

  14. Sieradzki, K., Roberts, R. B., Serur, D., Hargrave, J. & Tomasz, A. Heterogeneously vancomycin-resistant Staphylococcus epidermidis strain causing recurrent peritonitis in a dialysis patient during vancomycin therapy. J. Clin. Microbiol. 37, 39–44 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Ma, X. X., Wang, E. H., Liu, Y. & Luo, E. J. Antibiotic susceptibility of coagulase-negative staphylococci (CoNS): emergence of teicoplanin-non-susceptible CoNS strains with inducible resistance to vancomycin. J. Med. Microbiol. 60, 1661–1668 (2011).

    Article  CAS  PubMed  Google Scholar 

  16. Nakipoglu, Y., Derbentli, S., Cagatay, A. A. & Katranci, H. Investigation of Staphylococcus strains with heterogeneous resistance to glycopeptides in a Turkish university hospital. BMC Infect. Dis. 5, 31 (2005).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Sieradzki, K., Villari, P. & Tomasz, A. Decreased susceptibilities to teicoplanin and vancomycin among coagulase-negative methicillin-resistant clinical isolates of Staphylococci. Antimicrob. Agents Chemother. 42, 100–107 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Zhang, Y. Q. et al. Genome‐based analysis of virulence genes in a non‐biofilm‐forming Staphylococcus epidermidis strain (ATCC 12228). Mol. Microbiol. 49, 1577–1593 (2003).

    Article  CAS  PubMed  Google Scholar 

  19. Gill, S. R. et al. Insights on evolution of virulence and resistance from the complete genome analysis of an early methicillin-resistant Staphylococcus aureus strain and a biofilm-producing methicillin-resistant Staphylococcus epidermidis strain. J. Bacteriol. 187, 2426–2438 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Gao, W. et al. The RpoB H481Y rifampicin resistance mutation and an active stringent response reduce virulence and increase resistance to innate immune responses in Staphylococcus aureus. J. Infect. Dis. 207, 929–939 (2013).

    Article  CAS  PubMed  Google Scholar 

  21. Matsuo, M. et al. Mutation of RNA polymerase beta subunit (rpoB) promotes hVISA-to-VISA phenotypic conversion of strain Mu3. Antimicrob. Agents Chemother. 55, 4188–4195 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Howden, B. P., Davies, J. K., Johnson, P. D. R., Stinear, T. P. & Grayson, M. L. Reduced vancomycin susceptibility in Staphylococcus aureus, including vancomycin-intermediate and heterogeneous vancomycin-intermediate strains: resistance mechanisms, laboratory detection, and clinical implications. Clin. Microbiol. Rev. 23, 99–139 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. McLaws, F., Chopra, I. & O’Neill, A. J. High prevalence of resistance to fusidic acid in clinical isolates of Staphylococcus epidermidis. J. Antimicrob. Chemother. 61, 1040–1043 (2008).

    Article  CAS  PubMed  Google Scholar 

  24. Chen, H.-J. et al. Identification of fusB-mediated fusidic acid resistance islands in Staphylococcus epidermidis isolates. Antimicrob. Agents Chemother. 55, 5842–5849 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Bender, J. et al. Linezolid resistance in clinical isolates of Staphylococcus epidermidis from German hospitals and characterization of two cfr-carrying plasmids. J. Antimicrob. Chemother. 70, 1630–1638 (2015).

    CAS  PubMed  Google Scholar 

  26. Wong, A. et al. Polyphyletic emergence of linezolid-resistant staphylococci in the United States. Antimicrob. Agents Chemother. 54, 742–748 (2010).

    Article  CAS  PubMed  Google Scholar 

  27. Yang, S. J., Mishra, N. N., Rubio, A. & Bayer, A. S. Causal role of single nucleotide polymorphisms within the mprF gene of Staphylococcus aureus in daptomycin resistance. Antimicrob. Agents Chemother. 57, 5658–5664 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Koch, A., Mizrahi, V. & Warner, D. F. The impact of drug resistance on Mycobacterium tuberculosis physiology: what can we learn from rifampicin? Emerg. Microbes Infect. 3, e17 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Alifano, P., Palumbo, C., Pasanisi, D. & Talà, A. Rifampicin-resistance, rpoB polymorphism and RNA polymerase genetic engineering. J. Biotechnol. 202, 60–77 (2015).

    Article  CAS  PubMed  Google Scholar 

  30. Hellmark, B., Unemo, M., Nilsdotter-Augustinsson, Å. & Söderquist, B. Antibiotic susceptibility among Staphylococcus epidermidis isolated from prosthetic joint infections with special focus on rifampicin and variability of the rpoB gene. Clin. Microbiol. Infect. 15, 238–244 (2009).

    Article  CAS  PubMed  Google Scholar 

  31. Liu, C. et al. Clinical practice guidelines by the Infectious Diseases Society of America for the treatment of methicillin-resistant Staphylococcus aureus infections in adults and children. Clin. Infect. Dis. 52, e18–55 (2011).

    Article  PubMed  Google Scholar 

  32. Zimmerli, W., Frei, R., Widmer, A. F. & Rajacic, Z. Microbiological tests to predict treatment outcome in experimental device-related infections due to Staphylococcus aureus. J. Antimicrob. Chemother. 33, 959–967 (1994).

    Article  CAS  PubMed  Google Scholar 

  33. Karchmer, A. W., Archer, G. L. & Dismukes, W. E. Staphylococcus epidermidis causing prosthetic valve endocarditis—microbiologic and clinical observations as guides to therapy. Ann. Intern. Med. 98, 447–455 (1983).

    Article  CAS  PubMed  Google Scholar 

  34. Chamovitz, B., Bryant, R. E., Gilbert, D. N. & Hartstein, A. I. Prosthetic valve endocarditis caused by Staphylococcus epidermidis—development of rifampin resistance during vancomycin and rifampin therapy. JAMA 253, 2867–2868 (1985).

    Article  CAS  PubMed  Google Scholar 

  35. Jung, Y. J. et al. Effect of vancomycin plus rifampicin in the treatment of nosocomial methicillin-resistant Staphylococcus aureus pneumonia. Crit. Care Med. 38, 175–180 (2010).

    Article  CAS  PubMed  Google Scholar 

  36. Lee, J. Y. & Howden, B. P. Vancomycin in the treatment of methicillin-resistant Staphylococcus aureus—a clinician’s guide to the science informing current practice. Exp. Rev. Anti. Infect. Ther. 13, 855–869 (2015).

    Article  CAS  Google Scholar 

  37. Riedel, D. J., Weekes, E. & Forrest, G. N. Addition of rifampin to standard therapy for treatment of native valve infective endocarditis caused by Staphylococcus aureus. Antimicrob. Agents Chemother. 52, 2463–2467 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Monk, I. R., Shah, I. M., Xu, M., Tan, M.-W. & Foster, T. J. Transforming the untransformable: application of direct transformation to manipulate genetically Staphylococcus aureus and Staphylococcus epidermidis. mBio 3, e00277-11 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Clinical and Laboratory Standards Institute. Methods for Dilution and Antimicrobial Susceptibility Tests for Bacteria that Grow Aerobically 9th edn, 32 (Clinical and Laboratory Standards Institute, Wayne, PA, 2012).

  40. Cui, L. et al. An RpoB mutation confers dual heteroresistance to daptomycin and vancomycin in Staphylococcus aureus. Antimicrob. Agents Chemother. 54, 5222–5233 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Zhang, J., Kobert, K., Flouri, T. & Stamatakis, A. PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 30, 614–620 (2014).

    Article  CAS  PubMed  Google Scholar 

  43. Bankevich, A. et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J. Comput. Biol. 19, 455–477 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Seemann, T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30, 2068–2069 (2014).

    Article  CAS  PubMed  Google Scholar 

  45. Seemann, T. Snippy: Rapid Bacterial SNP Calling and Core Genome Alignments (2016); https://github.com/tseemann/snippy.git

  46. Nguyen, L.-T., Schmidt, H. A., von Haeseler, A. & Minh, B. Q. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268–274 (2015).

    Article  CAS  PubMed  Google Scholar 

  47. Kalyaanamoorthy, S., Minh, B. Q., Wong, T. K. F., von Haeseler, A. & Jermiin, L. S. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat. Methods 14, 587–589 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Minh, B. Q., Nguyen, M. A. T. & von Haeseler, A. Ultrafast approximation for phylogenetic bootstrap. Mol. Biol. Evol. 30, 1188–1195 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Goncalves da Silva, A. Pairwise_SNP_differences: An R Script to Summarise SNP Differences Among Groups of Samples (2015); https://github.com/MDU-PHL/pairwise_snp_differences.git

  50. Lechner, M. et al. Proteinortho: detection of (co-)orthologs in large-scale analysis. BMC Bioinformatics 12, 124 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  51. Powell, D. FriPan: Tnteractive Web Tool for Exploring Pan-Genome of Bacterial Strains (2017); https://github.com/drpowell/FriPan

  52. Seemann, T. MLST: Scan Contig Files Against PubMLST Typing Schemes (2016); https://github.com/tseemann/mlst.git

  53. Seemann, T. abricate: Mass Screening of Contigs for Antimicrobial and Virulence Genes (2018); https://github.com/tseemann/abricate

  54. Chen, L., Zheng, D., Liu, B., Yang, J. & Jin, Q. VFDB 2016: hierarchical and refined dataset for big data analysis—10 years on. Nucleic Acids Res. 44, D694–D697 (2016).

    Article  CAS  PubMed  Google Scholar 

  55. Cheng, L., Connor, T. R., Sirén, J., Aanensen, D. M. & Corander, J. Hierarchical and spatially explicit clustering of DNA sequences with BAPS software. Mol. Biol. Evol. 30, 1224–1228 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Arndt, D. et al. PHASTER: a better, faster version of the PHAST phage search tool. Nucleic Acids Res. 44, W16–W21 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Croucher, N. J. et al. Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins. Nucleic Acids Res. 43, e15 (2015).

    Article  PubMed  CAS  Google Scholar 

  59. Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Bouckaert, R. et al. BEAST 2: a software platform for Bayesian evolutionary analysis. PLoS Comput. Biol. 10, e1003537 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  61. R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2013).

  62. Paradis, E., Claude, J. & Strimmer, K. APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20, 289–290 (2004).

    Article  CAS  PubMed  Google Scholar 

  63. Wood, D. E. & Salzberg, S. L. Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biol. 15, R46 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  65. Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Monk, I. R., Howden, B. P., Seemann, T. & Stinear, T. P. Spontaneous secondary mutations confound analysis of the essential two-component system WalKR in Staphylococcus aureus. Nat. Commun. 8, 14403 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Zhang, Y., Werling, U. & Edelmann, W. SLiCE: a novel bacterial cell extract-based DNA cloning method. Nucleic Acids Res. 40, e55 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Harrison, P. Nesoni: High Throughput Sequencing Analysis Tools (2014); https://github.com/Victorian-Bioinformatics-Consortium/nesoni.git

  69. Pirt, S. J. Principles of Microbe and Cell Cultivation (Wiley, New York, 1975).

Download references

Acknowledgements

The authors thank D. Kotsanas (Monash Health), M. Hickey (Ireland), A. Boulos (Northern Ireland) and K. E. Greenwood Quaintance, S. M. Schmidt-Malan and Y. M. Wi (United States) for their submission of isolates used in this study. This project was supported by the Royal Australasian College of Physicians, Basser Research Entry Scholarship/Australian Government Research Training Program Scholarship (to J.Y.H.L.), a National Institutes of Health, National Institute of Allergy and Infectious Diseases Project Grant to R.P. (R21 AI125870), a National Health and Medical Research Council of Australia (NHMRC) Project Grant (GNT1066791), an NHMRC Senior Research Fellowship to T.P.S. (GNT1105525) and an NHMRC Practitioner Fellowship to B.P.H. (GNT1105905).

Author information

Authors and Affiliations

Authors

Contributions

B.P.H. and T.P.S. conceived the project, which was supervised by B.P.H., T.P.S. and I.R.M. J.Y.H.L. performed all experimental work, with assistance from I.R.M. J.Y.H.L., A.G.d.S., T.S., T.P.S. and B.P.H. analysed data, including analysis of genome sequence data. K.Y.L.C., A.K., R.H., N.W., M.D.B., B.S., F.L., M.D., A.D., R.P., A.R.L. and T.M.K. established and analysed clinical and reference isolate data sets and performed susceptibility testing. J.Y.H.L., I.R.M., B.P.H. and T.P.S. drafted the manuscript. All authors reviewed and contributed to the final manuscript.

Corresponding author

Correspondence to Benjamin P. Howden.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

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

Supplementary Information

Supplementary Information

Supplementary Figures 1–6, Supplementary Tables 1–3, Supplementary References.

Reporting Summary

Supplementary Table 1

Isolate metadata. Sheet A: clinical metadata. Sheet B: accession information. Sheet C: sequencing and assembly statistics. Sheet D: resistome data. Sheet E: SRA strain metadata.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lee, J.Y.H., Monk, I.R., Gonçalves da Silva, A. et al. Global spread of three multidrug-resistant lineages of Staphylococcus epidermidis. Nat Microbiol 3, 1175–1185 (2018). https://doi.org/10.1038/s41564-018-0230-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41564-018-0230-7

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing