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.
Subscribe to Journal
Get full journal access for 1 year
only $4.92 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012).
Becker, K., Heilmann, C. & Peters, G. Coagulase-negative staphylococci. Clin. Microbiol. Rev. 27, 870–926 (2014).
Götz, F. Staphylococcus and biofilms. Mol. Microbiol. 43, 1367–1378 (2002).
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).
Otto, M. Staphylococcus epidermidis—the ‘accidental’ pathogen. Nat. Rev. Microbiol. 7, 555–567 (2009).
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).
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).
Tolo, I. et al. Do Staphylococcus epidermidis genetic clusters predict isolation sources? J. Clin. Microbiol. 54, 1711–1719 (2016).
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).
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).
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).
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).
Gazzola, S. & Cocconcelli, P. S. Vancomycin heteroresistance and biofilm formation in Staphylococcus epidermidis from food. Microbiol. 154, 3224–3231 (2008).
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).
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).
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).
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).
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).
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).
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).
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).
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).
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).
Chen, H.-J. et al. Identification of fusB-mediated fusidic acid resistance islands in Staphylococcus epidermidis isolates. Antimicrob. Agents Chemother. 55, 5842–5849 (2011).
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).
Wong, A. et al. Polyphyletic emergence of linezolid-resistant staphylococci in the United States. Antimicrob. Agents Chemother. 54, 742–748 (2010).
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).
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).
Alifano, P., Palumbo, C., Pasanisi, D. & Talà, A. Rifampicin-resistance, rpoB polymorphism and RNA polymerase genetic engineering. J. Biotechnol. 202, 60–77 (2015).
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).
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).
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).
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).
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).
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).
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).
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).
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).
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).
Cui, L. et al. An RpoB mutation confers dual heteroresistance to daptomycin and vancomycin in Staphylococcus aureus. Antimicrob. Agents Chemother. 54, 5222–5233 (2010).
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).
Zhang, J., Kobert, K., Flouri, T. & Stamatakis, A. PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 30, 614–620 (2014).
Bankevich, A. et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J. Comput. Biol. 19, 455–477 (2012).
Seemann, T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30, 2068–2069 (2014).
Seemann, T. Snippy: Rapid Bacterial SNP Calling and Core Genome Alignments (2016); https://github.com/tseemann/snippy.git
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).
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).
Minh, B. Q., Nguyen, M. A. T. & von Haeseler, A. Ultrafast approximation for phylogenetic bootstrap. Mol. Biol. Evol. 30, 1188–1195 (2013).
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
Lechner, M. et al. Proteinortho: detection of (co-)orthologs in large-scale analysis. BMC Bioinformatics 12, 124 (2011).
Powell, D. FriPan: Tnteractive Web Tool for Exploring Pan-Genome of Bacterial Strains (2017); https://github.com/drpowell/FriPan
Seemann, T. MLST: Scan Contig Files Against PubMLST Typing Schemes (2016); https://github.com/tseemann/mlst.git
Seemann, T. abricate: Mass Screening of Contigs for Antimicrobial and Virulence Genes (2018); https://github.com/tseemann/abricate
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).
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).
Arndt, D. et al. PHASTER: a better, faster version of the PHAST phage search tool. Nucleic Acids Res. 44, W16–W21 (2016).
Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).
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).
Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).
Bouckaert, R. et al. BEAST 2: a software platform for Bayesian evolutionary analysis. PLoS Comput. Biol. 10, e1003537 (2014).
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2013).
Paradis, E., Claude, J. & Strimmer, K. APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20, 289–290 (2004).
Wood, D. E. & Salzberg, S. L. Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biol. 15, R46 (2014).
Camacho, C. et al. BLAST+: architecture and applications. BMC Bioinformatics 10, 421 (2009).
Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797 (2004).
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).
Zhang, Y., Werling, U. & Edelmann, W. SLiCE: a novel bacterial cell extract-based DNA cloning method. Nucleic Acids Res. 40, e55 (2012).
Harrison, P. Nesoni: High Throughput Sequencing Analysis Tools (2014); https://github.com/Victorian-Bioinformatics-Consortium/nesoni.git
Pirt, S. J. Principles of Microbe and Cell Cultivation (Wiley, New York, 1975).
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).
The authors declare no competing interests.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Figures 1–6, Supplementary Tables 1–3, Supplementary References.
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.
About this article
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
Identification of Eltrombopag as a Repurposing Drug Against Staphylococcus epidermidis and its Biofilms
Current Microbiology (2021)
Protective Face Mask Filter Capable of Inactivating SARS-CoV-2, and Methicillin-Resistant Staphylococcus aureus and Staphylococcus epidermidis
Genomic Insights Into Last-Line Antimicrobial Resistance in Multidrug-Resistant Staphylococcus and Vancomycin-Resistant Enterococcus
Frontiers in Microbiology (2021)