Matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry has revolutionized clinical microbiology, enabling the rapid and accurate identification of micro-organisms; it has become the standard in clinical microbiology laboratories. We evaluated the Bruker MALDI-TOF Biotyper ability to identify 485 Coagulase-negative Staphylococci (CNS) isolated from clinical specimens and previously identified by conventional techniques. Discrepant results were resolved by 16S rRNA analysis by a reference laboratory. Overall the Bruker BioTyper performed well identifying 485 (100%) of the CNS correctly to the species level, while the Vitek 2 identified 88.6% and the MIS gas liquid chromatography 60.8% correctly. A single discrepant result resolved by 16S rRNA analysis was confirmed to be S. xylosus, as identified by the Bruker BioTyper. We concluded that the Bruker BioTyper is an excellent identification modality for CNS in the routine microbiology laboratory.

Keywords: MALDI-TOF, identification, coagulase-negative, staphylococci

Coagulase-negative Staphylococci (CNS), once considered to be commensals or contaminants of clinical specimens are now recognized as potential and opportunistic pathogens. Forty different species are now recognized to be of significance in human disease.^1-3

CNS are associated with many different infections and among others causes infections of foreign bodies like prosthetic joints.⁴ and they are considered to be a major cause of line associated bacteremia in hospitalized patients.^5,6 Coagulase-negative Staphylococci are well-known to cause other significant infections; acting as opportunistic pathogens in surgical site infections, colonization of vascular access devices or as a urinary tract pathogen such as Staphylococcus saprophyticus .^4,5 Human diseases are most frequently caused by Staphylococcus epidermidis, Staphylococcus haemolyticus and Staphylococcus saprophyticus. Other significant opportunistic pathogens include Staphylococcus hominis, Staphylococcus warneri, Staphylococcus capitis, Staphylococcus simulans, Staphylococcus cohnii, Staphylococcus xylosus, Staphylococcus saccharolyticus and Staphylococcus lugdunensis .^2,3,7 Many different factors contribute to the disease progression of CNS associated infections including the species, host-pathogen interactions, the immune status of the host and the ability of the bacteria to produce a biofilm.^6,8,9  Identification of CNS are important to ensure the correct interpretation of susceptibility results and distinguishing between species of CNS with differing propensity to cause disease, thereby enabling clinicians to distinguish between colonizers, contaminants and potential pathogens.^4,5,10-12

Automated systems are available and have been used over the last 20 years to identify CNS. Systems such as the VITEK 2 (bioMerieux, Marcy l'etoile, France) and the BD Phoenix Automated Microbiology System (BD Diagnostics, Sparks, MD)^10,11 have been evaluated as to their ability to identify these bacteria to the species and subspecies level. These automated identification and susceptibility systems are hampered by the organism’s ability to express specific metabolic activity and morphological features. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF) has revolutionized clinical microbiology laboratories making rapid and accurate identification possible.¹³ A study performed by Wragg and associates compared the identification of seventy six bacterial isolates by the Biolog GEN III MicroStation semi-automated bacterial identification system and the VITEK MS matrix-assisted laser desorption ionization-time of flight mass spectrometry.¹⁴ Five isolates were Staphylococci that were identified correctly by both systems compared to 16S ribosomal RNA gene sequencing.¹⁴ To the best of our knowledge studies comparing the Bruker MALDI-TOF BioTyper and other automated identification systems for identifying CNS are lacking in Canada.

The objective of this study was to compare the identification capability of the Bruker MALDI-TOF BioTyper to the Vitek 2 (bioMerieux) and Microbial Identification System (Microbial ID Inc.) gas liquid chromatography of coagulase negative staphylococci to the species level using isolates previously characterized biochemically and phenotypically.

Coagulase negative staphylococci

CNS isolates were obtained from clinical specimens at London Health Sciences, London, Ontario from specimens submitted to the microbiology laboratory. Strains isolated from significant sources such as blood, cerebrospinal fluid, peritoneal fluid and catheter tips were saved in glycerol citrate at -70oC and included in the study. Duplicate isolates from the same patient were excluded.

Four hundred and eighty five CNS were selected from a bank of organisms previously identified to the species (sp.) and subspecies (subsp.) level. The organisms were identified according to the classification scheme of Kloos and Schleifer.^12,15-17 All of the CNS isolates were identified by VITEK-2 (GP #21342, BioMerieux), Microbial Identification System (MIS) (Microbial ID Inc. Newark, Del.) which uses gas liquid chromatography¹⁸ and Bruker MALDI-TOF BioTyper (Bruker Daltronics, Germany) the results were compared and discrepant results were resolved by 16sRNA sequencing.

The following strains were included to be identified by the Bruker BioTyper MALDI-TOF (Figure 1): S. capitis (n=100), S. caprae (n=50), S. capitis, S. cohnii (n=49), S. epidermidis (n=90), S. haemolyticus (n=25), S. hominis (n=17), S. intermedius (n=7), S. lugdunensis (n=25), S. saprophyticus(n=25), S. schleiferi (n=22), S. simulans (n=24), S. warneri (n=24) and S. xylosus (n=27).

American Type Culture Collection strains

The following American Type Culture Collection (ATCC) strains were used for quality control: Staphylococcus cohnii ATCC 29974, S. epidermidis ATCC 14990, S. haemolyticus ATCC 29970, S. hominis ATCC 27845, S. intermedius ATCC 29663, S. saprophyticus ATCC 15305, S. warneri ATCC 27836, and S. xylosus ATCC 29971.

Bruker MALDI-TOF BioTyper

The CNS were cultured from glycerol citrate onto Columbia 5% sheep blood agar plates (Oxoid, MP0351) subcultured twice and incubated at 35 °C in 5% CO₂. The Bruker MALDI-TOF BioTyper 48 target plate was inoculated with bacterial test standard (Bruker #8255343) and calibration was performed according to the recommendations of the manufacturer. The test organisms were applied to each target spot as a thin monolayer using the direct colony transfer method according to the manufacturer’s recommendation. The target spot was allowed to dry and 1uL of 70% formic acid was added, followed by 1uL of matrix (Bruker, HCCA #8255344) and the target plate was allowed to dry at room temperature.

Identification criteria for the Bruker MALDI-TOF BioTyper

The identificationsof the isolates were performed on a Microflex LT instrument (Bruker Daltonics, Germany) with Flex Control (version 3.0) software (Bruker Daltonics, Germany) for the automatic acquisition of mass spectra in the linear positive mode within a range of 2 to 20 kDa. Automated analysis of the raw spectral data was performed by the MALDI BioTyper automation (version 2.0) software (Bruker Daltonics, Germany).

Identification criteria were followed as stipulated by the manufacturer

The identification criteria included a score, a color grading and a consistency category. If identification was not considered acceptable according to the recommended criteria the identification was repeated, the result was recorded as a failed identification if all of the acceptance criteria were not met on repeat testing. The final Bruker MALDI-TOF BioTyper identification results were compared to the identification by Vitek2 and MIS gas liquid chromatography.

Discordant results

Results were considered to be discordant if the Bruner MALDI-TOF BioTyper identification did not correlate with the anticipated species. All discordant results at the specieslevel were sent for 16S rRNA sequencing at a reference facility.

Bruker MALDI-TOF BioTyper results

A total of 485 CNS isolates were identified by the Bruker MALDI-TOF BioTyper (B). The identifications were evaluated according to highest and lowest scores(hS, lS),best and worst consistency(bC, wC) for each species and the average (A) score for next possible identification as seen in Table 1.

The Bruker MALDI TOF BioTyper correctly identified 470 (96%) of the isolates on the initial identification run, thirteen isolates of S. cohnii, one S. warneri and one S. xylosus were re-identified on the Bruker BioTyper as they failed their initial identification run based on their consistency (C-) and their initial score of less than 1.7. Subsequently they all passed the identification criteria and identified as the correct species. The final results reflected that theBruker MALDI TOF BioTyper identified 485 (100%) of the isolates correctly to the species level (score≥2.0).

Comparative data for the three identification systems

The identification results were subsequently compared to the results obtained by the VITEK 2 (V) and MIS gas liquid chromatography (M) these results are presented in Table 2.

One isolate of S. saprophyticus was identified as S. xylosus (hS=2.216, bC=A++, next sp. score=1.648) by the Bruker MALDI-TOF BioTyper and by the MIS gas liquid chromatography. This isolate was confirmed by a reference laboratory with 16S rRNA analysis to be S. xylosus. Vitek 2 identified this isolate as S. warneri. The final results for S. saprophyticus and S. xylosus were adjusted and were as follows S. saprophyticus(n=24, B_sp.=100%, B_subsp.=100% V_sp.=79%,V_subsp.=79%, M_sp.= 92%, M_subsp.= 92%)and S. xylosus (n=28, B_sp.=100%, V_sp.=89%, M_sp.= 96%).

Overall the Bruker MALDI-TOF identified 485(100%) of the isolates to the species level, Vitek 2 identified 88.6% and the MIS gas liquid chromatography identified 60.8% of the coagulase staphylococcus correct to the species and subspecies where applicable.

This study compared the ability of the Bruker MALDI-TOF BioTyper to identify CNS to the species level. All isolates were identified with all three systems; this presented us with an excellent opportunity to evaluate the Bruker MALDI-TOF BioTyper.

CNS consists of organisms playing a complex and diverse role in infectious diseases, ranging from normal microbiota to opportunistic pathogens and accurate identification may be important to ensure effective patient care.⁵ The ease of use of the Bruker MALDI-TOF BioTyper makes it an attractive method. Current automated systems most frequently used in diagnostic laboratories include Vitek2 (bioMerieux) and the BD Phoenix system (Becton Dickinson).¹⁹ There is a lack of reports and or studies comparing these systems ability to identify CNS with the Bruker MALDI-TOF BioTyper. Ligozzi et al.²⁰ and Spanu et al.²¹ respectively reported success rates of identifying CNS with the Vitek 2 to the species level of 86% and 90,5% both these studies noted that the identification of S. hominis was problematic and needed improvement. Funke and Funke-Kissling²² used the colorimetric based VITEK 2 ID-GP identification card and concluded that the Vitek2 was reliable in identifying staphylococci correctly.²² In a study performed by Wragg and associates 5 isolates of CNS were identified to the correct genus and species level by the VITEK MS giving overall comparable results to the Biolog GEN III MicroStation semi-automated bacterial identification system and 16S ribosomal RNA gene sequencing.¹⁴

In our study we evaluated the ability of the Bruker MALDI-TOF BioTyper to identify most of the clinically relevant CNS that we routinely encounter in our laboratory. During the study we included eight American Type Culture Collection (ATCC) strains in every run of identifications to act as positive controls and reference isolates. All the instruments correctly identified the ATCC strains.

The Bruker MALDI-TOF BioTyper performed exceptionally well, speciating all four hundred and eighty five (100%) of the coagulase negative staphylococci compared to Vitek-2’s 88.6% and MIDI 60.8% (Table 2). Although we did not intentionally pursue or include subspeciating CNS we noted that S. capitis sub sp. ureolyticus posed some problems with 48 of 50 (96%) isolates being identified as S. capitis sub sp. Capitis by the Bruker BioTyper. Retesting of S. capitis sub sp. ureolyticus using a thinner monolayer on the target plate had no impact on the final identification. All of the S. capitis sub sp. ureolyticus had excellent scores in excess of 2.00, similarly the S. capitis sub sp. capitis had equally good results. This probably is indicative of the close relationship of these two species. One isolate S. saprophyticus was identified as a S. xylosus by both the Bruker BioTyper and the MIS gas liquid chromatography and we subsequently confirmed this identification by16S rRNA sequencing.. The results were adjusted accordingly and reflected that all of the S. saprophyticus (n=24) were in fact identified correctly.

The Bruker BioTyper databank supports identification of relevant staphylococci to the subspecies level. Subspeciating was however not part of the initial objective of this study, it was noted however that where applicable it did perform adequately in subspeciating the isolates correctly with the exception of S. capitis where a 48 (96%) of subspecies urealyticus were identified as subspecies capitis. This was noted with all three systems, indicating that these two subspecies are very closely related. The clinical impact of such an error is questionable, with no anticipated change in antibiotic treatment or disease spectrum. Since this study has been completed an update of the Bruker MALDI-TOF BioTyper databank has been performed, this update may actually improve identification of these closely related subspecies. In conclusion the Bruker MALDI-TOF BioTyper presents a simple and accurate identification system for coagulase negative staphylococci in the routine diagnostic microbiology laboratory.

None.

The author declares no conflict of interest.

1. Kloos WE, Schleifer KH. Simplified scheme for routine identification of human Staphylococcus species. J Clin Microbiol. 1975;1(1):82–88.
2. Kloos WE, Lambe DW. Staphylococcus. In: Balows A, Hausler WJ, Herrmann KL, Isenberg HD, Shadomy HJ, editors. Manual of clinical microbiology. 5th ed. USA: American Society for Microbiology; 1991. p. 222–237.
3. Crossley KB, Archer GL. The staphylococci in human disease. USA: Churchill Livingstone Inc; 1997.
4. Tornero E, Garcia–Oltra E, Garcia–Ramiro S, et al. Prosthetic joint infections due to Staphylococcus aureus and coagulase–negative staphylococci. Int J Artif Organs. 2012;35(10):884–892.
5. Rogers KL, Fey PD, Rupp ME. Coagulase–negative staphylococcal infections. Infect Dis Clin North Am. 2009;23(1):73–98.
6. Cabrera Contreras R, Morelos Ramirez R, Galicia Camacho AN, et al. Antibiotic Resistance and Biofilm Production in Staphylococcus epidermidis Strains, Isolated from a Tertiary Care Hospital in Mexico City. ISRN Microbiology. 2013;2013:918921.
7. Calvo J, Hernandez JL, Farinas MC, et al. Osteomyelitis caused by Staphylococcus schleiferi and evidence for misidentification of this Staphylococcus species by an automated bacterial identification system. J Clin Microbiol. 2000;38(10):3887–3889.
8. Oliveira A, Cunha M. Bacterial biofilms with emphasis on coagulase–negative staphylococci. J Venom Anim Toxins incl Trop Dis. 2008;14(4):572–596.
9. Piette A, Verschraegen G. Role of coagulase–negative staphylococci in human disease. Vet Microbiol. 2009;134(1–2):45–54.
10. Delmas J, Chacornac JP, Robin F, et al. Evaluation of the Vitek 2 System with a Variety of Staphylococcus Species. J Clin Microbiol. 2008;46(1):311–313.
11. Layer F, Ghebremedhin B, Moder KA, et al. Comparative study using various methods for identification of Staphylococcus species in clinical specimens. J Clin Microbiol. 2006;44(8):2824–2830.
12. Kloos WE, Zimmerman RJ, Smith RF. Preliminary studies on the characterization and distribution of Staphylococcus and Micrococcus species on animal skin. Appl Environ Microbiol. 1976;31(1):53–59.
13. Clark AE, Kaleta EJ, Arora A, et al. Matrix–assisted laser desorption ionization–time of flight mass spectrometry: a fundamental shift in the routine practice of clinical microbiology. Clin Microbiol Rev. 2013;26(3):547–603.
14. Wragg P, Randall L, Whatmore AM. Comparison of Biolog GEN III MicroStation semi–automated bacterial identification system with matrix–assisted laser desorption ionization–time of flight mass spectrometry and 16S ribosomal RNA gene sequencing for the identification of bacteria of veterinary interest. J Microbiol Methods. 2014;105:16–21.
15. Oeding P, Digranes A. Classification of coagulase–negative staphylococci in the diagnostic laboratory. Acta Pathol Microbiol Scand B. 1977;85(2):136–142.
16. Schleifer KH, Kloos WE. A simple test system for the separation of staphylococci from micrococci. J Clin Microbiol. 1975;1(3):337–338.
17. Wilkinson BJ, Maxwell S, Schaus SM. Classification and characteristics of coagulase–negative, methicillin–resistant staphylococci. J Clin Microbiol. 1980;12(2):161–166.
18. Stoakes L, John MA, Lannigan R, et al. Gas–liquid chromatography of cellular fatty acids for identification of staphylococci. J Clin Microbiol. 1994;32(8):1908–1910.
19. Wallet F, Loiez C, Renaux E, et al. Performances of VITEK 2 colorimetric cards for identification of gram–positive and gram–negative bacteria. J Clin Microbiol. 2005;43(9):4402–4406.
20. Ligozzi M, Bernini C, Bonora MG, et al. Evaluation of the VITEK 2 system for identification and antimicrobial susceptibility testing of medically relevant gram–positive cocci. J Clin Microbiol. 2002;40(5):1681–1686.
21. Spanu T, Sanguinetti M, Ciccaglione D, et al. Use of the VITEK 2 system for rapid identification of clinical isolates of staphylococci from bloodstream infections. J Clin Microbiol. 2003;41(9):4259–4263.
22. Funke G, P Funke–Kissling. Performance of the new VITEK 2 GP card for identification of medically relevant gram–positive cocci in a routine clinical laboratory. J Clin Microbiol. 2005;43(1):84–88.