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J Clin Microbiol. 2012 December; 50(12): 4087–4090.
PMCID: PMC3502998

Identification of Clinical Isolates of α-Hemolytic Streptococci by 16S rRNA Gene Sequencing, Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry Using MALDI Biotyper, and Conventional Phenotypic Methods: a Comparison


Fifty-six α-hemolytic streptococcal isolates were identified using MALDI Biotyper MS (Bruker Daltonics), API 20 Strep (bioMérieux), and BD Phoenix (Becton, Dickinson). The gold standard for identification was 16S rRNA gene sequence analysis with 16S-23S rRNA intergenic spacer sequencing. The following percentages of isolates were correctly identified to the species level: MALDI Biotyper, 46%; BD Phoenix, 35%; and API 20 Strep, 26%.


Identification of α-hemolytic streptococci is clinically important (3, 15, 26, 27, 33, 34). The aim of this study was to evaluate and compare the reliability of API 20 Strep, the automated BD Phoenix system, and MALDI Biotyper MS for clinically identifying significant isolates of α-hemolytic streptococci to the species and group levels. MALDI Biotyper has been found to give high-confidence identifications for β-hemolytic streptococci (8). As a gold standard, 16S rRNA gene sequencing was used (4, 5, 7, 15, 22, 31), with a sequence homology of 99% or greater with published species sequences considered to denote the same species, in accordance with CLSI guidelines (10). For Streptococcus mitis group species, better discrimination was obtained by sequence analysis of the 16S-23S rRNA intergenic spacer (ITS) region (7). Taxonomy and nomenclature followed that outlined by Facklam at the CDC's Streptococcal Laboratory, Atlanta, GA (15), and subsequently cited and expanded upon by others (11, 24). Unlike previous studies of phenotypic methods (5, 6, 12, 16, 19, 20), this was a direct comparison of phenotypic methods versus the gold standard.

Bacterial isolates.

Forty-nine clinically relevant isolates (40 blood culture, 2 cerebrospinal fluid (CSF), 3 urine, 1 each from ascitic fluid, joint fluid, and an infected wound, and 1 from an unspecified site but referred as clinically significant) of α-hemolytic streptococci (except Streptococcus pneumoniae) were collected prospectively from sterile sites cultured in three clinical laboratories. Additionally, a selection of fully characterized strains was used, including NCTC 11086 (Streptococcus sanguinis), NCTC 11427 (Streptococcus parasanguinis), NCTC 10904 (S. sanguinis), M99 and SK12 (both Streptococcus gordonii) (23), SK36 (S. sanguinis) (35), and UA159 (Streptococcus mutans) (1).

API 20 Strep and BD Phoenix automated identification.

API 20 Strep (bioMérieux) and BD Phoenix (Becton, Dickinson) tests were carried out according to the manufacturers' instructions, with Apiweb 1.2.1 software used to identify API codes. BD Phoenix SMIC/ID streptococcal identification panels were used. Following the manufacturers' recommendations, identification with a score of <80% for API 20 Strep or <90% for BD Phoenix was considered unacceptable. If a similar result was obtained on repeat testing, the strain was assigned as unidentified by that method.

MALDI Biotyper identification.

The MALDI Microflex (matrix-assisted laser desorption ionization–time of flight mass spectrometry [MALDI-TOF MS]; Bruker Daltonics GmbH, Bremen, Germany) with MALDI Biotyper software 2.0 was used. Identifications were performed according to the manufacturer's instructions, using the full extraction procedure as described previously (18) with isolates from chocolate blood agar (Oxoid, Basingstoke, United Kingdom). The extraction method is superior to direct colony testing for Gram-positive cocci (2). Samples on the target plate were left to air dry before adding the matrix solution (saturated solution of alpha-4-cyano-hydrocycinnamic acid in 50% acetonitrile and 2.5% trifluoracetic acid solution, all LC-MS quality; Sigma) and placing the plate in the MALDI Biotyper system. According to the manufacturer, a score of >2 indicates secure genus and probable species identification (18). These recommended evaluation criteria have been scrutinized in other studies which have found that acceptable identifications can be obtained by using scores ≥1.9 (25) or ≥1.7 (9, 13, 32) in most genera. Nonetheless, for isolates with a score of <2, the test was repeated. Where repeat testing still resulted in a score of <2 but ≥1.7, the result was recorded together with the score.

16S rRNA gene and 16S-23S ITS spacer region amplification and sequencing.

The 16S rRNA gene was amplified using the bacterium-specific universal primers LPW57 (5′ AGTTTGATCCTGGCTCAG) and LPW58 (5′AGGCCCGGGAACGTATTCAC) to amplify an ~1.5-kb fragment (34). PCR amplification was performed on a Rotorgene 6000 real-time PCR machine (Qiagen, Crawley, United Kingdom) (21) under the following conditions: an initial incubation at 95°C for 4 min, 35 cycles of 95°C for 30 s, 50°C for 45 s, and 72°C for 1 min, followed by a final incubation at 72°C for 10 min. Primers and excess nucleotides were removed using a PCR cleanup kit (Qiagen). DNA sequencing was performed by Source BioScience (Cambridge, United Kingdom) using the PCR primers. 16S rRNA gene sequences were subjected to BLAST analysis against the NCBI nucleotide database. When an isolate was from the S. mitis group and 16S rRNA BLAST analysis could not identify it to the species level, PCR amplification and sequencing of the shorter (<400 bp) ITS region of the 16S-23S rRNA genes were performed as described, using a second pair of bacterium-specific universal primers, 13BF (5′-GTGAATACGTTCCCGGGCCT-3′) and 6R (5′-GGGTTTCCCCGTTCGGAAAT-3′) (7). Identification of other isolates was solely by analysis of the 16S rRNA gene sequence against the NCBI database, with verification against the curated Greengenes database ( not revealing any differences in identification.


Of the 49 clinical isolates, 39 gave 16S rRNA gene sequencing results with ≥99% similarity to published species (10). An additional 6 isolates had a similarity of >97% but <99%, reportable under CLSI guidelines such as “Streptococcus species most closely related to (likely species name).” These are not included in the table. The species distribution of these significant (mainly bloodstream) α-hemolytic streptococcal isolates is similar to that described previously by others (17). The species identifications of the 39 clinical isolates definitively identified by molecular methods and the reference isolates are shown in Table 1, along with the relative performance of each test method. Separate columns show the MALDI Biotyper results when using scores of 2 and 1.7 as a cutoff. A score of <2 but ≥1.7 was recorded for four clinical isolates and one reference isolate. None of the phenotypic methods used were reliable for identification to the species level: the MALDI Biotyper system performed best. Among the reference strains alone, the MALDI Biotyper again performed best, correctly identifying all seven of the strains when a cutoff score of >1.7 was applied or 6 (86%) with a cutoff score of >2, followed by BD Phoenix, which correctly identified 4/7 (57%), and API 20 Strep, which correctly identified 2/7 (29%). For the clinical isolates alone, all methods scored less well than for the reference isolates: when the seven reference isolates were excluded from the analysis, the MALDI Biotyper correctly identified 36% (cutoff score of >1.7) or 28% (cutoff score of >2), BD Phoenix correctly identified 31%,and API 20 Strep correctly identified 23%. The MALDI Biotyper would have performed better overall were it not for its particularly poor performance with S. mitis isolates, failing to correctly identify any of the 20 S. mitis isolates, naming 13 as Streptococcus oralis (all with scores of >2) and 7 as Streptococcus pneumoniae (all with scores of >2). This led to much better success with identification at the group level than at the species level. The overidentification of S. pneumoniae by the MALDI Biotyper has been previously noted (30): the manufacturers give a “matching hint,” advising further testing when an identification of S. pneumoniae is obtained. API 20 Strep was let down by a poor ability to identify S. oralis, all bar one of which it identified as S. mitis. For group level identification, there was greater similarity between methods than for exact species identification (Table 1).

Comparison of BD Phoenix, API 20 Strep, and MALDI Biotyper for identification of clinical (n = 39) and reference (n = 7) α-hemolytic streptococci at the group and species levels

Gene sequence analysis remains the most reliable method by far for the laboratory identification of α-hemolytic streptococci. Although MALDI Biotyper identification performed slightly better than the conventional identification methods tested, it does not yet display the generally excellent identification seen with other genera of microorganisms (9, 14, 28, 29, 32). Further development of the database may help to improve its performance; in particular, an improvement in its ability to identify S. mitis group streptococci would greatly enhance its reliability.


This work was supported by an NHS R&D grant from Velindre NHS Trust and in part by a grant from the Wales Office for Research and Development, which allowed funding for the Rotorgene 6000 platform.

We thank the staff of Public Health Wales Microbiology Abertawe Bro Morgannwg Swansea Laboratory and Graham Harrison, Michael Ruddy, and the staff of Public Health Wales Microbiology Carmarthenshire and Aberystwyth Laboratories for collecting and supplying isolates and clinical information. We thank Bruker Daltonics GmbH, Bremen, Germany, for the loan of the Bruker Daltonics Microflex and the MALDI Biotyper system, which were used for the evaluation.


Published ahead of print 19 September 2012


1. Ajdić D, et al. 2002. Genome sequence of Streptococcus mutans UA159, a cariogenic dental pathogen. Proc. Natl. Acad. Sci. U. S. A. 99:14434–14439 [PubMed]
2. Alatoom AA, Cunningham SA, Ihde SM, Mandrekar J, Patel R. 2011. Comparison of direct colony method versus extraction method for identification of Gram-positive cocci by use of Bruker Biotyper matrix-assisted laser desorption ionization–time of flight mass spectrometry. J. Clin. Microbiol. 49:2868–2873 [PMC free article] [PubMed]
3. Baddour LM, et al. 2005. Infective endocarditis diagnosis, antimicrobial therapy, and management of complications: a statement for healthcare professionals from the Committee on Rheumatic Fever, Endocarditis, and Kawasaki Disease, Council on Cardiovascular Disease in the Young, and the Councils on Clinical Cardiology, Stroke, and Cardiovascular Surgery and Anesthesia, American Heart Association. Circulation 111:e394–e434 [PubMed]
4. Bizzini A, Greub G. 2010. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry, a revolution in clinical microbial identification. Clin. Microbiol. Infect. 16:1614–1619 [PubMed]
5. Bosshard PP, Abels S, Altwegg M, Bottger EC, Zbinden R. 2004. Comparison of conventional and molecular methods for identification of aerobic catalase-negative Gram-positive cocci in the clinical laboratory. J. Clin. Microbiol. 42:2065–2073 [PMC free article] [PubMed]
6. Brigante G, et al. 2006. Use of the Phoenix automated system for identification of Streptococcus and Enterococcus spp. J. Clin. Microbiol. 44:3263–3267 [PMC free article] [PubMed]
7. Chen CC, Teng LJ, Chang TC. 2004. Identification of clinically relevant viridans group streptococci by sequence analysis of the 16S-23S ribosomal DNA spacer region. J. Clin. Microbiol. 42:2651–2657 [PMC free article] [PubMed]
8. Cherkaoui A, Emonet S, Fernandez J, Schorderet D, Schrenzel J. 2011. Evaluation of matrix-assisted laser desorption ionization-time of flight mass spectrometry for rapid identification of beta-hemolytic streptococci. J. Clin. Microbiol. 49:3004–3005 [PMC free article] [PubMed]
9. Cherkaoui A, et al. 2010. Comparison of two matrix-assisted laser desorption ionization–time of flight mass spectrometry methods with conventional phenotypic identification for routine identification of bacteria to the species level. J. Clin. Microbiol. 48:1169–1175 [PMC free article] [PubMed]
10. Clinical and Laboratory Standards Institute 2008. Interpretive criteria for identification of bacteria and fungi by DNA target sequencing; approved guideline. MM18-A Clinical and Laboratory Standards Institute, Wayne, PA
11. Doern CD, Burnham CA. 2010. It's not easy being green: the viridans group streptococci, with a focus on pediatric clinical manifestations. J. Clin. Microbiol. 48:3829–3835 [PMC free article] [PubMed]
12. Donay JL, et al. 2004. Evaluation of the automated phoenix system for potential routine use in the clinical microbiology laboratory. J. Clin. Microbiol. 42:1542–1546 [PMC free article] [PubMed]
13. El-Bouri K, et al. 2012. Comparison of bacterial identification by MALDI-TOF mass spectrometry and conventional diagnostic microbiology methods: agreement, speed and cost implications. Br. J. Biomed. Sci. 69:47–55 [PubMed]
14. Emonet S, Shah HN, Cherkaoui A, Schrenzel J. 2010. Application and use of various mass spectrometry methods in clinical microbiology. Clin. Microbiol. Infect. 16:1604–1613 [PubMed]
15. Facklam R. 2002. What happened to the Streptococci: overview of taxonomic and nomenclature changes. Clin. Microbiol. Rev. 15:613–630 [PMC free article] [PubMed]
16. Friedrichs C, Rodloff AC, Chhatwal GS, Schellenberger W, Eschrich K. 2007. Rapid identification of viridans streptococci by mass spectrometric discrimination. J. Clin. Microbiol. 45:2392–2397 [PMC free article] [PubMed]
17. Han XY, Kamana M, Rolston KVI. 2006. Viridans streptococci isolated by culture from blood of cancer patients: clinical and microbiologic analysis of 50 cases. J. Clin. Microbiol. 44:160–165 [PMC free article] [PubMed]
18. Harris LG, et al. 2010. Rapid identification of staphylococci from prosthetic joint infections using MALDI-TOF mass spectrometry. Int. J. Artif. Organs 33:568–574 [PubMed]
19. Hirakata Y, et al. 2005. Evaluation of the BD Phoenix Automated Microbiology System SMIC/ID panel for identification and antimicrobial susceptibility testing of Streptococcus spp. Diagn. Microbiol. Infect. Dis. 53:169–173 [PubMed]
20. Ikryannikova LN, et al. 2011. Misidentification of alpha-haemolytic streptococci by routine tests in clinical practice. Infect. Genet. Evol. 11:1709–1715 [PubMed]
21. Jukes L, et al. 2010. Rapid differentiation of Staphylococcus aureus, Staphylococcus epidermidis and other coagulase-negative staphylococci and meticillin susceptibility testing directly from growth-positive blood cultures by multiplex real-time PCR. J. Med. Microbiol. 59:1456–1461 [PubMed]
22. Kawamura Y, Hou X, Sultana F, Miura H, Ezaki T. 1995. Determination of 16S rRNA sequences of Streptococcus mitis and Streptococcus gordonii and phylogenetic relationships among members of the genus Streptococcus. Int. J. Syst. Bacteriol. 45:406–408 [PubMed]
23. Kerrigan SW, et al. 2007. Role of Streptococcus gordonii surface proteins SspA/SspB and Hsa in platelet function. Infect. Immun. 75:5740–5747 [PMC free article] [PubMed]
24. Köhler W. 2007. The present state of species within the genera Streptococcus and Enterococcus. Int. J. Med. Microbiol. 297:133–150 [PubMed]
25. La Scola B, Raoult D. 2009. Direct identification of bacteria in positive blood culture bottles by matrix-assisted laser desorption ionisation time-of-flight mass spectrometry. PLoS One 4:e8041. [PMC free article] [PubMed]
26. Ruoff KL, Miller SI, Garner CV, Ferraro MJ, Calderwood SB. 1989. Bacteremia with Streptococcus bovis and Streptococcus salivarius: clinical correlates of more accurate identification of isolates. J. Clin. Microbiol. 27:305–308 [PMC free article] [PubMed]
27. Seifert H. 2009. The clinical importance of microbiological findings in the diagnosis and management of bloodstream infections. Clin. Infect. Dis. 48:S238–S245 [PubMed]
28. Seng P, et al. 2009. Ongoing revolution in bacteriology: routine identification of bacteria by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Clin. Infect. Dis. 49:543–551 [PubMed]
29. Seng P, et al. 2010. MALDI-TOF-mass spectrometry applications in clinical microbiology. Future Microbiol. 5:1733–1754 [PubMed]
30. Stevenson LG, Drake SK, Murray PR. 2010. Rapid identification of bacteria in positive blood culture broths by MALDI-TOF mass spectrometry. J. Clin. Microbiol. 48:444–447 [PMC free article] [PubMed]
31. Summanen PH, Rowlinson MC, Wooton J, Finegold SM. 2009. Evaluation of genotypic and phenotypic methods for differentiation of the members of the Anginosus group streptococci. Eur. J. Clin. Microbiol. 28:1123–1128 [PMC free article] [PubMed]
32. van Veen SQ, Claas EC, Kuijper EJ. 2010. High-throughput identification of bacteria and yeast by matrix-assisted laser desorption ionization–time of flight mass spectrometry in conventional medical microbiology laboratories. J. Clin. Microbiol. 48:900–907 [PMC free article] [PubMed]
33. Whiley RA, Beighton D, Winstanley TG, Fraser HY, Hardie JM. 1992. Streptococcus intermedius, Streptococcus constellatus, and Streptococcus anginosus (the Streptococcus milleri group): association with different body sites and clinical infections. J. Clin. Microbiol. 30:243–244 [PMC free article] [PubMed]
34. Woo PCY, Cheung EYL, Leung K, Yuen K. 2001. Identification by 16S ribosomal RNA sequencing of an Enterobacteriaceae species with ambiguous biochemical profile from a renal transplant recipient. Diagn. Microbiol. Infect. Dis. 39:85–93 [PubMed]
35. Xu P, et al. 2007. Genome of the opportunistic pathogen Streptococcus sanguinis. J. Bacteriol. 189:3166–3175 [PMC free article] [PubMed]

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