Superantigen gene complement of Streptococcus pyogenes—relationship with other typing methods and short-term stability

  • A. Friães
  • F. R. Pinto
  • C. Silva-Costa
  • M. RamirezEmail author
  • J. Melo-Cristino


The profiling of the superantigen (SAg) encoding genes has been frequently used as a complementary typing method for group A streptococci (GAS), but a confusing gene nomenclature and a large diversity of primers used in screening has led to some conflicting results. The aim of this work was to develop a polymerase chain reaction (PCR) method capable of efficiently amplifying all the known allelic variants of these genes, and to evaluate the congruence of this methodology with other commonly used molecular typing methods. The presence of the 11 known SAg genes and two other exotoxin-encoding genes (speB and speF) was tested in a collection of 480 clinical GAS isolates, using two multiplex PCR reactions. The SAg gene profile was compared with other typing methods. Four naturally occurring deletions involving the genes speB, speF, and rgg were characterized, two of which were found among invasive isolates. The absence of the chromosomally encoded genes speG and smeZ was supported by Southern blot hybridization and associated with specific GAS lineages, while the presence of phage-encoded genes was more variable. Positive associations between SAg genes or between SAg profiles and emm types or pulsed-field gel electrophoresis (PFGE) clusters were observed. The results suggest that the SAg profile diversifies faster than other properties commonly used for molecular typing, such as emm type and multilocus sequence typing (MLST) sequence types (STs), and can be a useful complement in GAS molecular epidemiology. Still, the short-term stability of the SAg gene profile among prevalent genetic lineages may largely explain the observed associations between SAg genes.


PFGE Cluster Multiplex Polymerase Chain Reaction Reaction Strain MGAS315 Pharyngeal Exudate Lateral Genetic Transfer Event 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was partially supported by Fundação para a Ciência e Tecnologia (FCT), Lisbon, Portugal (PTDC/SAU-ESA/72321/2006), and Fundação Calouste Gulbenkian.

Conflict of interest

Dr. José Melo-Cristino has received research grants administered through his university and received honoraria for consulting and serving on the speakers bureaus of Pfizer, Bial, GlaxoSmithKline, and Novartis. Dr. Mário Ramirez has received honoraria for consulting and serving on the speakers bureau of Pfizer. The other authors declare no conflict of interest. No company or financing body had any influence on the decision to publish this paper.

Supplementary material

10096_2012_1726_MOESM1_ESM.pdf (9 kb)
ESM 1 (PDF 8.62 kb)
10096_2012_1726_MOESM2_ESM.pdf (31 kb)
Figure S1 Relationship between individual SAgs and emm and PFGE. The significant Jaccard coefficients obtained when comparing all SAgs with emm types (panel A) and PFGE80 clusters (panel B) detected are represented. Lighter shades of gray represent weaker associations, while darker shades of gray represent stronger associations. (PDF 31 kb)
10096_2012_1726_MOESM3_ESM.pdf (30 kb)
Figure S2 Relationship between SAg profile and emm and PFGE. The significant Jaccard coefficients obtained when comparing all SAg profiles with emm types (panel A) and PFGE80 clusters (panel B) detected are represented. Lighter shades of gray represent weaker associations, while darker shades of gray represent stronger associations. (PDF 30 kb)
10096_2012_1726_MOESM4_ESM.pdf (22 kb)
Figure S3 Relationship between emm and PFGE. The significant Jaccard coefficients obtained when comparing all emm types detected with all PFGE80 clusters are represented. Lighter shades of gray represent weaker associations, while darker shades of gray represent stronger associations. (PDF 22 kb)


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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • A. Friães
    • 1
  • F. R. Pinto
    • 2
  • C. Silva-Costa
    • 1
  • M. Ramirez
    • 1
    Email author
  • J. Melo-Cristino
    • 1
  1. 1.Instituto de Microbiologia, Instituto de Medicina Molecular, Faculdade de MedicinaUniversidade de LisboaLisboaPortugal
  2. 2.Centro de Química e Bioquímica, Faculdade de CiênciasUniversidade de LisboaLisboaPortugal

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