Assignment of Streptococcus agalactiae isolates to clonal complexes using a small set of single nucleotide polymorphisms

E Honsa, T Fricke, A STEPHENS, Danny Ko, Fanrong Kong, G Gilbert,, F HUYGENS, Philip Giffard

    Research output: Contribution to journalArticle

    Abstract

    Background. Streptococcus agalactiae (Group B Streptococcus (GBS)) is an important human pathogen, particularly of newborns. Emerging evidence for a relationship between genotype and virulence has accentuated the need for efficient and well-defined typing methods. The objective of this study was to develop a single nucleotide polymorphism (SNP) based method for assigning GBS isolates to multilocus sequence typing (MLST)-defined clonal complexes. Results. It was found that a SNP set derived from the MLST database on the basis of maximisation of Simpsons Index of Diversity provided poor resolution and did not define groups concordant with the population structure as defined by eBURST analysis of the MLST database. This was interpreted as being a consequence of low diversity and high frequency horizontal gene transfer. Accordingly, a different approach to SNP identification was developed. This entailed use of the "Not-N" bioinformatic algorithm that identifies SNPs diagnostic for groups of known sequence variants, together with an empirical process of SNP testing. This yielded a four member SNP set that divides GBS into 10 groups that are concordant with the population structure. A fifth SNP was identified that increased the sensitivity for the clinically significant clonal complex 17 to 100%. Kinetic PCR methods for the interrogation of these SNPs were developed, and used to genotype 116 well characterized isolates. Conclusion. A five SNP method for dividing GBS into biologically valid groups has been developed. These SNPs are ideal for high throughput surveillance activities, and combining with more rapidly evolving loci when additional resolution is required. � 2008 Honsa et al; licensee BioMed Central Ltd.
    Original languageEnglish
    Pages (from-to)140-149
    Number of pages10
    JournalBMC Microbiology
    Volume8
    Publication statusPublished - 2008

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