Journal article
Identification and interrogation of highly informative single nucleotide polymorphism sets defined by bacterial multilocus sequence typing databases
Journal of Medical Microbiology, Vol.53(1), pp.35-45
2004
Abstract
A unified, bioinformatics-driven, single nucleotide polymorphism (SNP)-based approach to microbial genotyping has been developed. Multilocus sequence typing (MLST) databases consist of known variants of standardized housekeeping genes. Normally, seven fragments are defined; a seq uence type (ST) consists of the variants of these fragments that are found in a particular isolate. A computer program that can identify highly informative sets of SNPs in entire MLST databases has been constructed. The SNPs either define a particular user-specified ST or provide a high value for Simpson's index of diversity (D), and may thus be generally applicable to that species. SNP sets that are diagnostic for Neisseria meningitidis ST-11 and ST-42, and high-D SNP sets for N. meningitidis and Staphylococcus aureus, were identified and real-time PCR methods to interrogate these SNPs were demonstrated. High-D SNP sets were also identified in other MLST databases. This widely applicable approach allows rapid genetic fingerprinting of infectious agents.
Details
- Title
- Identification and interrogation of highly informative single nucleotide polymorphism sets defined by bacterial multilocus sequence typing databases
- Authors
- G A Robertson (Author) - Queensland University of TechnologyV Thiruvenkataswamy (Author) - Queensland University of TechnologyH Shilling (Author) - Queensland University of TechnologyErin P Price (Author) - Queensland University of TechnologyF Huygens (Author) - Queensland University of TechnologyF A Henskens (Author) - University of NewcastleP M Giffard (Author) - Queensland University of Technology
- Publication details
- Journal of Medical Microbiology, Vol.53(1), pp.35-45
- Publisher
- Microbiology Society
- Date published
- 2004
- DOI
- 10.1099/jmm.0.05365-0
- ISSN
- 0022-2615
- Organisation Unit
- University of the Sunshine Coast, Queensland; Centre for Bioinnovation
- Language
- English
- Record Identifier
- 99451050202621
- Output Type
- Journal article
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