Fast and simple epidemiological typing of Pseudomonas aeruginosa using the double-locus sequence typing (DLST) method

Eur J Clin Microbiol Infect Dis. 2014 Jun;33(6):927-32. doi: 10.1007/s10096-013-2028-0. Epub 2013 Dec 11.


Although the molecular typing of Pseudomonas aeruginosa is important to understand the local epidemiology of this opportunistic pathogen, it remains challenging. Our aim was to develop a simple typing method based on the sequencing of two highly variable loci. Single-strand sequencing of three highly variable loci (ms172, ms217, and oprD) was performed on a collection of 282 isolates recovered between 1994 and 2007 (from patients and the environment). As expected, the resolution of each locus alone [number of types (NT) = 35-64; index of discrimination (ID) = 0.816-0.964] was lower than the combination of two loci (NT = 78-97; ID = 0.966-0.971). As each pairwise combination of loci gave similar results, we selected the most robust combination with ms172 [reverse; R] and ms217 [R] to constitute the double-locus sequence typing (DLST) scheme for P. aeruginosa. This combination gave: (i) a complete genotype for 276/282 isolates (typability of 98%), (ii) 86 different types, and (iii) an ID of 0.968. Analysis of multiple isolates from the same patients or taps showed that DLST genotypes are generally stable over a period of several months. The high typability, discriminatory power, and ease of use of the proposed DLST scheme makes it a method of choice for local epidemiological analyses of P. aeruginosa. Moreover, the possibility to give unambiguous definition of types allowed to develop an Internet database ( ) accessible by all.

Publication types

  • Evaluation Study

MeSH terms

  • Genotype
  • Humans
  • Molecular Epidemiology / methods
  • Multilocus Sequence Typing / methods*
  • Pseudomonas Infections / epidemiology
  • Pseudomonas Infections / microbiology
  • Pseudomonas aeruginosa / classification*
  • Pseudomonas aeruginosa / genetics*
  • Pseudomonas aeruginosa / isolation & purification
  • Reproducibility of Results
  • Sensitivity and Specificity