Use of whole-genus genome sequence data to develop a multilocus sequence typing tool that accurately identifies Yersinia isolates to the species and subspecies levels

The genus Yersinia is a large and diverse bacterial genus consisting of human-pathogenic species, a fish-pathogenic species, and a large number of environmental species. Recently, the phylogenetic and population structure of the entire genus was elucidated through the genome sequence data of 241 strains encompassing every known species in the genus. Here we report the mining of this enormous data set to create a multilocus sequence typing-based scheme that can identify Yersinia strains to the species level to a level of resolution equal to that for whole-genome sequencing. Our assay is designed to be able to accurately subtype the important human-pathogenic species Yersinia enterocolitica to whole-genome resolution levels. We also report the validation of the scheme on 386 strains from reference laboratory collections across Europe. We propose that the scheme is an important molecular typing system to allow accurate and reproducible identification of Yersinia isolates to the species level, a process often inconsistent in nonspecialist laboratories. Additionally, our assay is the most phylogenetically informative typing scheme available for Y. enterocolitica

Changing concepts in the characterisation of microbes and the influence of mass spectrometry

This chapter contains sections titled:Background and Early Attempts to Use Mass Spectrometry on MicrobesCharacterisation of Microorganisms by MALDI-TOF-MS; from Initial Ideas to the Development of the First Comprehensive DatabaseCharacterisation of Microorganisms from Their Intracellular/Membrane Bound Protein Profiles Using Affinity Capture with Particular Reference to Surface-Enhanced Laser Desorption/Ionisation (SELDI)-TOF-MSComparative Analysis of Proteomes of Diverse Strains within a Species; Use of 2D Fluorescence Difference Gel Electrophoresis (DIGE)Nanoparticles as an Alternative Approach in the Analysis and Detection of Low Abundance and Low Molecular Weight Proteins Using MALDI-TOF-MSReference