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.

Assessment of the stability of cell-surface components of microorganisms by MALDI-TOF-MS following preservation on lenticule discs.

Strains representing the species Campylobacter coli, Escherichia coli, Listeria monocytogenes, Pseudomonas aeruginosa, Salmonella enterica, and Staphylococcus aureus were randomly selected to assess the consistency of cells preserved on lenticule discs to those archived in traditional freeze-dried ampoules. Each matched pair was cultured using identical conditions and analysed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MS) to profile the surface-associated molecules of the cells. In addition, the cytosolic/membrane-bound proteins of C. coli and S. aureus strains were further analysed by surface-enhanced laser desorption/ionization time-of-flight MS. The mass spectral profiles in all cases showed a high degree of concordance between cells preserved by both methods and suggest that the properties of cells preserved on lenticule disc are consistent with those archived by the traditional method of freeze-drying.

Tracing the transition of methicillin resistance in sub-populations of Staphylococcus aureus, using SELDI-TOF Mass Spectrometry and Artificial Neural Network Analysis.

Strains (n=99) of Staphylococcus aureus isolated from a large number of clinical sources and tested for methicillin sensitivity were analysed by MALDI-TOF-MS using the Weak Cation Exchange (CM10) ProteinChip Array (designated SELDI-TOF-MS). The profile data generated was analysed using Artificial Neural Network (ANN) Analysis modelling techniques. Seven key ions identified by the ANNs that were predictive of MRSA and MSSA were validated by incorporation into a model. This model exhibited an area under the ROC curve value of 0.9147 indicating the potential application of this approach for rapidly characterising MRSA and MSSA isolates. Nearly all strains (n=97) were correctly assigned to the correct group, with only two aberrant MSSA strains being misclassified. However, approximately 21% of the strains appeared to be in a process of transition as resistance to methicillin was being acquired.

High throughput identification of clinical isolates of Staphylococcus aureus using MALDI-TOF-MS of intact cells.

Staphylococcus aureus remains an important human pathogen responsible for a high burden of disease in healthcare and community settings. The emergence of multidrug-resistant strains is of increasing concern world-wide. The identification of S. aureus is currently based upon phenotypic and genotypic methods. Here, an alternative approach involving mass spectral analysis of surface-associated proteins of intact bacterial cells by matrix-assisted laser desorption/ionisation time of flight mass spectrometry (MALDI-TOF-MS) was investigated using 95 isolates obtained directly from a clinical laboratory at The Royal London Hospital and 39 isolates from the Staphylococcal Reference Unit, Health Protection Agency, London. Results obtained indicate that clinical isolates share many common mass ions with-type/reference strains which allowed their correct identification when searched against a comprehensive database that has been in the process of development for several years. The existing database contains more than 5000 profiles of various bacterial pathogens, but comprises mainly type or reference strains. The MicrobeLynx software successfully identified all isolates to the correct genus and all but four to the correct species. These were misidentified in the first instance due to contamination or low mass ion intensity but once the cultures were purified and re-analysed they were confirmed as S. aureus by both MALDI-TOF-MS and 16S rRNA sequence analysis. The high percentage of correct identifications coupled with the high speed and the minimal sample preparation required, indicate that MALDI-TOF-MS has the potential to perform high throughput identification of clinical isolates of S. aureus despite the inherent diversity of this species. The method is, however, only reproducible if variable parameters such as sample preparation, media, growth condition, etc. are standardised.