Details

Autor(en) / Beteiligte

• Lundquist, Margaretha
• Caspersen, Mikael B.
• Wikström, Per
• Forsman, Mats

Titel

Discrimination of Francisella tularensis subspecies using surface enhanced laser desorption ionization mass spectrometry and multivariate data analysis

Ist Teil von

• FEMS microbiology letters, 2005-02, Vol.243 (1), p.303-310

Ort / Verlag

Oxford, UK: Elsevier B.V

Erscheinungsjahr

2005

Link zum Volltext

Quelle

Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals

Beschreibungen/Notizen

• Francisella tularensis causes the zoonotic disease tularemia, and is considered a potential bioterrorist agent due to its extremely low infection dose and potential for airborne transmission. Presently, F. tularensis is divided into four subspecies; tularensis, holarctica, mediasiatica and novicida. Phenotypic discrimination of the closely related subspecies with traditional methods is difficult and tedious. Furthermore, the results may be vague and they often need to be complemented with virulence tests in animals. Here, we have used surface enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) to discriminate between the four subspecies of F. tularensis. The method is based on the differential binding of protein subsets to chemically modified surfaces. Bacterial thermolysates were added to anionic, cationic, and copper ion-loaded immobilized metal affinity SELDI chip surfaces. After binding, washing, and SELDI-TOF-MS different protein profiles were obtained. The spectra generated from the different surfaces were then used to characterize each bacterial strain. The results showed that the method was reproducible, with an average intensity variation of 21%, and that the mass precision was good (300–450 ppm). Moreover, in subsequent cluster analysis and principal component analysis (PCA) data for the analyzed Francisella strains grouped according to the recognized subspecies. Partial least squares-discriminant analysis (PLS-DA) of the protein profiles also identified proteins that differed between the strains. Thus, the protein profiling approach based on SELDI-TOF-MS holds great promise for rapid high-resolution phenotypic identification of bacteria.