Typing of the fish pathogen Listonella (Vibrio) anguillara by pyrolysis mass spectrometry

Characterization of Aphanomyces invadans isolates using pyrolysis mass spectrometry (PyMS)

Twenty-one isolates of Aphanomyces invadans, the fungal pathogen associated with the Asian fish disease epizootic ulcerative syndrome (EUS), were compared with other Oomycete fungi in terms of their pyrolysis mass spectrometry (PvMS) profiles. Canonical variate analysis (CVA) of the pyrolysis mass spectra distinguished the Aphanomyces species from a wide scatter of Achlya and Saprolegnia isolates. Further CVA and hierarchal cluster analysis (HCA) separated the Aphanomyces species into two main groups. The first group clustered A. invadans isolates from EUS outbreaks in Thailand, Bangladesh, Indonesia, Philippines, Australia and Japan together. However, HCA also included the crayfish plague fungus Aphanomyces astaci within this group. Non-pathogenic Aphanomyces strains isolated from ulcerative mycosis (UM)-affected fish were shown to be distinct from A. invadans, and instead clustered with saprophytic Aphanomyces strains to form the second group. Recently, an invasive Aphanomyces pathogen has been isolated from UNI-affected fish, but that was not tested here. This is the first report using PyMS in the study of Oomycete systematics. The technique was not sensitive enough to show any intraspecific differences, but it was considered a useful technique for the discrimination of species where taxonomic relationships are uncertain.

Classification of photobacteria associated with spoilage of fish products by numerical taxonomy and pyrolysis mass spectrometry

Forty strains of luminous and non-luminous Photobacterium phosphoreum isolates from cod (Gadus morhua) and seven reference strains of psychrotolerant and mesophilic photobacteria were examined for 156 unit characters in a numerical taxonomic study. The fish strains were isolated from the intestines, from spoiled products and by using a specific detection method. The data were analysed using the similarity coefficient and the unweighted pair-group with arithmetic averages algorithm. In addition twenty-six of the fish isolates and five reference strains were analysed by Curie-point pyrolysis mass spectrometry. The mesophilic and psychrotolerant photobacteria were clearly separated in each of the analyses. Both procedures indicated that the spoilage isolates of P. phosphoreum had originated from the live fish as strains from the fish intestines and from the spoiled products were recovered in the same sub-groups. One sub-group of psychrotolerant P. phosphoreum strains, which was selected in modified atmosphere packed fish stored at low temperature, was also highlighted using each of the methods. The importance of classifying food spoilage bacteria has been shown and a simple key generated for the identification of luminous and non-luminous isolates of Photobacterium phosphoreum.

Curie-point pyrolysis mass spectrometry as a tool in clinical microbiology

Pyrolysis mass spectrometry is a well established analytical tool that has received a considerable boost from the development of low cost, dedicated instruments and sophisticated statistical analyses on personal computers. Further analytical developments, especially in the area of neural networks, are pushing the technology to the forefront of methods for the discrimination and identification of microorganisms and their products. The speed and reproducibility of pyrolysis mass spectrometry and its applicability to a wide range of microorganisms make it an attractive method for epidemiological studies. For inter-strain comparisons, the method is at least as discriminatory as conventional typing systems and usually gives discrimination similar to that of nucleic acid fingerprinting techniques. There has been some success in using neural networks to make identifications across pyrolysis mass spectrometric batches. Further development of methods used to handle data from multiple PyMS analyses can be expected to extend the value of pyrolysis mass spectrometry in clinical microbiology.