A numerical taxonomic study of Streptococcus sanguis, S. mitis and similar organisms using conventional tests and pyrolysis mass spectrometry

Taxonomic study of "tufted mitior" strains of streptococci (Streptococcus sanguinis biotype 11); recognition of a new genospecies

The taxonomic position of tufted strains of streptococci, phenotypically resembling Streptococcus mitis and previously referred to as 'tufted mitior' was investigated. By 16S rRNA sequence analysis, it was clear that the "tufted mitior" strains belonged to the mitis group of species within the genus Streptococcus. It was confirmed that these strains were taxonomically independent at the species level, sharing less than 43%, DNA-DNA similarity with all established species of the mitis group. However biochemical test data obtained, using three commercial identification kits (Rapid ID32 Strep, STREPTOGRAM, and Biolog GP-plate) together with in-house biochemical tests employing 4-MUF-linked fluorogenic substrates did not reveal sufficient differential tests with which to identify the "tufted mitior" strains unequivocally. From these data, we conclude that these "tufted mitior" strains represent a new taxon within the mitis group of the genus Streptococcus, and propose that they should be considered as a genospecies until differential phenotypic characteristics are found for their identification.

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.

Pyrolysis mass spectrometry: data processing in classification studies

A scheme for numerical processing of pyrolysis mass spectrometry (Py-MS) data is detailed, along with methods for combining the results of conventional phenotypic and Py-MS taxonomic surveys. The importance of this combined approach in polyphasic taxonomy is emphasised; it yields data on cell composition and the nutritional and physiological interactions of strains with their environment. Large collections of strains can be surveyed rapidly and economically, yielding presumptive classifications, which may then be confirmed with a few representative strains in more demanding, difficult and expensive approaches. An objective, non-arbitrary method of establishing suitable cut-off points to delineate group structures in dendrograms is also described.