The Discrimination of Oral Microorganisms with the Metabonomics Technique

Objective:   To establish the spectra of metabolites employing in identification of oral pathogenic bacteria, and to find a convenient rapid way to discriminate oral microorganisms.

Methods:  Solutions of Streptococcus mutans ATCC25175, Streptococcus sanguis ATCC10556 and Lactobacillus acidophilus ATCC 4356 with same density were made and cultured respectively at improved TPY liquid. The growth quantities were measured periodically by turbidimetry. And the growth curves of the inoculated bacteria were measured. The culture solutions in stationary phases of the three bacteria were used to test with the ¹H-Nuclear magnetic resonance (¹H-NMR) spectroscopy respectively. The data of ¹H-NMR spectroscopy results were analyzed by principal components analysis (PCA).

Results:   The PCA showed the obvious clustering phenomena and the points of three group data stayed differentially together by three clusters. Therefore, the NMR-based metabonomics profiles can discriminate the three different kinds of bacteria. The data of same bacteria has clustering phenomenon. From the resultant loading plots, there are obvious chemical shifts which are responsible for the separation of the three groups of samples. The most important chemical shifts, such as 3.1998ppm, 3.6797ppm and 3.32ppm, are the difference of the three kinds of bacteria.

¡²Figure¡³

Fig1. ¹H -NMR spectra of the three bacteria which grew 30 h in culture medium

( a: S. mutans; b: S.sanguis; c: L.acidophilus)

Fig2. Score scattering plot (T1 vs. T2) for following PCA. The black represent S. mutans£¬the red represent S.sanguis£¬the blue represent L.acidophilus

Conclusion:     This is a pilot study of introducing NMR-based metabonomics method to discriminate oral microorganism. The study clearly shows that the metabonomics approach represents a promising new technology for the development of a rapid throughout in quick discrimination of oral pathogenic bacteria. In the future, the ways of NMR-based metabonomics can be used to classify and identify oral microorganism.