title: [Discrimination of common oral streptococcus with metabonomics method].
abstract: OBJECTIVE
  To evaluate the feasibility of identifying oral streptococcus by comparing their metabolic profiling, and to find a convenient and rapid way to discriminate oral microorganisms.
  
  
  METHODS
  The pure cultivation of Streptococcus sanguis ATCC 10556 and Streptococcus sobrinus 6715 (reference strain) from solid culture were respectively inoculated in TPY liquid medium. Then the growth quantity was measured periodically by turbidimetry and the growth curves of the inoculated bacteria were completed. The culture solutions in the stationary phase of the two bacteria were centrifuged, and then tested with the 1H-nuclear magnetic resonance (1H-NMR) spectrometer respectively. The gained free induction decay (FID) data were all inputted into MestReC Soft and finally transformed into metabolic profiling. The metabolic profiles were integrated segmentingly and the results were inputted into SIMCA-P Soft for principal components analysis (PCA).
  
  
  RESULTS
  The PCA results showed the obvious clustering phenomena and the points of two group data differentially centralized in two clusters. Therefore, the NMR-based metabonomics profiles can discriminate the two different kinds of bacteria.
  
  
  CONCLUSIONS
  The metabonomics can be expected to be a kind of promising useful method in quick discrimination of oral streptococcus.
authors.affiliation: State Key Laboratory of Oral Diseases, Sichuan University, Chengdu 610041, China.
authors.forename: Qiang
authors.initials: Q
authors.lastname: Guo
authors.forename: Li-ying
authors.initials: LY
authors.lastname: Xiao
authors.forename: Xue-dong
authors.initials: XD
authors.lastname: Zhou
authors.forename: Ming-yun
authors.initials: MY
authors.lastname: Li
authors.forename: Wei-xi
authors.initials: WX
authors.lastname: Lu
authors.forename: Ping
authors.initials: P
authors.lastname: Xiong
authors.forename: Xiang-ming
authors.initials: XM
authors.lastname: Jia
authors.forename: Wei
authors.initials: W
authors.lastname: Li
mesh_terms: D009682:Magnetic Resonance Spectroscopy; D055432:Metabolomics; D009055:Mouth / Q000382:microbiology; D013291:Streptococcus