Literature DB >> 18028703

Raman spectroscopic measurement of relative concentrations in mixtures of oral bacteria.

Qingyuan Zhu1, Robert G Quivey, Andrew J Berger.   

Abstract

Near-infrared Raman spectroscopy has been used for species identification of pure microbial specimens for more than a decade. More recently, this optical method has been extended to the analysis of specimens containing multiple species. In this report, we demonstrate rapid, reagent-free quantitative analysis of a simplified model of oral plaque containing three oral bacteria species, S. mutans, S. sanguis, and S. gordonii, using near-infrared Raman spectroscopy. Raman spectra were acquired from bacterial mixtures in 200 seconds. A prediction model was calibrated by the partial least squares method and validated by additional samples. On a scale from 0 to 1, relative fractions of each species could be predicted with a root mean square error of 0.07. These results suggest that near-infrared Raman spectroscopy is potentially useful in quantification of microbial mixtures in general and oral plaques in particular.

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Year:  2007        PMID: 18028703      PMCID: PMC2475336          DOI: 10.1366/000370207782597021

Source DB:  PubMed          Journal:  Appl Spectrosc        ISSN: 0003-7028            Impact factor:   2.388


  29 in total

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5.  Differentiation of Streptococcus mutans and Streptococcus sobrinus via genotypic and phenotypic profiles from three different populations.

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Authors:  D Hutsebaut; K Maquelin; P De Vos; P Vandenabeele; L Moens; G J Puppels
Journal:  Anal Chem       Date:  2004-11-01       Impact factor: 6.986

10.  The effects of mutual interaction and host diet on the growth rates of the bacteria Actinomyces viscosus and Streptococcus mutans during colonization of tooth surfaces in di-associated gnotobiotic rats.

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  1 in total

1.  Identification of different bacterial species in biofilms using confocal Raman microscopy.

Authors:  Brooke D Beier; Robert G Quivey; Andrew J Berger
Journal:  J Biomed Opt       Date:  2010 Nov-Dec       Impact factor: 3.170

  1 in total

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