Proteomic study of plaque fluid in high caries and caries free children

The occurrence and development of caries is a complex process affected by multiple factor.

Our study obtained the largest known dataset of the bacterial secretion protein in children with high caries, and screened the data set of high caries state. 603 peptides were statistically rich in 101 pathways, including glycolysis pyruvate acid metabolism, tricarboxylic acid cycle, pentyl phosphate pathway, fructose mannose metabolism, starch and sucrose metabolism, and ABC transporters.

The study enrolled 8 caries free (CF) children, whose decayed-missed-filled surface of teeth is 0 (dmfs = 0), and caries sensitive (CS) children, whose decayed-missed-filled surface of teeth is > 10(dmfs > 10) (3 ∼ 5 years old) for the smooth tooth plaque and the plaque in the high caries group. The plaque protein was extracted using the unlabeled quantitative technique like liquid chromatography-series mass spectrometry, using DeCyderTM MS Differential Analysis Software (version 1.0, GE Healthcare) that detected and compared the spectra, and quantified the full scanning before series mass spectroscopy. After obtaining all peptides with quantitative information, significantly differential polypeptide molecules were obtained (p< 0.05), and a metabolic pathway analysis was performed.

The present study was envisaged to evaluate the plaque fluid in caries free children and children with high caries, in order to establish a data set of bacterial secretion proteomics. A non-labeled quantitative technique based on two-dimensional liquid chromatography-series mass spectroscopy was employed to detect plaque fluid. Based on the proteomics data, the database search, data processing and pathway analysis illuminated the function of these proteins, and clarified the role of plaque microecology in caries occurrence and development.

We identified 1,804 peptides with quantitative information, including 39 in CF, 30 in CS, and 1,735 similarly expressing peptides. After statistical analysis, 603 statistically different expression peptide data sets were obtained, including 202 high-expressed peptides in Group CF, 33 greater than 1.5 fold peptides, 401 high-expressed in Group CS and 199 greater than 1.5 fold peptide (173 nonredundant proteins).