Abstract
The 21-day experimental gingivitis model, an established noninvasive model of inflammation in response to increasing bacterial accumulation in humans, is designed to enable the study of both the induction and resolution of inflammation. Here, we have analyzed gingival crevicular fluid, an oral fluid comprising a serum transudate and tissue exudates, by LC-MS/MS using Fourier transform ion cyclotron resonance mass spectrometry and iTRAQ isobaric mass tags, to establish meta-proteomic profiles of inflammation-induced changes in proteins in healthy young volunteers. Across the course of experimentally induced gingivitis, we identified 16 bacterial and 186 human proteins. Although abundances of the bacterial proteins identified did not vary temporally, Fusobacterium outer membrane proteins were detected. Fusobacterium species have previously been associated with periodontal health or disease. The human proteins identified spanned a wide range of compartments (both extracellular and intracellular) and functions, including serum proteins, proteins displaying antibacterial properties, and proteins with functions associated with cellular transcription, DNA binding, the cytoskeleton, cell adhesion, and cilia. PolySNAP3 clustering software was used in a multilayered analytical approach. Clusters of proteins that associated with changes to the clinical parameters included neuronal and synapse associated proteins.
Original language | English |
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Pages (from-to) | 4732-4744 |
Number of pages | 13 |
Journal | Journal of Proteome Research |
Volume | 9 |
Issue number | 9 |
DOIs | |
Publication status | Published - 27 Jul 2010 |
Bibliographical note
All articles with an ACS AuthorChoice logo published prior to April 1, 2013, are subject to the ACS AuthorChoice/ACS Editors’ Choice Terms and Conditions. © 2010 American Chemical SocietyKeywords
- acute disease
- adult
- liquid chromatography
- cluster analysis
- female
- fusobacterium
- gingival crevicular fluid
- gingivitis
- humans
- inflammation
- isotope labeling
- male
- metagenome
- biological models
- proteome
- proteomics
- Fourier transform infrared spectroscopy
- nonparametric statistics
- tandem mass spectrometry