Large-Scale Proteome of Gingival Crevicular Fluid by Mass Spectrometry

Gingival crevicular fluid (GCF) has been of major interest because of its unique relationship to gingival/periodontal health status. As gingival/periodontal inflammation increases, this fluid undergoes a transition from transudate to exudate and this may be concomitant with the appearance of additional proteins not found in the absence of inflammation. Knowledge about the protein components of GCF has been limited to those which could be identified by classical biochemical approaches. Objectives: To identify and document the large-scale proteome of GCF by highly sensitive mass spectrometric technologies. Methods: GCF samples were collected from 2 gingivally healthy subjects using the established “perio-strip” procedure at a total of 12 sites. The 12 strips, each containing 1-3 µl of GCF, were pooled and processed for MS analysis. The proteins were eluted from the strips with 30 µl of 50 mM NH₄HCO₃, pH 8.0, followed by centrifugation to collect the eluate. To minimize difficulties with the identification of low level proteins the highly abundant serum albumin was removed by “SwellGel Blue” treatment followed by sample trypsinization. Protein identification was carried out using nano-flow LC-ESI-MS/MS analysis. Results: A total of 86 proteins were identified none of which were related to salivary secretions. The GCF proteins identified reflect a wide range of components with a variety of different biological functions and origin. Apart from many serum proteins the data revealed the presence of macromolecules belonging to the immune system, a variety of enzymes including esterases, extracellular matrix proteins as well as enzyme inhibitors. Conclusions: The results provide evidence that this biologically important body fluid available only in small amounts can be characterized in great detail by MS approaches. Detailed information on the composition of GCF under a variety of clinical conditions may be of major significance for oral and systemic diagnostics. Supported by NIH/NIDCR Grants DE05672; DE07652; DE17788.