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SAL_12818 details
Primary information
SALIDSAL_12818
Biomarker nameGuanine nucleotide-binding protein G(k) subunit alpha (G(i) alpha-3)
Biomarker TypeNA
Sampling MethodNA
Collection MethodUnstimulated
Analysis MethodCombined dynamic range compression using hexapeptide beads, strong cation exchange HPLC peptide fractionation, and immobilized metal affinity chromatography prior to mass spectrometry
Collection SiteWhole Saliva
Disease CategoryHealthy
Disease/ConditionHealthy
Disease SubtypeNA
Fold Change/ ConcentrationNA
Up/DownregulatedNA
ExosomalNA
OrganismHomo sapiens
PMID16103422
Year of Publication2005
Biomarker IDP08754
Biomarker CategoryProtein
SequenceMGCTLSAEDKAAVERSKMIDRNLREDGEKAAKEVKLLLLGAGESGKSTIVKQMKIIHEDGYSEDECKQYKVVVYSNTIQSIIAIIRAMGRLKIDFGEAARADDARQLFVLAGSAEEGVMTPELAGVIKRLWRDGGVQACFSRSREYQLNDSASYYLNDLDRISQSNYIPTQQDVLRTRVKTTGIVETHFTFKDLYFKMFDVGGQRSERKKWIHCFEGVTAIIFCVALSDYDLVLAEDEEMNRMHESMKLFDSICNNKWFTETSIILFLNKKDLFEEKIKRSPLTICYPEYTGSNTYEEAAAYIQCQFEDLNRRKDTKEIYTHFTCATDTKNVQFVFDAVTDVIIKNNLKECGLY
Title of studyA catalogue of human saliva proteins identified by free flow electrophoresis-based peptide separation and tandem mass spectrometry
Abstract of studyHuman saliva has great potential for clinical disease diagnostics. Constructing a comprehensive catalogue of saliva proteins using proteomic approaches is a necessary first step to identifying potential protein biomarkers of disease. However, because of the challenge presented in cataloguing saliva proteins with widely varying abundance, new proteomic approaches are needed. To this end, we used a newly developed approach coupling peptide separation using free flow electrophoresis with linear ion trap tandem mass spectrometry to identify proteins in whole human saliva. We identified 437 proteins with high confidence (false positive rate below 1%), producing the largest catalogue of proteins from a single saliva sample to date and providing new information on the composition and potential diagnostic utility of this fluid. The statistically validated, transparently presented, and annotated dataset provides a model for presenting large scale proteomic data of this type, which should facilitate better dissemination and easier comparisons of proteomic datasets from future studies in saliva.