Lectin Based Salivary Glycoprotein Separation, Analysis And Its Application

Human saliva has the merits of low cost,non-invasive,easy to collect and rich in contents,which has been applied to the molecule diagnosis of oral diseases and systematic diseases.According to the literature,protein glycosylation is closely related to the occurrence and development of cancer.Glycoproteins could be promising biomarkers for cancer detection.Our previous research demonstrated that salivary proteins could be used as the biomarkers for the detection of lung cancer.In this thesis,we expect to further separate and analyze the glycoproteins in human saliva and explore their potentials in the diagnosis of cancer.It is very challenging to separate and analyze the glycoproteins in human saliva due to their low abundance.Lectins can specifically extract glycoproteins.However,there are few reports on using lectins to enrich and analyze salivary glycoproteins.In this thesis,lectins WGA and AAL were utilized to extract salivary glycoproteins.The effect of removing highly abundant proteins on salivary glycoprotein analysis was investigated.In-solution digestion and in-gel digestion were compared for the identification of salivary glycoproteins.The method of amylase depletion was modified,which shortened the handling time and improved the yield of salivary proteins by 34%.With in-gel digestion,115 and 67 high-confidence glycoproteins could be identified from the whole saliva through the enrichment of WGA and AAL,respectively,significantly higher than the 32 and 37 identified by in-solution digestion and 38 and 47 identified after amylase-depletion.Therefore,glycoproteins extracted by WGA combined with in-gel digestion was selected as the optimized method for the subsequent experiments.Salivary glycoproteins of lung cancer patients and normal persons were enriched by WGA,which were further compared through label-free quantification proteomics.According to the data analysis,139 proteins were identified,among which 102 proteins have glycosylation sites,including 14 glycoproteins that showed significant difference between cancer group and control group(p<0.05).All data collectively demonstrated that the developed methodology can be used for efficient separation and analysis of salivary glycoproteins,which could serve as biomarkers for cancer diagnosis.