| Human liver is the largest organ in the body, probably second only to the brain in complexity. It takes on many important physiological functions including the main digestive function for the metabolism of most substances.Liver diseases are great challenges for modern medicine with extremely poor prognosis due to failure of effective early diagnosis and stage analysis. In order to address this serious health issue, the human liver proteome project was initiated by HUPO in 2003.The research of liver proteome is a systematic and complicated project. Firstly, it was absolutely a challenge to separate and identify all liver proteins because of the very complex protein compositions. Secondly, the goal of liver proteome research is not just to identify all expressed proteins in human livers, but also to study the function of them. Recent advancement in proteomics allow us to study global patterns of protein content and activity and how these change during development or in response to disease, it has boosted our understanding of systems-level and mechanism of disease. In addition, proteomics benefits the identification of new drug targets and development of new diagnostic markers in clinical research. Therefore, the development of new technologies will play a key role in proteome research.Tremendous progress has been made in proteomics during the past few years. With the notable technology developments, one of the aims of our research is to optimize separation and identification techniques and develop an integrated analysis platform which can separate, detect, and identify as many liver proteins as possible. Then, the studies of new sample preparation technologies should be strengthened, and the targets of these studies should be concentrated on the enrichment low-abundance proteins and elucidation of the post-translational modification protein profiles. At last, we wanted to establish a quantitative strategy to analyze the differentially expressed protein profiles of human hepatocellular carcinoma (HCC), which might be helpful to identify new biomarkers of HCC and improve early detection of HCC for the patientsThis dissertation consists of 4 parts and contents are summarized as follows:In the first chapter, the status quo of proteomics and the technology developments in proteomics such as 2-DE, MUDPIT, enrichment of membrane proteins and glycoproteins, and quantitative methodologies, were summarized.The goal of the study in chapter two was to visualize and detect as many proteins as possible in normal human livers using two-dimensional gel electrophoresis and make a reference map of human normal liver proteins for the comprehensive analysis of human liver proteome and the other related research. To tackle the poor resolution in the alkaline pH range of 2-DE gels, we have optimized isoelectric focusing protocol including sample application using cup-loading at the anode and modification of rehydration buffer. With the application of optimized protocol we get reproducible better resolution both in analytical and preparative 2-DE gels. Narrow pH range ultra-zoom 2-DE gels were developed and optimized to improve the resolution and enhance the detection of low abundance proteins. High resolution patterns of human liver in pH gradients 4.5-5.5, 5-6, 5.5-6.7, 6-9 were presented. The ultra-zoom gels pH4.5-9 revealed a total of 5481 protein spots.429 unique proteins were successfully identified, and some of which were labeled on the 2-DE maps and annotated by GO analysis. It is hoped that the visualized reference map of human liver proteins presented in this work will be valuable for comparative proteomics of liver disease.Based on the expression profile of human liver proteome, the research of subcellular organelles and post-translational modification was the further study of human liver proteomics. In chapter three, we first developed a purification strategy to effectively enrich membrane glycoproteins, which involves biotinylation of cell surface membrane glycoproteins and affinity enrichment of the membrane glycoproteins.To address the practicability of the method, the whole strategy was first employed to isolate and identify the glycoproteins from a standard protein mixture. The result showed that the glycoproteins were unambiguously enriched and identified. Three technique lines were compared to investigate the efficiency and specificity of enrichment. It proved that capturing glycosylated peptides can effectively reduce sample complexity and fit for complexity. Then, we used the method to analyze hepatocarcinoma cells' membrane glycoprotein for the potential biomarker discover for liver cancer. From protein level, 171 integral membrane proteins were identified and 54% had more than one TMD, of which 44 were integral membrane glycoproteins. Frome peptide level, 70 unique glycopeptides with 73 glycosylation sites were identified, and it resulted in the identification of 48 membrane glycoproteins. Therefore, we have build up a HepG2 membrane glycoprotein database in the first time, and this data should have a great value for analysis of HCC metastasis.The work in chapter four is focus on the differentiated expressed protein profiles of hepatocellular carcinoma cell lines. To improve early diagnosis of HCC as well as better understanding the mechanisms underlying tumorigenesis, A quantitative proteomic analysis approach, stable isotope labeling with amino acids in cell culture (SILAC) combined with LTQ-FT-MS/MS identification and MSQuant quantitative software, was used to explore differentially expressed protein profiles between normal (HL-7702) and cancer (HepG2 and SK-HEP-1) cells. Some HCC related proteins were found out, and it suggested that TGM2 may serve as a novel candidate involved in HCC. These novel findings may add important clues to identify new biomarkers of HCC and improve early detection of HCC.
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