| The liver of mammalian has an impressive ability to regenerate. Rat liver can restore to the mass and functionality of organ within 7 days after partial hepatectomy, called liver regeneration. The abnormal of the liver function would result in a variety of liver diseases. The prognosis of hepatopaths which were treated with hepatectomy or living donor liver transplantation, were closely related with the regenerative capacity of liver. Therefore, uncovering molecular mechanism of liver regeneration was one of the research hotspots in biology and regenerative medicine fields at present.Many types of liver cells participate in liver regeneration. One of the most important cells is hepatocyte. As a terminally differentiated cell, most of the hepatocytes were in resting state at physiological condition. After partial hepatectomy, the residual hepatocytes of human and rodent would immediately start mitosis and cell proliferation. Liver can restore to the original mass and function in a relatively short period. Although liver regeneration has been an interesting research topic over a century, the regulation mechanisms of the initiate, proliferation, differentiaion and termination of hepatocytes during LR remain to be elucidated.In this thesis, we gain gene expression data of regenerating hapatocyte. Then, we use biological network analysis methods to cluster the gene expression profile with time series feature, analyze gene co-expression network and protein-protein interaction network of rat hepatocyte during liver regeneration. This study provides theoretical basis for mining regulation mechanisms of liver regeneration.The contributions of this thesis are as follows:(1) In this study, the classic 2/3 partial hepatectomy model in rats is used. Hepatocyte is isolated at different time points during liver regeneration. Then gene expression changes were measured at 0h, 2h, 6h, 12 h, 24 h, 30 h, 36 h, 72 h, 120 h,168h after partial hepatectomy and sham operation with the Rat Genome 230 2.0 microarray. The genome-wide gene expression profiles of hepatocytes during liver regeneration were gained(NCBI GEO: GSE55434).(2) Complicated regulation relations underlie the time series genes expression profiles of hepatocyte during liver regeneration, such as delay regulation, reverse regulation, instantaneous regulation between transcription factors and their target genes. So their gene expression profiles there may be a delay correlation, reversion correlation and instantaneous correlation. Based on multi-correlation underlied time-series gene expression profiles of hepatocyte, this thesis propose a similarity measure model for depicting various correlation of gene expression profile, and applied it to affinity propagation algorithm for hepatocyte gene expression profile clustering. The results showed that the genes involved in related biological process and signaling pathways can mostly cluster together, which is more in line with the law of biology. It indicates that the similarity measure model can produce better clustering effect.(3) This thesis attempts to identify subset of genes closely related to liver regeneration and mine critical pathway and key genes regulating liver regeneration from system level. The gene co-expression networks were constructed normal hepatocyte and regenerative hepatocyte, respectively. Then module detection was performed in PH network and SO network using use the clustering method. The gene modules between PH network and SO network were compared from network topology and bioinformatics. We identified 12 gene modules associated with liver regeneration. By biological pathway Enrichment analysis, we found that upregulated MCM5 may promote hepatocyte proliferation. BCL3 plays an important role through activation/inhibition of NF-k B signaling pathway during liver regeneration. MAPK9 play an important role in DNA replication at the proliferation stage by inhibiting p38 MAPK activity. We also find that IL6R->STAT signaling pathway, Adipocytokine signaling pathway, Notch pathway and FGFR1 signaling pathway also play an important role during liver regeneration.(4) Uncovering the protein-protein interactions relations and constructing protein-protein interaction networks is another hotspot in omics data analysis. We select significantly upregulated and downregulated genes during liver regeneration and use Pathway Studio software to construct protein-protein interaction network of hepatocyte. Then, a comprehensive statistical property including degree, betweenness and shortest path length is used to identify hub node as key protein candidate related to liver regeneration. Some key proteins closely related with liver regeneration, such as TNF, TGFβ1, EGF, IL-1β, IL-10, MYC, JUN, FOS, etc., are accurately identified, which demonstrate the effectiveness of critical node identification method. In the meantime, it also provides several other possible essential proteins associated with liver regeneration and its sub-networks, such as APP, CD8 A, CXCL12, CDH1, CD40, etc. This study provides novel insight into exploring the molecular mechanism of liver regeneration.Interactions between biomolecules constitute a complex biological network. In the biological network, abnormal expression of a single gene or protein cannot often affect the normal operation of cell or organ. Many physiological activities are often regulated by the biological pathways or gene modules in the synergistic form. Biological network methods are of great advantage to analyze omics data from the system level. This thesis uses biological network methods to research hepatocyte network structure during liver regeneration and identify gene modules, key genes and signaling pathways regulating liver regeneration. Network systems biology methods can find more abundant informations regulating liver regeneration than general bioinformatics methods. It provides new research ideas and direction in understanding molecular mechanism of liver regeneration. |
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