Gaiping Wang

Transcriptome analysis of hepatocytes after partial hepatectomy in rats

After partial hepatectomy (PH), the recovery of liver mass is mainly mediated by proliferation and enlargement of hepatocytes. Therefore, measuring the transcriptional profiling of hepatocytes after PH will be helpful in exploring the mechanism of liver regeneration (LR). Firstly, hepatocytes were isolated from rat regenerating liver at different time points following PH, and then global gene expression analysis of hepatocytes was performed using Rat Genome 230 2.0 Array. The results demonstrated that 1,417 genes in the array (including 767 known genes) were identified to be LR-related. Clustering analysis demonstrated that 767 known genes fell into six classes with distinct expression kinetics. When gene expression patterns were combined with gene functions, genes involved in acute-phase response and defense response were rapidly elevated in early phases; those in cell proliferation and DNA replication were significantly up-expressed in middle phase; a growing number of cell adhesion-involved genes were up-regulated as regeneration progressed; those in amino acid and lipid metabolism showed persistent down-regulation during LR. Based on the above analyses, it was suggested that hepatocyte defense mechanism was quickly triggered after PH; cell proliferation became active in middle phase; cell adhesion was strengthened in late phase; amino acid and lipid metabolism were attenuated during LR. Additionally, comparative analysis between transcriptional profiling of hepatocytes and regenerating liver indicated a major contribution of hepatocytes to LR.

The role of Kupffer cells in rat liver regeneration revealed by cell-specific microarray analysis.

Liver regeneration after partial hepatectomy is a process with various types of cells involved. The role of Kupffer cells (KCs) in liver regeneration is still controversial. In this study we isolated KCs from regenerating liver and conducted cell‐specific microarray analysis. The results demonstrated that the controversial role of KCs in liver regeneration could be explained with the expression patterns of TGF‐α, IL‐6, TNF, and possibly IL‐18 during liver regeneration. IL‐18 may play an important role in negative regulation of liver regeneration. The functional profiles of gene expression in KCs also indicated that KC signaling might play a negative role in cell proliferation: signaling genes were down regulated before cell division. Immune response genes in KCs were also down regulated during liver regeneration, demonstrating similar expression profiles to that of hepatocytes. The expression patterns of key genes in these functional categories were consistent with the temporal functional profiles. J. Cell. Biochem. 113: 229–237, 2012.

Analysis of the role of the integrin signaling pathway in hepatocytes during rat liver regeneration.

To explore the role of the integrin signaling pathway in hepatocytes during rat liver regeneration, the integrin signaling pathway-related gene expression profile in hepatocytes of regenerative liver was detected using Rat Genome 230 2.0 array. The chip data showed that 265 genes of the integrin signaling pathway were included by Rat Genome 230 2.0 array and 132 genes showed significant expression changes in hepatocytes of regenerative liver. The numbers of up-, down- and up/down-regulated genes were 110, 15 and 7 respectively. In addition, bioinformatics and systems biology methods were used to analyze the role of the integrin signaling pathway in hepatocytes. The analysis of gene synergy value indicated that paths 1, 8, 12, and 15 promoted hepatocyte proliferation at the priming phase of liver regeneration; paths 1, 3, 8, and 12–15 enhanced hepatocyte proliferation at the progressing phase; paths 11 and 14 promoted hepatocyte proliferation, while paths 12 and 13 reduced hepatocyte proliferation at the terminal phase. Additionally, the other 8 paths (2, 4, 5–7, 9–10, and 16) were not found to be related to liver regeneration. In conclusion, 132 genes and 8 cascades of the integrin signaling pathway participated in regulating hepatocyte proliferation during rat liver regeneration.

The number of the genes in a functional category matters during rat liver regeneration after partial hepatectomy

Rat liver regeneration after partial hepatectomy (PH) is a good model to study the regulation of cell proliferation. We isolated hepatocytes from regenerating liver at different time points after PH and used microarray Rat Genome 230 2.0 chip to analyze the functional profiles of all up‐ or down‐regulated genes manually and with automatic gene ontological tools. We found that the transcript expressions of PH and sham operation group were apparently different. For PH group, in the priming phase (2–12 h), signaling, transcription, response to stimulus genes predominated in up‐regulated genes; in the proliferation phase (24–72 h), cell proliferation genes predominated; in the termination phase (120–168 h), differentiation and translation genes predominated; while metabolism genes predominated in the down‐regulated genes at all time points (2–168 h). These functional profiles are consistent with the cellular and molecular phenomenon observed during liver regeneration, and can be closely connected with the biological process. Moreover, the results indicated that not only the quantity of specific genes but also the number of the genes in the specific functional category was regulated during liver regeneration, which means the number of similar genes in a specific functional category matters as well as the regulation of the genes. The changes of the number of the regulated cell proliferation genes and metabolism genes during liver regeneration were similar to the expression patterns of some cell division genes and metabolism genes. J. Cell. Biochem. 112: 3194–3205, 2011.

Analysis of gene expression profiles of liver stellate cells during liver regeneration in rats.

This study performed a large-scale, high-throughput analysis of transcriptional profiling of liver stellate cells (LSCs) at the cellular level to investigate changes in the biological activity of LSCs during rat liver regeneration (LR) and the relation of these changes to LR. First, a rat liver regeneration model was established by partial hepatectomy (PH). Stellate cells were isolated in high purity and yield from the regenerating rat liver by Percoll density gradient centrifugation and immunomagnetic bead sorting. The changes in gene expression of LSCs after PH were examined using a rat genome 230 2.0 array composed of 24622 genes. The results indicated that 10241 of the 24622 genes investigated on the array were differentially expressed in LSCs. Of the 10241 genes, 1563 known genes were related to LR, which were grouped into three major gene expression clusters according to three-fold cut-off threshold: the upregulated gene cluster, the down-regulated gene cluster, and the cluster composed of genes showing complex changes in expression. Additionally, the genes were grouped into those involved in transcription regulation, signal transduction, transport, cellular metabolism, inflammation and immunity by functional analysis. When gene expression profiles were combined with the results of gene functional analysis, most of the genes involved in cytokine secretion and retinol metabolism in LSCs were significantly enriched in the cluster characterized by decreased expression, whereas genes involved in lipid metabolism were mostly enriched in the cluster showing increased expression. Based on further analysis of genes expressed in a phase-dependent manner during LR, it was suggested that lipid metabolism in LSCs was enhanced in the whole regeneration process, and that immune response and cytokine secretion were impaired during all three regenerative phases.

Gene expression profiles reveal significant differences between rat liver cancer and liver regeneration.

Rapid cell proliferation and growth occur in both liver cancer (LC) and liver regeneration (LR). Does it imply that LC and LR share some similar molecular mechanisms? To elucidate the intrinsic similarities and differences between the above two processes at transcriptional level, rat models of diethylnitrosamine-induced LC and 2/3 partial hepatectomy-induced LR were separately established. Then Rat Genome 230 2.0 Array was used to detect gene expression profiles of liver tissues obtained from the above two models, and bioinformatics methods, such as hierarchical clustering, k-means clustering and Expression Analysis Systematic Explorer (EASE), were applied to uncover the correlation between gene expression changes and physiological activities in LC and LR. Subsequently expression changes of six selected genes were confirmed by real-time quantitative RT-PCR. As a result, the expressions of 909 genes were found significantly changed during LC occurrence and 948 genes in LR. The expression profiles of the above two events were extremely different, and their expression patterns were classified into 6 clusters. Based on the correlation between expression patterns and functional profiles, we found that drug/toxin metabolism and oxidation reduction were induced in LC, but decreased in LR at the transcription level, while lipid, steroid and chemical homeostasis were remarkably repressed in LC but induced in LR; inflammation/immune response and apoptosis were not obvious or weaker in LC than in LR, whereas the activities of angiogenesis and cell adhesion/migration in LC were much stronger.

Characterization of transcriptional profiling of Kupffer cells during liver regeneration in rats.

KCs (Kupffer cells), as an important hepatic immunoregulatory cells, play a key role in LR (liver regeneration). Uncovering the transcriptional profiling of KCs after PH (partial hepatectomy) would likely clarify its implication in LR. Here, we isolated KCs by methods of Percoll density gradient centrifugation and immunomagnetic beads. Transcriptional profiles of KCs were monitored up to 168 h post‐PH using microarray. By comparing the expression profile of KCs at 2–168 h post‐PH with that of the control and applying the statistical and bioinformatics criteria, we found 1407 known and 927 unknown genes related to LR. K‐means clustering analysis grouped these 1407 genes into robust 14 time‐course clusters representing distinct patterns of regulation. Based on gene‐set enrichment analysis, genes encoding products involved in cytokine signalling, inflammatory response and cell chaemotaxis were highly enriched in the cluster characterized by gradual up‐regulation and then return; genes in defence response and immune response were enriched in clusters ‘the general down‐regulation during LR’; genes in fatty acid synthesis and sterol metabolism were preferentially distributed in the cluster ‘gradual increase’; whereas genes in the categories ‘lipid catabolism’ and ‘glycolysis’ were enriched in cluster ‘decrease at two intervals’. According to the above analysis, KCs were seemingly sensitive to operative stimulus; immune defence and detoxification function of KCs obviously dropped post‐operatively; fatty acid synthesis were enhanced, whereas lipid catabolism and glycolysis were reduced after PH. This study provides a detailed in vivo gene expression profile of KCs, providing a framework to better understand the molecular mechanisms underlying the regeneration process at cellular level.

Analysis of time-course gene expression profiles of sinusoidal endothelial cells during liver regeneration in rats

Liver regeneration (LR) after partial hepatectomy (PH) requires the coordinate contribution of different cell types. Liver sinusoidal endothelial cells (LSECs), representing the largest population of nonparenchymal cells, are proven to be crucial in LR. However, the details about their implications in regeneration are not still clear. In this study, percoll density centrifugation and immunomagentic bead methods were used to isolate LSECs with high purity and yield; global transcriptional profiles of LSECs during the regeneration were investigated by microarray. 1,629 genes were identified to be LR-related. Among them, there were 833 known genes whose expression patterns were clustered into eight classes. Gene function enrichment analysis showed that genes involved in the major LSEC functions, i.e., coagulation, phagocytosis, and transport, were highly enriched in cluster characterized by rapid induction and gradual return, suggesting the quick reestablishment of LSEC function after PH. Genes in immunity/inflammation and defense response were enriched in clusters exhibiting transient downregulation and quick recovery, possibly being associated with suppression of immunity/inflammation pathway in LSECs at early phase. Genes in glycogen synthesis and glycolysis were enriched in the clusters marked by “significant increase and gradual return” and “slight increase and then downregulation”, implying an enhanced carbohydrate metabolism at early phase; detoxification-related genes were markedly distributed in the cluster with feature of rapid increase and then reduction, which was helpful in eliminating waste substance. Taken together, the measurement of gene expression profiling of LSECs and expression pattern analysis of functionally categorized genes gave insight into the mechanism of action of this cell on LR.

Gene expression profiles predict the possible regulatory role of OPN-mediated signaling pathways in rat liver regeneration

Osteopontin (OPN; gene Spp1), as a pro-inflammatory cytokine, has a range of activities relevant to the occurrence and progression of hepatitis, liver fibrosis or liver tumors. However, little is known about the role of OPN in liver regeneration (LR). To reveal the expression profiles of OPN and its receptors and the possible regulatory role of OPN in rat LR, Rat Genome 230 2.0 was used to detect expression profiles of OPN-mediated signaling pathway-associated genes after partial hepatectomy (PH), and the results showed that 81 genes were significantly changed at mRNA level, and among which, 65 genes were up-regulated. Then, k-means clustering was employed to classify above 81 genes into 5 clusters based on gene expression similarity, and EASE analysis further indicated that the above genes were mainly associated with stress response, inflammatory response, cell activation, proliferation, adhesion and migration. Thereafter, IPA software and Western blot were used to analyze potential effects of every branch of OPN signaling pathways during LR, and the results suggested that the genes expression changes of OPN signaling pathways may account for enhanced cell proliferation, survival, adhesion and migration, augmented inflammation response and attenuated apoptosis during LR.

Analysis of the ways and methods of signaling pathways in regulating cell cycle of NIH3T3 at transcriptional level

BackgroundTo analyze the ways and methods of signaling pathways in regulating cell cycle progression of NIH3T3 at transcriptional level, we modeled cell cycle of NIH3T3 and found that G1 phase of NIH3T3 cell cycle was at 5–15 h after synchronization, S phase at 15–21 h, G2 phase at 21–22 h, M phase at 22–25 h.ResultsMouse Genome 430 2.0 microarray was used to detect the gene expression profiles of the model, and results showed remarkable changes in the expressions of 64 cell cycle genes and 960 genes associated with other physiological activity during the cell cycle of NIH3T3. For the next step, IPA software was used to analyze the physiological activities, cell cycle genes-associated signal transduction activities and their regulatory roles of these genes in cell cycle progression, and our results indicated that the reported genes were involved in 17 signaling pathways in the regulation of cell cycle progression. Newfound genes such as PKC, RAS, PP2A, NGR and PI3K etc. belong to the functional category of molecular mechanism of cancer, cyclins and cell cycle regulation HER-2 signaling in breast cancer signaling pathways. These newfound genes could promote DNA damage repairment and DNA replication progress, regulate the metabolism of protein, and maintain the cell cycle progression of NIH3T3 modulating the reported genes CCND1 and C-FOS.ConclusionAll of the aforementioned signaling pathways interacted with the cell cycle network, indicating that NIH3T3 cell cycle was regulated by a number of signaling pathways.