Multi-omics analyses reveal metabolic alterations regulated by hepatitis B virus core protein in hepatocellular carcinoma cells.

Chronic hepatitis B virus (HBV) infection is partly responsible for hepatitis, fatty liver disease and hepatocellular carcinoma (HCC). HBV core protein (HBc), encoded by the HBV genome, may play a significant role in HBV life cycle. However, the function of HBc in the occurrence and development of liver disease is still unclear. To investigate the underlying mechanisms, HBc-transfected HCC cells were characterized by multi-omics analyses. Combining proteomics and metabolomics analyses, our results showed that HBc promoted the expression of metabolic enzymes and the secretion of metabolites in HCC cells. In addition, glycolysis and amino acid metabolism were significantly up-regulated by HBc. Moreover, Max-like protein X (MLX) might be recruited and enriched by HBc in the nucleus to regulate glycolysis pathways. This study provides further insights into the function of HBc in the molecular pathogenesis of HBV-induced diseases and indicates that metabolic reprogramming appears to be a hallmark of HBc transfection.

Hepatitis B virus X induces inflammation and cancer in mice liver through dysregulation of cytoskeletal remodeling and lipid metabolism.

Hepatitis B virus X protein (HBx) participates in the occurrence and development processes of hepatocellular carcinoma (HCC) as a multifunctional regulation factor. However, the underlying molecular mechanism remains obscure. Here, we describe the use of p21HBx/+ mouse and SILAM (Stable Isotope Labeling in Mammals) strategy to define the pathological mechanisms for the occurrence and development of HBx induced liver cancer. We systematically compared a series of proteome samples from regular mice, 12- and 24-month old p21HBx/+ mice representing the inflammation and HCC stages of liver disease respectively and their nontransgenic wild-type (WT) littermates. Totally we identified 22 and 97 differentially expressed proteins out of a total of 2473 quantified proteins. Bioinformatics analysis suggested that the lipid metabolism and CDC42-induced cytoskeleton remodeling pathways were strongly activated by the HBx transgene. Interestingly, the protein-protein interaction MS study revealed that HBx directly interacted with multiple proteins in these two pathways. The same effect of up-regulation of cytoskeleton and lipid metabolism related proteins, including CDC42, CFL1, PPARγ and ADFP, was also observed in the Huh-7 cells transfected with HBx. More importantly, CFL1 and ADFP were specifically accumulated in HBV-associated HCC (HBV-HCC) patient samples, and their expression levels were positively correlated with the severity of HBV-related liver disease. These results provide evidence that HBx induces the dysregulation of cytoskeleton remodeling and lipid metabolism and leads to the occurrence and development of liver cancer. The CFL1 and ADFP might be served as potential biomarkers for prognosis and diagnosis of HBV-HCC.

Quantitative proteomics reveals FLNC as a potential progression marker for the development of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) caused by hepatitis B virus (HBV) infection is one of the most life-threatening human cancers in China. However, the pathogenesis of HCC development is still unclear. Here, we systemically analyzed liver tissues from different stages of HCC patients through 8-plex Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) approach. A total of 4,620 proteins were identified and 3,781 proteins were quantified. When T1, T2 and T3 tumor tissues were compared with T1 non-tumor cells, 330, 365 and 387 differentially expressed proteins were identified respectively. IPA (Ingenuity Pathway Analysis) analysis revealed that these differentially expressed proteins were involved in endothelial cancer, cell spreading, cell adhesion and cell movement of tumor cell lines pathway and so on. Further study showed that the filamin C (FLNC) protein was significantly overexpressed with the development of HCC, which might play an important role in HCC invasion and metastasis. These results were also confirmed with western blot (WB). The mRNA levels were significantly increased in 50 pairs of tumor and adjacent non-tumor tissues from TCGA database. The higher expression of FLNC in HCC might be a common phenomenon, thereby shedding new light on molecular mechanism and biomarker for the diagnosis purpose of HCC development.

SILAC-based proteomic analysis reveals that salidroside antagonizes cobalt chloride-induced hypoxic effects by restoring the tricarboxylic acid cycle in cardiomyocytes.

Hypoxic status alters the energy metabolism and induces cell injury in cardiomyocytes, and it further triggers the occurrence and development of cardiovascular diseases. Our previous studies have shown that salidroside (SAL) exhibits anti-hypoxic activity. However, the mechanisms remain obscure. In the present study, we successfully screened 92 different expression proteins in CoCl2-induced hypoxic conditions, 106 different expression proteins in the SAL-mediated anti-hypoxic group were compared with the hypoxic group using quantitative proteomics strategy, respectively. We confirmed that SAL showed a positive protective function involving the acetyl-CoA metabolic, tricarboxylic acid (TCA) cycle using bioinformatics analysis. We also demonstrated that SAL plays a critical role in restoring the TCA cycle and in protecting cardiomyocytes from oxidative injury via up-regulation expressions of PDHE1-B, ACO2, SUCLG1, SUCLG2 and down-regulation of MDH2. SAL also inhibited H9c2 cell apoptosis by inhibiting the activation of pro-apoptotic molecules caspase 3 and caspase 9 as well as activation of the anti-apoptotic molecular Bcl-2. Additionally, SAL also improved mitochondrial membrane potential (ΔΨm), reduced reactive oxygen species (ROS) and intercellular Ca(2+) concentration ([Ca(2+)]i) accumulation and inhibited the excessive consumption of ATP in H9c2 cells.

Quantitative Proteomics Reveals That the Inhibition of Na(+)/K(+)-ATPase Activity Affects S-Phase Progression Leading to a Chromosome Segregation Disorder by Attenuating the Aurora A Function in Hepatocellular Carcinoma Cells.

Many studies have shown the Na(+)/K(+)-ATPase (NKA) might be a potential target for anticancer therapy. Cardiac glycosides (CGs), as a family of naturally compounds, inhibited the NKA activity. The present study investigates the antitumor effect of ouabain and elucidates the pharmacological mechanisms of CG activity in liver cancer HepG2 cell using SILAC coupled to LC-MS/MS method. Bioinformatics analysis of 330 proteins that were changed in cells under treatment with 0.5 µmol/L ouabain showed that the biological processes are associated with an acute inflammatory response, cell cycle, oxidation reduction, chromosome segregation, and DNA metabolism. We confirmed that ouabain induced chromosome segregation disorder and S-cell cycle block by decreasing the expression of AURKA, SMC2, Cyclin D, and p-CDK1 as well as increasing the expression of p53. We found that the overexpression or inhibition of AURKA significantly reduced or enhanced the ouabain-mediated the anticancer effects. Our findings suggest that AURKA is involved in the anticancer mechanisms of ouabain in HepG2 cells.

Special Enrichment Strategies Greatly Increase the Efficiency of Missing Proteins Identification from Regular Proteome Samples.

As part of the Chromosome-Centric Human Proteome Project (C-HPP) mission, laboratories all over the world have tried to map the entire missing proteins (MPs) since 2012. On the basis of the first and second Chinese Chromosome Proteome Database (CCPD 1.0 and 2.0) studies, we developed systematic enrichment strategies to identify MPs that fell into four classes: (1) low molecular weight (LMW) proteins, (2) membrane proteins, (3) proteins that contained various post-translational modifications (PTMs), and (4) nucleic acid-associated proteins. Of 8845 proteins identified in 7 data sets, 79 proteins were classified as MPs. Among data sets derived from different enrichment strategies, data sets for LMW and PTM yielded the most novel MPs. In addition, we found that some MPs were identified in multiple-data sets, which implied that tandem enrichments methods might improve the ability to identify MPs. Moreover, low expression at the transcription level was the major cause of the "missing" of these MPs; however, MPs with higher expression level also evaded identification, most likely due to other characteristics such as LMW, high hydrophobicity and PTM. By combining a stringent manual check of the MS2 spectra with peptides synthesis verification, we confirmed 30 MPs (neXtProt PE2 ∼ PE4) and 6 potential MPs (neXtProt PE5) with authentic MS evidence. By integrating our large-scale data sets of CCPD 2.0, the number of identified proteins has increased considerably beyond simulation saturation. Here, we show that special enrichment strategies can break through the data saturation bottleneck, which could increase the efficiency of MP identification in future C-HPP studies. All 7 data sets have been uploaded to ProteomeXchange with the identifier PXD002255.

Rapid development of proteomics in China: from the perspective of the Human Liver Proteome Project and technology development.

Proteomics focuses on the systematic identification and quantification of entire proteomes and interpretation of proteins' biological functions. During the last decade, proteomics in China has grown much faster than other research fields in the life sciences. At the beginning of the second decade of the 21(st) century, the rapid development of high-resolution and high-speed mass spectrometry makes proteomics a powerful tool to study the mechanisms underlying physiological/pathological processes in organisms. This article provides a brief overview of proteomics technology development and representative scientific progress of the Human Liver Proteome Project (HLPP) in China over the past three years.

Chromosome-8-coded proteome of Chinese Chromosome Proteome Data set (CCPD) 2.0 with partial immunohistochemical verifications.

We upgraded the preliminary CCPD 1.0 to CCPD 2.0 using the latest deep-profiling proteome (CCPD 2013) of three hepatocellular carcinoma (HCC) cell lines, namely, Hep3B, MHCC97H, and HCCLM3 (ProteomeXchange identifiers: PXD000529, PXD000533, and PXD000535). CCPD 2.0 totally covered 63.6% (438/689) of Chr. 8-coded proteins and 62.6% (439/701) of Chr. 8-coded protein-coding genes. Interestingly, we found that the missing proteins exhibited a tendency to form a cluster region in chromosomes, such as two ß-defensins clusters in Chr. 8, caused perhaps by their inflammation-related features. For the 41 Chr. 8-coded proteins being weakly or barely identified previously, we have performed an immunohistochemical (IHC) verification in 30 pairs of carcinoma/para-carcinoma HCC and 20 noncancerous liver tissues and confirmed their expressional evidence and occurrence proportions in tissue samples. We also verified 13 Chr. 8-coded HCC tumorigenesis-associated depleting or deficient proteins reported in CCPD 1.0 using IHC and screened 16 positive and 24 negative HCC metastatic potential-correlated proteins from large-scale label-free proteome quantitation data of CCPD 2013. Our results suggest that the selection of proper samples and the methodology to look for targeted missing proteins should be carefully considered in further verifications for the remaining Chr. 8-coded proteins.

Systematic analyses of the transcriptome, translatome, and proteome provide a global view and potential strategy for the C-HPP.

To estimate the potential of the state-of-the-art proteomics technologies on full coverage of the encoding gene products, the Chinese Human Chromosome Proteome Consortium (CCPC) applied a multiomics strategy to systematically analyze the transciptome, translatome, and proteome of the same cultured hepatoma cells with varied metastatic potential qualitatively and quantitatively. The results provide a global view of gene expression profiles. The 9064 identified high confident proteins covered 50.2% of all gene products in the translatome. Those proteins with function of adhesion, development, reproduction, and so on are low abundant in transcriptome and translatome but absent in proteome. Taking the translatome as the background of protein expression, we found that the protein abundance plays a decisive role and hydrophobicity has a greater influence than molecular weight and isoelectric point on protein detectability. Thus, the enrichment strategy used for low-abundant transcription factors helped to identify missing proteins. In addition, those peptides with single amino acid polymorphisms played a significant role for the disease research, although they might negligibly contribute to new protein identification. The proteome raw and metadata of proteome were collected using the iProX submission system and submitted to ProteomeXchange (PXD000529, PXD000533, and PXD000535). All detailed information in this study can be accessed from the Chinese Chromosome-Centric Human Proteome Database.

Systematic analysis of missing proteins provides clues to help define all of the protein-coding genes on human chromosome 1.

Our first proteomic exploration of human chromosome 1 began in 2012 (CCPD 1.0), and the genome-wide characterization of the human proteome through public resources revealed that 32-39% of proteins on chromosome 1 remain unidentified. To characterize all of the missing proteins, we applied an OMICS-integrated analysis of three human liver cell lines (Hep3B, MHCC97H, and HCCLM3) using mRNA and ribosome nascent-chain complex-bound mRNA deep sequencing and proteome profiling, contributing mass spectrometric evidence of 60 additional chromosome 1 gene products. Integration of the annotation information from public databases revealed that 84.6% of genes on chromosome 1 had high-confidence protein evidence. Hierarchical analysis demonstrated that the remaining 320 missing genes were either experimentally or biologically explainable; 128 genes were found to be tissue-specific or rarely expressed in some tissues, whereas 91 proteins were uncharacterized mainly due to database annotation diversity, 89 were genes with low mRNA abundance or unsuitable protein properties, and 12 genes were identifiable theoretically because of a high abundance of mRNAs/RNC-mRNAs and the existence of proteotypic peptides. The relatively large contribution made by the identification of enriched transcription factors suggested specific enrichment of low-abundance protein classes, and SRM/MRM could capture high-priority missing proteins. Detailed analyses of the differentially expressed genes indicated that several gene families located on chromosome 1 may play critical roles in mediating hepatocellular carcinoma invasion and metastasis. All mass spectrometry proteomics data corresponding to our study were deposited in the ProteomeXchange under the identifiers PXD000529, PXD000533, and PXD000535.

[Feeding mouse with stable isotope labelled with amino acid].

The stable isotope labeling by amino acids in culture (SILAC) based quantitative proteomics serves as a gold standard because of the high accuracy and throughput for protein identifications and quantification. In this study, we discussed the application of SILAC technology in mammal model, and developed quantitative internal standard for comparative proteomics of disease model. The C57BL/6J mice fed by special diet containing the 13C6-Lysine and bred F2 generation. We identified and analyzed total proteins of 9 mice tissues of F2 generation, including brain, lung, heart, stomach, intestine, liver, spleen, kidney, and muscle. Quantitative analysis information could evaluate the mice and different tissues' labeling efficiency. Liver was the most efficient, brain the least, and the labeling efficiency were 96.34%±0.90% and 92.62%±1.98% respectively. The average of the labeling efficiency of F2 generation was 95.80%±0.64%, which met the international standard (≥ 95%) for SILAC quantitative proteomics effective study. SILAC technology was successfully extended to mammalian model system, which will provide powerful tools for the mechanism study of the pathophysiology process with mouse model.

First proteomic exploration of protein-encoding genes on chromosome 1 in human liver, stomach, and colon.

The launch of the Chromosome-Centric Human Proteome Project provides an opportunity to gain insight into the human proteome. The Chinese Human Chromosome Proteome Consortium has initiated proteomic exploration of protein-encoding genes on human chromosomes 1, 8, and 20. Collaboration within the consortium has generated a comprehensive proteome data set using normal and carcinomatous tissues from human liver, stomach, and colon and 13 cell lines originating in these organs. We identified 12,101 proteins (59.8% coverage against Swiss-Prot human entries) with a protein false discovery rate of less than 1%. On chromosome 1, 1,252 proteins mapping to 1,227 genes, representing 60.9% of Swiss-Prot entries, were identified; however, 805 proteins remain unidentified, suggesting that analysis of more diverse samples using more advanced proteomic technologies is required. Genes encoding the unidentified proteins were concentrated in seven blocks, located at p36, q12-21, and q42-44, partly consistent with correlation of these blocks with cancers of the liver, stomach, and colon. Combined transcriptome, proteome, and cofunctionality analyses confirmed 23 coexpression clusters containing 165 genes. Biological information, including chromosome structure, GC content, and protein coexpression pattern was analyzed using multilayered, circular visualization and tabular visualization. Details of data analysis and updates are available in the Chinese Chromosome-Centric Human Proteome Database ( http://proteomeview.hupo.org.cn/chromosome/ ).