Motile hepatocellular carcinoma cells preferentially secret sugar metabolism regulatory proteins via exosomes

Exosomes are deliverers of critically functional proteins, capable of transforming target cells in numerous cancers, including hepatocellular carcinoma (HCC). We hypothesize that the motility of HCC cells can be featured by comparative proteome of exosomes. Hence, we performed the super‐SILAC‐based MS analysis on the exosomes secreted by three human HCC cell lines, including the non‐motile Hep3B cell, and the motile 97H and LM3 cells. More than 1400 exosomal proteins were confidently quantified in each MS analysis with highly biological reproducibility. We justified that 469 and 443 exosomal proteins represented differentially expressed proteins (DEPs) in the 97H/Hep3B and LM3/Hep3B comparisons, respectively. These DEPs focused on sugar metabolism‐centric canonical pathways per ingenuity pathway analysis, which was consistent with the gene ontology analysis on biological process enrichment. These pathways included glycolysis I, gluconeogenesis I and pentose phosphate pathways; and the DEPs enriched in these pathways could form a tightly connected network. By analyzing the relative abundance of proteins and translating mRNAs, we found significantly positive correlation between exosomes and cells. The involved exosomal proteins were again focusing on sugar metabolism. In conclusion, motile HCC cells tend to preferentially export more sugar metabolism‐associated proteins via exosomes that differentiate them from non‐motile HCC cells.     

Dissection of DEN-induced platelet proteome changes reveals the progressively dys-regulated pathways indicative of hepatocarcinogenesis

Due to the lack of precise markers indicative of its occurrence, progression, and malignant stages, hepatocellular carcinoma (HCC) is currently associated with high mortality. Given the fact that thrombocytopenia is associated with chronic liver diseases, and the multifunctional nature of platelets we reason that phenotype-specific platelets could be the systemic barometer for hepato-carcinogenesis. The mass spectrometry (MS)-based proteomic efforts to discover novel biomarkers in plasma or serum are largely compromised by a few of the overwhelmingly abundant proteins that comprise over 95% of the total protein mass of plasma or sera. Platelets however are free of these MS signal-suppressing proteins. On the basis of a HCC animal model where diethyl nitrosamine (DEN) administration on male rats specifically induces HCC, by using a multiplex quantitative proteomic approach, we profiled the phase-to-phase proteome changes in a series of viable phenotype-specific platelets along with the DEN-induced progressive liver transformation. The platelet proteome was found highly responsive to each physiological stage of liver inflammation or pathogenesis. Using data-dependent bioinformatics network analysis, we found that certain pathway modules involved in immune response, tissue wound repair, apoptosis, cell proliferation, and catabolism and metabolism were differentially regulated, which were uncovered by the DEN-induced differential expression of the corresponding pathway components. The phase-specific presentations of these pathways suggested that the DEN-induced progression of immune suppression and apoptosis resistance is dynamically coordinated in the platelets. These novel platelet signatures are interconnected in the dynamic networks along with HCC progression and could be identified noninvasively for HCC prognosis and early diagnosis.     

Surface plasmon resonance mass spectrometry in proteomics

Due to the enormous complexity of the proteome, focus in proteomics shifts more and more from the study of the complete proteome to the targeted analysis of part of the proteome. The isolation of this specific part of the proteome generally includes an affinity-based enrichment. Surface plasmon resonance (SPR), a label-free technique able to follow enrichment in real-time and in a semiquantitative manner, is an emerging tool for targeted affinity enrichment. Furthermore, in combination with mass spectrometry (MS), SPR can be used to both selectively enrich for and identify proteins from a complex sample. Here we illustrate the use of SPR-MS to solve proteomics-based research questions, describing applications that use very different types of immobilized components: such as small (drug or messenger) molecules, peptides, DNA and proteins. We evaluate the current possibilities and limitations and discuss the future developments of the SPR-MS technique.     

Proteomic analysis of cellular protein alterations using a hepatitis B virus-producing cellular model

Hepatitis B virus (HBV) is one of the major etiological factors responsible for acute and chronic liver disease and for the development of hepatocellular carcinoma (HCC). To determine the effects of HBV replication on host cell-protein expression, we utilized 2-DE and MS/MS analysis to compare and identify differentially expressed proteins between an HBV-producing cell line HepG2.2.15 and its parental cell line HepG2. Of the 66 spots identified as differentially expressed (+/- over twofold, p <0.05) between the two cell lines, 62 spots (corresponding to 61 unique proteins) were positively identified by MS/MS analysis. These proteins could be clearly divided into three major groups by cluster and metabolic/signaling pathway analysis: proteins involved in retinol metabolism pathway, calcium ion-binding proteins, and proteins associated with protein degradation pathways. Other proteins identified include those that function in diverse biological processes such as signal transduction, immune regulation, molecular chaperone, electron transport/redox regulation, cell proliferation/differentiation, and mRNA splicing. In summary, we profiled proteome alterations between HepG2.2.15 and HepG2 cells. The proteins identified in this study would be useful in revealing the mechanisms underlying HBV-host cell interactions and the development of HCC. This study can also provide some useful clues for antiviral research.     

Surface plasmon resonance mass spectrometry in proteomics

Due to the enormous complexity of the proteome, focus in proteomics shifts more and more from the study of the complete proteome to the targeted analysis of part of the proteome. The isolation of this specific part of the proteome generally includes an affinity-based enrichment. Surface plasmon resonance (SPR), a label-free technique able to follow enrichment in real-time and in a semiquantitative manner, is an emerging tool for targeted affinity enrichment. Furthermore, in combination with mass spectrometry (MS), SPR can be used to both selectively enrich for and identify proteins from a complex sample. Here we illustrate the use of SPR-MS to solve proteomics-based research questions, describing applications that use very different types of immobilized components: such as small (drug or messenger) molecules, peptides, DNA and proteins. We evaluate the current possibilities and limitations and discuss the future developments of the SPR-MS technique.     

Proteomic analysis of liver development of lean Pekin duck (Anas platyrhynchos domestica)

The liver plays vital roles in digestion, metabolism and immune defense. To elucidate the molecular mechanism of nutrient metabolism and antioxidation of lean Pekin duck liver from hatching to slaughter, the proteome changes were investigated using 2-DE, MS, quantitative real-time PCR and bioinformatics. A total of 59 differentially expressed proteins were identified. Proteins involved in transportation were highly up-regulated in newborn ducks whereas 37 proteins associated with metabolism, defense and antioxidation were up-regulated in adult ducks. The over-expression of proteins at the last developmental stage presumably occurs to fulfill the needs of multiple functions of the liver. However, the over-expressed proteins related to transportation during the first developmental stage are involved in maintaining the high basal metabolism of newborn ducks. The functional enrichment analysis also confirmed these results. Furthermore, the protein interaction network predicted 28 proteins acting as key nodes for liver development. The validated expression between proteins and genes provides us target genes for future genetic analyses to improve the health and performance of these ducks. These significant advanced proteome data expand our knowledge on the physiology of the duck liver, thereby providing a potentially valuable foundation for molecular breeding to enhance feed efficiency and immunity and for optimizing the feeding strategy.     

Quantitative proteomics reveal up-regulated protein expression of the SET complex associated with hepatocellular carcinoma

We combined culture-derived isotope tags (CDITs) with two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) to extensively survey abnormal protein expression associated with hepatocellular carcinoma (HCC) in clinical tissues. This approach yielded an in-depth quantitated proteome of 1360 proteins. Importantly, 267 proteins were significantly regulated with a fold-change of at least 1.5. The proteins up-regulated in HCC tissues are involved in regulatory processes, such as the granzyme A-mediated apoptosis pathway (The GzmA pathway). The SET complex, a central component in the GzmA pathway, was significantly up-regulated in HCC tissue. The elevated expressions of all of the SET complex components were validated by Western blotting. Among them, ANP32A and APEX1 were further investigated by immunohistochemistry staining using tissue microarrays (59 cases), confirming their overexpression in tumors. The up-regulation and nuclear accumulations of APEX1 was associated not only with HCC malignancy but also with HCC differentiation in 96 clinical HCC cases. Our work provided a systematic and quantitative analysis and demonstrated key changes in clinical HCC tissues. These proteomic signatures could help to unveil the underlying mechanisms of hepatocarcinogenesis and may be useful for the discovery of candidate biomarkers.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

Activity profiling of platelets by chemical proteomics

Chemical proteomics or activity based proteomics is a functional proteomics technology where molecular probes are used to target a selective group of functionally related proteins. Its emergence has enabled specific targeting of subproteomes, overcoming the limitations in dynamic range of traditional large‐scale proteomics experiments. Using a chemical proteomics strategy, we attempt to differentially profile the nucleotide‐binding proteome of active and resting platelets. We apply an affinity chromatography protocol using immobilized adenosine triphosphate, cyclic adenosine monophosphate, and cyclic guanosine monophosphate. The specificity of the immobilized nucleotides was demonstrated by competitive assays and by immunoblotting. LC coupled MS/MS was applied to identify the proteins recovered by our chemical proteomics strategy. When compared to a standard set of platelet lysate proteins, we confirmed that enrichment for nucleotide‐binding proteins was indeed taking place. Finally, by employing label‐free MS‐based comparative quantification, we found a small number of platelet proteins that show statistically significant difference between the active and resting nucleotide‐binding proteome.     

Bacterial proteome of streptococcus pneumoniae through multidimensional separations coupled with LC-MS/MS

Streptococcus pneumoniae is a major human respiratory pathogen causing considerable morbidity and mortality worldwide. In order to better understand the pathogenesis of S. pneumoniae, we employed SDS-PAGE combined with LC-MS/MS analysis and in-solution digestion coupled with 2D-LC-MS/MS to obtain the whole-cell proteome of the bacterium. Among the identified 1,210 proteins, 345 proteins were annotated for cellular components, 613 for biological processes, and 421 for molecular functions. Important virulence-associated surface proteins such as Eno, ZmpB, and PrtA were identified. Classification analysis and protein-protein interaction map revealed that these identified proteins are involved in many biological processes including protein biosynthesis, protein folding and proteolysis, cell cycle, or regulation and carbohydrate metabolism. These data represent a comprehensive reference map of S. pneumoniae proteome, providing a useful source for further analysis of the virulence factors and the regulatory network involved in the pathogenesis of the bacterium.     

Simple But Efficacious Enrichment of Integral Membrane Proteins and Their Interactions for In-Depth Membrane Proteomics

Membrane proteins play essential roles in various cellular processes, such as nutrient transport, bioenergetic processes, cell adhesion, and signal transduction. Proteomics is one of the key approaches to exploring membrane proteins comprehensively. Bottom–up proteomics using LC–MS/MS has been widely used in membrane proteomics. However, the low abundance and hydrophobic features of membrane proteins, especially integral membrane proteins, make it difficult to handle the proteins and are the bottleneck for identification by LC–MS/MS. Herein, to improve the identification and quantification of membrane proteins, we have stepwisely evaluated methods of membrane enrichment for the sample preparation. The enrichment methods of membranes consisted of precipitation by ultracentrifugation and treatment by urea or alkaline solutions. The best enrichment method in the study, washing with urea after isolation of the membranes, resulted in the identification of almost twice as many membrane proteins compared with samples without the enrichment. Notably, the method significantly enhances the identified numbers of multispanning transmembrane proteins, such as solute carrier transporters, ABC transporters, and G-protein–coupled receptors, by almost sixfold. Using this method, we revealed the profiles of amino acid transport systems with the validation by functional assays and found more protein–protein interactions, including membrane protein complexes and clusters. Our protocol uses standard procedures in biochemistry, but the method was efficient for the in-depth analysis of membrane proteome in a wide range of samples.     

A functional annotation of subproteomes in human plasma

The data collected by Human Proteome Organization's Plasma Proteome Pilot project phase was analyzed by members of our working group. Accordingly, a functional annotation of the human plasma proteome was carried out. Here, we report the findings of our analyses. First, bioinformatic analyses were undertaken to determine the likely sources of plasma proteins and to develop a protein interaction network of proteins identified in this project. Second, annotation of these proteins was performed in the context of functional subproteomes involved in the coagulation pathway, the mononuclear phagocytic system, the inflammation pathway, the cardiovascular system, and the liver; as well as the subset of proteins associated with DNA binding activities. Our analyses contributed to the Plasma Proteome Database (http://www.plasmaproteomedatabase.org), an annotated database of plasma proteins identified by HPPP as well as from other published studies. In addition, we address several methodological considerations including the selective enrichment of post-translationally modified proteins by the use of multi-lectin chromatography as well as the use of peptidomic techniques to characterize the low molecular weight proteins in plasma. Furthermore, we have performed additional analyses of peptide identification data to annotate cleavage of signal peptides, sites of intra-membrane proteolysis and post-translational modifications. The HPPP-organized, multi-laboratory effort, as described herein, resulted in much synergy and was essential to the success of this project.     

Protein expression profiling of nuclear membrane protein reveals potential biomarker of human hepatocellular carcinoma

Background

Complex molecular events lead to development and progression of liver cirrhosis to HCC. Differentially expressed nuclear membrane associated proteins are responsible for the functional and structural alteration during the progression from cirrhosis to carcinoma. Although alterations/ post translational modifications in protein expression have been extensively quantified, complementary analysis of nuclear membrane proteome changes have been limited. Deciphering the molecular mechanism that differentiate between normal and disease state may lead to identification of biomarkers for carcinoma.

Results

Many proteins displayed differential expression when nuclear membrane proteome of hepatocellular carcinoma (HCC), fibrotic liver, and HepG2 cell line were assessed using 2-DE and ESI-Q-TOF MS/MS. From the down regulated set in HCC, we have identified for the first time a 15 KDa cytochrome b5A (CYB5A), ATP synthase subunit delta (ATPD) and Hemoglobin subunit beta (HBB) with 11, 5 and 22 peptide matches respectively. Furthermore, nitrosylation studies with S-nitrosocysteine followed by immunoblotting with anti SNO-cysteine demonstrated a novel and biologically relevant post translational modification of thiols of CYB5A in HCC specimens only. Immunofluorescence images demonstrated increased protein S-nitrosylation signals in the tumor cells and fibrotic region of HCC tissues. The two other nuclear membrane proteins which were only found to be nitrosylated in case of HCC were up regulated ATP synthase subunit beta (ATPB) and down regulated HBB. The decrease in expression of CYB5A in HCC suggests their possible role in disease progression. Further insight of the functional association of the identified proteins was obtained through KEGG/ REACTOME pathway analysis databases. String 8.3 interaction network shows strong interactions with proteins at high confidence score, which is helpful in characterization of functional abnormalities that may be a causative factor of liver pathology.

Conclusion

These findings may have broader implications for understanding the mechanism of development of carcinoma. However, large scale studies will be required for further verification of their critical role in development and progression of HCC.     

Characterisation of Plasmodium invasive organelles; an ookinete microneme proteome

Secretion of microneme proteins is essential to Plasmodium invasion but the molecular composition of these secretory organelles remains poorly defined. Here, we describe the first Plasmodium microneme proteome. Purification of micronemes by subcellular fractionation from cultured ookinetes was confirmed by enrichment of known micronemal proteins and electron microscopy. Quantitation of electron micrographs showed >14‐fold microneme enrichment compared to the intact ookinete, such that micronemes comprised 85% of the identifiable organelles in the fraction. Gel LC‐MS/MS of the most abundant protein constituents of the fraction identified three known micronemal proteins chitinase, CTRP, SOAP, together with protein disulphide isomerase (PDI) and HSP70. Highly sensitive MudPIT shotgun proteomics described a total of 345 proteins in the fraction. M1 aminopeptidase and PDI, the former a recognised target of drug development, were both shown to have a micronemal location by IFA. We further identified numerous proteins with established vesicle trafficking and signaling functions consistent with micronemes being part of a regulated secretory pathway. Previously uncharacterised proteins comprise the largest functional group of the microneme proteome and will include secreted proteins important to invasion.     

Comprehensive proteomic datasets for studying adipocyte–macrophage cell–cell communication

Cellular communication is a fundamental process in biology. The interaction of adipocytes with macrophages is a key event in the development of common diseases such as type 2 diabetes. We applied an established bilayer cell coculture system and comprehensive MS detection to analyse on a proteome‐wide scale the paracrine interaction of murine adipocytes and macrophages. Altogether, we identified 4486 proteins with at least two unique peptides, of which 2392 proteins were informative for 3T3‐L1 adipocytes and 2957 proteins for RAW 264.7 macrophages. Further, we observed over 12000 phosphorylation sites, of which we could assign 3200 informative phosphopeptides with a single phosphosite for adipocytes and 4514 for macrophages. Using protein set enrichment and phosphosite analyses, we deciphered regulatory protein pathways involved in cellular stress and inflammation, which can contribute to metabolic impairment of cells including insulin resistance and other disorders. The generated datasets provide a holistic, molecular pathway‐centric view on the interplay of adipocytes and macrophages in disease processes and a resource for further studies.     

Tissue proteomics by one-dimensional gel electrophoresis combined with label-free protein quantification

Label-free methods streamline quantitative proteomics of tissues by alleviating the need for metabolic labeling of proteins with stable isotopes. Here we detail and implement solutions to common problems in label-free data processing geared toward tissue proteomics by one-dimensional gel electrophoresis followed by liquid chromatography tandem mass spectrometry (geLC MS/MS). Our quantification pipeline showed high levels of performance in terms of duplicate reproducibility, linear dynamic range, and number of proteins identified and quantified. When applied to the liver of an adenomatous polyposis coli (APC) knockout mouse, we demonstrated an 8-fold increase in the number of statistically significant changing proteins compared to alternative approaches, including many more previously unidentified hydrophobic proteins. Better proteome coverage and quantification accuracy revealed molecular details of the perturbed energy metabolism.