Quantitative proteomic profiling identifies global protein network dynamics in murine embryonic heart development

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Identification of a caleosin associated with hazelnut (Corylus avellana L.) oil bodies

• Caleosins are involved in several cellular and biological processes that are closely associated with the synthesis, degradation and stability of oil bodies (OB).
• Because of the importance and the multiple roles of these OB‐associated proteins, in silico identification of sequences corresponding to putative caleosins in the hazelnut genome has been performed, and the association with seed OB was verified using a proteomic approach.
• Five full‐length sequences (CavCLO‐H1, CavCLO‐H2, CavCLO‐H3, CavCLO‐L1, CavCLO‐L2), belonging to the two groups of caleosins (H and L), have been identified in the hazelnut genome. The number of identified caleosins is in agreement with that previously observed in other plant species, confirming that caleosins comprise small gene families in plants.
• A proteomic approach allowed us to verify only the presence of CavCLO‐H1 in hazelnut OB, suggesting that several members inside this family could have different roles during plant growth and development. In silico analysis also suggests that CavCLO‐H1 may act as a peroxygenase.

     

Towards a matrix mechanics framework for dynamic protein network

Protein–protein interaction networks are currently visualized by software generated interaction webs based upon static experimental data. Current state is limited to static, mostly non-compartmental network and non time resolved protein interactions. A satisfactory mathematical foundation for particle interactions within a viscous liquid state (situation within the cytoplasm) does not exist nor do current computer programs enable building dynamic interaction networks for time resolved interactions. Building mathematical foundation for intracellular protein interactions can be achieved in two increments (a) trigger and capture the dynamic molecular changes for a select subset of proteins using several model systems and high throughput time resolved proteomics and, (b) use this information to build the mathematical foundation and computational algorithm for a compartmentalized and dynamic protein interaction network. Such a foundation is expected to provide benefit in at least two spheres: (a) understanding physiology enabling explanation of phenomenon such as incomplete penetrance in genetic disorders and (b) enabling several fold increase in biopharmaceutical production using impure starting materials.     

A comparative Proteomics Analysis Identified Differentially Expressed Proteins in Pancreatic Cancer–Associated Stellate Cell Small Extracellular Vesicles

Human pancreatic stellate cells (HPSCs) are an essential stromal component and mediators of pancreatic ductal adenocarcinoma (PDAC) progression. Small extracellular vesicles (sEVs) are membrane-enclosed nanoparticles involved in cell-to-cell communications and are released from stromal cells within PDAC. A detailed comparison of sEVs from normal pancreatic stellate cells (HPaStec) and from PDAC-associated stellate cells (HPSCs) remains a gap in our current knowledge regarding stellate cells and PDAC. We hypothesized there would be differences in sEVs secretion and protein expression that might contribute to PDAC biology. To test this hypothesis, we isolated sEVs using ultracentrifugation followed by characterization by electron microscopy and Nanoparticle Tracking Analysis. We report here our initial observations. First, HPSC cells derived from PDAC tumors secrete a higher volume of sEVs when compared to normal pancreatic stellate cells (HPaStec). Although our data revealed that both normal and tumor-derived sEVs demonstrated no significant biological effect on cancer cells, we observed efficient uptake of sEVs by both normal and cancer epithelial cells. Additionally, intact membrane-associated proteins on sEVs were essential for efficient uptake. We then compared sEV proteins isolated from HPSCs and HPaStecs cells using liquid chromatography–tandem mass spectrometry. Most of the 1481 protein groups identified were shared with the exosome database, ExoCarta. Eighty-seven protein groups were differentially expressed (selected by 2-fold difference and adjusted p value ≤0.05) between HPSC and HPaStec sEVs. Of note, HPSC sEVs contained dramatically more CSE1L (chromosome segregation 1–like protein), a described marker of poor prognosis in patients with pancreatic cancer. Based on our results, we have demonstrated unique populations of sEVs originating from stromal cells with PDAC and suggest that these are significant to cancer biology. Further studies should be undertaken to gain a deeper understanding that could drive novel therapy.     

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.     

Quantitative secretome and glycome of primary human adipocytes during insulin resistance

Adipose tissue is both an energy storage depot and an endocrine organ. The impaired regulation of the secreted proteins of adipose tissue, known as adipocytokines, observed during obesity contributes to the onset of whole-body insulin resistance and the pathobiology of type 2 diabetes mellitus (T2DM). In addition, the global elevation of the intracellular glycosylation of proteins by O-linked β-N-acetylglucosamine (O-GlcNAc) via either genetic or pharmacological methods is sufficient to induce insulin resistance in both cultured cells and animal models. The elevation of global O-GlcNAc levels is associated with the altered expression of many adipocytokines. We have previously characterized the rodent adipocyte secretome during insulin sensitive and insulin resistant conditions. Here, we characterize and quantify the secretome and glycome of primary human adipocytes during insulin responsive and insulin resistant conditions generated by the classical method of hyperglycemia and hyperinsulinemia or by the pharmacological manipulation of O-GlcNAc levels. Using a proteomic approach, we identify 190 secreted proteins and report a total of 20 up-regulated and 6 down-regulated proteins that are detected in both insulin resistant conditions. Moreover, we apply glycomic techniques to examine (1) the sites of N-glycosylation on secreted proteins, (2) the structures of complex N- and O-glycans, and (3) the relative abundance of complex N- and O-glycans structures in insulin responsive and insulin resistant conditions. We identify 91 N-glycosylation sites derived from 51 secreted proteins, as well as 155 and 29 released N- and O-glycans respectively. We go on to quantify many of the N- and O-glycan structures between insulin responsive and insulin resistance conditions demonstrating no significant changes in complex glycosylation in the time frame for the induction of insulin resistance. Thus, our data support that the O-GlcNAc modification is involved in the regulation of adipocytokine secretion upon the induction of insulin resistance in human adipocytes.     

Proteomic profiling of lymphedema development in mouse model

The lymphatic vascular system plays an important role in tissue fluid homeostasis. Lymphedema is a chronic, progressive, and incurable condition that leads to lymphatic fluid retention; it may be primary (heritable) or secondary (acquired) in nature. Although there is a growing understanding of lymphedema, methods for the prevention and treatment of lymphedema are still limited. In this study, we investigated differential protein expressions in sham‐operated and lymphedema‐operated mice for 3 days, using two‐dimensional gel electrophoresis (2‐DE) and mass spectrometry analysis. Male improved methodology for culturing noninbred (ICR) mice developed lymphedema in the right hindlimb. Twenty functional proteins were found to be differentially expressed between lymphedema induced‐right leg tissue and normal left leg tissue. Out of these proteins, the protein levels of apolipoprotein A‐1 preprotein, alpha‐actinin‐3, mCG21744, parkinson disease, serum amyloid P‐component precursor, annexin A8, mKIAA0098 protein, and fibrinogen beta chain precursor were differentially upregulated in the lymphedema mice compared with the sham‐operated group. Western blotting analysis was used to validate the proteomics results. Our results showing differential up‐regulation of serum amyloid P‐component precursor, parkinson disease, and apolipoprotein A‐1 preprotein in lymphedema model over sham‐operated model suggest important insights into pathophysiological target for lymphedema. Copyright © 2016 John Wiley & Sons, Ltd.