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.     

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.     

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.     

Characterization of the Glycolipid Associated with Alzheimer Paired Helical Filaments

Abstract: In the present study, analytical techniques including gas chromatography/mass spectrometry (GC/MS)-assisted carbohydrate linkage-analysis, one- and two-dimensional NMR, and matrix-assisted laser desorption/ionization time of flight mass spectroscopy (MALDI-MS) have been used to characterize the structure of the glycolipid associated with the paired helical filaments (PHF) isolated from the neurofibrillary tangles of Alzheimer's diseased brain. The ¹H NMR spectrum of acid-hydrolyzed protein-resistant core PHF (prcPHF) displays resonances that can be assigned to fatty acid and glucose. There are no resonances present that would indicate the presence of protein, amino acids, or a sphingosine base. Using two-dimensional homonuclear correlated spectroscopy, homonuclear Hartmann-Hahn, and heteronuclear multiple quantum coherence experiments, resonances in the ¹H and ¹³C NMR spectrum of native PHF were assigned to a nonreducing terminal α-1,6-glycosidically linked glucose, an internal α-1,6-linked glucose, and an α-1,2,6-linked glucose. The narrow line-widths observed for these residues suggest that they arise from glucose residues undergoing rapid segmental motion. The carbohydrate portion of the PHF-associated glycolipid was analyzed using GC/MS linkage analysis and confirmed the presence of terminal and internal α-1,6-linked glucose and α-1,2,6-linked glucose in a molar ratio of 2:1:1. Three components of the PHF-associated glycolipid fraction having masses 2,416, 2,325, and 2,237 Da were observed using MALDI-MS. The least abundant, heavier mass component (2,416 Da) was best fit to a structure with a tridecamer of glucose having a single esterified C₂₀ fatty acid (Glc₁₃ + C₂₀ or Glc₁₃ + C_20:1), whereas the more abundant, lower mass components were best fit to noncovalently associated glycolipid dimers, each with a glucose pentamer or hexamer having two C₁₄, C₁₆, or C₁₈ esterified fatty acids {D[(Glc₅ + C₁₈) + (Glc₆ + C₁₆)] or D[(Glc₅ + C₁₄) + (Glc₆ + C₁₄)]}. The ratio of glucose to fatty acid calculated from these best-fit structures of the more abundant mass components (5.5 ± 1.1:1.0) is in reasonable agreement with the same ratio calculated from peak integrations in the NMR spectra of acid-hydrolyzed prcPHF (6.2 ± 1.6). Structural similarities between PHF-associated glycolipid and other glycolipid amphiphiles known to form PHF-like filaments indirectly suggest that this unique glycolipid may be an integral component of the PHF suprastructure.     

Deep-lipidotyping by mass spectrometry: recent technical advances and applications

In-depth structural characterization of lipids is an essential component of lipidomics. There has been a rapid expansion of mass spectrometry methods that are capable of resolving lipid isomers at various structural levels over the past decade. These developments finally make deep-lipidotyping possible, which provides new means to study lipid metabolism and discover new lipid biomarkers. In this review, we discuss recent advancements in tandem mass spectrometry (MS/MS) methods for identification of complex lipids beyond the species (known headgroup information) and molecular species (known chain composition) levels. These include identification at the levels of carbon-carbon double bond (C=C) location and sn-position, as well as characterization of acyl chain modifications. We also discuss the integration of isomer-resolving MS/MS methods with different lipid analysis workflows and their applications in lipidomics. The results showcase the distinct capabilities of deep-lipidotyping in untangling the metabolism of individual isomers and sensitive phenotyping by using relative fractional quantitation of the isomers.     

Novel biomarkers in amniotic fluid for early assessment of intraamniotic infection

Intra-amniotic infection/inflammation (IAI) is associated with preterm birth, short and long-term adverse clinical outcomes and oxidative stress. The diagnosis of IAI is based on histological and clinical findings; however, often these results are unspecific. Therefore, efforts have been directed towards validating reliable methods for patients lacking overt clinical symptoms. In this study, amniotic fluid (AF) samples were prospectively collected from 23 women grouped into two categories (with or without IAI) following clinical, microbiological and histological criteria. AFs were analyzed using liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) for the determination of the following biomarkers: oxidized and nitrated tyrosines (Tyr), 8-hydroxy-2'-deoxyguanosine (8OHdG), oxidized glutathione (GSSG) and glutathione sulfonamide (GSA). 3-NO₂-Tyrosine (3NO₂-Tyr) and GSSG concentrations in AF were not identified as significantly relevant biomarkers in the presence of IAI. However, inflammatory biomarkers such as GSA (p=0.002) and 3-Chloro-Tyrosine [3Cl-Tyr (p=0.049)], and oxidative stress biomarker 8OHdG (p=0.021) were significantly increased in AF with IAI as compared to normal controls. Biomarkers of inflammation and oxidative stress determined in AF samples could represent a new approach towards an early diagnosis of IAI and subsequent chorioamnionitis in the clinical setting.