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.     

Modelling the effect of forest cover on shallow landslides at the river basin scale

The potential for reducing the occurrence of shallow landslides through targeted reforestation of critical parts of a river basin is explored through mathematical modelling. Through the systematic investigation of land management options, modelling allows the optimum strategies to be selected ahead of any real intervention in the basin. Physically based models, for which the parameters can be evaluated using physical reasoning, offer particular advantages for predicting the effects of possible future changes in land use and climate. Typically a physically based landslide model consists of a coupled hydrological model (for soil moisture) and a geotechnical slope stability model, along with an impact model, such as basin sediment yield. An application of the SHETRAN model to the 65.8-km² Guabalcón basin in central Ecuador demonstrates a technique for identifying the areas of a basin most susceptible to shallow landsliding and for quantifying the effects of different vegetation covers on landslide incidence. Thus, for the modelled scenario, increasing root cohesion from 300 to 1500 Pa causes a two-thirds reduction in the number of landslides. Useful information can be obtained even on the basis of imperfect data availability but model output should be interpreted carefully in the light of parameter uncertainty.     

Heterogeneous phenotype of human glioblastoma: In vitro study

Glioblastomas (GBMs) are the most lethal primary brain tumours. Increasing evidence shows that brain tumours contain the population of stem cells, so‐called cancer stem cells (CSCs). Stem cell marker CD133 was reported to identify CSC population in GBM. Further studies have indicated that CD133 negative cells exhibiting similar properties and are able to initiate the tumour, self‐renew and undergo multilineage differentiation. GBM is a highly heterogeneous tumour and may contain different stem cell populations with different functional properties. We characterized five GBM cell lines, established from surgical samples, according to the marker expression, proliferation and differentiation potential. CD133 positive cell lines showed increased proliferation rate in neurosphere condition and marked differentiation potential towards neuronal lineages. Whereas two cell lines low‐expressing CD133 marker showed mesenchymal properties in vitro, that is high proliferation rate in serum condition and differentiation in mesenchymal cell types. Further, we compared therapy resistance capacity of GBM cell lines treated with hydroxyurea. Our results suggest that CSC concept is more complex than it was believed before, and CD133 could not define entire stem cell population within GBM. At least two different subtypes of GBM CSCs exist, which may have different biological characteristics and imply different therapeutic strategies. Copyright © 2013 John Wiley & Sons, Ltd.     

DQ α and β RFLP reveals the composition of the DQ molecule recognized by T-cell clones

Pst I RFLP, revealed with DQ and DQ probes, was compared with Taq I RFLP using a panel of DR-homozygous cell lines and HLA-typed family members. Taq I patterns, characteristic for each DR-associated DQ and allelic forms, were recognized in the homozygous state and then proven to segregate in the heterozygous members of informative families. The presence of both specific and chains was found to be necessary to form the type of DQ molecule specifically recognized by two alloreactive T-cell clones. Particular and associations also seem to be responsible for some Dw splits of the DRw6-positive cells. Taq I RFLP analysis may be more complex than the Pst I analysis, but is certainly more informative and complete, considering the type of information we were seeking by performing these types of experiments.Abbreviations used in this paper BSA bovine serum albumin - GLO glyoxalase - kb kilobase(s) - LCL lymphoblastoid cell line - MHC major histocompatibility complex - PBL peripheral blood lymphocyte - PLT primed lymphocyte test - RFLP restriction fragment length polymorphism - SDS sodium dodecyl sulfate - SSC standard sodium citrate - SSCP sodium, sodium citrate, sodium phosphate - TBE Tris-borate, boric acid, ethylenediaminetetraacetate (EDTA) - TCGF T-cell growth factor     

Quantitative in vivo nuclear magnetic resonance studies of hybridoma metabolism

Carbon-13 nuclear magnetic resonance (NMR) spectroscopy was used to study the metabolism of a murine hybridoma cell line at two feed glutamine concentrations, 4.0 and 1.7 mM. Carbon-13 labeling patterns were used in conjunction with nutrient uptake rates to calculate the metabolic fluxes through the glycolytic pathway, the pentose shunt, the malate shunt, lipid biosynthesis, and the tricarboxylic acid (TCA) cycle. Decreasing the feed glutamine concentration significantly decreased glutamine uptake but had little effect on glucose metabolism. A significant incrase in antibody productivity occurred upon decreasing the feed glutamine level. The increased antibody productivity in concert with decreased glutamine uptake and no apparent change in glucolytic metabolism suggests that antibody production was not energy limited. Metabolic flux calculations indicate that (1) approximately 92% of the glucose consumed proceeds directly through glycolysis with 8% channeled through the pentose shunt; (2) lipid biosynthesis appears to be greater than malate shunt activity; and (3) considerable exchange occurs between TCA cycle intermediates and amino acid metabolic pools, leading to substantial loss of (13)C label from the TCA cycle. These results illustrate that (13)NMR spectroscopy is a powerfulf tool in the calculation of metabolic fluxes, particularly for exchange pathways where no net flux occurs. (c) 1994 John Wiley & Sons, Inc.