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.     

Selective phagocytosis of gram-positive bacteria and interleukin 1-like factor production by a subpopulation of large granular lymphocytes

There has been a consensus that a large granular lymphocyte (LGL) population with natural killer (NK) function is nonadherent and nonphagocytic. However, a significant proportion of the nonadherent cells purified by the two-step depletion of adherent cells with a plastic surface and nylon wool columns engulfed Sta. aureus into their cytoplasm. These cells were morphologically identified as LGL in light and electron microscopies. Two-color immunofluorescence tests, furthermore, demonstrated that Leu-11+ LGL, Leu-11+7-, and Leu-11+7+, but not Leu-11-7+, phagocytosed Sta. aureus. Among the particles tested here, only Gram(+) bacteria were preferentially phagocytosed, whereas Gram(-) bacteria, other large-sized microbes (e.g., baker's yeast and Candida albicans), latex, silica, and carbonyl iron were not. LGL exhibited a substantial level of bactericidal activity against Sta. aureus, although the level was one third of that mediated by monocytes. When Gram(+) bacteria were incubated with nonadherent cells for 18 hr, significant amounts of interleukin 1 (IL 1)-like factors (or IL 1 itself) as well as interferon were detected in the supernatants. On the other hand, this incubation did not induce interleukin 2 (IL 2). The IL 1-like factor producer cells were demonstrated to be the low-density lymphocytes on Percoll separation and to have the Leu-11+ phenotype. The phagocytosis was suggested to be an important stimulus in producing IL 1-like factors from LGL. Thus, the treatment of cells with cytochalasin B, a microfilament disrupting agent, completely abrogated both phagocytosis and IL 1-like factor production. Some cell wall components of Gram(+) bacteria might be important to a recognition process of the phagocytosis, since the protoplasts of Sta. aureus, when prepared by the treatment of bacteria with lysostaphin, were no longer phagocytosed by LGL. The present results therefore identify an additional unique characteristic similar to, but not identical with, the myelomonocytic nature of Leu-11+ LGL.     

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     

Interaction of trace elements in a longitudinal study of human milk from full-term and preterm mothers

Concentrations of 8 trace elements (Fe, Cu, Zn, Se, Br, Pb, Rb, and Sr) at different lactation time were measured by the PIXE multi-elemental technique. Time dependence and interelement correlations were studied. A total of 200 milk samples from 32 lactating mothers were supplied from 2 to 120 d after delivery of 26 full-term and 6 preterm infants. All elements showed a lognormal frequency-distribution. The Fe, Cu, Zn, and Se contents in preterm milk were found to be somewhat different with respect to full-term milk. Cu, Zn, Se, Br, Pb, and Rb concentrations declined with lactation time, both in pre- and full-term samples. Sr and Fe contents did not show any change with time. Detailed analysis of data by partial correlation and multiple regression methods was performed. No substantial differences between preterm and full-term samples were found in the results of partial correlation analysis. Cu and Zn were found to be correlated with lactation time, whereas the measured time dependence for the other elements has to be attributed to the effect of the existing interelement correlation. All the measured elements appeared to be correlated with at least one other element. In particular, Se was inversely correlated with Zn and directly with Cu. The zinc and copper contents in milk can therefore depend on the variation in the mother selenium intake.