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.     

Sources of Variability in the Measurement of Fungal Spore Yields

Variability in the production of fungal spores and in the measurement of spore yields was investigated in four species of fungi: Colletotrichum gloeosporioides, Colletotrichum coccodes, Colletotrichum phomoides, and Acremonium strictum. When the fungi were grown on solid medium in microplates and spore yields were measured by counting the subsamples with a hemacytometer, the variability among hemacytometer squares was always the largest source of variation, accounting for 51 to 91% of the total variation. Variability among replicate cultures and results of repeat experiments were generally also significant. The effect of square-to-square variability on the precision of spore yield measurement was minimized by counting a moderate number (ca. 30) of squares per culture. Culture-to-culture variability limited the practical precision of spore production measurements to a 95% confidence interval of approximately the mean ± 25%. We provide guidelines for determining the number of replicate cultures required to attain this or other degrees of precision. Particle counter-derived spore counts and counts based on spore weights were much less variable than were hemacytometer counts, but they did not improve spore production estimates very much because of culture-to-culture variability. Results obtained by both of these methods differed from those obtained with a hemacytometer; particle counter measurements required a correction for spore pairs, while the relationship between spore weights and spore counts changed as the cultures aged.     

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     

T4 DNA replication and viral gene expression

The normal dependence of “late” T4 gene expression on concurrent viral DNA replication is circumvented in cells infected with a triple mutant in which viral DNA polymerase, DNA ligase, and the exonuclease functions of genes 46 or 47 are defective. Acrylamide gel electrophoresis of labeled proteins from infected cells has made possible an extension of the analysis of replication-uncoupled T4 protein synthesis. We find a number of late T4 proteins synthesized: the products of genes 34, 37, 18, 23 and 24. Processing of the gene 23 product, normally headassembly dependent, occurs, but with considerably diminished efficiency compared to wild-type infection. Late T4 protein synthesis in replication-uncoupled infection retains a requirement for T4 gene 33 and gene 55 function. Finally, a number of “early” T4 gene products, normally shut off late in wildtype infection, continue to be synthesized late in replication-uncoupled infection, concurrently with the late proteins.