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.     

Simulation methods with extended stability for stiff biochemical Kinetics

Background  

With increasing computer power, simulating the dynamics of complex systems in chemistry and biology is becoming increasingly routine. The modelling of individual reactions in (bio)chemical systems involves a large number of random events that can be simulated by the stochastic simulation algorithm (SSA). The key quantity is the step size, or waiting time, τ, whose value inversely depends on the size of the propensities of the different channel reactions and which needs to be re-evaluated after every firing event. Such a discrete event simulation may be extremely expensive, in particular for stiff systems where τ can be very short due to the fast kinetics of some of the channel reactions. Several alternative methods have been put forward to increase the integration step size. The so-called τ-leap approach takes a larger step size by allowing all the reactions to fire, from a Poisson or Binomial distribution, within that step. Although the expected value for the different species in the reactive system is maintained with respect to more precise methods, the variance at steady state can suffer from large errors as τ grows.     

The cell cycle modulated glycoprotein GP115 is one of the major yeast proteins containing glycosylphosphatidylinositol

The cell cycle modulated protein gp115 (115 kDa, isoelectric point about 4.8-5) of Saccharomyces cerevisiae undergoes various post-translational modifications. It is N-glycosylated during its maturation along the secretory pathway where an intermediary precursor of 100 kDa (p100), dynamically related to the mature gp115 protein, is detected at the level of endoplasmic reticulum. Moreover, we have shown by the use of metabolic labeling with [35S]methionine, [3H]palmitic acid and myo-[3H]inositol combined with high resolution two-dimensional gel electrophoresis and immunoprecipitation with a specific antiserum, that gp115 is one of the major palmitate- and inositol-containing proteins in yeast. These results, and the susceptibility of gp115 to phosphatidylinositol-specific phospholipase C treatment strongly indicate that gp115 contains the glycosylphosphatidylinositol (GPI) structure as membrane anchor domain. The two-dimensional analysis of the palmitate- and inositol-labeled proteins has also allowed the characterization of other polypeptides which possibly contain a GPI structure.