From components to regulatory motifs in signalling networks.

The developments in biochemistry and molecular biology over the past 30 years have produced an impressive parts list of cellular components. It has become increasingly clear that we need to understand how components come together to form systems. One area where this approach has been growing is cell signalling research. Here, instead of focusing on individual or small groups of signalling proteins, researchers are now using a more holistic perspective. This approach attempts to view how many components are working together in concert to process information and to orchestrate cellular phenotypic changes. Additionally, the advancements in experimental techniques to measure and visualize many cellular components at once gradually grow in diversity and accuracy. The multivariate data, produced by experiments, introduce new and exciting challenges for computational biologists, who develop models of cellular systems made up of interacting cellular components. The integration of high-throughput experimental results and information from legacy literature is expected to produce computational models that would rapidly enhance our understanding of the detail workings of mammalian cells.     

SHP2 Drives Adaptive Resistance to ERK Signaling Inhibition in Molecularly Defined Subsets of ERK-Dependent Tumors

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Plasma lipid peroxidation and erythrocyte antioxidants status in workers exposed to nickel

The objectives were to investigate the plasma lipid peroxidation and erythrocyte antioxidants status in workers exposed to nickel. The study groups comprised 69 nickel plating workers and 50 office workers residing in the same city, but away from the place of work of the study group subjects, considered as control group. Urinary nickel concentration was determined by graphite furnace atomic absorption spectrophotometry. The plasma lipid peroxidation and erythrocyte antioxidants were measured by spectrophotmetric methods. The plasma lipid peroxidation level was significantly increased in nickel-platers and their helpers as compared with controls. Erythrocyte antioxidants were significantly decreased in the nickel-platers compared with the controls. The level of plasma lipid peroxidation was positively and erythrocyte antioxidants were negatively and significantly correlated with the urine nickel levels. Multiple regression analysis assessed the oxidative stress associated with nickel and other potential confounding factors such as body mass index, the consumption of green vegetables, coffee, tea, smoking and alcohol consumption. Analysis showed that the lifestyle confounding factors: the consumption of green vegetables, smoking and alcohol, were not significantly associated with oxidative stress. The exposure to nickel, body mass index and coffee consumption were significantly associated with oxidative stress. The results show that the increased plasma lipid peroxidation and decreased erythrocyte antioxidants levels observed in nickel-exposed workers could be used as biomarkers of oxidative stress.     

In vitro culture of coffee zygotic embryos for germplasm preservation

Immature zygotic embryos of Coffea arabica L. Cv. Cauvery (Catimor) were cultured on Murashige and Skoog (1962) (MS) medium supplemented with abscisic acid (ABA) at 0, 0.4, 3.8, 18.9, 37.8 and 75.6 μM., L-cystein hydrochloride at 50 mg 1^-1 and sucrose at 3%. Cultures were preserved in parafilm sealed Petri dishes in dark at a temperature of 25 ± 1 °C for up to two years. The preserved embryos were taken out from the media at 6 month intervals in order to test their viability by germination on MS + NAA (0.5 μM) + BA (4.4 μM). On the preservation media devoid of ABA or with a low concentration (0.4 μM) of ABA, the embryos germinated and showed higher mortality with increasing duration of storage. In contrast, the embryos became increasingly dormant with increasing concentrations of ABA and a 74.2% survival was found even after 2 years on medium supplemented with 18.9 μM or 37.8 μM of ABA. The results suggest that embryos can be preserved with a little loss of viability in the presence of ABA even at the normal room temperature (25 + 1 °C) up to two years without any transfer. Application of this technique for germplasm preservation of coffee is discussed. This revised version was published online in June 2006 with corrections to the Cover Date.     

Insights into Fanconi Anaemia from the structure of human FANCE

Fanconi Anaemia (FA) is a cancer predisposition disorder characterized by spontaneous chromosome breakage and high cellular sensitivity to genotoxic agents. In response to DNA damage, a multi-subunit assembly of FA proteins, the FA core complex, monoubiquitinates the downstream FANCD2 protein. The FANCE protein plays an essential role in the FA process of DNA repair as the FANCD2-binding component of the FA core complex. Here we report a crystallographic and biological study of human FANCE. The first structure of a FA protein reveals the presence of a repeated helical motif that provides a template for the structural rationalization of other proteins defective in Fanconi Anaemia. The portion of FANCE defined by our crystallographic analysis is sufficient for interaction with FANCD2, yielding structural information into the mode of FANCD2 recruitment to the FA core complex. Disease-associated mutations disrupt the FANCE–FANCD2 interaction, providing structural insight into the molecular mechanisms of FA pathogenesis.     

A Time-Series-Based Feature Extraction Approach for Prediction of Protein Structural Class

This paper presents a novel feature vector based on physicochemical property of amino acids for prediction protein structural classes. The proposed method is divided into three different stages. First, a discrete time series representation to protein sequences using physicochemical scale is provided. Later on, a wavelet-based time-series technique is proposed for extracting features from mapped amino acid sequence and a fixed length feature vector for classification is constructed. The proposed feature space summarizes the variance information of ten different biological properties of amino acids. Finally, an optimized support vector machine model is constructed for prediction of each protein structural class. The proposed approach is evaluated using leave-one-out cross-validation tests on two standard datasets. Comparison of our result with existing approaches shows that overall accuracy achieved by our approach is better than exiting methods.