MODY 2: Mutation identification and molecular ancestry in a Brazilian family

Maturity Onset Diabetes of the Young (MODY) is a heterogeneous group of genetic diseases characterized by a primary defect in insulin secretion and hyperglycemia, non-ketotic disease, monogenic autosomal dominant mode of inheritance, age at onset less than 25 years, and lack of auto-antibodies. It accounts for 2–5% of all cases of non-type 1 diabetes. MODY subtype 2 is caused by mutations in the glucokinase (GCK) gene. In this study, we sequenced the GCK gene of two volunteers with clinical diagnosis for MODY2 and we were able to identify four mutations including one for a premature stop codon (c.76C>T). Based on these results, we have developed a specific PCR-RFLP assay to detect this mutation and tested 122 related volunteers from the same family. This mutation in the GCK gene was detected in 21 additional subjects who also had the clinical features of this genetic disease. In conclusion, we identified new GCK gene mutations in a Brazilian family of Italian descendance, with one due to a premature stop codon located in the second exon of the gene. We also developed a specific assay that is fast, cheap and reliable to detect this mutation. Finally, we built a molecular ancestry model based on our results for the migration of individuals carrying this genetic mutation from Northern Italy to Brazil.     

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.     

Genetic Targets of Hydrogen Sulfide in Ventilator-Induced Lung Injury – A Microarray Study

Recently, we have shown that inhalation of hydrogen sulfide (H₂S) protects against ventilator-induced lung injury (VILI). In the present study, we aimed to determine the underlying molecular mechanisms of H₂S-dependent lung protection by analyzing gene expression profiles in mice. C57BL/6 mice were subjected to spontaneous breathing or mechanical ventilation in the absence or presence of H₂S (80 parts per million). Gene expression profiles were determined by microarray, sqRT-PCR and Western Blot analyses. The association of Atf3 in protection against VILI was confirmed with a Vivo-Morpholino knockout model. Mechanical ventilation caused a significant lung inflammation and damage that was prevented in the presence of H₂S. Mechanical ventilation favoured the expression of genes involved in inflammation, leukocyte activation and chemotaxis. In contrast, ventilation with H₂S activated genes involved in extracellular matrix remodelling, angiogenesis, inhibition of apoptosis, and inflammation. Amongst others, H₂S administration induced Atf3, an anti-inflammatory and anti-apoptotic regulator. Morpholino mediated reduction of Atf3 resulted in elevated lung injury despite the presence of H₂S. In conclusion, lung protection by H₂S during mechanical ventilation is associated with down-regulation of genes related to oxidative stress and inflammation and up-regulation of anti-apoptotic and anti-inflammatory genes. Here we show that Atf3 is clearly involved in H₂S mediated protection.     

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.