A-RAF Kinase Functions in ARF6 Regulated Endocytic Membrane Traffic

BACKGROUND: RAF kinases direct ERK MAPK signaling to distinct subcellular compartments in response to growth factor stimulation. METHODOLOGY/PRINCIPAL FINDINGS: Of the three mammalian isoforms A-RAF is special in that one of its two lipid binding domains mediates a unique pattern of membrane localization. Specific membrane binding is retained by an N-terminal fragment (AR149) that corresponds to a naturally occurring splice variant termed DA-RAF2. AR149 colocalizes with ARF6 on tubular endosomes and has a dominant negative effect on endocytic trafficking. Moreover actin polymerization of yeast and mammalian cells is abolished. AR149/DA-RAF2 does not affect the internalization step of endocytosis, but trafficking to the recycling compartment. CONCLUSIONS/SIGNIFICANCE: A-RAF induced ERK activation is required for this step by activating ARF6, as A-RAF depletion or inhibition of the A-RAF controlled MEK-ERK cascade blocks recycling. These data led to a new model for A-RAF function in endocytic trafficking

Computational Homogenization of Architectured Materials

Architectured materials involve geometrically engineered distributions of microstructural phases at a scale comparable to the scale of the component, thus calling for new models in order to determine the effective properties of materials. The present chapter aims at providing such models, in the case of mechanical properties. As a matter of fact, one engineering challenge is to predict the effective properties of such materials; computational homogenization using finite element analysis is a powerful tool to do so. Homogenized behavior of architectured materials can thus be used in large structural computations, hence enabling the dissemination of architectured materials in the industry. Furthermore, computational homogenization is the basis for computational topology optimization which will give rise to the next generation of architectured materials. This chapter covers the computational homogenization of periodic architectured materials in elasticity and plasticity, as well as the homogenization and representativity of random architectured materials

The mutational landscapes of genetic and chemical models of Kras-driven lung cancer

Next-generation sequencing of human tumours has refined our understanding of the mutational processes operative in cancer initiation and progression, yet major questions remain regarding factors that induce driver mutations, and the processes that shape their selection during tumourigenesis. We performed whole-exome sequencing (WES) on adenomas from three mouse models of non-small cell lung cancer (NSCLC), induced by exposure to carcinogens (Methyl-nitrosourea (MNU) and Urethane), or by genetic activation of Kras (Kras(LA2)). Although the MNU-induced tumours carried exactly the same initiating mutation in Kras as seen in the Kras(LA2) model (G12D), MNU tumours had an average of 192 non-synonymous, somatic single nucleotide variants (SNVs), compared to only 6 in tumours from the Kras(LA2) model. In contrast, the Kras(LA2) tumours exhibited a significantly higher level of aneuploidy and copy number alterations (CNAs) compared to the carcinogen-induced tumours, suggesting that carcinogen and genetically-engineered models adopt different routes to tumour development. The wild type (WT) allele of Kras has been shown to act as a tumour suppressor in mouse models of NSCLC. We demonstrate that urethane-induced tumours from WT mice carry mostly (94%) Q61R Kras mutations, while those from Kras heterozygous animals carry mostly (92%) Q61L mutations, indicating a major role of germline Kras status in mutation selection during initiation. The exome-wide mutation spectra in carcinogen-induced tumours overwhelmingly display signatures of the initiating carcinogen, while adenocarcinomas acquire additional C>T mutations at CpG sites. These data provide a basis for understanding the conclusions from human tumour genome sequencing that identified two broad categories based on relative frequency of SNVs and CNAs(1), and underline the importance of carcinogen models for understanding the complex mutation spectra seen in human cancers