Proteomics of breast cancer for marker discovery and signal pathway profiling

Breast cancer is the most common form of cancer among women and the identification of markers to discriminate tumorigenic from normal cells, as well as the different stages of this pathology, is of critical importance. Two-dimensional electrophoresis has been used before for studying breast cancer, but the progressive completion of human genomic sequencing and the introduction of mass spectrometry, combined with advanced bioinformatics for protein identification, have considerably increased the possibilities for characterizing new markers and therapeutic targets. Breast cancer proteomics has already identified markers of potential clinical interest (such as the molecular chaperone 14-3-3 sigma) and technological innovations such as large scale and high throughput analysis are now driving the field. Methods in functional proteomics have also been developed to study the intracellular signaling pathways that underlie the development of breast cancer. As illustrated with fibroblast growth factor-2, a mitogen and motogen factor for breast cancer cells, proteomics is a powerful approach to identify signaling proteins and to decipher the complex signaling circuitry involved in tumor growth. Together with genomics, proteomics is well on the way to molecularly characterizing the different types of breast tumor, and thus defining new therapeutic targets for future treatment.

Homeotic genes influence the axonal pathway of a Drosophila embryonic sensory neuron

Each abdominal hemisegment of the Drosophila embryo has two sensory neurons intimately associated with a tracheal branch. During embryogenesis, the axons of these sensory neurons, termed the v'td2 neurons, enter the CNS and grow toward the brain with a distinctive pathway change in the third thoracic neuromere. We show that the axons use guidance cues that are under control of the bithorax gene complex (BX-C). Pathway defects in mutants suggest that a drop in Ultrabithorax expression permits the pathway change in the T3 neuromere, while combined Ultrabithorax and abdominal-A expression represses it in the abdominal neuromeres. We propose that the axons do not respond to a particular segmental identity in forming the pathway change; rather they respond to pathfinding cues that come about as a result of a drop in BX-C expression along the antero-posterior axis of the CNS.

Axon navigation in the mammalian primary olfactory pathway: Where to next?

The process of establishing long-range neuronal connections can be divided into at least three discrete steps. First, axons need to be stimulated to grow and this growth must be towards appropriate targets. Second, after arriving at their target, axons need to be directed to their topographically appropriate position and in some cases, such as in cortical structures, they must grow radially to reach the correct laminar layer Third, axons then arborize and form synaptic connections with only a defined subpopulation of potential post-synaptic partners. Attempts to understand these mechanisms in the visual system have been ongoing since pioneer studies in the 1940s highlighted the specificity of neuronal connections in the retino-tectal pathway. These classical systems-based approaches culminated in the 1990s with the discovery that Eph-ephrin repulsive interactions were involved in topographical mapping. In marked contrast, it was the cloning of the odorant receptor family that quickly led to a better understanding of axon targeting in the olfactory system. The last 10 years have seen the olfactory pathway rise in prominence as a model system for axon guidance. Once considered to be experimentally intractable, it is now providing a wealth of information on all aspects of axon guidance and targeting with implications not only for our understanding of these mechanisms in the olfactory system but also in other regions of the nervous system.

Secretory pathway of trypanosomatid parasites

The Trypanosomatidae comprise a large group of parasitic protozoa, some of which cause important diseases in humans. These include Tryanosoma brucei (the causative agent of African sleeping sickness and nagana in cattle), Trypanosoma cruzi (the causative agent of Chagas' disease in Central and South America), and Leishmania spp. (the causative agent of visceral and [muco]cutaneous leishmaniasis throughout the tropics and subtropics). The cell surfaces of these parasites are covered in complex protein- or carbohydrate-rich coats that are required for parasite survival and infectivity in their respective insect vectors and mammalian hosts. These molecules are assembled in the secretory pathway. Recent advances in the genetic manipulation of these parasites as well as progress with the parasite genome projects has greatly advanced our understanding of processes that underlie secretory transport in trypanosomatids. This article provides an overview of the organization of the trypanosomatid secretory pathway and connections that exist with endocytic organelles and multiple lytic and storage vacuoles. A number of the molecular components that are required for vesicular transport have been identified, as have some of the sorting signals that direct proteins to the cell surface or organelles it? the endosome-vacuole system. Finally, the subcellular organization of the major glycosylation pathways in these parasites is reviewed. Studies on these highly divergent eukaryotes provide important insights into the molecular processes underlying secretory transport that arose very early in eukaryotic evolution. They also reveal unusual or novel aspects of secretory), transport and protein glycosylation that may be exploited in developing new antiparasite drugs.

GPI-anchored proteins are delivered to recycling endosomes via a distinct cdc42-regulated, clathrin-independent pinocytic pathway

Endocytosis of cell-surface proteins via specific pathways is critical for their function. We show that multiple glycosylphosphatidylinositol-anchored proteins (GPI-APs) are endocytosed to the recycling endosomal compartment but not to the Golgi via a nonclathrin, noncaveolae mediated pathway. GPI anchoring is a positive signal for internalization into rab5-independent tubular-vesicular endosomes also responsible for a major fraction of fluid-phase uptake; molecules merely lacking cytoplasmic extensions are not included. Unlike the internalization of detergent-resistant membrane (DRM)-associated interleukin 2 receptor, endocytosis of DRM-associated GPI-APs is unaffected by inhibition of RhoA or dynamin 2 activity. Inhibition of Rho family GTPase cdc42, but not Rac1, reduces fluid-phase uptake and redistributes GPI-APs to the clathrin-mediated pathway. These results describe a distinct constitutive pinocytic pathway, specifically regulated by cdc42.

A genomewide survey of developmentally relevant genes in Ciona intestinalis - V. Genes for receptor tyrosine kinase pathway and Notch signaling pathway

In the present survey, we identified most of the genes involved in the receptor tyrosine kinase (RTK), mitogen activated protein kinase (MAPK) and Notch signaling pathways in the draft genome sequence of Ciona intestinalis, a basal chordate. Compared to vertebrates, most of the genes found in the Ciona genome had fewer paralogues, although several genes including ephrin, Eph and fringe appeared to have multiplied or duplicated independently in the ascidian genome. In contrast, some genes including kit/flt, PDGF and Trk receptor tyrosine kinases were not found in the present survey, suggesting that these genes are innovations in the vertebrate lineage or lost in the ascidian lineage. The gene set identified in the present analysis provides an insight into genes for the RTK, MAPK and Notch signaling pathways in the ancient chordate genome and thereby how chordates evolved these signaling pathway.

Rab23, a negative regulator of hedgehog signaling, localizes to the plasma membrane and the endocytic pathway

The regulation of hedgehog signaling by vesicular trafficking was exemplified by the finding that Rab23, a Rab-GTPase vesicular transport protein, is mutated in open brain mice. In this study, the localization of Rab23 was analyzed by light and immunoelectron microscopy after expression of wild-type (Rab23-GFP), constitutively active Rab23 (Rab23Q68L-GFP), and inactive Rab23 (Rab23S23N-GFP) in a range of mammalian cell types. Rab23-GFP and Rab23Q68L-GFP were predominantly localized to the plasma membrane but were also associated with intracellular vesicular structures, whereas Rab23S23N-GFP was predominantly cytosolic. Vesicular Rab23-GFP colocalized with Rab5Q79L and internalized transferrin-biotin, but not with a marker of the late endosome or the Golgi complex. To investigate Rab23 with respect to members of the hedgehog signaling pathway, Rab23-GFP was coexpressed with either patched or smoothened. Patched colocalized with intracellular Rab23-GFP but smoothened did not. Analysis of patched distribution by light and immunoelectron microscopy revealed it is primarily localized to endosomal elements, including transferrin receptor-positive early endosomes and putative endosome carrier vesicles and, to a lesser extent, with LBPA-positive late endosomes, but was excluded from the plasma membrane. Neither patched or smoothened distribution was altered in the presence of wild-type nor mutant Rab23-GFP, suggesting that despite the endosomal colocalization of Rab23 and patched, it is likely that Rab23 acts more distally in regulating hedgehog signaling.

Annexin II regulates multivesicular endosome biogenesis in the degradation pathway of animal cells

Proteins of the annexin family are believed to be involved in membrane-related processes, but their precise functions remain unclear. Here, we have made use of several experimental approaches, including pathological conditions, RNA interference and in vitro transport assays, to study the function of annexin II in the endocytic pathway. We find that annexin II is required for the biogenesis of multivesicular transport intermediates destined for late endosomes, by regulating budding from early endosomes-but not the membrane invagination process. Hence, the protein appears to be a necessary component of the machinery controlling endosomal membrane dynamics and multivesicular endosome biogenesis. We also find that annexin II interacts with cholesterol and that its subcellular distribution is modulated by the subcellular distribution of cholesterol, including in cells from patients with the cholesterol-storage disorder Niemann-Pick C. We conclude that annexin II forms cholesterol-containing platforms on early endosomal membranes, and that these platforms regulate the onset of the degradation pathway in animal cells.

Translation termination and protein folding pathway genes are not correlated in gastric cancer

Background: The eukaryotic release factor 3 (eRF3) has been shown to affect both tubulin and actin cytoskeleton, suggesting a role in cytoskeleton assembly, mitotic spindle formation and chromosome segregation. Also, direct interactions between eRF3 and subunits of the cytosolic chaperonin CCT have been described. Moreover, both eRF3a and CCT subunits have been described to be up-regulated in cancer tissues. Our aim was to evaluate the hypothesis that eRF3 expression levels are correlated with the expression of genes encoding proteins involved in the tubulin folding pathways. Methods: Relative expression levels of eRF1, eRF3a/GSPT1, PFDN4, CCT2, CCT4, and TBCA genes in tumour samples relative to their adjacent normal tissues were investigated using real time-polymerase chain reaction in 20 gastric cancer patients. Results: The expression levels of eRF3a/GSPT1 were not correlated with the expression levels of the other genes studied. However, significant correlations were detected between the other genes, both within intestinal and diffuse type tumours. Conclusions: eRF3a/GSPT1 expression at the mRNA level is independent from both cell translation rates and from the expression of the genes involved in tubulin-folding pathways. The differences in the patterns of expression of the genes studied support the hypothesis of genetically independent pathways in the origin of intestinal and diffuse type gastric tumours.

Alright: a distinctive pathway of change from the 18th century to the present day

The origins of the vast majority of the words we use in contemporary English go back as far as Old or Middle English. In contrast, alright and all right in their present-day application appear to be the result of a more recent evolution, as there is no evidence of their use, not even in the two-word form, in the published fiction before the 18th century. Furthermore, there are not in the research literature, at least to my knowledge, any previous linguistic studies on this specific subject matter. The present article is simply an attempt to describe the various processes of diachronic change that brought about the emergence of alright.

Cholesterol 24S-Hydroxylase overexpression inhibits the liver X receptor (LXR) pathway by activating small guanosine triphosphate-binding proteins (sGTPases) in neuronal cells

The neuronal-specific cholesterol 24S-hydroxylase (CYP46A1) is important for brain cholesterol elimination. Cyp46a1 null mice exhibit severe deficiencies in learning and hippocampal long-term potentiation, suggested to be caused by a decrease in isoprenoid intermediates of the mevalonate pathway. Conversely, transgenic mice overexpressing CYP46A1 show an improved cognitive function. These results raised the question of whether CYP46A1 expression can modulate the activity of proteins that are crucial for neuronal function, namely of isoprenylated small guanosine triphosphate-binding proteins (sGTPases). Our results show that CYP46A1 overexpression in SH-SY5Y neuroblastoma cells and in primary cultures of rat cortical neurons leads to an increase in 3-hydroxy-3-methyl-glutaryl-CoA reductase activity and to an overall increase in membrane levels of RhoA, Rac1, Cdc42 and Rab8. This increase is accompanied by a specific increase in RhoA activation. Interestingly, treatment with lovastatin or a geranylgeranyltransferase-I inhibitor abolished the CYP46A1 effect. The CYP46A1-mediated increase in sGTPases membrane abundance was confirmed in vivo, in membrane fractions obtained from transgenic mice overexpressing this enzyme. Moreover, CYP46A1 overexpression leads to a decrease in the liver X receptor (LXR) transcriptional activity and in the mRNA levels of ATP-binding cassette transporter 1, sub-family A, member 1 and apolipoprotein E. This effect was abolished by inhibition of prenylation or by co-transfection of a RhoA dominant-negative mutant. Our results suggest a novel regulatory axis in neurons; under conditions of membrane cholesterol reduction by increased CYP46A1 expression, neurons increase isoprenoid synthesis and sGTPase prenylation. This leads to a reduction in LXR activity, and consequently to a decrease in the expression of LXR target genes.

Thermodynamic pathway for the formation of SnSe and SnSe2 polycrystalline thin films by selenization of metal precursors

In this work, tin selenide thin films (SnSex) were grown on soda lime glass substrates by selenization of dc magnetron sputtered Sn metallic precursors. Selenization was performed at maximum temperatures in the range 300 °C to 570 °C. The thickness and the composition of the films were analysed using step profilometry and energy dispersive spectroscopy, respectively. The films were structurally and optically investigated by X-ray diffraction, Raman spectroscopy and optical transmittance and reflectance measurements. X-Ray diffraction patterns suggest that for temperatures between 300 °C and 470 °C, the films are composed of the hexagonal-SnSe2 phase. By increasing the temperature, the films selenized at maximum temperatures of 530 °C and 570 °C show orthorhombic-SnSe as the dominant phase with a preferential crystal orientation along the (400) crystallographic plane. Raman scattering analysis allowed the assignment of peaks at 119 cm−1 and 185 cm−1 to the hexagonal-SnSe2 phase and those at 108 cm−1, 130 cm−1 and 150 cm−1 to the orthorhombic-SnSe phase. All samples presented traces of condensed amorphous Se with a characteristic Raman peak located at 255 cm−1. From optical measurements, the estimated band gap energies for hexagonal-SnSe2 were close to 0.9 eV and 1.7 eV for indirect forbidden and direct transitions, respectively. The samples with the dominant orthorhombic-SnSe phase presented estimated band gap energies of 0.95 eV and 1.15 eV for indirect allowed and direct allowed transitions, respectively.

A checklist for patient safety rounds at the care pathway level

Objective - To define a checklist that can be used to assess the performance of a department and evaluate the implementation of quality management (QM) activities across departments or pathways in acute care hospitals. Design - We developed and tested a checklist for the assessment of QM activities at department level in a cross-sectional study using on-site visits by trained external auditors. Setting and Participants - A sample of 292 hospital departments of 74 acute care hospitals across seven European countries. In every hospital, four departments for the conditions: acute myocardial infarction (AMI), stroke, hip fracture and deliveries participated. Main outcome measures - Four measures of QM activities were evaluated at care pathway level focusing on specialized expertise and responsibility (SER), evidence-based organization of pathways (EBOP), patient safety strategies and clinical review (CR). Results - Participating departments attained mean values on the various scales between 1.2 and 3.7. The theoretical range was 0-4. Three of the four QM measures are identical for the four conditions, whereas one scale (EBOP) has condition-specific items. Correlations showed that every factor was related, but also distinct, and added to the overall picture of QM at pathway level. Conclusion - The newly developed checklist can be used across various types of departments and pathways in acute care hospitals like AMI, deliveries, stroke and hip fracture. The anticipated users of the checklist are internal (e.g. peers within the hospital and hospital executive board) and external auditors (e.g. healthcare inspectorate, professional or patient organizations).

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Interoperability frameworks for competencies and learning outcomes: databases vs ontologies

The changes introduced into the European Higher Education Area (EHEA) by the Bologna Process, together with renewed pedagogical and methodological practices, have created a new teaching-learning paradigm: Student-Centred Learning. In addition, the last few years have been characterized by the application of Information Technologies, especially the Semantic Web, not only to the teaching-learning process, but also to administrative processes within learning institutions. On one hand, the aim of this study was to present a model for identifying and classifying Competencies and Learning Outcomes and, on the other hand, the computer applications of the information management model were developed, namely a relational Database and an Ontology.