The interaction of human pathogenic arena viruses with the host cell

SummaryResearch projects presented in this thesis aimed to investigate two major aspects of the arenaviruses life cycle in the host cell: viral entry and the biosynthesis of the viral envelope glycoprotein.Old World arenaviruses (OWAV), such as Lassa virus (LASV) and lymphocytic choriomeningitis virus (LCMV), attach to the cell by binding to their receptor, alpha-dystroglycan. Virions are then internalized by a largely unknown pathway of endocytosis and delivered to the late endosome/lysosome where fusion occurs at low pH. In the major project of my thesis, we sought to identify cellular factors involved in OWAV cell entry. Our work indicates that OWAV cell entry requires microtubular transport and a functional multivesicular body (MVB) compartment. Infection indeed depends on phosphatidyl inositol 3-kinase (PI3K) activity and lysobisphosphatidic acid (LBPA), a lipid found in membranes of intraluminal vesicles (ILVs) of the MVB. We further found a requirement of factors that are part of the endosomal sorting complex required for transport (ESCRT), involved in the formation of ILVs. This suggests an ESCRT-mediated sorting of virus- receptor complex during the entry process.During viral replication, biosynthesis of viral glycoprotein takes place in the endoplasmic reticulum (ER) of the host cell. When protein load exceeds the folding capacity of the ER, the accumulation of unfolded proteins is sensed by three ER resident proteins, activating transcription factor 6 (ATF6), inositol-requiring enzyme 1 (IRE1) and PKR-like ER kinase (PERK), whose signaling induces the cellular unfolded protein response (UPR). Our results indicate that acute LCMV infection transiently induces the activation of the ATF6 branch of the UPR, whereas the PERK, and IRE1 axis of UPR are neither triggered nor blocked during infection. Our data also demonstrate that activation of ATF6 pathway is required for optimal viral replication during acute infection.The formation of the mature, fusion-active form of arenaviruses glycoproteins requires proteolytic cleavage mediated by the cellular protease subtilisin kexin isozyme-1 (SKI-l)/site-l protease (SIP). We show that targeting the SKI-1/S1P enzymatic activity with specific inhibitors is a powerful strategy to block arenaviruses productive infection. Moreover, characterization of protease function highlights differences in processing between cellular and viral substrates, opening new possibilities in term of drug development against human pathogenic arenaviruses.RésuméLes projets de recherche présentés dans cette thèse visaient à étudier deux aspects du cycle de vie des arenavirus: l'entrée du virus dans la cellule hôte et la biosynthèse de la glycoprotéine durant la réplication virale.Les arenavirus du vieux monde (OWAV), tels que le virus de Lassa (LASV) et le virus de la chorioméningite lymphocytaire (LCMV) s'attachent à la cellule hôte en se liant à leur récepteur, l'alpha-dystroglycane. Les virions sont ensuite intemalisés par une voie d'endocytose inconnue et livrés à l'endosome tardif/lysosome, où le pH acide permet la fusion entre l'enveloppe virale et la membrane du compartiment. Le projet principal de ma thèse consistait à identifier les facteurs cellulaires impliqués dans l'entrée des OWAV dans la cellule hôte. Nos résultats indiquent que l'entrée des OWAV nécessite le transport microtubulaire et la présence d'un corps multivésiculaire (MVB) fonctionnel. L'infection dépend en effet de l'activité de phosphatidyl inositol 3-kinase (PI3K) et de lysobisphosphatidic acid (LBPA), un lipide présent dans les membranes des vésicules intraluminales (ILVs) du MVB. Nous avons également trouvé l'implication de facteurs constituant l'endosomal sorting complex required for sorting (ESCRT) qui joue un rôle dans la formation des ILVs. Ces donnés suggèrent l'incorporation du complexe virus-récepteur dans des ILVs durant le processus d'entrée.Lors de la réplication virale, la biosynthèse de la glycoprotéine virale a lieu dans le réticulum endoplasmique (ER) de la cellule hôte. Lorsque la charge de protéines nouvellement synthétisées excède la capacité de pliage des protéines dans le ER, l'accumulation de protéines mal pliées est détectée par trois facteurs: activating transcription factor 6 (ATF6), inositol-requiring enzyme 1 (IRE1) et PKR-like ER kinase (PERK). Leur signalisation constitue la réponse cellulaire face aux protéines mal pliées (UPR). Nos résultats montrent que l'infection aiguë avec LCMV induit transitoirement l'activation de la voie de signalisation ATF6 alors que les axes PERK et IRE1 de l'UPR ne sont ni induits ni bloqués pendant l'infection. Nos données prouvent également que l'activation de la voie ATF6 est nécessaire à une réplication virale optimale lors de l'infection aiguë avec LCMV.La maturation des glycoprotéines des arenavirus nécessite un clivage protéolytique par la protéase cellulaire subtilisin kexin isozyme-1 (SKI-l)/site-l protease (SIP). Nous avons démontré que le ciblage de l'activité enzymatique de SKI-1/SIΡ avec des inhibiteurs spécifiques est une stratégie prometteuse pour bloquer l'infection par les arenavirus. La caractérisation du mécanisme d'action de la protéase a, par ailleurs, révélé des différences au niveau du clivage entre les substrats cellulaires et viraux, ce qui ouvre de nouvelles perspectives en terme de développement de médicaments contre les arenavirus pathogènes pour l'homme.

Coronary MR angiography: comparison of quantitative and qualitative data from four techniques.

OBJECTIVE: The optimal coronary MR angiography sequence has yet to be determined. We sought to quantitatively and qualitatively compare four coronary MR angiography sequences. SUBJECTS AND METHODS. Free-breathing coronary MR angiography was performed in 12 patients using four imaging sequences (turbo field-echo, fast spin-echo, balanced fast field-echo, and spiral turbo field-echo). Quantitative comparisons, including signal-to-noise ratio, contrast-to-noise ratio, vessel diameter, and vessel sharpness, were performed using a semiautomated analysis tool. Accuracy for detection of hemodynamically significant disease (> 50%) was assessed in comparison with radiographic coronary angiography. RESULTS: Signal-to-noise and contrast-to-noise ratios were markedly increased using the spiral (25.7 +/- 5.7 and 15.2 +/- 3.9) and balanced fast field-echo (23.5 +/- 11.7 and 14.4 +/- 8.1) sequences compared with the turbo field-echo (12.5 +/- 2.7 and 8.3 +/- 2.6) sequence (p < 0.05). Vessel diameter was smaller with the spiral sequence (2.6 +/- 0.5 mm) than with the other techniques (turbo field-echo, 3.0 +/- 0.5 mm, p = 0.6; balanced fast field-echo, 3.1 +/- 0.5 mm, p < 0.01; fast spin-echo, 3.1 +/- 0.5 mm, p < 0.01). Vessel sharpness was highest with the balanced fast field-echo sequence (61.6% +/- 8.5% compared with turbo field-echo, 44.0% +/- 6.6%; spiral, 44.7% +/- 6.5%; fast spin-echo, 18.4% +/- 6.7%; p < 0.001). The overall accuracies of the sequences were similar (range, 74% for turbo field-echo, 79% for spiral). Scanning time for the fast spin-echo sequences was longest (10.5 +/- 0.6 min), and for the spiral acquisitions was shortest (5.2 +/- 0.3 min). CONCLUSION: Advantages in signal-to-noise and contrast-to-noise ratios, vessel sharpness, and the qualitative results appear to favor spiral and balanced fast field-echo coronary MR angiography sequences, although subjective accuracy for the detection of coronary artery disease was similar to that of other sequences.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Selecting control genes for RT-QPCR using public microarray data.

Background: Gene expression analysis has emerged as a major biological research area, with real-time quantitative reverse transcription PCR (RT-QPCR) being one of the most accurate and widely used techniques for expression profiling of selected genes. In order to obtain results that are comparable across assays, a stable normalization strategy is required. In general, the normalization of PCR measurements between different samples uses one to several control genes (e. g. housekeeping genes), from which a baseline reference level is constructed. Thus, the choice of the control genes is of utmost importance, yet there is not a generally accepted standard technique for screening a large number of candidates and identifying the best ones. Results: We propose a novel approach for scoring and ranking candidate genes for their suitability as control genes. Our approach relies on publicly available microarray data and allows the combination of multiple data sets originating from different platforms and/or representing different pathologies. The use of microarray data allows the screening of tens of thousands of genes, producing very comprehensive lists of candidates. We also provide two lists of candidate control genes: one which is breast cancer-specific and one with more general applicability. Two genes from the breast cancer list which had not been previously used as control genes are identified and validated by RT-QPCR. Open source R functions are available at http://www.isrec.isb-sib.ch/similar to vpopovic/research/ Conclusion: We proposed a new method for identifying candidate control genes for RT-QPCR which was able to rank thousands of genes according to some predefined suitability criteria and we applied it to the case of breast cancer. We also empirically showed that translating the results from microarray to PCR platform was achievable.

HIV and STI surveillance in Northern Ireland 2010: An analysis of data for the calendar year 2009

This annual analysis of data provides an overview of HIV and STI epidemiology in Northern Ireland for the calendar year 2009. Information from a variety of sources is collated and analysed in detail, while any evident trends over time are highlightedwithgraphs and tables. As well as a general summary of STI diagnoses and a number of overall conclusions, the report looks specifically at each of the following STIs: chlamydia, gonorrhoea, genital herpes, genital warts, syphilis, lymphogranuloma venereum (LGV) and HIV.

Inca expansion and parasitism in the Lluta Valley: preliminary data

Assessing the impact of cultural change on parasitism has been a central goal in archaeoparasitology. The influence of civilization and the development of empires on parasitism has not been evaluated. Presented here is a preliminary analysis of the change in human parasitism associated with the Inca conquest of the Lluta Valley in Northern Chile. Changes in parasite prevalence are described. It can be seen that the change in life imposed on the inhabitants of the Lluta Valley by the Incas caused an increase in parasitism.

Modular analysis of gene expression data with R.

SUMMARY: Large sets of data, such as expression profiles from many samples, require analytic tools to reduce their complexity. The Iterative Signature Algorithm (ISA) is a biclustering algorithm. It was designed to decompose a large set of data into so-called 'modules'. In the context of gene expression data, these modules consist of subsets of genes that exhibit a coherent expression profile only over a subset of microarray experiments. Genes and arrays may be attributed to multiple modules and the level of required coherence can be varied resulting in different 'resolutions' of the modular mapping. In this short note, we introduce two BioConductor software packages written in GNU R: The isa2 package includes an optimized implementation of the ISA and the eisa package provides a convenient interface to run the ISA, visualize its output and put the biclusters into biological context. Potential users of these packages are all R and BioConductor users dealing with tabular (e.g. gene expression) data. AVAILABILITY: http://www.unil.ch/cbg/ISA CONTACT: sven.bergmann@unil.ch

Implementació d'un esquema criptogràfic per a la gestió segura d'historials mèdics a través d'una xarxa de comunicacions

Aquest projecte es proposa dissenyar i implementar un sistema de gestió d'historials mèdics per a ser usat remotament a través d'una xarxa de comunicacions, amb un èmfasi principal enl'assoliment d'un nivell de seguretat considerat alt.