Expanding the Disease Network of Glioblastoma Multiforme via Topological Analysis.

Glioblastoma multiforme (GBM), a grade IV glioma, is a challenging disease for patients and clinicians, with an extremely poor prognosis. These tumours manifest a high molecular heterogeneity, with limited therapeutic options for patients. Since GBM is a rare disease, sufficient statistically strong evidence is often not available to explore the roles of lesser-known GBM proteins. We present a network-based approach using centrality measures to explore some key, topologically strategic proteins for the analysis of GBM. Since network-based analyses are sensitive to changes in network topology, we analysed nine different GBM networks, and show that small but well-curated networks consistently highlight a set of proteins, indicating their likely involvement in the disease. We propose 18 novel candidates which, based on differential expression, mutation analysis, and survival analysis, indicate that they may play a role in GBM progression. These should be investigated further for their functional roles in GBM, their clinical prognostic relevance, and their potential as therapeutic targets.

Construction and contextualization approaches for protein-protein interaction networks.

Protein-protein interaction network (PPIN) analysis is a widely used method to study the contextual role of proteins of interest, to predict novel disease genes, disease or functional modules, and to identify novel drug targets. PPIN-based analysis uses both generic and context-specific networks. Multiple contextualization methodologies have been described, such as shortest-path algorithms, neighborhood-based methods, and diffusion/propagation algorithms. This review discusses these methods, provides intuitive representations of PPIN contextualization, and also examines how the quality of such context-specific networks could be improved by considering additional sources of evidence. As a heuristic, we observe that tasks such as identifying disease genes, drug targets, and protein complexes should consider local neighborhoods, while uncovering disease mechanisms and discovering disease-pathways would gain from diffusion-based construction.

L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness.

BACKGROUND: Metastasis is the predominant cause for cancer morbidity and mortality accounting for approximatively 90% of cancer deaths. The actin-bundling protein L-plastin has been proposed as a metastatic marker and phosphorylation on its residue Ser5 is known to increase its actin-bundling activity. We recently showed that activation of the ERK/MAPK signalling pathway leads to L-plastin Ser5 phosphorylation and that the downstream kinases RSK1 and RSK2 are able to directly phosphorylate Ser5. Here we investigate the involvement of the PI3K pathway in L-plastin Ser5 phosphorylation and the functional effect of this phosphorylation event in breast cancer cells. METHODS: To unravel the signal transduction network upstream of L-plastin Ser5 phosphorylation, we performed computational modelling based on immunoblot analysis data, followed by experimental validation through inhibition/overexpression studies and in vitro kinase assays. To assess the functional impact of L-plastin expression/Ser5 phosphorylation in breast cancer cells, we either silenced L-plastin in cell lines initially expressing endogenous L-plastin or neoexpressed L-plastin wild type and phosphovariants in cell lines devoid of endogenous L-plastin. The established cell lines were used for cell biology experiments and confocal microscopy analysis. RESULTS: Our modelling approach revealed that, in addition to the ERK/MAPK pathway and depending on the cellular context, the PI3K pathway contributes to L-plastin Ser5 phosphorylation through its downstream kinase SGK3. The results of the transwell invasion/migration assays showed that shRNA-mediated knockdown of L-plastin in BT-20 or HCC38 cells significantly reduced cell invasion, whereas stable expression of the phosphomimetic L-plastin Ser5Glu variant led to increased migration and invasion of BT-549 and MDA-MB-231 cells. Finally, confocal image analysis combined with zymography experiments and gelatin degradation assays provided evidence that L-plastin Ser5 phosphorylation promotes L-plastin recruitment to invadopodia, MMP-9 activity and concomitant extracellular matrix degradation. CONCLUSION: Altogether, our results demonstrate that L-plastin Ser5 phosphorylation increases breast cancer cell invasiveness. Being a downstream molecule of both ERK/MAPK and PI3K/SGK pathways, L-plastin is proposed here as a potential target for therapeutic approaches that are aimed at blocking dysregulated signalling outcome of both pathways and, thus, at impairing cancer cell invasion and metastasis formation. Video abstract.

Degree Adjusted Large-Scale Network Analysis Reveals Novel Putative Metabolic Disease Genes.

A large percentage of the global population is currently afflicted by metabolic diseases (MD), and the incidence is likely to double in the next decades. MD associated co-morbidities such as non-alcoholic fatty liver disease (NAFLD) and cardiomyopathy contribute significantly to impaired health. MD are complex, polygenic, with many genes involved in its aetiology. A popular approach to investigate genetic contributions to disease aetiology is biological network analysis. However, data dependence introduces a bias (noise, false positives, over-publication) in the outcome. While several approaches have been proposed to overcome these biases, many of them have constraints, including data integration issues, dependence on arbitrary parameters, database dependent outcomes, and computational complexity. Network topology is also a critical factor affecting the outcomes. Here, we propose a simple, parameter-free method, that takes into account database dependence and network topology, to identify central genes in the MD network. Among them, we infer novel candidates that have not yet been annotated as MD genes and show their relevance by highlighting their differential expression in public datasets and carefully examining the literature. The method contributes to uncovering connections in the MD mechanisms and highlights several candidates for in-depth study of their contribution to MD and its co-morbidities.

Topological network measures for drug repositioning.

Drug repositioning has received increased attention since the past decade as several blockbuster drugs have come out of repositioning. Computational approaches are significantly contributing to these efforts, of which, network-based methods play a key role. Various structural (topological) network measures have thereby contributed to uncovering unintuitive functional relationships and repositioning candidates in drug-disease and other networks. This review gives a broad overview of the topic, and offers perspectives on the application of topological measures for network analysis. It also discusses unexplored measures, and draws attention to a wider scope of application efforts, especially in drug repositioning.

Systemic network analysis identifies XIAP and IκBα as potential drug targets in TRAIL resistant BRAF mutated melanoma.

Metastatic melanoma remains a life-threatening disease because most tumors develop resistance to targeted kinase inhibitors thereby regaining tumorigenic capacity. We show the 2nd generation hexavalent TRAIL receptor-targeted agonist IZI1551 to induce pronounced apoptotic cell death in mutBRAF melanoma cells. Aiming to identify molecular changes that may confer IZI1551 resistance we combined Dynamic Bayesian Network modelling with a sophisticated regularization strategy resulting in sparse and context-sensitive networks and show the performance of this strategy in the detection of cell line-specific deregulations of a signalling network. Comparing IZI1551-sensitive to IZI1551-resistant melanoma cells the model accurately and correctly predicted activation of NFκB in concert with upregulation of the anti-apoptotic protein XIAP as the key mediator of IZI1551 resistance. Thus, the incorporation of multiple regularization functions in logical network optimization may provide a promising avenue to assess the effects of drug combinations and to identify responders to selected combination therapies.

Using Regularization to Infer Cell Line Specificity in Logical Network Models of Signaling Pathways.

Understanding the functional properties of cells of different origins is a long-standing challenge of personalized medicine. Especially in cancer, the high heterogeneity observed in patients slows down the development of effective cures. The molecular differences between cell types or between healthy and diseased cellular states are usually determined by the wiring of regulatory networks. Understanding these molecular and cellular differences at the systems level would improve patient stratification and facilitate the design of rational intervention strategies. Models of cellular regulatory networks frequently make weak assumptions about the distribution of model parameters across cell types or patients. These assumptions are usually expressed in the form of regularization of the objective function of the optimization problem. We propose a new method of regularization for network models of signaling pathways based on the local density of the inferred parameter values within the parameter space. Our method reduces the complexity of models by creating groups of cell line-specific parameters which can then be optimized together. We demonstrate the use of our method by recovering the correct topology and inferring accurate values of the parameters of a small synthetic model. To show the value of our method in a realistic setting, we re-analyze a recently published phosphoproteomic dataset from a panel of 14 colon cancer cell lines. We conclude that our method efficiently reduces model complexity and helps recovering context-specific regulatory information.

FALCON: a toolbox for the fast contextualization of logical networks.

MOTIVATION: Mathematical modelling of regulatory networks allows for the discovery of knowledge at the system level. However, existing modelling tools are often computation-heavy and do not offer intuitive ways to explore the model, to test hypotheses or to interpret the results biologically. RESULTS: We have developed a computational approach to contextualize logical models of regulatory networks with biological measurements based on a probabilistic description of rule-based interactions between the different molecules. Here, we propose a Matlab toolbox, FALCON, to automatically and efficiently build and contextualize networks, which includes a pipeline for conducting parameter analysis, knockouts and easy and fast model investigation. The contextualized models could then provide qualitative and quantitative information about the network and suggest hypotheses about biological processes. AVAILABILITY AND IMPLEMENTATION: FALCON is freely available for non-commercial users on GitHub under the GPLv3 licence. The toolbox, installation instructions, full documentation and test datasets are available at https://github.com/sysbiolux/FALCON. FALCON runs under Matlab (MathWorks) and requires the Optimization Toolbox. CONTACT: thomas.sauter@uni.lu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Near Full-Length Characterization and Population Dynamics of the Human Immunodeficiency Virus Type I Circulating Recombinant Form 42 (CRF42_BF) in Luxembourg.

A new recombinant form representing a mosaic of HIV-1 subtype B and F1 and designated as CRF42_BF was identified in Luxembourg. We confirmed the inedited nature of CRF42_BF by near full-length genome characterization and retrieved a possible ancestor originating from Brazil. The demographic history of CRF42_BF in Luxembourg using Bayesian coalescent-based methods was investigated. The exponential phase of the logistic growth happened in a very short time period of approximately 5 months associated with a high mean rate of population growth of 15.02 new infections per year. However, CRF42_BF was not characterized by either a higher ex vivo replication capacity in peripheral blood mononuclear cells (PBMCs) or a higher ex vivo transmission efficiency from monocyte-derived dendritic cells to PBMCs as compared to B and F1 viruses. These data do not support a high pathogenic potential of CFR42_BF but rather an initial bursting spread of the recombinant probably due to a more favorable transmission route.

Rescue of HIV-1 long-time archived X4 strains to escape maraviroc.

Entry of Human Immunodeficiency Virus type 1 (HIV-1) into target cells is mediated by the CD4 receptor and a coreceptor, CCR5 or CXCR4. Maraviroc interferes with HIV entry by binding the CCR5 coreceptor. Virological failure to maraviroc-containing regimens can occur through the emergence of resistance, or through tropism evolution and broadened coreceptor usage. In the latter case, the physiological relevance of minority strains is a major concern. Here we report a retrospective analysis of coreceptor-usage and evolution based on 454-ultra-deep-sequencing of plasma and Peripheral Blood Mononuclear Cell (PBMC)-derived envelope V3-loops, accounting for coreceptor usage, from a patient who failed a maraviroc-containing regimen through the emergence of X4 strains. The X4 maraviroc-escape variant resulted from recombination between a long time archived proviral sequence from 2003 (5'-portion, including the V3-loop) and the dominant R5 strains circulating in plasma at the time of maraviroc-treatment initiation (3'-portion). Phylogenetic analyses and BEAST modeling highlighted that an early diverse viral quasispecies underwent a severe bottleneck following reinitiation of HAART and repeated IL-2 cycles between 1999 and 2001, leading to the transient outgrowth and archiving of one highly homogeneous X4 population from plasma, and to the expansion in plasma of one PBMC-derived R5 strain. Under maraviroc selective pressure, the early, no longer detectable X4 strains archived in PBMC were partially rescued to provide X4-determinants to the main circulating strain.

Concentration and diversity of noroviruses detected in Luxembourg wastewaters in 2008-2009.

Noroviruses (NoV) in 78 wastewater samples from Luxembourg were quantified, cloned, and sequenced in 2008-2009. The concentrations of NoV genogroup II and the relative occurrences of certain genotypes changed significantly during the winter season. NoV genogroup I was frequently detected by real-time reverse transcription-PCR (RT-PCR), albeit at 30-fold lower concentrations than for genogroup II, hampering attempts to assess overall genetic diversity by the cloning/sequencing approach.

Reassortant low-pathogenic avian influenza H5N2 viruses in African wild birds.

To investigate the presence and persistence of avian influenza virus in African birds, we monitored avian influenza in wild and domestic birds in two different regions in Nigeria. We found low-pathogenic avian influenza (LPAI) H5N2 viruses in three spur-winged geese (Plectropterus gambensis) in the Hadejia-Nguru wetlands. Phylogenetic analyses revealed that all of the genes, except the non-structural (NS) genes, of the LPAI H5N2 viruses were more closely related to genes recently found in wild and domestic birds in Europe. The NS genes formed a sister group to South African and Zambian NS genes. This suggested that the Nigerian LPAI H5N2 viruses found in wild birds were reassortants exhibiting an NS gene that circulated for at least 7 years in African birds and is part of the African influenza gene pool, and genes that were more recently introduced into Africa from Eurasia, most probably by intercontinental migratory birds. Interestingly the haemagglutinin and neuraminidase genes formed a sister branch to highly pathogenic avian influenza (HPAI) H5N2 strains found in the same wild bird species in the same wetland only 1 year earlier. However, they were not the closest known relatives of each other, suggesting that their presence in the wetland resulted from two separate introductions. The presence of LPAI H5N2 in wild birds in the Hadejia-Nguru wetlands, where wild birds and poultry occasionally mix, provides ample opportunity for infection across species boundaries, with the potential risk of generating HPAI viruses after extensive circulation in poultry.

A multiplex TaqMan PCR assay for the detection of measles and rubella virus.

Measles and rubella virus cause fever/rash diseases that are difficult to differentiate clinically. Both viruses can be detected in the same clinical specimens and are propagated on the same cell cultures. A single-tube multiplex TaqMan assay is described for the simultaneous and rapid detection of the full spectrum of known genetic variants. The performance of the assay is similar to a conventional nested PCR and generates cDNA with random primers which can be used directly for virus genotyping.

Genetic characterization of HPAI (H5N1) viruses from poultry and wild vultures, Burkina Faso.

Genetic analysis of highly pathogenic avian influenza (H5N1) viruses from poultry and hooded vultures in Burkina Faso shows that these viruses belong to 1 of 3 sublineages initially found in Nigeria and later in other African countries. Hooded vultures could potentially be vectors or sentinels of influenza subtype H5N1, as are cats and swans elsewhere.

Co-circulation of multiple rubella virus strains in Belarus forming novel genetic groups within clade 1.

Although the WHO recommends a comprehensive genetic characterization, little is known about circulating strains and genotypes of rubella virus (RUBV) for many European countries. Studies investigating the genetic diversity of a sizeable number of strains from a certain location are rare. This study presents the first molecular characterization of isolates from Belarus. Throat swab and urine samples were collected between 2004 and 2005 from patients presenting in two infectious disease hospitals and three outpatient clinics in and around Minsk. In total, 14 isolates were obtained from this clinical material. Phylogenetic analysis of the E1 gene sequence of these isolates showed that three distinct groups of RUBV strains co-circulated. One group of isolates was assigned to genotype 1E, whereas the other two did not group with any of the recognized genotypes but grouped with a strain belonging to the provisional genotype 1g. Detailed analysis showed that the group comprising 1g strains also contained sequences formerly attributed to genotype 1B and could be divided into four subgroups, one of which might represent a putative novel provisional genotype of clade 1. These findings show that three distinct strains with limited variability are present in Belarus, suggesting independent introductory events. As there currently seem to be misattributions of strains to genotypes and unclear phylogenetic relationships, criteria for genotyping of RUBV should be clarified further.