Integration of gene expression data with prior knowledge for network analysis and validation

<p>Abstract</p> <p>Background</p> <p>Reconstruction of protein-protein interaction or metabolic networks based on expression data often involves in silico predictions, while on the other hand, there are unspecific networks of in vivo interactions derived from knowledge bases.</p> <p>We analyze networks designed to come as close as possible to data measured in vivo, both with respect to the set of nodes which were taken to be expressed in experiment as well as with respect to the interactions between them which were taken from manually curated databases</p> <p>Results</p> <p>A signaling network derived from the TRANSPATH database and a metabolic network derived from KEGG LIGAND are each filtered onto expression data from breast cancer (SAGE) considering different levels of restrictiveness in edge and vertex selection.</p> <p>We perform several validation steps, in particular we define pathway over-representation tests based on refined null models to recover functional modules. The prominent role of the spindle checkpoint-related pathways in breast cancer is exhibited. High-ranking key nodes cluster in functional groups retrieved from literature. Results are consistent between several functional and topological analyses and between signaling and metabolic aspects.</p> <p>Conclusions</p> <p>This construction involved as a crucial step the passage to a mammalian protein identifier format as well as to a reaction-based semantics of metabolism. This yielded good connectivity but also led to the need to perform benchmark tests to exclude loss of essential information. Such validation, albeit tedious due to limitations of existing methods, turned out to be informative, and in particular provided biological insights as well as information on the degrees of coherence of the networks despite fragmentation of experimental data.</p> <p>Key node analysis exploited the networks for potentially interesting proteins in view of drug target prediction.</p

The relevance of nanoscale biological fragments for ice nucleation in clouds

Most studies of the role of biological entities as atmospheric ice-nucleating particles have focused on relatively rare supermicron particles such as bacterial cells, fungal spores and pollen grains. However, it is not clear that there are sufficient numbers of these particles in the atmosphere to strongly influence clouds. Here we show that the ice-nucleating activity of a fungus from the ubiquitous genus Fusarium is related to the presence of nanometre-scale particles which are far more numerous, and therefore potentially far more important for cloud glaciation than whole intact spores or hyphae. In addition, we quantify the ice-nucleating activity of nano-ice nucleating particles (nano-INPs) washed off pollen and also show that nano-INPs are present in a soil sample. Based on these results, we suggest that there is a reservoir of biological nano-INPs present in the environment which may, for example, become aerosolised in association with fertile soil dust particles

Interleukin 21 inhibits cancer-mediated FOXP3 induction in naïve human CD4 T cells

IL-21 is known to promote anti-tumour immunity due to its ability to promote T cell responses and counteract Treg-mediated suppression. It has also been shown to limit Treg frequencies during tumour-antigen stimulations. However, whether this represents inhibition of FOXP3 induction in naïve CD4 T cells or curtailed expansion of natural Treg remains unclear. Moreover, whether this effect is maintained in an environment of tumour-derived immunosuppressive factors is not known. Here, we show that in the context of a number of cancers, naïve CD45RA+ CD4 T cells are induced to express high levels of FOXP3, and that FOXP3 expression correlates with inhibition of T cell proliferation. FOXP3 expression was most potently induced by tumours secreting higher levels of total and active TGFβ1 and this induction could be potently counteracted with IL-21, restoring T cell proliferation. We conclude that Treg induction in naïve T cells is a common phenomenon amongst a number of different cancers and that the ability of IL-21 to counteract this effect is further evidence of its promise in cancer therapy

Bayesian statistical modelling of human protein interaction network incorporating protein disorder information

<p>Abstract</p> <p>Background</p> <p>We present a statistical method of analysis of biological networks based on the exponential random graph model, namely p2-model, as opposed to previous descriptive approaches. The model is capable to capture generic and structural properties of a network as emergent from local interdependencies and uses a limited number of parameters. Here, we consider one global parameter capturing the density of edges in the network, and local parameters representing each node's contribution to the formation of edges in the network. The modelling suggests a novel definition of important nodes in the network, namely <it>social</it>, as revealed based on the local <it>sociality </it>parameters of the model. Moreover, the sociality parameters help to reveal organizational principles of the network. An inherent advantage of our approach is the possibility of hypotheses testing: <it>a priori </it>knowledge about biological properties of the nodes can be incorporated into the statistical model to investigate its influence on the structure of the network.</p> <p>Results</p> <p>We applied the statistical modelling to the human protein interaction network obtained with Y2H experiments. Bayesian approach for the estimation of the parameters was employed. We deduced <it>social </it>proteins, essential for the formation of the network, while incorporating into the model information on protein disorder. <it>Intrinsically disordered </it>are proteins which lack a well-defined three-dimensional structure under physiological conditions. We predicted the fold group (ordered or disordered) of proteins in the network from their primary sequences. The network analysis indicated that protein disorder has a positive effect on the connectivity of proteins in the network, but do not fully explains the interactivity.</p> <p>Conclusions</p> <p>The approach opens a perspective to study effects of biological properties of individual entities on the structure of biological networks.</p

Measurement of patients' knowledge of their medication in community pharmacies in Portugal

El objetivo do artículo es determinar el conocimiento de los pacientes sobre sus medicamentos. Estudio observacional descriptivo transversal. El conocimiento se midió mediante un cuestionario válido y fiable (CPM-PT-PT), a los pacientes que acudieron a las farmacias comunitarias participantes en el estudio solicitando uno o varios medicamentos en el Área Metropolitana de Lisboa. Se determinó el conocimiento en sus cuatro dimensiones: objetivo terapéutico, proceso de uso, seguridad y conservación de los medicamentos que el paciente utiliza. Participaron 35 farmacias, obteniéndose 633 pacientes válidos. El 82.5% (IC95%: 79,3%-85,3%) no conocen el medicamento que utilizan. En todos los ítems, hubo un alto porcentaje de pacientes con conocimiento incorrecto, destacando especialmente las precauciones (44,7%). La dimensión que menos conocen los pacientes fue la "seguridad del medicamento" (1,9%). 8 de cada 10 pacientes de la población no conocen el medicamento que utilizan. La mayor carencia de información correcta corresponde a la "seguridad" del medicamento.The scope of this article is to determine patients' knowledge about the medication they take. For this purpose, a cross-sectional, observational and descriptive study was conducted. Knowledge was measured by a valid and reliable questionnaire (CPM-PT-PT), given to the patients attending community pharmacies participating in the study, who had prescriptions for one or more drugs in the Lisbon Metropolitan Area. Knowledge was assessed in four dimensions: therapeutic objective, process of use, safety and maintenance of the medications that the patient takes. Thirty-five pharmacies participated, and 633 valid patients were obtained. Fully 82.5% (95% CI: 79.3% -85.3%) were uninformed about the nature of the drug they use. In all items, there was a high percentage of patients with incorrect knowledge, with emphasis on precautions (44.7%). The dimension that the patients were least aware of was "drug safety" (1.9%). Eight out of 10 patients in the population do not know what drug they use. The highest lack of correct information was with respect to the "safety" of the medication

The study of atmospheric ice-nucleating particles via microfluidically generated droplets

Ice-nucleating particles (INPs) play a significant role in the climate and hydrological cycle by triggering ice formation in supercooled clouds, thereby causing precipitation and affecting cloud lifetimes and their radiative properties. However, despite their importance, INP often comprise only 1 in 10³–10⁶ ambient particles, making it difficult to ascertain and predict their type, source, and concentration. The typical techniques for quantifying INP concentrations tend to be highly labour-intensive, suffer from poor time resolution, or are limited in sensitivity to low concentrations. Here, we present the application of microfluidic devices to the study of atmospheric INPs via the simple and rapid production of monodisperse droplets and their subsequent freezing on a cold stage. This device offers the potential for the testing of INP concentrations in aqueous samples with high sensitivity and high counting statistics. Various INPs were tested for validation of the platform, including mineral dust and biological species, with results compared to literature values. We also describe a methodology for sampling atmospheric aerosol in a manner that minimises sampling biases and which is compatible with the microfluidic device. We present results for INP concentrations in air sampled during two field campaigns: (1) from a rural location in the UK and (2) during the UK’s annual Bonfire Night festival. These initial results will provide a route for deployment of the microfluidic platform for the study and quantification of INPs in upcoming field campaigns around the globe, while providing a benchmark for future lab-on-a-chip-based INP studies

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field