Systems analysis of iron metabolism: the network of iron pools and fluxes

<p>Abstract</p> <p>Background</p> <p>Every cell of the mammalian organism needs iron as trace element in numerous oxido-reductive processes as well as for transport and storage of oxygen. The very versatility of ionic iron makes it a toxic entity which can catalyze the production of radicals that damage vital membranous and macromolecular assemblies in the cell. The mammalian organism maintains therefore a complex regulatory network of iron uptake, excretion and intra-body distribution. Intracellular regulation in different cell types is intertwined with a global hormonal signalling structure. Iron deficiency as well as excess of iron are frequent and serious human disorders. They can affect every cell, but also the organism as a whole.</p> <p>Results</p> <p>Here, we present a kinematic model of the dynamic system of iron pools and fluxes. It is based on ferrokinetic data and chemical measurements in C57BL6 wild-type mice maintained on iron-deficient, iron-adequate, or iron-loaded diet. The tracer iron levels in major tissues and organs (16 compartment) were followed for 28 days. The evaluation resulted in a whole-body model of fractional clearance rates. The analysis permits calculation of absolute flux rates in the steady-state, of iron distribution into different organs, of tracer-accessible pool sizes and of residence times of iron in the different compartments in response to three states of iron-repletion induced by the dietary regime.</p> <p>Conclusions</p> <p>This mathematical model presents a comprehensive physiological picture of mice under three different diets with varying iron contents. The quantitative results reflect systemic properties of iron metabolism: dynamic closedness, hierarchy of time scales, switch-over response and dynamics of iron storage in parenchymal organs.</p> <p>Therefore, we could assess which parameters will change under dietary perturbations and study in quantitative terms when those changes take place.</p

A comprehensive map of the influenza A virus replication cycle

BACKGROUND: Influenza is a common infectious disease caused by influenza viruses. Annual epidemics cause severe illnesses, deaths, and economic loss around the world. To better defend against influenza viral infection, it is essential to understand its mechanisms and associated host responses. Many studies have been conducted to elucidate these mechanisms, however, the overall picture remains incompletely understood. A systematic understanding of influenza viral infection in host cells is needed to facilitate the identification of influential host response mechanisms and potential drug targets. DESCRIPTION: We constructed a comprehensive map of the influenza A virus (‘IAV’) life cycle (‘FluMap’) by undertaking a literature-based, manual curation approach. Based on information obtained from publicly available pathway databases, updated with literature-based information and input from expert virologists and immunologists, FluMap is currently composed of 960 factors (i.e., proteins, mRNAs etc.) and 456 reactions, and is annotated with ~500 papers and curation comments. In addition to detailing the type of molecular interactions, isolate/strain specific data are also available. The FluMap was built with the pathway editor CellDesigner in standard SBML (Systems Biology Markup Language) format and visualized as an SBGN (Systems Biology Graphical Notation) diagram. It is also available as a web service (online map) based on the iPathways+ system to enable community discussion by influenza researchers. We also demonstrate computational network analyses to identify targets using the FluMap. CONCLUSION: The FluMap is a comprehensive pathway map that can serve as a graphically presented knowledge-base and as a platform to analyze functional interactions between IAV and host factors. Publicly available webtools will allow continuous updating to ensure the most reliable representation of the host-virus interaction network. The FluMap is available at http://www.influenza-x.org/flumap/

A complex scenario of tuberculosis transmission is revealed through genetic and epidemiological surveys in Porto

Tuberculosis (TB) incidence is decreasing worldwide and eradication is becoming plausible. In low-incidence countries, intervention on migrant populations is considered one of the most important strategies for elimination. However, such measures are inappropriate in European areas where TB is largely endemic, such as Porto in Portugal. We aim to understand transmission chains in Porto through a genetic characterization of Mycobacterium tuberculosis strains and through a detailed epidemiological evaluation of cases.This work was developed under the scope of the project NORTE-01-0145-FEDER-000013, supported by the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER), and supported by contributions from Iceland, Liechtenstein and Norway through the European Economic Area Grants under the Public Health Initiative programme, (PT06, Project 000138DT1). TR is supported by the Portuguese Foundation for Science and Technology (FCT) through a post-doctoral grant (SFRH/BPD/108126/2015)info:eu-repo/semantics/publishedVersio

CTen: a web-based platform for identifying enriched cell types from heterogeneous microarray data

Abstract Background Interpreting in vivo sampled microarray data is often complicated by changes in the cell population demographics. To put gene expression into its proper biological context, it is necessary to distinguish differential gene transcription from artificial gene expression induced by changes in the cellular demographics. Results CTen (cell type enrichment) is a web-based analytical tool which uses our highly expressed, cell specific (HECS) gene database to identify enriched cell types in heterogeneous microarray data. The web interface is designed for differential expression and gene clustering studies, and the enrichment results are presented as heatmaps or downloadable text files. Conclusions In this work, we use an independent, cell-specific gene expression data set to assess CTen's performance in accurately identifying the appropriate cell type and provide insight into the suggested level of enrichment to optimally minimize the number of false discoveries. We show that CTen, when applied to microarray data developed from infected lung tissue, can correctly identify the cell signatures of key lymphocytes in a highly heterogeneous environment and compare its performance to another popular bioinformatics tool. Furthermore, we discuss the strong implications cell type enrichment has in the design of effective microarray workflow strategies and show that, by combining CTen with gene expression clustering, we may be able to determine the relative changes in the number of key cell types. CTen is available at http://www.influenza-x.org/~jshoemaker/cten/</p

Correlation between different Scheimpflug-based lens densitometry analysis and effective phacoemulsification time in mild nuclear cataracts

To assess the correlations between preoperative Scheimpflug-based lens densitometry and effective phacoemulsification time (EPT) in age-related nuclear cataracts.Purpose To assess the correlations between preoperative Scheimpflug-based lens densitometry and effective phacoemulsification time (EPT) in age-related nuclear cataracts. Design Retrospective consecutive study. Methods The setting was the Ophthalmology Department, Hospital de Braga, Portugal. The study population included 50 eyes (42 patients) with age-related nuclear cataracts submitted to uneventful phacoemulsification surgery. Different analysis methods of Scheimpflug-based lens densitometry were performed: Pentacam Nucleus Staging (PNS) score with an ordinal scale from 0 to 5 and three-dimensional (3D), linear and region of interest (ROI) methods, which are displayed on an absolute scale (from 0 to 100%). EPT was calculated for the cataract surgery, which was performed by the same surgeon. Correlations between lens densitometry variables and EPT were determined using Pearson or Spearman correlation coefficients according to data normality. Results There were significant correlations between EPT and average density and maximum density variables derived from the 3D (r = 0.596, p < 0.001; r = 0.632, p < 0.001, respectively) and ROI (r = 0.527, p < 0.001; r = 0.575, p < 0.001, respectively) methods. The average density was the only parameter derived from the linear analysis that showed a significant correlation with EPT (r = 0.293, p = 0.039). The PNS score did not show a significant correlation with EPT (rho = 0.124, p = 0.390). Conclusion The densitometric parameters based on the 3D method showed the highest correlations with EPT. The referred lens densitometric analysis approach may be used in preoperative assessment in order to predict EPT more efficiently in age-related nuclear cataractsinfo:eu-repo/semantics/publishedVersio