Use of systems biology to decipher host–pathogen interaction networks and predict biomarkers

AbstractIn systems biology, researchers aim to understand complex biological systems as a whole, which is often achieved by mathematical modelling and the analyses of high-throughput data. In this review, we give an overview of medical applications of systems biology approaches with special focus on host–pathogen interactions. After introducing general ideas of systems biology, we focus on (1) the detection of putative biomarkers for improved diagnosis and support of therapeutic decisions, (2) network modelling for the identification of regulatory interactions between cellular molecules to reveal putative drug targets and (3) module discovery for the detection of phenotype-specific modules in molecular interaction networks. Biomarker detection applies supervised machine learning methods utilizing high-throughput data (e.g. single nucleotide polymorphism (SNP) detection, RNA-seq, proteomics) and clinical data. We demonstrate structural analysis of molecular networks, especially by identification of disease modules as a novel strategy, and discuss possible applications to host–pathogen interactions. Pioneering work was done to predict molecular host–pathogen interactions networks based on dual RNA-seq data. However, currently this network modelling is restricted to a small number of genes. With increasing number and quality of databases and data repositories, the prediction of large-scale networks will also be feasible that can used for multidimensional diagnosis and decision support for prevention and therapy of diseases. Finally, we outline further perspective issues such as support of personalized medicine with high-throughput data and generation of multiscale host–pathogen interaction models

Integrative analysis of the heat shock response in Aspergillus fumigatus

<p>Abstract</p> <p>Background</p> <p><it>Aspergillus fumigatus </it>is a thermotolerant human-pathogenic mold and the most common cause of invasive aspergillosis (IA) in immunocompromised patients. Its predominance is based on several factors most of which are still unknown. The thermotolerance of <it>A. fumigatus </it>is one of the traits which have been assigned to pathogenicity. It allows the fungus to grow at temperatures up to and above that of a fevered human host. To elucidate the mechanisms of heat resistance, we analyzed the change of the <it>A. fumigatus </it>proteome during a temperature shift from 30°C to 48°C by 2D-fluorescence difference gel electrophoresis (DIGE). To improve 2D gel image analysis results, protein spot quantitation was optimized by missing value imputation and normalization. Differentially regulated proteins were compared to previously published transcriptome data of <it>A. fumigatus</it>. The study was augmented by bioinformatical analysis of transcription factor binding sites (TFBSs) in the promoter region of genes whose corresponding proteins were differentially regulated upon heat shock.</p> <p>Results</p> <p>91 differentially regulated protein spots, representing 64 different proteins, were identified by mass spectrometry (MS). They showed a continuous up-, down- or an oscillating regulation. Many of the identified proteins were involved in protein folding (chaperones), oxidative stress response, signal transduction, transcription, translation, carbohydrate and nitrogen metabolism. A correlation between alteration of transcript levels and corresponding proteins was detected for half of the differentially regulated proteins. Interestingly, some previously undescribed putative targets for the heat shock regulator Hsf1 were identified. This provides evidence for Hsf1-dependent regulation of mannitol biosynthesis, translation, cytoskeletal dynamics and cell division in <it>A. fumigatus</it>. Furthermore, computational analysis of promoters revealed putative binding sites for an AP-2alpha-like transcription factor upstream of some heat shock induced genes. Until now, this factor has only been found in vertebrates.</p> <p>Conclusions</p> <p>Our newly established DIGE data analysis workflow yields improved data quality and is widely applicable for other DIGE datasets. Our findings suggest that the heat shock response in <it>A. fumigatus </it>differs from already well-studied yeasts and other filamentous fungi.</p

Automated Image Analysis of the Host-Pathogen Interaction between Phagocytes and Aspergillus fumigatus

Aspergillus fumigatus is a ubiquitous airborne fungus and opportunistic human pathogen. In immunocompromised hosts, the fungus can cause life-threatening diseases like invasive pulmonary aspergillosis. Since the incidence of fungal systemic infections drastically increased over the last years, it is a major goal to investigate the pathobiology of A. fumigatus and in particular the interactions of A. fumigatus conidia with immune cells. Many of these studies include the activity of immune effector cells, in particular of macrophages, when they are confronted with conidia of A. fumigus wild-type and mutant strains. Here, we report the development of an automated analysis of confocal laser scanning microscopy images from macrophages coincubated with different A. fumigatus strains. At present, microscopy images are often analysed manually, including cell counting and determination of interrelations between cells, which is very time consuming and error-prone. Automation of this process overcomes these disadvantages and standardises the analysis, which is a prerequisite for further systems biological studies including mathematical modeling of the infection process. For this purpose, the cells in our experimental setup were differentially stained and monitored by confocal laser scanning microscopy. To perform the image analysis in an automatic fashion, we developed a ruleset that is generally applicable to phagocytosis assays and in the present case was processed by the software Definiens Developer XD. As a result of a complete image analysis we obtained features such as size, shape, number of cells and cell-cell contacts. The analysis reported here, reveals that different mutants of A. fumigatus have a major influence on the ability of macrophages to adhere and to phagocytose the respective conidia. In particular, we observe that the phagocytosis ratio and the aggregation behaviour of pksP mutant compared to wild-type conidia are both significantly increased

P-West High Intensity Secondary Beam Area Design Report

This report gives the initial design parameters of a 1000 GeV High Intensity Superconducting Secondary Beam Laboratory to be situated in the Proton Area downstream of the existing Proton West experimental station. The area will provide Fermilab with a major capability for experimentation with pion and antiproton beams of intensities and of energies available at no other laboratory and with an electron beam with excellent spot size, intensity, and purity at energies far above that available at electron machines. Detailed beam design, area layouts, and cost estimates are presented, along with the design considerations

Comparison of the sensitivity of the UKCAT and A levels to sociodemographic characteristics: a national study

Background: The UK Clinical Aptitude Test (UKCAT) was introduced to facilitate widening participation in medical and dental education in the UK by providing universities with a continuous variable to aid selection; one that might be less sensitive to the sociodemographic background of candidates compared to traditional measures of educational attainment. Initial research suggested that males, candidates from more advantaged socioeconomic backgrounds and those who attended independent or grammar schools performed better on the test. The introduction of the A* grade at A level permits more detailed analysis of the relationship between UKCAT scores, secondary educational attainment and sociodemographic variables. Thus, our aim was to further assess whether the UKCAT is likely to add incremental value over A level (predicted or actual) attainment in the selection process. Methods: Data relating to UKCAT and A level performance from 8,180 candidates applying to medicine in 2009 who had complete information relating to six key sociodemographic variables were analysed. A series of regression analyses were conducted in order to evaluate the ability of sociodemographic status to predict performance on two outcome measures: A level ‘best of three’ tariff score; and the UKCAT scores. Results: In this sample A level attainment was independently and positively predicted by four sociodemographic variables (independent/grammar schooling, White ethnicity, age and professional social class background). These variables also independently and positively predicted UKCAT scores. There was a suggestion that UKCAT scores were less sensitive to educational background compared to A level attainment. In contrast to A level attainment, UKCAT score was independently and positively predicted by having English as a first language and male sex. Conclusions: Our findings are consistent with a previous report; most of the sociodemographic factors that predict A level attainment also predict UKCAT performance. However, compared to A levels, males and those speaking English as a first language perform better on UKCAT. Our findings suggest that UKCAT scores may be more influenced by sex and less sensitive to school type compared to A levels. These factors must be considered by institutions utilising the UKCAT as a component of the medical and dental school selection process

Regulatory network modelling of iron acquisition by a fungal pathogen in contact with epithelial cells

Peer reviewedPublisher PD

Comparative and functional genomics provide insights into the pathogenicity of dermatophytic fungi

ABSTRACT: BACKGROUND: Millions of humans and animals suffer from superficial infections caused by a group of highly specialized filamentous fungi, the dermatophytes, which exclusively infect keratinized host structures. To provide broad insights into the molecular basis of the pathogenicity-associated traits, we report the first genome sequences of two closely phylogenetically related dermatophytes, Arthroderma benhamiae and Trichophyton verrucosum, both of which induce highly inflammatory infections in humans. RESULTS: 97% of the 22.5 megabase genome sequences of A. benhamiae and T. verrucosum are unambiguously alignable and collinear. To unravel dermatophyte-specific virulence-associated traits, we compared sets of potentially pathogenicity-associated proteins, such as secreted proteases and enzymes involved in secondary metabolite production, with those of closely related onygenales (Coccidioides species) and the mould Aspergillus fumigatus. The comparisons revealed expansion of several gene families in dermatophytes and disclosed the peculiarities of the dermatophyte secondary metabolite gene sets. Secretion of proteases and other hydrolytic enzymes by A. benhamiae was proven experimentally by a global secretome analysis during keratin degradation. Molecular insights into the interaction of A. benhamiae with human keratinocytes were obtained for the first time by global transcriptome profiling. Given that A. benhamiae is able to undergo mating, a detailed comparison of the genomes further unraveled the genetic basis of sexual reproduction in this species. CONCLUSIONS: Our results enlighten the genetic basis of fundamental and putatively virulence-related traits of dermatophytes, advancing future research on these medically important pathogens

Integrative modeling of transcriptional regulation in response to antirheumatic therapy

<p>Abstract</p> <p>Background</p> <p>The investigation of gene regulatory networks is an important issue in molecular systems biology and significant progress has been made by combining different types of biological data. The purpose of this study was to characterize the transcriptional program induced by etanercept therapy in patients with rheumatoid arthritis (RA). Etanercept is known to reduce disease symptoms and progression in RA, but the underlying molecular mechanisms have not been fully elucidated.</p> <p>Results</p> <p>Using a DNA microarray dataset providing genome-wide expression profiles of 19 RA patients within the first week of therapy we identified significant transcriptional changes in 83 genes. Most of these genes are known to control the human body's immune response. A novel algorithm called TILAR was then applied to construct a linear network model of the genes' regulatory interactions. The inference method derives a model from the data based on the Least Angle Regression while incorporating DNA-binding site information. As a result we obtained a scale-free network that exhibits a self-regulating and highly parallel architecture, and reflects the pleiotropic immunological role of the therapeutic target TNF-alpha. Moreover, we could show that our integrative modeling strategy performs much better than algorithms using gene expression data alone.</p> <p>Conclusion</p> <p>We present TILAR, a method to deduce gene regulatory interactions from gene expression data by integrating information on transcription factor binding sites. The inferred network uncovers gene regulatory effects in response to etanercept and thus provides useful hypotheses about the drug's mechanisms of action.</p

Dynamic Assessment of Narrative Competence

In Developmental Education, language plays an essential role as a tool for communication (and thinking). Learning to produce coherent messages (“narratives”) with both cultural and personal value in the context of meaningful socio-cultural practices is considered as an important goal of Developmental Education. Narratives are essential for human action as they function as a tool for giving meaning to reality. Therefore, close observation and assessment of children’s narratives is essential in the context of Developmental Education. Over the past years we have developed a Dynamic Assessment (DA) instrument for assessing children’s narrative competence. This instrument combines two common approaches to DA, namely standardised interventionist DA and interactionist DA. With the help of this instrument, teachers are able to gain insight into children’s actual narrative competence as well as their developmental potential and their receptivity to certain forms of assistance to reach this potential. Our experience up to now shows that it is possible to assess children’s narrative competence in a valid and reliable manner